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Filamentous temperature-sensitive protein Z (FtsZ) is a protein encoded by the FtsZ gene that assembles into a Z-ring at the future site of the septum of bacterial cell division. Structurally, FtsZ is a homolog of eukaryotic tubulin but has low sequence similarity; this makes it possible to obtain FtsZ inhibitors without affecting the eukaryotic cell division. Computational studies were performed on a series of substituted 3-arylalkoxybenzamide derivatives reported as inhibitors of FtsZ activity in Staphylococcus aureus. Quantitative structure-activity relationship models (QSAR) models generated showed good statistical reliability, which is evident from r2ncv and r2loo values. The predictive ability of these models was determined and an acceptable predictive correlation (r2Pred) values were obtained. Finally, we performed molecular dynamics simulations in order to examine the stability of protein-ligand interactions. This facilitated us to compare free binding energies of cocrystal ligand and newly designed molecule B1. The good concordance between the docking results and comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) contour maps afforded obliging clues for the rational modification of molecules to design more potent FtsZ inhibitors. [ABSTRACT FROM AUTHOR]

Mechanistic target of rapamycin is involved in the formation of tumor microvasculature was an ideal target for computer-aided drug design. The predictive study of quantitative structure-activity relationship and molecular docking can shorten the cycle and reduce the cost of designing the higher activity mTOR inhibitors. In this article, comparative molecular field analysis and comparative molecular similarity indices analysis fields were used to analyse three-dimensional quantitative structure-activity relationship model. The model (comparative molecular similarity indices analysis with q2=0.607, r2=0.909; comparative molecular similarity indices analysis with q2=0.703, r2=0.935) has a good predictability. Three-dimensional quantitative structure-activity relationship model contour maps indicate the electrostatic, hydrophobic and hydrogen bond donor fields have crucial effects to derivatives biological activity. Molecular docking was employed to explore the conformations of 55 compounds with key amino acid residues. Finally, combining contour maps with molecular docking results, ten derivatives as potential mechanistic target of rapamycin inhibitors were designed to further verify established three-dimensional quantitative structure-activity relationship models. These data provide significant theoretical foundation for designing better activity mechanistic target of rapamycin inhibitors. [ABSTRACT FROM AUTHOR]

BACKGROUND Agrochemicals have been crucial to the production of food, and the need for the development of novel agrochemicals continues unceasing owing to the loss of existing produces via the growth of resistance and the desire for products with more propitious environmental and toxicological patterns. RESULTS The results of both CoMFA and CoMSIA models indicated that biological activity can effectively be improved through the structural optimisation and molecular design of these synthetic compounds from the aspects of steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. Data of postemergence herbicidal activity in the greenhouse explained that most new 3-(pyridin-2-yl)benzenesulfonamide derivatives ( 4c- 4 t) could control highly effectively against barnyardgrass, foxtail, vetleaf, and youth and old age (herbicidal activity ≥90%); for example, compounds 4q- 4 t exhibit excellent biological activity equivalent/superior to commercial saflufenacil/sulcotrione at the low concentration of 37.5 g a.i./ha, and in particular, the herbicidal activity of compound 4 t for four experimental plant species is found to be notably greater than saflufenacil (3.75 g a.i./ha). Meanwhile, compound 4 t also has good crop selectivity for weed control in maize. CONCLUSION The novel compounds such as 4 t have remarkable biological activity after the structural optimisation utilising the constructed 3D-QSAR models, i.e. such QSAR models have great accuracy. © 2017 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Recently, great attention has been paid to the identification and prediction of the androgen disrupting potencies of polybrominated diphenyl ethers (PBDEs). However, few existing models can discriminate active and inactive compounds, which make the quantitative prediction process including the quantitative structure-activity relationship (QSAR) technique unreliable. In this study, different grouping methods were investigated and compared for qualitative identification, including molecular docking and molecular dynamics simulations (MD). The results showed that qualitative identification based on MD, which is lab-independent, accurate and closer to the real transcriptional activation process, could separate 90.5% of active and inactive chemicals and was preferred. The 3D-QSAR models built as the quantitative simulation method showed r 2 and q 2 values of 0.513 and 0.980, respectively. Together, a novel workflow combining qualitative identification and quantitative simulations was generated with processes including activeness discrimination and activity prediction. This workflow, for analyzing the antagonism of androgen receptor (AR) of PBDEs is not only allowing researchers to reduce their intense laboratory experiments but also assisting them in inspecting and adjusting their laboratory systems and results. [ABSTRACT FROM AUTHOR]

In the present study, we have employed the ligand-based drug design technique, 3D-QSAR, through a comparative molecular field analysis (CoMFA) and a comparative molecular similarity indices analysis (CoMSIA) to determine the key factors for the plant growth promoting activity of brassinosteroids reported in literature, using the bean second-internode bioassay measured on two groups of compounds with different molar concentrations. This is the first 3D-QSAR study using the second internode elongation as biological activity. These results provide useful ideas for the design of new molecules, which could be explored in the future to identify novel vegetable growth promoters with similar or greater biological activity than natural brassinosteroids. The reliability of this study was supported by the robust statistical parameters obtained from CoMFA (Model A, r²pred = 0.751; Model B, r²pred = 0.770) and CoMSIA (Model A, r²pred = 0.946; Model B, r²pred = 0.923) analysis. [ABSTRACT FROM AUTHOR]

Rho Kinases (ROCK) has been found to regulate a wide range of fundamental cell functions such as contraction, motility, proliferation, and apoptosis. Recent experiments have defined new functions of ROCKs in cells, including centrosome positioning and cell-size regulation, which might contribute to various physiological and pathological states. In this study, we have performed pharmacophore modeling and 3D QSAR studies on a series of 36 indoles and 7-azoindoles derivatives as ROCK2 inhibitors to elucidate the structural variations with their inhibitory activities. Ligand based CoMFA and CoMSIA models were generated based on three different alignment methods such as systematic search, simulated annealing and pharmacophore. A total of 15 CoMFA models and 27 CoMSIA were generated using different alignments. One model from each alignment is selected based on the statistical values. Contour maps of the selected models were compared, analysed and reported. The 3D QSAR study revealed that electro positive group linked to the methoxy-benzene ring position of the structure will enhance the biological activity and bulkier substitutions are preferred in the methyl dihydroindole region. Also, it is found that the hydrogen bond donor substituted at the R 1 position enhances the inhibitory activity. In future, this study would give proper guidelines to further enhance the activity of novel inhibitors for ROCK2. [ABSTRACT FROM AUTHOR]

