the lowest possible energy level for an electron is known as vacuum level.
the lowest possible energy level for an electron is known as?
vacuum level
if an electron of the special pair in the reaction center becomes excited, it cannot transfer this energy to another pigment using resonance energy transfer. in normal circumstances, the electron should return to the ground state, but, because the reaction center is arranged so that a suitable electron acceptor is nearby, the excited electron can move from the initial molecule to the acceptor. this process results in the formation of a positive charge on the special pair (due to the loss of an electron) and a negative charge on the acceptor and is, hence, referred to as photoinduced charge separation. in other words, electrons in pigment molecules can exist at specific energy levels. under normal circumstances, they exist at the lowest possible energy level they can. however, if there is enough energy to move them into the next energy level, they can absorb that energy and occupy that higher energy level. the light they absorb contains the necessary amount of energy needed to push them into the next level. any light that does not have enough or has too much energy cannot be absorbed and is reflected. the electron in the higher energy level, however, does not want to be there; the electron is unstable and must return to its normal lower energy level. to do this, it must release the energy that has put it into the higher energy state to begin with. this can happen various ways. the extra energy can be converted into molecular motion and lost as heat. some of the extra energy can be lost as heat energy, while the rest is lost as light. (this re-emission of light energy is called fluorescence.) the energy, but not the e- itself, can be passed onto another molecule. (this is called resonance.) the energy and the e- can be transferred to another molecule. plant pigments usually utilize the last two of these reactions to convert the sun's energy into their own.
light-dependent reactions
as a means of surpassing the limitations of these techniques, projects such as folding@home and rosetta@home are aimed at resolving this problem using computational analysis, this means of resolving protein structure is referred to as protein structure prediction. although many labs have a slightly different approach, the main concept is to find, from a myriad of protein conformations, which conformation has the lowest energy or, in the case of folding@home, to find relatively low energies of proteins that could cause the protein to misfold and aggregate other proteins to itself—like in the case of sickle cell anemia. the general scheme in these projects is that a small number of computations are parsed to, or sent to be calculated on, a computer, generally a home computer, and then that computer analyzes the likelihood that a specific protein will take a certain shape or conformation based on the amount of energy required for that protein to stay in that shape, this way of processing data is what is generally referred to as distributed computing. this analysis is done on an extraordinarily large number of different conformations, owing to the support of hundreds of thousands of home-based computers, in hopes to find the conformation of lowest possible energy or set of conformations of lowest possible energy relative to any conformations that are just slightly different. although doing so is quite difficult, one can, by observing the energy distribution of a large number of conformations, despite the almost infinite number of different protein conformations possible for any given protein (see levinthal paradox), with a reasonably large number of protein energy samplings, predict relatively closely what conformation, within a range of conformations, has the expected lowest energy using methods in statistical inference. there are other factors such as salt concentration, ph, ambient temperature or chaperonins, which are proteins that assist in the folding process of other proteins, that can greatly affect how a protein folds. however, if the given protein is shown to fold on its own, especially in vitro, these findings can be further supported. once we can see how a protein folds then we can see how it works as a catalyst, or in intracellular communication, e.g. neuroreceptor-neurotransmitter interaction. how certain compounds may be used to enhance or prevent the function of these proteins and how an elucidated protein overall plays a role in diseases such as alzheimer's disease or huntington's disease can also be much better understood.
dry lab