DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space,Journal of Chemical Information and Modeling

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DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2022-11-29 , DOI: 10.1021/acs.jcim.2c00883
Rangsiman Ketkaew ₁ , Sandra Luber ₁

Affiliation

We present Deep learning for Collective Variables (DeepCV), a computer code that provides an efficient and customizable implementation of the deep autoencoder neural network (DAENN) algorithm that has been developed in our group for computing collective variables (CVs) and can be used with enhanced sampling methods to reconstruct free energy surfaces of chemical reactions. DeepCV can be used to conveniently calculate molecular features, train models, generate CVs, validate rare events from sampling, and analyze a trajectory for chemical reactions of interest. We use DeepCV in an example study of the conformational transition of cyclohexene, where metadynamics simulations are performed using DAENN-generated CVs. The results show that the adopted CVs give free energies in line with those obtained by previously developed CVs and experimental results. DeepCV is open-source software written in Python/C++ object-oriented languages, based on the TensorFlow framework and distributed free of charge for noncommercial purposes, which can be incorporated into general molecular dynamics software. DeepCV also comes with several additional tools, i.e., an application program interface (API), documentation, and tutorials.

中文翻译：

DeepCV：一种用于在扩展配置空间中盲目搜索集体变量的深度学习框架

我们介绍集体变量的深度学习(DeepCV)，一种计算机代码，可提供深度自动编码器神经网络 (DAENN) 算法的高效且可定制的实现，该算法已在我们小组中开发，用于计算集体变量 (CV)，并可与增强的采样方法一起使用以重建自由能化学反应的表面。DeepCV 可用于方便地计算分子特征、训练模型、生成 CV、验证采样中的罕见事件以及分析感兴趣的化学反应的轨迹。我们在环己烯构象转变的示例研究中使用 DeepCV，其中使用 DAENN 生成的 CV 执行元动力学模拟。结果表明，采用的 CV 提供的自由能与先前开发的 CV 和实验结果所获得的自由能一致。DeepCV 是用 Python/C++ 面向对象语言编写的开源软件，基于 TensorFlow 框架，为非商业目的免费分发，可以合并到通用的分子动力学软件中。DeepCV 还附带了几个附加工具，即应用程序接口 (API)、文档和教程。

更新日期：2022-11-29

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