2,4-二氨基嘧啶类FAK抑制剂的3D-QSAR研究

摘要 本文选取42个2,4-二氨基嘧啶类FAK小分子抑制剂,分别以比较分子场分析法（CoMFA）与相似性指数分析法（CoMSIA）构建3D-QSAR模型,评价模板分子、公共骨架点、最小能量优化参数、分子构象等因素对模型优化的影响。分析最优模型中立体场、静电场以及氢键等因素对抑制剂活性的影响,并应用分子对接分析该类抑制剂与FAK蛋白的相互作用。结果表明选择16号化合物作为模板分子,骨架A作为公共骨架点,最小能量优化参数中电荷、最大迭代系数、最低能量限定值分别为MMFF94、1000、0.01 Kcal/mol时所构建的模型最优。以CoMFA和CoMSIA构建的3D-QSAR模型的交叉验证系数（q2）分别为0.666和0.736,非交叉验证系数（R2）分别为0.990和0.989,表明此模型具有良好的预测能力。分子对接分析显示,其与FAK的氨基酸残基CYS502、ASP564形成了重要的氢键作用,并与周围残基形成了较强的疏水作用。通过3D-QSAR的构建与分子对接分析,可指导2,4-二氨基嘧啶类FAK小分子抑制剂的进一步结构优化设计。     

基于虚拟筛选策略发现新型潜在JAK3小分子抑制剂

利用已知活性的分子采用基于配体的策略构建药效团模型,通过基于类药规则、药效团模型、多种精度的分子对接算法、MM/GBSA结合能预测以及ADMET筛选手段对含约250万个分子的数据库进行虚拟筛选。发现5种JAK3抑制剂的新型骨架,其中6个以1-苯基咪唑烷-2-酮为骨架的分子在与JAK3激酶的结合能以及分子的ADMET性质评价方面均表现优异,具备高JAK3抑制剂潜力,被认为是虚拟筛选的命中分子。     

基于虚拟筛选和分子动力学模拟发现新型ULK1抑制剂

Unc-51样自噬激活激酶1（unc-51-like autophagy activating kinase 1,ULK1）作为自噬启动的重要调控因子,是肿瘤治疗的关键靶点之一。首先,以已知ULK1抑制剂为基础构建药效团模型,通过药效团模型筛选、分子对接以及分子力学广义波恩表面积（Molecular Mechanics/Generalized Born Surface Area,MM/GBSA）结合自由能计算等方法,对含有52万多个类药性小分子的数据库进行虚拟筛选,得到具有较高理论亲和力的化合物。随后,50ns的分子动力学模拟验证了蛋白质-配体复合物结合的稳定性,最后10ns的平均结合自由能的计算研究进一步验证了配体的结合能力。结果表明,6个化合物（F5258-0159、F3407-0428、F0529-1100、F0696-3531、F3222-5280、F6525-5596）具有骨架新颖、分子对接分数和结合自由能数值优异及与ULK1的结合状态稳定等特点,可以作为新型潜在的ULK1抑制剂用于肿瘤治疗的研究,也为新型ULK1抑制剂的设计和研发提供新的研究思路。     

整合药效团及共价对接用于虚拟筛选JAK3抑制剂

大量研究表明JAK3与炎症疾病的发生、发展具有密切的关系,使得JAK3成为一个极具潜力的药物靶点。其中,JAK3共价抑制剂因其选择性高、活性强的特点受到广泛关注。但是,JAK3与其家族的其他成员同源性高,使得开发JAK3选择性抑制剂充满挑战。计算机虚拟筛选方法可以在分子水平对JAK3的结构特征进行针对性筛选,但是传统的共价对接方法效率较低、准确度欠佳,因此本文提出了一种结合药效团和共价对接的虚拟筛选策略。该联用方法从DrugBank数据库成功地筛选出已报道的JAK3临床抑制剂,表明了这种虚拟筛选不仅具有较高的效率,同时具备了较强的筛选准确性,为JAK3共价抑制剂的虚拟筛选提供一定的指导作用。     

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.     

人血白蛋白结合位点II的分子结合模式研究

人血白蛋白是血浆中含量最高的蛋白,是一种重要的载体蛋白,能与多种内源性和外源性物质结合。人血白蛋白主要有两个药物结合位点,位点I和位点II,其中位点II的柔性较大,对药物分子的亲和性较高。本文采用分子模拟方法,基于12种结合于位点II的小分子-人血白蛋白晶体结构,分析了相互作用能,发现12种分子的结合以疏水作用为主,静电作用为辅。进一步采用丙氨酸扫描和结合能评价,分析结合部位的关键氨基酸残基,探究结合模式的规律性,发现从位点入口到空腔内部存在静电、疏水和杂合的三层相互作用分布,共同形成了稳定的分子结合。最后采用分子对接和分子动力学模拟,预测了L-色氨酸的结合模式。研究结果有助于深入了解人血白蛋白药物位点II的小分子结合模式,为基于位点II的药物和分离配基的优化设计提供指导。     

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.     

