乙酰胆碱酯酶AChE与1,7-二氮杂咔唑抑制剂的作用机理的分子动力学模拟

通过分子对接、分子动力学（MD）模拟以及成键自由能分析方法,从原子水平上模拟研究了3种1,7-二氮杂咔唑衍生物（分别记为M1、M2和M3）与AChE的结合模式及相互作用机理,分析和讨论了研究体系的静电相互作用和范德华相互作用（vdW）。用MM-PBSA方法计算的3种抑制剂与AChE之间的结合自由能与抑制剂的实验生物活性数据（IC₅₀值）相对应。分析结果表明,残基S286与抑制剂之间形成的氢键作用有利于抑制剂与AChE之间的结合。范德华相互作用,尤其是抑制剂与关键残基W279和Y334的作用,对抑制剂与AChE之间的结合自由能有较大的贡献,在区分抑制剂M1（或M2）和M3的生物活性上发挥着重要的作用。     

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。     

EGFR和4-苯胺喹唑啉类抑制剂之间相互作用模式的研究

采用分子动力学和MM/PBSA相结合的方法预测了表皮生长因子受体和4-苯胺喹 啉类抑制剂的相互作用模式。在分子动力学采样的基础上,采用MM/PBSA的方法分 别预测了四种可能结合模式下表皮生长因子受体和4-苯胺喹唑啉类抑制剂间的结合 自由能。在MM/PBSA计算中,受体和抑制剂之间的非键相互作用能采用分子力学 (MM)的方法得到;溶剂效应中极性部分对自由能的贡献通过解Possion- Boltzmanne (PB)方程的方法得到;溶液效应中非极性部分对自由能的贡献则通过 分子表面积计算(SA)的方法得到。计算表明,在四种结合模式下,表皮生长因子受 体和4-苯胺喹唑啉类抑制剂之间的结合自由能有较大的差别。在最佳的相互作用模 式中,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。抑制剂喹唑啉环上的N(1)原子能够和Met-769上的 NH形成稳定的氢键,而抑制剂上的N(3)原子则和周围的一个水分子形成氢键。同时 ,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 水相互作用。最佳结合模式能够很好地解释已有抑制剂结构和活性间的关系。     

分子模拟方法研究四氢化吡啶并[1,2-a]吲哚酮衍生物对GSK3β和CDK5的选择性

本文通过分子对接,分子动力学模拟(MD)和MM/PBSA能量计算的方法,从分子水平研究了3个四氢化吡啶并[1,2-a]吲哚酮衍生物与CDK5和GSK3β的相互作用,并揭示了这些抑制剂对GSK3β的选择性抑制机理。分子对接结果表明,抑制剂对2种激酶具有相似的结合模式,结合口袋处的残基也都根据晶体结构的序列比对相互对应。研究体系的RMSD随时间的稳定变化,表明模拟体系已达到稳定状态,因而后续的分析是可靠的。CDK5/抑制剂体系,RMSD在0.15 nm上下波动,CDK5/M1和CDK5/M2骨架轻微波动,稍高于CDK5/M3;而GSK3β体系的RMSD值略高于CDK5体系,在0.17 nm上下波动,GSK3β/M1和GSK3ββ/M2的骨架波动平衡值则稍低于GSK3β/M3。活性较大的抑制剂增强了蛋白骨架整体的"柔性",即对激酶构象产生一定影响。能量分析表明,静电能和范德华作用能够区分不同抑制剂对同种激酶的生物活性差异。极性溶剂化自由能对区分抑制剂选择性也很重要,残基分解表明GSK3β的Glu97、Thr138是造成抑制剂选择性的主要原因。抑制剂与CDK5和GSK3β结合的过程中,蛋白质残基的动态相关性存在差异,铰链区域的Thr138与Val135~Gln206区域残基正相关,证实Thr138残基是区分抑制剂选择性的关键。     

Hydroxamate类抑制剂与MMP-3的结合自由能的计算

用自由能微扰方法(FEP)计算了两种hydroxamate类的抑制剂和MMP-3的相对结合自由能。在计算中,对于催化区的锌离子与其共价结合的配体(包括抑制和组氨酸)采用了键合的模型,抑制剂和周围配体的部分电荷的计算采用两步静电势收敛方法。自由能计算采用了慢增长(Slowgrowth)和固定窗口增长(Fixedwidthwindowgrowth)两种方法,并且在每次计算中都采用了双向采样(Double-widesampling)的策略。两种方法计算得到的相对结合自由能都能和实验值很好的符合。同时从动力学模拟的得到的分子轨迹得到了抑制剂和受体之间相互作用模式,抑制剂的P1部分可以和受体的S1'口袋形成很强范德华和疏水相互作用,P1上的苯环可以和Tyr223上的苯环形成较好的π键堆积相互作用。     

