氧肟酸类组蛋白去乙酰化酶抑制剂的药效团模型研究

基于24个目前已知的氧肟酸类组蛋白去乙酰化酶抑制剂,我们运用Catalyst软件建立了一个三维药效团模型。其中,最好的药效团模型1,包含了四个化学特征（一个氢键供体,一个芳环和两个疏水基）,相关系数达到0.946,并由另外20个化合物进行了测试验证。我们第一次特征性描述了组蛋白去乙酰化酶的帽子（CAP）部分。我们的研究结果对于设计全新组蛋白去乙酰化酶抑制剂具有很好的指导作用。     

The Pharmacophore Hypothesis of Novel Inhibitors for Aurora A Kinase

A three-dimensional pharmacophore model was developed from a series of inhibitors of Aurora A kinase to discover new potent anti-cancer agents using the HypoGen module in the Catalyst software. The pharmacophore model was developed based on the structure of 20 currently available inhibitors, which were carefully selected from the literature. The best hypothesis （Hypo 1） was defined by four features： one hydrogen-bond donor and three hy- drophobic points, with the best correlation coefficient of 0.909, the lowest rms deviation of 1.563, and the highest cost difference of 99.075. The Hypo 1 was then validated by a test set consisting of 24 compounds and by a cross-validation of 95% confidence level through randomizing the data using the CatScramble program, which suggested that a predictive pharmacophore model had been successfully obtained.     

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.     

Pharmacophore Mode lingand Virtual Screening to Design the Potential Influenza Virus Endonuclease Inhibitors

Influenza virus endonuclease is an attractive target for antiviral therapy in the treatment of influenza infection. The purpos e of this study is to design a novel antiviral agent with improved biological activities against the influenza virus endonuclease. In this study, chemical feature‐based 3D pharmacophore models were developed from 41 known influenza virus endonuclease inhibitors. The best quantitative pharmacohore model (Hypo 1), which consists of two hydrogen‐bond acceptors and two hydrophobic features, yields the highest correlation coefficient (R = 0.886). Hypo 1 was further validated by the cross validation method and the test set compounds. The application of this model for predicting the activities of 11 known influenza virus endonuclease inhibitors in the test set shows great success. The correlation coefficient of 0.942 and a cross validation of 95;% confidence level prove that this model is reliable in identifying structurally diverse compounds for influenza virus endonuclease inhibition. The most active compound (compound 1) from the training set was docked into the active site of the influenza virus endonuclease as an additional verification that the pharmacophore model is accurate. The docked conformation showed important hydrogen bond interactions between the compound and two amino acids, Lys 134 and Lys 137. After validation, this model was used to screen the NCI chemical database to identify new influenza virus endonuclease inhibitors. Our study shows that the to pranking compound out of the 10 newly identified compounds using fit value ranking has an estimated activity of 0.049 μM. These newly identified lead compounds can be further experimentally validated using in vitro techniques.     

Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC₅₀ values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere–Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a Q_FIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.     

Construction of the Pharmacophore Model of Glycogen Synthase Kinase-3 Inhibitors

A three dimensional pharmacophore model has been generated for glycogen synthase kinase-3 （GSK-3） inhibitots. A dataset consisting of 89 compounds was selected on the basis of the information content of the structures and activity data as required by the CATALYST system. The optimum model with four features （one hydrogen-bond acceptor unit, one ring aromatic unit, and two hydrophobic aromatic units） was selected with a good correlation coefficient （0.95）. This model is able to predict the activity of other known GSK-3 inhibitors not included in the model generation, and can be further used to identify structurally diverse compounds with desired biological activity by virtual screening.     

Synthesis of a Regioisomer of β‐Lapachone and Analogs as Potent Antitumor Agents

A regioisomer of β‐lapachone and two analogs were synthesized and evaluated for their antitumor activities. All three compounds tested were found to exhibit promising activities against PC‐3, HepG2, and Raji cancer cell lines in μM range.     

Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products

Matrix metalloproteinase-9 (MMP-9) is an attractive target for cancer therapy. In this study, the pharmacophore model of MMP-9 inhibitors is built based on the experimental binding structures of multiple receptor-ligand complexes. It is found that the pharmacophore model consists of six chemical features, including two hydrogen bond acceptors, one hydrogen bond donor, one ring aromatic regions, and two hydrophobic (HY) features. Among them, the two HY features are especially important because they can enter the S1′ pocket of MMP-9 which determines the selectivity of MMP-9 inhibitors. The reliability of pharmacophore model is validated based on the two different decoy sets and relevant experimental data. The virtual screening, combining pharmacophore model with molecular docking, is performed to identify the selective MMP-9 inhibitors from a database of natural products. The four novel MMP-9 inhibitors of natural products, NP-000686, NP-001752, NP-014331, and NP-015905, are found; one of them, NP-000686, is used to perform the experiment of in vitro bioassay inhibiting MMP-9, and the IC₅₀ value was estimated to be only 13.4 µM, showing the strongly inhibitory activity of NP-000686 against MMP-9, which suggests that our screening results should be reliable. The binding modes of screened inhibitors with MMP-9 active sites were discussed. In addition, the ADMET properties and physicochemical properties of screened four compounds were assessed. The found MMP-9 inhibitors of natural products could serve as the lead compounds for designing the new MMP-9 inhibitors by carrying out structural modifications in the future.     

Three New Diterpenoids from Isodon nervosus

Three new ent‐kaurane diterpenoids, rabdonervosins D–F ( 1 – 3 ), were isolated from the leaves and stems of Isodon nervosus. Their structures were elucidated on the basis of spectroscopic methods including 1D‐ and 2D‐NMR analyses. Compounds 1 – 3 were evaluated for their cytotoxicity against HepG2, CNE2, PC‐9/ZD, HeLa, MCF‐7, and HCT116 cell lines. No compounds exhibited potent cytotoxicity.     

Virtual screening studies to design potent CDK2-cyclin A inhibitors

The cell division cycle is controlled by cyclin-dependent kinases (CDK), which consist of a catalytic subunit (CDK1-CDK8) and a regulatory subunit (cyclin A-H). Pharmacophore analysis indicates that the best inhibitor model consists of (1) two hydrogen bond acceptors, (2) one hydrogen bond donor, and (3) one hydrophobic feature. The HypoRefine pharmacophore model gave an enrichment factor of 1.31 and goodness of fit score of 0.76. Docking studies were carried out to explore the structural requirements for the CDK2-cyclin A inhibitors and to construct highly predictive models for the design of new inhibitors. Docking studies demonstrate the important role of hydrogen bond and hydrophobic interactions in determining the inhibitor-receptor binding affinity. The validated pharmacophore model is further used for retrieving the most active hits/lead from a virtual library of molecules. Subsequently, docking studies were performed on the hits, and novel series of potent leads were suggested based on the interaction energy between CDK2-cyclin A and the putative inhibitors.     

Synthesis and In Vitro Anticancer Evaluation of Symmetrically Bridged 1,3‐thiazine Derivatives

A series of bis‐1,3‐thiazine derivatives 3a–o were synthesized from the condensation reactions of symmetric dialdehydes 1a–c possessing aliphatic ether spacer units with 3‐substituted‐amino‐2‐cyano‐3‐mercaptoacrylamides 2a–e . The chemical structures of the products were fully characterized by using different spectroscopic techniques, such as ¹H NMR, ¹³C NMR, IR, electron impact mass spectrometry, and elemental analysis. Compounds 3a , 3f , and 3k underwent ring opening followed by recyclization and alkylation in basic medium to afford bis‐pyrimidinones 4a–c and 5a–c . The anticancer potential of the new bis‐1,3‐thiazines was assessed in vitro against six different human cell lines, including lung A549, colon HCT116, breast MCF‐7, prostate PC3, liver HepG2, and normal melanocyte HFB4. The results revealed a potent activity of compounds 3e and 3k against breast and liver cancer cell lines in comparison with the reference drug doxorubicin with no noticeable toxicity on normal cells.     

