cover of episode M-Ionic: Prediction of metal ion binding sites from sequence using residue embeddings

M-Ionic: Prediction of metal ion binding sites from sequence using residue embeddings

2023/4/6
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PaperPlayer biorxiv bioinformatics

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Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.04.06.535847v1?rss=1

Authors: Shenoy, A., Yogesh Kalakoti, Y., Sundar, D., Elofsson, A.

Abstract: Understanding metal-protein interaction can provide structural and functional insights into cellular processes. As the number of protein sequences increases, developing fast yet precise computational approaches to predict and annotate metal binding sites becomes imperative. Here, we have developed M-Ionic, a sequence-based method to predict which metals a protein binds and the binding residues. Since the predictions use only residue embeddings from a pre-trained protein language model, quick predictions can be made for the ten most frequent metal ions (Ca2+, Co2+, Cu2+, Mg2+, Mn2+, Po43-, So42-, Zn2+, Fe2+, Fe3+).

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