分子模拟方法研究四氢化吡啶并[1,2-a]吲哚酮衍生物对GSK3β和CDK5的选择性

本文通过分子对接,分子动力学模拟（MD）和MM/PBSA能量计算的方法,从分子水平研究了3个四氢化吡啶并[1,2-a]吲哚酮衍生物与CDK5和GSK3β的相互作用,并揭示了这些抑制剂对GSK3β的选择性抑制机理。分子对接结果表明,抑制剂对2种激酶具有相似的结合模式,结合口袋处的残基也都根据晶体结构的序列比对相互对应。研究体系的RMSD随时间的稳定变化,表明模拟体系已达到稳定状态,因而后续的分析是可靠的。CDK5/抑制剂体系,RMSD在0.15 nm上下波动,CDK5/M1和CDK5/M2骨架轻微波动,稍高于CDK5/M3;而GSK3β体系的RMSD值略高于CDK5体系,在0.17 nm上下波动,GSK3β/M1和GSK3ββ/M2的骨架波动平衡值则稍低于GSK3β/M3。活性较大的抑制剂增强了蛋白骨架整体的“柔性”,即对激酶构象产生一定影响。能量分析表明,静电能和范德华作用能够区分不同抑制剂对同种激酶的生物活性差异。极性溶剂化自由能对区分抑制剂选择性也很重要,残基分解表明GSK3β的Glu97、Thr138是造成抑制剂选择性的主要原因。抑制剂与CDK5和GSK3β结合的过程中,蛋白质残基的动态相关性存在差异,铰链区域的Thr138与Val135~Gln206区域残基正相关,证实Thr138残基是区分抑制剂选择性的关键。     

Hydroxamate类抑制剂与MMP-2的分子对接研究

通过分子动力学模拟研究了MMP-2和hydroxamate抑制剂之间的作用模式。在分子动力学模拟中,对于催化区的锌离子和其共价结合的配体(包括抑制剂和组氨酸)采用了键合的模型。从模拟的结果可以看到,R^1取代基和MMP-2的S1疏水口袋中的部分残基能形成很好的几何匹配,从而可以产生很强的范德华和疏水相互作用。模拟结果也表明,两个抑制剂和MMP-2之间分别能形成5个和8个氢键,抑制剂B比A活性更高的原因就是能够形成更加有利氢键作用模式。在整个模拟过程中,催化锌都能保持好的五配位形式,配位键的长度也处于稳定的状态,预测得到的MMP-2和其抑制剂的相互作用模式对于全新抑制剂的设计提供了非常重要的结构信息。     

基于配体与受体结构的酪氨酸酶抑制剂定量构效关系分析

酪氨酸酶是细胞内催化合成黑素的关键酶。 理解酪氨酸酶抑制剂结构与活性之间的关系对于设计新药和化妆品具有重要意义。 然而,酪氨酸酶抑制剂的定量构效关系仍不清楚。 本文利用配体和结构描述符构建了隐式和显式模型,阐明了酪氨酸酶抑制剂定量构效关系。 隐式模型的相关系数R高达0.961,显式模型的相关系数为0.775。 两个模型很好地预测了3个茶多酚的酪氨酸酶抑制活性,表儿茶素没食子酸酯(ECG)>表没食子儿茶素没食子酸酯(EGCG)>没食子酸(G)。 相关性分析发现,抑制剂与酪氨酸酶结合引起的构象熵损失与抑制剂的活性密切相关。 具有较少构象熵损失的ECG在4种茶多酚中具有较高酪氨酸酶抑制活性。 结合自由能计算也证实ECG与酪氨酸酶的结合能力最强。 此外,通过分解结合自由能发现,酪氨酸酶活性中心的氨基酸残基(His57、His201、Asn202、His205、Glu192和Val215)与抑制剂形成了较强的范德华和静电相互作用,进而稳定了复合物结构。     