STAT3环烷烃并噻吩类衍生物抑制剂的三维定量构效关系研究

本文对STAT3抑制剂的化学结构与生物活性之间的关系进行研究。采用三维定量构效关系(3D-QSAR)中的比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)方法针对52个STAT3抑制剂建立3D-QSAR模型,阐明了抑制剂化学结构与其生物活性之间的关系。所构建的CoMFA模型交叉验证系数为0.548,非交叉验证系数为0.754,标准偏差为0.278,显著系数为58.297;所构建的CoMSIA模型交叉验证系数为0.892,非交叉验证系数为0.597,标准偏差为0.192,显著系数为57.794。结果显示CoMFA和CoMSIA模型具有良好的稳定性和预测能力。3D-QSAR模型等势图提供的相关场信息对新型STAT3抑制剂的设计具有指导意义。     

新型嘧啶单环类非经典叶酸拮抗剂的合成及抗肿瘤活性研究

以课题组前期设计合成的非经典叶酸拮抗剂6-(4'-甲基苯乙基)-N5-氯乙酰基-2,4-二氨基哌啶并[3,2-d]嘧啶(wm-8.2)为先导化合物,将wm-8.2中的哌啶并嘧啶双环结构简化为嘧啶单环结构,以提高分子柔韧性并简化分子结构,根据6-位空间占位设计6-H和6-甲基两个系列,考察了不同桥链长度和不同芳香杂环侧链...     

由3D-QSAR、分子对接和分子动力学模拟研究吲唑类化合物与PI3Kδ抑制剂的相互作用

磷酸肌醇3-激酶δ(PI3Kδ)参与慢性阻塞性肺疾病的炎性过程并且被鉴定为一个新的潜在治疗靶点。本文采用三维定量构效关系(3D-QSAR)、分子对接和分子动力学方法研究了47个吲唑类化合物与P13Kδ激酶的相互作用,并建立了相应的模型。其中,比较分子场分析(CoMFA)模型q~2=0.719,r~2=0.972;比较分子相似性指数分析(CoMSIA)模型q~2=0.649,r~2=0.983,表明所建的QSAR模型具有稳定可靠的预测能力。CoMFA和CoMSIA等势图形象地描述了不同的场效应对活性的影响,其中立体场、疏水场及氢键受体场对活性有较大的贡献。接着采用分子对接探索小分子化合物与P13Kδ的结合模式,结合模式显示吲唑类化合物主要通过氢键作用与疏水作用与P13Kδ紧密结合,并且通过分子动力学模拟进一步验证了对接结果。最后根据等势图、对接模式和分子动力学模拟获取的信息设计了8个化合物,研究表明它们均能与PI3Kδ较好结合。     

Molecular Docking of 3-Methylindole-containing Drugs Binding into CYP3A4

Drugs SPD-304(6,7-dimethyl-3-{[methyl-(2-{methyl-[1-(3-trifluoromethyl-phenyl)-1H-indol-3-ylmethyl]- amino}-ethyl)-amino]-methyl}-chromen-4-one) and zafirlukast contain a common structural element of 3-substituted indole moiety which closely relates to a dehydrogenated reaction catalyzed by cytochrome P450s(CYPs). It was reported that the dehydrogenation can produce a reactive electrophilic intermediate which cause toxicities and inactivate CYPs. Drug L-745,870(3-{[4-(4-chlorophenyl)piperazin-1-yl]-methyl}-1H-pyrrolo- 2,3-β-pyridine) might have similar effect since it contains the same structural element. We used molecular docking approach combined with molecular dynamics(MD) simulation to model three-dimensional(3D) complex structures of SPD-304, zafirlukast and L-745,870 into CYP3A4, respectively. The results show that these three drugs can stably bind into the active site and the 3-methylene carbons of the drugs keep a reasonable reactive distance from the heme iron. The complex structure of SPD-304-CYP3A4 is in agreement with experimental data. For zafirlukast, the calculation results indicate that 3-methylene carbon might be the dehydrogenation reaction site. Docking model of L-745,870-CYP3A4 shows a potential possibility of L-745,870 dehydrogenated by CYP3A4 at 3-methylene carbon which is in agreement with experiment in vivo. In addition, residues in the phenylalanine cluster as well as S119 and R212 play a critical role in the ligands binding based on our calculations. The docking models could provide some clues to understand the metabolic mechanism of the drugs by CYP3A4.     

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.     

Prediction of the interaction of metallic moieties with proteins: An update for protein‐ligand docking techniques

In this article, we present a new approach to expand the range of application of protein‐ligand docking methods in the prediction of the interaction of coordination complexes (i.e., metallodrugs, natural and artificial cofactors, etc.) with proteins. To do so, we assume that, from a pure computational point of view, hydrogen bond functions could be an adequate model for the coordination bonds as both share directionality and polarity aspects. In this model, docking of metalloligands can be performed without using any geometrical constraints or energy restraints. The hard work consists in generating the convenient atom types and scoring functions. To test this approach, we applied our model to 39 high‐quality X‐ray structures with transition and main group metal complexes bound via a unique coordination bond to a protein. This concept was implemented in the protein‐ligand docking program GOLD. The results are in very good agreement with the experimental structures: the percentage for which the RMSD of the simulated pose is smaller than the X‐ray spectra resolution is 92.3% and the mean value of RMSD is < 1.0 Å. Such results also show the viability of the method to predict metal complexes–proteins interactions when the X‐ray structure is not available. This work could be the first step for novel applicability of docking techniques in medicinal and bioinorganic chemistry and appears generalizable enough to be implemented in most protein‐ligand docking programs nowadays available. © 2017 Wiley Periodicals, Inc.     

