Impact of early pandemic stage mutations on molecular dynamics of SARS-CoV-2 Mpro:
- Amamuddy, Olivier S, Verkhivker, Gennady M, Tastan Bishop, Özlem
- Authors: Amamuddy, Olivier S , Verkhivker, Gennady M , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/162330 , vital:40835 , https://0-doi.org.wam.seals.ac.za/10.1021/acs.jcim.0c00634
- Description: A new coronavirus (SARS-CoV-2) is a global threat to world health and economy. Its dimeric main protease (Mpro), which is required for the proteolytic cleavage of viral precursor proteins, is a good candidate for drug development owing to its conservation and the absence of a human homolog. Improving our understanding of Mpro behavior can accelerate the discovery of effective therapies to reduce mortality. All-atom molecular dynamics (MD) simulations (100 ns) of 50 mutant Mpro dimers obtained from filtered sequences from the GISAID database were analyzed using root-mean-square deviation, root-mean-square fluctuation, Rg, averaged betweenness centrality, and geometry calculations.
- Full Text:
- Date Issued: 2020
- Authors: Amamuddy, Olivier S , Verkhivker, Gennady M , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/162330 , vital:40835 , https://0-doi.org.wam.seals.ac.za/10.1021/acs.jcim.0c00634
- Description: A new coronavirus (SARS-CoV-2) is a global threat to world health and economy. Its dimeric main protease (Mpro), which is required for the proteolytic cleavage of viral precursor proteins, is a good candidate for drug development owing to its conservation and the absence of a human homolog. Improving our understanding of Mpro behavior can accelerate the discovery of effective therapies to reduce mortality. All-atom molecular dynamics (MD) simulations (100 ns) of 50 mutant Mpro dimers obtained from filtered sequences from the GISAID database were analyzed using root-mean-square deviation, root-mean-square fluctuation, Rg, averaged betweenness centrality, and geometry calculations.
- Full Text:
- Date Issued: 2020
Impact of emerging mutations on the dynamic properties the SARS-CoV-2 main protease: an in silico investigation
- Amamuddy, Olivier S, Verkhivker, Gennady M, Tastan Bishop, Özlem
- Authors: Amamuddy, Olivier S , Verkhivker, Gennady M , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/163035 , vital:41006 , doi: 10.1021/acs.jcim.0c00634
- Description: The new coronavirus (SARS-CoV-2) is a global threat to world health and its economy. Its main protease (Mpro), which functions as a dimer, cleaves viral precursor proteins in the process of viral maturation. It is a good candidate for drug development owing to its conservation and the absence of a human homolog. An improved understanding of the protein behaviour can accelerate the discovery of effective therapies in order to reduce mortality. 100 ns all-atom molecular dynamics simulations of 50 homology modelled mutant Mpro dimers were performed at pH 7 from filtered sequences obtained from the GISAID database. Protease dynamics were analysed using RMSD, RMSF, Rg, the averaged betweenness centrality and geometry calculations. Domains from each Mpro protomer were found to generally have independent motions, while the dimer-stabilising N-finger region was found to be flexible in most mutants.
- Full Text:
- Date Issued: 2020
- Authors: Amamuddy, Olivier S , Verkhivker, Gennady M , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/163035 , vital:41006 , doi: 10.1021/acs.jcim.0c00634
- Description: The new coronavirus (SARS-CoV-2) is a global threat to world health and its economy. Its main protease (Mpro), which functions as a dimer, cleaves viral precursor proteins in the process of viral maturation. It is a good candidate for drug development owing to its conservation and the absence of a human homolog. An improved understanding of the protein behaviour can accelerate the discovery of effective therapies in order to reduce mortality. 100 ns all-atom molecular dynamics simulations of 50 homology modelled mutant Mpro dimers were performed at pH 7 from filtered sequences obtained from the GISAID database. Protease dynamics were analysed using RMSD, RMSF, Rg, the averaged betweenness centrality and geometry calculations. Domains from each Mpro protomer were found to generally have independent motions, while the dimer-stabilising N-finger region was found to be flexible in most mutants.
- Full Text:
- Date Issued: 2020
Integrated computational approaches and tools for allosteric drug discovery:
- Amamuddy, Olivier S, Veldman, Wade, Manyumwa, Colleen, Khairallah, Afrah, Agajanian, Steve, Oluyemi, Odeyemi, Verkhivker, Gennady M, Tastan Bishop, Özlem
- Authors: Amamuddy, Olivier S , Veldman, Wade , Manyumwa, Colleen , Khairallah, Afrah , Agajanian, Steve , Oluyemi, Odeyemi , Verkhivker, Gennady M , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/163012 , vital:41004 , https://doi.org/10.3390/ijms21030847
- Description: Understanding molecular mechanisms underlying the complexity of allosteric regulation in proteins has attracted considerable attention in drug discovery due to the benefits and versatility of allosteric modulators in providing desirable selectivity against protein targets while minimizing toxicity and other side effects. The proliferation of novel computational approaches for predicting ligand–protein interactions and binding using dynamic and network-centric perspectives has led to new insights into allosteric mechanisms and facilitated computer-based discovery of allosteric drugs. Although no absolute method of experimental and in silico allosteric drug/site discovery exists, current methods are still being improved. As such, the critical analysis and integration of established approaches into robust, reproducible, and customizable computational pipelines with experimental feedback could make allosteric drug discovery more efficient and reliable. In this article, we review computational approaches for allosteric drug discovery and discuss how these tools can be utilized to develop consensus workflows for in silico identification of allosteric sites and modulators with some applications to pathogen resistance and precision medicine. The emerging realization that allosteric modulators can exploit distinct regulatory mechanisms and can provide access to targeted modulation of protein activities could open opportunities for probing biological processes and in silico design of drug combinations with improved therapeutic indices and a broad range of activities.
