Novel dynamic residue network analysis approaches to study allosteric modulation: SARS-CoV-2 Mpro and its evolutionary mutations as a case study
- Authors: Sheik Amamuddy, Olivier , Boateng, Rita A , Barozi, Victor , Nyamai, Dorothy W , Tastan Bishop, Özlem
- Date: 2021
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/476596 , vital:77940 , xlink:href="https://doi.org/10.1016/j.csbj.2021.11.016"
- Description: The rational search for allosteric modulators and the allosteric mechanisms of these modulators in the presence of mutations is a relatively unexplored field. Here, we established novel in silico approaches and applied them to SARS-CoV-2 main protease (Mpro) as a case study. First, we identified six potential allosteric modulators. Then, we focused on understanding the allosteric effects of these modulators on each of its protomers. We introduced a new combinatorial approach and dynamic residue network (DRN) analysis algorithms to examine patterns of change and conservation of critical nodes, according to five independent criteria of network centrality. We observed highly conserved network hubs for each averaged DRN metric on the basis of their existence in both protomers in the absence and presence of all ligands (persistent hubs). We also detected ligand specific signal changes. Using eigencentrality (EC) persistent hubs and ligand introduced hubs we identified a residue communication path connecting the allosteric binding site to the catalytic site. Finally, we examined the effects of the mutations on the behavior of the protein in the presence of selected potential allosteric modulators and investigated the ligand stability. One crucial outcome was to show that EC centrality hubs form an allosteric communication path between the allosteric ligand binding site to the active site going through the interface residues of domains I and II; and this path was either weakened or lost in the presence of some of the mutations. Overall, the results revealed crucial aspects that need to be considered in rational computational drug discovery.
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- Date Issued: 2021
Characterisation of plasmodial transketolases and identification of potential inhibitors: an in silico study
- Authors: Boateng, Rita A , Tastan Bishop, Özlem , Musyoka, Thommas M
- Date: 2020
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429372 , vital:72605 , xlink:href="https://doi.org/10.1186/s12936-020-03512-1"
- Description: Plasmodial transketolase (PTKT) enzyme is one of the novel pharmacological targets being explored as potential anti-malarial drug target due to its functional role and low sequence identity to the human enzyme. Despite this, features contributing to such have not been exploited for anti-malarial drug design. Additionally, there are no anti-malarial drugs targeting PTKTs whereas the broad activity of these inhibitors against PTKTs from other Plasmodium spp. is yet to be reported. This study characterises different PTKTs [Plasmodium falciparum (PfTKT), Plasmodium vivax (PvTKT), Plasmodium ovale (PoTKT), Plasmodium malariae (PmTKT) and Plasmodium knowlesi (PkTKT) and the human homolog (HsTKT)] to identify key sequence and structural based differences as well as the identification of selective potential inhibitors against PTKTs.
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- Date Issued: 2020
Determining the unbinding events and conserved motions associated with the pyrazinamide release due to resistance mutations of Mycobacterium tuberculosis pyrazinamidase:
- Authors: Sheik Amamuddy, Olivier , Musyoka, Thommas M , Boateng, Rita A , Zabo, Sophakama , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/148869 , vital:38781 , https://doi.org/10.1016/j.csbj.2020.05.0099
- Description: Pyrazinamide (PZA) is the only first-line antitubercular drug active against latent Mycobacterium tuberculosis (Mtb). It is activated to pyrazinoic acid by the pncA-encoded pyrazinamidase enzyme (PZase). Despite the emergence of PZA drug resistance, the underlying mechanisms of resistance remain unclear. This study investigated part of these mechanisms by modelling a PZA-bound wild type and 82 mutant PZase structures before applying molecular dynamics (MD) with an accurate Fe2+ cofactor coordination geometry.
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- Date Issued: 2020