text:
The Tortellis (1987)
Episode List
Season 1
22 Jan. 1987Pilot
After dreaming that he's going to Hell for his blatant misdeeds, Nick Tortelli relocates to Las Vegas with his family to start a new life.
28 Jan. 1987An Affair to Remember
When Charlotte discovers she's being two-timed, she uses Nick to make her boyfriend jealous.
4 Feb. 1987Frankie Comes to Dinner
When Norm and Cliff (Cheers (1982) crossover guests) come to visit, Nick tries to impress them by saying Frank Sinatra is a close, personal friend.
11 Feb. 1987Svengali
When Loretta gets a job as the round girl at the local fights, Nick gets her a singing gig in hopes that she'll fire her manager.
18 Feb. 1987The Ad Game
Nick promises to eat a bug if he can't fix a TV in 24 hours, and a nasty neighbor will take him up on that promise.
25 Feb. 1987Viva Las Vegas
Nick begins managing an Elvis impersonator who dreams of becoming an opera singer.
18 Mar. 1987Coochie, Coochie
Nick goes to fix Charo's TV and winds up spending the night out, so Loretta concludes he slept with the Las Vegas headliner.
25 Mar. 1987Man of the Year
Nick offers a year of free TV repair service to raise money for charity, which results in him garnering a "Man of the Year" award.
1 Apr. 1987The Good Life
Nick masquerades as a wealthy businessman so his family can spend the night in a luxurious hotel.
21 Apr. 1987Father Knows Best
After witnessing Anthony ironing Annie's clothes, Nick decides his son isn't as masculine as he should be, so he decides to teach Anthony how to be a man.
28 Apr. 1987The Customer's Always Right
When a condescending customer stiffs him on a bill, Nick takes him to court.
5 May 1987Innocent as Charged
Anthony and Nick are in the doghouse when Loretta and Annie arrive to find them cavorting by the pool with two ladies.
12 May 1987His Girl Friday
Nick hires a beautiful secretary who quickly proves to be tyrannical.
Season 1


text:
2nd & 3rd Floors are now Social Zones. Group Study is allowed.
1st & 4th Floors are now Quiet Zones. These are the best places for concentrating.
Your library is here to help. Besides being a quiet place to study, we can find information for you. And we host events. Currently, we even have Student Life & Leadership Planners from the UC available. Come visit us.
As you get into the swing of things don't forget to visit your library…online or in person. We're here to help you succeed academically. Be sure to check out our new "Swoop Search" at the Library's homepage. Start here for the best scholarly resources. Better than Google, you'll find research articles, E-books, and regular books and many other resources. Check out all the other helpful things available to you, such as, the Library catalog, Research Guides, and "chat" help from the Librarians.
The University of Texas at Tyler 3900 University Blvd. Tyler, Texas 75799 800 UT TYLER • 903.566.7000 FAX: email@example.com
At The University of Texas at Tyler, we are creating solutions today for a better tomorrow. A culture of excellence provides a nurturing environment to prepare our students to be future problem solvers. We take great pride in a tradition of offering quality academic programs, expert faculty, fascinating student life and well-rounded service opportunities.
© UT Tyler, 2001 - PresentContact Webmaster

subset: commoncrawl


text:
A brilliant moment in sports history
The name of Roger Bannister is one of the most famous in the history of sports. In 1954, he became the first to accomplish what had been considered impossible: running the distance of a mile in less than four minutes.
The Four Minute Mile is the compelling story of Roger Bannister and his rivals, the runners who shared his dream and pursued it with unrelenting tenacity. It was a quest for athletic immortality that spanned eight years, three continents and captivated a post-war world avidly seeking new heroes.


text:
Which sex is the worst about washing up? Why is it so important? We've got the dirty truth on how and when to wash your hands.
Exercises After Mastectomy
Topic Overview
After breast surgery (mastectomy), you may feel some pain going down your arm. Your shoulder and arm may be stiff and hard to move. You may also have some loss of feeling there.
The basic exercises described here will help you start moving your arm. But be careful not to overdo it. For example, don't lift anything heavy with your arm until your doctor says it's okay.
Getting started with exercises
Don't start to exercise until your doctor says it's okay. If you are not sure how to do an exercise, don't start it until your doctor or physical therapist shows you exactly how to do it.
Stop exercising if your arm or chest area hurts or begins to swell. Talk with your doctor about your symptoms. Also call your doctor if you have problems doing an exercise or if it hurts.
Wear loose-fitting clothing while you do your exercises.
Use your arm for your usual activities, such as brushing your teeth and hair.
Special exercises that will help you get back your strength and flexibility include:
- Shoulder shrug.
- Shoulder roll.
- Shoulder blade stretch.
- Overhead reach.
- Shoulder pinch.
- Wall climb.
- Elbow circles.
See pictures of how to do these exercises .
When should you call for help?
Watch closely for changes in your health, and be sure to contact your doctor if:
- Your exercises cause pain or are hard to do.
- You have fluid buildup in your arm.
- You notice swelling anywhere in your arm, armpit, or chest area.
WebMD Medical Reference from Healthwise
Exercises After Mastectomy Topics
Hot Topics
- Rheumatoid Arthritis: How It Affects Your Joints
- Treatments for Moderate-to-Severe Psoriasis
- Birth Control Options
- Multiple Sclerosis: Symptoms to Look For
- Are You Fed Up With Overeating?
- How to Treat Atrial Fibrillation
- What's Killing Your Concentration? 12 Culprits
- 19 Habits That Wreck Your Teeth
- Celebrities With Diabetes
- Alzheimer's Disease: Early Warning Signs


text:
Looking for a Jasper motherboard for cheap. I don't care if its banned or if you screwed up a JTAG or RGH and lifted pads or ruined the board. Don't need cords, DVD, or power supply.
What I do care about is RRoD, I don't want anything that has been under a towel or sitting in your oven. I will require pictures of the four ram chips on board. If you don't have any current pictures or no way of getting a camera, then there will be no deal. The only transaction method I will use is PayPal and you must have a confirmed address.
Wtb Jasper Motherboard
Started by ShadowGuy , Feb 23 2012 01:46 PM
No replies to this topic
0 user(s) are reading this topic
0 members, 0 guests, 0 anonymous users


text:
Star Trek Beyond
The Star Wars-ification of Star Trek continues; better than the others, but still not good enough.
The Star Wars-ification of Star Trek continues; better than the others, but still not good enough.
It's almost as if the writers were simply using ideas left over from other Ice Age scripts that are about as fresh as the wind…
"The Ballad of Narayama" is a Japanese film of great beauty and elegant artifice, telling a story of startling cruelty. What a space it opens…
Patrice Leconte's "Monsieur Hire" is a tragedy about loneliness and erotomania, told about two solitary people who have nothing else in common. It involves a…
Ken Loach's "I, Daniel Blake" wins the Palme d'Or at the 69th Cannes Film Festival.
Barbara Scharres on the cats of Cannes 2016.
Wednesday, July 18, is the 20th anniversary of our marriage. How can I begin to tell you about Chaz? She fills my horizon, she is…
This movie is trying to kill these women, but they endure.
Writers at RogerEbert.com pick their favorite movies featuring star-crossed lovers.
Writers at RogerEbert.com pick their favorite movies featuring aliens and UFOs.
A report from Comic-Con 2016 on the world premiere of "Star Trek Beyond."
Politics of the new "Ghostbusters"; The Suskinds on "Life, Animated"; Restoring the "Chinatown" score; Bryan McMahan on "Knight of Cups"; Netflix could save "The Little…
When I saw the coming attractions trailer for "Under Siege," I had the feeling I'd already seen the movie: Terrorists land on the USS Missouri and occupy the great battleship. The crew is caught off guard and neutralized. But the bad guys overlook one man - the cook - who turns into a one-man army and fights back. The formula is obvious: "Die Hard Goes to Sea." I walked into the screening in a cynical frame of mind, but then a funny thing happened. The movie started working for me.
One reason for that is obvious: The overwhelming and convincing presence of the battleship itself. I learn, by reading the production notes, that director Andrew Davis and his team did not shoot on the real Missouri, but instead used the decomissioned USS Alabama. In many shots the ship appears to be at sea when it's actually docked in Mobile, Ala. They could have fooled me. This movie does a terrific job of making every scene play like a real event on a ship at sea, and that's part of its charm. There's even a walk-on by George Bush, visiting the ship before its fateful final voyage.
The cast is also effective. The star is Steven Seagal, who has cut off his pony tail to play a former Navy hero serving out his last tour as a cook. The reasons for that assignment are complicated (he got in trouble, but the skipper is his friend) but Seagal makes a convincing cook; he can hit a target with a carving knife at 20 paces, and he even looks like he's put on a few pounds on the job, sipping the boulibaisse.
The villains are superb, vile and deliriously insane.
They're played by Tommy Lee Jones, as a former undercover operative for the CIA, and Gary Busey, as a disillusioned officer on board the ship. Jones has developed into one of the most effective and interesting villains in the movies, maybe because he's not afraid to go over the top - as he does here, masquerading as a heavy-metal rocker and later spieling political slogans into the radio like a deranged dictator. Busey, as the turncoat officer, plays his big murder scene in drag, gnashing the scenery as if he's enjoying every bite.
The plot of the movie is, of course, absurd, involving a half-explained scheme to steal the ship's nuclear warheads, offload them to a stolen North Korean submarine, and sell them in the Middle East. Never mind. The details of the cat-and-mouse chase around the ship are exciting and well-directed. And director Davis is not above the put-on, as when he introduces Playboy's Miss July 1989 (Erika Eleniak) into the plot, and has her follow Seagal on his dangerous rounds for no better reason than because she seems utterly incongrous in every scene.
Andrew Davis is not a director whose name is known to many moviegoers, I suppose, but he has built up an impressive body of action work: His "Code of Silence" was the best Chuck Norris movie, his "The Package" was a terrific Gene Hackman thriller, and he directed Seagal's movie debut in "Above The Law" (1988). Here is uses some of his trademarks: Effective fight scenes, electronic gimmicks, quirky casting of the supporting roles, bigger-than-life heroes and villains.
This movie is trying to kill these women, but they endure.
A compilation of reviews defending the new "Ghostbusters" film.
A Blu-ray review of "Batman v Superman: Dawn of Justice (Ultimate Edition)," arriving July 19.
The new "Ghostbusters" film brings a battle between distorted nostalgia and the power of a child's imagination.


