Calculating the knowledge-based similarity of functional groups using crystallographic data

A knowledge-based method for calculating the similarity of functional groups is described and validated. The method is based on experimental information derived from small molecule crystal structures. These data are used in the form of scatterplots that show the likelihood of a non-bonded interaction being formed between functional group A (the `central group') and functional group B (the `contact group' or `probe'). The scatterplots are converted into three-dimensional maps that show the propensity of the probe at different positions around the central group. Here we describe how to calculate the similarity of a pair of central groups based on these maps. The similarity method is validated using bioisosteric functional group pairs identified in the Bioster database and Relibase. The Bioster database is a critical compilation of thousands of bioisosteric molecule pairs, including drugs, enzyme inhibitors and agrochemicals. Relibase is an object-oriented database containing structural data about protein-ligand interactions. The distributions of the similarities of the bioisosteric functional group pairs are compared with similarities for all the possible pairs in IsoStar, and are found to be significantly different. Enrichment factors are also calculated showing the similarity method is statistically significantly better than random in predicting bioisosteric functional group pairs.     

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.     

Identification of potential HIV-1 integrase strand transfer inhibitors: In silico virtual screening and QM/MM docking studies

HIV-1 integrase (IN) is a retroviral enzyme that catalyses integration of the reverse-transcribed viral DNA into the host genome, which is necessary for efficient viral replication. In this study, we have performed an in silico virtual screening for the identification of potential HIV-1 IN strand transfer (ST) inhibitors. Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to 3-Hydroxypyrimidine-2,4-diones. Based on the ligand-based pharmacophore model, we obtained a five-point pharmacophore with two hydrogen bond acceptors (A), one hydrogen bond donor (D), one hydrophobic group (H) and one aromatic ring (R) as pharmacophoric features. The pharmacophore hypothesis AADHR was used as a 3D query in a sequential virtual screening study to filter small molecule databases Maybridge, ChemBridge and Asinex. Hits matching with pharmacophore hypothesis AADHR were retrieved and passed progressively through Lipinski’s rule of five filtering, molecular docking and hierarchical clustering. The five compounds with best hits with novel and diverse chemotypes were subjected to QM/MM docking, which showed improved docking accuracy. We further performed molecular dynamics simulation and found three compounds that form stable interactions with key residues. These compounds could be used as a leads for further drug development and rational design of HIV-1 IN inhibitors.     

Evaluation and application of multiple scoring functions for a virtual screening experiment

In order to identify novel chemical classes of factor Xa inhibitors, five scoring functions (FlexX, DOCK, GOLD, ChemScore and PMF) were engaged to evaluate the multiple docking poses generated by FlexX. The compound collection was composed of confirmed potent factor Xa inhibitors and a subset of the LeadQuest screening compound library. Except for PMF the other four scoring functions succeeded in reproducing the crystal complex (PDB code: 1FAX). During virtual screening the highest hit rate (80%) was demonstrated by FlexX at an energy cutoff of -40 kJ/mol, which is about 40-fold over random screening (2.06%). Limited results suggest that presenting more poses of a single molecule to the scoring functions could deteriorate their enrichment factors. A series of promising scaffolds with favorable binding scores was retrieved from LeadQuest. Consensus scoring by pair-wise intersection failed to enrich the hit rate yielded by single scorings (i.e. FlexX). We note that reported successes of consensus scoring in hit rate enrichment could be artificial because their comparisons were based on a selected subset of single scoring and a markedly reduced subset of double or triple scoring. The findings presented in this report are based upon a single biological system and support further studies.     

New leads for selective GSK-3 inhibition: pharmacophore mapping and virtual screening studies

Summary Glycogen Synthase Kinase-3 is a regulatory serine/threonine kinase, which is being targeted for the treatment of a number of human diseases including type-2 diabetes mellitus, neurodegenerative diseases, cancer and chronic inflammation. Selective GSK-3 inhibition is an important requirement owing to the possibility of side effects arising from other kinases. A pharmacophore mapping strategy is employed in this work to identify new leads for selective GSK-3 inhibition. Ligands known to show selective GSK-3 inhibition were employed in generating a pharmacophore map using distance comparison method (DISCO). The derived pharmacophore map was validated using (i) important interactions involved in selective GSK-3 inhibitions, and (ii) an in-house database containing different classes of GSK-3 selective, non-selective and inactive molecules. New Lead identification was carried out by performing virtual screening using validated pharmacophoric query and three chemical databases namely NCI, Maybridge and Leadquest. Further data reduction was carried out by employing virtual filters based on (i) Lipinski’s rule of 5 (ii) van der Waals bumps and (iii) restricting the number of rotatable bonds to seven. Final screening was carried out using FlexX based molecular docking study.     

基于雌激素β受体结构雌激素类化合物的三维定量结构-活性关系与分子对接研究

雌激素类化合物由于其对人和野生动物健康的负面影响而受到广泛关注.雌激素受体存在α和β两种亚型,由于雌激素β受体（ERβ）与α受体（ERα）两者结合腔中的氨基酸序列存在明显差异,因此配体化合物在与雌激素β受体和α受体的结合活性和模式上也可能存在较大差别.本文以50个与雌激素β受体结合的化合物为研究对象,应用比较分子相似性指数分析（COMSIA）的三维定量结构-活性关系（3D-QSAR）分析方法研究化合物结构与活性之间的关系,比较了原子契合和基于受体结构两种分子叠合方式对模型质量的影响,建立了相关性显著、预测能力强的定量活性预测模型（R^2=0.961,qLOO^2=0.671,R^2Pred=0.722）,并结合分子对接方法揭示了影响化合物活性的分子结构特征和分子机理.     

