Acute Lower Respiratory Infection in Childhood and Household Fuel Use in Bhaktapur, Nepal
May 2013

Michael N Bates
Division of Environmental Health Sciences
School of Public Health
University of California
Berkeley, BerkeleyCaliforniaUSA

Ram K Chandyo
Centre for International Health
University of Bergen
BergenNorway

Palle Valentiner-Branth
Department of Infectious Disease Epidemiology
Statens Serum Institut
CopenhagenDenmark

Amod K Pokhrel
Division of Environmental Health Sciences
School of Public Health
University of California
Berkeley, BerkeleyCaliforniaUSA

Maria Mathisen
Department of Microbiology and Infection Control
University Hospital of North Norway
TromsøNorway

Sudha Basnet
Centre for International Health
University of Bergen
BergenNorway

Child Health Department
Institute of Medicine
Tribhuvan University
KathmanduNepal

Prakash S Shrestha
Child Health Department
Institute of Medicine
Tribhuvan University
KathmanduNepal

Tor A Strand
Centre for International Health
University of Bergen
BergenNorway

Medical Microbiology
Department of Laboratory Medicine
Innlandet Hospital Trust
LillehammerNorway

Division of Infectious Disease Control
Norwegian Institute of Public Health
OsloNorway

Kirk R Smith
Division of Environmental Health Sciences
School of Public Health
University of California
Berkeley, BerkeleyCaliforniaUSA

Acute Lower Respiratory Infection in Childhood and Household Fuel Use in Bhaktapur, Nepal

Environmental Health Perspectives •
1215May 201310.1289/ehp.1205491637 Research | Children's Health [Online 19 March 2013]biomasscase-control studycookingheatinghousehold air pollutionkerosenepneumonia Environ Health
Background: Globally, solid fuels are used by about 3 billion people for cooking. These fuels have been associated with many health effects, including acute lower respiratory infection (ALRI) in young children. Nepal has a high prevalence of use of biomass for cooking and heating. oBjective: This case-control study was conducted among a population in the Bhaktapur municipality, Nepal, to investigate the relationship of cookfuel type to ALRI in young children. Methods: Cases with ALRI and age-matched controls were enrolled from an open cohort of children 2-35 months old, under active monthly surveillance for ALRI. A questionnaire was used to obtain information on family characteristics, including household cooking and heating appliances and fuels. The main analysis was carried out using conditional logistic regression. Populationattributable fractions (PAF) for stove types were calculated. results: A total of 917 children (452 cases and 465 controls) were recruited into the study. Relative to use of electricity for cooking, ALRI was increased in association with any use of biomass stoves [odds ratio (OR) = 1.93; 95% CI: 1.24, 2.98], kerosene stoves (OR = 1.87; 95% CI: 1.24, 2.83), and gas stoves (OR = 1.62; 95% CI: 1.05, 2.50). Use of wood, kerosene, or coal heating was also associated with ALRI (OR = 1.45; 95% CI: 0.97, 2.14), compared with no heating or electricity or gas heating. PAFs for ALRI were 18.0% (95% CI: 8.1, 26.9%) and 18.7% (95% CI: 8.4%-27.8%), for biomass and kerosene stoves, respectively. conclusions: The study supports previous reports indicating that use of biomass as a household fuel is a risk factor for ALRI, and provides new evidence that use of kerosene for cooking may also be a risk factor for ALRI in young children.

Solid fuels, consisting of coal and biomass (crop waste, wood, and animal dung), are used by nearly 3 billion people around the world for cooking and sometimes heating [Bonjour et al., in press; UNDP (United Nations Development Program)-WHO (World Health Organization) 2009]. These fuels are often burned in stoves, without chimneys or hoods and with little or no ventilation, and are a major source of household air pollution (HAP). Use of these fuels has been associated with a wide range of health effects, particularly in women, who are most exposed because they usually do the cooking (Bruce et al. 2000;Smith et al. 2004). Also particularly highly exposed are young children who spend most of their time with their mothers. Epidemiologic studies have produced evidence that cooking with biomass is associated with acute lower respiratory infection (ALRI) or pneumonia in young children, possibly through an immune suppressant mechanism (Dherani et al. 2008;Smith et al. 2011). ALRI is the major killer of children < 5 years of age in developing coun tries, and has been estimated to be responsible for > 2 million deaths per year (Black et al. 2010). It has also been estimated that solid fuel use is responsible for 30% of these cases globally, and for 38% of cases in the WHO's SouthEast Asian Region D, of which Nepal is a part (Niessen et al. 2009).

In Nepal, where the present study took place, many families use biomass for cook ing or heating, and there can be high indoor concentrations of combustion products. We know of only one previous investigation of ALRI in relation to stove type in Nepal. This study, in the Dhading district, attrib uted approximately 50% of ALRI in children < 5 years of age to household use of solid fuel burning stoves (Dhimal et al. 2010).

This case-control study was conducted in an area of Nepal with a balanced distribu tion of primary cookfuel types-electricity, liquified petroleum gas (LPG), kerosene, and biomass-with the primary objective of inves tigating the relationships of cookfuel types to ALRI and estimating populationattributable fractions.

Methods

The study was carried out as an adjunct to a case-control study designed primarily to investigate respiratory viruses in children with and without pneumonia (Mathisen et al. 2010). Cases and controls were enrolled from an open cohort of children < 3 years old, who were under active monthly surveil lance for respiratory illness in Bhaktapur, a small city (population about 72,000) 13 km east of Kathmandu, the capital of Nepal. The total population of Bhaktapur district is about 225,000, with a population density of 1,895/km 2 (Government of Nepal 2001). Residents are farmers with fields in the sur rounding area, semiskilled and unskilled laborers, and daily wage earners. There is one highway with moderate traffic on the border of the municipality and some narrow roads, mainly for motorcycles and tractors, inside. Around the municipality, there are about 10 brick kilns, which operate mainly during winter and summer and contribute to out door air pollution in the area.

Bhaktapur municipality represents an intermediate type between an ancient and modern city. The houses are usually joined together forming a courtyard. Most houses have traditional architecture of two or three stories and three or four rooms. The exter nal walls are of brick with cement or mud. Roofs are usually constructed with concrete, corrugated sheet metal, or brick tiles. Floors are constructed mainly with packed mud or concrete. Of 917 study participants, 236 (26%) had primary biomass fuel stoves. Of these, 186 (79%) had a traditional openfire mud stove, called a chulo, with 1-3 potholes. volume 121 | number 5 | May 2013 • Environmental Health Perspectives Fortynine participants (21%) had a ricehusk mud stove without a chimney or hood.

Trained fieldworkers referred children with respiratory complaints to the study clinic at the Siddhi Memorial Hospital inside Bhaktapur municipality. Selfreferrals were also accepted from the study population. Study physicians classified ALRIs according to standard WHO criteria (WHO 2005). ALRI was defined as cough or breathing diffi culty combined with fast breathing (i.e., > 50 breaths/min for children 2-11 months of age or > 40 breaths/min for children ≥ 12 months of age). Severe ALRI was defined as cough or breathing difficulty accompanied by lower chest wall indrawing. Excluded from the study were cases with other severe illness, documented tuberculosis or congenital heart disease, dysentery, severe anemia (hemoglo bin < 7mg/L), severe malnutrition [< 70% median weight for height or length (National Center for Health Statistics 1976)], cough for > 14 days, or having received antibiotics within the preceding 48 hr.

