基于分子动力学模拟提高嗜热磷酸三酯酶样内酯酶非特异性底物活力的理论研究

采用分子动力学模拟和拉伸分子动力学模拟方法, 结合分子力学-广义玻恩表面积(MM-GB/SA)方法进行自由能计算和结构交互指纹分析, 研究了模拟过程中非特异性底物(对氧磷/内酯)分别与嗜热磷酸三酯酶样内酯酶(SsoPox)野生型和突变体(W263F/W263T)结合的构象变化, 分析了Loop8中重要残基Trp263的突变提高SsoPox非特异性底物活力的原因, 发现其能够影响门控残基Phe229的构象变化, 导致活性口袋入口变宽(Phe229与Tyr99之间的距离变大), 使对氧磷和内酯更容易结合到蛋白质的活性位点上; Asp256和Arg223形成盐桥的几率高于野生型(WT)SsoPox, 在Arg223(位于Loop7)的协助下质子更加高效地从活性中心的Asp256(位于Loop8)传递到溶剂中去, 因而能够提高SsoPox水解底物的效率. 通过比较2个野生型复合物的结构稳定性和结合自由能差异, 发现在模拟过程中SsoPox与内酯的复合物体系更加稳定并且具有更低的结合自由能, 有利于SsoPox识别底物并使其埋在活性部位的疏水环境中, 促进氢氧化物亲核进攻底物的亲电中心. 因此, 底物与酶稳定的相互作用可能是SsoPox具有天然内酯酶活性的原因之一.     

活细胞单分子力谱研究阿托伐他汀对ICAM-1与CD11b相互作用的影响

调节细胞黏附的整合素蛋白CD11b与其配体ICAM-1的相互作用在动脉粥样硬化的炎症进程中起至关重要的作用.阿托伐他汀(Atorvastatin,ATV)作为他汀类药物中的主要成员,以其良好的降脂作用广泛应用于动脉粥样硬化疾病的临床治疗,同时大量证据表明ATV还具有独立的抗炎作用,但其具体分子机制尚未完全明确.我们应用活细胞单分子力谱法研究了ATV干预对ICAM-1/CD11b相互作用的影响.结果表明原子力显微镜(AFM)在活细胞表面测得单对黏附分子ICAM-1/CD11b的相互作用力值约为40pN,ATV不能通过直接阻断ICAM-1或CD11b影响其单分子黏附力,而抗ICAM-1单克隆抗体则有效降低了此对黏附分子作用力.此外,流式结果表明ATV干预有效抑制了肿瘤坏死因子(TNF-α)诱导的人脐静脉内皮细胞(HUVEC)表面ICAM-1表达增加.本研究建立的方法模型可作为活细胞体系研究临床药物影响细胞黏附分子间相互作用及抗炎机制的重要手段.     

基于多光谱方法和计算模拟的细胞色素CYP1A2与阿奇霉素的结合机制研究

为了解阿奇霉素(AZI)在模拟的人体环境中与CYP1A2的结合情况,探索AZI在人体内的转化机制,本论文使用分子对接、分子动力学模拟、荧光光谱、紫外分光光度法、傅立叶变换红外光谱、圆二色光谱等多种实验方法,阐明AZI与CYP1A2之间的相互作用机制。分子对接结果表明AZI与CYP1A2的结合方式是半包裹并且以疏水作用力相结合。分子动力学模拟结果表明,CYP1A2-AZI复合物的均方根偏差(RMSD)值增大;均方根波动(RMSF)值表明复合物体系柔性较大;回旋半径(Rg)值表明蛋白质特定区域的结构松散。荧光猝灭光谱实验表明,CYP1A2与AZI是以静态猝灭机制结合在一起。热力学参数表明AZI与CYP1A2之间的主导作用力为疏水作用力。时间分辨光谱表明AZI对CYP1A2的机制为静态猝灭。紫外光谱实验表明AZI与CYP1A2反应生成了复合物。红外光谱实验结果表明CYP1A2的二级结构含量发生了改变。圆二色光谱证实AZI对CYP1A2的二级结构产生影响。     

