Literature DB >> 31950981

Structural dynamics and allostery of Rab proteins: strategies for drug discovery and design.

Ammu Prasanna Kumar1,2, Chandra S Verma3,4,5, Suryani Lukman1.   

Abstract

Rab proteins represent the largest family of the Rab superfamily guanosine triphosphatase (GTPase). Aberrant human Rab proteins are associated with multiple diseases, including cancers and neurological disorders. Rab subfamily members display subtle conformational variations that render specificity in their physiological functions and can be targeted for subfamily-specific drug design. However, drug discovery efforts have not focused much on targeting Rab allosteric non-nucleotide binding sites which are subjected to less evolutionary pressures to be conserved, hence are likely to offer subfamily specificity and may be less prone to undesirable off-target interactions and side effects. To discover druggable allosteric binding sites, Rab structural dynamics need to be first incorporated using multiple experimentally and computationally obtained structures. The high-dimensional structural data may necessitate feature extraction methods to identify manageable representative structures for subsequent analyses. We have detailed state-of-the-art computational methods to (i) identify binding sites using data on sequence, shape, energy, etc., (ii) determine the allosteric nature of these binding sites based on structural ensembles, residue networks and correlated motions and (iii) identify small molecule binders through structure- and ligand-based virtual screening. To benefit future studies for targeting Rab allosteric sites, we herein detail a refined workflow comprising multiple available computational methods, which have been successfully used alone or in combinations. This workflow is also applicable for drug discovery efforts targeting other medically important proteins. Depending on the structural dynamics of proteins of interest, researchers can select suitable strategies for allosteric drug discovery and design, from the resources of computational methods and tools enlisted in the workflow.
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  allostery; conformational change; drug discovery; machine learning; protein dynamics; structural bioinformatics

Year:  2021        PMID: 31950981     DOI: 10.1093/bib/bbz161

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  3 in total

Review 1.  Therapeutic Targeting of Rab GTPases: Relevance for Alzheimer's Disease.

Authors:  Kate L Jordan; David J Koss; Tiago F Outeiro; Flaviano Giorgini
Journal:  Biomedicines       Date:  2022-05-16

2.  Active and Inactive Cdc42 Differ in Their Insert Region Conformational Dynamics.

Authors:  Nurit Haspel; Hyunbum Jang; Ruth Nussinov
Journal:  Biophys J       Date:  2020-12-19       Impact factor: 4.033

3.  The properties of human disease mutations at protein interfaces.

Authors:  Benjamin J Livesey; Joseph A Marsh
Journal:  PLoS Comput Biol       Date:  2022-02-04       Impact factor: 4.475

  3 in total

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