疏水蛋白在云母表面的吸附

采用分子动力学模拟方法研究了疏水蛋白(HFBI)在亲水云母表面的吸附过程.通过6组平行的分子动力学模拟得到了2种不同的稳定吸附结构,即通过N端和通过亲水的α螺旋与表面吸附,得到了5种吸附残基.进一步用自适应偏置力方法计算了所有吸附残基与表面的结合自由能.结果表明,残基Lys是吸附过程的关键残基,即当HFBI通过含有Lys残基的α螺旋与云母表面作用时,其吸附构象最稳定.静电作用是吸附过程的主要驱动力.在该吸附结构中,HFBI的疏水面暴露在溶液中,有效降低了云母表面的润湿性.     

喹啉加氧酶中氧气扩散的通道分析

通过生物信息学分析、量化计算优化、CAVER和MDpocket预测、随机加速分子动力学及伞状抽样动力学模拟等方法,对喹啉加氧酶(HOD)中的氧气扩散途径进行了计算预测.结果表明,氧气在HOD中的反应位点包埋在蛋白内部,而HOD中有数条可能的通道供氧气进出,其中长度最短的通道具有最高的优先度,不仅在随机加速动力学模拟中具有最高的氧气逸出概率,而且伞状抽样方法计算得到的自由能也最低.此通道的内端位于底物Re面的氧气结合位点,较好地解释了HOD的相关实验数据.     

自由能计算揭示苏氨酸对抗冻蛋白与冰晶结合能力的影响

采用分子动力学模拟和自由能计算研究了中等活性黑麦草抗冻蛋白(Lolium perenne antifreeze protein, LpAFP)冰结合位点(Ice-binding site, IBS)上苏氨酸(Thr)含量对其吸附冰晶能力的影响. 构建了一系列LpAFP突变体结构, 使其IBS上苏氨酸含量逐步增加, 其中包括一个对IBS上11个位点的突变, 使每个β片段均具有Thr-x-Thr基序(x是非保守的氨基酸, 主要是疏水氨基酸). 利用重要性采样算法(WTM-eABF)计算了LpAFP及其突变体与冰晶结合过程的自由能变化, 该算法结合了Well-tempering metadynamics的“填谷”和扩展拉格朗日自适应偏置力方法的“削峰”的优点, 显著提高了算法的采样效率. 结果表明, LpAFP突变体的IBS苏氨酸含量越高, 其与冰的结合在能量上越有利. 当突变体具有重复Thr-x-Thr基序时, 其与冰的结合能力最强. 进一步分析表明, 苏氨酸含量越高, IBS结合的液态水分子越多, 与冰晶结合时锚定包合水稳定存在的时间就越长, 抗冻蛋白的IBS与冰面之间的氢键网络也越稳定, 从而提高了抗冻蛋白与冰的结合能力. 增加苏氨酸残基的含量是提高中等活性抗冻蛋白抗冻活性的方法.     

副本交换分子动力学

副本交换分子动力学(REMD)是一种广泛应用于蛋白质功能性构象变化模拟及相应自由能计算的增强型采样算法。由于REMD理论严格且采样效率高,近年来备受关注,尤其是针对传统REMD方法的发展和优化,显著提高了REMD的采样效率,拓展了其应用范围。但是各种REMD新型方法的最佳适用范围也存在较大区别,使得如何选用合适的REMD方法成为实际应用的难题和挑战。因此,有必要对各种REMD方法及其应用进行阐述,深入比较各方法的优缺点及其实际应用体系。本综述从REMD的原理出发,回顾了近年来各类REMD方法的变形策略,以助于对REMD方法的理解、应用和继续改进。     

不同力场对B-DNA到A-DNA构型转变的影响

采用分子动力学模拟方法比较了最新版CHARMM和AMBER(包括bsc1和OL15)力场对水溶液中B-DNA到A-DNA转化过程的影响,利用扩展自适应偏置力(eABF)方法计算了转化过程的自由能变化.研究结果表明,在不同力场下,水环境中的DNA最稳定结构存在差异,AMBER力场比CHARMM力场更符合实验结果.AMBER力场下DNA最稳定结构的小沟较窄,稳定于B构型;而CHARMM力场下DNA最稳定结构的小沟较宽,介于B构型与A构型之间.通过分析DNA周围离子及水的分布情况发现,CHARMM力场下DNA小沟周围的离子密度明显低于AMBER力场,不能很好地抵消2条磷酸骨架之间的排斥作用,这是CHARMM力场下小沟较宽且趋向A构型的主要原因.     

