Molecular modeling studies,synthesis and biological evaluation of dabigatran analogues as thrombin inhibitors

In this work, 48 thrombin inhibitors based on the structural scaffold of dabigatran were analyzed using a combination of molecular modeling techniques. We generated three-dimensional quantitative structure–activity relationship (3D-QSAR) models based on three alignments for both comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) to highlight the structural requirements for thrombin protein inhibition. In addition to the 3D-QSAR study, Topomer CoMFA model also was established with a higher leave-one-out cross-validation q² and a non-cross-validation r², which suggest that the three models have good predictive ability. The results indicated that the steric, hydrophobic and electrostatic fields play key roles in QSAR model. Furthermore, we employed molecular docking and re-docking simulation explored the binding relationship of the ligand and the receptor protein in detail. Molecular docking simulations identified several key interactions that were also indicated through 3D-QSAR analysis. On the basis of the obtained results, two compounds were designed and predicted by three models, the biological evaluation in vitro (IC₅₀) demonstrated that these molecular models were effective for the development of novel potent thrombin inhibitors.     

3D-QSAR and molecular docking studies of benzaldehyde thiosemicarbazone, benzaldehyde, benzoic acid, and their derivatives as phenoloxidase inhibitors

Phenoloxidase (PO), also known as tyrosinase, is a key enzyme in insect development, responsible for catalyzing the hydroxylation of tyrosine into o-diphenols and the oxidation of o-diphenols into o-quinones. Inhibition of PO may provide a basis for novel environmentally friendly insecticides. In the present study, we determined the inhibitory activities and IC50 values of 57 compounds belonging to the benzaldehyde thiosemicarbazone, benzaldehyde, and benzoic acid families against phenoloxidase from Pieris rapae (Lepidoptera) larvae. In addition, the inhibitory kinetics of 4-butylbenzaldehyde thiosemicarbazone against PO was measured in air-saturated solutions for the oxidation of L-3,4-dihydroxyphenylalanine (L-DOPA). The results indicated that the compound is a reversible noncompetitive inhibitor. The bioactivity results were used to construct three-dimensional quantitative structure-activity relationship (3D-QSAR) models using two molecular field analysis techniques: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). After carrying out superimposition using common substructure-based alignment, robust and predictive 3D-QSAR models were obtained from CoMFA (q2=0.926, r2=0.986) and CoMSIA (q2=0.933, r2=0.984) with six optimum components. The 3D-QSAR model built here will provide hints for the design of novel PO inhibitors. The molecular interactions between the ligands and the target were studied using a flexible docking method (FlexX). The best scored candidates were docked flexibly, and the interaction between the representative compound 4-butylbenzaldehyde thiosemicarbazone and the active site was elucidated in detail.     

Synthesis and biological validation of novel pyrazole derivatives with anticancer activity guided by 3D-QSAR analysis

Using literature data on anticancer activity of pyrazole derivatives, 3D-QSAR models were developed and 3D-QSAR analysis was performed. The 3D-QSAR analysis enabled identification of molecular properties that have the highest impact on antitumor activity against lung cancer cells. The results of 3D-QSAR analysis were taken into account while new compounds were designed. Obtained 3D-QSAR models were used for prediction of activity of new compounds. In this way, design of new compounds was guided by 3D-QSAR analysis which was performed on literature data. Ten new pyrazole derivatives were synthesised and their antitumor activities against A549 and NCIH23 lung cancer cells were validated. In order to obtain full profile of anticancer activity, cells viability (MTS) assays were combined with cell proliferation (BrdU) assays which measure actively dividing cells in treated sample. Experimental measurements showed good agreement between predicted and measured activities for majority of compounds. Also, anticancer activities of new pyrazole derivatives pointed to the chemical groups that can be useful in designing antitumor molecules. Substitution of hydrazine linker with rigid, 1,2,4-oxadiazole moiety resulted in compound 10, which has low (if any) cytotoxic activity and high potential cytostatic activity. Therefore, compound 10 presents a good starting point for design of new, more potent and safer anticancer therapeutics.     

