Virtual screening based on pharmacophore model followed by docking simulation studies in search of potential inhibitors for p38 map kinase

P38 mitogen-activated protein (MAP) kinase inhibitors are closely involved in the production of inflammatory cytokines. These compounds are considered promising therapeutic agents for chronic inflammatory disorders. In this study, a ligand-based pharmacophore model of p38 map kinase inhibitors was developed. The best five features pharmacophore model includes two hydrogen bond acceptors, two hydrophobic and an aromatic hydrophobic features, which has the highest correlation coefficient (0.822), cost difference (134.158), low root mean square (RMS) of error (1.315). As well as the developed model shows a high goodness of fit and enrichment factor. The pharmacophore hypothesis has been validated by using a series of similar structures with varying affinities for the p38 map kinase. It also has been employed as a search query in different database searching with the ultimate goal of finding novel compounds which have the possibility to be modified into novel lead molecules. As a result, some hit compounds were introduced as final candidates by employing virtual screening and molecular docking procedure simultaneously. The results from pharmacophore modeling and molecular docking are complementary to each other and could serve as a useful approach for the discovery of potent small molecules as p38 map kinase inhibitors.     

Tubulin inhibitors： pharmacophore modeling,virtua screening and molecular docking

Aim： To construct a quantitative pharmacophore model of tubulin inhibitors and to discovery new leads with potent antitumor activities. Methods： Ligand-based pharmacophore modeling was used to identify the chemical features responsible for inhibiting tubulin polymerization. A set of 26 training compounds was used to generate hypothetical pharmacophores using the HypoGen algorithm. The structures were further validated using the test set, Fischer randomization method, leave-one-out method and a decoy set, and the best model was chosen to screen the Specs database. Hit compounds were subjected to molecular docking study using a Molecular Operating Environment （MOE） software and to biological evaluation in vitro. Results： Hypol was demonstrated to be the best pharmacophore model that exhibited the highest correlation coefficient （0.9582）, largest cost difference （70.905） and lowest RMSD value （0.6977）. Hypol consisted of one hydrogen-bond acceptor, a hydrogen-bond donor, a hydrophobic feature, a ring aromatic feature and three excluded volumes. Hypol was validated with four different methods and had a goodness-of-hit score of 0.81. When Hypol was used in virtual screening of the Specs database, 952 drug-like compounds were revealed. After docking into the colchicine-binding site of tubulin, 5 drug-like compounds with the required interaction with the critical amino acid residues and the binding free energies 〈-4 kcal/mol were selected as representative leads. Compounds 1 and 3 exhibited inhibitory activity against MCF-7 human breast cancer cells in vitro. Conclusion： Hypol is a quantitative pharmacophore model for tubulin inhibitors, which not only provides a better understanding of their interaction with tubulin, but also assists in discovering new potential leads with antitumor activities.     

The Discovery of a Novel and Selective Inhibitor of PTP1B Over TCPTP: 3D QSAR Pharmacophore Modeling,Virtual Screening,Synthesis, and Biological Evaluation

Given the special role of insulin and leptin signaling in various biological responses, protein‐tyrosine phosphatase‐1B (PTP1B) was regarded as a novel therapeutic target for treating type 2 diabetes and obesity. However, owing to the highly conserved (sequence identity of about 74%) in active pocket, targeting PTP1B for drug discovery is a great challenge. In this study, we employed the software package Discovery Studio to develop 3D QSAR pharmacophore models for PTP1B and TCPTP inhibitors. It was further validated by three methods (cost analysis, test set prediction, and Fisher's test) to show that the models can be used to predict the biological activities of compounds without costly and time‐consuming synthesis. The criteria for virtual screening were also validated by testing the selective PTP1B inhibitors. Virtual screening experiments and subsequent in vitro evaluation of promising hits revealed a novel and selective inhibitor of PTP1B over TCPTP. After that, a most likely binding mode was proposed. Thus, the findings reported here may provide a new strategy in discovering selective PTP1B inhibitors.     

