基于增强采样分子动力学模拟的蛋白质和小分子相互作用
热力学和动力学研究
摘要
蛋白质和小分子相互作用的热力学（结合自由能ΔG bind和平衡解离常数K D）是表征一个药物小分子与其靶蛋白结合稳定性的重要依据，也是评价一个药物小分子与其靶蛋白亲和力大小的重要指标。而近些年来逐渐受到重视的蛋白质和小分子之间的结合动力学（解离速率常数k off和滞留时间）与药物小分子的药效和毒性等药代动力学性质密切相关，所以在以靶蛋白和药物小分子的热力学性质为依据进行药物设计时应同时考虑它们的结合动力学性质。基于蛋白质和小分子热力学和动力学的计算方法和预测热力学和动力学的重要性，本论文的研究内容主要有以下五个部分。
本论文第一章详述了蛋白质和小分子相互作用的重要性，从蛋白质和小分子相互作用理论模型开始，介绍了二者相互作用的物理化学基础以及二者结合的热力学和动力学性质。接着总结了研究蛋白质和小分子相互作用的热力学和动力学的计算方法。对于热力学性质来说，主要有基于分子对接的打分函数和基于分子动力学模拟的自由能计算方法，如我们熟知的MM/PB(GB)和自由能微扰计算方法。而针对动力学性质的计算，目前比较成熟的有拉伸分子动力学模拟、自适应偏置力模拟以及meta动力学模拟等增强采样方法。
第二章通过常规分子动力学模拟和拉伸动力学模拟研究了B-RAF激酶的两个高效抑制剂PLX4720和TAK-632解离机制的差异以及解离机制与滞留时间的关系。从两个抑制剂与B-RAF激酶复合物的晶体结构出发，我们首先对常规分子动力学模拟的平衡轨迹做了能量分解，发现B-RAF激酶结合两个抑制剂的关键氨基酸残基的能量贡献有明显的差异，尤其在变构结合位点处。这说明变构位点处的疏水作用对于提高B-RAF激酶抑制剂的药效以及延长滞留时间有很重要的作用。之后我们用随机加速分子动力学模拟对多条平衡轨迹选择不同的参数进行了统计，结果表明抑制剂PLX4720是从ATP通道解离，而抑制剂TAK-632则有1/3的几率从变构通道解离。为了比较这两个抑制剂解离的难易程度，我们用拉伸分子动力学模拟对PLX4720沿ATP通道和TAK-632沿ATP通道和变构通道做了解离，结果表明TAK-632从变构通道比从ATP通道解离困难的多，所以
这两个抑制剂都是从ATP通道解离的，这与实验值k off值的排序是一致的。
接着第三章我们研究了ERK2激酶的四个抑制剂SCH772984、VTX-11e、FR180204以及5-iTU解离机制的差异。我们用常规分子动力学模拟和能量分解研究了ERK2激酶与四个抑制剂的结合差异，结果表明抑制剂SCH772984与其他三个抑制剂结合的最大差异是位于P-loop和αC-helix之间的变构位点处的结合。随后的拉伸分子动力学模拟和自适应偏置力模拟表明SCH772984与其它三个抑制剂有不同的解离机制。VTX-11e、FR180204和5-iTU在解离过程中都是只需要克服ATP结合位点处的疏水作用，而SCH772984需要先克服变构位点处的π-π堆积作用，再克服ATP结合位点处的疏水作用，这明显增加了
SCH772984解离时需要克服的自由能势垒。
第四章阐述了激酶抑制剂crizotinib的镜像异构体对MTH1蛋白的抑制活性差异的原因。我们的理论计算值与实验值有很好的吻合，分子动力学模拟和氨基酸残基能量分解表明，MTH1对(S)-crizotinib和(R)-crizotinib结合的差异来源于Tyr7, Phe27, Phe72 和Trp117这些残基的贡献。进一步的自适应偏置力模拟表明(S)-crizotinib和(R)-crizotinib的解离路径完全不同，这使得(S)-crizotinib解离时需要吸收的能量明显比(R)-crizotinib解离时吸收的能量高，也就是(S)-crizotinib要克服更大的自由能势垒。
同样第五章解释了SETD7蛋白的对映异构体(R)-PFI-2和(S)-PFI-2的抑制活性不同的原因。首先我们通过分子对接获得了(S)-PFI-2和SETD7的复合物结构。静态分析发现，这两个化合物与SETD7结合时的构象完全不同。进一步的分子动力学模拟发现，(S)-PFI-2与SETD7的结合很不稳定，这是通过监测模拟体系的RMSD值发现的。另外静态网络分析的结果表明范德华相互作用力对(R)-PFI-2和SETD7的结合起了关键作用。我们提取了常规分子动力学模拟平衡部分的平均结构发现，(S)-PFI-2/SETD7复合物中post-SET loop区域更向外移动，这样就使得(S)-PFI-2更多的暴露在溶剂中所以更加不稳定。所以我们又对两个体系做了自适应偏置力模拟，与(R)-PFI-2解离相比，(S)-PFI-2解离时明显要容易的多，最后得到的PMF曲线升高的幅度没有(R)-PFI-2的大。所以我们得出结论，(S)-PFI-2与SETD7结合的不稳定性导致了它的抑制活性没有(R)-PFI-2高。
上述研究结果直接从分子水平上阐明了这四个与癌症相关的靶点与其抑制剂的相互作用机制，这将有助于发展更高效，选择性更高的抗癌药物。
关键词：结合热力学和动力学，分子动力学模拟，拉伸分子动力学模拟，自适应偏置力模拟，结合自由能计算，静态网络分析
Thermodynamic and Kinetic Studies on the Interaction of Proteins and Small Molecules based on Enhanced Sampling Molecular Dynamics Simulation
Abstract
The thermodynamics of proteins and small molecules interaction (such as binding free energy ΔG bind and the equilibrium dissociation constant K D) is an important basis for the characterization of the binding stability of a drug and its target protein, and is also an important index to evaluate the affinity of a drug and its target protein interaction. But in recent years, the binding kinetics between protein and small molecules (such as the dissociation rate constant k off and the residence time), which has been paid more and more attention, is closely related to the pharmacokinetic and toxicity of a drug. Therefore, the binding kinetics should be taking into account in the drug design based on the thermodynamics of target proteins and small molecules interaction. Based on the calculation of thermo
