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MIB2: metal ion-binding site prediction and modeling server
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 th...
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Published in: | Bioinformatics 2022-09, Vol.38 (18), p.4428-4429 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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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ISSN: | 1367-4803 1460-2059 1367-4811 |
DOI: | 10.1093/bioinformatics/btac534 |