VEGFR-2 与抑制剂Sunitinib 的分子对接及分子动力学研究

用分子对接方法研究了VEGFR-2 和抑制剂Sunitinib 的相互作用模式, 并对其复合物进行了10 ns 的分子动力学(Molecular Dynamics, MD)模拟. 结果表明, 抑制剂Sunitinib 能与VEGFR-2 中位于活性空腔的Glu885, Ile888, His1026,Asp1028, Asp1046 五个氨基酸残基形成疏水作用; 另外, VEGFR-2 中His1026, Cys1024, Asp1046 三个氨基酸残基能与Sunitinib 形成三个作用强度不同的氢键. 这些基团之间的相互作用是Sunitinib 抑制VEGFR-2 活性的关键因素. 研究结果可为VEGFR-2 抑制剂的结构改良、分子设计、合成提供理论参考, 并有助于寻找活性更高、效果更好的抗肿瘤药物.     

二苯乙烯类LSD1抑制剂的分子对接及分子动力学模拟研究

本研究基于二苯乙烯的结构活性关系,设计了10个组蛋白赖氨酸特异性去甲基化酶1(LSD1)新型抑制剂.采用分子对接的方法并根据对接打分结果对得分最高的化合物进行分子动力学模拟,研究分析小分子和LSD1的相互作用机制,并对其进行ADME(吸收、分布、代谢和排泄)预测.分子对接和分子动力学结果显示设计的小分子与蛋白结合能力更...     

金丝桃素分子结构及其与HIV病毒蛋白酶作用的分子动力学研究

采用用计算化学方法研究金丝桃素分子结构特征, 并用分子动力学方法研究其与HIV蛋白酶的相互作用, 探讨其可能的抗HIV病毒作用机理. 结果表明, 金丝桃素分子结构具有刚性特征, 与HIV蛋白酶在酶的催化活性位点与ASP-A25 and ASP-B25以氢键作用相结合.     

洋刀豆脲酶与抑制剂相互作用的分子对接和分子动力学研究

通过洋刀豆脲酶抑制剂的筛选实验得到具有较好抑制活性的化合物2-乙酰基-γ-丁内酯(COM), 其半数抑制浓度在微摩尔浓度级别(IC₅₀＝375 μmol•L^－l). 在此基础上, 使用分子对接和分子动力学(MD)模拟的方法研究洋刀豆脲酶与抑制剂乙酰氧肟酸(AHA)及活性化合物COM之间的相互作用. 用Gold3.0程序将两个小分子与洋刀豆脲酶的晶体结构进行对接, 对接得到的复合物模型使用Amber程序进行MD模拟研究. 模拟过程中, 脲酶结构中的双核镍离子活性中心选用non-bonded模型. 研究结果显示: AHA与洋刀豆脲酶结合时, Ni(1)和Ni(2)均为五配位|COM与洋刀豆脲酶结合时Ni(1)为五配位, Ni(2)为六配位的结合模型更加合理. 这些研究为了解洋刀豆脲酶与抑制剂之间的相互作用提供了重要的参考信息.     

芬太尼类化合物与阿片μ受体相互作用的分子对接与分子动力学模拟

采用分子对接和分子动力学(MD)模拟方法研究了芬太尼类化合物与阿片μ受体的相互作用机制.先用AutoDock4.0程序将芬太尼类化合物对接到同源模建的阿片μ受体结构中,再用GROMACS程序包在水溶液体系中分别对12个芬太尼激动剂和阿片μ受体蛋白复合物进行了MD模拟研究,优化对接复合物的结构,最后利用MM-PBSA方法,在APBS程序中计算芬太尼类衍生物与阿片μ受体的结合自由能,计算出的受体配合物结合常数(Ki)与其实验值吻合较好,并预测了化合物的活性排序.结果表明,复合物蛋白结构与空载受体蛋白结构有较大差异,特别是胞内区IL2、IL3和跨膜区段TM4骨架构象变化较大,不同的化合物对受体结构影响也有差异,活性较好的化合物会增加蛋白特定区域结构的柔性.芬太尼类化合物可能是通过和受体结合后诱导阿片μ受体构象转变为活性构象,引起一系列的信号传导激活G蛋白,从而引发生理效应.     

