Three-dimensional quantitative structure-activity relationship (QSAR) and receptor mapping of cytochrome P-450(14 alpha DM) inhibiting azole antifungal agents

Molecular modeling was performed by a combined use of conformational analysis and 3D-QSAR methods to distinguish structural attributes common to a series of azole antifungal agents. Apex-3D program was used to recognize the common biophoric structural patterns of 13 diverse sets of azole antifungal compounds demonstrating different magnitudes of biological activity. Apex-3D identified three common biophoric features significant for activity: N1 atom of azole ring, the aromatic ring centroid 1, and aromatic ring centroid 2. A common biophore model proposed from the Apex-3D analysis can be useful for the design of novel cytochrome P-450(14 alpha DM) inhibiting antifungal agents.     

Linear and nonlinear 3D-QSAR approaches in tandem with ligand-based homology modeling as a computational strategy to depict the pyrazolo-triazolo-pyrimidine antagonists binding site of the human adenosine A2A receptor

The integration of ligand- and structure-based strategies might sensitively increase the success of drug discovery process. We have recently described the application of Molecular Electrostatic Potential autocorrelated vectors (autoMEPs) in generating both linear (Partial Least-Square, PLS) and nonlinear (Response Surface Analysis, RSA) 3D-QSAR models to quantitatively predict the binding affinity of human adenosine A3 receptor antagonists. Moreover, we have also reported a novel GPCR modeling approach, called Ligand-Based Homology Modeling (LBHM), as a tool to simulate the conformational changes of the receptor induced by ligand binding. In the present study, the application of both linear and nonlinear 3D-QSAR methods and LBHM computational techniques has been used to depict the hypothetical antagonist binding site of the human adenosine A2A receptor. In particular, a collection of 127 known human A2A antagonists has been utilized to derive two 3D-QSAR models (autoMEPs/PLS&RSA). In parallel, using a rhodopsin-driven homology modeling approach, we have built a model of the human adenosine A2A receptor. Finally, 3D-QSAR and LBHM strategies have been utilized to predict the binding affinity of five new human A2A pyrazolo-triazolo-pyrimidine antagonists finding a good agreement between the theoretical and the experimental predictions.     

A 3D QSAR approach to the search for geometrical similarity in a series of nonpeptide angiotensin II receptor antagonists

Summary A 3D QSAR methodology based on the combined use of conformational analysis and chemometrics was applied to perform a comparative analysis of the 3D conformational features of 13 nonpeptide angiotensin II receptor antagonists showing different levels of binding affinity. Conformational analysis by using a molecular mechanics MM2 method was carried out for each of these structures to obtain conformational minima. These minima were described by ten interatomic distances which define the relative spatial disposition of five significant atoms belonging to relevant functional groups present in all the 13 molecules. The structure-activity relationship between the interatomic distances and the biological activity was then assessed by using chemometric methods (cluster analysis, principal component analysis, classification methods). With our indirect approach based on the search for geometrical similarity it was possible, even though structural information on the receptor active site was lacking, to identify the 3D geometrical requirements for the binding affinity of nonpeptide angiotensin II receptor inhibitors.     

3D QSAR analyses of novel tyrosine kinase inhibitors based on pharmacophore alignment

In an effort to develop a quantitative ligand-binding model for the receptor tyrosine kinases, a pharmacophore search was first used to identify structural features that are common in two novel sets of 12 molecules of the 3-substituted indolin-2-ones and 19 compounds of the benzylidene malononitriles with low-to-high affinity for HER2, a kind of receptor tyrosine kinase. The common pharmacophore model based on these 31 compounds was used as a template to obtain the aligned molecular aggregate, which provided a good starting point for 3D-QSAR analysis of only the 19 benzylidene malononitriles. Two molecular field analysis (MFA) techniques, including CoMFA and CoMSIA, were used to derive the quantitative structure-activity relationships of the studied molecules. From the studied results, it was obvious that the 3D-QSAR models based on the pharmacophore alignment were superior to those based on the simple atom-by-atom fits. Considering the flexibility of the studied molecules and the difference between the active conformers and the energy-lowest conformers, the pharmacophore model can usually provide the common features for the flexible regions. Moreover, the best CoMSIA model based on the pharmacophore hypothesis gave good statistical measure from partial least-squares analysis (PLS) (q(2) = 0.71), which was slightly better than the CoMFA one. Our study demonstrated that pharmacophore modeling and CoMSIA research could be effectively combined. Results obtained from both methods helped with understanding the specific activity of some compounds and designing new specific HER2 inhibitors.     

