期刊
BIOINFORMATICS
卷 34, 期 21, 页码 3666-3674出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bty374
关键词
-
类别
资金
- Polish Ministry of Science and Higher Education [POIG. 02.03.00-00-003/09-00, IP2010 037470]
Motivation: Structure based ligand discovery is one of the most successful approaches for augmenting the drug discovery process. Currently, there is a notable shift towards machine learning (ML) methodologies to aid such procedures. Deep learning has recently gained considerable attention as it allows the model to 'learn' to extract features that are relevant for the task at hand. Results: We have developed a novel deep neural network estimating the binding affinity of ligand-receptor complexes. The complex is represented with a 3D grid, and the model utilizes a 3D convolution to produce a feature map of this representation, treating the atoms of both proteins and ligands in the same manner. Our network was tested on the CASF-2013 'scoring power' benchmark and Astex Diverse Set and outperformed classical scoring functions.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据