dynamics and kinetics of proteins and small molecules, and the importance of predicting thermodynamics and kinetics, the main contents of present paper include the following five parts.
The first chapter of this paper describes the importance of proteins and small molecules. Starting from the theory model of proteins and small molecules interaction, this chapter introduces the physical and chemical basis of the interaction and the thermodynamics and kinetics between the proteins and small molecules. Then we summed up the calculation methods of thermodynamics and kinetics of proteins and small molecules interaction. For thermodynamics of proteins and small molecules, there are mainly scoring functions based on molecular docking and binding free energy calculations based on molecular dynamic simulations, such as the well-known MM/PB (GB) method and free energy perturbation calculations. While the most mature methods for the calculation of binding kinetics including steered molecular dynamic simulations, the adaptive biasing force simulations and metadynamic simulations.
In the second chapter, we studied the dissociation mechanism of two potent inhibitors PLX4720 and TAK-632 of B-RAF kinase and the relationship between the dissociation mechanism and the residence time. Starting from the crystal structures of the two inhibitors with
reaction kinetics mechanism期刊B-RAF complexes, we firstly simulated the equilibrium trajectory of conventional molecular dynamics for energy decomposition, and we found that the energy contribution of the key amino acid residues for binding the two inhibitors is obvious differences, especially in the allosteric site. This shows that the hydrophobic interaction located in the allosteric site is very important to improve the efficacy and prolong the residence time of the B-RAF kinase inhibitors. we then used the random acceleration molecular dynamic simulations with different parameters for multiple equilibrium trajectories carried out statistics, found that the ligand PLX4720 dissociated from the ATP channel, while the ligand TAK-632 has a 1/3 chance to dissociate from the allosteric channel. In order to compare the ease of the two inhibitors dissociation from the different channel, we applied the steered molecular dynamic simulations to study the ligands PLX4720 and TAK-632 dissociate along the A TP channel and the ligand TAK-632 dissociates along the allosteric channel. The results show that TAK-632 dissociating along the allosteric channel is more difficult than that along the ATP channel, so the two ligands both dissociate along the ATP channel, which is agreement with the experimental data k off.