基于药效团模型的DHODH抑制剂构效关系研究

利用药效团模型研究二氢乳清酸脱氢酶(Dihydroorotate dehydrogenase,DHODH)抑制剂的构效关系,为DHODH抑制剂的虚拟筛选提供新的方法.以31个具有DHODH抑制活性的化合物为训练集化合物,半数抑制浓度(IC50)范围为7~63000 nmol/L,利用Catalyst/HypoGen算法构建DHODH抑制剂药效团模型,通过对训练集化合物多个构象进行叠合,提取药效团特征及三维空间限制构建药效团模型.利用基于CatScramble的交叉验证方法及评价模型对已知活性化合物的活性预测能力,确定较优药效团模型.模型包含1个氢键受体、3个疏水中心,表征了受体配体相互作用时可能发生的氢键相互作用、疏水相互作用和π-π相互作用,4个药效特征在三维空间的排列概括了DHODH抑制剂产生活性的结构特点.所得较优模型对训练集化合物及测试集化合物的计算活性值与实验活性值的相关系数分别为0.8405和0.8788.利用药效团模型对来源于微生物的系列化合物进行虚拟筛选,筛选出59个预测活性较好的化合物,可作为进一步药物研发的候选化合物.     

表皮生长因子受体酪氨酸激酶抑制剂的药效团研究

根据一系列表皮生长因子受体酪氨酸激酶抑制剂的三维定量构效关系研究，得 到了该类抑制剂的药效团，研究结果与Novartis的药效团模型相当类似．药效团包 括一个氢键受体，一个氢键给体，一个疏水区和一个带有氯或溴原子药效团对于研 究表皮生长因子受体酪氨酸激酶抑制剂结构与活性的关系具有重要的意义．通过三 维数据库搜索可能会得到新的先导化合物．     

Accounting of ligand–receptor interactions to explore and design novel architecture for PTP 1B inhibition: a legitimate approach

Computer‐aided drug design was performed on a diverse set of 103 biphenyl derivatives that demonstrated antidiabetic activity by restraining the protein tyrosine phosphatase 1B (PTP 1B) receptor. A four‐point pharmacophore hypothesis using the PHASE module of Schrödinger suite with one hydrogen bond acceptor (A) and three aromatic rings (R) as pharmacophoric features was generated. The hypothesis, ARRR.2, considered the best hypothesis in the present study is characterized by survival score (3.553), cross‐validated r² (Q²) (0.722), regression coefficient (0.949), Pearson R (0.867), and F value (492.6). The developed pharmacophore model was externally validated by predicting the activity of test set molecules. Docking algorithm combined with the drug–receptor binding free energetic and pharmacokinetic drug profile envisaged a novel concept, which may provide structural insights for the development of potential PTP 1B inhibitors. The study also provided a valid rapport between pharmacophore drug mapping, atom‐based three‐dimensional quantitative structure–activity relationship, molecular docking, sitemap, molecular simulations, and pharmacokinetic prediction approaches demonstrating the trends in activity. The results of these ligand–receptor relationship studies may account to design a legitimate template for the development and optimization of highly selective and potent PTP 1B inhibitors. Copyright © 2012 John Wiley & Sons, Ltd.     

Development of predictive pharmacophore model for in silico screening,and 3D QSAR CoMFA and CoMSIA studies for lead optimization,for designing of potent tumor necrosis factor alpha converting enzyme inhibitors

A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.     