拟南芥TIR1与生长素IAA相互作用的分子对接及分子动力学研究

基于最新得到的拟南芥运输抑制剂响应蛋白质1(TIR1)与吲哚乙酸(IAA)复合物的晶体结构, 使用分子对接方法和分子动力学方法对TIR1与生长素IAA相互作用的方式进行了研究. 分子对接结果表明, 通过逐级考察辅酶InsP₆和中心水分子的影响, 发现辅酶InsP₆和中心水分子对生长素IAA正确结合到活性位点有重要作用. 分子动力学结果表明, 复合物体系在整个模拟过程中较为稳定, 2个水分子相继作为中心水分子与生长素IAA形成了稳定的氢键作用, IAA与活性位点处残基的相互作用与晶体结构相比略有差异.     

HIV-1整合酶链转移抑制剂的3D-QSAR、分子对接和分子动力学模拟研究

为了获得高活性、结构新颖的整合酶链转移(INST)抑制剂,本文采用Co MFA和Co MSIA两种方法对32个萘啶类INST抑制剂进行了三维定量构效关系研究,并建立了相关模型,其交叉验证系数分别为q~2=0. 809和q~2=0. 816,拟合验证系数分别为r~2=0. 998和r~2=0. 981,表明所建立的模型是可靠的且具有一定的预测能力。利用分子对接探讨小分子化合物与INST蛋白的相互作用模式,结果表明,萘啶类化合物主要通过疏水作用和氢键作用与INSTIs蛋白结合。最后通过分子动力学模拟进一步验证对接结果发现,对接的结合模式与分子动力学模拟得到的结果是一致的。本研究获得的综合模型和推论可以为开发有效的HIV INSTIs提供重要的理论信息。     

贯叶连翘有效成分金丝桃素与HIV逆转录酶相互作用的研究

采用理论计算化学分子动力学模拟方法研究金丝桃素的分子结构,并从分子水平上研究金丝桃素与HIV逆转录酶的相互作用,建立了酶-抑制剂复合物模型,分析可能的相互作用关系和作用机理．研究结果表明,金丝桃素分子结构具有刚性特征．金丝桃素与HIV逆转录酶以氢键相互作用和Ⅱ-Ⅱ相互作用结合．     

血管紧张素转换酶与抑制肽结合模式的分子动力学研究

应用分子模拟方法研究了血管紧张素转换酶(Angiotensin-converting enzyme,ACE)C端结构域(C-domain)与两种抑制肽(RIGLF/AHEPVK)的结合机制,预测了两个体系的结合模式,提出在C-domain-RIGLF中His353,Asp377,Asp453,Phe457,His513,Tyr523和Phe527为RIGLF主要结合残基,而在C-domainAHEPVK中Gln281,His353,Ser355,Glu384,Lys511,His513和Tyr523等残基起关键作用.应用结合自由能计算比较了两个体系的结合能力,结果表明,RIGLF和AHEPVK均与C-domain活性位点残基存在较强作用,且AHEPVK对C-domain的结合能力较强,与实验结果一致.     

Molecular Docking and Molecular Dynamics Studies Reveal Secretory Proteins as Novel Targets of Temozolomide in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is a tumor of glial origin and is the most malignant, aggressive and prevalent type, with the highest mortality rate in adult brain cancer. Surgical resection of the tumor followed by Temozolomide (TMZ) therapy is currently available, but the development of resistance to TMZ is a common limiting factor in effective treatment. The present study investigated the potential interactions of TMZ with several secretory proteins involved in various molecular and cellular processes in GBM. Automated docking studies were performed using AutoDock 4.2, which showed an encouraging binding affinity of TMZ towards all targeted proteins, with the strongest interaction and binding affinity with GDF1 and SLIT1, followed by NPTX1, CREG2 and SERPINI, among the selected proteins. Molecular dynamics (MD) simulations of protein–ligand complexes were performed via CABS-flex V2.0 and the iMOD server to evaluate the root-mean-square fluctuations (RMSFs) and measure protein stability, respectively. The results showed that docked models were more flexible and stable with TMZ, suggesting that it may be able to target putative proteins implicated in gliomagenesis that may impact radioresistance. However, additional in vitro and in vivo investigations can ascertain the potential of the selected proteins to serve as novel targets for TMZ for GBM treatment.     