A collection of 36 thiosemicarbazone analogues possessed a broad span of tyrosinase inhibitory activities was designed and obtained. Robust and reliable CoMFA and CoMSIA models were gained to predict the structure–activity relationship and the new modifier direction. Inhibitory activities of the compounds were found to greatly depend upon molecular shape, size, and charge. The sterically bulky group at the C-4 position of the thiophene ring contributed a high capacity for biological activity. Some bulky substituents at the C1-position and C12-position, and electron-negative groups at the C3-position, helped to improve the activity of these analogues. The molecular docking results provided visual evidence for QSAR analysis and detailed information about binding mode, affinity, and the principal mechanism between the ligands and tyrosinase. Based on these, a prospective structure modification and optimization of the most potent compound, T32 , was suggested for further research. [ABSTRACT FROM AUTHOR]

Influenza endonuclease plays important role in the viral transcription and translation processes. Inhibition of endonuclease enzyme may be an interesting choice to restrict influenza infection. This current study deals with validated multi-chemometric modelling approaches namely regression-based and classification-based quantitative structure-activity relationships (QSARs), hologram QSAR, comparative molecular similarity analysis (CoMSIA), Open3DQSAR study and pharmacophore mapping to identify the structural and physicochemical requirements along with the chemico-biological interactions of pyridinones and pyranones for anti-endonuclease activity. The results suggest that the pyridinone scaffold is more preferable than the pyranone ring. The keto function at 4th position and aryl tetrazole substitution at 1st position of the parent moiety may be important for endonuclease inhibition. Hydroxyl group at 5th position of the parent ring may act as hydrogen bond acceptor feature. The steric substituent is suitable at 2nd position whereas hydrophobic substitution is found to be unfavourable at this position. Bulky hydrophobic substituents are not preferred at the 3rd position of the parent moiety. The information revealed from these integrated ligand-based modelling methods may provide useful informations for designing newer potential anti-influenza agents in future. [ABSTRACT FROM AUTHOR]

Rearranged during transfection is a transmembrane receptor tyrosine kinase. It is involved in medullary thyroid cancer and lung adenocarcinoma in humans. In this work, molecular docking and three-dimensional quantitative structure-activity relationship studies were performed on recently reported series of two-substituted phenol quinazoline derivatives as rearranged during transfection inhibitors. Docking study identified key active site residues such as Ala807, Lys758, Leu802, Leu730, Tyr806, Ala756, Val804, Asp892, and Glu775 that participate in the inhibition of rearranged during transfection. A reasonable comparative molecular field analysis ( q = 0.592, optimal number of components = 4, r = 0.921) and comparative molecular similarity indices analysis ( q = 0.580, optimal number of components = 6, r = 0.963) models were generated in three-dimensional quantitative structure-activity relationship study. Various validation techniques such as external test set validation, bootstrapping analysis, and progressive scrambling were carried out to check the predictive ability of the obtained models. The validated models resulted in acceptable statistical values and proved to be predictive and robust. comparative molecular similarity indices analysis model was selected as the final model based on the reasonable statistical values of q , r , standard error of estimate, and r . The contour maps analysis of comparative molecular similarity indices analysis model revealed the favorable regions to enhance the inhibitory activity of compounds. R and R positions were favorable for bulky substitution. Hydrophilic and negative substitutions at R position were favorable. Thus results of our study can provide insights in the designing potent and selective rearranged during transfection kinase inhibitors. [ABSTRACT FROM AUTHOR]

The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four QSAR models were successfully established by CoMSIA, CoMFA, topomer CoMFA and HQSAR approaches with respective characteristic values q = 0.567, R = 0.968, ONC = 5; q = 0.547, R = 0.980, ONC = 7; q = 0.559, R = 0.921, ONC = 7 and q = 0.527, R = 0.921, ONC = 6. The predictive ability of CoMSIA with r = 0.991 is the best one compared with the other three approaches, such as CoMFA (r = 0.787), topomer CoMFA (r = 0.819) and HQSAR (r = 0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities. [ABSTRACT FROM AUTHOR]

Protein kinase B (PKB/Akt) regulates all aspects of cell growth, differentiation, and division. PKB/Akt has recently garnered a great deal of attention as a promising molecular target for cancer therapy due to its involvement in the development of several human cancers. In this study a diverse set of 56 Akt1 inhibitors were aligned by three different methods (pharmacophore-, docking-based and rigid body alignment) for CoMFA, CoMSIA and HQSAR analysis. The best QSAR models were obtained using rigid body alignment (Distill). CoMFA and CoMSIA models were found statistically significant with leave-one-out correlation coefficient (q2) of 0.627 and 0.598, respectively, cross validated coefficient (rcv2) of 0.644 and 0.563, respectively, and conventional coefficient (r2) of 0.867 and 0.865, respectively. QSAR models were validated by a test set of 9 compounds giving satisfactory predicted correlation coefficient (rpred2) of 0.603 and 0.613 for CoMFA and CoMSIA models, respectively. Leave-one-out correlation value (q2) of 0.687, rpred2 of 0.742 and r2 of 0.868 were obtained for HQSAR analysis and found satisfactory. This study provides valuable clues to design new compounds against PKB/Akt.

Caspase-3 has become an attractive target in the treatment of many diseases such as Alzheimer, Parkinson’s, myocardial infarction and cancer. In the present study, molecular three-dimensional quantitative structure activity relationship (3D-QSAR) and docking studies were performed on a series of caspase-3 activators. Comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and step-wise k-nearest neighboring molecular field analysis [(SW) kNN MFA] were performed to gain insight into the key structural factors affecting the activity. The results of 3D-QSAR are reliable and significant having high predictive (q2) ability showing good correlation between predicted and observed activity. The lower value of standard error of estimation shows that most of the observed values cluster fairly close to the regression line. Molecular docking was performed with the GOLD docking program used to explore the binding mode between the ligands and the receptor.