Docking and 3D-QSAR Analysis on a Series of Pyridone-based EZH2 Inhibitors

Enhancer of Zeste homolog 2(EZH2) is closely correlated with malignant tumor and regarded as a promising target to treat B-cell lymphoma. In our research, the molecular docking and three-dimensional quantitative structure-activity relationships(3D-QSAR) studies were performed on a series of pyridone-based EZH2 compounds. Molecular docking allowed us to study the critical interactions at the binding site of EZH2 protein with inhibitors and identify the practical conformations of ligands in binding pocket. Moreover, the docking-based alignment was applied to derive the reliable 3D-QSAR models. Comparative molecular field analysis(CoMFA) and comparative molecular similarity indices analysis(CoMSIA) provided available ability of visualization. All the derived 3D-QSAR models were considered to be statistically significant with respect to the internal and external validation parameters. For the CoMFA model, q~2 = 0.649, r~2 = 0.961 and r~2 pred = 0.877. For the CoMSIA model, q~2 = 0.733, r~2 = 0.980 and r~2 pred = 0.848. With the above arguments, we extracted the correlation between the biological activity and structure. Based on the binding interaction and 3D contour maps, several new potential inhibitors with higher biological activity predicted were designed, which still awaited experimental validation. These theoretical conclusions could be helpful for further research and exploring potential EZH2 inhibitors.     

Estimation of molecular similarity based on 4D-QSAR analysis: formalism and validation

The 4D-QSAR paradigm has been used to develop a formalism to estimate molecular similarity measures as a function of conformation, alignment, and atom type. It is possible to estimate the molecular similarity of pairs of molecules based upon the entire ensemble of conformational states each molecule can adopt at a given temperature, normally room temperature. Molecular similarity can be measured in terms of the types of atoms composing each molecule leading to multiple measures of molecular similarity. Multiple measures of molecular similarity can also arise from using different alignment rules to perform relative molecular similarity, RMS, analysis. An alignment independent method of determining molecular similarity measures, referred to as absolute molecular similarity, AMS, analysis has been developed. Various sets and libraries of compounds, including the amino acids, are analyzed using 4D-QSAR molecular similarity analysis to demonstrate the features of the formalism. Exploration of molecular similarity as a function of chirality, identification of common embedded 3D pharmacophores in compounds, and elucidation of 3D-isosteric compounds from structurally diverse libraries are carried out in the application studies.     

Identification of potential Gly/NMDA receptor antagonists by cheminformatics approach: a combination of pharmacophore modelling,virtual screening and molecular docking studies

The Gly/NMDA receptor has become known as potential target for the management of neurodegenerative diseases. Discovery of Gly/NMDA antagonists has thus attracted much attention in recent years. In the present research, a cheminformatics approach has been used to determine structural requirements for Gly/NMDA antagonism and to identify potential antagonists. Here, 37 quinoxaline derivatives were selected to develop a significant pharmacophore model with good certainty. The selected model was validated by leave-one-out cross-validation, an external test set, decoy set and Y-randomization test. Applicability domain was verified by the standardization approach. The validated 3D-QSAR model was used to screen virtual hits from the ZINC database by pharmacophore mapping. Molecular docking was used for assessment of receptor–ligand binding modes and binding affinities. The GlideScore and molecular interactions with critical amino acids were considered as crucial features to identify final hits. Furthermore, hits were analysed for in silico pharmacokinetic parameters and Lipinski’s rule of five, demonstrating their potential as drug-like candidates. The PubChem and SciFinder search tools were used to authenticate the novelty of leads retrieved. Finally, five different leads have been suggested as putative novel candidates for the exploration of potent Gly/NMDA receptor antagonists.     

Pharmacophore identification by molecular modeling and chemometrics: The case of HMG-CoA reductase inhibitors

Summary A methodology based on molecular modeling and chemometrics is applied to identify the geometrical pharmacophore and the stereoelectronic requirements for the activity in a series of inhibitors of 3-hydroxy 3-methylglutaryl coenzyme A (HMG-CoA) reductase, an enzyme involved in cholesterol biosynthesis. These inhibitors present two common structural features—a 3,5-dihydroxy heptanoic acid which mimics the active portion of the natural substrate HMG-CoA and a lipophilic region which carries both polar and bulky groups. A total of 432 minimum energy conformations of 11 homologous compounds showing different levels of biological activity are calculated by the molecular mechanics MM2 method. Five atoms are selected as representatives of the relevant fragments of these compounds and three interatomic distances, selected among 10 by means of a Principal Component Analysis (PCA), are used to describe the three-dimensional disposition of these atoms. A cluster analysis procedure, performed on the whole set of conformations described by these three distances, allows the selection of one cluster whose centroid represents a geometrical model for the HMG-CoA reductase pharmacophore and the conformations included are candidates as binding conformations. To obtain a refinement of the geometrical model and to have a better insight into the requirements for the activity of these inhibitors, the Molecular Electrostatic Potential (MEP) distributions are determined by the MNDO semiempirical method.     

