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Increasing evidence has shown collagen hydrolysate involves a variety of bioactivities. In our previous study, multiple antiplatelet peptides containing Hyp/Pro-Gly were identified in collagen hydrolysates from Salmo salar and silver carp skin and exhibited anti-thrombosis activity without bleeding risks in vivo. However, the relationship between structure and activity remains unknown. We performed 3D-QSAR studies on 23 Hyp/Pro-Gly-containing peptides in which 13 peptides were reported before. CoMFA, Topomer CoMFA and CoMSIA analyses were used to generate the QSAR models. Topomer CoMFA analysis showed a q2 value of 0.710, an r2 value of 0.826, an r2pred value of 0.930, and the results showed that Hyp instead of Pro was more important for improving the antiplatelet activity. CoMSIA analysis showed a q2 value of 0.461, an r2 value of 0.999, and an r2pred value of 0.999. Compared with the electrostatic field and hydrogen bond donor field, the steric field, hydrophobic field and hydrogen bond receptor field have great influence on the activity of antiplatelet peptides. The predicted peptide EOGE exhibited antiplatelet activity induced by ADP, and inhibited thrombus formation (300 μmol/kg bw) without bleeding risks. Combined results of these studies indicate that OG-containing peptides had a potential to be developed into an effective specific medical food in the prevention of thrombotic diseases. [ABSTRACT FROM AUTHOR]

In this paper, a three-dimensional quantitative structure-activity relationship (3D-QSAR) namely CoMFA and CoMSIA has been carried out on a series (43 compounds) of capsid assembly inhibitors on N-phenyl-3-sulfamoyl-benzamide-based. The statistical parameters from the models (CoMFA: r2 = 0.998, q2 = 0.625, r2pred = 0.837; CoMSIA: r2 = 0.987, q2 = 0.645, r2pred = 0.698) indicate that the data are well fitted and have high predictive ability. Molecular docking was employed to explore the binding mode between these compounds and the receptor protein, as well as help understand the structure-activity relationship revealed by CoMFA and CoMSIA. Contour maps of the QSAR models were generated and validated by molecular docking study. The final models of CoMFA/CoMSIA and molecular docking could be useful for the design and development of novel potent HBV capsid assembly inhibitors. [ABSTRACT FROM AUTHOR]

Soluble epoxide hydrolase (sEH), a member of the α/β hydrolase fold family, catalyzes the hydrolysis of epoxy eicosatrienoic acids to vicinal diol which are involved in the regulation of blood pressure and inflammation. In this study, 2D and 3D‐QSAR analysis of novel N,N′‐disubstituted urea derivatives as sEH inhibitors were performed by stepwise multiple linear regressions (SW‐MLR), stepwise artificial neural networks (SW‐ANN), Comparative Molecular Field Analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). It was found that SW‐MLR model with r2 of 0.954 for the training set and r2 of 0.876 for the test set were more favorable than model established by CoMFA method with r2=0.983, r2pred=0.602 and CoMSIA with r2=0.987, r2pred=0.751 in 3D‐QSAR. In addition, obtaining models were validated by cross validation with cut off value of q2> 0.5. These developed models could be a useful guideline to design and predict the activity of novel compounds with enhanced sEH inhibitory activities. [ABSTRACT FROM AUTHOR]

In Quantitative Structure‐Activity Relationship (QSAR) studies, selection of an appropriate method to assign the partial charge is crucial to derive a reliable model. The prediction accuracy of 3D‐QSAR models depends mainly on the method by which the partial charges were calculated. Therefore, we are interested in examining the effects of empirical and semi‐empirical partial charges on 3D‐QSAR methods, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The feasibility and performance of these charges have been tested on Janus Kinase 2 inhibitors. Both empirical (Gasteiger‐Huckel, Del‐Re, Gasteiger Marsili, Huckel, Merck Molecular Force Field 94 (MMFF94), Pullman) and semi‐empirical (Austin Model 1 (AM1), Parameterized Model 3 (PM3), Recife Model 1 (RM1), and Modified Neglect of Diatomic Overlap (MNDO)) charges exhibited statistically significant quality. Among them, MMFF94, MNDO and AM1 charges yielded higher cross‐validation correlation coefficient (q2) values whereas Del‐Re and MMFF94 charges produced topmost predictive ability (r2pred). Overall, MMFF94 in CoMFA and MMFF94 and MNDO in CoMSIA models was found to be the best charges when both q2 and r2pred values were used as an evaluation criterion. Our results could provide an idea of selection of appropriate charge rather than using default charge to enhance the quality of 3D‐QSAR when prediction accuracy and predictive ability were employed. [ABSTRACT FROM AUTHOR]

