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. 2022 Sep 15;38(18):4428-4429.
doi: 10.1093/bioinformatics/btac534.

MIB2: metal ion-binding site prediction and modeling server

Chih-Hao Lu  1   2 , Chih-Chieh Chen  3 , Chin-Sheng Yu  4 , Yen-Yi Liu  5 , Jia-Jun Liu  1 , Sung-Tai Wei  6 , Yu-Feng Lin  7
Affiliations

MIB2: metal ion-binding site prediction and modeling server

Chih-Hao Lu et al. Bioinformatics. .

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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