Potential controls, matched to cases by age in months, were randomly selected from a list of children under surveillance that was updated monthly. The surveillance was based on a baseline census conducted before the study began. Using data from the census, we generated a list of all children < 3 years of age and updated the list by identifying new born babies and excluding children who had reached 36 months of age, moved away from the area, or left the cohort for other reasons. Fieldworkers visited homes of potential con trols and requested consent from parents for their child's participation. If consent was obtained, the child was examined for eligibil ity in the study clinic. Eligibility included confirmation that the child did not have ALRI and application of the same exclusion criteria as for cases. Although we measured hemoglo bin concentration in all cases, we measured it only in those controls with suspected severe anemia. So it is possible that some controls with severe anemia were retained in the study.

When parents of a potential control child refused participation, another child's family was approached. For the larger study involv ing viral prevalence, from which these cases and controls were drawn, 1,955 potential controls were approached, with a refusal rate of about 8% (Mathisen et al. 2010). From the case group the refusal rate was 8.5% (Mathisen et al. 2009).

During May 2006-June 2007, the house hold fuel use study team was notified about confirmed cases of pneumonia as they were diagnosed and about potential control house holds as they were identified. Subject to informed consent, a questionnaire was admin istered to an adult household member, usually the child's mother, to obtain information on family characteristics, including household cooking and heating appliances, both primary and secondary. All interviews were conducted in the children's homes, and the stoves and cookfuels used were confirmed by inspection during this visit.

Human subjects' approvals were obtained from the institutional review boards at the University of California, Berkeley; the Institute of Medicine; Tribhuvan University Teaching Hospital; and the Regional Committee for Medical and Health Research Ethics (REK VEST), Norway.

Statistical procedures. Although a one toone ageinmonths matching of cases and controls was originally sought, it was not exactly achieved, for logistical reasons and because of refusals to participate. To preserve study power, corresponding cases or controls were not eliminated from the study when a participation refusal occurred. Instead, we ran conditional logistic regression models using age in months as a matching variable, rather than individual casetocontrol matchings.

We first identified all potentially appro priate covariates for which data had been col lected. We selected covariates for the final model after investigating candidate variables in the following way: First we selected vari ables that we considered related directly to the exposure of the child (primary and secondary stove types, child in kitchen during cooking, space heating in winter, usual kitchen ventila tion). Then, to identify potential confounders of the association with stove type, for each remaining variable we examined two asso ciations: a) between primary stove type and potential confounder in the control group, and b) between the candidate variable and the outcome (ALRI) in study participants after removal of those whose families used biomass or kerosene stoves as their primary stoves. These associations were investigated without adjusting for any other variables. Any variable that predicted both primary stove type and ALRI with a pvalue of ≤ 0.2 was included in the final model. Finally, as a pre caution, we considered the model in terms of a causal diagram to ensure that we were not adjusting for anything on the causal pathway and not adjusting for a collider (Greenland et al. 1999). In addition, we evaluated the influence of adding covariates back to the selected final models on odds ratios (ORs) as a sensitivity analysis.

Some models were run after creating indicator variables for any biomass stove, any kerosene stove, and any gas stove, combining comparable primary and secondary stove types.

Populationattributable fractions (PAF) and associated confidence intervals were cal culated using the aflogit command of Stata (Eide 2008). Because this procedure does not work when used with conditional logistic regression analysis, the corresponding uncon ditional model was used instead. The calcula tion of PAFs controls for covariates in the model and is based on the method described by Greenland and Drescher (1993).

Results

A total of 917 children (452 cases and 465 controls) were recruited into the study. Table 1 shows the distribution across cases and controls of selected household character istics, including stove/fuel types. Unadjusted ORs for ALRI and 95% CIs are also shown for each of the displayed variables. Because age was a matching factor, ORs for age are not shown.

Several HAP exposure-related variables were associated with ALRI in the bivariate analyses. These include having a child in the kitchen when cooking, having a small kitchen, having either doors or windows (but not both) open while cooking, and using wood, kerosene, or coal for heating. Among primary stoves, kerosene burners had the highest OR relative to electric stoves, followed by bio mass stoves and then gas stoves. There was no evidence of increased risk associated with sec ondary stoves when households using either electric secondary stoves or having no second ary stove were used as the baseline category. However, inspection of the joint distribution of primary and secondary stoves (Table 2) suggested associations between ALRI and the type of secondary stove could be negatively confounded by primary stoves: Households with no secondary stove or where the second ary stove was electric were much more likely to have primary stoves fueled by either kero sene or biomass than were other secondary stove type users. Fiftyfive percent of primary electric stoveusing households had biomass or kerosenefueled secondary stoves, com pared with < 16% in all the other primary stove categories.

Other than those factors, only a few of the other household characteristics in Table 1 showed evidence of association with child ALRI. Lower education of both the father and the mother and having two or more smok ers in the household were associated with increased ORs. ALRI was less likely among children whose mother did housework rather than work outside the home, and was less likely if incense or mosquito coils were burned inside the home.

Included in our final model (Table 3) were the exposurerelated variables: primary and secondary stove types, usual kitchen ventilation, child in kitchen during cooking, and space heating used in winter. Because they were identified as potential confound ers of the primary stove-ALRI relationship, we also included mother's education, moth er's occupation, having one or more family members who smoke indoors, and living in a single-family dwelling or sharing a house. Categorization in the model was as shown in Table 1.

Adjusted odds ratios for non-electric primary and secondary stoves were higher than unadjusted estimates, particularly for secondary stoves-reflecting adjustment for confounding by primary stoves. Increased risks were associated with use of all three types of fuel-using primary cookstoves: biomass (OR = 2.13; 95% CI: 1.34, 3.41), kerosene In relation to the proportion of time the child spent in the kitchen during cooking, we found marked differences across primary stove types: For kerosene the proportion of children reported to be in the kitchen all of the time was 89%, compared with 29% for biomass (47% for electricity and 60% for gas). There was much less variation of ventilation (doors or windows open during cooking) across stove types than was observed for having the child in the kitchen. We therefore carried out analyses, similar to that of the main model, stratified by the variable for having a child in the kitchen during cooking. Table 4 shows the results. In the situation when the child is never in the kitchen, ORs are quite variable with broad confidence intervals, including the null. When the child is in the kitchen, either some of the time or all of the time during cooking, ORs are appreciably higher, with confidence intervals that exclude the null.

We carried out extensive sensitivity test ing by adding covariates to the final model, but the ORs for primary fuel types changed relatively little whichever the additional cova riates. For example, in a model with all cova riates in Table 1, the ORs for primary stoves were as follows: gas (OR = 1.54; 95% CI: 0.93, 2.56), kerosene (OR = 2.14; 95% CI: 1.25, 3.67); and biomass (OR = 2.00; 95% CI: 1.22, 3.29), which are not substan tially different from those in Table 3.