A RET (Rearranged during transfection) kinase belongs to a receptor tyrosine kinase family. It plays a major role in development, maturation, survival, and maintenance of cells and tissues. Oncogenic activation of RET has been reported in numerous cancers. Thus, it is a significant therapeutic target for cancer. Present work covers docking and 3D‐QSAR techniques executed on anilinoquinazoline derivatives as RET kinase antagonists. Docking study recognized important active site amino acid residues like Leu730, Gly731, Gly733, Glu734, Ala807, Gly810, Ser811, and Asp874 which inhibits the RET kinase. In 3D‐QSAR technique, receptor‐guided CoMFA (q2 = 0.723, NOC = 5, r2 = 0.980) as well as CoMSIA (q2 = 0.767, NOC = 6, r2 = 0.967) models were produced. The stabilities of these models were evaluated using diverse validation techniques. Contour maps showed that steric and hydrogen bond donor substitutions are favored at R1 and R2 positions whereas positive and negative substitutions are favored at the R1 position to enhance the potency. In addition, the substitution of H‐bond accepting group to the region which is close to both phenyl and piperazine is favored. Hence, the outcome of this study could be beneficial to design more potent inhibitors for RET kinase. [ABSTRACT FROM AUTHOR]

Abstract As a kind of potential anticancer compounds, Cyclin-dependent kinase (CDK) inhibitors have receved great attention in recent years. In order to deep research the bioactivity and corresponding key influence factors of CDK8/19 inhibitors on molecular level, quantum chemistry and 3D-QSAR have been performed on 64 molecules based on pyridine ring scaffold. Two high predictive QSAR models have been built, in which both the CoMFA model (q2 = 0.69, r2 = 0.98) and CoMSIA model (q2 = 0.61, r2 = 0.98) have displayed quite good external predictablility on test set with excellent values of r p r e d 2 (0.94 and 0.97). In these models, the steric, electrostatic and hydrophobic fields have played key roles on bioactivity. Docking simulation has been carried out to further investigate possible binding modes of compounds into the active site of CDK8 (PDB. 5I5Z), the results show that some high bioactivity molecules are quite well embedded in the active pocket. Nitrogen-atom of pyridine ring and some other groups (ie. NH, CO, SO. NH, CO, SO) have formed medium strength hydrogen bonds (1.5 Å to 2.2 Å) with the N, H, O atoms of the protein. The geometric structures of the inhibitor molecules have been changed differently during the processes of docking, surflex-dock has confirmed the acting force stability of predicted molecules in the protein. Our method and results can be helpful for finding new targets and developing new drugs. Graphical abstract 3D-surface of active site of CDK8 (pdb:5I5Z) included compound 28. Image 1 Highlights • The 3D-QSAR and molecular docking were carried out to study the CDK8 inhibitors. • All calculations were conducted using the Gaussian 09 program package. • QSAR models have excellent external predictive ability. • New compounds were designed and their biological activity were predicted by using built models. • The docking results among the existing CDK8 inhibitors and the target compounds were compared. [ABSTRACT FROM AUTHOR]

The 3D QSAR analysis using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques is performed on novel nalidixic acid based 1,2,4-triazole derivatives suggested earlier as antibacterial agents. The CoMFA and CoMSIA models employed for a training set of 28 compounds gives reliable values of Q2 (0.53 and 0.52, respectively) and R2 (0.79 and 0.85, respectively). The contour maps produced by the CoMFA and CoMSIA models are used to determine a three-dimensional quantitative structure-activity relationship. Based on the 3D QSAR contours new molecules with high predicted activities are designed. In addition, surflex-docking is performed to confirm the stability of predicted molecules in the receptor. [ABSTRACT FROM AUTHOR]

The study deals with CoMFA, CoMSIA and HQSAR to explore the important features of tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepinone (TIBO) derivatives for exerting potent HIV-1 reverse transcriptase (HIV-1 RT) inhibitors activity. The cross-validated q 2 value of CoMFA model is 0.641 and the non-cross-validated r 2 value is 0.847. The best cross-validated q 2 value of CoMSIA Model is 0.706 and the non-cross-vaildated r 2 value is 0.939. The most effective HQSAR model was obtained that the cross-validation q 2 value of 0.839, the non-cross-validated r 2 value of 0.942, the standard error of prediction SD CV value of 0.604, and the best hologram length value of 307 using atoms and bonds as fragment distinctions. The statistical parameters from models indicate that the data are well fitted and have high predictive ability. Furthermore, Molecular docking was employed to explore the binding requirements between the ligands and the receptor protein which included several hydrogen bonds between the TIBO inhibitors and active site residues. Observations derived from these QSAR modeling study may be utilized further in designing promising HIV-1 reverse transcriptase inhibitors. [ABSTRACT FROM AUTHOR]

The N-methyl-D-aspartate (NMDA) is the family of glutamate receptor, which is involved in controlling synaptic plasticity and memory function; but overactivation of this receptor results to excess intracellular calcium formation, triggers neuronal injury and also involves in several pathologies. Both ligand- and structure-based quantitative structure-activity relationship (QSAR), pharmacophore, docking and simulation studies have been performed on a set of structurally diverse inhibitors to explore prime molecular structural features involve for specific binding to NMDA, and vis-à-vis inhibiting enzyme activity. 3D QSAR studies, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models showed the importance of steric, electrostatic and hydrophobic features; while hydrogen bond acceptor and hydrophobic features are depicted as important pharmacophore features of the molecule. Molecular docking and simulation studies corroborated the consequence of the features obtained from ligand-based Bayesian model (AUROCcv = 0.878); 3D QSAR CoMFA (R2 = 0.895, se = 0.513, Q2 = 0.602, R2pred = 0.673); CoMSIA (R2 = 0.877, se = 0.555, Q2 = 0.615, R2pred = 0.727); hologram QSAR (Q2 = 0.812, R2 = 0.941, R2pred = 0.772), and pharmacophore models (Q2 = 0.926, R2 = 0.927, R2pred = 0.621). Presence of aromatic ring, hetero and halogen atoms along with alkyl group of molecular scaffold shows their importance for binding affinity to NMDA receptor. Stability of the complex is adjudged by both docking and simulation studies. [ABSTRACT FROM AUTHOR]

