3D QSAR studies on peroxisome proliferator-activated receptor γ agonists using CoMFA and CoMSIA

The peroxisome proliferator-activated receptors (PPARs) have increasingly become attractive targets for developing novel anti-type 2 diabetic drugs. We employed comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) to study three-dimensional quantitative structure–activity relationship (3D QSAR) based on existing agonists of PPAR (including five thiazolidinediones and 74 tyrosine-based compounds). Predictive 3D QSAR models with conventional r² and cross-validated coefficient (q²) values up to 0.974 and 0.642 for CoMFA and 0.979 and 0.686 for COMSIA were established using the SYBYL package. These models were validated by a test set containing 18 compounds. The CoMFA and CoMSIA field distributions are in general agreement with the structural characteristics of the binding pockets of PPAR, which demonstrates that the 3D QSAR models built here are very useful in predicting activities of novel compounds for activating PPAR.      

Active-site characteristics of CYP2C19 and CYP2C9 probed with hydantoin and barbiturate inhibitors

Three series of N-3 alkyl substituted phenytoin, nirvanol, and barbiturate derivatives were synthesized and their inhibitor potencies were tested against recombinant CYP2C19 and CYP2C9 to probe the interaction of these ligands with the active sites of these enzymes. All compounds were found to be competitive inhibitors of both enzymes, although the degree of inhibitory potency was generally much greater towards CYP2C19. Inhibitor stereochemistry did not markedly influence K(i) towards CYP2C9, and log P adequately predicted inhibitor potency for this enzyme. In contrast, stereochemistry was an important factor in determining inhibitor potency towards CYP2C19. (S)-(+)-N-3-Benzylnirvanol and (R)-(-)-N-3-benzylphenobarbital emerged as the most potent and selective CYP2C19 inhibitors, with K(i) values of < 250nM--at least two orders of magnitude greater inhibitor potency than towards CYP2C9. Both inhibitors were metabolized preferentially at their C-5 phenyl substituents, indicating that CYP2C19 prefers to orient the N-3 substituents away from the active oxygen species. These features were incorporated into expanded CoMFA models for CYP2C9, and a new, validated CoMFA model for CYP2C19.     

Reliable structural information for rational design of benzoxazole type potential cholesteryl ester transfer protein (CETP) inhibitors through multiple validated modeling techniques

Abstract

The drug design and discovery of lipid modulators is very demanding as no new molecule has entered into the market in the last 35 years. Cholesteryl ester transfer protein (CETP) is a promising target as lipid modulators. Inhibition of the CETP enzyme reduces the risk of cardiovascular events. The first CETP inhibitor torcetrapib and related drug candidates failed in the clinical trial due to the off-target effects leading to high toxicity. Thus, newer CETP inhibitors have now paramount importance to accelerate the drug discovery efforts in the field of cardiovascular disease (CVD). In the present study, 140 benzoxazole compounds were studied by using different chemometric techniques, for example, pharmacophore mapping, molecular docking, three-dimensional quantitative structure–activity relationship comparative molecular field analysis (3D-QSAR CoMFA), topomer CoMFA and Bayesian classification, in order to generate complete and reliable information regarding the structural requirements for the CETP inhibition. The best pharmacophore hypothesis was statistically significant (regression coefficient of 0.957 and a lower root mean square of 0.890). Molecular docking study revealed that cyano-substituted compounds form hydrogen bond with targeted macromolecule. The 3D-QSAR CoMFA model also produced a leave-one-out (LOO) cross-validated Q² of 0.527, an R² of 0.853 and an R²_Pred of 0.603. Similarly, two topomer CoMFA models were also statistically significant and reliable in terms of their Q², R² and R²_Pred values. The Bayesian classification study also provided the excellent ROC values of 0.919 and 0.939 for training and test sets, respectively. Overall, this study may help in the rational design of newer benzoxazole type compounds with higher CETP inhibition.

Communicated by Ramaswamy H. Sarma     

An explorative study on potent Gram-negative specific LpxC inhibitors: CoMFA,CoMSIA, HQSAR and molecular docking

Pathogenic Gram-negative bacteria are responsible for nearly half of the serious human infections. Hologram quantitative structure–activity relationships (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) were implemented on a group of 32 of potent Gram-negative LpxC inhibitors. The most effective HQSAR model was obtained using atoms, bonds, donor, and acceptor as fragment distinction. The cross-validated correlation coefficient (q²), non-cross-validated correlation coefficient (r²), and predictive correlation coefficient (r²_Pred) for test set of HQSAR model were 0.937, 0.993, and 0.892, respectively. The generated models were found to be statistically significant as the CoMFA model had (r²?=?0.967, q²?=?0.804, r²_Pred?=?0.827); the CoMSIA model had (r²?=?0.963, q²?=?0.752, r²_Pred?=?0.857). Molecular docking was employed to validate the results of the HQSAR, CoMFA, and CoMSIA models. Based on the obtained information, six new LpxC inhibitors have been designed.     