A three-dimensional chemical phase pharmacophore mapping,QSAR modelling and electronic feature analysis of benzofuran salicylic acid derivatives as LYP inhibitors

Lymphoid tyrosine phosphatase (LYP), encoded by the PTPN22 gene, has a critical negative regulatory role in T-cell antigen receptor (TCR) and emerged as a promising drug target for human autoimmune diseases. A five-point pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and two aromatic ring features was generated for a series of benzofuran salicylic acid derivatives as LYP inhibitors in order to elucidate their anti-autoimmune activity. The generated pharmacophore yielded a significant 3D-QSAR model with r² of 0.9146 for a training set of 27 compounds. The model also showed excellent predictive power with Q² of 0.7068 for a test set of eight compounds. The investigation of the 3D-QSAR model has revealed the structural insights which could lead to more potent analogues. The most active and inactive compounds were further subjected to electronic structure analysis using density functional theory (DFT) at B3LYP/3?21^?G level to support the 3D-QSAR predictions. The results obtained from this study are expected to be useful in the proficient design and development of benzofuran salicylic acid derivatives as inhibitors of LYP.     

β分泌酶抑制剂的药效团模型研究

选择活性跨越0.002至25 μmol•L－1的4类共25个β分泌酶抑制剂作为训练集, 使用Catalyst软件包构建出药效团模型, 并通过对药效团的有效性分析, 筛选得到的最佳模型(correlCorrel＝0.969, Config＝16.32, Δcost＝62.422)由一个环芳香性、一个疏水中心、一个正电荷中心和一个氢键供体组成. 并用其它209个抑制剂组成测试集对模型进行验证, 结果表明该模型显示出较强的预测能力, 能够为进一步的数据库搜索, 寻找新型的β分泌酶抑制剂先导物提供依据.     

Natural compounds as potential Hsp90 inhibitors for breast cancer-Pharmacophore guided molecular modelling studies

Breast cancer is one of the major impediments affecting women globally. The ATP-dependant heat shock protein 90 (Hsp90) forms the central component of molecular chaperone machinery that predominantly governs the folding of newly synthesized peptides and their conformational maturation. It regulates the stability and function of numerous client proteins that are frequently upregulated and/or mutated in cancer cells, therefore, making Hsp90 inhibition a promising therapeutic strategy for the development of new efficacious drugs to treat breast cancer. In the present in silico investigation, a structure-based pharmacophore model was generated with hydrogen bond donor, hydrogen bond acceptor and hydrophobic features complementary to crucial residues Ala55, Lys58, Asp93, Ile96, Met98 and Thr184 directed at inhibiting the ATP-binding activity of Hsp90. Subsequently, the phytochemical dataset of 3210 natural compounds was screened to retrieve the prospective inhibitors after rigorous validation of the model pharmacophore. The retrieved 135 phytocompounds were further filtered by drug-likeness parameters including Lipinski’s rule of five and ADMET properties, then investigated via molecular docking-based scoring. Molecular interactions were assessed using Genetic Optimisation for Ligand Docking program for 95 drug-like natural compounds against Hsp90 along with two clinical drugs as reference compounds – Geldanamycin and Radicicol. Docking studies revealed three phytochemicals are better than the investigated clinical drugs. The reference and hit compounds with dock scores of 48.27 (Geldanamycin), 40.90 (Radicicol), 73.04 (Hit1), 72.92 (Hit2) and 68.12 (Hit3) were further validated for their binding stability through molecular dynamics simulations. We propose that the non-macrocyclic scaffolds of three identified phytochemicals might aid in the development of novel therapeutic candidates against Hsp90-driven cancers.     

黄酮类醛糖还原酶抑制剂的抑制机理研究

为了研究黄酮类醛糖还原酶抑制剂的抑制机理, 选择了31个黄酮类化合物作为训练集, 使用Catalyst软件包构建了此类抑制剂的药效团模型. 并专门针对黄酮类化合物定制了氢键给体和受体模型, 效果优于使用Catalyst内预定义的模型. 最终的药效团模型由两个氢键给体和一个氢键受体组成, 对训练集具有较好预测能力(Correl=0.9013). 此外, 使用InsightII/Affinity对6个黄酮类化合物进行了分子对接研究. 综合药效团模型和分子对接研究的结果, 发现黄酮类化合物的抑制活性主要源于黄酮骨架上的C4’或C3’位的羟基与醛糖还原酶活性口袋中的TYR48、VAL47、GLN49和C7位的羟基与HIS110, TRP111所形成的两组氢键.     

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.