螺环吲哚类MDM2抑制剂的分子对接、定量构效关系和分子动力学模拟

采用分子对接、三维定量构效关系(3D-QSAR)和分子动力学方法研究了21个螺环吲哚类化合物与MDM2蛋白的相互作用, 并建立了相关预测模型. 比较分子场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA)模型的交互验证相关系数q²分别为0.573 和0.651, 非交互验证相关系数r²分别为0.948和0.980. 分子对接得到的结合模式与分子动力学模拟得到的结果一致, 结合模式表明该类螺环吲哚化合物主要通过疏水相互作用和氢键与MDM2结合. 基于上述相互作用模型设计并合成了6个新结构螺环吲哚化合物, 并在MDM2高表达的前列腺癌LNCaP细胞株上测定其活性, 结果表明化合物5, 6的半数抑制浓度均低于1μg·mL^-1, 可作为新的抗肿瘤药物先导化合物进一步深入研究. 本研究对以MDM2为靶点的新结构螺环吲哚类抑制剂的开发提供了理论和实验依据.     

Design of Novel IRAK4 Inhibitors Using Molecular Docking,Dynamics Simulation and 3D-QSAR Studies

Treatment of several autoimmune diseases and types of cancer has been an intense area of research over the past two decades. Many signaling pathways that regulate innate and/or adaptive immunity, as well as those that induce overexpression or mutation of protein kinases, have been targeted for drug discovery. One of the serine/threonine kinases, Interleukin-1 Receptor Associated Kinase 4 (IRAK4) regulates signaling through various Toll-like receptors (TLRs) and interleukin-1 receptor (IL1R). It controls diverse cellular processes including inflammation, apoptosis, and cellular differentiation. MyD88 gain-of-function mutations or overexpression of IRAK4 has been implicated in various types of malignancies such as Waldenström macroglobulinemia, B cell lymphoma, colorectal cancer, pancreatic ductal adenocarcinoma, breast cancer, etc. Moreover, over activation of IRAK4 is also associated with several autoimmune diseases. The significant role of IRAK4 makes it an interesting target for the discovery and development of potent small molecule inhibitors. A few potent IRAK4 inhibitors such as PF-06650833, RA9 and BAY1834845 have recently entered phase I/II clinical trial studies. Nevertheless, there is still a need of selective inhibitors for the treatment of cancer and various autoimmune diseases. A great need for the same intrigued us to perform molecular modeling studies on 4,6-diaminonicotinamide derivatives as IRAK4 inhibitors. We performed molecular docking and dynamics simulation of 50 ns for one of the most active compounds of the dataset. We also carried out MM-PBSA binding free energy calculation to identify the active site residues, interactions of which are contributing to the total binding energy. The final 50 ns conformation of the most active compound was selected to perform dataset alignment in a 3D-QSAR study. Generated RF-CoMFA (q² = 0.751, ONC = 4, r² = 0.911) model revealed reasonable statistical results. Overall results of molecular dynamics simulation, MM-PBSA binding free energy calculation and RF-CoMFA model revealed important active site residues of IRAK4 and necessary structural properties of ligand to design more potent IRAK4 inhibitors. We designed few IRAK4 inhibitors based on these results, which possessed higher activity (predicted pIC₅₀) than the most active compounds of the dataset selected for this study. Moreover, ADMET properties of these inhibitors revealed promising results and need to be validated using experimental studies.     