基于药效团技术与专利检索的降脂中药发现研究

抑制HMG-CoA还原酶的他汀类药物与激动PPAR-α的贝特类药物联合应用相较于单纯应用能产生更好的降脂效果, 但同时也会产生较强的不良反应。中药与HMG-CoA还原酶抑制剂合用治疗高血脂疗效稳定、毒副作用小, 为药物联用提供了新的选择。该文利用药效团技术搜索中药化学成分, 追溯其来源中药, 确定潜在的具有PPAR-α激动活性的常用中药。由于现有中医经典中未涉及治疗高脂血症的相关用药方案以供参考, 为确保所选中药的联合应用具有较高的安全性和有效性, 该文选择世界传统药物专利数据库中已有临床验证的能与他汀类药物联合降脂之中药, 并据此分析药效团命中结果中的相应药物, 最终获得能作用于PPAR-α且能与他汀类药物联合使用的常用中药。其中, 药效团模型以PPAR-α的8个配体-受体结合物为研究对象, 利用DS程序中的Receptor-Ligand Pharmacophore Generation模块建立, 并以Screen Library模块进行优化, 获得最优子药效团。最优子药效团模型由2个氢键受体、3个疏水基团以及19个排除体积组成, 辨识有效性指数N值2.82、综合评价指数CAI值1.84。采用该模型对TCMD数据库进行筛选, 命中5 235种化学成分、1 193种来源天然动植物, 最后确定常用中药62味。专利检索得到38味常用中药, 与虚拟筛选结果进行比对, 最终获得7味中药。     

GPCR配体药效团数据库的构建

G蛋白偶联受体（GPCR）是人体内一类重要的药物作用靶标。针对GPCR配体进行了较全面的药效团模拟研究,有效地整合针对GPCR进行药物发现研究的数据,并构建了相应的药效团数据库。收集并构建了GPCR的8个大类17个亚型的不同配体共110个药效团模型,作为GPCR配体药效团数据库的首批数据。通过统计分析发现：87%GPCR配体药效团中含有疏水性基团（Hydrophobic, HY）、66%包含芳香性基团（Ring aromatic, RA）、45%含有正离子基团（Positive ions, PI）。GPCR药效团数据库的建立极大地方便了开发设计新的具有选择性的GPCR配体。     

PI3K/mTOR双重抑制剂的研究进展

磷脂酰肌醇3-激酶/哺乳动物雷帕霉素靶蛋白（phosphoinosmde-3-kinase/the mammalian target of rapamycin,PI3K/mTOR）双重抑制剂已经成为抗肿瘤药物研发的热点之一。本文介绍芳基脲类和3-吡啶基杂环类等PI3K/mTOR双重抑制剂的化学结构,根据其结构特点及其与PI3Kγ共结晶模式,剖析了两类抑制剂药效团的基本结构。     

Discovery of novel acyl coenzyme a: cholesterol acyltransferase inhibitors: pharmacophore-based virtual screening, synthesis and pharmacology

The present study describes ligand‐based pharmacophore modeling of a series of structurally diverse acyl coenzyme A cholesterol acyltransferase inhibitors. Quantitative pharmacophore models were generated using HypoGen module of Discovery Studio 2.1, whereby the best pharmacophore model possessing two hydrophobic, one ring aromatic, and one hydrogen bond acceptor feature for inhibition of acyl coenzyme A cholesterol acyltransferase showed a very good correlation coefficient (r = 0.942) along with satisfactory cost analysis. Hypo1 was also validated by test set and cross‐validation methods. Developed models were found to be predictive as indicated by low error values for test set molecules. Virtual screening against Maybridge database using Hypo1 was performed. The two most potent compounds ( 47 and 48 ; predicted IC₅₀ = 1 nm ) of the retrieved hits were synthesized and biologically evaluated. These compounds showed 86% and 88% inhibition of acyl coenzyme A cholesterol acyltransferase (at 10 μg/mL) with IC₅₀ value of 3.6 and 2.5 nm , respectively. As evident from the close proximity of biological data to the predicted values, it can be concluded that the generated model (Hypo1) is a reliable and useful tool for lead optimization of novel acyl coenzyme A cholesterol acyltransferase inhibitors.     