Human immunodeficiency virus type-1 reverse transcriptase (HIV-1 RT) plays a key in the life cycle of HIV-1. It is considered to be one of the promising targets for treating HIV/AIDS which contains two drug binding sites, a substrate binding site, and an allosteric site. Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are a class of RT inhibitors that bind to allosteric sites on HIV-1 RT in a non-competitive manner and thereby disrupting the conformation of RT. Hence, they can act as potent inhibitors against HIV-1 RT. In present study, the key structural requirements for enhancing HIV-1 RT inhibitory activity were explored from combined docking and three-dimensional quantitative structure activity relationship (3D QSAR) protocols. Initially, multiple-receptor conformation docking (MRCD) was performed using a series of diaryl pyridine and pyrimidine derivatives into the active site of ten X-ray crystal structures and one NMR-resolved conformation of HIV-1 RT. Later, the dock poses obtained from docking were clustered and 3D QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods. Finally, a robust model was established using cross-validation techniques and the robustness of the model was confirmed through high accuracy of q2loo of 0.843 and 0.682, r2ncv of 0.977 and 0.949, and r2pred of 0.702 and 0.690, respectively, for CoMFA and CoMSIA. Based on the outcome of the results, new pyrimidine derivatives having potential inhibitory against HIV-1 RT were designed. [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]

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]

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]

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]

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]

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]

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]

Lots of unexpected disinfection by-products were formed during the chlorination disinfection of contaminated water bodies, leading to a potential threat to human health and ecological safety. In this study, SOS/umu assay was used to trace the genotoxicity variation of 20 quinolone compounds during the chlorination disinfection. Furthermore, two- and three-dimensional quantitative structure-activity relationship models were developed based on the electronic and hydrophobic properties of the quinolones, which were used to quantify the impact of the different structural features of the compounds on their genotoxicity variation. The results revealed that quinolones bearing hydrophilic substituents with less H-bond donors and negative charge at the 1-position of the quinolone ring exhibited a positive correlation with genotoxicity elevation. More notably, the chlorination of quinolones in both ultrapure water and secondary effluent matrices provided comparable levels of genotoxicity, indicating that our research could potentially be used to evaluate the environmental risk of quinolone antibiotics in chlorination disinfection treatment. [ABSTRACT FROM AUTHOR]

A series of [1,2,4]triazolo[4,3- b ][1,2,4,5]tetrazine derivatives have been synthesized and their structures were confirmed by single-crystal X-ray diffraction. Compared to some reported structures of 1,6-dihydro-1,2,4,5-tetrazine, these compounds can’t be considered as having homoaromaticity. Their antiproliferative activities were evaluated against MCF-7, Bewo and HL-60 cells in vitro. Two compounds were highly effective against MCF-7, Bewo and HL-60 cells with IC 50 values in 0.63–13.12 μM. Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were carried out on 51 [1,2,4]triazolo[4,3- b ][1,2,4,5]tetrazine derivatives with antiproliferative activity against MCF-7 cell. Models with good predictive abilities were generated with the cross validated q 2 values for CoMFA and CoMSIA being 0.716 and 0.723, respectively. Conventional r 2 values were 0.985 and 0.976, respectively. The results provide the tool for guiding the design and synthesis of novel and more potent tetrazine derivatives. [ABSTRACT FROM AUTHOR]

Janus kinase 1 (JAK 1) plays a critical role in initiating responses to cytokines by the JAK—signal transducer and activator of transcription (JAK-STAT). This controls survival, proliferation and differentiation of a variety of cells. Docking, 3D quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) studies were performed on a series of Imidazo-pyrrolopyridine derivatives reported as JAK 1 inhibitors. QSAR model was generated using 30 molecules in the training set; developed model showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of this model was determined using a test set of 13 molecules that gave acceptable predictive correlation (r 2 Pred ) values. Finally, molecular dynamics simulation was performed to validate docking results and MM/GBSA calculations. This facilitated us to compare binding free energies of cocrystal ligand and newly designed molecule R1. The good concordance between the docking results and CoMFA/CoMSIA contour maps afforded obliging clues for the rational modification of molecules to design more potent JAK 1 inhibitors. [ABSTRACT FROM AUTHOR]