text:
The Norman Station Conservation Club will host its monthly Bluegrass Jamboree this weekend.
The event will take place 1 to 5 p.m. Sunday and will feature Norman Station, Hickory Wind, Lost River Risin' and The Sure Shot Turkey Dusters.
The jamboree is free, and the public is invited.
This story appears in the print edition of The Tribune. Subscribers can read the entire story online by signing in here or in our e-Edition by clicking here.
All content copyright ©2016 The Tribune, a publication of AIM Media Indiana unless otherwise noted.
All rights reserved. Click here to read our privacy policy.


text:
In the figure , consider the closed loop . This is a cyclic process in which the initial and final states are the same.
a. Find the total work done by the system in this process, and show that it is equal to the area enclosed by the loop.
b.How is the work done during the process in part A related to the work done if the loop is traversed in the opposite direction, ?
c. How much work is done in the cycle ?


text:
Castiel stare by MezameroWatch
©2012-2016 Mezamero
that wasn't easy
just for practice
Castiel from Supernatural
just for practice
Castiel from Supernatural
I really like your style as I could see how did you brush his face XD
job on this one!
job on this one!
Каас)) Ну зая просто, слов нет ^^
Hey I am meeting Misha Collins mid next year and am making him a fanbook! I want to collect as many submissions as possible to let Misha know just how much he means to his fans and am currently searching for some more fanart submissions. If you are interested in submitting your fantastic work for Misha to see then check out the Tumblr page for my book: [link] or follow me on twitter: @mishafanbook Don't worry, your work will be credited, you can attach a name, username or whatever you wish. Look forward to hearing from you! Kayla.
This is amazing. Love his eyes!
I love Castiel. This picture definitely captures the curiosity he has towards humans very well :3
Very beautiful.
'whats the matter? you dont think you deserve to be saved...'
my cass' favorite quote
my cass' favorite quote
Just... perfect!
Don't know what to say...
Jap, it IS perfect! ^^
Don't know what to say...
Jap, it IS perfect! ^^
OMFGR! I love it!
I love how you did this, especially his eyes!
You got his puppy-eyes perfect!!!
FAVE FAVE FAVE I DIE! Lol Beautiful, you really captured is deep ocean stare.
Haha d'aww he is so cute!
oh my god its cas! from supernatural
awesome, just epic
wonderful eyes !!! i love your work, is amazing. very very "Castiel" xD
Pretty eyes.... must kidnap castiel!!!!!! hehe your awsome by the way *bows with deep respect for master of beauty
His eyes!
Dat face D: You captured his expression very well. And marvelous job of the eyes.
classic cas head tilt!
Wow! This is fantastic! You captured his "what-is-Dean-talking-about?" expression perfectly!
god looks soo realistic!!!!
I LOVE THIS SO MUCH!!!! You're amazing
his eyes.....so prettiful! lol....Amazing work on this though, You've really captured Castiel in this picture and i'm very impressed
thats pretty awesome
thats pretty awesome
I love this!!
О боже *__* Кастиэль *___*
...а как насчёт нарисовать Кастиэля и Дина вместе?.. *троллфейс.джпг
...а как насчёт нарисовать Кастиэля и Дина вместе?.. *троллфейс.джпг
Hahaha, his expression is charming and sweet and perfectly curious! Lovely work!!
I'm shocked! .... He is just as real! I would like to see the portraits of the)))
Uwaaah! I love Cas.... Love him so much.
~Dramatic sniffle~
~Dramatic sniffle~
I love that look.
Classic head tilt! Beautifully captured
Nice work. How's things going?
How can he be creepy and absolutely adorable at the same time?! My brain!!
OMG I love Castiel! AND I love your artwork! I'm so happy right now <3
This is amazing.
this is so beautiful
You really captured his expression here! Amazing work XD
Oh...My...Cas...he just looks so innocent and adorable and questioning. This head tilt is pure Castiel. Beautifully done!


text:
Women's Pictures - Vote For Your Favorite Female Filmmakers!
Hello, it's Anne Marie. Since the first month of "Women's Pictures" went so well (and because I have an extra week in February to fill), today I would like to hear from all of you charming readers and commenters. When I first asked for suggestions of female filmmakers on which to focus this series, you all chimed in with over 50 directors from 8 countries and 9 decades in movie history. We can't write about all of them (yet), so I've narrowed the list down to 10 Female Filmmakers. Please know that this is not meant as a list of the best 10 female directors. When winnowing down the original suggestions, I took into consideration size of filmography, ease of access to their films, and reader interest. The goal is to find 10 women within those restrictions who represent a variety of genre, vision, nationality, sexuality, and focus. And these 10 women are pretty incredible.
Vote for as many as you like and tell us why in the comments
In alphabetical order, our ladies are...
Dorothy Arzner - Years active: 1927-1943. Arzner is best known as the "only female director during Hollywood's Golden Age" (more on that at the end of this post). Arzner was a lesbian proto-feminist credited with (among other things) inventing the boom mic, looking dapper in menswear, and dressing Katharine Hepburn in that bizarre Moth Gown. Best known films: The Wild Party, The Bride Wore Red, Christopher Strong.
Kathryn Bigelow - Years active: 1981-present. I mean, we all know who Kathryn Bigelow is, right? She's the only female director to win an Academy Award so far! (For The Hurt Locker in 2010.) Divorced James Cameron in 1991 and beat him for Best Director two decades later. Makes action films, war films, and defies silly questions about what kinds of movies women "usually make." Best known films: The Hurt Locker, Point Break, Zero Dark Thirty
Jane Campion - Years active: 1982-present. For her film The Piano, native Kiwi Jane Campion was the first female director to win the Palm D'Or at Cannes, and became the second woman in the history of the Academy Awards to be nominated for Best Director. Most recently, she returned to the scene of her earlier triumph to be the head judge for the 2014 Cannes Film Festival. Best known films: The Piano, Bright Star, Sweetie
Sofia Coppola - Years active: 1999-present. Another fruit that fell from the ever-blossoming Coppola family tree. In 2004, Sofia Coppola became the third woman in Oscars history to be nominated for Best Director for her film Lost In Translation. Since then, she's taken on everything from historical fiction to memoir to true crime, all with a distinct pop art sensibility. Best known films: The Virgin Suicides, Lost in Translation, Marie Antoinette.
Mira Nair - Years active: 1979-present. Indian director Mira Nair has had a globe-trotting career over the past few decades. She's made documentaries, big budget Indian movies, indie films set in the American South, period pieces, shorts and more. About the most consistent thing you can say about Nair's career is that she's consistently refused to be tied to just one genre. Best known films: Monsoon Wedding, Vanity Fair, Salaam Bombay!
Miwa Nishikawa - Years active: 2003-present. Miwa Nishikawa is the newest addition to this list, having only 7 films and a little over a decade of experience so far. However, while her movies haven't travelled much outside of Japan yet, she is already heralded as a strong new voice in Japanese film. (Thank you, reader BRB for the suggestion!) Best known films: Dreams for Sale, Dear Doctor, Wild Strawberries.
Leni Riefenstahl - Years active: 1932-1958, 2002. Best known for her Nazi propadanda film, The Triumph of the Will. It was supposedly so well-made that when the US government requested that Hollywood re-edit the movie to show Germany negatively, they were told it couldn't be done. She pushed forward documentary film & experimented with genre. Best known films (besides that one): Olympia, Lowlands, Underwater Impressions.
Julie Taymor - Years active: 1999-present. This MacArthur Genius Grant recipient is a theater director-turned film director-turned theater director who turned off the dark (and the safety precautions) for Spiderman on Broadway. Before that, she turned lions into puppets for Disney's The Lion King. Her films are visually vibrant, beautiful, and totally bonkers. Best known films: Frida, Across The Universe, Titus.
Agnes Varda - Years active: 1955-2011. The only female member of the talented boys club that was the French New Wave. Varda was an artist before making her way to film, a journey for which she attributes her unique perspective. She's still alive and kicking (and occasionally at film festivals), but seems to be enjoying resting on her well-deserved laurels now. Best known films: Cleo from 5 to 7, Vagabond, The Beaches of Agnes.
Lina Wertmuller - Years active 1965-2009. This Italian director was the first woman ever nominated for Best Director, when the Academy nominated her in 1975 for her film Seven Beauties. One of her films also holds the record for longest title (it was shortened to Blood Feud). A highly vocal political activist, many of her characters reflect her more extreme stances. Best known films: Seven Beauties, The Seduction of Mimi, Swept Away.
Who do you vote for? (You may vote for more than one.)
Coming in March: IDA LUPINO
The noir-actress-turned-writer/producer originally became a director out of necessity, but quickly made a name for herself by writing the kinds of films that the big studios wouldn't touch. Using her buddy Howard Hughes's money and support, Lupino started a production company, and a directing career that lasted two decades. Follow along as we watch a blonde bombshell turn herself into a behind-the-scenes bigshot.
March Schedule:
3/5 - Never Fear (1949) - Ida's first directing credit about a dancer who contracts polio. (Available on Amazon Prime)
3/12 - The Hitch-Hiker (1953) - A foray into film noir with a hitch-hiker holding two men hostage. (Available on Amazon Prime)
3/19 - The Bigamist (1953) - Ida Lupino and Joan Fontaine are married to the same man. (Available on Amazon Prime)
3/26 - The Trouble With Angels (1966) - Lupino's last feature film involves Rosalind Russell, Hayley Mills, and nuns. (Available on Amazon Prime)


text:
For questions concerning various types of tremolo systems (also "vibrato" or "whammy bars") typically seen on electric guitars and similar instruments.
31 views
Using a tremolo stompbox between the swell pedal and the synth?
I'm quite new to the practical aspects of synthesizers and fx modules (I only just got my first synth a few months ago). As is typical these days, my synth has a variety of onboard effects, but it ...


