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+).
Copy rights belong to original authors. Visit the link for more info
Podcast created by Paper Player, LLC