The three dimensional-quantitative structure activity relationship (3D-QSAR) study was performed on a series of 4-hydroxyamino α-pyranone carboxamide analogues using comparative molecular similarity indices analysis (COMSIA). The purpose of the present study was to develop a satisfactory model providing a reliable prediction based on 4-hydroxyamino α-pyranone carboxamide analogues as anti-HCV (hepatitis C virus) inhibitors. The statistical results and the results of validation of this optimum COMSIA model were satisfactory. Furthermore, analysis of the contour maps helped to provide guidelines for finding structural requirement. Therefore, the satisfactory results from this study may provide useful guidelines for drug development of anti-HCV inhibitors. [ABSTRACT FROM AUTHOR]

Viral hepatitis C infection is one of the main causes of the hepatitis after blood transfusion and hepatitis C virus (HCV) infection is a global health threat. The HCV NS5B polymerase, an RNA dependent RNA polymerase (RdRp) and an essential role in the replication of the virus, has no functional equivalent in mammalian cells. So the research and development of efficient NS5B polymerase inhibitors provides a great strategy for antiviral therapy against HCV. A combined three-dimensional quantitative structure–activity relationship (QSAR) modeling was accomplished to profoundly understand the structure-activity correlation of a train of indole-based inhibitors of the HCV NS5B polymerase to against HCV. A comparative molecular similarity indices analysis (COMSIA) model as the foundation of the maximum common substructure alignment was developed. The optimum model exhibited statistically significant results: the cross-validated correlation coefficient q 2 was 0.627 and non-cross-validated r 2 value was 0.943. In addition, the results of internal validations of bootstrapping and Y-randomization confirmed the rationality and good predictive ability of the model, as well as external validation (the external predictive correlation coefficient r ext 2 = 0.629). The information obtained from the COMSIA contour maps enables the interpretation of their structure–activity relationship. Furthermore, the molecular docking study of the compounds for 3TYV as the protein target revealed important interactions between active compounds and amino acids, and several new potential inhibitors with higher activity predicted were designed basis on our analyses and supported by the simulation of molecular docking. Meanwhile, the OSIRIS Property Explorer was introduced to help select more satisfactory compounds. The satisfactory results from this study may lay a reliable theoretical base for drug development of hepatitis C virus NS5B polymerase inhibitors. [ABSTRACT FROM AUTHOR]

Design of selective cyclooxygenase-2 (COX-2) inhibitors is still a challenging task because of active site similarities between COX isoenzymes. To help with this issue, we tried to generate a 3D-QSAR (3 dimensional quantitative structure activity relationships) model that might reflect the essential features of COX-2 active sites. Compounds in a series of resveratrol derivatives inhibitors with reported biological activity against COX-2 were used to construct a predictive comparative molecular similarity indices (CoMSIA) model. A CoMSIA model with acceptable internal and external predictability was developed and employed to design new not yet synthesized molecules with improved activity and selectivity toward COX-2. Finally, molecular docking of the inhibitors in COX-2 active site demonstrated the possible ability of proposed compounds to inhibit COX-2, selectively. [ABSTRACT FROM AUTHOR]

An indole ring system is considered as a versatile scaffold in the pharmaceutical field. In this article, comparative QSAR modeling (2D-QSAR, 3D-QSAR; kNN-MFA and CoMSIA) was performed on some Knoevenagel-type cytotoxic indole derivatives to understand the structural requirements for the cytotoxic property of these compounds. The 2D-QSAR model was statistically significant and imparted high predictive ability ( nTrain = 30; R = 0.917; = 0.801; = 0.757; Q2 = 0.722; nTest = 9; = 0.799). A statistically significant 3D-QSAR kNN-MFA model (both with stepwise forward and simulated annealing model selection method) as well as a 3D-QSAR CoMSIA model was developed to identify the key chemical features associated with enhancing the cytotoxic activities of these indoles. The results suggest that the presence of bulky group in R position can cause better cytotoxic activities. Consequently, substitution with cyano group at X portion and cyano/ester/keto/sulphonyl features at Y position is favourable for the cytotoxicity. However, hydrophobic features in R′ region are unfavourable for the biological activity. The chemical and structural features identified from the study may provide important avenues to modulate the structure of these indoles to a desirable biological end point. [ABSTRACT FROM AUTHOR]

Structure-based 3D-QSAR study was performed on a class of 5-benzylidene-2-phenylthiazolinones non-redox type 5-LOX inhibitors. In this study, binding pocket of 5-Lipoxygenase (pdb id 3o8y ) was identified by manual docking using 15-LOX (pdb id 2p0m ) as a reference structure. Additionally, most of the binding site residues were found conserved in both structures. These non-redox inhibitors were then docked into the binding site of 5-LOX. To generate reliable CoMFA and CoMSIA models, atom fit data base alignment method using docked conformation of the most active compound was employed. The q 2 cv and r 2 ncv values for CoMFA model were found to be 0.549 and 0.702, respectively. The q 2 cv and r 2 ncv values for the selected CoMSIA model comprised four descriptors steric, electrostatic, hydrophobic and hydrogen bond donor fields were found to be 0.535 and 0.951, respectively. Obtained results showed that our generated model was statistically reliable. Furthermore, an external test set validates the reliability of the predicted model by calculating r 2 pred i.e.0.787 and 0.571 for CoMFA and CoMSIA model, respectively. 3D contour maps generated from CoMFA and CoMSIA models were utilized to determine the key structural features of ligands responsible for biological activities. The applied protocol will be helpful to design more potent and selective inhibitors of 5-LOX. [ABSTRACT FROM AUTHOR]