text:
The Week of May 23
Posted by Jay McGaughy on 23rd May 2016
Monday, May 23
Bell Ringer: None!
In Class: Students completed The Later Middle Ages test.
Students turned in textbooks.
Assignment: None!
Tuesday, May 24
Bell Ringer: None!
In Class: Any student needing to complete Visitor from the Past make-up today had that opportunity.
Students received their test scores and fourth quarter averages.
We signed yearbooks in class.
Assignment: None!
Wednesday, May 25
Bell Ringer: None!
In Class: 8th Grade Breakfast, Awards Day, Field Day!
Assignment: None!
Thursday, May 26
Bell Ringer: None!
In Class: Assemblies today!
Assignment: I wish you all the best in high school!
Friday, May 27
Bell Ringer: Have a wonderful summer!
In Class: Have a wonderful summer!
Assignment: Have a wonderful summer!
Posted in Assignments, Bell Ringer, In Class, World History | No Comments »


text:
House Speaker John Boehner cast his ballot early Tuesday in his hometown at Voice of America MetroPark in West Chester Township.
Boehner faces a three-way challenge in the GOP primary for Ohio's 8th District from J.D. Winteregg, a tea party favorite from Troy, and Eric Gurr of Liberty Township.
Candidate Matthew Ashworth of Liberty Township withdrew from the race last week but his name will still appear on the ballot.


