Literature DB >> 27399277

Perturbation Approaches for Exploring Protein Binding Site Flexibility to Predict Transient Binding Pockets.

Daria B Kokh1, Paul Czodrowski2, Friedrich Rippmann2, Rebecca C Wade1,3,4.   

Abstract

Simulations of the long-time scale motions of a ligand binding pocket in a protein may open up new perspectives for the design of compounds with steric or chemical properties differing from those of known binders. However, slow motions of proteins are difficult to access using standard molecular dynamics (MD) simulations and are thus usually neglected in computational drug design. Here, we introduce two nonequilibrium MD approaches to identify conformational changes of a binding site and detect transient pockets associated with these motions. The methods proposed are based on the rotamerically induced perturbation (RIP) MD approach, which employs perturbation of side-chain torsional motion for initiating large-scale protein movement. The first approach, Langevin-RIP (L-RIP), entails a series of short Langevin MD simulations, each starting with perturbation of one of the side-chains lining the binding site of interest. L-RIP provides extensive sampling of conformational changes of the binding site. In less than 1 ns of MD simulation with L-RIP, we observed distortions of the α-helix in the ATP binding site of HSP90 and flipping of the DFG loop in Src kinase. In the second approach, RIPlig, a perturbation is applied to a pseudoligand placed in different parts of a binding pocket, which enables flexible regions of the binding site to be identified in a small number of 10 ps MD simulations. The methods were evaluated for four test proteins displaying different types and degrees of binding site flexibility. Both methods reveal all transient pocket regions in less than a total of 10 ns of simulations, even though many of these regions remained closed in 100 ns conventional MD. The proposed methods provide computationally efficient tools to explore binding site flexibility and can aid in the functional characterization of protein pockets, and the identification of transient pockets for ligand design.

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Year:  2016        PMID: 27399277     DOI: 10.1021/acs.jctc.6b00101

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  7 in total

1.  POVME 3.0: Software for Mapping Binding Pocket Flexibility.

Authors:  Jeffrey R Wagner; Jesper Sørensen; Nathan Hensley; Celia Wong; Clare Zhu; Taylor Perison; Rommie E Amaro
Journal:  J Chem Theory Comput       Date:  2017-08-30       Impact factor: 6.006

Review 2.  Investigating Cryptic Binding Sites by Molecular Dynamics Simulations.

Authors:  Antonija Kuzmanic; Gregory R Bowman; Jordi Juarez-Jimenez; Julien Michel; Francesco L Gervasio
Journal:  Acc Chem Res       Date:  2020-03-05       Impact factor: 22.384

3.  Identification of Cryptic Binding Sites Using MixMD with Standard and Accelerated Molecular Dynamics.

Authors:  Richard D Smith; Heather A Carlson
Journal:  J Chem Inf Model       Date:  2021-02-18       Impact factor: 4.956

4.  Protein conformational flexibility modulates kinetics and thermodynamics of drug binding.

Authors:  M Amaral; D B Kokh; J Bomke; A Wegener; H P Buchstaller; H M Eggenweiler; P Matias; C Sirrenberg; R C Wade; M Frech
Journal:  Nat Commun       Date:  2017-12-22       Impact factor: 14.919

5.  Small-molecule modulators of TRMT2A decrease PolyQ aggregation and PolyQ-induced cell death.

Authors:  Michael A Margreiter; Monika Witzenberger; Yasmine Wasser; Elena Davydova; Robert Janowski; Jonas Metz; Pardes Habib; Sabri E M Sahnoun; Carina Sobisch; Benedetta Poma; Oscar Palomino-Hernandez; Mirko Wagner; Thomas Carell; N Jon Shah; Jörg B Schulz; Dierk Niessing; Aaron Voigt; Giulia Rossetti
Journal:  Comput Struct Biotechnol J       Date:  2021-12-28       Impact factor: 7.271

6.  TRAPP webserver: predicting protein binding site flexibility and detecting transient binding pockets.

Authors:  Antonia Stank; Daria B Kokh; Max Horn; Elena Sizikova; Rebecca Neil; Joanna Panecka; Stefan Richter; Rebecca C Wade
Journal:  Nucleic Acids Res       Date:  2017-07-03       Impact factor: 16.971

Review 7.  Computer-Aided Ligand Discovery for Estrogen Receptor Alpha.

Authors:  Divya Bafna; Fuqiang Ban; Paul S Rennie; Kriti Singh; Artem Cherkasov
Journal:  Int J Mol Sci       Date:  2020-06-12       Impact factor: 5.923

  7 in total

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