Literature DB >> 23776011

A compound-based computational approach for the accurate determination of hot spots.

Lincong Wang1, Yaqin Hou, Haihua Quan, Weiwei Xu, Yongli Bao, Yuxin Li, Yuan Fu, Shuxue Zou.   

Abstract

A plethora of both experimental and computational methods have been proposed in the past 20 years for the identification of hot spots at a protein-protein interface. The experimental determination of a protein-protein complex followed by alanine scanning mutagenesis, though able to determine hot spots with much precision, is expensive and has no guarantee of success while the accuracy of the current computational methods for hot-spot identification remains low. Here, we present a novel structure-based computational approach that accurately determines hot spots through docking into a set of proteins homologous to only one of the two interacting partners of a compound capable of disrupting the protein-protein interaction (PPI). This approach has been applied to identify the hot spots of human activin receptor type II (ActRII) critical for its binding toward Cripto-I. The subsequent experimental confirmation of the computationally identified hot spots portends a potentially accurate method for hot-spot determination in silico given a compound capable of disrupting the PPI in question. The hot spots of human ActRII first reported here may well become the focal points for the design of small molecule drugs that target the PPI. The determination of their interface may have significant biological implications in that it suggests that Cripto-I plays an important role in both activin and nodal signal pathways.
© 2013 The Protein Society.

Entities:  

Keywords:  Cripto-I; activin receptor; activin signal pathway and nodal signal pathway; hot spot; hot-spot prediction; protein-ligand docking; protein-protein docking; protein-protein interaction; scoring function

Mesh:

Substances:

Year:  2013        PMID: 23776011      PMCID: PMC3832042          DOI: 10.1002/pro.2296

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  39 in total

1.  Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations.

Authors:  Raphael Guerois; Jens Erik Nielsen; Luis Serrano
Journal:  J Mol Biol       Date:  2002-07-05       Impact factor: 5.469

2.  ZDOCK: an initial-stage protein-docking algorithm.

Authors:  Rong Chen; Li Li; Zhiping Weng
Journal:  Proteins       Date:  2003-07-01

3.  Development and testing of a general amber force field.

Authors:  Junmei Wang; Romain M Wolf; James W Caldwell; Peter A Kollman; David A Case
Journal:  J Comput Chem       Date:  2004-07-15       Impact factor: 3.376

4.  Context-based identification of protein-protein interfaces and "hot-spot" residues.

Authors:  Tim Geppert; Benjamin Hoy; Silja Wessler; Gisbert Schneider
Journal:  Chem Biol       Date:  2011-03-25

5.  Cripto forms a complex with activin and type II activin receptors and can block activin signaling.

Authors:  Peter C Gray; Craig A Harrison; Wylie Vale
Journal:  Proc Natl Acad Sci U S A       Date:  2003-04-07       Impact factor: 11.205

6.  Solution structure of mouse Cripto CFC domain and its inactive variant Trp107Ala.

Authors:  Luisa Calvanese; Angela Saporito; Daniela Marasco; Gabriella D'Auria; Gabriella Minchiotti; Carlo Pedone; Livio Paolillo; Lucia Falcigno; Menotti Ruvo
Journal:  J Med Chem       Date:  2006-11-30       Impact factor: 7.446

7.  DrugScorePPI webserver: fast and accurate in silico alanine scanning for scoring protein-protein interactions.

Authors:  Dennis M Krüger; Holger Gohlke
Journal:  Nucleic Acids Res       Date:  2010-05-28       Impact factor: 16.971

8.  The overlap of small molecule and protein binding sites within families of protein structures.

Authors:  Fred P Davis; Andrej Sali
Journal:  PLoS Comput Biol       Date:  2010-02-05       Impact factor: 4.475

9.  HotRegion: a database of predicted hot spot clusters.

Authors:  Engin Cukuroglu; Attila Gursoy; Ozlem Keskin
Journal:  Nucleic Acids Res       Date:  2011-11-12       Impact factor: 16.971

Review 10.  Deciphering protein-protein interactions. Part II. Computational methods to predict protein and domain interaction partners.

Authors:  Benjamin A Shoemaker; Anna R Panchenko
Journal:  PLoS Comput Biol       Date:  2007-04-27       Impact factor: 4.475

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  3 in total

1.  Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application to Repurposing.

Authors:  E Sila Ozdemir; Farideh Halakou; Ruth Nussinov; Attila Gursoy; Ozlem Keskin
Journal:  Methods Mol Biol       Date:  2019

Review 2.  Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions.

Authors:  Maxence Delaunay; Tâp Ha-Duong
Journal:  Methods Mol Biol       Date:  2022

3.  Hot spot prediction in protein-protein interactions by an ensemble system.

Authors:  Quanya Liu; Peng Chen; Bing Wang; Jun Zhang; Jinyan Li
Journal:  BMC Syst Biol       Date:  2018-12-31
  3 in total

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