Computer-aided design, synthesis and biological assay of p-methylsulfonamido phenylethylamine analogues

Class III antiarrhythmic agents selectively delay the effective refractory period (ERP) and increase the transmembrance action potential duration (APD). Based on our previous studies, a set of 17 methylsulfonamido phenylethylamine analogues were investigated by 3D-QSAR techniques of CoMFA and CoMSIA. The 3D-QSAR models proved a good predictive ability, and could describe the steric, electrostatic and hydrophobic requirements for recognition forces of the receptor site. According to the clues provided by this 3D-QSAR analysis, we designed and synthesized a series of new analogues of methanesulfonamido phenylethylamine (VIa-i). Pharmacological assay indicated that the effective concentrations of delaying the functional refractory period (FRP) 10ms of these new compounds have a good correlation with the 3D-QSAR predicted values. It is remarkable that the maximal percent change of delaying FRP in microM of compound VIc is much higher than that of dofetilide. The results showed that the 3D-QSAR models are reliable.     

Structure-based approach to pharmacophore identification, in silico screening, and three-dimensional quantitative structure-activity relationship studies for inhibitors of Trypanosoma cruzi dihydrofolate reductase function

We have employed a structure-based three-dimensional quantitative structure-activity relationship (3D-QSAR) approach to predict the biochemical activity for inhibitors of T. cruzi dihydrofolate reductase-thymidylate synthase (DHFR-TS). Crystal structures of complexes of the enzyme with eight different inhibitors of the DHFR activity together with the structure in the substrate-free state (DHFR domain) were used to validate and refine docking poses of ligands that constitute likely active conformations. Structural information from these complexes formed the basis for the structure-based alignment used as input for the QSAR study. Contrary to indirect ligand-based approaches the strategy described here employs a direct receptor-based approach. The goal is to generate a library of selective lead inhibitors for further development as antiparasitic agents. 3D-QSAR models were obtained for T. cruzi DHFR-TS (30 inhibitors in learning set) and human DHFR (36 inhibitors in learning set) that show a very good agreement between experimental and predicted enzyme inhibition data. For crossvalidation of the QSAR model(s), we have used the 10% leave-one-out method. The derived 3D-QSAR models were tested against a few selected compounds (a small test set of six inhibitors for each enzyme) with known activity, which were not part of the learning set, and the quality of prediction of the initial 3D-QSAR models demonstrated that such studies are feasible. Further refinement of the models through integration of additional activity data and optimization of reliable docking poses is expected to lead to an improved predictive ability.     

Developing consensus 3D-QSAR and pharmacophore models for several beta-secretase,farnesyl transferase and histone deacetylase inhibitors

Three consensus 3D-QSAR (c-3D-QSAR) models were built for 38, 34, and 78 inhibitors of β-secretase, histone deacetylase, and farnesyltransferase, respectively. To build an individual 3D-QSAR model, the structures of an inhibitor series are aligned through docking of a protein receptor into the active site using the program GOLD. CoMFA, CoMSIA, and Catalyst are then performed for the training set of each structurally aligned inhibitor series to obtain a 3D-QSAR model. Since the consensus in features identified is high for the same pharmacophore features selected for building a 3D-QSAR model by a 3D-QSAR method, a c-3D-QSAR model for each inhibitor series is constructed by combining the pharmacophore features selected for building the 3D-QSAR model using the SYBYL spread sheet and PLS module. Each c-3D-QSAR pharmacophore model built was examined visually and compared with that obtained by simultaneous mapping of the corresponding 3D-QSAR pharmacophores built onto a selected inhibitor structure. It was found that the c-3D-QSAR model built for an inhibitor series improves not only the overall prediction statistics for both training and test sets but also the prediction accuracy for some less active inhibitors of the series.     

Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1

Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r2, q2(loo) and r2(pred) values. To obtain a consensus for predictive ability from all the models, average regression coefficient r2(avg) was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.     

Predicting the potency of hERG K<Superscript>+</Superscript> channel inhibition by combining 3D-QSAR pharmacophore and 2D-QSAR models

Blockade of the hERG K⁺ channel has been identified as the most important mechanism of QT interval prolongation and thus inducing cardiac risk. In this work, an ensemble of 3D-QSAR pharmacophore models was constructed to provide insight into the determinants of the interactions between the hERG K⁺ channel and channel inhibitors. To predict hERG inhibitory activities, the predicted values from the ensemble of models were averaged, and the results thus obtained showed that the predictive ability of the combined 3D-QSAR pharmacophore model was greater that those of the individual models. Also, using the same training and test sets, a 2D-QSAR model based on a heuristic machine-learning method was developed in order to analyze the physicochemical characters of hERG inhibitors. The models indicated that the inhibitors have certain key inhibitory features in common, including hydrophobicity, aromaticity, and flexibility. A final model was developed by combining the combined 3D-QSAR pharmacophore with the 2D-QSAR model, and this final model outperformed any other individual model, showing the highest predictive ability and the lowest deviation. This model can not only predict hERG inhibitory potency accurately, thus allowing fast cardiac safety evaluation, but it provides an effective tool for avoiding hERG inhibitory liability and thus enhanced cardiac risk in the design and optimization of new chemical entities.     

