Litcius/Paper detail

MIB2: metal ion-binding site prediction and modeling server

Chih‐Hao Lu, Chih-Chieh Chen, Chin‐Sheng Yu, Yen‐Yi Liu, Jiajun Liu, Sung‐Tai Wei, Yu‐Feng Lin

2022Bioinformatics145 citationsDOI

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.

Topics & Concepts

Computer scienceTemplateDocking (animal)MetalWeb siteWeb serverProtein structure predictionData miningBiological systemChemistryBioinformaticsProtein structureThe InternetBiologyWorld Wide WebProgramming languageBiochemistryOrganic chemistryMedicineNursingProtein Structure and DynamicsBacterial Genetics and BiotechnologyMachine Learning in Bioinformatics