Long Time Scale Ensemble Methods in Molecular Dynamics: Ligand-Protein Interactions and Allostery in SARS-CoV-2 Targets.
Long Time Scale Ensemble Methods in Molecular Dynamics: Ligand-Protein Interactions and Allostery in SARS-CoV-2 Targets.
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DOI：
10.1021/acs.jctc.3c00020
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发表时间：
2023-06-13
影响因子：
5.5
通讯作者：
Coveney, Peter V.
中科院分区：
文献类型：
--
作者：
Bhati, Agastya P.;Hoti, Art;Potterton, Andrew;Bieniek, Mateusz K.;Coveney, Peter V.
我们进行了一系列的5个蛋白质配体系统，其中包含重要的SARS-CoV-2的目标，3-糜蛋白酶样蛋白酶（3CLPro），木瓜蛋白酶样蛋白酶，和腺苷核糖磷酸酶，长时间尺度和自适应采样的分子动力学模拟。通过对每个系统进行10或12次10 μs模拟，我们准确且可重复地确定配体结合位点，包括晶体学解析和其他方面，从而发现可用于药物发现的结合位点。我们还报告了由于在变构结合位点存在另一种配体而发生在3CLPro的主要结合位点的构象变化的稳健的、基于整体的观察，解释了负责其抑制作用的事件的潜在级联。使用我们的模拟，我们发现了一种新型的变构抑制机制，用于抑制已知仅在底物结合位点结合的配体。由于分子动力学轨迹的混沌性质，无论它们的持续时间，单个轨迹都不允许准确或可再现地阐明宏观期望值。在这个时间尺度上，我们前所未有地比较了这些10/12个10 μs轨迹的蛋白质-配体接触频率的统计分布，发现超过90%的轨迹具有显著不同的接触频率分布。此外，使用直接结合自由能计算协议，我们确定的配体结合自由能为每个确定的网站使用长时间尺度模拟。的自由能不同的0.77至7.26千卡/摩尔的各个轨迹取决于结合位点和系统。我们表明，虽然这是目前在长时间尺度上报道的标准方式，但单个模拟并不能产生可靠的自由能。为了获得统计上有意义和可重复的结果，独立轨迹的集合是必要的，以克服任意的不确定性。最后，我们比较了不同的自由能方法在这些体系中的应用，并讨论了它们的优缺点。我们的研究结果一般适用于所有基于分子动力学的应用，而不限于本研究中使用的自由能方法。
We subject a series of five protein–ligand systems which contain important SARS-CoV-2 targets, 3-chymotrypsin-like protease (3CLPro), papain-like protease, and adenosine ribose phosphatase, to long time scale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10 μs simulations for each system, we accurately and reproducibly determine ligand binding sites, both crystallographically resolved and otherwise, thereby discovering binding sites that can be exploited for drug discovery. We also report robust, ensemble-based observation of conformational changes that occur at the main binding site of 3CLPro due to the presence of another ligand at an allosteric binding site explaining the underlying cascade of events responsible for its inhibitory effect. Using our simulations, we have discovered a novel allosteric mechanism of inhibition for a ligand known to bind only at the substrate binding site. Due to the chaotic nature of molecular dynamics trajectories, regardless of their temporal duration individual trajectories do not allow for accurate or reproducible elucidation of macroscopic expectation values. Unprecedentedly at this time scale, we compare the statistical distribution of protein–ligand contact frequencies for these ten/twelve 10 μs trajectories and find that over 90% of trajectories have significantly different contact frequency distributions. Furthermore, using a direct binding free energy calculation protocol, we determine the ligand binding free energies for each of the identified sites using long time scale simulations. The free energies differ by 0.77 to 7.26 kcal/mol across individual trajectories depending on the binding site and the system. We show that, although this is the standard way such quantities are currently reported at long time scale, individual simulations do not yield reliable free energies. Ensembles of independent trajectories are necessary to overcome the aleatoric uncertainty in order to obtain statistically meaningful and reproducible results. Finally, we compare the application of different free energy methods to these systems and discuss their advantages and disadvantages. Our findings here are generally applicable to all molecular dynamics based applications and not confined to the free energy methods used in this study.
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