Enrichment of ligands for the serotonin receptor using the Shape Signatures approach

Shape Signatures, a new 3-dimensional molecular comparison method, has been adapted to rank ligands of the serotonin receptors. A set of 825 agonists and 400 antagonists together with approximately 10,000 randomly chosen compounds from the NCI database were used in this study. Both 1D and 2D Shape Signature databases were created, and enrichment studies were carried out. Results from these studies reveal that the 1D Shape Signature approach is highly efficient in separating agonists from a mixture of molecules which includes compounds randomly selected from the NCI database taken as inactives. It is also equally effective at separating agonists and antagonists from a pool of active ligands for the serotonin receptor. Parallel enrichment studies using 2D shape signatures showed high selectivity with more restricted coverage due to the high specificity of 2D signatures. The influence of conformational variation of the shape signature on enrichment was explored by docking a subset of ligands into the crystal structure of serotonin N-acetyltransferase. Enrichment studies on the resulting "docked" conformations produced only slightly improved results compared with the CORINA-generated conformations.     

2(1H)-喹啉-2,4-二酮类化合物抗小麦锈病的3D-QSAR研究

用比较分子力场分析(CoMFA)方法和比较分子相似性指数分析(CoMSIA)方法研究了21个2(1H)-喹啉-2,4-二酮类化合物抗小麦锈病的三维定量构效关系(3D-QSAR),发现用CoMFA方法可以找到最佳的3D-QSAR模型,并通过量子化学从头计算的方法研究了不同活性化合物的前线轨道及静电势分布图的差异.所得构效关系模型为发现更高活性的化合物提供理论指导.     

两类促肾上腺皮质释放激素(CRH)拮抗剂的分子场分析

采用比较分子相似性指数分析方法(CoMSIA)及比较分子场分析方法(CoMSIA)研究了两组CRH拮抗剂结构与活性的关系。在两种方法中,都考虑了静电场、立体场以及氢键场对构效关系的影响,结果表明采用CoMSIA得到构效关系模型要明显优于采用CoMFA得到的构效关系模型,在CoMSIA计算中,当引入疏水场时,三维构效关系模型能得到明显的改善,通过这个三维构效关系模型,可以较为精确地预测化合物的活性。通过分析分子场等值面图在空间的分布,可以观察到叠合分子周围的立体、静电以及疏水特征对化合物活性的影响。     

Molecular modeling and 3D-QSAR studies in 2-aziridinyl-and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives as potential antimalarial agents

Malaria is still continuing to be one of the most dreadful diseases of the tropical countries particularly due to the development of resistance to the existing antimalarials. From observed, antimalarial activity of 2-aziridinyl- and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives acting through redox cycling mechanism, molecular modeling and three dimensional-quantitative structure activity relationship (3D-QSAR) studies have been carried out on a set of 63 compounds to identify important pharmacophors. Among several 3D-QSAR models generated, three models with correlation coefficient r > 0.82, match > 0.60 and chance = 0.00 have shown two common biophoric sites: one being the oxygen atom at position 1 of the naphthoquinone ring in terms of pi-population, charge and electron donating ability while the second being the center of the phenyl ring in terms of its 6pi-electrons. In addition to these sites, the models also share two common secondary sites: one positively contributing H-acceptor site while the second site contributing negatively in terms of steric refractivity. All these models showed good agreement between the experimental, calculated and predicted antimalarial activities.     

