The role of water in host-guest interaction.
The role of water in host-guest interaction.
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DOI：
10.1038/s41467-020-20310-0
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发表时间：
2021-01-04
影响因子：
16.6
通讯作者：
Parrinello M
中科院分区：
文献类型：
--
作者：
Rizzi V;Bonati L;Ansari N;Parrinello M
原子计算机模拟的主要应用之一是计算配体结合自由能。这些计算的准确性取决于力场的质量和构型抽样的彻底性。由于在自由能环境中经常出现动力学瓶颈，采样是模拟中的一个障碍。通常，这一困难可以通过改进的抽样技术来规避。通常，这些技术依赖于引入适当的集体变量，这些变量旨在捕获系统的自由度。在配基结合中，水一直被认为起着关键作用，但其复杂的行为被证明很难完全捕捉到。在本文中，我们将机器学习和物理直觉相结合，构建了一个非局部的、高效的描述水的集合变量。我们使用它来研究SAMPL5挑战中的一组主机-客户系统。我们得到了高精度的结合自由能，与实验符合得很好。然后对水在结合过程中的作用进行了较为详细的分析。预测水在宿主-配体结合中的作用的计算方法引起了人们的极大关注。在这里，作者使用元动力学增强的采样方法和机器学习来计算SAMPL5挑战中主客体系统的结合能，并提供了水结构变化的细节。
One of the main applications of atomistic computer simulations is the calculation of ligand binding free energies. The accuracy of these calculations depends on the force field quality and on the thoroughness of configuration sampling. Sampling is an obstacle in simulations due to the frequent appearance of kinetic bottlenecks in the free energy landscape. Very often this difficulty is circumvented by enhanced sampling techniques. Typically, these techniques depend on the introduction of appropriate collective variables that are meant to capture the system’s degrees of freedom. In ligand binding, water has long been known to play a key role, but its complex behaviour has proven difficult to fully capture. In this paper we combine machine learning with physical intuition to build a non-local and highly efficient water-describing collective variable. We use it to study a set of host-guest systems from the SAMPL5 challenge. We obtain highly accurate binding free energies and good agreement with experiments. The role of water during the binding process is then analysed in some detail. Computational approaches to predict water’s role in host-ligand binding attract a great deal of attention. Here the authors use a metadynamics enhanced sampling method and machine learning to compute binding energies for host-guest systems from the SAMPL5 challenge and provide details of water structural changes.
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影响因子：
15
作者：
Abel, Robert;Young, Tom;Friesner, Richard A.
通讯作者：
Friesner, Richard A.
影响因子：
5.5
作者：
Brotzakis, Z. Faidon;Limongelli, Vittorio;Parrinello, Michele
通讯作者：
Parrinello, Michele
影响因子：
4.4
作者：
Horn, HW;Swope, WC;Head-Gordon, T
通讯作者：
Head-Gordon, T
影响因子：
4.4
作者：
JORGENSEN, WL;CHANDRASEKHAR, J;KLEIN, ML
通讯作者：
KLEIN, ML
DOI：
10.1073/pnas.1112181108
发表时间：
2012-01-31
影响因子：
11.1
作者：
Limongelli, Vittorio;Marinelli, Luciana;Parrinello, Michele
通讯作者：
Parrinello, Michele