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。     

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.     

多肽抑制剂抑制淀粉质多肽42构象转换的分子动力学模拟和结合自由能计算

应用分子动力学模拟和结合自由能计算方法研究了多肽抑制剂KLVFF、VVIA和LPFFD抑制淀粉质多肽42 (Aβ42)构象转换的分子机理. 结果表明, 三种多肽抑制剂均能够有效抑制Aβ42的二级结构由α-螺旋向β-折叠的构象转换. 另外, 多肽抑制剂降低了Aβ42分子内的疏水相互作用, 减少了多肽分子内远距离的接触, 有效抑制了Aβ42的疏水塌缩, 从而起到稳定其初始构象的作用. 这些抑制剂与Aβ42之间的疏水和静电相互作用(包括氢键)均有利于它们抑制Aβ42的构象转换. 此外, 抑制剂中的带电氨基酸残基可以增强其和Aβ42之间的静电相互作用(包括氢键), 并降低抑制剂之间的聚集, 从而大大增强对Aβ42构象转换的抑制能力. 但脯氨酸的引入会破坏多肽的线性结构, 从而大大降低其与Aβ42 之间的作用力. 上述分子模拟的结果揭示了多肽抑制剂KLVFF、VVIA和LPFFD抑制Aβ42构象转换的分子机理, 对于进一步合理设计Aβ的高效短肽抑制剂具有非常重要的理论指导意义.     

新型二氟甲基磷酸类酪氨酸蛋白磷酸酯酶1B抑制剂的分子动力学模拟和结合自由能计算

通过分子对接建立了一系列含二氟甲基磷酸基团(DFMP)或二氟甲基硫酸基团(DFMS)的抑制剂与酪氨酸蛋白磷酸酯酶1B(PTP1B)的相互作用模式, 并通过1 ns的分子动力学模拟和molecular mechanics/generalized Born surface area (MM/GBSA)方法计算了其结合自由能. 计算获得的结合自由能排序和抑制剂与靶酶间结合能力排序一致; 通过基于主方程的自由能计算方法, 获得了抑制剂与靶酶残基间相互作用的信息, 这些信息显示DFMP/DFMS基团的负电荷中心与PTP1B的221位精氨酸正电荷中心之间的静电相互作用强弱决定了此类抑制剂的活性, 进一步的分析还显示位于DFMP/DFMS基团中的氟原子或其他具有适当原子半径的氢键供体原子会增进此类抑制剂与PTP1B活性位点的结合能力.     

新型二氟甲基磷酸类酪氨酸蛋白磷酸酯酶1B抑制剂的分子动力学模拟和结合自由能计算（英文）

通过分子对接建立了一系列含二氟甲基磷酸基团（DFMP）或二氟甲基硫酸基团（DFMS）的抑制剂与酪氨酸蛋白磷酸酯酶1B（PTP1B）的相互作用模式,并通过1ns的分子动力学模拟和molecular mechanics/generalized Born surface area（MM/GBSA）方法计算了其结合自由能.计算获得的结合自由能排序和抑制剂与靶酶间结合能力排序一致;通过基于主方程的自由能计算方法,获得了抑制剂与靶酶残基间相互作用的信息,这些信息显示DFMP/DFMS基团的负电荷中心与PTP1B的221位精氨酸正电荷中心之间的静电相互作用强弱决定了此类抑制剂的活性,进一步的分析还显示位于DFMP/DFMS基团中的氟原子或其他具有适当原子半径的氢键供体原子会增进此类抑制剂与PTP1B活性位点的结合能力.     

非对称二甲基精氨酸二甲胺水解酶-2的理论研究

利用同源模建的方法,构建了DDAH-2的三位结构.并与L-瓜氨酸、L-高半胱氨酸分别进行对接研究.其中,Asp77,Gly269,Glu27和Arg96是与L-瓜氨酸相互作用较强的残基,Asp77,His171,Asp125和Ala270是与-L高半胱氨酸相互作用较强的残基.尤其Asp77是在两种复合物中同时起重要作用的氨基酸,并且它与抑制剂之间都形成了氢键.     

毒素DON单链抗体的同源建模及与DON结合的分子模拟研究

通过同源模建及分子力学构建并优化了呕吐毒素DON单链抗体的三维结构, 结合Procheck和verify_3D方法评估得到合理的抗体模型. 利用分子对接方法研究了单链抗体与其抗原DON的识别及相互作用. 结果表明, 毒素结合到抗体轻链上, 通过轻重链的交界区残基与重链结合, 与残基Pro107之间存在氢键作用. 采用分子动力学模拟和MM/GBSA方法计算了毒素DON与抗体之间的结合自由能, 计算结果与实验值相吻合, 体系疏水相互作用是维持复合物稳定结构的主要驱动力. 动力学模拟氢键分析和能量分解结果共同表明, 残基Pro107参与稳定氢键的形成并贡献很强的范德华作用, 是毒素结合抗体最关键的残基. 本研究为该毒素抗体的结构设计提供了重要的线索和理论依据, 对毒素类分子新型抗体的研究和开发具有理论指导价值.     