We also created indicator variables for any biomass stove, any kerosene stove and any gas stove, combining comparable primary and secondary stove types, and ran these in a model adjusted for the covariates in the final model (Table 3). For biomass stoves, the OR was 1.93 (95% CI: 1.24, 2.98), for kerosene stoves, 1.87 (95% CI: 1.24, 2.83), and for gas stoves 1.62 (95% CI: 1.05, 2.50).

PAFs associated with these combined stove variables were calculated after adjustment for the covariates in the final model. For ALRI in the population < 3 years of age of Bhaktapur, PAFs were as follows: biomass stoves, 18.0% (95% CI: 8.1, 26.9%), kerosene stoves, 18.7% (95% CI: 8.4, 27.8%), and gas stoves, 12.0% (95% CI: 2.5, 20.7%). For space heat ing with wood, kerosene, or coal, the PAF was 5.0% (95% CI: -0.6, 10.3%). The total estimated PAF for all cooking and heating fuels was 49.0% (95% CI: 25.6, 65.1%). These PAFs were calculated using the aflogit procedure following an unconditional logis tic regression model that included all covari ates used in the conditional model plus age. This model produced results similar to those from the conditional model. For example, for biomass and kerosene stoves, correspond ing unconditional ORs were 1.97 (95% CI: 1.26, 3.07) and 1.91 (95% CI: 1.26, 2.91), respectively.

Discussion

The database used for this analysis is possibly unique. It contains a roughly equal four way split of households that use electricity, gas, biomass, and kerosene as their primary cookfuel. Importantly, the existence of a substantial number of houses using electric stoves provides a good baseline against which the effect of fuelconsuming stoves can be estimated. All three fuelusing stove types were positively associated with ALRI. Of par ticular note, the OR for kerosene primary stoves, compared with electric stoves (2.33; 95% CI: 1.40, 3.86), is comparable to or greater than that for biomass stoves (2.13; 95% CI: 1.34, 3.41).

Another unusual feature of this study is that it collected and analyzed data on second ary stoves. Most other investigations of health effects of household cookfuel in developing countries have focused on primary stoves. However, as this analysis has shown, second ary stoves may be important predictors of health risk in their own right.

Previous studies have produced evidence that biomassburning stoves are associated with increased relative risk estimates for ALRI. A metaanalysis of 24 studies produced a sum mary estimate of 1.78 (95% CI: 1.45, 2.18) for the relationship between household use of solid fuels (wood, dung, charcoal, and coal), relative to use of fuels considered "clean" (elec tricity, gas, or kerosene), and ALRI in chil dren < 5 years of age (Dherani et al. 2008). More recent studies have found ALRI risks of a similar magnitude associated with solid fuel use (Bautista et al. 2009;Rehfuess et al. 2009). This compares with our OR of 2.13 (Table 3) for having a main stove that used biomass. The difference may reflect that our baseline category is electricity, whereas most of the studies included in the metaanalysis used gas or liquid fuels as their baseline.

To our knowledge, only one previous investigation has examined keroseneburning stoves as a possible risk factor for ALRI. In a study of ALRI in 642 children < 1 year of age in two slums in Delhi, India, the OR for kerosene use in one slum was 1.98 (95% CI: 1.14, 3.45), but in the other slum was 0.95 (95% CI: 0.59, 1.54) (Sharma et al. 1998). The authors provided no explanation for the difference in results. There have been few epidemiologic studies that have investigated kerosene stove use as a possible risk fac tor for any respiratory disease. However, a recent study of risk factors for pulmonary tuberculosis in Nepal reported a substantially stronger association with kerosene cook stoves (OR = 3.4; 95% CI: 1.0, 11), than  with biomassburning cookstoves (OR = 1.2; 95% CI: 0.5, 3.1) (Pokhrel et al. 2010). In the same study, the OR for use of simple kerosene lamps, relative to electric lighting, was 9.43 (95% CI: 1.45, 61). We also note the elevated ORs for cooking with gas. Because most studies investigating associations between cooking with biomass and ALRI have been carried out using LPG in the reference fuel category, there are few, if any, available comparisons. In some coun tries, however, LPG use has been associated with increased respiratory risk (Moshammer et al. 2010), suggesting that its use may not be entirely benign. Other studies using cook ing with electricity as a baseline category are needed to ascertain whether our finding for gas cooking represents a real risk increase.

Although the responsible components of cooksmoke that induce respiratory problems are unknown, it has been well established by a number of studies that the amount of indoor air pollution from particulate matter emitted by kerosene stoves is appreciably less than that associated with biomassburning stoves (Saksena et al. 2003). In one study, however, kerosene stove-and wood stove-using cooks had approximately the same levels of per sonal exposures to particulate matter, despite kitchen PM concentrations for wood users being approximately twice that of kerosene users (Saksena et al. 2003). The authors sug gested that this difference occurred because kerosene users cook for longer periods than wood users, are more likely to cook indoors, and spend more time in closer proximity to the stove. Because young children are likely to spend most of their waking time close to their mothers, our findings on the rela tive proportions of time children spend in the kitchen in families with primary bio mass or kerosene stoves are consistent with Saksena's observations.

Alternative explanations for our results, particularly those for kerosene, need to be considered. Information bias seems unlikely because the ALRI was clinically confirmed and interviews were carried out in homes, permitting interviewers to confirm the accu racy of stove reporting. Use of primary and secondary stove/fuel types as categorical vari ables is a somewhat crude representation of exposures within a home, because it does not account for relative frequency of use or for other fuelusing devices, such as lamps or additional stoves. This would lead to exposure misclassification, which, assuming it to be nondifferential, would most likely bias results toward the null. Thus, it would not provide a likely explanation for our findings.

In general, the type of cookfuel used by a household is related to socioeconomic status, which is commonly associated with ALRI. It is therefore possible that there may be residual confounding by unmeasured factors related to socioeconomic status. Our analysis took into account a range of socioeconomic factors, including parental occupation and education, land ownership, house size and construction materials, and house ownership.

Selection bias arising from study participa tion must be considered because not all fami lies invited agreed to participate. For this to be a factor, the ratio of willingness to partici pate by kerosene cookstove-using case fami lies to willingness to participate by kerosene cookstove-using control families would need to have been greater than the correspond ing ratio for electric cookstove-using case and control families. We have no data that would allow us to judge whether this could have been the case. Because there was a low refusal rate of both case and control families (8-9%), however, this seems unlikely to have been a significant source of bias. Notably, we excluded cases of ALRI who had received antibiotics within the 48 hr before assess ment, which would have resulted in exclusion of more severe cases. The consequence for the described associations between fuel type and ALRI is unclear.

For the PAF calculation we have assumed that the proportion of controls exposed would estimate the proportion exposed in the popu lation < 3 years of age. The baseline census and the subsequent monthly active surveil lance in all the neighborhoods of Bhaktapur municipality, including the free treatment offered by our study clinic, made the proj ect well known in the area and encouraged families to use our services. Due to delay in registration after birth, we may have failed to include in our surveillance some of the youngest children, as well as some children from migrant families, who come to the area in search of work and have limited social net works in the local community. These groups would, however, comprise a small proportion of the population < 3 years old, and any bias would be nondifferential with regard to case and control status.