Checkpoint kinase 1 (Chk1) is an important serine/threonine kinase with a self-protection function. The combination of Chk1 inhibitors and anti-cancer drugs can enhance the selectivity of tumor therapy. In this work, a set of 1,7-diazacarbazole analogs were identified as potent Chk1 inhibitors through a series of computer-aided drug design processes, including three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking, and molecular dynamics simulations. The optimal QSAR models showed significant cross-validated correlation q² values (0.531, 0.726), fitted correlation r² coefficients (higher than 0.90), and standard error of prediction (less than 0.250). These results suggested that the developed models possess good predictive ability. Moreover, molecular docking and molecular dynamics simulations were applied to highlight the important interactions between the ligand and the Chk1 receptor protein. This study shows that hydrogen bonding and electrostatic forces are key interactions that confer bioactivity. [ABSTRACT FROM AUTHOR]

Urease enzyme (EC 3.5.1.5) has been determined as a virulence factor in pathogenic microorganisms that are accountable for the development of different diseases in humans and animals. In continuance of our earlier study on the helicobacter pylori urease inhibition by barbituric acid derivatives, 3D-QSAR (three dimensional quantitative structural activity relationship) advance studies were performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. Different partial charges were calculated to examine their consequences on the predictive ability of the developed models. The finest developed model for CoMFA and CoMSIA were achieved by using MMFF94 charges. The developed CoMFA model gives significant results with cross-validation (q2) value of 0.597 and correlation coefficients (r2) of 0.897. Moreover, five different fields i.e., steric, electrostatic, and hydrophobic, H-bond acceptor and H-bond donors were used to produce a CoMSIA model, with q2 and r2 of 0.602 and 0.98, respectively. The generated models were further validated by using an external test set. Both models display good predictive power with r2pred ě 0.8. The analysis of obtained CoMFA and CoMSIA contour maps provided detailed insight for the promising modification of the barbituric acid derivatives with an enhanced biological activity. [ABSTRACT FROM AUTHOR]

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modelling was conducted on a series of leucine-rich repeat kinase 2 (LRRK2) antagonists using CoMFA and CoMSIA methods. The data set, which consisted of 37 molecules, was divided into training and test subsets by using a hierarchical clustering method. Both CoMFA and CoMSIA models were derived using a training set on the basis of the common substructure-based alignment. The optimum PLS model built by CoMFA and CoMSIA provided satisfactory statistical results (q2= 0.589 andr2= 0.927 andq2= 0.473 andr2= 0.802, respectively). The external predictive ability of the models was evaluated by using seven compounds. Moreover, an external evaluation set with known experimental data was used to evaluate the external predictive ability of the porposed models. The statistical parameters indicated that CoMFA (after region focusing) has high predictive ability in comparison with standard CoMFA and CoMSIA models. Molecular docking was also performed on the most active compound to investigate the existence of interactions between the most active inhibitor and the LRRK2 receptor. Based on the obtained results and CoMFA contour maps, some features were introduced to provide useful insights for designing novel and potent LRRK2 inhibitors. [ABSTRACT FROM AUTHOR]

The dopamine hypothesis states that decreased dopaminergic neurotransmission reduces schizophrenia symptoms. Neurokinin-3 receptor (NK3) antagonists reduce dopamine release and have shown positive effects in pre-clinical and clinical trials. We employed 2D and 3D-QSAR analysis on a series of 40 non-peptide NK3antagonists. Multivariate statistical analysis, PCA and HCA, were performed to rational training/test set splitting and PLS regression was employed to construct all QSAR models. We constructed one highly predictive CoMFA model (q2 = 0.810 andr2 = 0.929) and acceptable HQSAR and CoMSIA models (HQSARq2 = 0.644 andr2 = 0.910; CoMSIAq2 = 0.691,r2 = 0.911). The three different techniques provided convergent physicochemical results. All models indicate cyclopropane, piperidine and di-chloro-phenyl ring attached to cyclopropane ring and also the amide group attached to the piperidine ring could play an important role in ligand–receptor interactions. These findings may contribute to develop potential NK3receptor antagonists for schizophrenia. [ABSTRACT FROM AUTHOR]

