3D-QSAR Analysis of Naphthyltriazole(Lesinurad) Analogs as Potent Inhibitors of Urate Transporter 1

To obtain useful information for identifying inhibitors of urate transporter 1(URAT1), three-dimensional quantitative structure-activity relationship(3 D-QSAR) analysis was conducted for a series of lesinurad analogs via Topomer comparative molecular field analysis(CoMFA). A 3 D-QSAR model was established using a training set of 51 compounds and externally validated with a test set of 17 compounds. The Topomer CoMFA model obtained(q^2 = 0.976, r2 = 0.990) was robust and satisfactory. Subsequently, seven compounds with significant URAT1 inhibitory activity were designed according to the contour maps produced by the Topomer CoMFA model.     

CoMFA 3D-QSAR Analysis of Epothilones Based on Docking Conformation and Alignment

Epothilones belong to a class of novel microtubule stabilizing and anti-mitotic agents, which have a paclitaxel-like mechanism of action. A three-dimensional quantitative structure-activity relationship （3D-QSAR） model was built for epothilones by the method of comparative molecular field analysis （CoMFA） combined with the flexible docking technology. The docking CoMFA model gave a good cross-validated value of q2=0.784 with an optimized component of 6 and the conventional correlation coefficient of r^2=0.985. The statistical results show that the model has good ability to predict the activity of the studied compounds. At last, the docking CoMFA model was analyzed through contour maps complemented with MOLCAD-generated active site potential surface in the α,β-tubulin receptor, which can provide important information for the structure-based drug design.     

Three-dimensional Quantitative Structure-Activity Relationship Analyses of a Series of Butenolide ETA Antagonists

Two kinds of Three-dimensional Quantitative Structure-activity Relationship(3D-QSAR) methods,comparative molecular filed analysis(CoMFA) and comparative molecular similarity indices analysis (CoMSIA) ,were applied to analyze the structure-activity relationship of a series of 63 butenolide ETA selective antagonists with respect to their inhibition against human ETA receptor,The CoMFA and CoMSIA models were developed for the conceivable alignment of the molecules based on a template structure from the crystallized data.The statistical results from the initial orientation of the aligned molecules show that the 3D-QSAR model from CoMFA(q^2=0.543) is obviously superior to that from the conventional CoMSIA(q^2=0.407).In order to refine the model,all-space search (ASS) was applied to minimize the field sampling process.By rotating and translating the molecular aggregate within the grid systematically,all the possible samplings of the molecular fields were tested and subsequently the one with the highest q^2 was picked out .The comparison of the sensitivity of CoMFA and CoMSIA to different space orientation shows that the CoMFA q^2 values are more sensitive to the translations and rotations of the aligned molecules with respect to the lattice than those of CoMSIA.The best CoMFA model from ASS was further refined by the region focused technique.The high quality of the best model is indicated by the high corss-validated correlation and the prediction on the external test set.The CoMFA coefficient contour plots identify several key features that explain the wide range of activities,which may help us to design new effective ETA selective antagonists.     

Study on the Three-dimensional Quantitative Structure-activity Relationship of Pyridazinonyl-substituted 1,3,4-Thiadiazoles

The three-dimensional quantitative structure-activity relationships of a series of 5-[ 1-aryl-1,4-dihydro-6-methylpyridazin-4-one-3-yl]-2-arylamino-1,3,4-thiadiazoles, related to the fungicidal activity, were studied using the comparative molecular field analysis （CoMFA）. The results show that the contributions of steric and electrostatic fields to the activity are 0.505 and 0.495, respectively. The cross-validated q^2 and the correlation coefficient r^2 for the model established by the study are 0.769 and 0.938, respectively, with the F value of 60.996, and the standard deviation s of 0.074. These values indicate that the model is significant and has good predictability. The analysis results are in good agreement well with the study of 2D-QSAR, and offered important structural insights into designing highly active compounds prior to synthesis.     