Conclusions

Our investigation supports other findings that use of biomass as a household fuel is a risk fac tor for ALRI, and provides new evidence that the types of kerosene and kerosene stoves used in Nepal for cooking may also be a risk factor for ALRI in young children. It also suggests that keeping children out of the kitchen dur ing cooking is useful in reducing risk. These results add to the small body of evidence that kerosene, sometimes viewed as a "modern" or "clean" fuel, may be much less benign than previously assumed. The results of this study concerning possible health impacts of kerosene need to be confirmed in other settings. More generally, it is important that investigators studying health effects of household fuel use consider kerosene as a distinct fuel category, deserving specific investigation, rather than combining it with other fuels in the refer ence "clean" fuel category, as has often been done in the past. If the health implications of household kerosene use are confirmed, it would call into question the common practice in developing countries of providing kerosene subsidies to poor households.

Table 2 .
2Joint distribution of primary and secondary stove types across participating households, Bhaktapur, Nepal.Table 1. Distribution of demographic and exposure variables, with ORs for ALRI, matched for age in months, using conditional logistic regression, in Bhaktapur children, 2-36 months of age. for the three types of secondary stoves.Relative to either use of an electric or LPG space heater or no use of space heating (many people in Nepal just wear more cloth ing during cold temperatures), use of wood, coal, or kerosene for space heating in winter was associated with an OR of 1.Secondary stove

Primary stove [n (%)]

Electricity
Gas
Kerosene
Biomass
Total
Electricity or no secondary stove
62 (31.6)
222 (85.1)
207 (93.7)
194 (81.2)
685 (74.7)
Gas
21 (10.7)
5 (1.9)
1 (0.5)
8 (3.4)
35 (3.8)
Kerosene
44 (22.5)
27 (10.3)
1 (0.5)
25 (10.5)
97 (10.6)
Biomass
69 (35.2)
6 (2.3)
11 (5.0)
12 (5.0)
98 (10.7)
Undefined
0 (0)
1 (0.4)
1 (0.5)
0 (0)
2 (0.2)
Total
196 (100)
261 (100)
221 (100)
239 (100)
917 (100)

Table 3 .
3Exposure-related variables in final conditional multivariate logistic regression model for ALRI, in Bhaktapur children, 2-35 months of age.Variable
OR a (95% CI)
Primary stove fuel
Electricity
1.00
Gas
1.71 (1.08, 2.72)
Kerosene
2.33 (1.40, 3.86)
Biomass
2.13 (1.34, 3.41)
Secondary stove fuel
Electricity or no secondary stove
1.00
Gas
1.52 (0.72, 3.22)
Kerosene
1.50 (0.93, 2.43)
Biomass
1.67 (0.99, 2.84)
Child in kitchen during cooking
Never
1.00
Sometimes
1.30 (0.85, 1.99)
All the time
1.60 (1.08, 2.35)
Space heating in winter
Electric, LPG, or nothing
1.00
Wood, kerosene or coal
1.45 (0.97, 2.14)
Usual kitchen ventilation b
Both doors and windows open
1.00
Either doors or windows open
1.42 (0.99, 2.05)

a Model includes the variables in the table, as well as
mother's education, mother's occupation, family mem-
bers smoke indoors, and single-family dwelling or shar-
ing a house. b Too few participants with neither doors nor
windows open for inclusion in model (Table 1).

Table 4 .
4Results of stratified analysis of the main stove type, by how often the child was in the kitchen during cooking.Child in kitchen during cooking
n

OR (95% CI)

Gas
Kerosene
Biomass
Never
191
1.61 (0.44, 5.91)
0.35 (0.04, 2.66)
1.72 (0.54, 5.47)
Sometimes
189
3.62 (1.07, 12.27)
9.12 (1.35, 61.5)
2.66 (0.90, 7.86)
Always
511
1.97 (1.05, 3.72)
2.99 (1.56, 5.71)
2.17 (1.06, 4.44)

The authors declare they have no actual or potential competing financial interests.
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molecules Molecular Docking and Fluorescence Characterization of Benzothieno[3,2-d]pyrimidin-4-one Sulphonamide Thio-Derivatives, a Novel Class of Selective Cyclooxygenase-2 Inhibitors
2014

Mariarita Barone e-mails:firstname.lastname@example.com.
Department of Pharmaceuticals Sciences
University of Catania
V.le A. Doria 695125CataniaItaly

Giovanna Pannuzzo email@example.com
Department of Bio-medical Sciences
Section of Physiology
University of Catania
V.le A. Doria 695125CataniaItaly

Andrea Santagati email@example.com.
Department of Pharmaceuticals Sciences
University of Catania
V.le A. Doria 695125CataniaItaly

Alfio Catalfo
Department of Chemical Science, Section of Photochemistry
University of Catania
V.le A. Doria 695125CataniaItaly

Guido De Guidi
Department of Chemical Science, Section of Photochemistry
University of Catania
V.le A. Doria 695125CataniaItaly

Venera Cardile
Department of Bio-medical Sciences
Section of Physiology
University of Catania
V.le A. Doria 695125CataniaItaly

molecules Molecular Docking and Fluorescence Characterization of Benzothieno[3,2-d]pyrimidin-4-one Sulphonamide Thio-Derivatives, a Novel Class of Selective Cyclooxygenase-2 Inhibitors

Molecules
19201410.3390/molecules19056106Received: 15 January 2014; in revised form: 2 May 2014 / Accepted: 9 May 2014 /E-Mails: email@example.com (A.C.); email@example.com (G.D.G.) * Author to whom correspondence should be addressed; E-Mail: firstname.lastname@example.com; 6107anti-inflammatoryantipyrinecancer detectionCOX-2fluorescence
The aims of this study were: (i) to explore the structure-activity relationship of some new anti-inflammatory benzothieno[3,2-d]pyrimidin-4-one sulphonamide thio-derivatives 1-11; and (ii) to evaluate the possibility of using the most active compounds as fluorescent probes to determine tumours or their progression. Therefore, to know the precise mechanism by which these compounds interact with cyclooxygenase (COX)-2 enzyme, a molecular docking study was carried out; to assess spectroscopic characteristics, their absorption and emission properties were determined. The results demonstrated that some derivatives of benzothieno[3,2-d] pyrimidine exhibit interesting anti-inflammatory properties related to interactions with active sites of COX-2 and are fluorescent. The antipyrine-bearing compound 4 displayed high COX-2 affinity (ΔG = −9.4) and good fluorescent properties (Φ fl = 0.032). Thus, some members of this new class of anti-inflammatory may be promising for fluorescence imaging of cancer cells that express the COX-2 enzyme. Further in vitro and in vivo studies are needed to confirm this hypothesis.