text:
Despite intense interest and considerable effort via high-throughput screening, there are few examples of small molecules that directly inhibit protein-protein interactions. This suggests that many protein interaction surfaces may not be intrinsically "druggable" by small molecules, and elevates in importance the few successful examples as model systems for improving our fundamental understanding of druggability. Here we describe an approach for exploring protein fluctuations enriched in conformations containing surface pockets suitable for small molecule binding. Starting from a set of seven unbound protein structures, we find that the presence of low-energy pocket-containing conformations is indeed a signature of druggable protein interaction sites and that analogous surface pockets are not formed elsewhere on the protein. We further find that ensembles of conformations generated with this biased approach structurally resemble known inhibitor-bound structures more closely than equivalent ensembles of unbiased conformations. Collectively these results suggest that "druggability" is a property encoded on a protein surface through its propensity to form pockets, and inspire a model in which the crude features of the predisposed pocket(s) restrict the range of complementary ligands; additional smaller conformational changes then respond to details of a particular ligand. We anticipate that the insights described here will prove useful in selecting protein targets for therapeutic intervention.
Author Summary
Identifying small-molecule inhibitors of protein interactions has traditionally presented a challenge for modern screening methods, despite interest stemming from the fact that such interactions comprise the underlying mechanisms for cell proliferation, differentiation, and survival. This suggests that many protein interaction surfaces may not be intrinsically "druggable" by small molecules, and elevates in importance the few successful examples as model systems for improving our understanding of factors contributing to druggability. Here we describe a new approach for exploring protein fluctuations leading to surface pockets suitable for small molecule binding. We find that the presence of such pockets is indeed a signature of druggable protein interaction sites, suggesting that "druggability" is a property encoded on a protein surface through its propensity to form pockets. We anticipate that the insights described here will prove useful in selecting protein targets for therapeutic intervention.
Citation: Johnson DK, Karanicolas J (2013) Druggable Protein Interaction Sites Are More Predisposed to Surface Pocket Formation than the Rest of the Protein Surface. PLoS Comput Biol 9(3): e1002951. doi:10.1371/journal.pcbi.1002951
Editor: James M. Briggs, University of Houston, United States of America
Received: August 7, 2012; Accepted: January 11, 2013; Published: March 7, 2013
Copyright: © 2013 Johnson, Karanicolas. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by grants from the National Center for Research Resources (5P30RR030926) and the National Institute of General Medical Sciences (1R01GM099959 and 8P30GM103495) of the National Institutes of Health, and the Alfred P. Sloan Fellowship (JK). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Manipulating the interactions between proteins represents a promising avenue for therapeutic intervention in a variety of settings. Given the ubiquitous nature of protein interactions, selectively manipulating such interactions could serve as a means to treat conditions including viral and bacterial infections, cancer, and autoimmune disorders [1]–[7]. In spite of recent ongoing efforts that have provided cause for optimism, protein interactions continue to be viewed as a challenging class of therapeutic target [8]–[12]. While high-throughput screening efforts that fail to yield extensive hits are typically not reported in the literature, hit rates as low as 0.01% in a large pharmaceutical library have been described [13].
This dearth of successful representatives to study has given increased importance to the several cases in which a protein structure has been solved in complex with a biological protein partner and also in complex with a small molecule inhibitor. Wells and McClendon [8] compared six such cases and observed that binding was not associated with a large conformational change in any of these examples; and yet, the concave pocket on the protein surface at which the small molecule binds was typically smaller or not present in the unbound protein structure. In order for inhibitor binding to occur, the surface of the unbound structure therefore had to undergo local rearrangement to reveal a small molecule binding site that would not necessarily be evident from the unbound structure [8].
Given the limited success in identifying modulators of protein-protein interactions, it has proven helpful at an early stage to validate a protein surface site by evaluating its "druggability". As such, fragment-based methods have been developed to experimentally assess the druggability of a protein interaction site by determining which members of a small molecule probe set bind to a target protein, and where on the protein surface these bind. This experiment can be conducted using "SAR by NMR" [14], which tracks chemical shift differences to identify binding sites on the protein surface, or by the "multiple solvent crystal structures" method [15], in which independent structures of the target protein are solved after soaking with a collection of organic solvents. Both of these approaches aim to probe the regions of a protein surface that can accommodate small-molecule binding, with a preference for sites that are not uniquely disposed to bind a particular pre-selected ligand. In either technique, specific regions of the protein surface that interact with a variety of probe molecules – albeit weakly – are inferred to be a putative site for more potent binding by some yet unidentified compound.
Inspired by these methods, we hypothesize that the ability to form a binding pocket may be the limiting factor for druggability of a protein surface site. We further propose that compounds identified in biochemical screens as inhibitors of protein interactions result from natural shape complementarity to specific surface pockets that form with little energetic cost to the protein. Together these hypotheses imply that druggable sites differ from the rest of the protein surface, in that fluctuations under physiological conditions at druggable sites include a special subset of "pocket-containing" conformations.
To test these hypotheses, we have developed computational methodology to explore protein fluctuations in a biased way, by providing a driving force towards conformations in which a surface pocket is present. Several other studies have generated ensembles of protein conformations reflecting fluctuations around the native state and used these either to assess druggability [16] or as a starting point for docking studies [17]–[24]. Because these ensembles are generated in an unbiased manner, however, a large fraction of the resulting ensembles correspond to protein conformations that are dissimilar to the corresponding bound structure in both pocket size and hydrophobicity [18]. One of these studies found that carrying out simulations in methanol led to formation of surface pockets which could accommodate small molecules [25], but the use of this non-biological solvent may lead to unphysical artifacts in the resulting models. Molecular dynamics has also been used in a computational analog of "SAR by NMR" in which simulations are carried out using an explicit mixed solvent, allowing druggable sites to be identified by locating accumulation of probe molecules [17], [20], [26]. Though these methods proved effective for binding sites, the unbiased nature of the underlying simulations make these approaches very computationally intensive. Recently Kozakov et al. have developed a computational analog of the multiple solvent crystal structures method, by using docking to identify "consensus" sites at which several probe molecules cluster [27]. They confirmed that these molecular probes indeed cluster at established druggable sites and that known inhibitors often occupy these consensus sites. Such an approach, however, cannot efficiently explore surface pockets that form via concerted motions involving the protein backbone due to the computational expense associated with repeatedly docking multiple small molecule probes. The biasing potential we describe here avoids this limitation by not needing to dock probe molecules, and therefore can be used in the course of a simulation that samples a broader range of conformational fluctuations.
Quantitative analysis of surface pockets
Because a wide, shallow pocket that is unsuitable for small molecule binding can have the same volume as a deep pocket that is more suitable for small molecule binding, we introduce the concept of "deep" volume of a pocket: the volume of the pocket that is well-sequestered away from solvent. To quantitatively identify small molecule binding pockets and measure their "deep" volume, we implemented a modified version of the LIGSITEcs algorithm [28]. This approach starts by creating a grid around a protein and marking each grid point as occupied by protein, surface, or solvent. Next, the algorithm performs linear searches on the grid to find "Surface-Solvent-Surface" events: lines drawn between two surface points that pass through only solvent (Figure S1), indicating a concave region on the protein surface. To distinguish between total pocket volume and deep volume, pocket points that fall within 2.5 Å of solvent are marked as "surface pocket" points and are excluded from the "deep volume" calculation. Finally, the remaining contiguous points involved in these events are clustered into "deep pockets". As expected, the deep pocket volumes we use here are correlated to, but smaller than, pocket volumes found by other pocket detection methods, such as Q-SiteFinder [19] (Figure S2). Our implementation differs from the original LIGSITEcs algorithm [28] in that our search is restricted to the region around a specific "target" residue on the protein surface, allowing us to rapidly test for pockets at a specific surface site. Additional minor differences are described in Text S1.
A demonstration of this method is shown in Figure 1A. Bcl-XL is an anti-apoptotic protein in the Bcl-2 family whose over-expression has been implicated in the survival of cancer cells. A series of acyl-sulfonamide-based ligands have been shown to inhibit Bcl-XL activity by competing for its peptide-binding groove. Here, we have removed one such inhibitor from a co-crystal structure and applied our modified implementation of the LIGSITEcs algorithm at this surface site. The resulting pocket has intuitive shape complementarity to the ligand even though it was generated from the protein structure without the ligand present. This is unsurprising, given that the ligand occupying this pocket is complementary in shape to the protein surface.
(A) Bcl-XL (grey surface) is shown in complex with an inhibitor (blue sticks). The protein surface features a large pocket (red spheres) complementary in shape to the inhibitor. (B) Deep pocket volumes of surface pockets at protein interaction sites harboring a bound inhibitor (red line) are larger than those found elsewhere on the protein surface (black line). Data are collected from a test set of seven proteins, each of which has been solved in complex with a small-molecule inhibitor (Bcl-XL, IL-2, FKBP12, HPV E2, ZipA, MDM2, and the BIR3 domain of XIAP).
We compiled a test set of all seven proteins for which structures have been solved both alone and in complex with a small-molecule inhibitor bound to a protein interaction site (Bcl-XL, IL-2, FKBP12, HPV E2, ZipA, MDM2, and the BIR3 domain of XIAP) (Table 1). We compared the deep pocket volume at randomly selected regions of the protein surface (see Text S1) to the deep volume of the inhibitor-bound pocket. Since the pocket definition can depend somewhat on the particular "target" residue used, the deep volume of the inhibitor-bound pocket was measured several times using different target residues. As shown in Figure 1B, across all seven proteins, most pockets identified by this algorithm at randomly selected sites (black line) on the protein surface have a deep volume smaller than 25 Å3, and all are smaller than 75 Å3. In contrast, the distribution of inhibitor-bound pocket volumes (red line) is significantly shifted, with about half of the inhibitor-bound deep pocket volumes larger than 75 Å3. This observation is consistent with results generated using other pocket detection methods [29]–[33], although those other studies were not focused on inhibitors of protein-protein interactions.
Druggability of protein surface sites
The results presented above demonstrate that inhibitor binding occurs at surface sites containing a pocket, and that these sites are distinct from the remainder of the protein surface. We therefore formulated the hypothesis that the ability of the protein surface to form such pockets may be the limiting determinant of the inherent druggability at this site.
Unlike previous standalone methods for pocket detection, we instead implemented our algorithm as a term in the Rosetta [34] energy function alongside the canonical energetic determinants of protein structure such as packing, hydrogen bonding, and solvation (see Methods section). By including this biasing term in the energy function, we may use any of the standard functionalities provided in Rosetta; inclusion of this term, meanwhile, will lead to simultaneous optimization of both "pocket score" and the traditional energy terms. In essence, the contribution from the "pocket" term serves as a proxy for the energy associated with binding of some (unspecified) small molecule partner.
