采用柔性分子对接技术模拟蛋白质在疏水作用色谱上的保留行为

将蛋白质与疏水作用色谱(HIC)固定相相互作用分为直接非键/构象作用和蛋白质表面疏水效应两个热力学过程, 从而定量给出了处于浓盐析盐水溶液中HIC保留时间与配基/蛋白质结合自由能之间的二元线性关系. 通过ICM柔性分子对接策略及遗传算法(GA)对27个已知晶体结构的蛋白质与疏水配基的可能结合方式进行模拟和分析, 所得结果与实验观测情况吻合良好. 研究表明, 蛋白质局部疏水效应以及配基与蛋白质的非键/构象作用皆对HIC色谱保留行为影响显著, 且作用区域多集中于蛋白质表面突出部位.     

HIV蛋白酶抑制剂——利迪链菌素的分子对接研究

用分子对接的方法, 对利迪链菌素的抗HIV蛋白酶活性进行了研究. 为了更准确地反映利迪链菌素分子与酶蛋白结合的情况, 充分考虑受体活性部位的柔性, 采用了FlexX(初步对接)和Flexidock(精确对接)分两步将配体与受体进行对接. 在初步对接中, 设计了不同的受体活性部位来考察是否有结合水分子参与抑制剂与酶的结合. 对一种作用方式已知的非肽类HIV蛋白酶抑制剂Aha006进行的对接研究显示, 分子模拟的结果与实际情况吻合得较好, 证明了本文所采用的方法的可靠性. 利迪链菌素与蛋白酶活性部位的对接结果显示, 配体分子与受体之间的结合没有结合水分子的参与, 两者通过5对氢键作用结合成为稳定的复合物. 利迪链菌素占据结合腔, 覆盖了蛋白酶的活性三联体Asp25-Thr26-Gly27, 从而起到抑制其生物活性的作用.     

基于几何约束的蛋白质-配体准确结合自由能计算

蛋白质-配体的结合过程伴随着复杂的结构变化,在分子模拟可及的时间尺度内难以完全捕获,这使得准确估计蛋白质-配体的结合自由能十分困难.一种有效的解决途径是采用几何约束减小需要采样的构象空间,再通过后处理方式扣除约束的影响.本文综述了三种几何约束策略——漏斗状约束、球形约束和七自由度约束与自由能计算算法结合准确计算结合自由...     

新烟碱类化合物药效构象的分子对接研究

从烟碱型乙酰胆碱受体(nACHR)-烟碱(nicotine)复合体晶体模型出发, 采用SYBYL 6.92软件包中FlexX分子对接模块对新烟碱类化合物的3种已上市化合物吡虫啉、噻虫啉、烯啶虫胺和3种吡虫啉的结构衍生物同受体蛋白作用的精确模型进行了研究. 通过全局搜索方法构建配体的构象库进行对接, 依据构象间RMS值对结果进行分类结合CScore打分函数数据对对接结果进行筛选, 最终给出合理的新烟碱类化合物-烟碱型乙酰胆碱受体的药效作用构象模型: 配体吡啶环上氮原子通过水分子同受体Leu102, Met114形成氢键并且咪唑环或噻唑环上亲水侧链同受体CYS187或SER186形成氢键, 疏水侧链同疏水部位A (TYR164, TRP53, TYR89以及TYR185残基), 或疏水部位B (TYR132, CYS187和CYS188)相互作用. 此模型同早先有关文献报道的试验结果部分吻合, 充分表明了其合理性. 同时依据本构象模型, 在新烟碱类化合物结构方面提出了一些改良建议并为研究其高选择性指出方向.     