Molecular docking and dynamics simulation, receptor-based hypothesis: application to identify novel sirtuin 2 inhibitors

Sirtuin, NAD(+)-dependent histone deacetylase enzyme, emerged as a potential therapeutic target, and modulations by small molecules could be effective drugs for various diseases. Owing to the absence of complex structure of sirtuin 2 (SIRT2), sirtinol was docked in the NAD(+) binding site and subjected to 5-nseconds molecular dynamics (MD) simulation. LigandScout was used to develop hypotheses based on 3-representative SIRT2 complex structures from MD. Three structure-based hypotheses are generated and merged to form dynamics hypothesis. The dynamics hypothesis was validated using test and decoy sets. The results showed that dynamic hypothesis represents the complementary features of SIRT2 active site. Dynamic hypothesis was used to screen ChemDiv database, and hits were filtered through ADMET, rule of five, and two different molecular docking studies. Finally, 21 molecules were selected as potent leads based on consensus score from LigandFit, Gold fitness score, binding affinity from VINA as well as based on the important interactions with critical residues in SIRT2 active site. Hence, we suggest that the dynamic hypothesis will be reliable in the identification of SIRT2 new lead as well as to reduce time and cost in the drug discovery process.     

Multicomplex-based pharmacophore-guided 3D-QSAR studies of N-substituted 2'-(aminoaryl)benzothiazoles as Aurora-A inhibitors

Aurora-A has been known as one of the most important targets for cancer therapy, and some Aurora-A inhibitors have entered clinical trails. In this study, combination of the ligand-based and structure-based methods is used to clarify the essential quantitative structure-activity relationship of known Aurora-A inhibitors, and multicomplex-based pharmacophore-guided method has been suggested to generate a comprehensive pharmacophore of Aurora-A kinase based on a collection of crystal structures of Aurora-A-inhibitor complex. This model has been successfully used to identify the bioactive conformation and align 37 structurally diverse N-substituted 2'-(aminoaryl)benzothiazoles derivatives. The quantitative structure-activity relationship analyses have been performed on these Aurora-A inhibitors based on multicomplex-based pharmacophore-guided alignment. These results may provide important information for further design and virtual screening of novel Aurora-A inhibitors.     

Computational and in vitro studies on the inhibitory effects of herbal compounds on human cytochrome P450 1A2

1. Human CYP1A2 is an important enzyme for drug metabolism and procarcinogen activation. This study aimed to explore the binding mode of ligands with CYP1A2 and to screen potential inhibitors from a library of herbal compounds using computational and in vitro approaches.

2. The heme prosthetic group and six residues (Thr124, Phe125, Phe226, Phe260, Gly316, and Ala317) in the active site of CYP1A2 were identified as important residues for ligand binding using the LIGPLOT program. Ala317 in helix I immediately above heme was highly conserved in most human CYPs with known crystal structures.

3. In molecular docking, 19 of the 56 herbal compounds examined were identified as potential inhibitors of CYP1A2. Up to 21 of the 56 herbal compounds were hit by the pharmacophore model of CYP1A2 inhibitors developed and validated in this study.

4. In the in vitro inhibition study, 8 herbal compounds were identified as moderate to potent inhibitors of CYP1A2. Five of the 8 herbal compounds predicted to be potential inhibitors were confirmed as CYP1A2 inhibitors in the in vitro study.

5. A combination of computational and in vitro approaches, represent a useful tool to identify potential inhibitors for CYP1A2 from herbal compounds.