力场/溶剂水模型对EGFRvⅢ抗原-MR1(scFv)抗体复合物的MM-PBSA计算精度的影响与实验验证

以表皮生长因子Ⅲ型突变体(EGFRvⅢ)抗原多肽与其抗体(MR1)及其人源化突变体的复合物结构为出发点,采用分子动力学中的6种常用力场及3种常用溶剂水模型,分别对上述抗原-抗体复合物进行100ns的分子动力学模拟与分子力学和连续介质模型计算自由能(MM-PBSA),并在实验上利用等温滴定量热(ITC)仪测定了抗原和抗体相互作用的热力学参数.通过在结构变化、能量变化及野生型与突变体比较等几个方面进行综合分析,给出了最佳的计算模型.对不同力场及水模型计算精度等相关问题进行了探讨.     

Importance of individual side chains for the stability of a protein fold: computational alanine scanning of the insulin monomer

A new computational approach is proposed to probe the importance of residue side chains for the stability of a protein fold. Computational mutations to estimate protein stability (CMEPS) is based on the notion that the binding free energy corresponding to the complexation of a given side chain, considered as a "pseudo-ligand" of the wild type protein, reflects the importance of this side chain to the thermodynamic stability of the protein. The contribution of a particular side chain to the folding energy is estimated according to the molecular mechanics-generalized born surface area MM-GBSA approach, using a single molecular dynamics simulation trajectory of the wild type protein. CMEPS is a first principles method which does not contain any adjustable parameter that could be fitted to experimental data. The approach is first validated for Barnase and the B1 domain of protein L, for which a correlation coefficient R = 0.73, between experimental and CMEPS calculated DeltaDeltaG values, is found and then applied to the insulin monomer. In the present application, CMEPS replaces each amino acid by an alanine residue. Therefore, most mutations lead to cavities in the protein. From this the change in stability can be correlated with increased cavity volume. For insulin, this correlation is very similar compared with data previously analyzed for T4 lysozyme from an experiment for buried apolar side chains. There, the increased cavity volume has been related to the hydrophobic effect. However, since CMEPS uses the energetics in terms of electrostatic and van der Waals interactions (and not the hydrophobic effect which is difficult to relate to physical interactions), it is possible to study the effect of mutations of polar and solvent accessible side chains. According to CMEPS, residues Leu A16, Tyr A19, Leu B11, Leu B15, and Arg B22 are most important for the stability of the monomeric insulin fold. This is in agreement with experimental data. As a consequence, mutation of these residues may lead to misfolded and inactive insulin analogues.     

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.     

On Restraints in End-Point Protein–Ligand Binding Free Energy Calculations

The impact of harmonic restraints on protein heavy atoms and ligand atoms on end-point free energy calculations is systematically characterized for 54 protein–ligand complexes. We observe that stronger restraints reduce the equilibration time and statistical inefficiency, suppress conformational sampling, influence correlation with experiment, and monotonically decrease the estimated loss of entropy upon binding, leading to stronger estimated binding free energies in most systems. A statistical estimator that reweights for the biasing potential and includes data prior to the estimated equilibration time has the highest correlation with experiment. A spring constant of 20 cal mol⁻¹ Å⁻² maintains a near-native energy landscape and suppresses artifactual energy minima while minimally limiting thermal fluctuations about the crystal structure. © 2019 Wiley Periodicals, Inc.     

Could chroman-4-one derivative be a better inhibitor of PTR1? – Reason for the identified disparity in its inhibitory potency in Trypanosoma brucei and Leishmania major

Most notable Kinetoplastids are of the genus Trypanosoma and Leishmania, affecting several millions of humans in Africa and Latin America. Current therapeutic options are limited by several drawbacks, hence the need to develop more efficacious inhibitors. An investigation to decipher the mechanism behind greater inhibitory potency of a chroman-4-one derivative (compound 1) in Trypanosoma brucei pteridine reductase 1 (TbPTR1) and Leishmania major pteridine reductase 1 (LmPTR1) was performed. Estimation of ΔG_bind revealed that compound 1 had a greater binding affinity in TbPTR1 with a ΔG_bind value of −49.0507 Kcal/mol than −29.2292 Kcal/mol in LmPTR1. The ΔGbind in TbPTR1 were predominantly contributed by “strong” electrostatic energy compared to the “weak” van der Waals in LmPTR1. In addition to this, the NADPH cofactor contributed significantly to the total energy of TbPTR1. A characteristic weak aromatic π interaction common in PTR1 was more prominent in TbPTR1 than LmPTR1. The consistent occurrence of high-affinity conventional hydrogen bond interactions as well as a steady interaction of crucial active site residues like Arg14/Arg17, Ser95/Ser111, Phe97/Phe113 in TbPTR1/LmPTR1 with chroman-4-one moiety equally revealed the important role the moiety played in the activity of compound 1. Overall, the structural and conformational analysis of the active site residues in TbPTR1 revealed them to be more rigid than LmPTR1. This could be the mechanism of interaction TbPTR1 employs in exerting a greater potency than LmPTR1. These findings will further give insight that will be assistive in modifying compound 1 for better potency and the design of novel inhibitors of PTR1.     