Acetyl-CoA carboxylase (ACC) is a crucial metabolic enzyme, which plays a vital role in fatty acid metabolism and obesity induced type 2 diabetes. Herein, we have performed 3D-QSAR and molecular docking analysis on a novel series of (4-piperidinyl)-piperazines to design potent ACC inhibitors. This study correlates the ACC inhibitory activities of 68 (4-piperidinyl)-piperazine derivatives with several stereo-chemical parameters representing steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. The CoMFA and CoMSIA models exhibited excellent rncv2 values of 0.974 and 0.985, and rcv2 values of 0.671 and 0.693, respectively. CoMFA predicted rpred2 of 0.910 and CoMSIA predicted rpred2 of 0.963 showed that the predicted values were in good agreement with experimental values. Glide5.5 program was used to explore the binding mode of inhibitors inside the active site of ACC. We have accordingly designed novel ACC inhibitors by utilising the LeapFrog and predicted with excellent inhibitory activity in the developed models.

HER-2 and EGFR are biological targets related to the development of cancer and the discovery and/or development of a dual inhibitor could be a good strategy to design an effective drug candidate. In this study, analyses of the chemical properties of a group of substances having affinity for both HER-2 and EGFR were carried out with the aim of understanding the main factors involved in the interaction between these inhibitors and the biological targets. Comparative analysis of molecular interaction fields (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques were applied on 63 compounds. From CoMFA analyses, we found for both HER-2 (r2 calibration = 0.98 and q2cv = 0.83) and EGFR (r2 calibration = 0.98 and q2cv = 0.73) good predictive models. Good models for CoMSIA technique have also been found for HER-2 (r2 calibration = 0.92 and q2cv = 0.74) and EGFR (r2 calibration = 0.97 and q2cv = 0.72). The constructed models could indicate some important characteristics for the inhibition of the biological targets. New compounds were proposed as candidates to inhibit both proteins. Therefore, this study may guide future projects for the development of new drug candidates for the treatment of breast cancer.

To explore the relationship between the structures of substituted pyrrolidine derivatives and their inhibition of dipeptidyl peptidase IV inhibitors. The QSAR, including CoMFA, CoMSIA and HQSAR, were applied to identify the key structures impacting their inhibitory potencies. The CoMFA, CoMSIA and HQSAR with cross-validated correlation coefficient (q) value of 0.727, 0.870 and 0.939 and r value of 0.973, 0.981 and 0.949. Based on the structure-activity relationship revealed by the present study, we have designed a set of novel dipeptidyl peptidase IV inhibitors that showed excellent potencies in the developed models. Thus, our results allowed us to design new derivatives with desired activities. [ABSTRACT FROM AUTHOR]

3D-QSAR (comparative molecular field analysis (CoMFA)) and comparative molecular similarity indices analysis (CoMSIA) were performed on novel 2,5 disubstituted 1,3,4-oxadiazoles analogues as anti-fungal agents. The CoMFA and CoMSIA models using 13 compounds in the training set gives Q 2 values of 0.52 and 0.51 respectively, while R 2 values of 0.92. The adapted alignment method with the suitable parameters resulted in reliable models. The contour maps produced by the CoMFA and CoMSIA models were employed to determine a three-dimensional quantitative structure–activity relationship. Based on this study a set of new molecules with high predicted activities were designed. Surflex-docking confirmed the stability of predicted molecules in the receptor. [ABSTRACT FROM AUTHOR]

A series of nineteen DHFR inhibitors was studied based on the combination of two computational techniques namely, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking. The comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were developed using 19 molecules having p IC 50 ranging from 9.244 to 5.839. The best CoMFA and CoMSIA models show conventional determination coefficients R 2 of 0.96 and 0.93 as well as the Leave One Out cross-validation determination coefficients Q 2 of 0.64 and 0.72, respectively. The predictive ability of those models was evaluated by the external validation using a test set of five compounds with predicted determination coefficients R 2 test of 0.92 and 0.94, respectively. The binding mode between this kind of compounds and the DHFR enzyme in addition to the key amino acid residues were explored by molecular docking simulation. Contour maps and molecular docking identified that the R 1 and R 2 natures at the pyrazole moiety are the important features for the optimization of the binding affinity to the DHFR receptor. According to the good concordance between the CoMFA/CoMSIA contour maps and docking results, the obtained information was explored to design novel molecules. [ABSTRACT FROM AUTHOR]

We recently reported a series of 39 weakly basic N -arylsulfonylindoles as novel 5-HT 6 antagonists. Eight of the compounds exhibited moderate to high binding affinities, with 2-(4-(2-Methoxyphenyl)piperazin-1-yl)-1-(1-tosyl-1 H -indol-3-yl)ethanol 16 showing the highest binding affinity (p K i = 7.87). Given these encouraging results and as a continuation of our research, we performed an extensive step-by-step search for the best 3D-QSAR model that allows us to rationally propose novel molecules with improved 5-HT 6 affinity based on our previously reported series. A comparative molecular similarity indices analysis (CoMSIA) model built on a docking-based alignment was developed, wherein steric, electrostatic, hydrophobic and hydrogen bond properties are correlated with biological activity. The model was validated internally and externally (q 2 = 0.721; r 2 pred = 0.938), and identified the sulfonyl and hydroxyl groups and the piperazine ring among the main regions of the molecules that can be modified to create new 5-HT 6 antagonists. [ABSTRACT FROM AUTHOR]

The inhibition of β-secretase (BACE1) is currently the main pharmacological strategy available for Alzheimer’s disease (AD). 2D QSAR and 3D QSAR analysis on some cyclic sulfone hydroxyethylamines inhibitors against β-secretase (IC 50 : 0.002–2.75 μM) were carried out using hologram QSAR (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) methods. The best model based on the training set was generated with a HQSAR q 2 value of 0.693 and r 2 value of 0.981; a CoMFA q 2 value of 0.534 and r 2 value of 0.913; and a CoMSIA q 2 value of 0.512 and r 2 value of 0.973. In order to gain further understand of the vital interactions between cyclic sulfone hydroxyethylamines and the protease, the analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the BACE1. The final QSAR models could be helpful in the design and development of novel active BACE1 inhibitors. [ABSTRACT FROM AUTHOR]