Molecular docking and CoMFA studies of thiazoloquin(az)olin(on)es as CD38 inhibitors: determination of inhibitory mechanism,pharmacophore interactions,and design of new inhibitors

In this research, molecular docking and 3D-QSAR studies were carried out on a series of 79 thiazoloquin(az)olin(on)es as CD38 inhibitors. Based on docking results, four interactions including hydrogen bonding with main chain of GLU-226 (H-M-GLU-226), Van der Waals interactions with side chain of TRP-125 (V-S-TRP-125), TRP-189 (V-S-TRP-189), and THR-221 (V-S-THR-221) were considered as pharmacological interactions. Active conformation of each ligand was extracted from docking studies and was used for carrying out 3D-QSAR modeling. Comparative molecular field analysis (CoMFA) was performed on CD38 inhibitory activities of these compounds on human and mouse. We developed CoMFA models with five components as optimum models for both data-sets. For human data-set, a model with high predictive power was developed. R², RMSE, and F-test values for training set of this model were .94, .24, and 179.58, respectively, and R² and RMSE for its test set were .92 and .32, respectively. The q² and RMSE values for leave-one-out cross validation test on training set were .78 and .46, respectively, that demonstrate created model is robust. Based on extracted steric and electrostatic contour maps for this model, three inhibitors with pIC₅₀ larger than 8.85 were designed.     

Improved 3D-QSAR CoMFA of the dopamine transporter blockers with multiple conformations using the genetic algorithm

A 3D-QSAR/CoMFA was performed for a series of 42 piperidine-based dopamine transporter (DAT) blockers. The overall process consisted of three major steps: (1) a pharmacophore model was built using the Genetic Algorithm Similarity Program (GASP); (2) the Flexible Superposition (FlexS) technique was applied to generate multiple conformations for each of the ligands based on the pharmacophore; (3) the Genetic Algorithm was employed to optimize the selection of the ligand conformations for the CoMFA modeling. The CoMFA models were found to be more detailed in the putative binding site by exploring multiple conformations of each ligand. The comparison of the contour maps shows that, in general, these models are comparable and the differences between them result from the ability of the flexible 3-substituents of the ligands to adopt multiple conformations satisfying the same pharmacophore model. These findings provide guidance for the design and improvement of compounds with DAT activity, which is important for the development of a treatment of cocaine addiction and certain neurological disorders.     

Exhaustive CoMFA and CoMSIA analyses around different chemical entities: a ligand-based study exploring the affinity and selectivity profiles of 5-HT1A ligands

The 5-hydroxytryptamine (5-HT_1A) receptors represent an attractive target in drug discovery. In particular, 5-HT_1A agonists and partial agonists are deeply investigated for their potential role in the treatment of anxiety, depression, ischaemic brain disorder and more recently, of pain. On the other hand, 5-HT_1A antagonists have been revealed promising compounds in cognition disorders and, lately, in cancer. Thus, the discovery of 5HT_1A ligands is nowadays an appealing research activity in medicinal chemistry. In this work, Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) were applied on an in-house library of 5-HT_1A ligands bearing different chemical scaffolds in order to elucidate their affinity and selectivity for the target_. Following this procedure, a number of structural modifications have been drawn for the development of much more effective 5-HT_1AR ligands.

     

3D-QSAR study of adamantyl N-benzylbenzamides as melanogenesis inhibitors

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling, comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) of polyhydroxylated N-benzylbenzamide derivatives containing an adamantyl moiety were performed to understand the mechanism of action and structure–activity relationship of these compounds. Contour map analysis indicated that steric contributions of the adamantyl moiety and electrostatic contributions of the hydroxyl group at the 3-position are important in the activity. Activities of the training set and test sets predicted by CoMFA fit well with actual activities, demonstrating that CoMFA, along with the best calculated q² value, has the best predictive ability.     

3D QSAR Studies on Cytotoxin Actives of Ent- kauranoids from Isodon xerophilus ( Labiatae) by CoMFA

It is our aim to establish the CoMFA models of the en-t kauranoids from Isodon x erophilus and guide the design for new ant-i cancer drugs. The advanced 3D-QSAR ( quantitative structure- activity relationship) method CoMFA ( comparative molecular field analysis) was used to study the QSAR relationship of en-t kauranoids with cytotoxicity activity in vitro and led to four CoMFA models. The results of CoMFA models reveal the 3D- relationship between bioactivities and structures of these en-t kauranoids, and will be helpful to further design and find new drugs for higher ant-i cancer activities.     

Discovery and evaluation of nNav1.5 sodium channel blockers with potent cell invasion inhibitory activity in breast cancer cells

Voltage-gated sodium channels (VGSC) are a well-established drug target for anti-epileptic, anti-arrhythmic and pain medications due to their presence and the important roles that they play in excitable cells. Recently, their presence has been recognized in non-excitable cells such as cancer cells and their overexpression has been shown to be associated with metastatic behavior in a variety of human cancers. The neonatal isoform of the VGSC subtype, Na_v1.5 (nNa_v1.5) is overexpressed in the highly aggressive human breast cancer cell line, MDA-MB-231. The activity of nNa_v1.5 is known to promote the breast cancer cell invasion in vitro and metastasis in vivo, and its expression in primary mammary tumors has been associated with metastasis and patient death. Metastasis development is responsible for the high mortality of breast cancer and currently there is no treatment available to specifically prevent or inhibit breast cancer metastasis. In the present study, a 3D-QSAR model is used to assist the development of low micromolar small molecule VGSC blockers. Using this model, we have designed, synthesized and evaluated five small molecule compounds as blockers of nNa_v1.5-dependent inward currents in whole-cell patch-clamp experiments in MDA-MB-231 cells. The most active compound identified from these studies blocked sodium currents by 34.9?±?6.6% at 1?μM. This compound also inhibited the invasion of MDA-MB-231 cells by 30.3?±?4.5% at 1?μM concentration without affecting the cell viability. The potent small molecule compounds presented here have the potential to be developed as drugs for breast cancer metastasis treatment.