维甲化合物与维甲X受体相互作用模拟及QSAR研究

用分子对接确定了一系列RXR激动剂与受体的作用方式,与X衍射测得的晶体复合物中9-cis-RA的作用方式相近。对接后的配体-受体复和物经分子力学优化后更接近药效构象,两者相互作用能与活性具有一定的相关性,相关系数R^2=0.64。用活性构象建立的CoMFA模型比低能构象建立的CoMFA模型有更高的可信度,其交叉验证相关系q^2=0.791,非交叉验证相关系数γ^2=0.988,绝对误差SE=0.099,f6,33=456.8。     

紫杉醚与αβ微管蛋白的分子对接

采用Insight II/Affinity对紫杉醚与αβ微管蛋白进行分子对接, 共得到10个对接构象. 应用密度泛函B3LYP/6-31G 方法计算对接口袋构象的结合能, 筛选出结合能达-190.53 kJ·mol-1的最优对接构象5. 通过构象分析建立紫杉醚与受体结合的作用模型, 结果表明, 在活性口袋的底部紫杉醚与受体间的作用主要是疏水作用, 而在活性口袋的顶部两者间主要是氢键作用. 氢键作用位置可分为A和B两个作用区, 其中A区有3个氢键, 由C13侧链分别与受体的ASP26和ARG369作用形成; B区也有3个氢键, 是由紫杉醚母环上的极性基团分别与受体的THR276、ARG278和GLN282作用产生的. 紫杉醚与αβ微管蛋白间形成的6个氢键可以有效地将紫杉醚固定在活性口袋中.     

配体活性构象搜寻方法及其应用研究——Ⅰ.搜寻方法及凝血酶抑制剂活性构象的搜寻

在综合系统构象搜寻和配体-生物大分子对接(Dock)方法的基础上,发展了根据受体活性部位三维结构搜寻配体活性构象的搜寻方法BCSPL.用此方法搜寻了凝血酶抑制剂PPACK的活性构象,结果与晶体结构非常吻合,又用此方法搜寻了膦酰肽类和二肽、三肽类凝血酶抑制剂与人体α凝血酶结合时的活性构象,并在此基础上用分子力学计算了抑制剂与凝血酶的结合能,结果表明结合能与活性有很好的相关性,计算结果能合理地解释抑制剂与凝血酶的相互作用方式及结构与活性的关系.     

基于分子对接的咪唑啉类α_(2A)-肾上腺素能配体三维定量构效关系研究

对系列咪唑啉类α2A-肾上腺素能配体类似物进行MFA和CoMFA两种方法的定量构效关系研究。化合物的构象采用与α2A-肾上腺素能受体分子对接的最佳结合构象,计算结果表明,两种方法的计算结果有较好的一致性。MFA模型的r2和xv_r2分别为0.997和0.946,CoMFA模型的r2和xv_r2分别为0.999和0.580,两种方法得到的定量构效关系模型均有较好的拟合能力和预测能力,可用于对咪唑啉类α2A-肾上腺素能配体化合物进行虚拟筛选和活性评价。研究结果为进一步设计合成新的候选化合物提供理论依据。     

用分子对接方法预测HIV-1整合酶与金精三羧酸抑制剂的相互作用

用分子对接方法(Docking)研究了HIV-1整合酶与其抑制剂金精三羧酸的结合过程.为弄清金属离子在结合中所起的作用,选择含有一个Mg+2或不含Mg+2的两种不同的整合酶受体分别与金精三羧酸对接.结果表明, Mg+2对稳定配体与受体的结合起了重要作用. 金精三羧酸配体与含有一个金属Mg+2的整合酶受体对接,最优结合自由能为-45.19 kJ/mol. 当Mg+2失去后,整合酶的活性中心构象将发生变化,使金精三羧酸抑制剂与整合酶的结合自由能(-24.35 kJ/mol)明显增加. 预测了未知的HIV-1整合酶与其抑制剂金精三羧酸的复合物结构, 并可对基于结构的抗HIV-1整合酶的药物设计提供重要信息.     