基于分子对接和自由能计算的高活性苯并噻唑类ROCK抑制剂的设计、合成和生物学评价

以3个已报道的苯并噻唑类Rho关联含卷曲螺旋蛋白激酶(ROCK)抑制剂(化合物1~3)为研究对象,经分子动力学模拟获得其在ROCK2蛋白结合口袋中的稳定结合构象,通过分子对接结果从氨基酸角度初步揭示了此类抑制剂的结构-活性关系(SAR);然后,对这3个抑制剂进行MM/GBSA结合自由能(ΔG_(bind))研究,结合自由能计算可知ΔG_(bind)与化合物活性之间具有良好的相关性,且范德华作用能(ΔG_(VDW))对ΔG_(bind)的贡献最大.通过自由能分解获得了对于高活性抑制剂具有重要影响的关键残基.最后,根据分子对接和自由能研究结果设计并合成了3类新型苯并噻唑类似物(D1~D10).生物学评价结果表明,这10个化合物分别具有11~288 nmol/L(ROCK1)和2~105 nmol/L(ROCK2)的抑制活性.其中,化合物D3~D5在人肝微粒体代谢研究中展现出比已报道化合物更高的代谢稳定性.本研究不仅为高活性ROCK抑制剂的设计提供了理论指导,也为ROCK的应用研究提供了一系列结构新颖的高活性抑制剂.     

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.     

Studies of chirality effect of 4-(phenylamino)-pyrrolo[2,1-f][1,2,4]triazine on p38α by molecular dynamics simulations and free energy calculations

4-(Phenylamino)-pyrrolo[2,1-f][1,2,4]triazines have been discovered as inhibitors of p38α. Experimental assays have proven that the configuration of α-Me-benzyl connected with amide at C6 is essential for the binding affinity. The S-configured inhibitor (11j) displays 80 times more potency than the R-configured one (11k). Here we investigated the mechanism how different configurations influence the binding affinity using molecular dynamics simulations, free energy calculations and free energy decomposition analysis. We found that the van der Waals interactions play the most important role in differentiating the activities between 11j and 11k with p38α. The difference of the van der Waals interactions is primarily determined by two residues, LEU108 and LEU167. Consequently stabilization of pyrrolo[2,1-f][1,2,4]triazine ring is important for the activities of inhibitors. Meanwhile we observed that the different configuration of the α-Me-benzyl group leads to the difference of binding between 11j and 11k. In conclusion, our work shows that it is feasible to analyze the chirality effect of inhibitors with different configurations by molecular dynamics simulations and free energy calculations, and provides useful information for drug design.     

Energetic basis for drug resistance of HIV-1 protease mutants against amprenavir

Amprenavir (APV) is a high affinity (0.15 nM) HIV-1 protease (PR) inhibitor. However, the affinities of the drug resistant protease variants V32I, I50V, I54V, I54M, I84V and L90M to amprenavir are decreased 3 to 30-fold compared to the wild-type. In this work, the popular molecular mechanics Poisson-Boltzmann surface area method has been used to investigate the effectiveness of amprenavir against the wild-type and these mutated protease variants. Our results reveal that the protonation state of Asp25/Asp25′ strongly affects the dynamics, the overall affinity and the interactions of the inhibitor with individual residues. We emphasize that, in contrast to what is often assumed, the protonation state may not be inferred from the affinities but requires pK_a calculations. At neutral pH, Asp25 and Asp25′ are ionized or protonated, respectively, as suggested from pK_a calculations. This protonation state was thus mainly considered in our study. Mutation induced changes in binding affinities are in agreement with the experimental findings. The decomposition of the binding free energy reveals the mechanisms underlying binding and drug resistance. Drug resistance arises from an increase in the energetic contribution from the van der Waals interactions between APV and PR (V32I, I50V, and I84V mutant) or a rise in the energetic contribution from the electrostatic interactions between the inhibitor and its target (I54M and I54V mutant). For the V32I mutant, also an increased free energy for the polar solvation contributes to the drug resistance. For the L90M mutant, a rise in the van der Waals energy for APV-PR interactions is compensated by a decrease in the polar solvation free energy such that the net binding affinity remains unchanged. Detailed understanding of the molecular forces governing binding and drug resistance might assist in the design of new inhibitors against HIV-1 PR variants that are resistant against current drugs.     

