Literature DB >> 29605932

Protein-Protein Docking Using Evolutionary Information.

Aravindan Arun Nadaradjane1, Raphael Guerois2, Jessica Andreani3.   

Abstract

The structural modeling of protein complexes by docking simulations has been attracting increasing interest with the rise of proteomics and of the number of experimentally identified binary interactions. Structures of unbound partners, either modeled or experimentally determined, can be used as input to sample as extensively as possible all putative binding modes and single out the most plausible ones. At the scoring step, evolutionary information contained in the joint multiple sequence alignments of both partners can provide key insights to recognize correct interfaces. Here, we describe a computational protocol based on the InterEvDock web server to exploit coevolution constraints in protein-protein docking methods. We provide methodology guidelines to prepare the input protein structures and generate improved alignments. We also explain how to extract and use the information returned by the server through the analysis of two representative examples.

Keywords:  Bioinformatics; Coevolution; Complex interface; Evolutionary information; InterEvDock; InterEvolAlign; Protein docking; Protein interactions; Protein scoring; Protein structure

Mesh:

Substances:

Year:  2018        PMID: 29605932     DOI: 10.1007/978-1-4939-7759-8_28

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

1.  Performance and enhancement of the LZerD protein assembly pipeline in CAPRI 38-46.

Authors:  Charles Christoffer; Genki Terashi; Woong-Hee Shin; Tunde Aderinwale; Sai Raghavendra Maddhuri Venkata Subramaniya; Lenna Peterson; Jacob Verburgt; Daisuke Kihara
Journal:  Proteins       Date:  2019-11-25

2.  Protein docking model evaluation by 3D deep convolutional neural networks.

Authors:  Xiao Wang; Genki Terashi; Charles W Christoffer; Mengmeng Zhu; Daisuke Kihara
Journal:  Bioinformatics       Date:  2020-04-01       Impact factor: 6.937

3.  Coevolutive, evolutive and stochastic information in protein-protein interactions.

Authors:  Miguel Andrade; Camila Pontes; Werner Treptow
Journal:  Comput Struct Biotechnol J       Date:  2019-11-20       Impact factor: 7.271

4.  Protein Docking Model Evaluation by Graph Neural Networks.

Authors:  Xiao Wang; Sean T Flannery; Daisuke Kihara
Journal:  Front Mol Biosci       Date:  2021-05-25
  4 in total

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