Introduction

Over the last few years, we have focused our research in the synthesis of condensed heterocyclic derivatives, with the goal of developing efficient molecules with interesting pharmacological properties [1]. In a recent work, we described a new alternative synthetic method to produce new benzothieno [3,2-d]pyrimidin-4-one sulphonamide thio-derivatives 1-11 with anti-inflammatory properties (Figure 1), which is economically and environmentally very advantageous and characterized by the simplicity of the procedures, reduction of isolation and purification steps, time, costs, and waste production [2]. The anti-inflammatory activity of these derivatives was evaluated in vitro on a human keratinocyte NCTC 2544 cell line exposed to interferon (IFN)-γ and histamine, as well as on a monocytemacrophage J774 cell line stimulated with bacterial lipopolysaccharide (LPS). These are two cell models particularly useful for reproducing the mechanisms involved in inflammation. To prove the biological efficacy of the new compounds, the expression of some mediators involved in the inflammation, such as cyclooxygenase (COX)-2, inducible nitric oxide synthase (iNOS), immuno-modulatory membrane molecules such as intercellular adhesion molecule-1 (ICAM-1), and the release of prostaglandins (PG)E 2 and interleukin-8 (IL-8), were determined. The biological assays showed that, among the derivatives 1-11, only the following compounds act as inhibitors of COX-2, iNOS and ICAM-1 expression (Table 1): [2-[(1,3-dimethyl-2,4-dioxo-1,2,3,4-tetrahydropyrimidin-5-yl)thio]-4-oxo [1]benzothieno [3,2-d]pyrimidin-3(4H)yl]methanesulfonamide (1);  N- [2-[(1,5-dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)thio]-4oxo [1]benzothieno [3,2-d]pyrimidin-3(4H)yl]methanesulfonamide (2);  N- [2-[(2,4-nitrophenyl)thio]-4-oxo [1]benzothieno [3,2-d]pyrimidin-3(4H)yl]methanesulfonamide (4);  N- [2-(cyclohexylthio)-4-oxo [1]benzothieno [3,2-d]pyrimidin-3(4H)yl]methanesulfonamide (8);  N- [2-[(2,4-difluorophenyl)thio]-4-oxo [1]benzothieno [3,2-d]pyrimidin-(4H)yl]methanesulfonamide (9);  2-({3-[(methylsulfonyl)amino]-4-oxo-3,4-dihydro [1]benzothieno [3,2-d]pyrimidin-2-yl}thio)benzoic acid (10).
 N-
At the same time, these compounds suppress the production of PGE 2 and IL-8 in human keratinocytes NCTC 2544 and monocyte-macrophages J774 [2]. Therefore, the efficacy of benzo-thieno [3,2-d] pyrimidine derivatives in inhibiting COX-2 activity in inflamed cells indicates that this novel compound class may serve as potential therapeutic agents in inflammatory and proliferative disorders.  7.0 ± 0.2 6.8 ± 0.5 7.3 ± 0.3 6.9 ± 0.9 2 7.0 ± 0.9 6.7 ± 0.3 6.5 ± 0.5 6.9 ± 0.5 4

Inflammation and carcinogenesis are interrelated phenomena [3]. The enzymes that mediate the constitutive synthesis of nitric oxide (NO) and PG from arginine and arachidonate, respectively, have relatively little influence on inflammation or on carcinogenesis [4]. In contrast, iNOS and COX-2 play critical roles in the response of tissues to injury or infectious agents [5]. These inducible enzymes are essential components of the inflammatory response, the ultimate repair of injury, and carcinogenesis [6,7]. Although physiological activity of iNOS and COX-2 may provide a definite benefit to the organism, aberrant or excessive expression of iNOS and/or COX-2 has been implicated in the pathogenesis of many disease processes, as septic shock, cardiomyopathy, acute and chronic neurodegenerative disease, rheumatoid arthritis, and carcinogenesis [8][9][10]. Clinical data suggest that over-expression of the COX-2 isozyme is associated with a diverse variety of human cancers that encompass gastric, breast, lung, colon, oesophageal, prostate, and hepatocellular carcinomas [11,12]. COX-2 enzymes are found at high levels in inflammatory lesions and tumours, whereas mainly absent in normal cells. The COX-2 signalling pathway is important in cancer because when it is activated, it can stimulate many key steps in cancer development, including cell division, inhibition of cell death, angiogenesis, and metastasis [13]. Recently, some authors reported that chronic inflammation drives the progression of colorectal cancer (CRC) and that COX-2 is one of the most important inflammatory genes involved in solid tumor metastasis. They demonstrated that store-operated Ca 2+ entry is involved in the activation of transcription factors (CREB/NFAT) that are responsible for delivering EGF-mediated signals to evoke inflammatory cascades related to colorectal cancer tumorigenesis [14,15]. The alliance between COX-2 over-expression and cancer makes the COX-2 isozyme an attractive molecular target. Immense efforts were devoted to developing new molecules that are direct inhibitors of the enzymatic activity of COX-2. In a search for phytochemicals with anti-inflammatory activity, isodesacetyluvaricin, from the Formosan tropical fruit tree Annona glabra, exhibited potent anti-COX-2 activity, demonstrating to serve as a lead compound for targeting inflammatory diseases as well as angiogenesis and cancer metastasis [16]. The same authors demonstrated that 11-episinulariolide acetate from Simularia flexibilis shows functional inhibitory activity on cytoplasmic calcium concentration COX-2 and IL-8 gene expressions [17].

Several non-steroidal anti-inflammatory drugs (NSAIDs) were found to play an important role in cancer prevention providing evidence that COX-2 inhibitors may decrease the risk of developing cancer. Initially, COX-2-selective inhibitors were developed as anti-inflammatory agents with fewer gastrointestinal side effects compared to non-selective non-steroidal anti-inflammatory drugs (NSAIDs) [18]. These selective COX-2 inhibitors proved to be effective in inhibiting tumour growth in animal studies, and exhibited antiangiogenic activity in vitro that may contribute to their antineoplastic effects in vivo [19]. The antiangiogenic effects of COX-2-selective inhibitors and their ability to reduce haematogenous metastasis of COX-2-expressing tumours raised the possibility that they may be useful for treatment as well as for prevention of some cancers [19,20].

Recently, it was reported that the over-expression of COX-2 in cancer cells, relative to normal adjacent tissue where COX-2 is not expressed, constitutes a logical molecular diagnostic design strategy to discover non-invasive diagnostic agents to detect tumours, and the subsequent monitoring of disease progression and/or treatment efficacy [20,21]. A COX-2 inhibitory agent, fluorescent or coupled to a fluorescence tag, can serve as a potential COX-2 imaging emitting probe. Since the derivatives 1, 2, 4, 8, 9 and 10 were shown to possess good anti-inflammatory activity, the aims of this study were to know the precise mechanism by which these new anti-inflammatory benzothieno[3,2-d]pyrimidin-4-one sulphonamide thio-derivatives interact with the COX-2 enzyme and to explore their structure-activity relationships through a molecular docking study. In addition, the possibility of using these derivatives to determine tumours or their progression was evaluated by spectroscopic characterization and determination of their absorption and emission properties.

