Literature DB >> 25340971

Allosteric pathway identification through network analysis: from molecular dynamics simulations to interactive 2D and 3D graphs.

Ariane Allain1, Isaure Chauvot de Beauchêne, Florent Langenfeld, Yann Guarracino, Elodie Laine, Luba Tchertanov.   

Abstract

Allostery is a universal phenomenon that couples the information induced by a local perturbation (effector) in a protein to spatially distant regulated sites. Such an event can be described in terms of a large scale transmission of information (communication) through a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. To elaborate a rational description of allosteric coupling, we propose an original approach - MOdular NETwork Analysis (MONETA) - based on the analysis of inter-residue dynamical correlations to localize the propagation of both structural and dynamical effects of a perturbation throughout a protein structure. MONETA uses inter-residue cross-correlations and commute times computed from molecular dynamics simulations and a topological description of a protein to build a modular network representation composed of clusters of residues (dynamic segments) linked together by chains of residues (communication pathways). MONETA provides a brand new direct and simple visualization of protein allosteric communication. A GEPHI module implemented in the MONETA package allows the generation of 2D graphs of the communication network. An interactive PyMOL plugin permits drawing of the communication pathways between chosen protein fragments or residues on a 3D representation. MONETA is a powerful tool for on-the-fly display of communication networks in proteins. We applied MONETA for the analysis of communication pathways (i) between the main regulatory fragments of receptors tyrosine kinases (RTKs), KIT and CSF-1R, in the native and mutated states and (ii) in proteins STAT5 (STAT5a and STAT5b) in the phosphorylated and the unphosphorylated forms. The description of the physical support for allosteric coupling by MONETA allowed a comparison of the mechanisms of (a) constitutive activation induced by equivalent mutations in two RTKs and (b) allosteric regulation in the activated and non-activated STAT5 proteins. Our theoretical prediction based on results obtained with MONETA was validated for KIT by in vitro experiments. MONETA is a versatile analytical and visualization tool entirely devoted to the understanding of the functioning/malfunctioning of allosteric regulation in proteins - a crucial basis to guide the discovery of next-generation allosteric drugs.

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Year:  2014        PMID: 25340971     DOI: 10.1039/c4fd00024b

Source DB:  PubMed          Journal:  Faraday Discuss        ISSN: 1359-6640            Impact factor:   4.008


  16 in total

1.  Structural signatures of DRD4 mutants revealed using molecular dynamics simulations: Implications for drug targeting.

Authors:  Nidhi Jatana; Lipi Thukral; N Latha
Journal:  J Mol Model       Date:  2015-12-17       Impact factor: 1.810

2.  The PyInteraph Workflow for the Study of Interaction Networks From Protein Structural Ensembles.

Authors:  Matteo Lambrughi; Valentina Sora; Matteo Tiberti
Journal:  Methods Mol Biol       Date:  2021

Review 3.  Detecting Allosteric Networks Using Molecular Dynamics Simulation.

Authors:  S Bowerman; J Wereszczynski
Journal:  Methods Enzymol       Date:  2016-06-20       Impact factor: 1.600

4.  Decoding Structural Properties of a Partially Unfolded Protein Substrate: En Route to Chaperone Binding.

Authors:  Suhani Nagpal; Satyam Tiwari; Koyeli Mapa; Lipi Thukral
Journal:  PLoS Comput Biol       Date:  2015-09-22       Impact factor: 4.475

5.  Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics: strength in unity.

Authors:  Elena Papaleo
Journal:  Front Mol Biosci       Date:  2015-05-27

6.  How Intrinsic Molecular Dynamics Control Intramolecular Communication in Signal Transducers and Activators of Transcription Factor STAT5.

Authors:  Florent Langenfeld; Yann Guarracino; Michel Arock; Alain Trouvé; Luba Tchertanov
Journal:  PLoS One       Date:  2015-12-30       Impact factor: 3.240

7.  Differential effects of CSF-1R D802V and KIT D816V homologous mutations on receptor tertiary structure and allosteric communication.

Authors:  Priscila Da Silva Figueiredo Celestino Gomes; Nicolas Panel; Elodie Laine; Pedro Geraldo Pascutti; Eric Solary; Luba Tchertanov
Journal:  PLoS One       Date:  2014-05-14       Impact factor: 3.240

8.  Hotspot mutations in KIT receptor differentially modulate its allosterically coupled conformational dynamics: impact on activation and drug sensitivity.

Authors:  Isaure Chauvot de Beauchêne; Ariane Allain; Nicolas Panel; Elodie Laine; Alain Trouvé; Patrice Dubreuil; Luba Tchertanov
Journal:  PLoS Comput Biol       Date:  2014-07-31       Impact factor: 4.475

9.  Dissecting protein architecture with communication blocks and communicating segment pairs.

Authors:  Yasaman Karami; Elodie Laine; Alessandra Carbone
Journal:  BMC Bioinformatics       Date:  2016-01-20       Impact factor: 3.169

10.  WONKA: objective novel complex analysis for ensembles of protein-ligand structures.

Authors:  A R Bradley; I D Wall; F von Delft; D V S Green; C M Deane; B D Marsden
Journal:  J Comput Aided Mol Des       Date:  2015-09-19       Impact factor: 3.686

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