Synthesis and in vitro Study of Novel Methylenebis(phenyl- 1,5-benzothiazepine)s and Methylenebis(benzofuryl-1,5- benzothiazepine)s as Antimicrobial Agents

A series of methylenebis(phenyl-1,5-benzothiazepine)s 4 and methylenebis(benzofuryl-1,5-benzothiazepine)s 5 were prepared by the reaction of methylene-bis-chalcones 3 with 2-aminothiophenol for 4 and followed by the condensation with chloroacetone for 5. The structures of the synthesized compounds have been confirmed by their IR, 1H NMR, 13C NMR, MS and elemental analyses. All the synthesized compounds were tested for their antimicrobial activity against Gram-positive, Gram-negative bacteria and fungi. To elucidate the essential structural requirements for the antimicrobial activity, the preliminary structure-activity relationship has been described. Among the compounds tested, the dimeric compounds 4f, 4g, 5f and 5g were found to be most active against Bacillus subtilis, Bacillus sphaericus, Staphylococcus aureus, Klebsiella aerogenes and Chromobacterium violaceum. Similarly these dimeric compounds showed potent antifungal activity against Candida albicans, Aspergillus fumigatus, Trichophyton rubrum, and Trichophyton mentagrophytes. It is interesting to note that the dimeric compounds with substituents of heterocyclic ring at the 4th position of benzothiazepine system displayed notable antibacterial activity equal to that of streptomycin and penicillin. Further, the activity of all the dimeric compounds was compared with that of their monomeric compounds, and it is interesting to note that almost all the dimeric compounds showed enhanced activity than their monomeric compounds.     

Comparative Molecular Field Analysis （CoMFA） of Curcumin-related Compounds for Anticancer Activity

Three-dimensional （3D） quantitative structure-activity relationship （QSAR） studies of 44 curcumin-related compounds have been carried out based on our previously reported result for their anticancer activity against pancreas cancer Panc-I cells and colon cancer HT-29 cells. The established 3D-QSAR models from the comparative molecular field analysis （CoMFA） in training set showed not only significant statistical quality, but also satisfying predictive ability, with high correlation coefficient values （R12= 0.911, R22= 0.985） and cross-validation coefficient values （q2= 0.580, q22= 0.722）. Based on the CoMFA contour maps, some key structural factors responsible for anticancer activity of these series of compounds were revealed. The results provide some useful theoretical references for understanding the mechanism of action, designing new curcumin-related compounds with anticancer activity and predicting their activities prior to synthesis.     

Molecular Modeling and Design of Arylthioindole Derivatives as Tubulin Inhibitors

Three-dimensional quantitative structure activity relationship （3D-QSAR） and docking studies of a series of arylthioindole derivatives as tubulin inhibitors against human breast cancer cell line MCF-7 have been carried out. An optimal 3D-QSAR model from the comparative molecular field analysis （CoMFA） for training set with significant statistical quality （R2=0.898） and predictive ability （q2=0.654） was established. The same model was further applied to predict pIC50 values of the compounds in test set, and the resulting predictive correlation coefficient R2（pred） reaches 0.816, further showing that this CoMFA model has high predictive ability. Moreover, the appropriate binding orientations and conformations of these compounds interacting with tubulin are located by docking study, and it is very interesting to find the consistency between the CoMFA field distribution and the 3D topology structure of active site of tubulin. Based on CoMFA along with docking results, some important factors improving the activities of these compounds were discussed in detail and were summarized as follows： the substituents R3-R5 （on the phenyl ring） with higher electronegativity, the substituent R6 with higher eleetropositivity and bigger bulk, the substituent R7 with smaller bulk, and so on. In addition, five new compounds with higher activities have been designed. Such results can offer useful theoretical references for experimental works.     

Acrosin structure-based design,synthesis and biological activities of 7-azaindol derivatives as new acrosin inhibitors

A series of 7-azaindol derivatives were designed based on the homologous 3D model of human acrosin.These compounds were synthesized and evaluated for their human acrosin inhibitory activities in vitro.Compounds 7a,7i,7j,7k and 7n showed highly inhibitory activity against human acrosin.The three-dimensional structure-activity relationship was investigated through a CoMFA model,which provided valuable information to further study of potential human acrosin inhibitors.     