Probing molecular mechanism of inhibitor bindings to bromodomain-containing protein 4 based on molecular dynamics simulations and principal component analysis

ABSTRACT

It is well known that bromodomain-containing protein 4 (BRD4) has been thought as a promising target utilized for treating various human diseases, such as inflammatory disorders, malignant tumours, acute myelogenous leukaemia (AML), bone diseases, etc. For this study, molecular dynamics (MD) simulations, binding free energy calculations, and principal component analysis (PCA) were integrated together to uncover binding modes of inhibitors 8P9, 8PU, and 8PX to BRD4(1). The results obtained from binding free energy calculations show that van der Waals interactions act as the main regulator in bindings of inhibitors to BRD4(1). The information stemming from PCA reveals that inhibitor associations extremely affect conformational changes, internal dynamics, and movement patterns of BRD4(1). Residue-based free energy decomposition method was wielded to unveil contributions of independent residues to inhibitor bindings and the data signify that hydrogen bonding interactions and hydrophobic interactions are decisive factors affecting bindings of inhibitors to BRD4(1). Meanwhile, eight residues Trp81, Pro82, Val87, Leu92, Leu94, Cys136, Asn140, and Ile146 are recognized as the common hot interaction spots of three inhibitors with BRD4(1). The results from this work are expected to provide a meaningfully theoretical guidance for design and development of effective inhibitors inhibiting of the activity of BRD4.     

Magnesium effect on the acetylcholinesterase inhibition mechanism: A molecular chromatographic approach

The acetylcholinesterase enzyme (AChE) was immobilized on a chromatographic support to study the effect of magnesium on the binding mechanism of five AChE inhibitors (donepezil, tacrine, galanthamine, physostigmine and huperzine). The determination of the enthalpy and entropy changes of this binding at different magnesium concentration values suggested that van der Waals interactions and hydrogen bonds predominated the donepezil and tacrine association to AChE. As well, hydrophobic and electrostatic forces seemed to be the major interactions controlling the huperzine, galanthamine and physostigmine association with AChE. In addition, it appeared that magnesium cation increased the binding affinity of galanthamine and physostigmine to the active site gorge of AChE. A comparison of the inhibitors hydrophobicity to their relative bound percentage with AChE showed an affinity enhanced with the increase in the molecule hydrophobicity and confirmed that the hydrophobic forces played an important role in the AChEI-AChE binding process. This novel biochromatographic column could be useful to find a specific inhibitor for this enzyme and so open new perspectives to be investigated.     

6-羟基石松碱与乙酰胆碱酯酶的相互作用

目前治疗阿尔茨海默症(Alzheimer’s disease,AD)的主要药物为乙酰胆碱酯酶抑制剂(AChEI).为探讨石松碱类化合物对AChE的抑制作用,以6-羟基石松碱(6-hydroxylycopodine,HLD)为对象,应用核磁共振、分子对接、酶活性测定、分子动力学模拟及自由能分析,研究了HLD与AChE的相互作用.研究发现6-羟基石松碱对乙酰胆碱酯酶具有混合型抑制作用,其结合作用主要来自氢键和范德华作用.     

PEARLS: program for energetic analysis of receptor-ligand system

Analysis of the energetics of small molecule ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions facilitates the quantitative understanding of molecular interactions that regulate the function and conformation of proteins. It has also been extensively used for ranking potential new ligands in virtual drug screening. We developed a Web-based software, PEARLS (Program for Energetic Analysis of Ligand-Receptor Systems), for computing interaction energies of ligand-protein, ligand-nucleic acid, protein-nucleic acid, and ligand-protein-nucleic acid complexes from their 3D structures. AMBER molecular force field, Morse potential, and empirical energy functions are used to compute the van der Waals, electrostatic, hydrogen bond, metal-ligand bonding, and water-mediated hydrogen bond energies between the binding molecules. The change in the solvation free energy of molecular binding is estimated by using an empirical solvation free energy model. Contribution from ligand conformational entropy change is also estimated by a simple model. The computed free energy for a number of PDB ligand-receptor complexes were studied and compared to experimental binding affinity. A substantial degree of correlation between the computed free energy and experimental binding affinity was found, which suggests that PEARLS may be useful in facilitating energetic analysis of ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions. PEARLS can be accessed at http://ang.cz3.nus.edu.sg/cgi-bin/prog/rune.pl.     

The application of three approximate free energy calculations methods to structure based ligand design: Trypsin and its complex with inhibitors

Three approximate free energy calculation methods are examined and applied to an example ligand design problem. The first of the methods uses a single simulation to estimate the relative binding free energies for related ligands that are not simulated. The second method is similar, except that it uses only first derivatives of free energy with respect to atomic parameters (most often charge, van der Waals equilibrium distance, and van der Waals well depth) to calculate free energy differences. The last method PROFEC (Pictorial Representation of Free Energy Components), generates contour maps that show how binding free energy changes when additional particles are added near the ligand. These three methods are applied to a benzamidine/trypsin complex. They each reproduce the general trends in the binding free energies, indicating that they might be useful for suggesting how ligands could be modified to improve binding and, consequently, useful in structure-based drug design.