To test the hypothesis that pocket formation may be the limiting determinant of druggability, we performed biased and unbiased simulations on the unbound conformations of Bcl-XL, targeting residues at the protein interaction site as well as at equivalent randomly selected residues elsewhere on the protein surface. Surface sites included in the random set were matched to those at the protein interaction site on the basis of their secondary structure, and further that a contacting pocket of equivalent size to that of the protein interaction site (evaluated by Q-SiteFinder [19]) was present in the unbound conformation (see Text S1 and Figure S3); further, the random sites were each at least 12 Å from one another. Both backbone and sidechain degrees of freedom were allowed to move during simulations (see Methods section). The deep pocket volumes from each of 1,000 conformations generated via each method are shown as cumulative histograms in Figure 2A. Pockets at the protein interaction site (solid red lines) form more often and are significantly larger than those formed elsewhere on the protein surface (dashed black lines). The largest pockets in the biased simulations are sampled with much higher frequency than in the corresponding unbiased simulations (Figure 2A), demonstrating that the biasing potential drives sampling towards these conformations. These observations further hold for each of the other six additional proteins comprising our test set (Figures 2B–G), and also after inclusion of additional random sites (Figure S4) or starting from the protein-bound conformation (Figure S5).
Volumes of surface pockets are shown from conformations generated with no biasing potential (left) and upon inclusion of a "pocket opening" biasing potential (right) for each of the seven proteins that comprise our test set. Surface pockets occur at druggable protein interaction sites (solid red lines) more frequently than elsewhere on the protein surface (dashed black lines). (A) Bcl-XL. (B) IL-2. (C) FKBP12. (D) HPV E2. (E) ZipA. (F) MDM2. (G) BIR3 domain of XIAP.
To examine the physiological relevance of the conformations generated in biased simulations, we compared their energies to those obtained in equivalent unbiased simulations. For Bcl-XL, we used Rosetta to evaluate the (unbiased) energy for each of 1000 conformations generated from an unbiased simulation, a simulation with the biasing term applied to either the protein interaction site or a random surface residue, and equivalent simulations in which the weight of the biasing term was increased tenfold. In all cases we evaluated energies without contribution from the biasing term; a histogram of these energies is shown in Figure 3A. Conformations from the unbiased simulation (green solid line) have a very similar distribution of energies as conformations from a simulation in which the biasing potential was applied to a randomly selected target residue (black dashed line); this is unsurprising given that few of these conformations contain pockets, implying that a similar ensemble of conformations are sampled. Applying a stronger weight to the biasing potential using the same randomly selected target residue (solid black line) leads to conformations that are far less energetically favorable, indicating that pocket opening to satisfy the biasing potential could not be achieved without extensive energetic cost to the protein. In contrast, applying the biasing potential to a residue at the protein interaction site led to conformations that were only slightly higher in energy (and with overlapping distributions) than those conformations sampled in the unbiased simulation, for either weight of the biasing potential (red lines). A scatterplot showing the deep pocket volume for each of these conformations highlights the fact that conformations containing large pockets are sampled with the moderate biasing potential only if it is applied at the protein interaction site (Figure 3B, cyan vs. red points). Application of the stronger biasing potential to random (carefully matched) surface sites leads to generations of low-energy conformations without large pockets, and also pocket-containing conformations with much higher energy (Figure 3B, blue points).
(A) Conformations generated without the use of a biasing potential (solid green line) show a similar distribution of energies to those generated with the biasing potential at a randomly selected target residue (dashed black line); increasing the strength of the biasing potential here leads to conformations with higher energies (solid black line). In contrast, application of the biasing potential at the protein interaction site (red lines) leads to conformations with a distribution of energies that strongly overlaps with those energies of conformations sampled in the unbiased simulations, suggesting that these conformations represent low-energy states accessible to the unbound protein. (B) A scatterplot showing the deep pocket volume for conformations generated with the biasing potential applied to one of the random sites (moderate bias in cyan, strong bias in blue) or to the protein interaction site (moderate bias in red, strong bias in orange). Low-energy conformations containing large pockets are sampled only if the biasing potential it is applied at the protein interaction site; while large pockets are sampled using the strong bias at random sites, these conformations have considerably higher energy. All energies shown here were evaluated in the absence of the biasing potential, for fair comparison.
The same observations also hold for each of the other six proteins comprising our test set (Figure S6, Table 1). Collectively, these results demonstrate that pocket opening at the druggable site can occur with little energetic cost to the protein, while pocket opening elsewhere on the protein surface requires that the protein adopt a highly unfavorable conformation.
It is notable that in each of these seven examples surface pockets were identified at the protein interaction site. It is equally notable, however, that similar surface pockets were not observed elsewhere on the protein surface (Figure 2). This comparison highlights the qualitative difference between the protein interaction site – already demonstrated to be druggable in a practical sense for each of these examples – and the remainder of the protein surface, at which high-affinity interactions with small molecules have not been observed.
Pocket shapes are encoded on the protein surface
The results presented above demonstrate that there is a natural predisposition towards pocket formation in certain druggable regions on the protein surface. We next asked whether these preferred pocket-containing conformations dictate the range of potential small-molecule inhibitors suitable for binding at this site. Should this be the case, protein conformations generated using a biasing potential to induce pocket formation should resemble inhibitor-bound conformations more than conformations generated using an equivalent unbiased protocol.
Turning first to Bcl-XL, we aligned the lowest-energy conformation produced from the biased simulations described earlier (which were started from the unbound protein structure) to both unbound and inhibitor-bound crystal structures (Figure 4A). Direct superposition of the inhibitor from the bound structure onto the unbound crystal structure reveals extensive steric clashes (Figure 4B), highlighting the local protein conformational changes that must take place in order for inhibitor binding to occur. Remarkably, examination of the conformation from the biased simulation shows that part of the protein surface has adopted a shape highly complementary to the inhibitor (Figure 4C, right side) – even though no information about the identity of the inhibitor was included in the simulation that produced this conformation. Further, this conformational change occurred without direct involvement of the "target" residue at which the biasing term was applied.
. An unbound crystal structure (pink), an inhibitor-bound crystal structure (green, with inhibitor shown in sticks), and a low-energy conformation generated from the unbound crystal structure using the biasing potential (cyan, with target residue in red) are shown. (A) The overall protein architecture is preserved amongst all three; movement of the helix in the foreground upon binding is not recapitulated in the pocket-opened conformation. (B–D) The pocket revealed in this low-energy conformation nonetheless strongly resembles the surface pocket in the bound crystal structure, and even bears shape-complementarity to the inhibitor. The identity of the inhibitor was not used in generating this conformation, but was added retrospectively for visual comparison.
On the other hand, the conformation from the biased simulation did not recapitulate the bound conformation exactly: the latter contains an extension to the surface pocket (left side in the orientation shown) to accommodate the "tail" of the inhibitor (Figure 4D). Comparison of the protein backbone in all three structures (Figure 4A) reveals the protein structural reorganization required to accommodate this "tail": the helix below the inhibitor (Figure 4A, foreground) unwinds on the left side, and tightens on the right side (in the orientation shown). Because the deep pocket volume is larger in the inhibitor-bound crystal structure than in the conformation from the biased simulation, we anticipate that sampling in these simulations was insufficient to fully recapitulate this highly concerted conformational change.
The diversity of conformational changes associated with inhibitor binding in different proteins is highlighted in Figure S7. In IL-2, slight rearrangement of a helix (at top of the orientation shown) allows a sidechain rotamer change that both reveals the binding pocket and creates new interactions with inhibitor shown (Figure S7A). In contrast FKBP12, HPV E2 and ZipA each contain a pre-formed pocket on the unbound protein surface that strongly complements the inhibitor, indicating that inhibitor binding occurs primarily via a "lock-and-key" mechanism in these cases (Figure S7B–D). Expansion of the ZipA pocket observed in the biased simulations (Figure 2E) resulted from sidechain rearrangement on the surface to the left side of the binding site (in the orientation shown), without disrupting the pre-ordered portions of the binding site. Nutlin binding to MDM2, on the other hand, requires splaying apart of two surface helices to create the binding pocket: this conformational change is dramatically recapitulated in the lowest-energy individual conformation from the biased simulations (Figure S7E). Finally, unlike these previous examples showing modest conformational changes, binding of a Smac-mimetic to the BIR3 domain of XIAP is associated with extensive rearrangement of long surface loops (Figure S7F).
To assess whether the protein conformations generated using the biasing potential resemble inhibitor-bound conformations more closely than conformations generated using an equivalent unbiased protocol, we quantitatively compared the ensembles of conformations produced by each method. We note that neither method uses any knowledge of any particular inhibitor when generating an ensemble of conformations. Therefore, rather than report the protein RMSD in reference to one pre-selected bound conformation we instead individually computed the interface RMSD (iRMSD) relative to every available inhibitor-bound crystal structure (see Text S1), and took the lowest of this set of iRMSD values to reflect the suitability of this conformation for binding some (known) unspecified inhibitor.
For each of the seven proteins in our test set described earlier, we show the iRMSD for each member of the biased and unbiased ensembles to its closest inhibitor-bound crystal structure (Figure 5). We note that the iRMSD values of conformations sampled vary across these seven different proteins; this stems from the fact discussed earlier that in some cases the unbound starting structure strongly resembles the inhibitor-bound structure (FKBP12, HPV E2, ZipA), while in other cases a more extensive conformational change accompanies binding (MDM2, XIAP) (Figure S7). For reference, we also indicate the iRMSD of the unbound starting structure relative to the closest and most distant inhibitor-bound structures (Figure 5, dashed brown lines) and the protein-bound structure relative to the closest and most distal inhibitor-bound structures (Figure 5, dashed green lines).
Distributions of RMSD over interface atoms (iRMSD) to the closest inhibitor-bound crystal structure for conformations generated with (red lines) or without (black lines) the biasing potential. The iRMSDs from the unbound structure to the most and least similar inhibitor-bound crystal structures are also indicated (dashed brown vertical lines). For all seven proteins comprising the test set, the biased simulations produced conformations closer to an inhibitor-bound crystal structure than the unbiased simulations.
Though there is overlap between the resulting distributions, for every one of the seven proteins we examined the conformations sampled in the biased simulations are closer to an inhibitor-bound conformation than the conformations sampled in the corresponding unbiased simulations. This observation applies not just to the iRMSD of atoms directly involved in binding (Figure 5), but to the backbone atoms of the corresponding residues as well (Figure S8). Further, in five of the seven cases (Bcl-XL, IL-2, FKBP12, ZipA, and XIAP) the conformations generated from the biased simulations are closer than the starting unbound conformation to an inhibitor-bound structure (Figure 5). Conformations sampled in simulations of HPV E2 and MDM2 that moved further than the unbound conformation from the inhibitor-bound structures may be due to slight inaccuracies in the Rosetta energy function, or alternatively may be sampling novel truly "druggable" conformations for which complementary inhibitors have not yet been identified.