According to WHO statistics, lung cancer is one of the leading causes of death among all other types of cancer. Many genes get mutated in lung cancer but involvement of EGFR and KRAS are more common. Unavailability of drugs or resistance to the available drugs is the major problem in the treatment of lung cancer. In the present research, mTOR was selected as an alternative target for the treatment of lung cancer which involves PI3K/AKT/mTOR pathway. 28 synthetic mTOR inhibitors were selected from the literature. Ligand based approach (CoMFA and CoMSIA) and structure based approach (molecular dynamics simulations assisted molecular docking study) were applied for the identification of important features of benzoxazepine moiety, responsible for mTOR inhibition. Three different alignments were tried to obtain best QSAR model, of which, distil was found to be the best method, as it gave good statistical results. In CoMFA, Leave One Out (LOO) cross validated coefficients ( q 2 ), conventional coefficient ( r 2 ) and predicted correlation coefficient ( r 2 pred ) values were found to be 0.615, 0.990 and 0.930, respectively. Similarly in CoMSIA, q 2 , r 2 ncv and r 2 pred values were found to be 0.748, 0.986 and 0.933, respectively. Molecular dynamics and simulations study revealed that B-chain of mTOR protein was stable at and above 500 FS with respect to temperature (at and above 298 K), Potential energy (at and above 7669.72 kJ/mol) and kinetic energy (at and above 4009.77 kJ/mol). Molecular docking study was performed on simulated protein of mTOR which helped to correlate interactions of amino acids surrounded to the ligand with contour maps generated by QSAR method. Important features of benzoxazepine were identified by contour maps and molecular docking study which would be useful to design novel molecules as mTOR inhibitors for the treatment of lung cancer. [ABSTRACT FROM AUTHOR]

The glucocorticoid receptor (GR) antagonistic activities of hydroxylated polychlorinated biphenyls (HO-PCBs) were recently characterised. To further explore the interactions between HO-PCBs and the GR, and to elucidate structural characteristics that influence the GR antagonistic activity of HO-PCBs, molecular docking and three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed. Comparative molecular similarity indices analysis (CoMSIA) was performed using both ligand- and receptor-based alignment schemes. Results generated from the receptor-based model were found to be more satisfactory, withq2of 0.632 andr2of 0.931 compared with those from the ligand-based model. Some internal validation strategies (e.g. cross-validation analysis, bootstrapping analysis and Y-randomisation) and an external validation method were used respectively to further assess the stability and predictive ability of the derived model. Graphical interpretation of the model provided some insights into the structural features that affected the GR antagonistic activity of HO-PCBs. Molecular docking studies revealed that some key residues were critical for ligand–receptor interactions by forming hydrogen bonds (Glu540) and hydrophobic interactions with ligands (Ile539, Val543 and Trp577). Although CoMSIA sometimes depends on the alignment of the molecules, the information provided is beneficial for predicting the GR antagonistic activities of HO-PCB homologues and is helpful for understanding the binding mechanisms of HO-PCBs to GR. [ABSTRACT FROM PUBLISHER]

Based on the experimental data of octanol-air partition coefficients ( K OA ) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using log K OA values as the dependent variable with the Sybyl software to predict the K OA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient ( q 2 ) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825–0.969 (>0.5), the correlation coefficient ( r 2 ) obtained was in the range of 0.957–1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070–0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the log K OA . The correlation analysis of the relationship between the number of Cl atoms and the average log K OA values of PCBs indicated that log K OA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher log K OA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, log K OA decreased when substituents possessed electropositive groups at the 2-, 3-, 3′-, 5- and 6- positions, which could reduce the PCB migration ability. These results are expected to be beneficial in predicting log K OA values of PCB homologues and derivatives and in providing a theoretical foundation for further elucidation of the global migration behaviour of PCBs. [ABSTRACT FROM AUTHOR]

HIV integrase enzyme is well established potential target for antiretroviral therapy since a decade. Resistance to drugs (Raltegravir and Elvitegravir) used as HIV integrase inhibitors is already been identified and there is an urgent need to discover newer molecules which can overcome this issue. With this aim, ligand based drug design technique, 3D-QSAR, was carried out on a series of 5-hydroxy-6-oxo-1,6-dihydropyrimidine-4-carboxamide derivatives as HIV-1 integrase inhibitors. CoMFA and CoMSIA approaches were used for this study. The total dataset of 35 derivatives were divided into training set (28) and test set (7) in 80:20 ratio. In CoMFA model, the cross validated q 2 and the non-cross validated r 2 value for training set were found as 0.683 and 0.988, respectively; while in CoMSIA model, q 2 value was 0.707 and r 2 value was 0.989. Further the most active compound 3 was docked into binding site of integrase enzyme using SurFlex-Dock. The CoMFA and CoMSIA contour maps, MOLCAD-generated surface maps of binding site and docking poses were found complimentary with each other in terms of electrostatic, lipophilicity, and hydrogen-bonding potential. These results were used to design novel quinoxaline derivatives as HIV-1 integrase inhibitors which could be explore in future to identify novel HIV-1 integrase inhibitors. [ABSTRACT FROM AUTHOR]

Aurora-B kinase plays a crucial role in cell cycle events and is identified as an important factor in regulation of spindle check point assembly. Thus, it can be proved as an important target in the field of oncology. 3D-QSAR model was generated using 54 molecules reported in literature containing thienopyrimidine and thienopyridine as scaffolds. All molecules were aligned using Distill function in Sybyl X1.2. This generated best model of CoMFA-RG (Region focusing) and CoMSIA were statistically significant with correlation coefficient r 2 ncv of 0.97, for both & Leave one out coefficient (LOO) q 2 of 0.70 and 0.72, respectively. Best CoMSIA model was built up using various combination of descriptors and proved statistical significant among all models. Best CoMFA-RG and CoMSIA models were validated by 12 test set molecules giving satisfactory prediction ( r 2 pred ) values of 0.86 and 0.88, respectively. External test set validation was performed using 20 molecules and satisfactory prediction of their biological activity was found. Active compounds were docked on protein (PDB ID: 4C2V ) by GOLD module and revealed important interactions with amino acids at ATP-binding region. These data explored insight requirements for Aurora-B inhibition which might be fruitful for understanding mechanisms with kinase ligand interactions. [ABSTRACT FROM AUTHOR]

