Literature DB >> 29253082

Comprehensive review and empirical analysis of hallmarks of DNA-, RNA- and protein-binding residues in protein chains.

Jian Zhang, Zhiqiang Ma, Lukasz Kurgan.   

Abstract

Proteins interact with a variety of molecules including proteins and nucleic acids. We review a comprehensive collection of over 50 studies that analyze and/or predict these interactions. While majority of these studies address either solely protein-DNA or protein-RNA binding, only a few have a wider scope that covers both protein-protein and protein-nucleic acid binding. Our analysis reveals that binding residues are typically characterized with three hallmarks: relative solvent accessibility (RSA), evolutionary conservation and propensity of amino acids (AAs) for binding. Motivated by drawbacks of the prior studies, we perform a large-scale analysis to quantify and contrast the three hallmarks for residues that bind DNA-, RNA-, protein- and (for the first time) multi-ligand-binding residues that interact with DNA and proteins, and with RNA and proteins. Results generated on a well-annotated data set of over 23 000 proteins show that conservation of binding residues is higher for nucleic acid- than protein-binding residues. Multi-ligand-binding residues are more conserved and have higher RSA than single-ligand-binding residues. We empirically show that each hallmark discriminates between binding and nonbinding residues, even predicted RSA, and that combining them improves discriminatory power for each of the five types of interactions. Linear scoring functions that combine these hallmarks offer good predictive performance of residue-level propensity for binding and provide intuitive interpretation of predictions. Better understanding of these residue-level interactions will facilitate development of methods that accurately predict binding in the exponentially growing databases of protein sequences.
© The Author(s) 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  DNA-binding residues; RNA-binding residues; protein–DNA interactions; protein–RNA interactions; protein–nucleic acid interactions; protein–protein interactions

Mesh:

Substances:

Year:  2019        PMID: 29253082     DOI: 10.1093/bib/bbx168

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  22 in total

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Journal:  Bioinformatics       Date:  2020-02-15       Impact factor: 6.937

2.  Dissecting and predicting different types of binding sites in nucleic acids based on structural information.

Authors:  Zheng Jiang; Si-Rui Xiao; Rong Liu
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

Review 3.  How RNA-Binding Proteins Interact with RNA: Molecules and Mechanisms.

Authors:  Meredith Corley; Margaret C Burns; Gene W Yeo
Journal:  Mol Cell       Date:  2020-04-02       Impact factor: 17.970

4.  Deep Learning for Protein-Protein Interaction Site Prediction.

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5.  dSPRINT: predicting DNA, RNA, ion, peptide and small molecule interaction sites within protein domains.

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Journal:  Nucleic Acids Res       Date:  2021-07-21       Impact factor: 16.971

6.  Characteristics of interactions at protein segments without non-local intramolecular contacts in the Protein Data Bank.

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Journal:  PLoS One       Date:  2018-12-11       Impact factor: 3.240

7.  IDP⁻CRF: Intrinsically Disordered Protein/Region Identification Based on Conditional Random Fields.

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Journal:  Int J Mol Sci       Date:  2018-08-22       Impact factor: 5.923

8.  PSIONplusm Server for Accurate Multi-Label Prediction of Ion Channels and Their Types.

Authors:  Jianzhao Gao; Hong Wei; Alberto Cano; Lukasz Kurgan
Journal:  Biomolecules       Date:  2020-06-07

9.  High-Throughput Identification of Mammalian Secreted Proteins Using Species-Specific Scheme and Application to Human Proteome.

Authors:  Jian Zhang; Haiting Chai; Song Guo; Huaping Guo; Yanling Li
Journal:  Molecules       Date:  2018-06-14       Impact factor: 4.411

10.  A Tale of Loops and Tails: The Role of Intrinsically Disordered Protein Regions in R-Loop Recognition and Phase Separation.

Authors:  Leonardo G Dettori; Diego Torrejon; Arijita Chakraborty; Arijit Dutta; Mohamed Mohamed; Csaba Papp; Vladimir A Kuznetsov; Patrick Sung; Wenyi Feng; Alaji Bah
Journal:  Front Mol Biosci       Date:  2021-06-10
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