Quantitative structure-activity relationship studies on 1-aryl-tetrahydroisoquinoline analogs as active anti-HIV agents

Predictive quantitative structure-activity relationship analysis was developed for a diverse series of recently synthesized 1-aryl-tetrahydroisoquinoline analogs with anti-HIV activities in this study. The conventional 2D-QSAR models were developed by genetic function approximation (GFA) and stepwise multiple linear regression (MLR) with acceptable explanation of 94.9% and 95.5% and good predicted power of 91.7% and 91.7%, respectively. The results of the 2D-QSAR models were further compared with 3D-QSAR model generated by molecular field analysis (MFA), investigating the substitutional requirements for the favorable receptor-drug interaction and quantitatively indicating the important regions of molecules for their activities. The results obtained by combining these methodologies give insights into the key features for designing more potent analogs against HIV.     

New potent 5-substituted benzofuroxans as inhibitors of Trypanosoma cruzi growth: quantitative structure-activity relationship studies

Benzofuroxan derivatives have been shown to inhibit the growth of Trypanosoma cruzi, the etiological agent of Chagas' disease. Therefore, 2D- and 3D-QSAR models of their in vitro antichagasic activity were developed. Six new derivatives were synthesized to complete a final set of 26 structurally diverse benzofuroxans. The 2D-QSAR model (r = 0.939, r(adj)(2) = 0.849) was generated using multiple regression analysis of tabulated substituents' physicochemical properties and indicator variables. In addition, a 3D-QSAR model (r(2) = 0.997, q(2) = 0.802) was obtained using a comparative molecular field analysis (CoMFA). Due to the well-known benzofuroxan tautomerism, in both approaches (2D- and 3D-QSAR) it was necessary to include an indicator variable to consider the N-oxide position (I(6)). This parameter was established using low-temperature NMR experiments. Both QSAR models identified the electrophilic character of the substituent alpha-atom as a requirement for activity. Further support was found using a density functional theory (DFT) approach.     

Structure-activity relationships of a series of tariquidar analogs as multidrug resistance modulators

Tariquidar (XR9576) analogs, modulators of cancer multidrug resistance (MDR), were subjected to QSAR and 3D-QSAR analyses. The structural features contributing to anti-MDR activity were identified by the Free-Wilson analysis and pharmacophore search using Hoechst 33342 as a template. 3D-QSAR CoMFA and CoMSIA models were derived and tested. The best models yielded an external predictivity of 0.66-0.75 squared correlation coefficient and outlined HB-acceptor, steric, and hydrophobic fields as the most important 3D properties. On the basis of the QSAR and 3D-QSAR analyses it was suggested that the strong inhibitory potency of the compounds studied is related to the presence of a bulky aromatic ring system with a 3rd positioned heteroatom toward the anthranilamide nucleus in the opposite end of the tetrahydroquinoline group. The results can help in directing the rational design of new generations of potent P-glycoprotein MDR modulators.     

Molecular docking and 3D-QSAR studies of Yersinia protein tyrosine phosphatase YopH inhibitors

Three-dimensional quantitative structure-activity relationship (QSAR) studies were conducted on two classes of recently explored compounds with known YopH inhibitory activities. Docking studies were employed to position the inhibitors into the YopH active site to determine the probable binding conformation. Good correlations between the predicated binding free energies and the inhibitory activities were found for two subsets of phosphate mimetics: alpha-ketocarboxylic acid and squaric acid (R2=0.70 and 0.68, respectively). The docking results also provided a reliable conformational alignment scheme for 3D-QSAR modeling. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed based on the docking conformations, giving q2 of 0.734 and 0.754 for CoMFA and CoMSIA models, respectively. The 3D-QSAR models were significantly improved after removal of an outlier (q2=0.829 for CoMFA and q2=0.837 for CoMSIA). The predictive ability of the models was validated using a set of compounds that were not included in the training set. Mapping the 3D-QSAR models to the active site of YopH provides new insight into the protein-inhibitor interactions for this enzyme. These results should be applicable to the prediction of the activities of new YopH inhibitors, as well as providing structural implications for designing potent and selective YopH inhibitors as antiplague agents.     

