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Machine-learning methods for ligand–protein molecular docking
Drug Discovery Today ( IF 6.5 ) Pub Date : 2021-09-21 , DOI: 10.1016/j.drudis.2021.09.007 Kevin Crampon 1 , Alexis Giorkallos 2 , Myrtille Deldossi 2 , Stéphanie Baud 3 , Luiz Angelo Steffenel 4
中文翻译:
配体-蛋白质分子对接的机器学习方法
更新日期:2021-09-21
Drug Discovery Today ( IF 6.5 ) Pub Date : 2021-09-21 , DOI: 10.1016/j.drudis.2021.09.007 Kevin Crampon 1 , Alexis Giorkallos 2 , Myrtille Deldossi 2 , Stéphanie Baud 3 , Luiz Angelo Steffenel 4
Affiliation
Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains use AI, including molecular simulation for drug discovery. In this review, we provide an overview of ligand–protein molecular docking and how machine learning (ML), especially deep learning (DL), a subset of ML, is transforming the field by tackling the associated challenges.
中文翻译:
配体-蛋白质分子对接的机器学习方法
人工智能 (AI) 通常被描述为一场新的工业革命。许多领域都使用人工智能,包括用于药物发现的分子模拟。在这篇综述中,我们概述了配体-蛋白质分子对接,以及机器学习 (ML),尤其是深度学习 (DL),它是 ML 的一个子集,如何通过应对相关挑战来改变该领域。