用分子模拟方法研究HIV-1整合酶与咖啡酰基类抑制剂的相互作用

用分子对接和分子动力学(MD)模拟方法研究了一类咖啡酰基和没食子酰基类HIV-1整合酶抑制剂与整合酶之间的相互作用模式, 结果表明该类抑制剂分子上的两个侧链基团(咖啡酰基或没食子酰基)与整合酶的DDE基序之间的相互作用对抑制整合酶活性起到关键作用. 当侧链基团为没食子酰基时, 可以提高该类抑制剂与整合酶的结合能力. 采用线性相互作用能方法(LIE)计算了该类抑制剂与整合酶之间的结合自由能, 预测值与实验值相吻合, 均方根偏差RMSD为1.39 kJ•mol^-1, 以上结果可为基于结构的HIV-1整合酶抑制剂设计提供有用的信息.     

人顶体酶三维结构的同源模建及其与KF950的分子对接研究

采用同源模建方法首次构建了人顶体酶的三维结构模型, 模型的可靠性经Ramachandran图和Profile_3D图验证. 采用InsightII/Binding site方法准确定位了人顶体酶的活性位点, 并研究了顶体酶重要功能残基在活性位点的立体分布. 在此基础上, 通过柔性分子对接方法首次阐明了顶体酶高效抑制剂KF950与靶酶活性位点的相互作用模式, 发现特异性的氢键相互作用是KF950产生高抑制活性的重要分子基础. 其研究结果将为合理设计新型顶体酶抑制剂, 寻找男性口服避孕药奠定坚实基础.     

硝基二肽类嗜热菌蛋白酶抑制剂的分子动力学研究

采用分子对接和分子动力学方法,考察了硝基类二肽类化合物抑制剂的侧链结构对嗜热菌蛋白酶(TLN)的抑制效能的影响.计算结果表明:当侧链基团为异丁基时,抑制剂与TLN的活性部位之间形成的氢键数目最多,并可以提高抑制剂与TLN的结合能力.理论计算的结合自由能大小与抑制剂的抑制常数相吻合.以上结果从理论上进一步揭示了硝基类二肽化合物侧链结构对TLN的抑制能力的影响复杂性,即除了一般意义上的疏水作用外,侧链结构的变化导致氢键的形成能力变化也不可忽略.     

Structure of the virus capsid protein VP1 of enterovirus 71 predicted by some homology modeling and molecular docking studies

The homology modeling technique has been used to construct the structure of enterovirus 71 (EV 71) capsid protein VP1. The protein is consisted of 297 amino acid residues and treated as the target. The amino acid sequence identity between the target protein and sequences of template proteins 1EAH, 1PIV, and 1D4M searched from NCBI protein BLAST and WorkBench protein tools were 38, 37, and 36%, respectively. Based on these template structures, the protein model was constructed by using the InsightII/Homology program. The protein model was briefly refined by energy minimization and molecular dynamics (MD) simulation steps. The protein model was validated using some web available servers such as ERRAT, PROCHECK, PROVE, and PROSA2003. However, an inconsistency between the docking scores and the measured activity was observed for a series of EV 71 VP1 inhibitors synthesized by Shia et al. (J Med Chem 2002, 45, 1644) and docked into the binding pocket of the protein model using the DOCK 4.0.2 program. The protein model with an EV 71 VP1 inhibitor docked and engulfed was then refined further by some MD simulation steps in the presence of water molecules. The docking scores obtained for these inhibitors after such a MD refinement were well correlated with the activities. The structure-activity relationships for the ligand-protein model system was also analyzed using the GRID-VOLSURF programs and the corresponding noncrossvalidated and crossvalidated (by leave-one-out) r2 and q2 were 0.99 and 0.61, respectively. The hydrophobic nature of the binding pocket of the protein model was also examined using the GRID21 program. The possibility of improving the potency of the current series of EV 71 VP1 inhibitors was discussed based on all the studies presented.     

鼠源雌激素硫酸转移酶的结构模型研究

利用同源模建和分子动力学模拟方法搭建了鼠源雌激素硫酸转移酶的三维结构,并用Profile-3D和Prostat评估了模型的可靠性.鼠源雌激素硫酸转移酶的三维结构的提出对硫酸转移酶家族催化机理的深入研究提供了重要的参考信息.     