Aphrodisiac Performance of Bioactive Compounds from Mimosa pudica Linn.: In Silico Molecular Docking and Dynamics Simulation Approach

Plants and their derived molecules have been traditionally used to manage numerous pathological complications, including male erectile dysfunction (ED). Mimosa pudica Linn. commonly referred to as the touch-me-not plant, and its extract are important sources of new lead molecules in drug discovery research. The main goal of this study was to predict highly effective molecules from M. pudica Linn. for reaching and maintaining penile erection before and during sexual intercourse through in silico molecular docking and dynamics simulation tools. A total of 28 bioactive molecules were identified from this target plant through public repositories, and their chemical structures were drawn using Chemsketch software. Graph theoretical network principles were applied to identify the ideal target (phosphodiesterase type 5) and rebuild the network to visualize the responsible signaling genes, proteins, and enzymes. The 28 identified bioactive molecules were docked against the phosphodiesterase type 5 (PDE5) enzyme and compared with the standard PDE5 inhibitor (sildenafil). Pharmacokinetics (ADME), toxicity, and several physicochemical properties of bioactive molecules were assessed to confirm their drug-likeness property. Molecular dynamics (MD) simulation modeling was performed to investigate the stability of PDE5–ligand complexes. Four bioactive molecules (Bufadienolide (−12.30 kcal mol⁻¹), Stigmasterol (−11.40 kcal mol⁻¹), Isovitexin (−11.20 kcal mol⁻¹), and Apigetrin (−11.20 kcal mol⁻¹)) showed the top binding affinities with the PDE5 enzyme, much more powerful than the standard PDE5 inhibitor (−9.80 kcal mol⁻¹). The four top binding bioactive molecules were further validated for a stable binding affinity with the PDE5 enzyme and conformation during the MD simulation period as compared to the apoprotein and standard PDE5 inhibitor complexes. Further, the four top binding bioactive molecules demonstrated significant drug-likeness characteristics with lower toxicity profiles. According to the findings, the four top binding molecules may be used as potent and safe PDE5 inhibitors and could potentially be used in the treatment of ED.     

Study of Endogen Substrates,Drug Substrates and Inhibitors Binding Conformations on MRP4 and Its Variants by Molecular Docking and Molecular Dynamics

Multidrug resistance protein-4 (MRP4) belongs to the ABC transporter superfamily and promotes the transport of xenobiotics including drugs. A non-synonymous single nucleotide polymorphisms (nsSNPs) in the ABCC4 gene can promote changes in the structure and function of MRP4. In this work, the interaction of certain endogen substrates, drug substrates, and inhibitors with wild type-MRP4 (WT-MRP4) and its variants G187W and Y556C were studied to determine differences in the intermolecular interactions and affinity related to SNPs using protein threading modeling, molecular docking, all-atom, coarse grained, and umbrella sampling molecular dynamics simulations (AA-MDS and CG-MDS, respectively). The results showed that the three MRP4 structures had significantly different conformations at given sites, leading to differences in the docking scores (DS) and binding sites of three different groups of molecules. Folic acid (FA) had the highest variation in DS on G187W concerning WT-MRP4. WT-MRP4, G187W, Y556C, and FA had different conformations through 25 ns AA-MD. Umbrella sampling simulations indicated that the Y556C-FA complex was the most stable one with or without ATP. In Y556C, the cyclic adenosine monophosphate (cAMP) and ceefourin-1 binding sites are located out of the entrance of the inner cavity, which suggests that both cAMP and ceefourin-1 may not be transported. The binding site for cAMP and ceefourin-1 is quite similar and the affinity (binding energy) of ceefourin-1 to WT-MRP4, G187W, and Y556C is greater than the affinity of cAMP, which may suggest that ceefourin-1 works as a competitive inhibitor. In conclusion, the nsSNPs G187W and Y556C lead to changes in protein conformation, which modifies the ligand binding site, DS, and binding energy.     

Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking

One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.     

非连续分子动力学模拟方法及其在大分子研究中的应用

计算机模拟技术已成为大分子构象等基础研究的一种重要手段。非连续分子动力学模拟(DMD)与传统的分子动力学模拟(MD)方法有所不同,基于不连续势能和相关的模拟编程方法,运行速度大大提高。本文讨论了DMD方法的特点,总结了DMD方法的应用,重点以蛋白质折叠为例介绍了如何使用DMD方法,最后对DMD方法的发展前景进行了展望。