Databases of ligand-binding pockets and protein-ligand interactions

被引:6
|
作者
Carpenter, Kristy A. [1 ]
Altman, Russ B. [1 ,2 ,3 ,4 ]
机构
[1] Stanford Univ, Dept Biomed Data Sci, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Bioengn, Stanford, CA 94305 USA
[3] Stanford Univ, Dept Genet, Stanford, CA 94305 USA
[4] Stanford Univ, Dept Med, Stanford, CA 94305 USA
关键词
Binding sites; Protein-ligand interaction; Pocket detection; Databases; Protein structure; Structural bioinformatics; INHIBITOR STARTING POINTS; MACHINE LEARNING APPROACH; DRUGGABILITY PREDICTION; IMPORTANT RESIDUES; SITE PREDICTION; FOLD SPACE; HOT-SPOTS; MOLECULES; TARGETS; IDENTIFICATION;
D O I
10.1016/j.csbj.2024.03.015
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket -finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.
引用
收藏
页码:1320 / 1338
页数:19
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