- Full Text:
- Date Issued: 2020
- Authors: Amamuddy, Olivier S , Veldman, Wade , Manyumwa, Colleen , Khairallah, Afrah , Agajanian, Steve , Oluyemi, Odeyemi , Verkhivker, Gennady M , Tastan Bishop, Özlem
- Date: 2020
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/163012 , vital:41004 , https://doi.org/10.3390/ijms21030847
- Description: Understanding molecular mechanisms underlying the complexity of allosteric regulation in proteins has attracted considerable attention in drug discovery due to the benefits and versatility of allosteric modulators in providing desirable selectivity against protein targets while minimizing toxicity and other side effects. The proliferation of novel computational approaches for predicting ligand–protein interactions and binding using dynamic and network-centric perspectives has led to new insights into allosteric mechanisms and facilitated computer-based discovery of allosteric drugs. Although no absolute method of experimental and in silico allosteric drug/site discovery exists, current methods are still being improved. As such, the critical analysis and integration of established approaches into robust, reproducible, and customizable computational pipelines with experimental feedback could make allosteric drug discovery more efficient and reliable. In this article, we review computational approaches for allosteric drug discovery and discuss how these tools can be utilized to develop consensus workflows for in silico identification of allosteric sites and modulators with some applications to pathogen resistance and precision medicine. The emerging realization that allosteric modulators can exploit distinct regulatory mechanisms and can provide access to targeted modulation of protein activities could open opportunities for probing biological processes and in silico design of drug combinations with improved therapeutic indices and a broad range of activities.
- Full Text:
- Date Issued: 2020
Establishing computational approaches towards identifying malarial allosteric modulators: a case study of plasmodium falciparum hsp70s
- Amusengeri, Arnold, Astl, Lindy, Lobb, Kevin A, Verkhivker, Gennady M, Tastan Bishop, Özlem
- Authors: Amusengeri, Arnold , Astl, Lindy , Lobb, Kevin A , Verkhivker, Gennady M , Tastan Bishop, Özlem
- Date: 2019
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/163000 , vital:41003 , https://doi.org/10.3390/ijms20225574
- Description: Combating malaria is almost a never-ending battle, as Plasmodium parasites develop resistance to the drugs used against them, as observed recently in artemisinin-based combination therapies. The main concern now is if the resistant parasite strains spread from Southeast Asia to Africa, the continent hosting most malaria cases. To prevent catastrophic results, we need to find non-conventional approaches. Allosteric drug targeting sites and modulators might be a new hope for malarial treatments. Heat shock proteins (HSPs) are potential malarial drug targets and have complex allosteric control mechanisms. Yet, studies on designing allosteric modulators against them are limited. Here, we identified allosteric modulators (SANC190 and SANC651) against P. falciparum Hsp70-1 and Hsp70-x, affecting the conformational dynamics of the proteins, delicately balanced by the endogenous ligands. Previously, we established a pipeline to identify allosteric sites and modulators. This study also further investigated alternative approaches to speed up the process by comparing all atom molecular dynamics simulations and dynamic residue network analysis with the coarse-grained (CG) versions of the calculations. Betweenness centrality (BC) profiles for PfHsp70-1 and PfHsp70-x derived from CG simulations not only revealed similar trends but also pointed to the same functional regions and specific residues corresponding to BC profile peaks.
- Full Text:
- Date Issued: 2019
- Authors: Amusengeri, Arnold , Astl, Lindy , Lobb, Kevin A , Verkhivker, Gennady M , Tastan Bishop, Özlem
- Date: 2019
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/163000 , vital:41003 , https://doi.org/10.3390/ijms20225574
- Description: Combating malaria is almost a never-ending battle, as Plasmodium parasites develop resistance to the drugs used against them, as observed recently in artemisinin-based combination therapies. The main concern now is if the resistant parasite strains spread from Southeast Asia to Africa, the continent hosting most malaria cases. To prevent catastrophic results, we need to find non-conventional approaches. Allosteric drug targeting sites and modulators might be a new hope for malarial treatments. Heat shock proteins (HSPs) are potential malarial drug targets and have complex allosteric control mechanisms. Yet, studies on designing allosteric modulators against them are limited. Here, we identified allosteric modulators (SANC190 and SANC651) against P. falciparum Hsp70-1 and Hsp70-x, affecting the conformational dynamics of the proteins, delicately balanced by the endogenous ligands. Previously, we established a pipeline to identify allosteric sites and modulators. This study also further investigated alternative approaches to speed up the process by comparing all atom molecular dynamics simulations and dynamic residue network analysis with the coarse-grained (CG) versions of the calculations. Betweenness centrality (BC) profiles for PfHsp70-1 and PfHsp70-x derived from CG simulations not only revealed similar trends but also pointed to the same functional regions and specific residues corresponding to BC profile peaks.
- Full Text:
- Date Issued: 2019
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