In the third chapter, we studied the differences of the four ERK2 kinase inhibitors SCH772984、VTX-11e、FR180204 and 5-iTU dissociating mechanism. Conventional molecular dynamic simulations and energy decomposition were employed to study the binding difference of ERK2 protein and the four liga
nds, the results show that the maximum difference between the ligand and the other three ligands is the binding of SCH772984 with the ERK2 protein between the P-loop and the αC helix. Afterwards, the steered molecular dynamic simulations and adaptive biasing force were applied to study the dissociation mechanism of the four ligands, the results show that SCH772984 has different dissociation mechanisms with the other three ligands. VTX-11e, FR180204 and 5-iTU are only required to overcome the hydrophobic interaction located in ATP binding site in the dissociation course, and SCH772984 needs to overcome the pi-pi interaction in the allosteric site, and then it needs to overcome the hydrophobic interaction in the ATP binding site, which significantly increases the free energy barrier of SCH772984 dissociation.
In the fourth chapter, we discussed the influence of chirality of crizotinib on its MTH1 protein inhibitory activity, and our theoretical calculations are well agreement with the experimental values. the results of molecular dynamic simulations and amino acid residues energy decomposition indicate that the difference in (S)-crizotinib/MTH1 and (R)-crizotinib/MTH1 binding is due to the energy contribution of these residues Tyr7、Phe27、Phe72 and Trp117. The adaptive biasing force simulations show that (S)-crizotinib and (R)-crizotinib have the completely different dissociation paths, which makes (S)-crizotinib need to absorb more energy than
(R)-crizotinib when dissociating from the MTH1 binding site, that is to say, (S)-crizotinib need to overcome the larger free energy barrier.
The fifth chapter also explains the difference in the inhibitory activity of (S)-PFI and (R)-PFI-2 against SETD7 protein. We first obtain the complex structure of (S)-PFI-2 and SETD7 by molecular docking, and the static analysis revealed the two ligands binding SETD7 by completely different conformation. Further molecular dynamic simulations show that the binding of (S)-PFI-2 with SETD7 is very unstable, which is found by monitoring the RMSD of the simulated system. In addition, the results of residues interaction network analysis show that the van del Waal interaction plays a key role in the binding of (R)-PFI-2 with SETD7. we got the average structure of the equilibrium trajectory from conventional molecular dynamic simulations and found that the post-SET loop in the (S)-PFI-2/SETD7 complex move more outward, which makes (S)-PFI-2 more exposed to the solvent and more unstable. Therefore, the adaptive biasing force was employed to study the dissociation behavior of the two ligands. Comparing with the (R)-PFI-2 dissociating along its reaction coordinate, the (S)-PFI-2 dissociates significantly easier along its reaction coordinate. The amplitude of the PMF curve of (S)-PFI-2/SETD7 is not larger than that of (R)-PFI-2/SETD7, so we get the conclusion that the instability of (S)-PFI-2 binding to SETD7 leads to the inhibitory activity of (S)-PFI-2 is less high than that of (R)-PFI-2.
The results of these studies directly elucidate the molecular mechanism of the interaction between the four targets and their inhibitors, which will be helpful the development of more efficient and selective anticancer drugs.
Key words: the binding thermodynamics and kinetics, molecular dynamic simulations, steered molecular dynamic simulations, adaptive biasing force simulations, binding free energy calculations, residues interaction network analysis

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