HDAC对接研究:苯甲酰胺类抑制剂结合方式推测

通过计算机模拟的对接过程研究，发现了MS-275— 一种苯甲酰胺类的组蛋白去乙酰酶（HDAC）抑制剂与酶的可能的全新结合方式.这种结合方式与已经阐明的组蛋白去乙酰酶类似蛋白（HDLP）与曲古柳菌素A(trichostatin A, TSA)和suberoylanilide hydroxamic acid(SAHA)形成的复合物晶体结构中配体与酶的作用方式完全不同.从对接结果看，MS-275的作用靶点在酶活性口袋的最狭窄部位，而不是直接作用于锌离子.这似乎能够解释MS-275的低毒性特点，并且为设计和筛选全新的HDAC抑制剂提供了新思路.     

Modeling loop backbone flexibility in receptor‐ligand docking simulations

The relevance of receptor conformational change during ligand binding is well documented for many pharmaceutically relevant receptors, but is still not fully accounted for in in silico docking methods. While there has been significant progress in treatment of receptor side chain flexibility sampling of backbone flexibility remains challenging because the conformational space expands dramatically and the scoring function must balance protein–protein and protein–ligand contributions. Here, we investigate an efficient multistage backbone reconstruction algorithm for large loop regions in the receptor and demonstrate that treatment of backbone receptor flexibility significantly improves binding mode prediction starting from apo structures and in cross docking simulations. For three different kinase receptors in which large flexible loops reconstruct upon ligand binding, we demonstrate that treatment of backbone flexibility results in accurate models of the complexes in simulations starting from the apo structure. At the example of the DFG‐motif in the p38 kinase, we also show how loop reconstruction can be used to model allosteric binding. Our approach thus paves the way to treat the complex process of receptor reconstruction upon ligand binding in docking simulations and may help to design new ligands with high specificity by exploitation of allosteric mechanisms. © 2012 Wiley Periodicals, Inc.     

Molecular modelling prediction of ligand binding site flexibility

We have investigated the efficacy of generating multiple sidechain conformations using a rotamer library in order to find the experimentally observed ligand binding site conformation of a protein in the presence of a bound ligand. We made use of a recently published algorithm that performs an exhaustive conformational search using a rotamer library to enumerate all possible sidechain conformations in a binding site. This approach was applied to a dataset of proteins whose structures were determined by X-ray and NMR methods. All chosen proteins had two or more structures, generally involving different bound ligands. By taking one of these structures as a reference, we were able in most cases to successfully reproduce the experimentally determined conformations of the other structures, as well as to suggest alternative low-energy conformations of the binding site. In those few cases where this procedure failed, we observed that the bound ligand had induced a high-energy conformation of the binding site. These results suggest that for most proteins that exhibit limited backbone motion, ligands tend to bind to low energy conformations of their binding sites. Our results also reveal that it is possible in most cases to use a rotamer search-based approach to predict alternative low-energy protein binding site conformations that can be used by different ligands. This opens the possibility of incorporating alternative binding site conformations to improve the efficacy of docking and structure-based drug design algorithms.     

Exploring hierarchical refinement techniques for induced fit docking with protein and ligand flexibility

We present a series of molecular‐mechanics‐based protein refinement methods, including two novel ones, applied as part of an induced fit docking procedure. The methods used include minimization; protein and ligand sidechain prediction; a hierarchical ligand placement procedure similar to a‐priori protein loop predictions; and a minimized Monte Carlo approach using normal mode analysis as a move step. The results clearly indicate the importance of a proper opening of the active site backbone, which might not be accomplished when the ligand degrees of freedom are prioritized. The most accurate method consisted of the minimized Monte Carlo procedure designed to open the active site followed by a hierarchical optimization of the sidechain packing around a mobile flexible ligand. The methods have been used on a series of 88 protein‐ligand complexes including both cross‐docking and apo‐docking members resulting in complex conformations determined to within 2.0 Å heavy‐atom RMSD in 75% of cases where the protein backbone rearrangement upon binding is less than 1.0 Å α‐carbon RMSD. We also demonstrate that physics‐based all‐atom potentials can be more accurate than docking‐style potentials when complexes are sufficiently refined. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Representing receptor flexibility in ligand docking through relevant normal modes