To further characterize the pockets generated using the biasing potential, we evaluated the percentage of solvent accessible surface area that is hydrophobic (hSASA) for each pocket (Figure S9). While the hydrophobicity of the inhibitor-bound pockets vary amongst the different protein test cases, in each case the pockets generated using the biasing potential exhibit similar hydrophobicity to the corresponding inhibitor-bound conformation. Like the shape of these pockets, then, their hydrophobicity appears to be an intrinsic property resulting from details of the surface geometry and composition.
Collectively these results demonstrate that biasing simulations towards conformations in which a surface pocket is present drives the resulting ensemble towards the conformations observed in inhibitor-bound crystal structures. Because no information about the identity of any particular inhibitory compound was included in the biasing potential, this suggests that the general shape (and hydrophobicity) of surface pockets available to a potential inhibitor is an inherent property of the druggable interface itself.
Druggability of survivin
The examples comprising our test set in the studies above were selected on the basis of a known compound directly inhibiting a protein interaction. For each of these cases, then, the druggable site is coincident with the protein functional site. We next turned to survivin, an example of a protein in which the two sites are non-overlapping.
Survivin is among the most strongly tumor-specific proteins known [35], is a notable signature of unfavorable disease outcome [36], and has been well-validated as a therapeutic target using an antisense oligonucleotide [37] and a transcriptional repressor [38], [39]. Despite this intense interest, however, no direct inhibitors of survivin function have been identified. Survivin carries dual functions which together explain its important role in cancer: it serves as an inhibitor of apoptosis and is also required for cell division [40]. The anti-apoptotic activity of survivin derives from binding the Smac/DIABLO peptide via a BIR domain. While small-molecule inhibitors of other Smac-binding BIR domains have been identified [41]–[44] (we included the XIAP BIR domain in the test set described in previous sections), efforts in this vein using survivin have not yet proven fruitful [40], [45]. Consistent with a hypothesis that the peptide-binding surface of survivin may be intrinsically undruggable, an SAR by NMR approach used by Hajduk et al. found only a single probe that interacted with this site (of 9,370 probes tested) – a full order of magnitude fewer than the number of interacting probes found using proteins for which potent inhibitors have been identified [14]. Intriguingly, this study revealed a separate distal site (Figure 6A) at which 33 probe compounds bound, well within the frequency observed for druggable sites on other proteins but not useful as a starting point for modulating survivin function.
(A) The crystal structure of survivin, showing the protein interaction site (red) and the distal druggable site identified by NMR (blue) [14]. (B) Volumes of surface pockets are compared for conformations generated with the biasing potential applied at random surface residues (dashed black lines), applied at the protein interaction site (dashed red lines), and applied at the distal druggable site (solid blue lines). Pockets emerge at the druggable site but not elsewhere on the protein surface.
We carried out a series of biased simulations as described earlier, using the unbound crystal structure of survivin as a starting point. In agreement with results from SAR by NMR [14], we find that pockets at the "undruggable" peptide-binding site of the BIR domain do not form with any higher propensity than at randomly selected equivalent surface sites (Figure 6B). This result is particularly notable as it stands in contrast to our observations from the XIAP BIR domain, in which surface pockets are formed at the peptide-binding site (Figure 2G). Though beyond the scope of the current work, we anticipate that further detailed studies may reveal the precise origin of the differing propensity for binding small-molecules exhibited by the peptide-binding groove of these two highly similar BIR domains.
Though large surface pockets do not form at the peptide-binding site of survivin, they do form readily at a specific alternate site: the same distal surface identified by Hajduk et al. [14] (Figure 6B, blue lines). Taken together, these studies of survivin suggest that low-energy fluctuations that induce pocket formation on the protein surface are indeed a primary determinant of druggability at protein interaction sites rather than a signature of the evolved protein-binding function of these sites.
The results presented above support the hypothesis that the conformational transitions that open pockets at a druggable site occur with little energetic cost to the protein. This has two important consequences.
First, pocket formation within the ensemble of physiological protein fluctuations occurs only at a limited subset of surface sites. Because pocket-containing conformations are rare, it is primarily the lack of a suitable surface pocket – and not chemical composition – that renders most protein surface sites undruggable. The highly restricted druggability of protein surfaces supported by both NMR [14] and crystallographic [15] observations that probe molecules interact with a very limited subset of the protein surface. Sites at which the unbound protein crystal structure includes a pre-formed pocket (HPV E2, FKPB12, ZipA) typically exhibit only minor conformational changes that change the size or shape of this pocket, and are driven primarily by sidechain reorganization. In contrast, for the examples in which the unbound protein crystal structure does not have a pre-formed pocket or has only a small surface pocket (XIAP, MDM2, Bcl-XL, IL-2) concerted motions are needed that couple backbone conformational changes to the sidechain reorganization that reveals the binding pocket. In both cases, the biasing potential we describe here serves as a proxy for the binding energy associated with some (unspecified) complementary compound, and thus drives sampling towards these conformations.
Second, these results suggest that a small number of low-resolution, low energy inhibitor shapes are encoded on the protein surface through intrinsic structural and dynamic features of the protein. We propose that low-energy fluctuations produce protein conformations displaying one of these preferred shapes, at which point a complementary small-molecule ligand may be accommodated. The protein then responds to the particular steric and chemical details of the ligand via subsequent smaller conformational changes, without changing the gross features of the pocket. This model implies that exploring the pocket shapes may give clues at low-resolution to the shapes of complementary ligands, and may form the basis for a computational screening approach that matches pocket shapes to potential inhibitory ligands.
As pointed out by Cheng and colleagues [46], pocket formation is necessary but may not be sufficient for a protein surface to be druggable: the curvature and hydrophobicity of the pocket are also important. By applying their methodology to the pocket conformations generated using the biasing potential described here, it may be possible to filter for the most druggable conformations from among these pocket-containing ensembles. These conformations may not necessarily correspond to the protein-bound conformation, which has been used in some cases as a starting point for mimicry by small-molecules [47]. Generating an ensemble of druggable conformations for a given protein target may prove valuable in identifying new inhibitory compounds, even in cases where one or more inhibitors are already known. Rather than aiming to identify additional inhibitors by analogy to these known compounds, or even using the protein structure solved in complex with one of these known compounds (or the natural protein partner), matching directly against an ensemble of pocket-containing conformations removes bias towards this parent compound (or protein partner). We anticipate that the surface pockets to which the protein is most predisposed, as revealed by this approach and therefore identified without artifacts of conformational changes in response to any particular binding partner, may serve as an optimal starting point for computational screening and may facilitate identification of chemotypes unrelated to those of known inhibitors ("scaffold hopping" [3], [48]). These new scaffolds may in turn yield potent novel small molecule inhibitors through subsequent chemical elaboration.
In principle, fragment-based approaches allow multiple probe molecules to be subsequently linked together to create a single compound presenting these probe moieties in the appropriate orientation [49]. Computational solvent mapping [27], while suitable for assessing druggability in certain cases, may prove limiting for early drug discovery because of its inability to explore the concerted backbone motions necessary for thoroughly sampling the "pocket ensemble". While FKBP sidechain motions within 6 Å of the binding site are sufficient for recognizing small probe molecules [49], the further necessity of backbone reorganization in other cases described here (XIAP, MDM2, Bcl-XL, IL-2) underscores the importance of backbone motions for conformational fluctuations that reveal surface pockets. Exploring these alternate conformations may further prove useful in guiding efforts to improve potency of known inhibitors, by identifying sites at which substituents can make additional strong contacts with the protein surface.
Finally, we note that the generality of our approach is conducive to its large-scale application for comparing druggability across many protein interaction sites. In the future, we expect this approach may be used to address the outstanding question of whether these few successful examples of small-molecules disrupting protein interaction sites are outliers, or whether they instead represent the first step towards an important class of new tools for therapeutic intervention.
Identifying pockets on protein surfaces
We implemented our modified version of the LIGSITEcs [28] algorithm in the Rosetta software suite [34]. Briefly, a grid is centered at the residue of interest on the protein surface and grid points are marked as occupied by either protein (P) or solvent (S). The algorithm performs linear searches in the X, Y and Z directions as well as in each diagonal for "P-nS-P" events: cases where a line no longer than 12 Å can be drawn between two points on the protein surface that pass through only solvent, establishing this solvent region as part of a surface pocket. Subsequent additional criteria were used to eliminate spurious definition of pockets and reduce the effect of grid-based artifacts (described in Text S1). Adjoining grid points defined as "pocket" were clustered to determine the deep pocket volume of the largest contiguous single pocket in contact with the target residue.
Simulation protocol
Simulations were carried out using the "relax" protocol [50] in Rosetta, which incorporates both backbone and sidechain degrees of freedom in a Monte Carlo search. To bias the simulations towards pocket-containing conformations we added to the standard energy function an additional energy term corresponding to the current deep pocket volume multiplied by a proportionality constant of −0.25 Rosetta energy units per Å3 ("moderate" bias). Simulations carried out with the "strong" bias used a proportionality constant of −0.25 Rosetta energy units per Å3. Data for each histogram was collected from 1,000 independent simulations. The simulation protocol is described in complete detail in Text S1.
Supporting Information
Figure S1.
Identifying pockets on protein surfaces (complements Figure 1). A grid is centered at the residue of interest on the protein surface (only partial grid is shown here). Grid points are classified as either "protein" (grey background) or "solvent" (white background). Linear searches (red lines) are used to identify and mark "protein-surface-protein" events (green gridpoints). These are further classified based on degree of buried (light vs. dark green) and adjoining grid points are clustered to yield discrete "pockets". Only a surface pocket in contact with the surface of the "target" residue (orange) contributes to the biasing potential.
Figure S2.
Deep pocket volumes compared to Q-SiteFinder pocket volumes (complements Figure 1). Deep pocket volumes of surface pockets at protein interaction sites harboring a bound inhibitor (red circles) and pockets found elsewhere on the protein surface (black x's) are plotted against the corresponding pocket volumes identified by Q-SiteFinder, for each of the sites used in Figure 1B. While the two are correlated, Q-SiteFinder volumes are typically larger than the corresponding deep pocket volumes.
Figure S3.
Matching of random surface sites to protein interaction sites (complements Figure 2). The distribution of pocket volumes identified by Q-SiteFinder for the complete set of random surface sites matched to the protein interaction sites on the basis of burial and secondary structure is shown (black); the corresponding pocket volumes for the protein interaction sites are also shown (red arrows). In order to create a matched set, only random sites with Q-SiteFinder pocket volumes greater than 100 Å3 were considered for Figures 2 and 3.