Results and Discussion

Docking Study

In this study, the interaction of COX-2 active site residues with benzothieno[3,2-d] pyrimidine derivatives 1-11 ( Figure 1) was described. Considering their good biological proprieties in the reduction of some anti-inflammatory parameters obtained on two cell models, an investigation of new derivatives/COX-2 interactions using structure-activity analysis was carried out. Molecular docking was performed on derivatives 1-11 of benzothieno [3,2-d] pyrimidine, that differed for the presence of a functional group; aryl or heterocyclic group. Nimesulide and naproxen were used as reference compounds.

We chose nimesulide (4-nitro-2-phenoxymethanesulphonanilide) as a prototype of selective COX-2 inhibitors. Nimesulide contains a polar nitro group that may hydrogen bond with Ser-530 and/or Tyr-385, in addition to a sulfone that may bind in the side pocket. Members of the methanesulfonanilide class of COX-2 inhibitors generally exhibit preferential COX-2 selectivity. These compounds are characterized as derivatives of alkylsulfonanilide. Nimesulide was the first member of this class to be discovered.

We chose naproxen [(S)-6-methoxy-α-methyl-2-naphthaleneacetic acid] for its high anti-inflammatory potency, confirmed by ΔG of our docking studies (−9.0 kcal/mol). Naproxen is a powerful non-selective non-steroidal anti-inflammatory drug that inhibits both COX-1 and COX-2 with comparable IC50 values [22]. Strong electron density was observed for a single orientation of naproxen binding within the COX-2 active site, making no contacts in the COX-2 side pocket or lobby region. As predicted by the mutagenesis data, the binding mode of naproxen is similar to that of other members of the 2-arylpropionic acid family of NSAIDs with the carboxylate group of naproxen participating in hydrogen-bonding interactions with Arg-120 and Tyr-355 at the base of the active site.

The structure of COX-2 consists of three distinct domains: an N-terminal epidermal growth factor (EGF) domain, followed by a membrane-binding motif and a C-terminal catalytic domain. This latter contains the cyclooxygenase and peroxidase active sites, with 87% identity and strict sequence conservation with respect to the cyclooxygenase active site. The structure of human COX-2 is expected to be very similar to the murine enzyme (mCOX-2) [23,24].

Our docking results indicated that the derivatives 1, 2, 4, 8 and 10, independently of their functional group, are able to bind the mCOX-2 active site while the compounds 3, 5, 6 and 7 have unfavourable interactions with mCOX-2.

The active site of mCOX-2 is a long, narrow hydrophobic channel extending from the membrane-binding region to the protein core. It is divided into three important region, the first is a hydrophobic pocket containing Tyr-385, Trp-387, Phe-518, Ala-201, Tyr-248 and Leu-352; the second region being entrance of the active site lined by the hydrophilic residues Arg-120, Glu-524, Tyr-355, and the third is a side pocket lined by His-90, Arg-513 and Val-523 [24].

In this study, ligand-protein docking methods were applied to predict the optimal positions, orientations and energies for interactions of the derivatives 1-11 with mCOX-2. The results suggested that the derivatives 1, 2, 4, 8, 9 and 10 have high binding energies ( Table 2); unlike the derivatives 3, 5, 6 and 7 have low binding energies. It is possible to observe that the derivative 4 containing the antipyrine group showed the best binding energy: ΔG = −9.4 kcal/mol. Thus, there is a good correlation between the results of binding energies of the benzothieno[3,2-d] pyrimidine derivatives to mCOX-2 and the biological assays published in our previous article [2]. The interactions of compounds 1, 2, 4, 8, 9 and 10 with the mCOX-2 active site are shown in Figures 2-7. Derivatives 1, 2, 6, 8 and 10 exhibited interaction with the following enzyme amino acid residues: Lys-83, Pro-84, Val-89, Leu-93, Ile-112, Tyr-115, Val-116, Ser-119, Arg-120, Tyr-122, Tyr-355, and Ser-471. The compounds 1, 2, 6, 8 and 10 were able to interact through a strong hydrogen bond with the amino acid residue Arg-120. Compounds 9 and 10 exhibit hydrogen bond with Tyr-355, whereas compound 1 and 2 with Tyr-112. In addition, the same compounds (1, 2, 4, 8,  9, and 10) showed strong hydrophobic interactions of van der Waals with different amino acid residues in the mCOX-2 active site. By "strong" we mean hydrogen bonds that are able to control crystal and supramolecular structure effectively. This certainly By "weak" we mean hydrogen bonds whose influence on crystal structure and packing is variable.      Thus, the methanesulphonamide group present in all compounds was directed towards the channel where the active site is located. It forms a hydrogen bond with the hydroxyl group of Tyr-355 or Tyr-112 and amino of Arg-120. These results were comparable to interaction obtained by nimesulide and naproxen (Table 2). Kaur et al. demonstrated that, within the investigated group, 1,4 diaryl-substituted triazoles, 4-{2-[4-(4-chlorophenyl)-[1,2,3]triazol-1-yl]-ethyl}-benzenesulfonamide displayed highest COX-2 inhibitory potency and selectivity. Results of molecular docking studies revealed that COX-2 SO 2 NH 2 pharmacophore in this compound is positioned in the secondary pocket of the COX-2 active site; with the nitrogen atom of the SO 2 NH 2 group hydrogen bonded to Gln-192, and one of the oxygen atoms of SO 2 NH 2 group forming a hydrogen bond to His-90 [25].

Moreover, the computational simulation studies showed that the compound 4 is the best candidate to inhibit COX-2, because its binding energy results the highest between all derivatives. The results demonstrated that compound 4 can interact with the following amino acid residues: His-207, Phe-210, Thr-212, His-214, Leu-294, Leu-298, Asn-382, Tyr-385, His-386, His-388 ( Figure 4). The optimized complex of compound 4 and COX-2 showed three strong hydrogen bonds with the protons of His-386, Asn-382 and Thr-212.

The docking experiments performed on thiophene derivatives and some non-steroidal anti-inflammatory drugs (NSAIDs) indicated that His-386, His-388, His-214, His-207 amino acids are important residues that stabilize the conformations of compounds interacting with the binding pocket of COX-2 [26].

Finally, docking results revealed that the perpendicular orientation of thiophene and/or phenyl rings to the plane of imidazole rings of His residues (His-386, His-388, and His-207) was significant for locking the geometries of thiophene compounds in the COX-2 [26]. Our docking results confirmed that the amino acid residues His-386, His-388, His-214 and His-20 are very important for selective inhibition of COX-2. In conclusion, the data obtained by docking studies resulted perfectly in correlation with the results of biological assays previously published [2].

