越南槐根的抗HIV活性成分研究

为研究越南槐(Sophora tonkinensis)根的抗HIV蛋白酶活性成分及其分子对接机制,采用硅胶、MCI、Sephadex LH-20等多种色谱分离方法,对越南槐根的化学成分进行分离,采用HIV蛋白酶对化合物进行体外抗HIV活性筛选,运用分子对接手段初步探究活性化合物与HIV-1蛋白酶的结合机制。结果表明,从越南槐中共分离得到8个化合物,根据波谱数据分别鉴定为三叶豆紫檀苷(1)、苦参碱(2)、N-acetylnicotinamide (3)、2′-O-甲基腺苷(4)、毛蕊异黄酮苷(5)、玫瑰花苷(6)、环广豆根素(7)、芒柄花苷(8),此外还分离得到塑化剂衍生物邻苯二甲酸二(2-乙基)己酯(9)和邻苯二甲酸二异丁酯(10)。抗HIV蛋白酶活性测试显示化合物1和2的IC50分别为13.2和38.6μg/m L,分子对接表明其与HIV蛋白酶有一定的结合作用。化合物3～5为首次从该植物中分离得到,化合物1和2显示中等的抗HIV蛋白酶活性。     

鸡血藤中黄酮类化合物与环氧合酶-2对接研究北大核心CSCD

探索黄酮类化合物抗环氧合酶-2的分子机理,筛选鸡血藤中选择性抗环氧合酶-2的黄酮类化合物。本研究应用Autodock 4.2软件对环氧合酶和环氧合酶抑制剂进行分子对接研究,建立阳性抑制剂结合自由能与抑制活性关系模型,并筛选鸡血藤中选择性抗环氧合酶-2的黄酮类化合物。阳性抑制剂与环氧合酶的对接模型R2分别为0.96997和0.84171,建立了预测能力较好的对接模型,可用于指导环氧合酶抑制剂的筛选。筛选结果表明,3',4',7-三羟基黄酮、儿茶素、没食子儿茶素、表儿茶素具有较强的环氧合酶-2选择性抑制活性,可作为母体用于新型抗炎药物设计。     

基于分子对接和系统药理学小青龙汤治疗哮喘的作用机制

为从分子层面阐述小青龙汤治疗哮喘的作用机制,探索小青龙汤的潜在靶标,本研究检索中药系统药理学数据库及分析平台(TCMSP)并根据口服生物利用度(oralbioavailability,OB)、药物相似性(drug-likeness,DL)筛选出小青龙汤的活性成分,利用Pharmmapper数据库筛选小青龙汤潜在作用靶点,挖掘CTD、Genecards数据库以筛选与哮喘相关的作用靶点,利用Cytoscape 3.6.1软件构建小青龙汤的蛋白互作网络图、化合物靶点图,并通过计算拓扑学参数找到小青龙汤中关键的作用靶点和化合物。对小青龙汤对哮喘的作用靶点进行GO分析和KEGG分析。利用iGEMDOCK软件进行分子对接,预测作用靶点和主要化合物的结合度。通过筛选得到小青龙汤活性成分、潜在作用靶点;GO分析得到43个生物学过程、11个细胞组成和9个分子功能;KEGG分析包括PI3K-Akt信号通路、HIF-1信号通路、Wnt信号通路等。初步验证和预测了小青龙汤对治疗哮喘的作用机制,并为进一步深入揭示其作用机制提供参考。     

基于处方挖掘与分子动力学模拟筛选严重急性呼吸综合征冠状病毒2潜在抑制剂分子的研究

目的 从中药筛选具有潜在抑制严重急性呼吸综合征冠状病毒2 （SARS-CoV-2） 活性的成分，进一步从原子水平揭 示其抑制SARS-CoV-2 表面刺突蛋白（S 蛋白） 受体结合域（RBD） 与血管紧张素转化酶2 （ACE2） 结合的内在机制。 方法 检索新型冠状病毒（简称“新冠肺炎”） 治疗中药处方，构建“新冠肺炎中药候选活性成分数据库”。用具有ACE2 抑制活性的小分子化合物构建HipHop药效团模型，并对“新冠肺炎中药候选活性成分数据库”中活性成分筛选。采用分子 对接和分子动力学模拟方法研究候选活性成分与ACE2 的结合方式及其对SARS-CoV-2 S 蛋白与ACE2 识别的影响。 结果 本文通过中药处方挖掘和分子动力学模拟，从143 个新冠肺炎治疗中药处方中筛选出10 种可与SARS-CoV-2 S 蛋白/ 人源ACE2 识别位点结合的中药成分。其中，枇杷叶主要活性成分23-trans-p-coumaryhormentic acid 与ACE2 具有最高的亲和 力，且23-trans-p-coumaryhormentic acid 的结合可有效阻断SARS-CoV-2 S蛋白与宿主细胞ACE2 的结合。结论 本文通过虚 拟筛选发现了SARS-CoV-2 潜在抑制剂分子23-trans-p-coumaryhormentic acid，同时从原子水平预测了其抑制SARS-CoV-2 S 蛋白与ACE2 结合的内在机制，这将为SARS-CoV-2 特异性抗病毒药物的研发提供理论依据。     

基于网络药理学和分子对接技术探讨冬虫夏草治疗肾纤维化的潜在作用机制

为了探究冬虫夏草治疗肾纤维化的分子机制,本研究运用网络药理学方法筛选出冬虫夏草抗肾纤维化的活性成分、潜在作用靶点及相关信号通路,并对关键的化合物和靶点进行分子对接。结果表明,冬虫夏草共有22个化合物和364个潜在靶点参与治疗肾纤维化,蛋白互作（PPI）分析出IL-6、TNF-α、MAPK3、EGFR、SRC、CASP3和MAPK1等关键潜在靶点,KEGG通路富集筛选得到163条信号通路。分子对接结果显示,冬虫夏草治疗肾纤维化过程中,其核心化合物金色酰胺醇酯、啤酒甾醇、酒渣碱、花生四烯酸、11,14-二十碳二烯酸分别与PIK3CA、PIK3CB、PIK3CD、MAPK1、MAPK3、RELA等具有良好的结合性能。分析结果显示,冬虫夏草具有通过多成分、多靶点、多通路减缓肾纤维化的潜力,为其抗肾纤维化临床使用提供了一定的依据。     

基于天然产物的蛋白酪氨酸磷酸酶1B 抑制剂的虚拟筛选

蛋白酪氨酸磷酸酶1B(protein tyrosine phosphatase 1B,PTP1B)是治疗Ⅱ型糖尿病的靶点之一,筛选PTP1B抑制剂具有十分重要的意义.本文采用分子对接虚拟筛选方法,构建共含有42 296个小分子的天然产物库,分别与PTP1B靶点蛋白进行分子对接,以原配体的结合能量为阈值,经过三轮筛选选取打分值高于阈值的小分子进行药代动力学参数和毒性参数预测,最终筛选出3个PTP1B抑制剂,对苯醌类化合物7、异香豆素类衍生物10和Clavepictine类似物11.结合方式研究表明,3个候选抑制剂类药性良好,均具有较好的PTP1B抑制活性,其中化合物10和11的PTP1B抑制活性未见报道.对化合物10进行体外抑制活性检测,其IC50为(74.58±1.23)μmol/L,可作为潜在Ⅱ型糖尿病治疗药物.     

基于天然产物的蛋白酪氨酸磷酸酶1B抑制剂的虚拟筛选（英文）

蛋白酪氨酸磷酸酶1B(protein tyrosine phosphatase 1B,PTP1B)是治疗Ⅱ型糖尿病的靶点之一,筛选PTP1B抑制剂具有十分重要的意义.本文采用分子对接虚拟筛选方法,构建共含有42 296个小分子的天然产物库,分别与PTP1B靶点蛋白进行分子对接,以原配体的结合能量为阈值,经过三轮筛选选取打分值高于阈值的小分子进行药代动力学参数和毒性参数预测,最终筛选出3个PTP1B抑制剂,对苯醌类化合物7、异香豆素类衍生物10和Clavepictine类似物11.结合方式研究表明,3个候选抑制剂类药性良好,均具有较好的PTP1B抑制活性,其中化合物10和11的PTP1B抑制活性未见报道.对化合物10进行体外抑制活性检测,其IC50为(74.58±1.23)μmol/L,可作为潜在Ⅱ型糖尿病治疗药物.     

基于作用机制的氨基恶唑啉呫吨类BACE1抑制剂的分子设计

天冬氨酰蛋白酶(β-site amyloid precursor protein cleaving enzyme 1, BACE1)作为治疗阿尔兹海默症的潜在靶点,其抑制剂的开发已成为医学领域的重要研究方向。本文以59个氨基恶唑啉呫吨类BACE1抑制剂为研究对象,运用比较分子相似性指数(comparative molecular similarity index, CoMSIA)和分子对接方法,深入挖掘影响抑制剂活性的特征结构,以及抑制剂与BACE1间的结合模式和作用力类型,并以此为基础设计新型抑制剂并预测其活性。CoMSIA模拟结果表明,由立体场、静电场、疏水场和氢键供体场4个场组合建立的构效关系模型具有较强的预测能力,交叉验证相关系数Q2=0.48, 非交叉验证相关系数Rncv2=0.94, 外部预测相关系数Rpre2=0.85;通过分子对接,发现抑制剂占据了靶标的S3、S1和S2'位点,与BACE1之间的结合主要是通过氢键作用力和π-π堆积作用实现的;占据S2'位点的R取代基是立体场、静电场和疏水场影响的敏感区域,氨基恶唑啉核心官能团是氢键供体场的敏感区域。基于以上分析获得的抑制剂特征结构信息及其与蛋白质受体的作用机制,成功设计出了新的分子并预测了抑制活性。实验所得模型和信息,为后续新型BACE1抑制剂的结构优化和改造提供了重要理论依据     

鸡血藤中黄酮类化合物与环氧合酶-2对接研究

探索黄酮类化合物抗环氧合酶-2的分子机理,筛选鸡血藤中选择性抗环氧合酶-2的黄酮类化合物。本研究应用Autodock 4.2软件对环氧合酶和环氧合酶抑制剂进行分子对接研究,建立阳性抑制剂结合自由能与抑制活性关系模型,并筛选鸡血藤中选择性抗环氧合酶-2的黄酮类化合物。阳性抑制剂与环氧合酶的对接模型R2分别为0.96997和0.84171,建立了预测能力较好的对接模型,可用于指导环氧合酶抑制剂的筛选。筛选结果表明,3',4',7-三羟基黄酮、儿茶素、没食子儿茶素、表儿茶素具有较强的环氧合酶-2选择性抑制活性,可作为母体用于新型抗炎药物设计。     

新型2-喹诺酮类Polo样激酶1抑制剂的设计合成及分子对接研究

目的:设计合成新型2-喹诺酮类Polo样激酶1(Plk1)抑制剂。方法:以Plk1抑制剂ON 01910为先导化合物,利用生物电子等排原理设计一系列2-喹诺酮类衍生物,用Autodock软件将该类化合物与Plk1进行分子对接和虚拟筛选,计算结合自由能;以取代的氯(溴)苄为起始原料,先后经巯基乙酸取代、双氧水氧化、与(对甲氧基)苯胺酰化,再经环合、水解制得目标化合物。结果:设计的化合物大多数与Plk1的结合自由能均比ON 01910的低,结合强度高、稳定性好;合成了16个2-喹诺酮类衍生物,产物结构经1H-NMR确证。结论:所得化合物中有15个为新化合物,化合物的结构设计科学合理,虚拟筛选结果良好,为后续实体筛选和化合物结构优化提供了理论依据和参考。     

Discovery of promising FtsZ inhibitors by E-pharmacophore, 3D-QSAR,molecular docking study,and molecular dynamics simulation

Filamentous temperature-sensitive protein Z (FtsZ), playing a key role in bacterial cell division, is regarded as a promising target for the design of antimicrobial agent. This study is looking for potential high-efficiency FtsZ inhibitors. Ligand-based pharmacophore and E-pharmacophore, virtual screening and molecular docking were used to detect promising FtsZ inhibitors, and molecular dynamics simulation was used to study the stability of protein-ligand complexes in this paper. Sixty-three inhibitors from published literatures with pIC₅₀ ranging from 2.483 to 5.678 were collected to develop ligand-based pharmacophore model. 4DXD bound with 9PC was selected to develop the E-pharmacophore model. The pharmacophore models validated by test set method and decoy set were employed for virtual screening to exclude inactive compounds against ZINC database. After molecular docking, ADME analysis, IFD docking and MM-GBSA, 8 hits were identified as potent FtsZ inhibitors. A 50?ns molecular dynamics simulation was implemented on the compounds to assess the stability between potent inhibitors and FtsZ. The results indicated that the candidate compounds had a high docking score and were strongly combined with FtsZ by forming hydrogen bonding interactions with key amino acid residues, and van der Waals forces and hydrophobic interactions had significant contribution to the stability of the binding. Molecular dynamics simulation results showed that the protein-ligand compounds performed well in both the stability and flexibility of the simulation process.     

Novel virtual lead identification in the discovery of hematopoietic cell kinase (HCK) inhibitors: application of 3D QSAR and molecular dynamics simulation

High level of hematopoietic cell kinase (Hck) is associated with drug resistance in chronic myeloid leukemia. Additionally, Hck activity has also been connected with the pathogenesis of HIV-1 and chronic obstructive pulmonary disease. In this study, three-dimensional (3D) QSAR pharmacophore models were generated for Hck based on experimentally known inhibitors. A best pharmacophore model, Hypo1, was developed with high correlation coefficient (0.975), Low RMS deviation (0.60) and large cost difference (49.31), containing three ring aromatic and one hydrophobic aliphatic feature. It was further validated by the test set (r?=?0.96) and Fisher’s randomization method (95%). Hypo 1 was used as a 3D query for screening the chemical databases, and the hits were further screened by applying Lipinski’s rule of five and ADMET properties. Selected hit compounds were subjected to molecular docking to identify binding conformations in the active site. Finally, the appropriate binding modes of final hit compounds were revealed by molecular dynamics (MD) simulations and free energy calculation studies. Hence, we propose the final three hit compounds as virtual candidates for Hck inhibitors.     

Identification of potential inhibitors for HCV NS3 genotype 4a by combining protein–ligand interaction fingerprint, 3D pharmacophore,docking, and dynamic simulation

HCV NS3 protease domain has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting HCV genotype 1 infection. HCV genotype 4a dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS3 of genotype 4a using homology modeling, PLIF (protein–ligand interaction fingerprint), docking, pharmacophore, and dynamic simulation. A high-quality 3D model of HCV NS3 protease of genotype 4a was constructed using crystal structure of HCV NS3 protease of genotype 1b (PDB ID: 4u01) as a template. PLIF was generated using five crystal structures of HCV NS3 (PDB ID: 4u01, 3kee, 4ktc, 4i33, and 5epn) which revealed the most important residues and their interactions with the co-crystalized ligands. A 3D pharmacophore model consisting of six features was developed from the generated PLIF data and then used as a screening filter for 11,244 compounds. Only 423 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. The highest ranked five hits from docking result (compound (C1–C5)) were selected for further analysis. They exhibited stronger interaction and higher binding affinity than HCV NS3 protease ligands. Dynamic simulation of the protein–best lead complex was performed to validate and augment the virtual screening results and it showed that these compounds have a strong binding affinity and could be very effective in treating HCV genotype 4a infections.     

Pharmacophore models generation by catalyst and phase consensus-based virtual screening protocol against PI3Kα inhibitors

Phosphoinositide 3-kinases (PI3Ks) family has emerged as promising targets for novel therapeutic agents against neoplastic diseases. Pharmacophore and 3D-quantitative structure–activity relationship modelling were applied to study the structure–activity relationship of PI3K inhibitors. The best HypoGen pharmacophore hypothesis Hypo1 with a correlation coefficient of 0.961 consists of one hydrogen-bond acceptor, one hydrogen-bond donor and two hydrophobic features, whereas the best phase hypothesis AADRRR.378 with favourable statistics (q² = 0.7368, r² = 0.9863) has two hydrogen-bond acceptors, one hydrogen-bond donor and three ring aromatic features. Multiple methods, such as Fischer validation, molecular docking and mapping of test set molecules, were carried out to validate these pharmacophore models. Furthermore, a comparative molecular similarity indices analysis candidate hypothesis model was generated as a supplement of pharmacophore hypothesis. Detailed protein–ligand binding information obtained by Glide was utilised in compound optimisation and virtual screening. A molecular database of 133 known inhibitors and 6179 decoys was built for a screening test to quantitatively analyse various hypotheses and scoring parameters. Finally, we designed a workflow integrating HypoGen pharmacophore searching, phase pharmacophore searching and molecular docking for screening the database. With an improved criterion of enrichment factor (EF = 17.43) and ROC curve (AUC = 0.946), this workflow would provide us an original method for novel PI3K inhibitors.     

Rational design of 2-pyrrolinones as inhibitors of HIV-1 integrase

HIV-1 integrase is an essential enzyme for viral replication and a validated target for the development of drugs against AIDS. With an aim to discover new potent inhibitors of HIV-1 integrase, we developed a pharmacophore model based on reported inhibitors embodying structural diversity. Eight compounds of 2-pyrrolinones fitting all the features of the pharmacophore query were found through the screening of an in-house database. These candidates were successfully synthesized, and three of them showed strand transfer inhibitory activity, in which, one compound showed antiviral activity. Further mapping analysis and docking studies affirmed these results.     

HIV-1 integrase pharmacophore model derived from diverse classes of inhibitors

A three-dimensional pharmacophore model has been generated for HIV-1 integrase (HIV-1 IN) from known inhibitors. A dataset consisting of 26 inhibitors was selected on the basis of the information content of the structures and activity data as required by the catalyst/HypoGen program. Our model was able to predict the activity of other known HIV-1 IN inhibitors not included in the model generation, and can be further used to identify structurally diverse compounds with desired biological activity by virtual screening.     

Discovery of potent apoptosis signal-regulating kinase 1 inhibitors via integrated computational strategy and biological evaluation

Abstract

Apoptosis signal-regulating Kinase 1 (ASK1) has been confirmed as a potential therapeutic target for the treatment of non-alcoholic steatohepatitis (NASH) disorder and the discovery of ASK1 inhibitors has attracted increasing attention. In this work, a series of in silico methods including pharmacophore screening, docking binding site analysis, protein-ligand interaction fingerprint (PLIF) similarity investigation and molecular docking were applied to find the potential hits from commercial compound databases. Five compounds with potential inhibitory activity were purchased and submitted to biological activity validation. Thus, one hit compound was discovered with micromolar IC₅₀ value (10.59?μM) against ASK1. Results demonstrated that the integration of computation methods and biological test was quite reliable for the discovery of potent ASK1 inhibitors and the strategy could be extended to other similar targets of interest.     

Discovery of selective farnesoid X receptor agonists for the treatment of hyperlipidemia from traditional Chinese medicine based on virtual screening and in vitro validation

Abstract

Farnesoid X receptor (FXR), a bile acid receptor, has important roles in maintaining bile acid and cholesterol homeostasis, which is an attractive target for hyperlipidemia. Present study aimed to discover potential selective FXR agonists over G-protein coupled bile acid receptor 1 (GPBAR1, TGR5) from traditional Chinese medicine (TCM) by using virtual screening, in vitro studies and molecular dynamics simulation (MD). Ligand-based pharmacophore model for FXR was firstly built to screen FXR agonists from the Traditional Chinese Medicine Database (TCMD). Then, 21 FXR crystal structures were clustered in two types and two representative structures (PDB ID: 3OMM and 3P89) were, respectively, used to carry out molecular docking to refine the screened result. Moreover, the pharmacophore model for GPBAR1 was built to screen selective FXR agonists with no activity on GPBAR1. A set of 24 candidate selective FXR agonists which fitvalue of FXR pharmacophore model and docking score of 3OMM and 3P89 were in the top 100 and cannot match the pharmacophore model for GPBAR1 were obtained. By the lipid-lowering activity test in HepG2 cell lines, Arctigenin was identified to be potential selective FXR agonist with the activity of 20?μmol·L^?1. After down-regulating FXR, Arctigenin could increase the mRNA of FXR while exerted no effect on the mRNA of GPBAR1. MD was further used to interpret the mechanism of Arctigenin with the representative structures. This research provided a new screening procedure for finding selective candidate compounds and appropriate docking models of a target by considering the structure diversity of PDB structures, which was applied to discovery novel selective FXR agonists to treat hyperlipidemia.

Communicated by Ramaswamy H. Sarma     

Dynamic and Multi-Pharmacophore Modeling for Designing Polo-Box Domain Inhibitors

The polo-like kinase 1 (Plk1) is a critical regulator of cell division that is overexpressed in many types of tumors. Thus, a strategy in the treatment of cancer has been to target the kinase activity (ATPase domain) or substrate-binding domain (Polo-box Domain, PBD) of Plk1. However, only few synthetic small molecules have been identified that target the Plk1-PBD. Here, we have applied an integrative approach that combines pharmacophore modeling, molecular docking, virtual screening, and in vitro testing to discover novel Plk1-PBD inhibitors. Nine Plk1-PBD crystal structures were used to generate structure-based hypotheses. A common pharmacophore model (Hypo1) composed of five chemical features was selected from the 9 structure-based hypotheses and used for virtual screening of a drug-like database consisting of 159,757 compounds to identify novel Plk1-PBD inhibitors. The virtual screening technique revealed 9,327 compounds with a maximum fit value of 3 or greater, which were selected and subjected to molecular docking analyses. This approach yielded 93 compounds that made good interactions with critical residues within the Plk1-PBD active site. The testing of these 93 compounds in vitro for their ability to inhibit the Plk1-PBD, showed that many of these compounds had Plk1-PBD inhibitory activity and that compound Chemistry_28272 was the most potent Plk1-PBD inhibitor. Thus Chemistry_28272 and the other top compounds are novel Plk1-PBD inhibitors and could be used for the development of cancer therapeutics.