Figure S4.
Surface pockets emerge only at druggable sites, upon inclusion of additional random surface sites (complements Figure 2). Pocket opening is not observed at random surface sites upon inclusion of additional sites that were previously excluded on the basis of Q-SiteFinder pocket volumes less than 100 Å3 (dashed black lines). Symbols are as defined in Figure 2. (A) Bcl-XL. (B) IL-2. (C) FKBP12. (D) HPV E2. (E) ZipA. (F) MDM2. (G) BIR3 domain of XIAP.
Figure S5.
Surface pockets emerge at druggable sites, when starting from protein-bound conformations (complements Figure 2). Simulations were carried out only applying the biasing potential to the protein interaction site (red). With the exception of XIAP, results are in agreement with simulations started from the unbound protein structures (Figure 2). (A) Bcl-XL. (B) IL-2. (C) FKBP12. (D) HPV E2. (E) ZipA. (F) MDM2. (G) BIR3 domain of XIAP.
Figure S6.
Energetic analysis of pocket opening for the other members of our test set (complements Figure 3). (A) Conformations generated using the biasing potential typically have a distribution of energies that overlaps those generated with the biasing potential, suggesting that these conformations represent low-energy states accessible to the unbound protein. (B) As with Bcl-xL, low-energy conformations containing large pockets are not observed for the other members of our test set unless the biasing potential is applied to the protein interaction site. Symbols are as defined in Figure 3.
Figure S7.
Representative conformations generated using the biasing potential (complements Figure 4). An unbound crystal structure (pink), an inhibitor-bound crystal structure (green, with inhibitor shown in sticks), and a low-energy conformation generated from the unbound crystal structure using the biasing potential (cyan, with target residue in red) are shown for each of the proteins comprising our test set (except Bcl-XL, shown in Figure 4). (A) IL-2. (B) FKBP12. (C) HPV E2. (D) ZipA. (E) MDM2. (F) BIR3 domain of XIAP.
Figure S8.
Opening pockets shifts the protein backbone towards inhibitor-bound structures (complements Figure 5). Distributions of backbone RMSD over interface residues to the closest inhibitor-bound crystal structure for conformations generated with (red lines) or without (black lines) the biasing potential. The backbone RMSD over interface residues from the unbound structure to the most and least similar inhibitor-bound crystal structures are also indicated (dashed brown vertical lines).
Figure S9.
Hydrophobicity of pockets generated using the biasing potential are similar to the corresponding inhibitor-bound pockets (complements Figure 5). Distributions of percentage hydrophobic solvent accessible surface area (%hSASA) over interface atoms for conformations generated with the biasing potential (red lines). The lowest and highest %hSASAs from amongst all available inhibitor-bound crystal structures are indicated (dashed green vertical lines). (A) Bcl-XL. (B) IL-2. (C) FKBP12. (D) HPV E2. (E) ZipA. (F) MDM2. (G) BIR3 domain of XIAP.
Text S1.
Supplementary methods. This supporting text contains a complete description of methodology used, including PDB structures used in calculations. A description of pocket-opened conformations for each protein in our test set is also included in this text.
Author Contributions
Conceived and designed the experiments: DKJ JK. Performed the experiments: DKJ. Analyzed the data: DKJ JK. Wrote the paper: DKJ JK.
- 1. Sun H, Stuckey JA, Nikolovska-Coleska Z, Qin D, Meagher JL, et al. (2008) Structure-based design, synthesis, evaluation, and crystallographic studies of conformationally constrained Smac mimetics as inhibitors of the X-linked inhibitor of apoptosis protein (XIAP). J Med Chem 51: 7169–7180. doi: 10.1021/jm8006849
- 2. Bruncko M, Oost TK, Belli BA, Ding H, Joseph MK, et al. (2007) Studies leading to potent, dual inhibitors of Bcl-2 and Bcl-xL. J Med Chem 50: 641–662. doi: 10.1021/jm061152t
- 3. Rush TS 3rd, Grant JA, Mosyak L, Nicholls A (2005) A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction. Journal of medicinal chemistry 48: 1489–1495. doi: 10.1021/jm040163o
- 4. Wang Y, Coulombe R, Cameron DR, Thauvette L, Massariol MJ, et al. (2004) Crystal structure of the E2 transactivation domain of human papillomavirus type 11 bound to a protein interaction inhibitor. J Biol Chem 279: 6976–6985. doi: 10.1074/jbc.m311376200
- 5. Thanos CD, Randal M, Wells JA (2003) Potent small-molecule binding to a dynamic hot spot on IL-2. J Am Chem Soc 125: 15280–15281. doi: 10.1021/ja0382617
- 6. Becker JW, Rotonda J, Cryan JG, Martin M, Parsons WH, et al. (1999) 32-Indolyl ether derivatives of ascomycin: three-dimensional structures of complexes with FK506-binding protein. J Med Chem 42: 2798–2804. doi: 10.1021/jm9806042
- 7. Vassilev LT, Vu BT, Graves B, Carvajal D, Podlaski F, et al. (2004) In vivo activation of the p53 pathway by small-molecule antagonists of MDM2. Science 303: 844–848. doi: 10.1126/science.1092472
- 8. Wells JA, McClendon CL (2007) Reaching for high-hanging fruit in drug discovery at protein-protein interfaces. Nature 450: 1001–1009. doi: 10.1038/nature06526
- 9. Alsmadi O, Herz R, Murphy E, Pinter A, Tilley SA (1997) A novel antibody-dependent cellular cytotoxicity epitope in gp120 is identified by two monoclonal antibodies isolated from a long-term survivor of human immunodeficiency virus type 1 infection. J Virol 71: 925–933.
- 10. Domling A (2008) Small molecular weight protein-protein interaction antagonists: an insurmountable challenge? Curr Opin Chem Biol 12: 281–291. doi: 10.1016/j.cbpa.2008.04.603
- 11. Rechfeld F, Gruber P, Hofmann J, Kirchmair J (2011) Modulators of protein-protein interactions: novel approaches in targeting protein kinases and other pharmaceutically relevant biomolecules. Curr Top Med Chem 11: 1305–1319. doi: 10.2174/156802611795589610
- 12. Zinzalla G, Thurston DE (2009) Targeting protein-protein interactions for therapeutic intervention: a challenge for the future. Future Med Chem 1: 65–93. doi: 10.4155/fmc.09.12
- 13. Kenny CH, Ding W, Kelleher K, Benard S, Dushin EG, et al. (2003) Development of a fluorescence polarization assay to screen for inhibitors of the FtsZ/ZipA interaction. Anal Biochem 323: 224–233. doi: 10.1016/j.ab.2003.08.033
- 14. Hajduk PJ, Huth JR, Fesik SW (2005) Druggability indices for protein targets derived from NMR-based screening data. Journal of medicinal chemistry 48: 2518–2525. doi: 10.1021/jm049131r
- 15. Mattos C, Bellamacina CR, Peisach E, Pereira A, Vitkup D, et al. (2006) Multiple solvent crystal structures: probing binding sites, plasticity and hydration. J Mol Biol 357: 1471–1482. doi: 10.1016/j.jmb.2006.01.039
- 16. Metz A, Pfleger C, Kopitz H, Pfeiffer-Marek S, Baringhaus KH, et al. (2012) Hot spots and transient pockets: predicting the determinants of small-molecule binding to a protein-protein interface. J Chem Inf Model 52: 120–133. doi: 10.1021/ci200322s
- 17. Seco J, Luque FJ, Barril X (2009) Binding site detection and druggability index from first principles. Journal of medicinal chemistry 52: 2363–2371. doi: 10.1021/jm801385d
- 18. Eyrisch S, Helms V (2007) Transient pockets on protein surfaces involved in protein-protein interaction. J Med Chem 50: 3457–3464. doi: 10.1021/jm070095g
- 19. Laurie AT, Jackson RM (2005) Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites. Bioinformatics 21: 1908–1916. doi: 10.1093/bioinformatics/bti315
- 20. Foster TJ, MacKerell AD Jr, Guvench O (2012) Balancing target flexibility and target denaturation in computational fragment-based inhibitor discovery. Journal of computational chemistry 33: 1880–1891. doi: 10.1002/jcc.23026
- 21. Clodfelter KH, Waxman DJ, Vajda S (2006) Computational solvent mapping reveals the importance of local conformational changes for broad substrate specificity in mammalian cytochromes P450. Biochemistry 45: 9393–9407. doi: 10.1021/bi060343v
- 22. Landon MR, Amaro RE, Baron R, Ngan CH, Ozonoff D, et al. (2008) Novel druggable hot spots in avian influenza neuraminidase H5N1 revealed by computational solvent mapping of a reduced and representative receptor ensemble. Chemical biology & drug design 71: 106–116. doi: 10.1111/j.1747-0285.2007.00614.x
- 23. Landon MR, Lancia DR Jr, Yu J, Thiel SC, Vajda S (2007) Identification of hot spots within druggable binding regions by computational solvent mapping of proteins. Journal of medicinal chemistry 50: 1231–1240. doi: 10.1021/jm061134b
- 24. Prasad JC, Goldstone JV, Camacho CJ, Vajda S, Stegeman JJ (2007) Ensemble modeling of substrate binding to cytochromes P450: analysis of catalytic differences between CYP1A orthologs. Biochemistry 46: 2640–2654. doi: 10.1021/bi062320m
- 25. Eyrisch S, Helms V (2009) What induces pocket openings on protein surface patches involved in protein-protein interactions? J Comput Aided Mol Des 23: 73–86. doi: 10.1007/s10822-008-9239-y
- 26. Bakan A, Nevins N, Lakdawala AS, Bahar I (2012) Druggability Assessment of Allosteric Proteins by Dynamics Simulations in the Presence of Probe Molecules. Journal of chemical theory and computation 8: 2435–2447. doi: 10.1021/ct300117j
- 27. Kozakov D, Hall DR, Chuang GY, Cencic R, Brenke R, et al. (2011) Structural conservation of druggable hot spots in protein-protein interfaces. Proc Natl Acad Sci U S A 108: 13528–13533. doi: 10.1073/pnas.1101835108
- 28. Huang B, Schroeder M (2006) LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation. BMC structural biology 6: 19.
- 29. Brady GP Jr, Stouten PF (2000) Fast prediction and visualization of protein binding pockets with PASS. J Comput Aided Mol Des 14: 383–401.
- 30. Hendlich M, Rippmann F, Barnickel G (1997) LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins. Journal of Molecular Graphics & Modelling 15: 359–389, 359-363, 389. doi: 10.1016/s1093-3263(98)00002-3
- 31. Liang J, Edelsbrunner H, Woodward C (1998) Anatomy of protein pockets and cavities: measurement of binding site geometry and implications for ligand design. Protein Sci 7: 1884–1897. doi: 10.1002/pro.5560070905
- 32. Peters KP, Fauck J, Frommel C (1996) The automatic search for ligand binding sites in proteins of known three-dimensional structure using only geometric criteria. J Mol Biol 256: 201–213. doi: 10.1006/jmbi.1996.0077
- 33. Weisel M, Proschak E, Schneider G (2007) PocketPicker: analysis of ligand binding-sites with shape descriptors. Chem Cent J 1: 7. doi: 10.1186/1752-153x-1-7
- 34. Leaver-Fay A, Tyka M, Lewis SM, Lange OF, Thompson J, et al. (2011) ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules. Methods Enzymol 487: 545–574.
- 35. Velculescu VE, Madden SL, Zhang L, Lash AE, Yu J, et al. (1999) Analysis of human transcriptomes. Nat Genet 23: 387–388.
- 36. Paik S, Shak S, Tang G, Kim C, Baker J, et al. (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351: 2817–2826. doi: 10.1056/nejmoa041588
- 37. Rodel F, Frey B, Leitmann W, Capalbo G, Weiss C, et al. (2008) Survivin antisense oligonucleotides effectively radiosensitize colorectal cancer cells in both tissue culture and murine xenograft models. Int J Radiat Oncol Biol Phys 71: 247–255. doi: 10.1016/j.ijrobp.2008.02.011
- 38. Lewis KD, Samlowski W, Ward J, Catlett J, Cranmer L, et al. (2011) A multi-center phase II evaluation of the small molecule survivin suppressor YM155 in patients with unresectable stage III or IV melanoma. Invest New Drugs 29: 161–166. doi: 10.1007/s10637-009-9333-6
- 39. Kita A, Nakahara T, Yamanaka K, Nakano K, Nakata M, et al. (2011) Antitumor effects of YM155, a novel survivin suppressant, against human aggressive non-Hodgkin lymphoma. Leukemia research 35: 787–792. doi: 10.1016/j.leukres.2010.11.016
- 40. Altieri DC (2008) Survivin, cancer networks and pathway-directed drug discovery. Nature reviews Cancer 8: 61–70. doi: 10.1038/nrc2293
- 41. Sun H, Lu J, Liu L, Yi H, Qiu S, et al. (2010) Nonpeptidic and potent small-molecule inhibitors of cIAP-1/2 and XIAP proteins. J Med Chem 53: 6361–6367. doi: 10.1021/jm100487z
- 42. Dean EJ, Ward T, Pinilla C, Houghten R, Welsh K, et al. (2010) A small molecule inhibitor of XIAP induces apoptosis and synergises with vinorelbine and cisplatin in NSCLC. Br J Cancer 102: 97–103.
- 43. Wang Z, Cuddy M, Samuel T, Welsh K, Schimmer A, et al. (2004) Cellular, biochemical, and genetic analysis of mechanism of small molecule IAP inhibitors. J Biol Chem 279: 48168–48176. doi: 10.1074/jbc.m405022200
- 44. Schimmer AD, Welsh K, Pinilla C, Wang Z, Krajewska M, et al. (2004) Small-molecule antagonists of apoptosis suppressor XIAP exhibit broad antitumor activity. Cancer Cell 5: 25–35. doi: 10.1016/s1535-6108(03)00332-5
- 45. Wendt MD, Sun C, Kunzer A, Sauer D, Sarris K, et al. (2007) Discovery of a novel small molecule binding site of human survivin. Bioorg Med Chem Lett 17: 3122–3129. doi: 10.1016/j.bmcl.2007.03.042
- 46. Cheng AC, Coleman RG, Smyth KT, Cao Q, Soulard P, et al. (2007) Structure-based maximal affinity model predicts small-molecule druggability. Nature Biotechnology 25: 71–75. doi: 10.1038/nbt1273
- 47. Koes D, Khoury K, Huang Y, Wang W, Bista M, et al. (2012) Enabling large-scale design, synthesis and validation of small molecule protein-protein antagonists. PLoS One 7: e32839. doi: 10.1371/journal.pone.0032839
- 48. Quintus F, Sperandio O, Grynberg J, Petitjean M, Tuffery P (2009) Ligand scaffold hopping combining 3D maximal substructure search and molecular similarity. BMC Bioinformatics 10: 245. doi: 10.1186/1471-2105-10-245
- 49. Shuker SB, Hajduk PJ, Meadows RP, Fesik SW (1996) Discovering high-affinity ligands for proteins: SAR by NMR. Science 274: 1531–1534. doi: 10.1126/science.274.5292.1531
- 50. Qian B, Raman S, Das R, Bradley P, McCoy AJ, et al. (2007) High-resolution structure prediction and the crystallographic phase problem. Nature 450: 259–264. doi: 10.1038/nature06249