A major problem today is bacterial resistance to antibiotics and the small number of new therapeutic agents approved in recent years. The development of new antibiotics capable of acting on new targets is urgently required. The filamenting temperature-sensitive Z (FtsZ) bacterial protein is a key biomolecule for bacterial division and survival. This makes FtsZ an attractive new pharmacological target for the development of antibacterial agents. There have been several attempts to develop ligands able to inhibit FtsZ. Despite the large number of synthesized compounds that inhibit the FtsZ protein, there are no quantitative structure–activity relationships (QSAR) that allow for the rational design and synthesis of promising new molecules. We present the first 3D-QSAR study of a large and diverse set of molecules that are able to inhibit the FtsZ bacterial protein. We summarize a set of chemical changes that can be made in the steric, electrostatic, hydrophobic and donor/acceptor hydrogen-bonding properties of the pharmacophore, to generate new bioactive molecules against FtsZ. These results provide a rational guide for the design and synthesis of promising new antibacterial agents, supported by the strong statistical parameters obtained from CoMFA (r2pred= 0.974) and CoMSIA (r2pred= 0.980) analyses. [ABSTRACT FROM AUTHOR]

Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q 2 value of 0.792 and an r 2 value of 0.985. The best CoMSIA model predicted a q 2 value of 0.633 and an r 2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients ( r pred 2 ) of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted. [ABSTRACT FROM AUTHOR]

The development of resistant malaria and lethality of the disease demands the search for new therapeutic candidates. In this line-up, thiolactone was identified as the potential lead structure and subjected to hologram quantitative structure–activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Overall, the QSAR results shows that the LOO cross-validatedq2values of HQSAR, CoMFA and CoMSIA models are 0.791, 0.737 and 0.753, respectively. According to HQSAR, the hydrogen bond donor and acceptor were found to play an important role in governing antimalarial activity of thiolactone derivatives. The fragment contribution map of HQSAR, and contour maps of CoMFA and CoMSIA showed the presence of an electronegative group at the fifth position, and a bulky group at the third and fourth positions of the thiolactone ring, positively contributing to antimalarial activity. Furthermore, molecular docking was performed to analyze the binding mode of newly designed thiolactones with the active site residues ofpfKAS I/II. The prediction of newly designed thiolactone molecules based on QSAR and docking score are in good accordance with each other. Therefore the ligand-based QSAR models and target structure-based docking model developed in this study may be successfully utilized for the design of new antimalarial agents. [ABSTRACT FROM AUTHOR]

Antimitotic agents are potential compounds for the treatment of breast cancer. Cytotoxicity is one of the parameters required for anticancer activity. A validated comparative molecular modeling study was performed on a set of phenylindole derivatives through R-group QSAR (RQSAR), regression-based and linear discriminant analysis (LDA)-based 2D QSAR studies and kernel-based partial least square (KPLS) analyses as well as CoMSIA 3D-QSAR study. Antiproliferative activities against two breast cancer cell lines (MDA-MB-231 and MCF7) were separately used as dependent variables. The RQSAR analysis highlighted different E-state indices and pharmacophoric requirements of important substitutions. The best 2D-QSAR model is established on the basis of three machine learning tools – MLR, SVM and ANN. The 2D-QSAR models depicted importance of different structural, physicochemical and topological descriptors. While RQSAR analyses demonstrated the fingerprint requirements of various substitutions, the KPLS analyses showed these requirements for the entire molecule. The CoMSIA model further refines these interpretations and reveals how subtle variations in these structures may influence biological activities. Observations of different modeling techniques complied with each other. The current QSAR study may be used to design potential antimitotic agents. It also demonstrates the utilities of different molecular modeling tools to elucidate the SAR. [ABSTRACT FROM AUTHOR]

The quinoline moiety is one of the widely studied scaffolds for generating derivatives with various pharmacophoric groups due to its potential antimalarial activities. In the present study, a series of 7-substituted-4-aminoquinoline derivatives were selected to understand their antimalarial properties computationally by molecular modeling techniques including 2D QSAR, comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and molecular docking. The 2D-QSAR model built with four descriptors selected by genetic algorithm technique and CoMFA model showed satisfactory statistical results ( Q 2 = 0.540, R 2 ncv = 0.881, F value = 157.09). A reliable CoMSIA model out of the fourteen different combinations has a Q 2 value of 0.638. The molecular docking studies of the compounds for 1CET as the protein target revealed that ten compounds showed maximum interactions with the binding site of the protein. The present study highlights the unique binding signatures of the ligands within the active site groove of the target and it explains the subtle differences in their EC 50 values and their mechanism of inhibition. [ABSTRACT FROM AUTHOR]