机器学习加速氧化还原电位和酸度常数计算

氧化还原电位和酸度常数作为重要的物理化学性质被应用于分析能源材料重要指标值。为了实现能源材料的计算设计,发展计算电化学的方法,在复杂电化学环境下计算这些性质至关重要。近年来,利用计算电化学方法计算氧化还原电位和酸度常数已经受到了广泛的关注。然而,常用的计算方法如基于隐式溶剂化模型的小分子自由能计算,对于复杂溶剂化环境的处理非常有限。因此,基于第一性原理分子动力学（AIMD）的自由能计算被引入来描述复杂溶剂化环境中的溶质-溶剂相互作用。同时,基于AIMD的自由能计算方法已经被证实可以准确预测这些物理化学性质。然而,由于AIMD计算效率低且计算资源需求大,需要引入机器学习分子动力学（MLMD）加速计算。MLMD通过机器学习方法,构建模拟体系结构到第一性原理计算结果的一对一映射,可以在低成本下实现长时间尺度的AIMD。对于氧化还原电位和酸度常数计算,如何构建训练机器学习势函数模型所需的数据集至关重要。本文介绍了如何通过自动化工作流实现自由能计算势函数的自动化构建,通过机器学习分子动力学计算自由能并转化为对应的物理化学性质。     

γ-环糊精和波尼松龙的相互作用分子动力学模拟和自由能计算

运用分子动力学（Molecular dynamics,MD）和MM—PBSA（molecular mechanics／Poisson Boltzmann surfaeearea）相结合的方法预测了γ-环糊精（γ-cyclodextrin,γ-CD）和波尼松龙的包结模式．在MD模拟过程中,波尼松龙分别采用A环和D环两种取向从γ-CD大口端进入其空腔．在MD轨迹采样基础上,采用高效MM—PBSA方法计算了两种取向的包结自由能．结果表明,计算包结自由能值和实验包结自由能值非常吻合．进一步分析各个能量项,发现范德华相互作用能为包结的主要驱动力．通过比较两种取向的包结自由能大小,预测D环取向为优势包结模式．     

分子动力学模拟3(5)-(9-蒽基)吡唑分子在自组装膜上的选择性沉积

采用平衡分子动力学和拉伸分子动力学模拟方法研究了模板诱导有机发光小分子3(5)-(9-蒽基)吡唑(ANP)在自组装膜上的选择性沉积,并利用伞形取样方法和加权柱状图分析法计算了沉积过程的均力势.模拟中以二氧化硅为底板分别构筑2种不同密度的烷烃链自组装膜模板,即低密度的液体扩展相和高密度的液体压缩相.平衡分子动力学结果显示,ANP分子容易沉积至低密度的液体扩展相中,难以沉积至高密度的液体压缩相中.拉伸分子动力学结果表明,当ANP分子沉积至液体压缩相表面时,在进入烷烃膜时遇到较大阻力,因而不易进入到烷烃链单层膜中;而ANP分子在进入液体扩展相的过程中受到的阻力较小.通过比较这2种不同密度自组装膜与ANP分子之间的结合自由能,发现ANP分子进入液体压缩相的能垒较高,而ANP分子与液体扩展相结合更加稳定,导致有机发光小分子在不同密度的模板上具有选择吸附性.所得模拟结果与实验现象一致,在分子水平上为实验提供了更加丰富的微观信息.     

天然产物法卡林二醇与人类GABAA受体相互作用的机制

通过分子动力学模拟、伞形采样模拟、结合自由能计算和分子对接等方法,研究了法卡林二醇在γ-氨基丁酸A型(GABA_A)受体上结合作用的模式和对GABA_A受体动态属性的影响,确定了3个有效结合位点均对此受体产生拮抗作用,为后续研究聚乙炔醇类化合物对GABA_A受体作用及相应药物开发提供了理论依据.     

MMP-2和Hydroxamate类抑制剂绝对自由能的计算

采用基于线性响应近似的自由能计算方法计算了一类hydroxamate抑制剂和MMP-2的绝对结合自由能。计算中,催化锌离子和MMP-2以及配体之间采用了非键模型。分子动力学模拟结果显示,采用非键模型时,催化Zn离子采用五配位的形式,但配位键的形式和初始结构比较有很大的差别。通过拟合,分别得到了单参数、双参数以及三参数的自由能预测模型,其中,含有常数校正项的三参数模型具有最佳的预测能力,预测自由能和实际自由能之间平均绝对误差仅为2.38kJ/mol。     