The preceding years have brought an exponential increase in our understanding of the endocannabinoid system (ECS), including the knowledge of CB1 and CB2 cannabinoid receptors, endocannabinoids, and the enzymes that synthesize and degrade endocannabinoids. Among these ECS components CB2 receptors have been the subject of considerable attention, primarily due to their promising therapeutic potential to treat numerous pathologies while avoiding the adverse psychotropic effects that can accompany CB1 receptor–based therapies. Recently, our research group has reported a new series of non-cytotoxic benzo[ d ]imidazoles and benzo[ b ]thiophenes displaying high CB2/CB1 selectivity index. In order to investigate the structural requirements for CB2 ligands and to derive a predictive model that can be used for the design of novel selective CB2 ligands, a three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed on the above mentioned chemical series employing comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques. The CoMFA and CoMSIA models displayed high external predictability (r pred 2 0.919 and 0.908) and good statistical robustness. Valuable information regarding the steric, electrostatic and hydrophobic properties of the molecules was obtained, and several modifications around both heterocycles were evaluated with the aim to generate new promising series of benzo[ d ]imidazoles and benzo[ b ]thiophenes derivatives displaying high CB2 selectivity and low toxicity. [ABSTRACT FROM AUTHOR]

DPP IV is an important biological target for treatment of diabetes. The CoMFA, CoMSIA and HQSAR models have been developed on thirty two aminomethyl piperidones derivatives. The data set consisting of twenty one training set compounds and eleven test set compounds that showed good statistical significance with internal cross validation (q2) 0.849, 0.790 and 0.901, non-cross validation (r2) 0.863, 0.793 and 0.903 and predicted (pred. r2) 0.845, 0.822 and 0.901 for CoMFA, CoMSIA and HQSAR, respectively for anti-diabetic activity. The docking study explored with active site of DPP IV, in particular, the contribution of the -NH, 2,5 di-F (Ar) with Asn 151, Asn 169 and Asn 170 of the compound 22, respectively, which is important for the bioactive conformation for DPP IV inhibition. The QSAR models, contour maps, and docking binding affinity obtained could be successfully utilized as a guiding tool for design and discovery of novel derivatives. [ABSTRACT FROM AUTHOR]

Background: Bruton tyrosine kinase (Btk) plays an important role in B-cell development, differentiation, and signaling. It is also found be in involved in male immunodeficiency disease such as X-linked agammaglobulinemia (XLA). Btk is considered as a potential therapeutic target for treating autoimmune diseases and hematological malignancies. Results: In this work, a combined molecular modeling study was performed on a series of thieno [3,2-c] pyridine-4- amine derivatives as Btk inhibitors. Receptor-guided COMFA (q2 = 0.574, NOC= 3, r2 = 0.924) and COMSIA (q2 = 0.646, NOC = 6, r2 = 0.971) models were generated based on the docked conformation of the most active compound 26. All the developed models were tested for robustness using various validation techniques. Furthermore, a 5-ns molecular dynamics (MD) simulation and binding free energy calculations were carried out to determine the binding modes of the inhibitors and to identify crucial interacting residues. The rationality and stability of molecular docking and 3D-QSAR results were validated by MD simulation. The binding free energies calculated by the MM/PBSA method showed the importance of the van der Waals interaction. Conclusions: A good correlation between the MD results, docking studies, and the contour map analysis were observed. The study has identified the key amino acid residues in Btk binding pocket. The results from this study can provide some insights into the development of potent, novel Btk inhibitors. [ABSTRACT FROM AUTHOR]

The β3 adrenergic receptor is raising as an important drug target for the treatment of pathologies such as diabetes, obesity, depression, and cardiac diseases among others. Several attempts to obtain selective and high affinity ligands have been made. Currently, Mirabegron is the only available drug on the market that targets this receptor approved for the treatment of overactive bladder. However, the FDA (Food and Drug Administration) in USA and the MHRA (Medicines and Healthcare products Regulatory Agency) in UK have made reports of potentially life-threatening side effects associated with the administration of Mirabegron, casting doubts on the continuity of this compound. Therefore, it is of utmost importance to gather information for the rational design and synthesis of new β3 adrenergic ligands. Herein, we present the first combined 2D-QSAR (two-dimensional Quantitative Structure-Activity Relationship) and 3D-QSAR/CoMSIA (three-dimensional Quantitative Structure-Activity Relationship/Comparative Molecular Similarity Index Analysis) study on a series of potent β3 adrenergic agonists of indole-alkylamine structure. We found a series of changes that can be made in the steric, hydrogen-bond donor and acceptor, lipophilicity and molar refractivity properties of the compounds to generate new promising molecules. Finally, based on our analysis, a summary and a regiospecific description of the requirements for improving β3 adrenergic activity is given. [ABSTRACT FROM AUTHOR]

In order to well understand the chemical-biological interactions governing their activities toward HIV protease activity, QSAR models of 34 cyclic-urea derivatives with inhibitory HIV were developed. The quantitative structure activity relationship (QSAR) model was built by using comparative molecular similarity indices analysis (CoMSIA) technique. And the best CoMSIA model has r cv 2 , r ncv 2 values of 0.586 and 0.931 for cross-validated and non-cross-validated. The predictive ability of CoMSIA model was further validated by a test set of 7 compounds, giving r pred 2 value of 0.973. Docking studies were used to find the actual conformations of chemicals in active site of HIV protease, as well as the binding mode pattern to the binding site in protease enzyme. The information provided by 3D-QSAR model and molecular docking may lead to a better understanding of the structural requirements of 34 cyclic-urea derivatives and help to design potential anti-HIV protease molecules. [ABSTRACT FROM AUTHOR]