Inspired by the current representation of the ligand-receptor binding process, a normal-mode-based methodology is presented to incorporate receptor flexibility in ligand docking and virtual screening. However, the systematic representation of the deformation space grows geometrically with the number of modes, and furthermore, midscale loop rearrangements like those found in protein kinase binding pockets cannot be accounted for with the first lowest-frequency modes. We thus introduced a measure of relevance of normal modes on a given region of interest and showed that only very few modes in the low-frequency range are necessary and sufficient to describe loop flexibility in cAMP-dependent protein kinase. We used this approach to generate an ensemble of representative receptor backbone conformations by perturbing the structure along a combination of relevant modes. Each ensemble conformation is complexed with known non-native binders to optimize the position of the binding-pocket side chains through a full flexible docking procedure. The multiple receptor conformations thus obtained are used in a small-scale virtual screening using receptor ensemble docking. We evaluated this algorithm on holo and apo structures of cAMP-dependent protein kinase that exhibit backbone rearrangements on two independent loop regions close to the binding pocket. Docking accuracy is improved, since the ligands considered in the virtual screening docked within 1.5 A to at least one of the structures. The discrimination between binders and nonbinders is also enhanced, as shown by the improvement of the enrichment factor. This constitutes a new step toward the systematic integration of flexible ligand-flexible receptor docking tools in structure-based drug discovery.     

Conformational selection of protein kinase A revealed by flexible-ligand flexible-protein docking

Protein kinases have high structural plasticity: their structure can change significantly, depending on what ligands are bound to them. Rigid-protein docking methods are not capable of describing such effects. Here, we present a new flexible-ligand flexible-protein docking model in which the protein can adopt conformations between two extremes observed experimentally. The model utilized a molecular dynamics-based simulated annealing cycling protocol and a distance-dependent dielectric model to perform docking. By testing this model on docking four diverse ligands to protein kinase A, we found that the ligands were able to dock successfully to the protein with the proper conformations of the protein induced. By imposing relatively soft conformational restraints to the protein during docking, this model reduced computational costs yet permitted essential conformational changes that were essential for these inhibitors to dock properly to the protein. For example, without adequate movement of the glycine-rich loop, it was difficult for the ligands to move from the surface of the protein to the binding site. In addition, these simulations called for better ways to compare simulation results with experiment other than using the popular root-mean-square deviation between the structure of a ligand in a docking pose and that in experiment because the structure of the protein also changed. In this work, we also calculated the correlation coefficient between protein-ligand/protein-protein distances in the docking structure and those in the crystal structure to check how well a ligand docked into the binding site of the protein and whether the proper conformation of the protein was induced.     

Predicting bioactive conformations and binding modes of macrocycles

Macrocyclic compounds experience increasing interest in drug discovery. It is often thought that these large and chemically complex molecules provide promising candidates to address difficult targets and interfere with protein–protein interactions. From a computational viewpoint, these molecules are difficult to treat. For example, flexible docking of macrocyclic compounds is hindered by the limited ability of current docking approaches to optimize conformations of extended ring systems for pose prediction. Herein, we report predictions of bioactive conformations of macrocycles using conformational search and binding modes using docking. Conformational ensembles generated using specialized search technique of about 70 % of the tested macrocycles contained accurate bioactive conformations. However, these conformations were difficult to identify on the basis of conformational energies. Moreover, docking calculations with limited ligand flexibility starting from individual low energy conformations rarely yielded highly accurate binding modes. In about 40 % of the test cases, binding modes were approximated with reasonable accuracy. However, when conformational ensembles were subjected to rigid body docking, an increase in meaningful binding mode predictions to more than 50 % of the test cases was observed. Electrostatic effects did not contribute to these predictions in a positive or negative manner. Rather, achieving shape complementarity at macrocycle-target interfaces was a decisive factor. In summary, a combined computational protocol using pre-computed conformational ensembles of macrocycles as a starting point for docking shows promise in modeling binding modes of macrocyclic compounds.     