Spectroscopic Characterization

The absorption and emission properties of compounds are listed in Table 3. The excitation and emission spectra were determined by solution of 1, 2, 4, 8, 9, and 10 in DMSO. Almost all compounds displayed peaks with absorption maxima at two different wavelengths (~340 and ~350 nm), and for all the compounds, the corresponding λ em maxima were centred in the range 415-450 nm. In a study on yellow pigments, fomitellanols A (1a) and B (2a), and drimane-type sesquiterpenoid ethers of isocitric acid, cryptoporic acids P (3) and Q (4), isolated from the fruiting bodies of Fomitella fraxinea (Polyporaceae) and analysed their biological activity against COX-1, COX-2, and 5-LO, the UV spectrum of 5-hydroxy-7-hydroxymethyl-1-isopropoxy-9b-methyl-9a,9b-dihydro-H-2-oxacyclopenta[d]acenaphthylen-9-one (1a) showed absorption bands at 224, 291, 347, and 385 nm, indicating the presence of a conjugated system [27]. For a general example, in Figures 8 and 9 the absorption and emission spectra of 10 and 4 are reported. In Figure 10 the emission spectra of the investigated compounds were shown. Excitation was fixed in the tail of the absorption spectrum to avoid re-absorption phenomena. All spectra were normalized for an absorbance in the exciting wavelength of 0.074. All the derivatives showed an important difference between λ exc and λ em (Stokes shift). Quantum yields (Φ) were determined to probe the environment affecting the sensitivity of the compounds (high quantum yield in nonpolar solvents or when bound to hydrophobic sites). Indeed, all tested compounds exhibited good fluorescence in organic solvent. Molar extinction coefficients (ε) were carried out for all compounds (in DMSO), resulting in similar values (about 10.000 L mol −1 cm −1 ); the highest value was displayed by the compound 1, also if this latter was accompanied by a lower fluorescence intensity.

Fluorescence Microscopy

Preliminary fluorescence microscopy experiments were carried out in vitro. Since compounds 4 and 10 displayed the best COX-2 affinity and a suitable fluorescence, they were tested on some cancer cell lines. The results obtained in human epithelial colorectal adenocarcinoma HCA-7 cultures were promising ( Figure 11). However, further studies on new cancer cell lines are needed to verify the possibility to use the derivative 4 or 10 as biomarkers to detect cancer or its progression.

Experimental

General Information

All commercial solvents and chemicals purchased from Aldrich, Fluka, Merck, Lancaster and Carlo-Erba were of analytic grade and used without further purification. NMR spectra ( 1 H-NMR were recorded at 500 MHz, 13 C-NMR were recorded at 125 MHz) on a Varian Instruments; chemical shifts (δ) are reported in ppm from tetramethylsilane as an internal standard; coupling constants (J) are in Hertz (Hz). IR spectra were recorded on a Perkin Elmer 1600 Series FT-IR in potassium bromide disks. Microanalyses for C, H, N and S were obtained from an EA 1108 elemental analyzer Fisons Carlo-Erba instrument. Analyses indicated by the symbols of the elements were within ±0.4% of the theoretical values. Melting points were determined in open capillary tubes on a SMP1 apparatus (Stuart Scientific Staffordshire) and are uncorrected. The purity of substances was checked by thin layer chromatography on Merck silica gel 60 F-254 plates. Mass spectra were recorded by Perkin Elmer Turbo Mass Clarus 560 Mass Spectrometer, with a 70 eV working ionization energy, source temperature 250 °C, trap current 90 μA. Synthesis and characterization of investigated compounds were reported previously [2].

Computational Method

It is known that the structure of human COX-2 is very similar to the murine enzyme [24]. To perform the protein-ligand modelling, the X-ray crystallographic 3D structure of murine COX-2 (mCOX-2) complex with naproxen was downloaded from the online Protein Data Bank (PDB ID: 3q7d) [28]. The inhibitor was subsequently removed and the structure subjected to energy minimization. The ligands were then built as pdb files by means of the server PRODRG2 [28].

The energies of the protein and the inhibitors were minimized by steepest descent algorithm. Simulations were performed by using the GROMACS simulation package (4.5.5) and GROMOS force-field parameter set 53A6. Force field was used to describe atomistically receptor, ligands, and ions, respectively [29,30].

Prior to dock inhibitors into target, naproxen was used as an inhibitor to mCOX-2 (PDB: 3q7d) to ensure whether the method was valid. The amino acid residues that bind compounds produced by the re-docking process were then compared with amino acid residues that bind crystal molecules; a root-mean-square deviation (RMSD) that was less than or equal to 2.0 Å was defined as reasonable criteria [31]. The value of RMSD for mCOX-2 obtained by us was 0.910 Å. This indicated that the parameter set for docking was suitable of reproducing the X-ray structure. In addition, the re-docking result for naproxen demonstrated that ligand invades COX-2 receptor-binding pockets, and that hydrogen bonds occur between inhibitors and carboxylic group of amino acid residue of Arg-120 and Tyr-355. These results were consistent with those reported before [24,32,33].

All docking calculations were carried out using software AutoDock 4.0. It is one of the most suitable methods for performing molecular docking of ligands to their macromolecular receptors, as well as to discriminate potential inhibitors. The ligand molecule is in an arbitrary conformation, orientation, and position and this molecular docking program [34] finds favourable poses in a protein-binding site using Lamarckian genetic algorithms implemented therein to search for the best conformers. The free energy of binding (ΔG) of mCOX-2 (prostaglandin synthase-2) complex with the inhibitors 1-11 was generated using this molecular docking program.

For mCOX-2 preparation, polar hydrogen were added, and then Kollman United Atom charges and atomic solvation parameters assigned. For ligands preparation, Gasteiger partial charges were added, non-polar hydrogen atoms merged, and rotatable bonds defined. The grid maps of docking studies were computed using the Autogrid program [31]. The grid must surround the region of interest in the macromolecule. The spacing between grid points was 1 Å for blind docking and 0.37 Å for active site, respectively. All parameters used in docking were default. A preliminary blind docking study was performed in order to discriminate the preferential binding sites of the ligand to the receptor. For the first simulation, in fact, the grid size was properly set up in order to contain the entire receptor structure up (40, 40, 40 Å along x, y and z, respectively, space between grid points of 1 Å).

For successive simulation, the pose of the ligand was selected in the active site and the grid was centered on this catalytic active region of the receptor (50, 50, 50 Å along x, y and z, respectively, space between grid points of 0.37 Å).

Absorption and Emission Spectroscopy

Absorption spectra were recorded with a HP (8452A) UV-VIS spectrophotometer, and fluorescence spectra were obtained with a Spex Fluorolog-2 (Mod F-111) spectrofluorometer. Molar extinction coefficients (ε) were determined for each final compound dissolved in DMSO, with concentration ranging from 1 to 50 μM and absorbance spectra recorded from 200 to 800 nm in standard quartz cuvettes. Epsilon values were determined by fitting the Beer's law: A = ε c d where (A) is the absorbance at the λ exc ; (c) is the molar concentration of the solution, and (d) was the optical path length (d = 1 cm). Measurements were repeated three times.