MkVsites: A tool for creating GROMACS virtual sites parameters to increase performance in all-atom molecular dynamics simulations

The absolute performance of any all-atom molecular dynamics simulation is typically limited by the length of the individual timesteps taken when integrating the equations of motion. In the GROMACS simulation software, it has for a long time been possible to use so-called virtual sites to increase the length of the timestep, resulting in a large gain of simulation efficiency. Up until now, support for this approach has in practice been limited to the standard 20 amino acids however, shrinking the applicability domain of virtual sites. MkVsites is a set of python tools which provides a convenient way to obtain all parameters necessary to use virtual sites for virtually any molecules in a simulation. Required as input to MkVsites is the molecular topology of the molecule(s) in question, along with a specification of where to find the parent force field. As such, MkVsites can be a very valuable tool suite for anyone who is routinely using GROMACS for the simulation of molecular systems.     

Temperature‐shuffled parallel cascade selection molecular dynamics accelerates the structural transitions of proteins

Parallel cascade selection molecular dynamics (PaCS‐MD) is an enhanced conformational sampling method for searching structural transition pathways from a given reactant to a product. Recently, a temperature‐aided PaCS‐MD (Vinod et al., Eur. Biophys. J. 2016, 45, 463) has been proposed as its extension, in which the temperatures were introduced as additional parameters in conformational resampling, whereas the temperature is fixed in the original PaCS‐MD. In the present study, temperature‐shuffled PaCS‐MD is proposed as a further extension of temperature‐aided PaCS‐MD in which the temperatures are shuffled among different replicas at the beginning of each cycle of conformational resampling. To evaluate their conformational sampling efficiencies, the original, temperature‐aided, and temperature‐shuffled PaCS‐MD were applied to a protein‐folding process of Trp‐cage, and their minimum computational costs to identify the native state were addressed. Through the evaluation, it was confirmed that temperature‐shuffled PaCS‐MD remarkably accelerated the protein‐folding process of Trp‐cage compared with the other methods. © 2017 Wiley Periodicals, Inc.     

Essential dynamics for the study of microstructures in liquids

Essential Dynamics (ED) is a powerful tool for analyzing molecular dynamics (MD) simulations and it is widely adopted for conformational analysis of large molecular systems such as, for example, proteins and nucleic acids. In this study, we extend the use of ED to the study of clusters of arbitrary size constituted by weakly interacting particles, for example, atomic clusters and supramolecular systems. The key feature of the method we present is the identification of the relevant atomic‐molecular clusters to be analyzed by ED for extracting the information of interest. The application of this computational approach allows a straightforward and unbiased conformational study of the local microstructures in liquids, as emerged from semiclassical MD simulations. The good performance of the method is demonstrated by calculating typical observables of liquid water, that is, NMR, NEXAFS O1s, and IR spectra, known to be rather sensitive both to the presence and to the conformational features of hydrogen‐bonded clusters. © 2014 Wiley Periodicals, Inc.     

Advances in Enhanced Sampling Molecular Dynamics Simulations for Biomolecules

Molecular dynamics simulation has emerged as a powerful computational tool for studying biomolecules as it can provide atomic insights into the conformational transitions involved in biological functions. However, when applied to complex biological macromolecules, the conformational sampling ability of conventional molecular dynamics is limited by the rugged free energy landscapes, leading to inherent timescale gaps between molecular dynamics simulations and real biological processes. To address this issue, several advanced enhanced sampling methods have been proposed to improve the sampling efficiency in molecular dynamics. In this review, the theoretical basis, practical applications, and recent improvements of both constraint and unconstrained enhanced sampling methods are summarized. Furthermore, the combined utilizations of different enhanced sampling methods that take advantage of both approaches are also briefly discussed.     

Molecular dynamics simulation study of the structural features and inclusion capacities of cucurbit[6]uril derivatives in aqueous solutions

Molecular dynamics (MD) simulations were performed for cucurbit[6]uril (CB6) methyl and cyclohexyl derivatives in aqueous solutions. Furthermore, MD simulations have been conducted to study the inclusion complexes between each CB6 derivative with α,ω-pentane diammonium ion (NH₃⁺(CH₂)₅NH₃⁺) to estimate the binding free energies, the complex geometries and the intermolecular forces responsible for complex formation. Results show a complete inclusion of the guest molecule in the cavity of the host for all complexes. Results also indicate that the guest dynamics inside the cavity of the substituted host is similar to that for the unsubstituted host. This demonstrates that the molecular recognition of the host is not affected by the alkyl substitution at the equator. Also, there is an insignificant conformational change of the macrocyclic structure upon inclusion of the guest. Molecular mechanics/Poisson Boltzmann surface area method was used to estimate the binding free energy of each complex. Results indicate that host–guest electrostatic interactions make the largest contribution to the complex binding free energy. Moreover, van der Waals interactions add significantly to the complex stability. The guest molecules show more or less similar binding free energies with the substituted CB6 that exhibits slightly more negative values than unsubstituted CB6 which is proved also by umbrella sampling.     

