计算机科学
模板
对接(动物)
Web服务器
蛋白质结构预测
金属
网站
生物系统
数据挖掘
化学
生物信息学
蛋白质结构
互联网
生物
万维网
程序设计语言
生物化学
医学
护理部
有机化学
作者
Chih‐Hao Lu,Chih-Chieh Chen,Chin‐Sheng Yu,Yen‐Yi Liu,Jiajun Liu,Sung‐Tai Wei,Yu‐Feng Lin
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2022-07-29
卷期号:38 (18): 4428-4429
被引量:82
标识
DOI:10.1093/bioinformatics/btac534
摘要
Abstract Motivation MIB2 (metal ion-binding) attempts to overcome the limitation of structure-based prediction approaches, with many proteins lacking a solved structure. MIB2 also offers more accurate prediction performance and more metal ion types. Results MIB2 utilizes both the (PS)2 method and the AlphaFold Protein Structure Database to acquire predicted structures to perform metal ion docking and predict binding residues. MIB2 offers marked improvements over MIB by collecting more MIB residue templates and using the metal ion type-specific scoring function. It offers a total of 18 types of metal ions for binding site predictions. Availability and implementation Freely available on the web at http://bioinfo.cmu.edu.tw/MIB2/. Supplementary information Supplementary data are available at Bioinformatics online.
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