A series of sulfonylnitrophenylthiazoles derivatives were identified as effective targeting agents that block the interaction of the thyroid hormone receptor with its coactivators. In this work, in order to analyze the structure-activity relationship of these inhibitors and investigate the structural requirements for thyroid hormone receptor inhibitory activity, new statistically validated in silico models adopting different molecular descriptors were established. The two-dimensional quantitative structure-activity relationship models were developed using multiple linear regression method, which show both significant statistical quality and predictive ability ( R = 0.939, Q = 0.622 for thyroid hormone receptor β; R = 0.862, Q = 0.763 for thyroid hormone receptor α), and different molecular descriptors were included, namely R2, H5, EEigo4r and Ram for thyroid hormone receptor β, MATS1, IC and R5e+ for thyroid hormone receptor α. The optimum comparative molecular field analysis models were established using the template ligand-based alignment, which show satisfactory linear correlations (thyroid hormone receptor β: R = 0.577, R = 0.8013; thyroid hormone receptor α: R = 0.549, R = 0.8639). In addition, the R of 0.543, R of 0.8523 for thyroid hormone receptor β and R of 0.560, R of 0.8695 for thyroid hormone receptor α have been observed when comparative molecular similarity analysis fields were applied. All the developed statistical models give satisfactory results with accurate fitting and strong predictive abilities. Moreover, the contour maps provide an intuitive understanding of the structural requirements for the inhibitors. In conclusion, these data can provide some meaningful theoretical references to understand the factors influencing the inhibitory activity and direct the molecular design of novel inhibitors with increased activity. [ABSTRACT FROM AUTHOR]

Acetyl-CoA carboxylases (ACC) have long been recognized as an attractive target for metabolic syndrome because of its indispensable role in the regulation of fatty acid metabolism in most living organisms. Based on the lead compound CP-640186, a series of spiro-compounds of benzothiazole derivatives have been identified as ACC inhibitors, which displayed high ACC inhibitor activities and good metabolic stability. Nevertheless, no quantitative structure-activity relationship study has been developed for this kind of ACC inhibitors. In order to evaluate the correlation between changes on structures and variation on biological activity, three-dimensional quantitative structure-activity relationship analysis was employed. Satisfactory results were obtained after performing a leave-one-out cross-validation study with q and r values of 0.625 and 0.927 by the comparative molecular field analysis model, 0.779 and 0.937 by the comparative molecular similarity indices analysis model, respectively. The predictive ability of the models was validated using external validation test set. The contour map analysis of comparative molecular field analysis and comparative molecular similarity indices analysis models indicated that electropositive and bulky groups substituted at the R position of carbamido group, and hydrophilic groups substituted at the phenyl ring were favorable for the inhibitory activity. Furthermore, FlexX docking was employed to investigate the binding mode between human ACC1 and its inhibitors and to validate the three-dimensional quantitative structure-activity relationship models. As a result, based on the results of three-dimensional quantitative structure-activity relationship and FlexX docking, a series of ACC inhibitors with higher predictive activities have been designed. This work might provide valuable information in further optimization of human ACC inhibitors. [ABSTRACT FROM AUTHOR]

The high edible oil content of Xanthoceras sorbifolia Bunge seeds contributes to its economic value. In this study, we analysed the barrigenol-like triterpenoids derived from X . sorbifolia husks. We also identified anti-tumour agents that could enhance the health benefits and medicinal value of X . sorbifolia . We isolated 10 barrigenol triterpenoids, including six new compounds ( 1 – 6 ) and four known compounds ( 7 – 10 ). New compounds 3 and 5 showed significant inhibitory activity against the proliferation of three human tumour cell lines, namely, HepG2, HCT-116 and U87-MG. We determined the relationship between the structures and inhibitory activity of 25 barrigenol triterpenoids and 15 penta-cyclic triterpenoids through analysis of three-dimensional quantitative structure activity relationships (3D-QSAR). The isolation of novel barrigenol derivatives with anti-tumour activity from X . sorbifolia implied that husks of this plant may be a good source of anti-tumour agents. [ABSTRACT FROM AUTHOR]

Respiratory syncytial virus (RSV) has been identified as a main cause of hospitalisation in infants and children. To date, the current therapeutic arsenal is limited to ribavirin and palivizumab with variable efficacy. In this work, starting from a number of in-house series of previously described anti-RSV agents based on the benzimidazole scaffold, with the aim at gaining a better understanding of the related chemical features involved in potency and safety profiles, we applied a computational study including two focussed comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The results allowed us to derive useful suggestions for the design of derivatives and also to set up statistical models predicting the potency and selectivity index (SI = CC50/EC50) of any new analogue prior to synthesis. Accordingly, here, we discuss preliminary results obtained through the applied exhaustive QSAR analyses, leading to design and synthesise more effective anti-RSV agents. [ABSTRACT FROM PUBLISHER]

The 5-hydroxytryptamine (5-HT1A) receptors represent an attractive target in drug discovery. In particular, 5-HT1Aagonists and partial agonists are deeply investigated for their potential role in the treatment of anxiety, depression, ischaemic brain disorder and more recently, of pain. On the other hand, 5-HT1Aantagonists have been revealed promising compounds in cognition disorders and, lately, in cancer. Thus, the discovery of 5HT1Aligands is nowadays an appealing research activity in medicinal chemistry. In this work, Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) were applied on an in-house library of 5-HT1Aligands bearing different chemical scaffolds in order to elucidate their affinity and selectivity for the target.Following this procedure, a number of structural modifications have been drawn for the development of much more effective 5-HT1AR ligands. [ABSTRACT FROM AUTHOR]

• 1,4-Dihydropyrimidines are usually synthesized from Biginelli reaction. • A series of novel Biginelli-1,4-dihydropyrimidines are rationally designed and synthesized. • Screened against MCF-7 breast cancer cells for their anti-cancer activity by measuring the cytotoxicity. • Dihydropyrimidines exhibited weak to significant cytotoxicity. • Most potent compound (compound 14) is found to inhibit EGFR and HER2 • 3D-QSAR studies were executed to elucidate structure activity relationships in a 3D grid space. • Identified compound 14 to investigate further for its anticancer activity. 1,4-Dihydropyrimidines are usually synthesized from Biginelli reaction which are well known for their anti-cancer activity. A series of novel Biginelli-1,4-dihydropyrimidines are rationally designed, synthesized, purified, analyzed by IR, NMR, Mass spectrometry and screened against MCF-7 breast cancer cells for their anti-cancer activity by measuring the cytotoxicity. Dihydropyrimidines exhibited weak to significant cytotoxicity proportionate to their anti-cancer activity. 14, 7 and 5 have exhibited potent cytotoxicity amongst the screened 33 dihydropyrimidines. Most potent compound 14 is further tested for inhibition of EGFR (epidermal growth factor receptor) and HER2 (human epidermal growth factor receptor 2) expression at 2 different concentrations by taking lapatinib as standard in flow cytometry. 42.02% and 36.45% of cells expressing EGFR and HER2 were inhibited at 500nM/L concentration. Furthermore, 3D-QSAR studies were executed to elucidate structure activity relationships in a 3D grid space by plotting experimental vs predicted cytotoxic activities. [Display omitted] [ABSTRACT FROM AUTHOR]