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。     

Identification of inhibitors against p90 ribosomal S6 kinase 2 (RSK2) through structure-based virtual screening with the inhibitor-constrained refined homology model

P90 ribosomal S6 kinase 2 (RSK2), which was shown to be overexpressed in human cancers, is a serine/threonine kinase and a potential target for cancer treatment. RSK2 comprises two terminal kinase domains (NTKD and CTKD) that can be inhibited by binding with different types of inhibitors at the ATP binding sites. In the absence of a crystal structure of RSK2, we constructed a model for the 3D structure of the RSK2 NTKD by homology modeling and stepwise constrained refinement with the reported inhibitors using a molecular docking method. Structure-based virtual screening was subsequently performed against a library containing commercially available compounds using the refined model. This resulted in the identification of seven novel RSK2 inhibitors with IC?? values ranging from 2.4 to 14.45 μM.     

细胞死亡蛋白的三维结构及活性位点的理论研究

利用同源模建和分子动力学模拟方法,构建了细胞死亡蛋白（CED-10）的三维结构,并预测了其可能的活性位点,为细胞死亡蛋白家族催化机理的深入研究提供了、重要的参考信息．     

Using Homology Modeling, Molecular Dynamics and Molecular Docking Techniques to Identify Inhibitor Binding Regions of Somatostatin Receptor 1

The G protein coupled receptor(GPCR), one of the members in the superfamily, which consists of thousands of integral membrane proteins, exerts a wide variety of physiological functions and responses to a large portion of the drug targets. The 3D structure of somatostatin receptor 1(SSTR1) was modeled and refined by means of homology modeling and molecular dynamics simulation. This model was assessed by Verify-3D and Vadar, which confirmed the reliability of the refined model. The interaction between the inhibitor cysteamine, somatostatin(SST) and SSTR1 was investigated by a molecular docking program, Affinity. The binding module not only showed the crucial residues involved in the interaction, but also provided important information about the interaction between SSTR1 on the one hand and ligands on the other, which might be the significant evidence for the structure-based design.     

基于“底物包膜”假说筛选新型HIV-1蛋白酶抑制剂

基于“底物包膜”假说, 以现有HIV-1蛋白酶抑制剂Darunavir为模板构建药效团模型并对中药化学数据库进行搜索; 采用分子对接方法进一步考察化合物与HIV-1蛋白酶结合情况及其与“底物包膜”符合程度, 优先选出两个化合物Annomonicin和去乙酰蟾蜍它灵; 应用分子动力学方法对这两个化合物进行动力学模拟, 观察它们与蛋白酶结合的复合物在动力学过程中的稳定性并计算其结合自由能, 综合评价筛选结果, 最终确定化合物Annomonicin具有更潜在的深入研究价值.     

Steric exclusion and constraint satisfaction in multi-scale coarse-grained simulations

An algorithm is described for the interaction of a hierarchy of objects that seeks to circumvent a fundamental problem in coarse-grained modelling which is the loss of fine detail when components become bundled together. A “currants-in-jelly” model is developed that provides a flexible approach in which the contribution of the soft high-level objects (jelly-like) are employed to protect the underlying atomic structure (currants), while still allowing them to interact. Idealised chains were used to establish the parameters to achieve this degree of interaction over a hierarchy spanning four levels and in a more realistic example, the distortion experienced by a protein domain structure during collision was measured and the parameters refined. This model of steric repulsion was then combined with sets of predicted distance constraints, derived from correlated mutation analysis. Firstly, an integral trans-membrane protein was modelled in which the packing of the seven helices was refined but without topological rearrangement. Secondly, an RNA structure was ‘folded’ under the predicted constraints, starting only from its 2-dimensional secondary structure prediction.     

A proposed model of Mycobacterium avium complex dihydrofolate reductase and its utility for drug design

A homology model of Mycobacterium avium complex dihydrofolate reductase (MAC DHFR) was constructed on the basis of the X-ray crystal structure of Mycobacterium tuberculosis (Mtb) DHFR. The homology searching of the MAC DHFR resulted in the identification of the Mtb DHFR structure (PDB 1DF7) as the template for the model building. The MAC enzyme sequence was aligned to that of the Mtb counterpart using a modified Needleman and Wunsch methodology. The initial geometry to be modeled was copied from the template, either fully or partially depending on whether the residues were conserved or not, respectively. Using a randomized modeling procedure, 10 independent models of the target protein were built. The cartesian average of all the model structures was then refined using molecular mechanics. The resulting model was assessed for stereochemical quality using a Ramachandran plot and by analyzing the consistency of the model with the experimental data. The structurally and functionally important residues were identified from the model. Further, 5-deazapteridines recently reported as inhibitors of MAC DHFR were docked into the active site of the developed model. All the seven inhibitors used in the docking study have a similar docking mode at the active site. The network of hydrogen bonds around the 2,4-diamino-5-deazapteridine ring was found to be crucial for the binding of the inhibitors with the active site residues. The 5-methyl group of the inhibitors was located in a narrow hydrophobic pocket at the bottom of the active site. The relative values of the three torsion angles of the inhibitors were found to be important for the proper orientation of the inhibitor functional groups into the active site.