Efficient inclusion of receptor flexibility in grid-based protein-ligand docking

Accounting for receptor flexibility is an essential component of successful protein-ligand docking but still marks a major computational challenge. For many target molecules of pharmaceutical relevance, global backbone conformational changes are relevant during the ligand binding process. However, popular methods that represent the protein receptor molecule as a potential grid typically assume a rigid receptor structure during ligand-receptor docking. A new approach has been developed that combines inclusion of global receptor flexibility with the efficient potential grid representation of the receptor molecule. This is achieved using interpolation between grid representations of the receptor protein deformed in selected collective degrees of freedom. The method was tested on the docking of three ligands to apo protein kinase A (PKA), an enzyme that undergoes global structural changes upon inhibitor binding. Structural variants of PKA were generated along the softest normal mode of an elastic network representation of apo PKA. Inclusion of receptor deformability during docking resulted in a significantly improved docking performance compared with rigid PKA docking, thus allowing for systematic virtual screening applications at small additional computational cost.     

Closing the side-chain gap in protein loop modeling

The success of structure-based drug design relies on accurate protein modeling where one of the key issues is the modeling and refinement of loops. This study takes a critical look at modeled loops, determining the effect of re-sampling side-chains after the loop conformation has been generated. The results are evaluated in terms of backbone and side-chain conformations with respect to the native loop. While models can contain loops with high quality backbone conformations, the side-chain orientations could be poor, and therefore unsuitable for ligand docking and structure-based design. In this study, we report on the ability to model loop side-chains accurately using a variety of commercially available algorithms that include rotamer libraries, systematic torsion scans and knowledge-based methods. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Ensemble docking into flexible active sites. Critical evaluation of FlexE against JNK-3 and beta-secretase

One of the main complicating factors in structure-based drug design is the conformational rearrangement of the receptor upon ligand binding implicating protein flexibility as a crucial component in virtual screening. The FlexE approach allows flexibility through discrete alternative conformations of varying parts of the protein taken from structures having similar backbone traces. Here the performance of FlexE was tested against that of FlexX and FlexX-Pharm, by carrying out virtual screening experiments on two sets of structurally distinct complexes, for the enzymes beta-secretase (BACE), and c-jun N-terminal kinase 3 (JNK-3). A large number of incompatible instances occurred between structural elements of the proteins thus loop movements could not be studied in JNK-3 as well as in BACE. The investigation of the side-chain flexibility revealed that at the most FlexE could achieve the enrichment yielded by FlexX in JNK-3 but not in BACE. Although limited side-chain variations (e.g. different protonation states) can be treated by FlexE, docking into protein ensembles remains a practical tool that decreases the average run time for a ligand.     

Site‐Specific Investigation of the Steady‐State Kinetics and Dynamics of the Multistep Binding of Bile Acid Molecules to a Lipid Carrier Protein

The investigation of multi‐site ligand–protein binding and multi‐step mechanisms is highly demanding. In this work, advanced NMR methodologies such as 2D ¹H–¹⁵N line‐shape analysis, which allows a reliable investigation of ligand binding occurring on micro‐ to millisecond timescales, have been extended to model a two‐step binding mechanism. The molecular recognition and complex uptake mechanism of two bile salt molecules by lipid carriers is an interesting example that shows that protein dynamics has the potential to modulate the macromolecule–ligand encounter. Kinetic analysis supports a conformational selection model as the initial recognition process in which the dynamics observed in the apo form is essential for ligand uptake, leading to conformations with improved access to the binding cavity. Subsequent multi‐step events could be modelled, for several residues, with a two‐step binding mechanism. The protein in the ligand‐bound state still exhibits a conformational rearrangement that occurs on a very slow timescale, as observed for other proteins of the family. A global mechanism suggesting how bile acids access the macromolecular cavity is thus proposed.