Aurora A kinase is involved in the inactivation of apoptosis leading to ovarian, breast, colon, and pancreatic cancers. Inhibitors of Aurora A kinase promote aberrant mitosis resulting in arrest at a pseudo G1 state to induce mitotic catastrophe, ultimately leading to apoptosis. In this study, ligand-based and docking-based three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses of imidazole and thiazolidine derivatives as potential Aurora A kinase inhibitors were performed. The results provided highly reliable and predictive 3D-QSAR comparative molecular similarity index analysis (CoMSIA) models with a cross-validated q value of 0.768, non-cross-validated r value of 0.983, and predictive coefficient $${\text{r}}_{\text{pred}}^{2}$$ value of 0.978. CoMSIA contour maps suggested that the NH and benzyl hydroxy groups in R, and the CO group in the thiazolidine ring and pyridine ring were important components for biological activity. The maps also suggest that the introduction of hydroxy groups at C of the imino-phenyl ring, C in the pyridine ring, or the substitution of the imino-phenyl ring for the imino-2-pyridine ring could be applied to enhance biological activity. [ABSTRACT FROM AUTHOR]

Mer kinase is implicated as therapeutic target for the prevention and treatment of thrombosis. A molecular modeling study was performed on a series of pyrimidine-based inhibitors of Mer specific tyrosine kinase. The relationship between the structure and the activity of these inhibitors was studied using three-dimensional quantitative structure-activity relationship, molecular docking and molecular dynamics simulations. A reliable comparative molecular similarity indices analysis model with a cross-validated correlation coefficient ( q ) of 0.637 and a conventional correlation coefficient ( r ) of 0.955 was obtained from the combination of steric and hydrogen bond donor fields. Model showed acceptable predictive capability with predicted correlation coefficient ( r ) of 0.614. Satisfactory performance in several validation procedures indicated the reliability and robustness of the model. Docking study was performed to determine the binding mode of these inhibitors inside the active site of Mer kinase. Molecular dynamics simulation was performed on the docked structure to explore the thorough binding process. Docking and molecular dynamics simulation identified some crucial binding residues such Leu593, Pro672, Phe673, Met674, Gly677, Asp678, Thr681, Tyr685, and Met730. This study provides useful information for the design of novel and more potent antithrombotic agents. [ABSTRACT FROM AUTHOR]

We earlier reported thiophene-containing trisubstituted methanes (TRSMs) as novel cores carrying anti-tubercular activity, and identified S006-830 as the phenotypic lead with potent bactericidal activity against single- and multi-drug resistant clinical isolates ofMycobacterium tuberculosis(M. tb). In this work, we carried out additional synthesis of several TRSMs. The reaction scheme essentially followed the Grignard reaction and Friedel–Crafts alkylation, followed by insertion of a dialkylaminoethyl chain. We also performed microbiological evaluations includingin vitroscreening against the virulent strainM. tbH37Rv, cytotoxicity assessment in the Vero C-1008 cell line, and 3D-QSAR studies with comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). CoMFA and CoMSIA models yielded good statistical results in terms ofq2andr2values, suggesting the validity of the models. It was concluded that a para-substituted benzene ring with bulkier electron-donating groups and aminoalkyl chains are required for higher inhibitory capacity againstM. tuberculosis. We believe that these insights will rationally guide the design of newer, optimal, TRSMs. [ABSTRACT FROM AUTHOR]

Janus kinase 2 (JAK2) is an intracellular nonreceptor tyrosine kinase that belongs to the JAK family of kinases, which play an important role in survival, proliferation, and differentiation of a variety of cells. JAK2 inhibitors are potential drugs for the treatment of myeloproliferative neoplasms. The three dimensional quantitative structure-activity relationships have been studied on a series of JAK2 inhibitors by comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA). The CoMFA model had a cross-validated coefficient q2 of 0.633, and the relation non-cross-validated coefficient r2 of 0.976. The F value is 225.030. The contributions of steric and electrostatic fields to the activity are 55.2% and 44.8%, respectively. For the CoMSIA study, the q2, r2, and F values of the model are 0.614, 0.929, and 88.771, respectively. The contributions of steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond donor fields to the activity are 27.3%, 23.9%, 16.4%, 21.7%, and 10.7%, respectively. The CoMFA and CoMSIA models showed strong predictive ability, and the 3D contour plots give the basis on the structure modification of JAK2 inhibitors.

Phenolic acids are potent antioxidants, yet the quantitative structure-activity relationships of phenolic acids remain unclear. The purpose of this study was to establish 3D-QSAR models able to predict phenolic acids with high DPPH• scavenging activity and understand their structure-activity relationships. The model has been established by using a training set of compounds with cross-validated q2 = 0.638/0.855, non-cross-validated r2 = 0.984/0.986, standard error of estimate = 0.236/0.216, and F = 139.126/208.320 for the best CoMFA/CoMSIA models. The predictive ability of the models was validated with the correlation coefficient r2pred = 0.971/0.996 (>0.6) for each model. Additionally, the contour map results suggested that structural characteristics of phenolics acids favorable for the high DPPH• scavenging activity might include: (1) bulky and/or electron-donating substituent groups on the phenol ring; (2) electron-donating groups at the meta-position and/or hydrophobic groups at the meta-/ortho-position; (3) hydrogen-bond donor/electron-donating groups at the ortho-position. The results have been confirmed based on structural analyses of phenolic acids and their DPPH• scavenging data from eight recent publications. The findings may provide deeper insight into the antioxidant mechanisms and provide useful information for selecting phenolic acids for free radical scavenging properties.