Molecular modeling, design, synthesis, and biological evaluation of novel 3',4'-dicamphanoyl-(+)-cis-khellactone (DCK) analogs as potent anti-HIV agents

Our current studies aimed at developing new potential anti-AIDS drug candidates have focused on the design and synthesis of new DCK analogs with improved molecular water solubility. Based on the structures and biodata of previous DCK analogs, 3D-QSAR studies have been performed which resulted in two reliable computational models, CoMFA and CoMSIA, with r(2) values of 0.995 and 0.987, and q(2) values of 0.662 and 0.657, respectively. In accord with these 3D-QSAR models, 15 new DCK analogs with polar functional groups at the 3-position were subsequently designed, synthesized, and evaluated against HIV-1 replication in H9 and MT4 cell lines. New DCK analogs 3b, 3c, 4b, 4c, 6a, 7c, and 9a showed promising potency with EC(50) values ranging from 0.09 to 0.0002 microM in both assays. Meanwhile, these promising compounds also showed a wide range of predicted logP values from 0.90 to 5.19, which increased the probability of identifying anti-HIV drug candidates from this class of compounds for clinical trials. Furthermore, both experimental and predicted values matched well, corroborating the reliability of the established 3D-QSAR models.     

Three-dimensional quantitative structure-activity relationship (3 D-QSAR) and docking studies on (benzothiazole-2-yl) acetonitrile derivatives as c-Jun N-terminal kinase-3 (JNK3) inhibitors

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for 44 (benzothiazole-2-yl) acetonitrile derivatives, inhibiting c-Jun N-terminal kinase-3 (JNK3). It includes molecular field analysis (MFA) and receptor surface analysis (RSA). The QSAR model was developed using 34 compounds and its predictive ability was assessed using a test set of 10 compounds. The predictive 3D-QSAR models have conventional r2 values of 0.849 and 0.766 for MFA and RSA, respectively; while the cross-validated coefficient r(cv)2 values of 0.616 and 0.605 for MFA and RSA, respectively. The results of the QSAR model were further compared with a structure-based analysis using docking studies with crystal structure of JNK3. Ligands bind in the ATP pocket and the hydrogen bond with GLN155 was found to be crucial for selectivity among other kinases. The results of 3D-QSAR and docking studies validate each other and hence, the combination of both methodologies provides a powerful tool directed to the design of novel and selective JNK3 inhibitors.     

Quantitative structure-activity analysis of 5-arylidene-2,4-thiazolidinediones as aldose reductase inhibitors

Design of aldose reductase (ALR2) inhibitors has received considerable attention. Aldose reductase inhibitors, when administered from the onset of hyperglycemia, prevent the progression of polyol accumulation-linked complications. The feasibility that inhibition of aldose reductase provides a pharmacologically direct treatment for diabetic complications that is independent of the control of blood sugar levels has spurred the development of structurally diverse aldose reductase inhibitors. In this work, we report quantitative structure-activity relationship (QSAR) analysis performed by 3D-QSAR analysis, Hansch analysis, and Fujita-Ban analysis on a series of 5-arylidene-2,4-thiazolidinediones as aldose reductase inhibitors. The 2D & 3D-QSAR models were generated using 18 compounds and Fujita-Ban analysis models were obtained using 23 compounds. The predictive ability of the resulting 2D and 3D models was evaluated against a test set of 5 compounds. Analyses of results from the present QSAR study inferred that 3rd position of the phenyl ring and acetic acid substitution at N-position of thiazolidinediones play a key role in the aldose reductase inhibitory activity.     

旱生香茶菜二萜化合物细胞毒活性的三维构效研究

应用比较分子力场法（COMFA）研究了一系列旱生香茶菜二萜化合物对人红细胞白血病（K562）、人旱幼粒白血病（HL-60）、人胃腺癌（MKN-28）和人结肠癌（HCT）细胞体外抗肿瘤活性进行了三维定量构效关系的初步研究,其结果将为香条菜二萜的结构修饰和简化,先导化合物的发现提供理论依据。     

3D-QSAR studies on thieno[3,2-d]pyrimidines as phosphodiesterase IV inhibitors

Cyclic nucleotide phosphodiesterase IV (PDE IV) inhibitors find utility in asthma and Chronic Obstructive Pulmonary Disease (COPD) therapy. A series of 29 thieno[3,2-d]pyrimidines with affinity for PDE IV was subjected to three dimensional quantitative structure activity relationship (3D-QSAR) studies using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Both CoMFA and CoMSIA provided statistically valid models with good correlative and predictive power. The incorporation of hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields showed insignificant improvement in CoMSIA model. The 3D-QSAR models provide information for predicting the affinity of related compounds and designing more potent inhibitors.