Emission spectra of derivatives 1-11 were determined in DMSO solution. In all experiments, the excitation and the emission bandpass was set at 2.5 nm and at 5 nm, respectively. The emission spectra were obtained from 388 to 700 nm, with excitation wavelength set at 368 nm. The excitation spectra of the compounds were obtained from about 250 to 450 nm, with the emission being recorded at the appropriate wavelength. Fluorescence quantum yields were calculated with respect to quinine sulphate (Fluka) in 0.5 M H 2 SO 4 as a standard (Φ = 0.546) [35]. Solutions of both the sample and the reference were prepared from original solutions diluted with the appropriate solvent so that absorbance was below 0.1 at the same excitation wavelength (368 nm). Fluorescence measurements were carried out for each solution with the same instrument parameters, and the fluorescence spectra were corrected for instrumental response before integration. The quantum yield Φ x for each sample was calculated according the following equation [36]: Φ x = Φ S (A S /A x ) (F X /F S ) (n x /n s ) 2 where Φ is the emission quantum yield, A is the absorbance at the excitation wavelength, F is the area under the corrected emission curve, n is the refractive index of the solvent for the sample (X) and the standard (S).

Fluorescence Microscopy

In order to identify intracellular fluorescence of compounds 4 and 10, fluorescent procedures were carried out using human epithelial colorectal adenocarcinoma HCA-7 cultures. HCA-7 cell line was provided by American Type culture Collection (Manassas, VA, USA) and routinely maintained in Dulbecco's Modified Eagle's Medium (DMEM, Sigma-Aldrich, Milan, Italy) supplemented with 10% fetal calf serum, 1% glutamine, 100 U/mL penicillin, and 100 μg/mL streptomycin, and incubated at 37 °C in a humidified, 95% air/5% CO 2 atmosphere. The medium was changed every 2-3 days. For experiments, 24 h before the cells were trypsinized (Trypsin-EDTA; Sigma-Aldrich), counted in a haemocytometer, and plated (2 × 10 5 /well) in a 12-well culture plate for 24 h. Hence, the medium was removed and replaced with medium without phenol red containing 100 μM of experimental compounds for 12 h. Cells were first washed with PBS and then fixed with 4% paraformaldheyde in PBS for 30 min. Digital images were acquired using a fluorescence microscope (OPTIKA, M.A.D. Apparecchiature Scientifiche, Milan, Italy) at λ exc = 325-375 nm and λ em = 440 nm.

Conclusions

Our study demonstrated that some derivatives of benzothieno [3,2-d] pyrimidine could be developed as a novel class of anti-inflammatory agents. They are synthesized by a simple, efficient and ecologically friendly method, exhibit interesting anti-inflammatory properties related to interactions with active sites of COX-2, and show good fluorescence characteristics. Thus, this new class of anti-inflammatory may be promising for fluorescence imaging of cancer cells that express the COX-2 isozyme.

Figure 1 .
1Benzo-thieno[3,2-d] pyrimidine derivatives 1-11.

includes O-H•••O=C, N-H•••O=C and O-H•••O-H.

Figure 2 .
2Binding of 1 into the active site of COX-2.

Figure 3 .
3Binding of 2 into the active site of COX-2.

Figure 4 .
4Binding of 4 into the active site of COX-2.

Figure 5 .
5Binding of 8 into the active site of COX-2.

Figure 6 .
6Binding of 9 into the active site of COX-2.

Figure 7 .
7Binding of 10 into the active site of COX-2. For derivative 1, donor/acceptor hydrogen bonds: OH (Tyr 112)-SO 2 CH 3 (1), NH (Arg 120)-CO (1). For derivative 2, donor/acceptor hydrogen bonds: OH (Tyr 112)-SO 2 CH 3 (2), NH (Arg 120)-CO of the group 4-oxo-tetrahydropyrimidine (2). For derivative 4, donor/acceptor hydrogen bonds: NH (His 386)-SO 2 CH 3 (4), NH (Asn 382)-SO 2 CH 3 (4), OH (Thr 212)-SO 2 CH 3 (4).For derivative 8, donor/acceptor hydrogen bonds: NH (Arg 120)-SO 2 CH 3(8).For derivative 9, donor/acceptor hydrogen bonds: OH (Tyr 355)-SO 2 CH 3 (9), NH (Arg 120)-SO 2 CH 3(9).For derivative 10, the presence of carboxylate group changes the nature of donor/acceptor hydrogen bonds: OH (Tyr 355)-CO (10), NH (Arg 120)-CO(10).

Figure 8 .
8Absorbance (straight line) and emission (dashed line) spectra of 10.

Figure 9 .
9Absorbance (straight line) and emission (dashed line) of 4.

Figure 10 .
10Emission spectra of 1, 2, 4, 8-10.

Figure 11 .
11Fluorescent images of human epithelial colorectal adenocarcinoma HCA-7 cultures untreated (A) or treated with derivative 4 (B).

Table 1 .
1iNOS and COX-2 IC 50 values (μM) of human keratinocytes NCTC 2544 and mouse monocyte-macrophages J774 treated with interferon-γ plus histamine and lipopolysaccharides, respectively.Compounds
NCTC2544
J774
iNOS
COX-2
iNOS
COX-2
1

Table 2 .
2Energy contributions for derivatives (1, 2, 4, 8, 9, 10) with high binding energies.Compound
Docking energies
(ΔG) (kcal/mol)

Number of
H-bonds

Donor/Acceptor
Hydrogen bond

H-bond distance
(Å)

Naproxen
−9.0
2
ARG-120:NH1
TYR-355:OH 1

1.863
2.165

Nimesulide
−7.3
2
ARG-120:NH1
TYR-355:OH 1

3.088
2.737

Derivative 1
−7.9
2
ARG-120:NH1
TYR-112:OH 1

3.149
2.806

Derivative 2
−8.1
2
ARG-120:NH1
TYR-112:OH 1

3.002
2.788

Derivative 4
−9.4
3

ASN-382:NH2
HIS-386:NH2
THR-212:OH1

2.867
2.945
2.692
Derivative 8
−8.9
1
ARG-120:NH1
2.882

Derivative 9
−9.1
2
TYR-355:OH
ARG-120:NH

2.875
2.876

Derivative 10
−8.2
2
ARG-120:NH
TYR-355:OH

2.970
3.120

Table 3 .
3Absorption and emission properties of investigated compounds. molar absorption coefficient, L/mol −1 /cm −1 ; λ max , absorption maximum wavelength, nm; Φ fl , fluorescence quantum yield.Derivative
ε (λ max )
ε (λ max )
Φ fl
1
10,991 (340)
9916 (354)
0.080
2
8304 (338)
7500 (352)
0.013
4
9784 (338)
8905 (352)
0.032
8
9662 (338)
8199 (350)
0.055
9
10,773 (338)
9855 (352)
0.007
10
9435 (334)
8643 (346)
0.087

ε,
© 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
AcknowledgmentsThe authors thank Martina Pannuzzo, Department of Computational Biology, University of Erlangen-Nuremberg, Erlangen, Germany, for the suggestions provided during the docking studies.Author ContributionsM. Barone, work planning and compounds synthesis; G. Pannuzzo, docking study; A. Santagati, compounds synthesis; A. Catalfo, absorption and emission spectroscopy; G. De Guidi, spectroscopic characterization; V. Cardile, work management, anti-inflammatory properties and manuscript writing.Conflicts of InterestThe authors declare no conflict of interest.
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Sample Availability: Samples of all compounds are available from the authors. Sample Availability: Samples of all compounds are available from the authors.