Identification of potential CRAC channel inhibitors: Pharmacophore mapping, 3D-QSAR modelling,and molecular docking approach

Upregulation of store-operated Ca²⁺ influx via ORAI1, an integral component of the CRAC channel, is responsible for abnormal cytokine release in active rheumatoid arthritis, and therefore ORAI1 has been proposed as an attractive molecular target. In this study, we attempted to predict the mechanical insights of ORAI1 inhibitors through pharmacophore modelling, 3D-QSAR, molecular docking and free energy analysis. Various hypotheses of pharmacophores were generated and from that, a pharmacophore hypothesis with two hydrogen bond acceptors, one hydrogen bond donor and two aromatic rings (AADRR) resulted in a statistically significant 3D-QSAR model (r² = 0.84 and q² = 0.74). We believe that the obtained statistical model is a reliable QSAR model for the diverse dataset of inhibitors against the IL-2 production assay. The visualization of contours in active and inactive compounds generated from the 3D-QSAR models and molecular docking studies revealed major interaction with GLN108, HIS113 and ASP114, and interestingly, these residues are located near the Ca²⁺ selectivity filter region. Free energy binding analysis revealed that Coulomb energy, van der Waals energy and non-polar solvation terms are more favourable for ligand binding. Thus, the present study provides the physical and chemical requirements for the development of novel ORAI1 inhibitors with improved biological activity.     

The identification of new ATAD2 bromodomain inhibitors: the application of combined ligand and structure-based virtual screening

Ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches were used to identify new inhibitors for ATAD2 bromodomain. The LBVS approach was used to search 23,129,083 clean compounds to identify compounds similar to an active compound with reported pIC₅₀ equal to 7.2. Based on LBVS results, 19 compounds were selected. To perform SBVS, by applying nine filters on 23,129,083 clean compounds, 1,057,060 compounds were selected. After performing SBVS on these selected compounds with idock software, 16 compounds with the lowest binding energies were selected. More accurate molecular docking analysis was performed on these 35 selected compounds by using iGEMDOCK software and six of them with the lowest binding energies were selected as hit compounds. These compounds were zinc36647229, zinc77969074, zinc13637358, zinc77971540, zinc12991296 and zinc19374204.     

EUDOC: a computer program for identification of drug interaction sites in macromolecules and drug leads from chemical databases

The completion of the Human Genome Project, the growing effort on proteomics, and the Structural Genomics Initiative have recently intensified the attention being paid to reliable computer docking programs able to identify molecules that can affect the function of a macromolecule through molecular complexation. We report herein an automated computer docking program, EUDOC, for prediction of ligand-receptor complexes from 3D receptor structures, including metalloproteins, and for identification of a subset enriched in drug leads from chemical databases. This program was evaluated from the standpoints of force field and sampling issues using 154 experimentally determined ligand-receptor complexes and four "real-life" applications of the EUDOC program. The results provide evidence for the reliability and accuracy of the EUDOC program. In addition, key principles underlying molecular recognition, and the effects of structural water molecules in the active site and different atomic charge models on docking results are discussed. Copyright 2001 John Wiley & Sons, Inc. J Comput Chem 22: 1750-1771, 2001     

新磺酰脲类化合物除草活性的3D-QSAR分析

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) 方法对所合成的新磺酰脲类化合物的除草活性进行了较为系统的3D-QSAR分析.两种方法所建立的模型对化合物的除草活性预测能力均较好,所得三维等值线图为合成高活性的化合物能提供指导作用     

苯并呋喃类N-肉豆蔻酰基转移酶抑制剂的三维定量构效关系研究

摘要采用比较分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA), 系统地研究了40个苯并呋喃类N-肉豆蔻酰基转移酶(NMT)抑制剂的三维定量构效关系. 在CoMFA研究中, 考察了网格点步长对模型统计结果的影响. 在CoMSIA研究中, 研究了各种分子场组合、 网格点步长和衰减因子对模型统计结果的影响, 发现立体场、 静电场、 疏水场和氢键受体场的组合可得到最佳模型. 所建立的CoMFA和CoMSIA模型的交叉相关系数q2值分别为0.759和0.730, 均具有较强的预测能力. 利用CoMFA和CoMSIA模型的三维等值线图直观地解释了化合物的构效关系, 阐明了化合物结构中苯并呋喃环上各位置取代基对抑酶活性的影响, 为进一步结构优化提供了重要依据.     

The affinity of histamine to serum albumin: Capillary electrophoresis-frontal analysis and in-silico molecular docking approaches

Histamine is a biogenic amine found in various body tissues and responsible for many critical vital activities. It is also responsible for allergic reactions in the body. Ingestion of foods containing high amounts of histamine can cause fatal allergic reactions. Albumin in plasma controls drugs and free concentrations of bioactive constituents taken to the body with food. Hence, this study aimed to characterise the interactions of histamine with bovine serum albumin. Capillary electrophoresis in the frontal analysis mode was employed in this study as a practical approach for assessing histamine-bovine serum albumin affinity. The plateau-shaped free histamine peak was well separated from the bovine serum albumin (BSA)-histamine complex peak. The free histamine concentration was obtained by following the height of the free histamine peak. Whereas the bound histamine concentrations were obtained by calculating the difference between the height of total and free histamine peaks. Histamine bound to BSA at one independent site with a K_b value of 2.50 × 10³ L/mol. Moreover, an in-silico molecular docking method was performed, and it was revealed that the binding site of histamine was located closer to Lysine-131 in subdomain IIA of bovine serum albumin.