Receptor-based modeling and 3D-QSAR for a quantitative production of the butyrylcholinesterase inhibitors based on genetic algorithm

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of structurally related steroidal alkaloids as butyrylcholinesterase (BuChE) inhibitors. Docking studies were employed to position the inhibitors into the BuChE active site to determine the most probable binding mode. The strategy was to explore multiple inhibitor conformations in producing a more reliable 3D-QSAR model. These multiple conformations were derived using the FlexS program. The conformation selection step for CoMFA was done by genetic algorithm. The genetic algorithm based CoMFA approach was found to be the best. Both CoMFA and CoMSIA yielded significant cross-validated q(2) values of 0.701 and 0.627 and the r(2) values of 0.979 and 0.982, respectively. These statistically significant models were validated by a test set of five compounds. Comparison of CoMFA and CoMSIA contour maps helped to identify structural requirements for the inhibitors and serves as a basis for the design of the next generation of the inhibitor analogues. The results demonstrate that the combination of ligand-based and receptor-based modeling with use of a genetic algorithm is a powerful approach to build 3D-QSAR models. These data can be used for the lead optimization process with respect to inhibition enhancement which is important for the drug discovery and development for Alzheimer's disease.     

Molecular Modeling and 3D-QSAR Studies in 2-Aziridinyl-and 2,3-Bis(Aziridinyl)-1,4-Naphthoquinonyl Sulfonate and Acylate Derivatives as Potential Antimalarial Agents

Abstract

Malaria is still continuing to be one of the most dreadful diseases of the tropical countries particularly due to the development of resistance to the existing antimalarials. From observed, antimalarial activity of 2-aziridinyl- and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives acting through redox cycling mechanism, molecular modeling and three dimensional-quantitative structure activity relationship (3D-QSAR) studies have been carried out on a set of 63 compounds to identify important pharmacophors. Among several 3D-QSAR models generated, three models with correlation coefficient r > 0.82, match > 0.60 and chance = 0.00 have shown two common biophoric sites: one being the oxygen atom at position 1 of the naphthoquinone ring in terms of π-population, charge and electron donating ability while the second being the center of the phenyl ring in terms of its 6π-electrons. In addition to these sites, the models also share two common secondary sites: one positively contributing H-acceptor site while the second site contributing negatively in terms of steric refractivity. All these models showed good agreement between the experimental, calculated and predicted antimalarial activities.     

Insights into phenylalanine derivatives recognition of VLA-4 integrin: from a pharmacophoric study to 3D-QSAR and molecular docking analyses

The very late antigen-4 (VLA-4), also known as integrin alpha4beta1, is expressed on monocytes, T- and B-lympohocytes, basophils, and eosinophils and is involved in the massive recruitment of granulocytes in different pathological conditions such as multiple sclerosis and asthma. VLA-4 interacts with its endogenous ligand VCAM-1 during chronic inflammation, and blockade of VLA-4 /VCAM-1 interaction is a potential target for immunosuppression. Two classes of VLA-4 antagonists have so far been reported: beta-amino acid derivatives containing a diaryl urea moiety (BIO-1211) and phenylalanine derivatives (TR-14035). With the aim of clarifying the structural basis responsible for VLA-4 recognition by phenylalanine derivatives, we developed a combined computational study on a set of 128 antagonists available through the literature. Our computational approach is composed of three parts. (i) A VCAM-1 based pharmacophore was constructed with a restricted number of phenylalanine derivatives to identify the region of the protein that resembles synthetic antagonists. The pharmacophore was instrumental in constructing an alignment of a set of 128 compounds. This alignment was exploited to build a pseudoreceptor model with the RECEPTOR program. (ii) 3D-QSAR analysis was carried out on the computed electrostatic and steric interaction energies with the pseudoreceptor surface. The 3D-QSAR analysis yielded a predictive model able to explain much of the variance of the 128 antagonists. (iii) A homology modeling study of the headpiece of VLA-4 based on the crystal structure of alphavbeta3 was performed. Docking experiments of TR-14035 into the binding site of VLA-4 aided the interpretation of the 3D-QSAR model. The obtained results will be fruitful for the design of new potent and selective antagonists of VLA-4.     

Ordinal classification using Comparative Molecular Field Analysis

Comparative Molecular Field Analysis (CoMFA) is most widely used as one of the 3-dimensional QSAR (3D-QSAR) methods to identify the relationship between chemical structure and biological activity. Conventional CoMFA requires at least 3 orders of experimental data, such as IC50 and Ki, to obtain a good model, although practically there are many screening assays where biological activity is measured only by a rating scale. Hence, rating classification-oriented CoMFA coupled with ordinal logistic regression has been developed, and its predictive ability and 3D graphical analysis ability have been investigated. As a result, this novel CoMFA (Logistic CoMFA) has been found to be more robust than conventional CoMFAs in both predictive and 3D graphical analysis abilities. Furthermore, Logistic CoMFA is useful since it can provide the probability of each rank.