Mechanistic Insights into the Mutational Landscape of the Main Protease/3CLPro and Its Impact on Long-Term COVID-19/SARS-CoV-2 Management

The main proteinase (Mpro), or 3CLpro, is a critical enzyme in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lifecycle and is responsible for breaking down and releasing vital functional viral proteins crucial for virus development and transmission. As a catalytically active dimer, its dimerization interface has become an attractive target for antiviral drug development. Recent research has extensively investigated the enzymatic activity of Mpro, focusing on its role in regulating the coronavirus replication complex and its significance in virus maturation and infectivity. Computational investigations have identified four druggable pockets, suggesting potential allosteric sites beyond the substrate-binding region. Empirical validation through site-directed alanine mutagenesis has targeted residues in both the active and allosteric regions and corroborated these predictions. Structural studies of drug target proteins can inform therapeutic approaches, with metadynamics simulations shedding light on the role of H163 in regulating Mpro function and providing insights into its dynamic equilibrium to the wild-type enzyme. Despite the efficacy of vaccines and drugs in mitigating SARS-CoV-2 spread, its ongoing viral evolution, selective pressures, and continued transmission pose challenges, potentially leading to resistant mutations. Phylogenetic analyses have indicated the existence of several resistant variations predating drug introduction to the human population, emphasizing the likelihood of drug spread. Hydrogen/deuterium-exchange mass spectrometry reveals the structural influence of the mutation. At the same time, clinical trials on 3CLPro inhibitors underscore the clinical significance of reduced enzymatic activity and offer avenues for future therapeutic exploration. Understanding the implications of 3CLPro mutations holds promise for shaping forthcoming therapeutic strategies against COVID-19. This review delves into factors influencing mutation rates and identifies areas warranting further investigation, providing a comprehensive overview of Mpro mutations, categorization, and terminology. Moreover, we examine their associations with clinical outcomes, illness severity, unresolved issues, and future research prospects, including their impact on vaccine efficacy and potential therapeutic targeting.

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Journal
Future Pharmacology
Published
2024-11-28
DOI
https://doi.org/10.3390/futurepharmacol4040044
Citations
3
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.08

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article

Mechanistic Insights into the Mutational Landscape of the Main Protease/3CLPro and Its Impact on Long-Term COVID-19/SARS-CoV-2 Management

Hezekiel Mathambo Kumalo, Mukanda Gedeon Kadima, Rene Bernadette Khan, Kahumba Byanga et al.
3 citations
Future Pharmacology
Computational Drug Discovery Methods
1.08
article

Mechanistic Insights into the Mutational Landscape of the Main Protease/3CLPro and Its Impact on Long-Term COVID-19/SARS-CoV-2 Management

Hezekiel Mathambo Kumalo, Mukanda Gedeon Kadima, Rene Bernadette Khan, