人类丝氨酸消旋酶的同源模建及其与多肽类抑制剂的分子对接

利用同源模建和分子动力学模拟方法构建了人类丝氨酸消旋酶(hSR)的三维结构, 并利用profile-3D和procheck方法评估了模型的可靠性. 在此基础上用分子对接程序(affinity)将多肽类抑制剂A和B分别与hSR进行对接, 获得了其复合物结构的理论模型. 通过配体与受体之间相互作用能和结构分析给出了此类抑制剂与hSR的具体结合方式, 明确了hSR与此类抑制剂结合时起重要作用的氨基酸残基, 为基于人类丝氨酸消旋酶三维结构的药物设计提供重要的参考信息.     

GPCR structure-based virtual screening approach for CB2 antagonist search

The potential for therapeutic specificity in regulating diseases has made cannabinoid (CB) receptors one of the most important G-protein-coupled receptor (GPCR) targets in search for new drugs. Considering the lack of related 3D experimental structures, we have established a structure-based virtual screening protocol to search for CB2 bioactive antagonists based on the 3D CB2 homology structure model. However, the existing homology-predicted 3D models often deviate from the native structure and therefore may incorrectly bias the in silico design. To overcome this problem, we have developed a 3D testing database query algorithm to examine the constructed 3D CB2 receptor structure model as well as the predicted binding pocket. In the present study, an antagonist-bound CB2 receptor complex model was initially generated using flexible docking simulation and then further optimized by molecular dynamic and mechanical (MD/MM) calculations. The refined 3D structural model of the CB2-ligand complex was then inspected by exploring the interactions between the receptor and ligands in order to predict the potential CB2 binding pocket for its antagonist. The ligand-receptor complex model and the predicted antagonist binding pockets were further processed and validated by FlexX-Pharm docking against a testing compound database that contains known antagonists. Furthermore, a consensus scoring (CScore) function algorithm was established to rank the binding interaction modes of a ligand on the CB2 receptor. Our results indicated that the known antagonists seeded in the testing database can be distinguished from a significant amount of randomly chosen molecules. Our studies demonstrated that the established GPCR structure-based virtual screening approach provided a new strategy with a high potential for in silico identifying novel CB2 antagonist leads based on the homology-generated 3D CB2 structure model.     

Molecular modelling studies on the ORL1-receptor and ORL1-agonists

The ORLI (opioid receptor like 1)- receptor is a member of the family of rhodopsin-like G protein-coupled receptors (GPCR) and represents an interesting new therapeutical target since it is involved in a variety of biomedical important processes, such as anxiety, nociception, feeding, and memory. In order to shed light on the molecular basis of the interactions of the GPCR with its ligands, the receptor protein and a dataset of specific agonists were examined using molecular modelling methods. For that purpose, the conformational space of a very potent non-peptide ORL1-receptor agonist (Ro 64-6198) with a small number of rotatable bonds was analysed in order to derive a pharmacophoric arrangement. The conformational analyses yielded a conformation that served as template for the superposition of a set of related analogues. Structural superposition was achieved by employing the program FlexS. Using the experimental binding data and the superposition of the ligands, a 3D-QSAR analysis applying the GRID/GOLPE method was carried out. After the ligand-based modelling approach, a 3D model of the ORL1-receptor has been constructed using homology modelling methods based on the crystal structure of bovine rhodopsin. A representative structure of the model taken from molecular dynamics simulations was used for a manual docking procedure. Asp-130 and Thr-305 within the ORL1-receptor model served as important hydrophilic interaction partners. Furthermore, a hydrophobic cavity was identified stabilizing the agonists within their binding site. The manual docking results were supported using FlexX, which identified the same protein-ligand interaction points.     

辛味中药与嗅觉受体相互作用的分子模拟

采用分子模拟的方法, 在Schrdinger软件平台上, 用同源模建的方法构建了嗅觉受体OR1D2, OR7D4和OR51E1的三维结构模型. 运用分子动力学模块Desmond将与激动剂以及抑制剂分别对接的嗅觉受体复合物置于磷脂双膜中进行模拟. 最后将辛味中药的小分子分别对接到嗅觉受体中, 并与苦味中药的对接结果相对照, 依据实验结果, 讨论辛味中药发挥作用的分子机制. 该研究着重于同源模建、分子动力学和分子对接技术的综合应用, 探讨辛味中药化学成分与嗅觉受体的相互作用及其分子机理, 为从分子层面揭示辛味中药的药效物质基础提供帮助, 也为中药药性的研究提供了新的思路和方法.     

CCK1受体的同源模拟和分子对接研究

采用同源建模法对CCK1受体的三维结构进行了模拟,并采用分子动力学方法对模型进行修正和优化,再采用与训练集激动剂和拮抗剂分子对接的方法分别得到激动状态和拮抗状态CCK1受体的三维结构模型。得到的模型使用DOCK对接软件对训练集中的分子进行对接,所得结果与其实际活性拟合度较好,说明我们建立的激动和拮抗状态下的CCK1受体的三维结构模型比较合理,可以作为化合物虚拟筛选的模型对新化合物进行虚拟筛选。     

Expression of Somatostatin Receptor Subtypes (SSTR-1–SSTR-5) in Pediatric Hematological and Oncological Disorders

Hematological and oncological disorders represent leading causes of childhood mortality. Neuropeptide somatostatin (SST) has been previously demonstrated in various pediatric tumors, but limited information exists on the expression and characteristics of SST receptors (SSTR) in hematological and oncological disorders of children. We aimed to investigate the expression of mRNA for SSTR subtypes (SSTR-1–5) in 15 pediatric hematological/oncological specimens by RT-PCR. The presence and binding characteristics of SSTRs were further studies by ligand competition assay. Our results show that the pediatric tumor samples highly expressed mRNA for the five SSTR subtypes with various patterns. The mRNA for SSTR-2 was detected in all specimens independently of their histological type. A Hodgkin lymphoma sample co-expressed mRNA for all five SSTR subtypes. SSTR-3 and SSTR-5 were detected only in malignant specimens, such as rhabdomyosarcoma, Hodgkin lymphoma, acute lymphoblastic leukemia, and a single nonmalignant condition, hereditary spherocytosis. The incidence of SSTR-1 and SSTR-4 was similar (60%) in the 15 specimens investigated. Radioligand binding studies demonstrated the presence of specific SSTRs and high affinity binding of SST analogs in pediatric solid tumors investigated. The high incidence of SSTRs in hematological and oncological disorders in children supports the merit of further investigation of SSTRs as molecular targets for diagnosis and therapy.     

3C-like蛋白酶抑制剂的构效关系、分子对接和分子动力学

3C-like蛋白酶是中东呼吸综合征冠状病毒（MERS-CoV）等其它冠状病毒的繁殖过程中极为重要的蛋白酶。它已成为人类在抗冠状病毒领域中的研究热点。本文基于计算生物学方法对与MERS-CoV同属的蝙蝠冠状病毒HKU4（HKU4-CoV）的43个肽类3C-like蛋白酶抑制剂分子,建立三维定量构效关系（3D-QSAR）模型。在基于配体叠合的基础上,发现比较分子相似性指数分析法（CoMSIA）中的四个场组合（位阻场、静电场、氢键供体场与氢键受体场）为最优的模型（Q²=0.522,R_ncv²=0.996,R_pre²=0.904;Q²：交叉验证相关系数,R_ncv²：非交叉验证相关系数,R_pre²：验证集分子的预测值相关系数）,并借助该模型通过分子对接（docking）与分子动力学（MD）方法阐明了配受体结合作用。实验结果表明：（1）基于最优的CoMSIA模型基础上的三维等势图形象地说明了分子基团的位阻作用、静电作用、氢键供体与氢键受体作用对分子生物活性的影响;（2）分子对接研究结果显示了疏水性以及结晶水、氨基酸His166和Glu169在配体和受体结合过程中产生重要作用;（3）分子动力学模拟进一步验证了分子对接模型的可靠性,并发现了两个新的关键氨基酸Ser24与Gln192,它们与配体产生了两个较强的氢键。此外,根据这些结果,一些新的具有潜在抑制活性的肽类化合物作为3C-like蛋白酶抑制剂被获得。以上结果能够帮助深入了解3C-like蛋白酶与肽类抑制剂的作用机理,并且能够为今后的抗MERS-CoV药物设计提供有价值的参考。     

4-苄基哌啶类拮抗剂选择性识别hCCR3的分子模拟

以牛视网膜紫质X射线衍射晶体结构为模板, 参考定位突变实验数据, 采用配体支持同源模建(Ligand-supported homology modeling)方法构建了拮抗剂键合(Antagonist-bound)的人类趋化因子受体hCCR3和hCCR1的三维结构模型. 将一系列1,4-二取代哌啶类拮抗剂分别对接进优化后的hCCR3和hCCR1模型中, 以配体在hCCR3中的结合自由能理论值对-lgIC₅₀值进行线性回归, 确定性系数r²为0.94. 分析对接结果发现, 配体主要通过疏水芳香作用与hCCR3结合, 而4-苄基哌啶类拮抗剂对hCCR3产生选择性的主要原因在于配体的哌啶环与hCCR3中Tyr255(TM7)的苯酚侧链产生面对面的范德华作用, 而且hCCR3中处于结合口袋的EL2区的疏水性也为拮抗剂对hCCR3的选择性做出了贡献.     

人类2-氨基3-羧基粘康酸6-半醛脱羧酶(ACMSD)与底物及抑制剂作用模型的理论研究

利用同源模建和分子动力学模拟方法构建了人类2-氨基3-羧基粘康酸6-半醛脱羧酶(hACMSD)的三维结构, 并利用Profile-3D和Procheck等方法评估了模型的可靠性. 在此基础上, 用分子对接程序(Affinity), 将其底物2-氨基3-羧基粘康酸6-半醛(ACMS)和抑制剂喹啉酸(QA)分别与hACMSD进行对接, 获得了复合物结构的理论模型. 通过配体与受体之间相互作用能和结构分析给出了底物和抑制剂的具体结合方式, 明确了hACMSD与底物和抑制剂结合时起重要作用的氨基酸残基.     

人类胞外信号调节激酶1的同源模建及其抑制剂的对接与结构改造

通过同源模建和分子动力学模拟构建了人类胞外信号调节激酶1(hERK1)的三维结构,并利用profile-3D和procheck方法评估了模型的合理性.对所得的结构使用分子对接程序Affinity和CDOCKER进行了两种抑制剂的对接.结果显示这两种抑制剂与酶的结合方式相似,它们均与残基K36,Q87之间存在氢键作用,二者取代基的不同导致了抑制能力的差别.基于对接结果分析,对已知抑制剂进行结构改造,得到了一个理论上结合能力更强的抑制剂.它在保持与K36和Q87之间氢键的同时,又与残基D93,K96,S135形成了四条氢键,显著提高了与酶的相互作用.对接相互作用能显著下降,MM-PBSA结合自由能降为负值,这些均体现了抑制能力的提高.本工作对于针对该酶的抑制剂设计和相关疾病的新药开发具有理论指导价值.     

Modelling of the binding site of the human m1 muscarinic receptor: Experimental validation and refinement

Our model of the human m1 muscarinic receptor has been refined on the basis of the recently published projection map of bovine rhodopsin. The refined model has a slightly different helix arrangement, which reveals the presence of an extra hydrophobic pocket located between helices 3, 4 and 5. The interaction of series of agonists and antagonists with the m1 muscarinic receptor has been studied experimentally by site-directed mutagenesis. In order to account for the observed results, three-dimensional models of m1 ligands docked in the target receptor are proposed. Qualitatively, the obtained models are in good agreement with the experimental observations. Agonists and partial agonists have a relatively small size. They can bind to the same region of the receptor using, however, different anchoring receptor residues. Antagonists are usually larger molecules, filling almost completely the same pocket as agonists. They can usually produce much stronger interactions with aromatic residues. Experimental data combined with molecular modelling studies highlight how subtle and diverse receptor–ligand interactions could be.     

表皮生长因子受体和抑制剂之间分子对接的研究

研究了表皮生长因子受体(EGFR)和4-苯胺喹唑啉类抑制剂之间的相互作用模式，表皮生长因子受体的三维结构通过同源蛋白模建的方法得到，而抑制剂和靶酶结合复合物结构则通过分子力学和分子动力学结合的方法计算得到。从模拟结果得到的抑制剂和靶酶之间的相互作用模式表明范德华相互作用、疏水相互作用以及氢键相互作用对抑制剂的活性都有重要的影响，抑制剂的苯胺部分位于活性口袋的底部，能够与受体残基的非极性侧链产生很强的范德华和疏水相互作用，抑制剂双环上的取代基团也能和活性口袋外部的部分残基形成一定的范德华和疏水性相互作用，而抑制剂喹唑啉环上的氮原子能和周围的残基形成较强的氢键相互作用，对抑制剂的活性有较大的影响，计算得到抑制剂和靶酶之间的非键相互作用能以及抑制剂和靶酶之间的相互作用信息能够很好地解释抑制剂活性和结构的关系，为全新抑制剂的设计提供了重要的结构信息。     

Three-dimensional modelling of human cytochrome P450 1A2 and its interaction with caffeine and MeIQ

The three-dimensional modelling of proteins is a useful tool to fill the gap between the number of sequenced proteins and the number of experimentally known 3D structures. However, when the degree of homology between the protein and the available 3D templates is low, model building becomes a difficult task and the reliability of the results depends critically on the correctness of the sequence alignment. For this reason, we have undertaken the modelling of human cytochrome P450 1A2 starting by a careful analysis of several sequence alignment strategies (multiple sequence alignments and the TOPITS threading technique). The best results were obtained using TOPITS followed by a manual refinement to avoid unlikely gaps. Because TOPITS uses secondary structure predictions, several methods that are available for this purpose (Levin, Gibrat, DPM, NnPredict, PHD, SOPM and NNSP) have also been evaluated on cytochromes P450 with known 3D structures. More reliable predictions on -helices have been obtained with PHD, which is the method implemented in TOPITS. Thus, a 3D model for human cytochrome P450 1A2 has been built using the known crystal coordinates of P450 BM3 as the template. The model was refined using molecular mechanics computations. The model obtained shows a consistent location of the substrate recognition segments previously postulated for the CYP2 family members. The interaction of caffeine and a carcinogenic aromatic amine (MeIQ), which are characteristic P450 1A2 substrates, has been investigated. The substrates were solvated taking into account their molecular electrostatic potential distributions. The docking of the solvated substrates in the active site of the model was explored with the AUTODOCK programme, followed by molecular mechanics optimisation of the most interesting complexes. Stable complexes were obtained that could explain the oxidation of the considered substrates by cytochrome P450 1A2 and could offer an insight into the role played by water molecules.     

Molecular Docking of SP40 Peptide towards Cellular Receptors for Enterovirus 71 (EV-A71)

Enterovirus 71 (EV-A71) is one of the predominant etiological agents of hand, foot and mouth disease (HMFD), which can cause severe central nervous system infections in young children. There is no clinically approved vaccine or antiviral agent against HFMD. The SP40 peptide, derived from the VP1 capsid of EV-A71, was reported to be a promising antiviral peptide that targeted the host receptor(s) involved in viral attachment or entry. So far, the mechanism of action of SP40 peptide is unknown. In this study, interactions between ten reported cell receptors of EV-A71 and the antiviral SP40 peptide were evaluated through molecular docking simulations, followed by in vitro receptor blocking with specific antibodies. The preferable binding region of each receptor to SP40 was predicted by global docking using HPEPDOCK and the cell receptor-SP40 peptide complexes were refined using FlexPepDock. Local molecular docking using GOLD (Genetic Optimization for Ligand Docking) showed that the SP40 peptide had the highest binding score to nucleolin followed by annexin A2, SCARB2 and human tryptophanyl-tRNA synthetase. The average GoldScore for 5 top-scoring models of human cyclophilin, fibronectin, human galectin, DC-SIGN and vimentin were almost similar. Analysis of the nucleolin-SP40 peptide complex showed that SP40 peptide binds to the RNA binding domains (RBDs) of nucleolin. Furthermore, receptor blocking by specific monoclonal antibody was performed for seven cell receptors of EV-A71 and the results showed that the blocking of nucleolin by anti-nucleolin alone conferred a 93% reduction in viral infectivity. Maximum viral inhibition (99.5%) occurred when SCARB2 was concurrently blocked with anti-SCARB2 and the SP40 peptide. This is the first report to reveal the mechanism of action of SP40 peptide in silico through molecular docking analysis. This study provides information on the possible binding site of SP40 peptide to EV-A71 cellular receptors. Such information could be useful to further validate the interaction of the SP40 peptide with nucleolin by site-directed mutagenesis of the nucleolin binding site.     

神经介素B受体与拮抗剂、激动剂的分子模拟研究

大鼠神经介素B受体(rat neuromedin B receptor, rNMBR)属于G蛋白偶联受体(G-protein coupled receptor, GPCR) A家族的成员. GPCR的结构特征和在信号传导中的重要作用决定了其可以作为很好的药物靶标. 关于rNMBR与内源性激动剂神经介素B (neuromedin B, NMB)以及与非肽类拮抗剂pd168368作用机制的研究对于合理设计受体药物分子有重要的指导意义. 在这一研究中, 我们使用同源模建, 构建受体的三维结构, 进行分子对接和分子动力学的计算. 基于受体三维结构, 通过10 ns的空载受体、激动剂-受体、拮抗剂-受体的分子动力学模拟, 探讨受体与激动剂与拮抗剂的作用机制. 研究表明rNMB-R中跨膜(transmembrane, TM)螺旋3, 5, 6, 7参与配体的结合. NMB与受体的结合, 使受体转变为活性构象, 而受体同拮抗剂pd168368恰好相反.     

含磷嘧啶类CDK9抑制剂的分子对接、3D-QSAR和分子动力学模拟

选取64个具有潜力的含磷嘧啶类细胞周期依赖性蛋白激酶(CDK9)小分子抑制剂,采用分子对接方法研究了该类小分子与CDK9的结合作用,结果表明,分子构象、氢键形成、疏水性和氨基酸残基Cys106在此类抑制剂与CDK9的结合过程中具有重要作用.在配体叠合的基础上,运用比较分子力场分析(Co MFA)、比较分子相似性指数分析(Co MSIA)和Topomer Co MFA(T-COMFA)研究了分子结构与抑制活性的关系,发现由训练集立体场、静电场和疏水场组合的Co MSIA模型为最优模型,其内部交叉验证相关系数(Q2=0.557)、非交叉验证相关系数(R2=0.959)和外部预测相关系数(r2=0.863)具有统计学意义,该模型的三维等值线图直观显示了化合物的活性与其三维结构的关系.根据这些结果设计了10个具有新结构的含磷嘧啶类化合物,分子对接和分子动力学模拟结果表明,新化合物和CDK9的结合模式与原化合物64相同,自由能分析从理论上证明了新化合物64d的CDK9抑制活性优于化合物64,并且显示含磷基团与残基Asp109的静电场能在化合物与CDK9作用过程中有重要作用.     

3D-QSAR and receptor modeling of tyrosine kinase inhibitors with flexible atom receptor model (FLARM)

A set of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors was investigated with the aim of developing 3D-QSAR models using the Flexible Atom Receptor Model (FLARM) method. Some 3D-QSAR models were built with high correlation coefficients, and the FLARM method predicted the biological activities of compounds in test set well. The FLARM method also gave the pseudoreceptor model, which indicates the possible interactions between the receptor and the ligand. The possible interactions include two hydrogen bonds, one hydrophobic interaction, and one sulfur-aromatic interaction, which are in accord with those in the pharmacophore model given by the scientists at Novartis. This shows that the FLARM method can bridge 3D-QSAR and receptor modeling in computer-aided drug design. Pharmacophore can be obtained according to these results, and 3D searching can then be done with databases to find the lead compound of EGFR tyrosine kinase inhibitors.     

Multi-way PLS modeling of structure–activity data by incorporating electrostatic and lipophilic potentials on molecular surface

We devised and elaborated a surface-based three-dimensional-quantitative structure–activity relationship (3D-QSAR) method, which had been proposed in the previous study. This approach can be applied to more general case where both the electrostatic and lipophilic potentials on molecular surface simultaneously change. The 3D coordinates of all sampling points on molecular surface are projected into a 2D map by Kohonen neural network (KNN). Each node in the map is coded by the associated molecular electrostatic potential (MEP) or molecular lipophilic potential (MLP) values. The electrostatic and lipophilic KNN maps are generated for each compound and the four-way array is constructed by collecting two KNN maps of all samples. The correlation between four-way array and biological activity is examined by four-way partial least-squares (PLS). For validation, the structure–activity data of estrogen receptor antagonists was investigated. The four-way PLS model gave the high statistics at calibration and validation stages. The coefficients of the four-way PLS model back-projected on molecular surface had a reasonable 3D distribution and it was nicely consistent with active site of the estrogen receptor which was recently made clear by X-ray crystallography.     

Multi-way PLS modeling of structure-activity data by incorporating electrostatic and lipophilic potentials on molecular surface

We devised and elaborated a surface-based three-dimensional-quantitative structure-activity relationship (3D-QSAR) method, which had been proposed in the previous study. This approach can be applied to more general case where both the electrostatic and lipophilic potentials on molecular surface simultaneously change. The 3D coordinates of all sampling points on molecular surface are projected into a 2D map by Kohonen neural network (KNN). Each node in the map is coded by the associated molecular electrostatic potential (MEP) or molecular lipophilic potential (MLP) values. The electrostatic and lipophilic KNN maps are generated for each compound and the four-way array is constructed by collecting two KNN maps of all samples. The correlation between four-way array and biological activity is examined by four-way partial least-squares (PLS). For validation, the structure-activity data of estrogen receptor antagonists was investigated. The four-way PLS model gave the high statistics at calibration and validation stages. The coefficients of the four-way PLS model back-projected on molecular surface had a reasonable 3D distribution and it was nicely consistent with active site of the estrogen receptor which was recently made clear by X-ray crystallography.