Development and evaluation of a deep learning model for protein–ligand binding affinity prediction
Author:
Affiliation:
1. Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
2. Department of Systems Biology, Institute of Experimental Plant Biology and Biotechnology, University of Warsaw, Warsaw, Poland
Funder
Polish Ministry of Science and Higher Education
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Link
http://academic.oup.com/bioinformatics/article-pdf/34/21/3666/26147031/bty374.pdf
Reference50 articles.
1. Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning;Alipanahi;Nat. Biotechnol,2015
2. Deep learning for computational biology;Angermueller;Mol. Syst. Biol,2016
3. Structure-based virtual screening approaches in kinase-directed drug discovery;Bajusz;Curr. Top. Med. Chem,2017
4. A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking;Ballester;Bioinformatics,2010
Cited by 347 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. SQM2.20: Semiempirical quantum-mechanical scoring function yields DFT-quality protein–ligand binding affinity predictions in minutes;Nature Communications;2024-02-06
2. Advances in machine-learning approaches to RNA-targeted drug design;Artificial Intelligence Chemistry;2024-02
3. Genetic Algorithm-Based Receptor Ligand: A Genetic Algorithm-Guided Generative Model to Boost the Novelty and Drug-Likeness of Molecules in a Sampling Chemical Space;Journal of Chemical Information and Modeling;2024-02-01
4. Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives;Journal of Chemical Information and Modeling;2024-01-31
5. Accurate Prediction of Protein-Ligand Interactions by Combining Physical Energy Functions and Graph-Neural Networks;2024-01-25
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3