Interleukin-2 is an essential cytokine in an innate immune response, and is a promising drug target for several immunological disorders. In the present study, structure-based 3D-QSAR modeling was carried out via Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) methods. Six different partial charge calculation methods were used in combination with two different alignment methods to scrutinize their effects on the predictive power of 3D-QSAR models. The best CoMFA and CoMSIA models were obtained with the AM1 charges when used with co-conformer based substructure alignment (CCBSA) method. The obtained models posses excellent correlation coefficient value and also exhibited good predictive power (for CoMFA: q 2 = 0.619; r 2 = 0.890; r 2 Pred = 0.765 and for CoMSIA: q 2 = 0.607; r 2 = 0.884; r 2 Pred = 0.655). The developed models were further validated by using a set of another sixteen compounds as external test set 2 and both models showed strong predictive power with r 2 Pred = >0.8. The contour maps obtained from these models better interpret the structure activity relationship; hence the developed models would help to design and optimize more potent IL-2 inhibitors. The results might have implications for rational design of specific anti-inflammatory compounds with improved affinity and selectivity. [ABSTRACT FROM AUTHOR]

Ligand-based and structure-based methods were applied in combination to exploit the physicochemical properties of 2,3-dideoxy hex-2-enopyranosid-4-uloses against Mycobacterium tuberculosis H37Rv. Statistically valid 3D-QSAR models with good correlation and predictive power were obtained with CoMFA steric and electrostatic fields ( r 2 = 0.797, q 2 = 0.589) and CoMSIA with combined steric, electrostatic, hydrophobic and hydrogen bond acceptor fields ( r 2 = 0.867, q 2 = 0.570) based on training set of 33 molecules with predictive r 2 of 0.808 and 0.890 for CoMFA and CoMSIA respectively. The results illustrate the requirement of optimal alkyl chain length at C-1 position and acceptor groups along hydroxy methyl substituent of C-6 to enhance the anti-tubercular activity of the 2,3-dideoxy hex-2-enopyranosid-4-uloses while any substitution at C-3 position exert diminishing effect on anti-tubercular activity of these enulosides. Further, homology modeling of M. tuberculosis alpha-mannosidase followed by molecular docking and molecular dynamics simulations on co-complexed models were performed to gain insight into the rationale for binding affinity of selected inhibitors with the target of interest. The comprehensive information obtained from this study will help to better understand the structural basis of biological activity of this class of molecules and guide further design of more potent analogues as anti-tubercular agents. [ABSTRACT FROM AUTHOR]

The anti-influenza virus activities of 50 resveratrol ( RV: 3, 5, 4′-trihydroxy-trans-stilbene) derivatives were evaluated using a neuraminidase ( NA) activity assay. The results showed that 35 compounds exerted an inhibitory effect on the NA activity of the influenza virus strain A/ PR/8/34 ( H1 N1) with 50% inhibitory concentration ( IC50) values ranging from 3.56 to 186.1 μ m. Next, the 35 RV derivatives were used to develop 3 D quantitative structure-activity relationship (3 D QSAR) models for understanding the chemical-biological interactions governing their activities against NA. The comparative molecular field analysis (Co MFA r2 = 0.973, q2 = 0.620, q test2 = 0.661) and the comparative molecular similarity indices analysis (Co MSIA r2 = 0.956, q2 = 0.610, q test2 = 0.531) were applied. Afterward, molecular docking was performed to study the molecular interactions between the RV derivatives and NA. Finally, a cytopathic effect ( CPE) reduction assay was used to evaluate the antiviral effects of the RV derivatives in vitro. Time-of-addition studies demonstrated that the RV derivatives might have a direct effect on viral particle infectivity. Our results indicate that the RV derivatives are potentially useful antiviral compounds for new drug design and development for influenza treatment. [ABSTRACT FROM AUTHOR]

Selective thyroid hormone receptor β (TRβ) binding over TRα is an important requirement for improved therapeutic profile of TRβ agonists. Since selective compounds might be tolerated at doses that lead to complete binding without side effects, thus a selectivity study is valuable. Initially, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed on a series of agonists of TRβ and TRα, respectively. These models produced statistically significant results: TRβ-CoMFA ( R cv 2 , R pred 2 : 0.634, 0.6825), TRβ-CoMSIA ( R cv 2 , R pred 2 : 0.711, 0.5622), TRα-CoMFA ( R cv 2 , R pred 2 : 0.602, 0.5384) and TRα-CoMSIA ( R cv 2 , R pred 2 : 0.674, 0.5078). These cross-validated results suggest that the developed models have excellent internal and external predictability and consistency. To further explore the origin of the selectivity at the amino acid residue level, the comparison between molecular docking and contour maps was conducted, it is revealed that steric, electrostatic and hydrogen bonding interactions play critical roles on selectivity; and Arg316, Arg282, Asn331, His435 for TRβ, Arg228, Arg262, Ser277, His381 for TRα are the significant residues, an in-depth comparative investigation suggests that the single different amino acid Asn331/Ser277 in the ligand binding pocket mainly introduce the ligand selectivity. All these analyses provide valuable information for better understand the mechanism of ligand–receptor interaction and facilitate structural modifications of the agonists to increase activity and selectivity. [ABSTRACT FROM AUTHOR]