text:
Custom Printed
Homes are your business, why not feature
a homes and houses on your Christmas cards this year?
Order personalized Christmas cards for real estate agents,
title companies, inspectors and other realtor related business offices.
Christmas Cards for Real Estate Agents!
Personalized Happy Thanksgiving Cards
2016 Christmas Business Calendar Holiday Cards
Personalized Holiday Card Index


text:
Healthbeat - Diabetes in ChildrenUPDATED 6:14 AM MDT Mar 20, 2013
On the Healthbeat, Doctor Ramo talks about the things you can do to make sure your children don't get type two diabetes.
More Video
CommentsThe views expressed are not those of this site, this station or its affiliated companies. By posting your comments you agree to accept our terms of use.blog comments powered by Disqus


text:
|By Pat Romanski
Article Rating:
|February 1, 2013 03:00 PM EST
Cloud Expo New York $500 Savings here!
SYS-CON Events announced today that Supermicro, a global leader in high-performance, high-efficiency server technology and innovation, will exhibit at SYS-CON's 12th International Cloud Expo, which will take place on June 10-13, 2013, at the Javits Center in New York City, New York.
Explore Cloud Expo Sponsorship & Exhibit Opportunities !
Super Micro Computer, Inc. or Supermicro®, a global leader in high-performance, high-efficiency server technology and innovation, is a premier provider of end-to-end green computing solutions for Enterprise IT, Datacenter, Cloud Computing, HPC and Embedded Systems worldwide. Supermicro's advanced server Building Block Solutions® offers a vast array of modular, interoperable components for building energy-efficient, application-optimized, computing solutions. This broad line of products includes servers, blades, GPU systems, workstations, motherboards, chassis, power supplies, storage technologies, networking solutions and SuperRack® cabinets/accessories. Architecture innovations include Twin Architecture, SuperServer®, SuperBlade®, MicroCloud, Super Storage Bridge Bay (SBB), Double-Sided StorageTM, Universal I/O (UIO) and WIO expansion technology all of which deliver unrivaled performance and value.
For more information, please visit http://www.supermicro.com.
A Rock Star Faculty, Top Keynotes, Sessions, and Top Delegates!
Cloud Expo 2013 New York, June 10-13, at the Javits Center in New York City, New York, will feature technical sessions from a rock star conference faculty and the leading Cloud industry players in the world.
The growth and success of Cloud Computing will be on display at the upcoming Cloud Expo conference and exhibition in New York City, New York, June 10-13, 2013.
The recent Cloud Expo at the Santa Clara Convention Center in Santa Clara, CA, was the largest Cloud Computing conference ever produced with more sponsors, exhibitors and delegates than all other Cloud events of the year combined!
Cloud Expo New York will attract more than 10,000 delegates from 48 countries and over 200 sponsors and exhibitors!
All main layers of the Cloud ecosystem will be represented at the 12th International Cloud Expo - the infrastructure players, the platform providers, and those offering applications, and they'll all be here to speak, sponsor, exhibit and network.
"Cloud Expo was announced on February 24, 2007, the day the term 'cloud computing' was coined," said Fuat Kircaali, founder and chairman of SYS-CON Events, Inc. "Cloud has become synonymous with 'computing' and 'software' in two short years, and this event has become the new PC Expo, Comdex, and InternetWorld of our decade. By 2013, more than 50,000 delegates per year will be attending Cloud Expo."
Sponsorship Opportunities
for Cloud Expo 2013 New York
Cloud Expo 2013 New York "show prospectus" has shipped. Sponsorship, exhibit, and keynote opportunities can be obtained from Carmen Gonzalez by email at events (at) sys-con.com, or by phone 201 802-3021.
Early Bird Registration Options
for Cloud Expo 2013 New York
Cloud Expo delegates can pre-register for Cloud Expo New York with $500+ savings here.
About SYS-CON Media & Events
SYS-CON Media (www.sys-con.com) has since 1994 been connecting technology companies and customers through a comprehensive content stream at www.sys-con.com - featuring over forty focused subject areas, from Cloud Computing to Web Security - interwoven with market-leading full-scale conferences produced by SYS-CON Events. The company's internationally recognized brands include among others Cloud Expo (www.CloudComputingExpo.com), Big Data Expo (http://BigDataExpo.net), Virtualization Conference & Expo (www.VirtualizationConference.com), Government IT Conference & Expo (www.GovITExpo.com), Cloud Computing Bootcamp (www.CloudComputingBootcamp.com), and UlitzerLive! New Media Conference & Expo (http://events.sys-con.com).
Cloud Expo, Cloud Expo East, Cloud Expo West, Cloud Expo New York, Cloud Expo Silicon Valley, Cloud Expo Europe, Cloud Expo Tokyo, Cloud Expo Prague, Cloud Expo Hong Kong, Cloud Expo Sao Paolo are trademarks and /or registered trademarks (USPTO serial number 85009040) of Cloud Expo, Inc.
Jacqueline Chang (1-408-373-2497) [email protected]
Martin Jiang (1-408-396-0882) [email protected]
Janelyn Rosario (1-408-898-6457) [email protected]
Edison Shih (1-408-614-5701) [email protected]
[guide] Cloud Analytics for Dummies | @CloudExpo @Informatica #API #Cloud #Analytics #BusinessIntelligence
Cloud analytics is dramatically altering business intelligence. Some businesses will capitalize on these promising new technologies and gain key insights that'll help them gain competitive advantage. And others won't. Whether you're a business leader, an IT manager, or an analyst, we want to help you and the people you need to influence with a free copy of "Cloud Analytics for Dummies," the essential guide to this explosive new space for business intelligence.
Jul. 30, 2016 08:30 AM EDT Reads: 1,013
Manufacturers are embracing the Industrial Internet the same way consumers are leveraging Fitbits – to improve overall health and wellness. Both can provide consistent measurement, visibility, and suggest performance improvements customized to help reach goals. Fitbit users can view real-time data and make adjustments to increase their activity. In his session at @ThingsExpo, Mark Bernardo Professional Services Leader, Americas, at GE Digital, discussed how leveraging the Industrial Internet a...
Jul. 30, 2016 08:00 AM EDT Reads: 735
UpGuard has become a member of the Center for Internet Security (CIS), and will continue to help businesses expand visibility into their cyber risk by providing hardening benchmarks to all customers. By incorporating these benchmarks, UpGuard's CSTAR solution builds on its lead in providing the most complete assessment of both internal and external cyber risk. CIS benchmarks are a widely accepted set of hardening guidelines that have been publicly available for years. Numerous solutions exist t...
Jul. 30, 2016 07:45 AM EDT Reads: 854
Amazon has gradually rolled out parts of its IoT offerings in the last year, but these are just the tip of the iceberg. In addition to optimizing their back-end AWS offerings, Amazon is laying the ground work to be a major force in IoT – especially in the connected home and office. Amazon is extending its reach by building on its dominant Cloud IoT platform, its Dash Button strategy, recently announced Replenishment Services, the Echo/Alexa voice recognition control platform, the 6-7 strategic...
Jul. 30, 2016 07:45 AM EDT Reads: 708
In addition to all the benefits, IoT is also bringing new kind of customer experience challenges - cars that unlock themselves, thermostats turning houses into saunas and baby video monitors broadcasting over the internet. This list can only increase because while IoT services should be intuitive and simple to use, the delivery ecosystem is a myriad of potential problems as IoT explodes complexity. So finding a performance issue is like finding the proverbial needle in the haystack.
Jul. 30, 2016 07:45 AM EDT Reads: 2,395
There will be new vendors providing applications, middleware, and connected devices to support the thriving IoT ecosystem. This essentially means that electronic device manufacturers will also be in the software business. Many will be new to building embedded software or robust software. This creates an increased importance on software quality, particularly within the Industrial Internet of Things where business-critical applications are becoming dependent on products controlled by software. Qua...
Jul. 30, 2016 07:30 AM EDT Reads: 1,675
In his session at Cloud Expo, Robert Cohen, an economist and senior fellow at the Economic Strategy Institute, will provide economic scenarios that describe how the rapid adoption of software-defined everything including cloud services, SDDC and open networking will change GDP, industry growth, productivity and jobs. This session will also include a drill down for several industries such as finance, social media, cloud service providers and pharmaceuticals.
Jul. 30, 2016 07:15 AM EDT Reads: 447
DevOps at Cloud Expo – being held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA – announces that its Call for Papers is open. Born out of proven success in agile development, cloud computing, and process automation, DevOps is a macro trend you cannot afford to miss. From showcase success stories from early adopters and web-scale businesses, DevOps is expanding to organizations of all sizes, including the world's largest enterprises – and delivering real results. Am...
Jul. 30, 2016 05:45 AM EDT Reads: 2,388
The 19th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Digital Transformation, Microservices and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportuni...
Jul. 30, 2016 05:15 AM EDT Reads: 2,710
"We host and fully manage cloud data services, whether we store, the data, move the data, or run analytics on the data," stated Kamal Shannak, Senior Development Manager, Cloud Data Services, IBM, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Jul. 30, 2016 05:15 AM EDT Reads: 1,470
With the proliferation of both SQL and NoSQL databases, organizations can now target specific fit-for-purpose database tools for their different application needs regarding scalability, ease of use, ACID support, etc. Platform as a Service offerings make this even easier now, enabling developers to roll out their own database infrastructure in minutes with minimal management overhead. However, this same amount of flexibility also comes with the challenges of picking the right tool, on the right ...
Jul. 30, 2016 04:45 AM EDT Reads: 1,473
IoT is rapidly changing the way enterprises are using data to improve business decision-making. In order to derive business value, organizations must unlock insights from the data gathered and then act on these. In their session at @ThingsExpo, Eric Hoffman, Vice President at EastBanc Technologies, and Peter Shashkin, Head of Development Department at EastBanc Technologies, discussed how one organization leveraged IoT, cloud technology and data analysis to improve customer experiences and effi...
Jul. 30, 2016 04:00 AM EDT Reads: 2,133
The Internet of Things will challenge the status quo of how IT and development organizations operate. Or will it? Certainly the fog layer of IoT requires special insights about data ontology, security and transactional integrity. But the developmental challenges are the same: People, Process and Platform. In his session at @ThingsExpo, Craig Sproule, CEO of Metavine, demonstrated how to move beyond today's coding paradigm and shared the must-have mindsets for removing complexity from the develo...
Jul. 30, 2016 03:00 AM EDT Reads: 1,653
SYS-CON Events announced today that MangoApps will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. MangoApps provides modern company intranets and team collaboration software, allowing workers to stay connected and productive from anywhere in the world and from any device.
Jul. 30, 2016 02:45 AM EDT Reads: 1,493
"delaPlex Software provides software outsourcing services. We have a hybrid model where we have onshore developers and project managers that we can place anywhere in the U.S. or in Europe," explained Manish Sachdeva, CEO at delaPlex Software, in this SYS-CON.tv interview at @ThingsExpo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Jul. 30, 2016 02:00 AM EDT Reads: 1,693
Predictive analytics tools monitor, report, and troubleshoot in order to make proactive decisions about the health, performance, and utilization of storage. Most enterprises combine cloud and on-premise storage, resulting in blended environments of physical, virtual, cloud, and other platforms, which justifies more sophisticated storage analytics. In his session at 18th Cloud Expo, Peter McCallum, Vice President of Datacenter Solutions at FalconStor, discussed using predictive analytics to mon...
Jul. 30, 2016 12:30 AM EDT Reads: 2,138
Keeping pace with advancements in software delivery processes and tooling is taxing even for the most proficient organizations. Point tools, platforms, open source and the increasing adoption of private and public cloud services requires strong engineering rigor – all in the face of developer demands to use the tools of choice. As Agile has settled in as a mainstream practice, now DevOps has emerged as the next wave to improve software delivery speed and output. To make DevOps work, organization...
Jul. 30, 2016 12:30 AM EDT Reads: 2,353
The IoT is changing the way enterprises conduct business. In his session at @ThingsExpo, Eric Hoffman, Vice President at EastBanc Technologies, discussed how businesses can gain an edge over competitors by empowering consumers to take control through IoT. He cited examples such as a Washington, D.C.-based sports club that leveraged IoT and the cloud to develop a comprehensive booking system. He also highlighted how IoT can revitalize and restore outdated business models, making them profitable ...
Jul. 29, 2016 10:15 PM EDT Reads: 2,085
SYS-CON Events announced today that Isomorphic Software will exhibit at DevOps Summit at 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Isomorphic Software provides the SmartClient HTML5/AJAX platform, the most advanced technology for building rich, cutting-edge enterprise web applications for desktop and mobile. SmartClient combines the productivity and performance of traditional desktop software with the simp...
Jul. 29, 2016 10:00 PM EDT Reads: 1,296
"When you think about the data center today, there's constant evolution, The evolution of the data center and the needs of the consumer of technology change, and they change constantly," stated Matt Kalmenson, VP of Sales, Service and Cloud Providers at Veeam Software, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Jul. 29, 2016 09:45 PM EDT Reads: 1,511