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。     

二氢异喹啉类BACE1抑制剂的特征结构及结合模式研究

β-分泌酶(BACE1)是水解淀粉样前体蛋白生成β-淀粉样多肽的关键限速酶,近年来已成为治疗阿尔茨海默症的一个理想靶点。本文以34个二氢异喹啉类BACE1抑制剂为研究对象,采用比较分子相似性指数(CoMSIA)法定量研究其结构与生物活性间的构效关系,并建立可靠的3D-QSAR预测模型,运用分子对接法分析其与受体BACE1间的结合模式。结果显示,基于立体场、疏水场和氢键供体场建立的CoMSIA模型稳定性良好、预测能力强(Q~2=0.47,R_(ncv)~2=0.93,R_(pre)~2=0.95)。本研究所得模型和信息较好地解释了二氢异喹啉类BACE1抑制剂的结构特征及其与受体间的结合模式,为后续新型BACE1抑制剂的设计开发提供理论指导。     

Pharmacophore and Docking-based 3D-QSAR Studies on HIV-1 Integrase Inhibitors

Integrase（IN） plays an essential role in the process of HIV-1 replication.IN inhibitors of diketo acid derivatives（DKAs） were analysed by the Comparative Molecular Field Analysis（CoMFA） and Comparative Molecular Similarity Induces Analysis（CoMSIA） methods.A set of 42 compounds were randomly selected as the training set（35） and test set（7）.Firstly,a good pharmacophore（goodness of hit=0.787） was obtained and used to align ligands.Then,predictive models were constructed with the CoMFA and CoMSIA methods based on the pharmacophore alignment.As a result,the CoMS1A method yielded the best model with an r2 of 0.955 and a q2 of 0.665,which can predict the activities of the tested DKAs very well（r2=0.559）.Finally,DKAs were docked into IN,and the predicit modes were superimposed on the contour maps obtained from the best CoMSIA model.The superimposed maps gave a visualized and meaningful insight into the inhibitory behaviors,providing significantly useful information for the rational drug design of anti-IN agents.     

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.     

Design of Ligand Binding to an Engineered Protein Cavity Using Virtual Screening and Thermal Up-shift Evaluation

Summary Proteins could be used to carry and deliver small compounds. As a tool for designing ligand binding sites in protein cores, a three-step virtual screening method is presented that has been optimised using existing data on T4 lysozyme complexes and tested in a newly engineered cavity in flavodoxin. The method can pinpoint, in large databases, ligands of specific protein cavities. In the first step, physico-chemical filters are used to screen the library and discard a majority of compounds. In the second step, a flexible, fast docking procedure is used to score and select a smaller number of compounds as potential binders. In the third step, a finer method is used to dock promising molecules of the hit list into the protein cavity, and an optimised free energy function allows discarding the few false positives by calculating the affinity of the modelled complexes. To demonstrate the portability of the method, several cavities have been designed and engineered in the flavodoxin from Anabaena PCC 7119, and the W66F/L44A double mutant has been selected as a suitable host protein. The NCI database has then been screened for potential binders, and the binding to the engineered cavity of five promising compounds and three tentative non-binders has been experimentally tested by thermal up-shift assays and spectroscopic titrations. The five tentative binders (some apolar and some polar), unlike the three tentative non-binders, are shown to bind to the host mutant and, importantly, not to bind to the wild type protein. The three-step virtual screening method developed can thus be used to identify ligands of buried protein cavities. We anticipate that the method could also be used, in a reverse manner, to identify natural or engineerable protein cavities for the hosting of ligands of interest.     

CYP2C9酶与Warfarin结合模型的立体选择性理论研究

对CYP2C9酶与S-Warfarin复合物的晶体结构进行分子对接、分子动力学模拟、通道分析及结合自由能计算,发现原晶体结构中的结合模式为"亚稳态",提出了CYP2C9与S-Warfarin结合的可催化模式;比较了CYP2C9与S-和R-Warfarin结合的异同,确定了在结合过程中起重要作用的锚定氨基酸残基,尤其是位于活性位点区域的苯丙氨酸簇.在结合过程中这些残基通过芳香环的移动对稳定底物的结合模式起到至关重要的作用,阐明了该酶呈现相关底物选择性的原因.对于CYP2C9与底物对接模式及立体选择性的研究有助于在分子层面上理解特异性底物与酶的结合特点,为潜在的药物设计提供了合理可信的理论依据.