Structural dissimilarity sampling with dynamically self‐guiding selection

Structural dissimilarity sampling (SDS) has been proposed as an enhanced conformational sampling method for reproducing the structural transitions of a given protein. SDS consists of cycles of two steps: (1) Selections of initial structures with structural dissimilarities by referring to a measure. (2) Conformational resampling by restarting short‐time molecular dynamics (MD) simulations from the initial structures. In the present study, an efficient measure is proposed as a dynamically self‐guiding selection to accelerate the structural transitions from a reactant state to a product state as an extension to the original SDS. In the extended SDS, the inner product (IP ) between the reactant and the snapshots generated by short‐time MD simulations are evaluated and ranked according to the IP s at every cycle. Then, the snapshots with low IP s are selected as initial structures for the short‐time MD simulations. This scheme enables one to choose dissimilar and distant initial structures from the reactant, and thus the initial structures dynamically head towards the product, promoting structural transitions from the reactant. To confirm the conformational sampling efficiency, the extended SDS was applied to maltodextrin binding protein (MBP), and we successfully reproduced the structural transition from the open to closed states with submicrosecond‐order simulation times. However, a conventional long‐time MD simulation failed to reproduce the same structural transition. We also compared the performance with that obtained by the ordinary SDS and other sampling techniques that have been developed by us to characterize the possible utility of the extended SDS for actual applications. © 2017 Wiley Periodicals, Inc.     

Local conformational dynamics regulating transport properties of a Cl−/H+ antiporter

ClC-ec1 is a Cl⁻/H⁺ antiporter that exchanges Cl⁻ and H⁺ ions across the membrane. Experiments have demonstrated that several mutations, including I109F, decrease the Cl⁻ and H⁺ transport rates by an order of magnitude. Using reactive molecular dynamics simulations of explicit proton transport across the central region in the I109F mutant, a two-dimensional free energy profile has been constructed that is consistent with the experimental transport rates. The importance of a phenylalanine gate formed by F109 and F357 and its influence on hydration connectivity through the central proton transport pathway is revealed. This work demonstrates how seemingly subtle changes in local conformational dynamics can dictate hydration changes and thus transport properties. © 2019 Wiley Periodicals, Inc.     

Systematic and statistical error in histogram-based free energy calculations

A common technique for the numerical calculation of free energies involves estimation of the probability density along a given coordinate from a set of configurations generated via simulation. The process requires discretization of one or more reaction coordinates to generate a histogram from which the continuous probability density is inferred. We show that the finite size of the intervals used to construct the histogram leads to quantifiable systematic error. The width of these intervals also determines the statistical error in the free energy, and the choice of the appropriate interval is therefore driven by the need to balance the two sources of error. We present a method for the construction of the optimal histogram for a given system, and show that the use of this technique requires little additional computational expense. We demonstrate the efficacy of the technique for a model system, and discuss how the principles governing the choice of discretization interval could be used to improve extended sampling techniques.     

The Permeation Mechanism of Cisplatin Through a Dioleoylphosphocholine Bilayer**

The investigation of the intermolecular interactions between platinum-based anticancer drugs and lipid bilayers is of special relevance to unveil the mechanisms involved in different steps of the anticancer mode of action of these drugs. We have simulated the permeation of cisplatin through a model membrane composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine lipids by means of umbrella sampling classical molecular dynamics simulations. The initial physisorption of cisplatin into the polar region of the lipid membrane is controlled by long-range electrostatic interactions with the choline groups in a first step and, in a second step, by long-range electrostatic and hydrogen bond interactions with the phosphate groups. The second half of the permeation pathway, in which cisplatin diffuses through the nonpolar region of the bilayer, is characterized by the drop of the interactions with the polar heads and the rise of attractive interactions with the non-polar tails, which are dominated by van der Waals contributions. The permeation free-energy profile is explained by a complex balance between the drug/lipid interactions and the energy and entropy contributions associated with the dehydration of the drug along the permeation pathway and with the decrease and increase of the membrane ordering along the first and second half of the mechanism, respectively.