A challenging system: free energy prediction for factor Xa

Factor Xa (fXa) is a promising target for antithrombotic drugs. Recently, we presented a molecular dynamics study on fXa, which highlighted the need for a careful system setup to obtain stable simulations. Here, we show that these simulations can be used to predict the free energy of binding of several fXa inhibitors. We tested molecular mechanics/Poisson-Boltzmann surface area, molecular mechanics/Generalized Born surface area, and linear interaction energy (LIE) on a small data set of fXa ligands. The continuum solvent approaches only yield satisfying correlations to the experimental results if some of the water molecules are explicitly included in the free energy calculations. LIE gave reasonable results if a sufficiently large data set is used. In general, our procedure of setting up the fXa simulation system enabled MD simulations, which produce adequate ensembles for free energy calculations.     

Calculation of hot spots for protein–protein interaction in p53/PMI-MDM2/MDMX complexes

The recently developed MM/GBSA_IE method is applied to computing hot and warm spots in p53/PMI-MDM2/MDMX protein–protein interaction systems. Comparison of the calculated hot (>2 kcal/mol) and warm spots (>1 kcal/mol) in P53 and PMI proteins interacting with MDM2 and MDMX shows a good quantitative agreement with the available experimental data. Further, our calculation predicted hot spots in MDM2 and MDMX proteins in their interactions with P53 and PMI and they help elucidate the interaction mechanism underlying this important PPI system. In agreement with the experimental result, the present calculation shows that PMI has more hot and warm spots and binds stronger to MDM2/MDMX. The analysis of these hot and warm spots helps elucidate the fundamental difference in binding between P53 and PMI to the MDM2/MDMX systems. Specifically, for p53/PMI-MDM2 systems, p53 and PMI use essentially the same residues (L54, I61, Y67, Q72, V93, H96, and I99) of MDM2 for binding. However, PMI enhanced interactions with residues L54, Y67, and Q72 of MDM2. For the p53/PMI-MDMX system, p53 and PMI use similar residues (M53, I60, Y66, Q71, V92, and Y99) of MDMX for binding. However, PMI exploited three extra residues (M61, K93, and L98) of MDMX for enhanced binding. In addition, PMI enhanced interaction with four residues (M53, Y66, Q71, and Y99) of MDMX. These results gave quantitative explanation on why the binding affinities of PMI-MDM2/MDMX interactions are stronger than that of p53-MDM2/MDMX although their binding modes are similar. © 2018 Wiley Periodicals, Inc.     

Crystal molecular dynamics simulations to speed up MM/PB(GB)SA evaluation of binding free energies of di-mannose deoxy analogs with P51G-m4-Cyanovirin-N

Complexes of two Cyanovirin-N (CVN) mutants, m4-CVN and P51G-m4-CVN, with deoxy di-mannose analogs were employed as models to generate conformational ensembles using explicit water Molecular Dynamics (MD) simulations in solution and in crystal environment. The results were utilized for evaluation of binding free energies with the molecular mechanics Poisson-Boltzmann (or Generalized Born) surface area, MM/PB(GB)SA, methods. The calculations provided the ranking of deoxy di-mannose ligands affinity in agreement with available qualitative experimental evidences. This confirms the importance of the hydrogen-bond network between di-mannose 3'- and 4'-hydroxyl groups and the protein binding site B(M) as a basis of the CVN activity as an effective HIV fusion inhibitor. Comparison of binding free energies averaged over snapshots from the solution and crystal simulations showed high promises in the use of the crystal matrix for acceleration of the conformational ensemble generation, the most time consuming step in MM/PB(GB)SA approach. Correlation between energy values based on solution versus crystal ensembles is 0.95 for both MM/PBSA and MM/GBSA methods.     

Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking

In molecular docking, it is challenging to develop a scoring function that is accurate to conduct high-throughput screenings. Most scoring functions implemented in popular docking software packages were developed with many approximations for computational efficiency, which sacrifices the accuracy of prediction. With advanced technology and powerful computational hardware nowadays, it is feasible to use rigorous scoring functions, such as molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) in molecular docking studies. Here, we systematically investigated the performance of MM/PBSA and MM/GBSA to identify the correct binding conformations and predict the binding free energies for 98 protein-ligand complexes. Comparison studies showed that MM/GBSA (69.4%) outperformed MM/PBSA (45.5%) and many popular scoring functions to identify the correct binding conformations. Moreover, we found that molecular dynamics simulations are necessary for some systems to identify the correct binding conformations. Based on our results, we proposed the guideline for MM/GBSA to predict the binding conformations. We then tested the performance of MM/GBSA and MM/PBSA to reproduce the binding free energies of the 98 protein-ligand complexes. The best prediction of MM/GBSA model with internal dielectric constant 2.0, produced a Spearman's correlation coefficient of 0.66, which is better than MM/PBSA (0.49) and almost all scoring functions used in molecular docking. In summary, MM/GBSA performs well for both binding pose predictions and binding free-energy estimations and is efficient to re-score the top-hit poses produced by other less-accurate scoring functions.     

Pharmacophore and docking-based virtual screening approach for the design of new dual inhibitors of Janus kinase 1 and Janus kinase 2

Janus kinase 1 and 2, non-receptor protein tyrosine kinases, are implicated in various cancerous diseases. Involvement of these two enzymes in the pathways that stimulate cell proliferation in cancerous conditions makes them potential therapeutic targets for designing new dual-targeted agents for the treatment of cancer. In the present study, two separate pharmacophore models were developed and the best models for JAK1 (AAADH.25) and JAK2 (ADRR.92) were selected on the basis of their external predictive ability. Both models were subjected to a systematic virtual screening (VS) protocol using a PHASE database of 1.5 million molecules. The hits retrieved in VS were investigated for ADME properties to avoid selection of molecules with a poor pharmacokinetic profile. The molecules considered to be within the range of acceptable limits of ADME properties were further employed for docking simulations with JAK1 and JAK2 proteins to explore the final hits that possess structural features of both pharmacophore models as well as display essential interactions with both of them. Thus, the new molecules obtained in this way should show inhibitory activity against JAK1 and JAK2 and may serve as novel therapeutic agents for the treatment of cancerous disease conditions.     

Molecular dynamics simulations reveal the allosteric effect of F1174C resistance mutation to ceritinib in ALK-associated lung cancer

Anaplastic lymphoma kinase (ALK) has become as an important target for the treatment of various human cancers, especially non-small-cell lung cancer. A mutation, F1174C, suited in the C-terminal helix αC of ALK and distal from the small-molecule inhibitor ceritinib bound to the ATP-binding site, causes the emergence of drug resistance to ceritinib. However, the detailed mechanism for the allosteric effect of F1174C resistance mutation to ceritinib remains unclear. Here, molecular dynamics (MD) simulations and binding free energy calculations [Molecular Mechanics/Generalized Born Surface Area (MM/GBSA)] were carried out to explore the advent of drug resistance mutation in ALK. MD simulations observed that the exquisite aromatic-aromatic network formed by residues F1098, F1174, F1245, and F1271 in the wild-type ALK-ceritinib complex was disrupted by the F1174C mutation. The resulting mutation allosterically affected the conformational dynamic of P-loop and caused the upward movement of the P-loop from the ATP-binding site, thereby weakening the interaction between ceritinib and the P-loop. The subsequent MM/GBSA binding free energy calculations and decomposition analysis of binding free energy validated this prediction. This study provides mechanistic insight into the allosteric effect of F1174C resistance mutation to ceritinib in ALK and is expected to contribute to design the next-generation of ALK inhibitors.