An ensemble 3D deep-learning model to predict protein metal-binding site-Reference-Cited by-同舟云学术

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An ensemble 3D deep-learning model to predict protein metal-binding site

Published:2022-09 Issue:9 Volume:3 Page:101046
ISSN:2666-3864
Container-title:Cell Reports Physical Science
language:en
Short-container-title:Cell Reports Physical Science

Author:

Mohamadi Ahmad,Cheng Tianfan,Jin Lijian,Wang Junwen,Sun Hongzhe,Koohi-Moghadam Mohamad

Funder

Research Grants Council, University Grants Committee

University of Hong Kong

Publisher

Elsevier BV

Subject

General Physics and Astronomy,General Energy,General Engineering,General Materials Science,General Chemistry

Reference35 articles.

1. Metalloproteins and metal sensing;Waldron;Nature,2009

2. Handbook of Metalloproteins;Messerschmidt,2001

3. Metals in proteins: correlation between the metal-ion type, coordination number and the amino-acid residues involved in the coordination;Dokmanić;Acta Crystallogr. D Biol. Crystallogr.,2008

4. Structure-oriented bioinformatic approach exploring histidine-rich clusters in proteins;Cun;Metallomics,2013

5. Histidine-rich proteins in prokaryotes: metal homeostasis and environmental habitat-related occurrence;Cheng;Metallomics,2013

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