Mitogen-activated protein kinase-activated protein kinase 2 (MK-2) has been identified as a drug target for the treatment of inflammatory diseases. Currently, a series of thiourea analogs as potent MK-2 inhibitors were studied using comprehensive computational methods by 3D-QSAR, molecular docking and molecular dynamics simulations for a further improvement in activities. The optimal 3D models exhibit high statistical significance of the results, especially for the CoMFA results with r2ncv, q2 values of 0.974, 0.536 for the internal validation, and r2pred, r2m values of 0.910, 0.723 for the external validation and Roy’s index, respectively. In addition, more rigorous validation criteria suggested by Tropsha were also employed to check the built models. Graphic representation of the results, as contoured 3D coefficient plots, also provides a clue to the reasonable modification of molecules: (i) The substituent with a bulky size and electron-rich group at the C5 position of the pyrazine ring is required to enhance the potency; (ii) The H-bond acceptor group in the C3 position of the pyrazine ring is likely to be helpful to increase MK-2 inhibition; (iii) The small and electropositive substituent as a hydrogen bond donor of the C2 position in the oxazolone ring is favored; In addition, several important amino acid residues were also identified as playing an important role in MK-2 inhibition. The agreement between 3D-QSAR, molecular docking and molecular dynamics simulations also proves the rationality of the developed models. These results, we hope, may be helpful in designing novel and potential MK-2 inhibitors.

Topoisomerase I is important for DNA replication and cell division, making it an attractive drug target for anticancer therapy. A series of indenoisoquinolines displaying potent Top1 inhibitory activity in human renal cell carcinoma cell line SN12C were selected to establish 3D-QSAR models using CoMFA and CoMSIA methods. Internal and external cross-validation techniques were investigated, as well as some measures taken, including region focusing, bootstrapping and the “leave-group-out” cross-validation method. The satisfactory CoMFA model predicted a q2 value of 0.659 and an r2 value of 0.949, indicating that electrostatic and steric properties play a significant role in potency. The best CoMSIA model, based on a combination of steric, electrostatic and H-bond acceptor descriptors, predicted a q2 value of 0.523 and an r2 value of 0.902. The models were graphically interpreted by contour plots which provided insight into the structural requirements for increasing the activity of a compound, providing a solid basis for future rational design of more active anticancer agents.

A three-dimensional quantitative structure-activity relationship (3D-QSAR) model of sulfonamide analogs binding a monoclonal antibody (MAbSMR) produced against sulfamerazine was carried out by Distance Comparison (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA). The affinities of the MAbSMR, expressed as Log10IC50, for 17 sulfonamide analogs were determined by competitive fluorescence polarization immunoassay (FPIA). The results demonstrated that the proposed pharmacophore model containing two hydrogen-bond acceptors, two hydrogen-bond donors and two hydrophobic centers characterized the structural features of the sulfonamides necessary for MAbSMR binding. Removal of two outliers from the initial set of 17 sulfonamide analogs improved the predictability of the models. The 3D-QSAR models of 15 sulfonamides based on CoMFA and CoMSIA resulted in q2cv values of 0.600 and 0.523, and r2 values of 0.995 and 0.994, respectively, which indicates that both methods have significant predictive capability. Connolly surface analysis, which mainly focused on steric force fields, was performed to complement the results from CoMFA and CoMSIA. This novel study combining FPIA with pharmacophore modeling demonstrates that multidisciplinary research is useful for investigating antigen-antibody interactions and also may provide information required for the design of new haptens.

Enoyl acyl carrier protein (ACP) reductase (FabI) is a potential target for the development of antibacterial agents. Three-dimensional quantitative structure-activity relationships (3D-QSAR) for substituted formamides series of FabI inhibitors were investigated using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Pharmacophore and molecular docking methods were used for construction of the molecular alignments. A training set of 36 compounds was performed to create the 3D-QSAR models and their external predictivity was proven using a test set of 11 compounds. Graphical interpretation of the results revealed important structural features of the formamides related to the active site of FabI. The results may be exploited for further optimization of the design of new potent FabI inhibitors.

Androgen receptor antagonists have been proved to be effective anti-prostate cancer agents. 3D-QSAR and Molecular docking methods were performed on curcumin derivatives as androgen receptor antagonists. The bioactive conformation was explored by docking the potent compound 29 into the binding site of AR. The constructed Comparative Molecular Field Analysis (CoMFA) and Comparative Similarity Indices Analysis (CoMSIA) models produced statistically significant results with the cross-validated correlation coefficients q2 of 0.658 and 0.567, non-cross-validated correlation coefficients r2 of 0.988 and 0.978, and predicted correction coefficients r2pred of 0.715 and 0.793, respectively. These results ensure the CoMFA and CoMSIA models as a tool to guide the design of novel potent AR antagonists. A set of 30 new analogs were proposed by utilizing the results revealed in the present study, and were predicted with potential activities in the developed models.

Kinase insert domain receptor (KDR) inhibitors have been proved to be very effective anticancer agents. Molecular docking, 3D-QSAR methods, CoMFA and CoMSIA were performed on pyrrolo[3,2-d]pyrimidine derivatives as non-ATP competitive KDR inhibitors (type II). The bioactive conformation was explored by docking one potent compound 20 into the active site of KDR in its DFG-out inactive conformation. The constructed CoMFA and CoMSIA models produced statistically significant results with the cross-validated correlation coefficients q2 of 0.542 and 0.552, non-cross-validated correlation coefficients r2 of 0.912 and 0.955, and predicted correction coefficients r2pred of 0.913 and 0.897, respectively. These results ensure the CoMFA and CoMSIA models as a tool to guide the design of a series of new potent KDR inhibitors.