3D-QSAR Study on Diindolylmethane and Its Analogues with Comparative Molecular Field Analysis (CoMFA)

ＩｎｔｒｏｄｕｃｔｉｏｎＢｒｅａｓｔｃａｎｃｅｒｉｓｏｎｅｏｆｔｈｅｌｅａｄｉｎｇｃａｕｓｅｓｏｆｐｒｅｍａｔｕｒｅｄｅａｔｈｉｎＮｏｒｔｈＡｍｅｒｉｃａｎｗｏｍｅｎ .Ｉｔｉｓａｎｅｓｔｒｏｇｅｎ ｄｅｐｅｎｄｅｎｔｃａｎｃｅｒ,1ｗｈｅｒｅｖａｒｉｏｕｓａｎｔｉｅｓｔｒｏｇｅｎｈａｖｅｂｅｅｎｅｘｔｅｎｓｉｖｅｌｙｄｅ ｖｅｌｏｐｅｄｆｏｒｉｔｓｔｒｅａｔｍｅｎｔ,ｓｕｃｈａｓｂｅｎｚｏｔｈｉｏｐｈｅｎｅ ,ｐｒｏｇｅｓ ｔｅｒｏｎｅ,ａｎｄｔｈｅｃｕｒｒｅｎｔｔａｍｏｘｉｆｅｎ ,ｗｈｉｃｈｐｒｉｍａ…     

Molecular modeling studies of human immunodeficiency virus type 1 protease inhibitors using three‐dimensional quantitative structure‐activity relationship,virtual screening,and docking simulations

In this paper, two 3‐dimensional quantitative structure‐activity relationship models for 60 human immunodeficiency virus (HIV)‐1 protease inhibitors were established using random sampling analysis on molecular surface and translocation comparative molecular field vector analysis (Topomer CoMFA). The non–cross‐validation (r²), cross‐validation (q²), correlation coefficient of external validation (Q²_ext), and F of 2 models were 0.94, 0.80, 0.79, and 198.84 and 0.94, 0.72, 0.75, and 208.53, respectively. The results indicated that 2 models were reasonable and had good prediction ability. Topomer Search was used to search R groups in the ZINC database, 20 new compounds were designed, and the Topomer CoMFA model was used to predicate the biological activity. The results showed that 18 new compounds were more active than the template molecule. So the Topomer Search is effective in screening and can guide the design of new HIV/AIDS drugs. The mechanism of action was studied by molecular docking, and it showed that the protease inhibitors and Ile50, Asp25, and Arg8 sites of HIV‐1 protease have interactions. These results have provided an insight for the design of new potent inhibitors of HIV‐1 protease.     

Docking-based CoMFA and CoMSIA study of azaindole carboxylic acid derivatives as promising HIV-1 integrase inhibitors

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed based on a series of azaindole carboxylic acid derivatives that had previously been reported as promising HIV-1 integrase inhibitors. Docking studies to explore the binding mode were performed based on the highly active molecule 36. The best docked conformation of molecule 36 was used as template for alignment. The comparative molecular field analysis (CoMFA) model (including steric and electrostatic fields) yielded the cross validation q ² = 0.655, non-cross validation r ² = 0.989 and predictive r ² _pred = 0.979. The best comparative molecular similarity indices analysis (CoMSIA) model (including steric, electrostatic, hydrophobic and hydrogen-bond acceptor fields) yielded the cross validation q ² = 0.719, non-cross validation r ² = 0.992 and predictive r ² _pred = 0.953. A series of new azaindole carboxylic acid derivatives were designed and the HIV-1 integrase inhibitory activities of these designed compounds were predicted based on the CoMFA and CoMSIA models.     

