Literature DB >> 34787783

Protein-Protein Docking: Past, Present, and Future.

Sharon Sunny1, P B Jayaraj2.   

Abstract

The biological significance of proteins attracted the scientific community in exploring their characteristics. The studies shed light on the interaction patterns and functions of proteins in a living body. Due to their practical difficulties, reliable experimental techniques pave the way for introducing computational methods in the interaction prediction. Automated methods reduced the difficulties but could not yet replace experimental studies as the field is still evolving. Interaction prediction problem being critical needs highly accurate results, but none of the existing methods could offer reliable performance that can parallel with experimental results yet. This article aims to assess the existing computational docking algorithms, their challenges, and future scope. Blind docking techniques are quite helpful when no information other than the individual structures are available. As more and more complex structures are being added to different databases, information-driven approaches can be a good alternative. Artificial intelligence, ruling over the major fields, is expected to take over this domain very shortly.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Artificial intelligence; Deep learning; Geometric algorithms; Nature-inspired algorithms; Protein–protein docking; Searching and scoring

Mesh:

Substances:

Year:  2021        PMID: 34787783     DOI: 10.1007/s10930-021-10031-8

Source DB:  PubMed          Journal:  Protein J        ISSN: 1572-3887            Impact factor:   2.371


  92 in total

1.  Protein-protein docking with a reduced protein model accounting for side-chain flexibility.

Authors:  Martin Zacharias
Journal:  Protein Sci       Date:  2003-06       Impact factor: 6.725

2.  Stereochemistry of polypeptide chain configurations.

Authors:  G N RAMACHANDRAN; C RAMAKRISHNAN; V SASISEKHARAN
Journal:  J Mol Biol       Date:  1963-07       Impact factor: 5.469

Review 3.  Protein modeling and structure prediction with a reduced representation.

Authors:  Andrzej Kolinski
Journal:  Acta Biochim Pol       Date:  2004       Impact factor: 2.149

4.  EROS-DOCK: protein-protein docking using exhaustive branch-and-bound rotational search.

Authors:  Maria Elisa Ruiz Echartea; Isaure Chauvot de Beauchêne; David W Ritchie
Journal:  Bioinformatics       Date:  2019-12-01       Impact factor: 6.937

5.  Atomic-resolution protein structure determination by cryo-EM.

Authors:  Ka Man Yip; Niels Fischer; Elham Paknia; Ashwin Chari; Holger Stark
Journal:  Nature       Date:  2020-10-21       Impact factor: 49.962

6.  CABS-fold: Server for the de novo and consensus-based prediction of protein structure.

Authors:  Maciej Blaszczyk; Michal Jamroz; Sebastian Kmiecik; Andrzej Kolinski
Journal:  Nucleic Acids Res       Date:  2013-06-08       Impact factor: 16.971

Review 7.  Advances to tackle backbone flexibility in protein docking.

Authors:  Ameya Harmalkar; Jeffrey J Gray
Journal:  Curr Opin Struct Biol       Date:  2020-12-23       Impact factor: 7.786

8.  The Contribution of Missense Mutations in Core and Rim Residues of Protein-Protein Interfaces to Human Disease.

Authors:  Alessia David; Michael J E Sternberg
Journal:  J Mol Biol       Date:  2015-07-11       Impact factor: 5.469

9.  A Pan-Cancer Catalogue of Cancer Driver Protein Interaction Interfaces.

Authors:  Eduard Porta-Pardo; Luz Garcia-Alonso; Thomas Hrabe; Joaquin Dopazo; Adam Godzik
Journal:  PLoS Comput Biol       Date:  2015-10-20       Impact factor: 4.475

10.  Less Is More: Coarse-Grained Integrative Modeling of Large Biomolecular Assemblies with HADDOCK.

Authors:  Jorge Roel-Touris; Charleen G Don; Rodrigo V Honorato; João P G L M Rodrigues; Alexandre M J J Bonvin
Journal:  J Chem Theory Comput       Date:  2019-10-10       Impact factor: 6.006

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  2 in total

Review 1.  Protein Function Analysis through Machine Learning.

Authors:  Chris Avery; John Patterson; Tyler Grear; Theodore Frater; Donald J Jacobs
Journal:  Biomolecules       Date:  2022-09-06

2.  Protein-Protein Interaction Prediction for Targeted Protein Degradation.

Authors:  Oliver Orasch; Noah Weber; Michael Müller; Amir Amanzadi; Chiara Gasbarri; Christopher Trummer
Journal:  Int J Mol Sci       Date:  2022-06-24       Impact factor: 6.208

  2 in total

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