Objective: Monocyte chemo attractant protein-1 (MCP-1) is a member of the CC-chemokine family and it selectively recruits leukocytes from the circulation to the site of inflammation through binding with the chemotactic cytokine receptor 2B (CCR2B). The recruitment and activation of selected populations of leukocytes is a key feature in a variety of inflammatory conditions. Thus MCP-1 receptor antagonist represents an attractive target for drug discovery. To understand the structural requirements that will lead to enhanced inhibitory potencies, we have carried out 3D-QSAR (quantitative structure-activity relationship) studies on (R)-3-aminopyrrolidine series of molecules as CCR2B receptor antagonists. Materials and Methods: Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of (R)-3-aminopyrrolidine derivatives as antagonists of CCR2B receptor with Sybyl 6.7v. Results: We have derived statistically significant model from 37 molecules and validated it against an external test set of 13 compounds. The CoMFA model yielded a leave one out r 2 (r 2 loo ) of 0.847, non-cross-validated r 2 (r 2 ncv ) of 0.977, F value of 267.930, and bootstrapped r 2 (r 2 bs ) of 0.988. We have derived the standard error of prediction value of 0.367, standard error of estimate 0.141, and a reliable external predictivity, with a predictive r 2 (r 2 pred ) of 0.673. While the CoMSIA model yielded an r 2 loo of 0.719, r 2 ncv of 0.964,F value of 135.666, r 2 bs of 0.975, standard error of prediction of 0.512, standard error of estimate of 0.180, and an external predictivity with an r 2 pred of 0.611. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r 2 pred, based on the mean activity of test set compounds can accurately estimate external predictivity. Conclusion: The QSAR model gave satisfactory statistical results in terms of q 2 and r 2 values. We analyzed the contour maps obtained, to study the activity trends of the molecules. We have tried to demonstrate structural features of compounds to account for the activity in terms of positively contributing physicochemical properties such as steric, electrostatic, hydrophobic, hydrogen bond donor, and acceptor fields. These contour plots identified several key features, which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel CCR2B antagonists before their synthesis.

Fructose 1,6-bisphosphatase (FBPase) has been identified as a drug discovery target for lowering glucose in type 2 diabetes mellitus. In this study, a large series of 105 FBPase inhibitors were studied using a combinational method by 3D-QSAR, molecular docking and molecular dynamics simulations for a further improvement in potency. The optimal 3D models exhibit high statistical significance of the results, especially for the CoMFA results with rncv2, q2 values of 0.986, 0.514 for internal validation, and rpred2, rm2 statistics of 0.902, 0.828 statistics for external validation. Graphic representation of the results, as contoured 3D coefficient plots, also provides a clue to the reasonable modification of molecules. (1) Substituents with a proper length and size at the C5 position of the thiazole core are required to enhance the potency; (2) A small and electron-withdrawing group at the C2 position linked to the thiazole core is likely to help increase the FBPase inhibition; (3) Substituent groups as hydrogen bond acceptors at the C2 position of the furan ring are favored. In addition, the agreement between 3D-QSAR, molecular docking and molecular dynamics simulation proves the rationality of the developed models. These results, we hope, may be helpful in designing novel and potential FBPase inhibitors.

The α1A-adrenergic receptor (α1A-AR) antagonist is useful in treating benign prostatic hyperplasia, lower urinary tract symptoms, and cardiac arrhythmia. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a set of α1A-AR antagonists of N-aryl and N-nitrogen class. Statistically significant models constructed from comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were established based on a training set of 32 ligands using pharmacophore-based molecular alignment. The leave-one-out cross-validation correlation coefficients were q2CoMFA = 0.840 and q2CoMSIA = 0.840. The high correlation between the cross-validated/predicted and experimental activities of a test set of 12 ligands revealed that the CoMFA and CoMSIA models were robust (r2pred/CoMFA = 0.694; r2pred/CoMSIA = 0.671). The generated models suggested that electrostatic, hydrophobic, and hydrogen bonding interactions play important roles between ligands and receptors in the active site. Our study serves as a guide for further experimental investigations on the synthesis of new compounds. Structural modifications based on the present 3D-QSAR results may lead to the discovery of other α1A-AR antagonists.

Selective S1P1 receptor agonists have therapeutic potential to treat a variety of immune-mediated diseases. A series of 2-imino-thiazolidin-4-one derivatives displaying potent S1P1 receptor agonistic activity were selected to establish 3D-QSAR models using CoMFA and CoMSIA methods. Internal and external cross-validation techniques were investigated as well as some measures including region focusing, progressive scrambling, bootstraping and leave-group-out. The satisfactory CoMFA model predicted a q2 value of 0.751 and an r2 value of 0.973, indicating that electrostatic and steric properties play a significant role in potency. The best CoMSIA model, based on a combination of steric, electrostatic, hydrophobic and H-bond donor descriptors, predicted a q2 value of 0.739 and an r2 value of 0.923. The models were graphically interpreted using contour plots which gave more insight into the structural requirements for increasing the activity of a compound, providing a solid basis for future rational design of more active S1P1 receptor agonists.

MGluR2 is G protein-coupled receptor that is targeted for diseases like anxiety, depression, Parkinson’s disease and schizophrenia. Herein, we report the three-dimensional quantitative structure–activity relationship (3D-QSAR) studies of a series of 1,3-dihydro-benzo[b][1,4]diazepin-2-one derivatives as mGluR2 antagonists. Two series of models using two different activities of the antagonists against rat mGluR2, which has been shown to be very similar to the human mGluR2, (activity I: inhibition of [3H]-LY354740; activity II: mGluR2 (1S,3R)-ACPD inhibition of forskolin stimulated cAMP.) were derived from datasets composed of 137 and 69 molecules respectively. For activity I study, the best predictive model obtained from CoMFA analysis yielded a Q2 of 0.513, R2ncv of 0.868, R2pred = 0.876, while the CoMSIA model yielded a Q2 of 0.450, R2ncv = 0.899, R2pred = 0.735. For activity II study, CoMFA model yielded statistics of Q2 = 0.5, R2ncv = 0.715, R2pred = 0.723. These results prove the high predictability of the models. Furthermore, a combined analysis between the CoMFA, CoMSIA contour maps shows that: (1) Bulky substituents in R7, R3 and position A benefit activity I of the antagonists, but decrease it when projected in R8 and position B; (2) Hydrophilic groups at position A and B increase both antagonistic activity I and II; (3) Electrostatic field plays an essential rule in the variance of activity II. In search for more potent mGluR2 antagonists, two pharmacophore models were developed separately for the two activities. The first model reveals six pharmacophoric features, namely an aromatic center, two hydrophobic centers, an H-donor atom, an H-acceptor atom and an H-donor site. The second model shares all features of the first one and has an additional acceptor site, a positive N and an aromatic center. These models can be used as guidance for the development of new mGluR2 antagonists of high activity and selectivity. This work is the first report on 3D-QSAR modeling of these mGluR2 antagonists. All the conclusions may lead to a better understanding of the mechanism of antagonism and be helpful in the design of new potent mGluR2 antagonists.