Literature DB >> 34687719

hdANM: a new comprehensive dynamics model for protein hinges.

Pranav M Khade1, Domenico Scaramozzino2, Ambuj Kumar1, Giuseppe Lacidogna2, Alberto Carpinteri2, Robert L Jernigan3.   

Abstract

Hinge motions are essential for many protein functions, and their dynamics are important to understand underlying biological mechanisms. The ways that these motions are represented by various computational methods differ significantly. By focusing on a specific class of motion, we have developed a new hinge-domain anisotropic network model (hdANM) that is based on the prior identification of flexible hinges and rigid domains in the protein structure and the subsequent generation of global hinge motions. This yields a set of motions in which the relative translations and rotations of the rigid domains are modulated and controlled by the deformation of the flexible hinges, leading to a more restricted, specific view of these motions. hdANM is the first model, to our knowledge, that combines information about protein hinges and domains to model the characteristic hinge motions of a protein. The motions predicted with this new elastic network model provide important conceptual advantages for understanding the underlying biological mechanisms. As a matter of fact, the generated hinge movements are found to resemble the expected mechanisms required for the biological functions of diverse proteins. Another advantage of this model is that the domain-level coarse graining makes it significantly more computationally efficient, enabling the generation of hinge motions within even the largest molecular assemblies, such as those from cryo-electron microscopy. hdANM is also comprehensive as it can perform in the same way as the well-known protein dynamics models (anisotropic network model, rotations-translations of blocks, and nonlinear rigid block normal mode analysis), depending on the definition of flexible and rigid parts in the protein structure and on whether the motions are extrapolated in a linear or nonlinear fashion. Furthermore, our results indicate that hdANM produces more realistic motions as compared to the anisotropic network model. hdANM is an open-source software, freely available, and hosted on a user-friendly website.
Copyright © 2021 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2021        PMID: 34687719      PMCID: PMC8633836          DOI: 10.1016/j.bpj.2021.10.017

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  42 in total

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Journal:  Biophys J       Date:  2007-05-04       Impact factor: 4.033

4.  Protein elastic network models and the ranges of cooperativity.

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Authors:  R K Singhal; R Prasad; S H Wilson
Journal:  J Biol Chem       Date:  1995-01-13       Impact factor: 5.157

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Authors:  William A Beard; Samuel H Wilson
Journal:  Biochemistry       Date:  2014-04-23       Impact factor: 3.162

9.  Drug-resistant HIV-1 protease regains functional dynamics through cleavage site coevolution.

Authors:  Nevra Özer; Ayşegül Özen; Celia A Schiffer; Türkan Haliloğlu
Journal:  Evol Appl       Date:  2015-01-11       Impact factor: 5.183

10.  Computational prediction of hinge axes in proteins.

Authors:  Rittika Shamsuddin; Milka Doktorova; Sheila Jaswal; Audrey Lee-St John; Kathryn McMenimen
Journal:  BMC Bioinformatics       Date:  2014-07-14       Impact factor: 3.169

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