QSAR models of cytochrome P450 enzyme 1A2 inhibitors using CoMFA,CoMSIA and HQSAR

Quantitative structure–activity relationship (QSAR) studies were conducted on an in-house database of cytochrome P450 enzyme 1A2 inhibitors using the comparative molecular field analysis (CoMFA), comparative molecular similarity analysis (CoMSIA) and hologram QSAR (HQSAR) approaches. The database consisted of 36 active molecules featuring varied core structures. The model based on the naphthalene substructure alignment incorporating 19 molecules yielded the best model with a CoMFA cross validation value q² of 0.667 and a Pearson correlation coefficient r² of 0.976; a CoMSIA q² value of 0.616 and r² value of 0.985; and a HQSAR q² value of 0.652 and r² value of 0.917. A second model incorporating 34 molecules aligned using the benzene substructure yielded an acceptable CoMFA model with q² value of 0.5 and r² value of 0.991. Depending on the core structure of the molecule under consideration, new CYP1A2 inhibitors will be designed based on the results from these models.     

Comparative molecular field analysis and comparative molecular similarity index analysis studies on 1H NMR chemical shift of NH group of diaryl triazene derivatives

Comparative molecular field analysis (CoMFA), comparative molecular field analysis region focusing (CoMFA‐RF) for optimizing the region for the final partial least square analysis, and comparative molecular similarity indices analysis (CoMSIA) methods were employed to develop three‐dimensional quantitative structure–activity relationship (3D‐QSAR) models of ¹H NMR chemical shift of NH proton of diaryl triazene derivatives. The best orientation was searched by all‐orientation search (AOS) strategy to minimize the effect of the initial orientation of the structures. The predictive abilities of CoMFA‐RF and CoMSIA models were determined using a test set of ten compounds affording predictive correlation coefficients of 0.721 and 0.754, respectively, indicating good predictive power. For further model validation, cross validation (leave one out), progressive scrambling, and bootstrapping were also applied. The accuracy and speed of obtained 3D‐QSAR models for the prediction of ¹H NMR chemical shifts of NH group of diaryl triazene derivatives were greater compared to some computational well‐known procedures. Copyright © 2013 John Wiley & Sons, Ltd.     

3D CoMFA,CoMSIA, topomer CoMFA and HQSAR studies on aromatic acid esters for carbonic anhydrase inhibitory activity

Molecular modelling studies [comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), topomer CoMFA and hologram quantitative structure–activity relationship (HQSAR)] have been performed on the series of 28 molecules belonging to the series of aromatic acid ester derivatives for their carbonic anhydrase inhibitory activity. The model exhibited good correlation coefficient (r²) and cross‐validated correlation coefficient (q²) for CoMFA, CoMSIA and HQSAR methods. On the basis of the findings from all these studies, a structure–activity relationship was established. Copyright © 2013 John Wiley & Sons, Ltd.     

Using the QSPR Approach for Estimating the Density of Azole‐based Energetic Compounds

The relationship between density of energetic azole‐based compounds and their molecular structure is investigated through quantitative structure‐property relationship (QSPR) approach. The methodology of this work introduces a new model, which related density of azole‐based energetic compounds to the optimum elemental composition, the degree of unsaturation (DoU) of the compounds, presence of nitroimino group in the structural formula, as well as several non‐additive structural parameters. The presence of nitroimino functional group and also increasing the value of n_O/n_N in the formula of these compounds can enhance their density. The correlation is derived on the basis of experimental density values of 100 azole‐based energetic compounds with different molecular structure as training set. The determination coefficient of the new correlation is 0.923. Also, it has the root mean square deviation (RMSD) and the average absolute deviation (AAD) of 0.038 and 0.030 g · cm^–3, respectively. In addition, the correlation gives good predictions for further 25 azole‐based energetic compounds as test set (Q²_EXT = 0.901). The predictive ability of the correlation is checked using a cross validation method (Q²_LMO = 0.918). The proposed method can also apply for designing novel azole‐based energetic compounds.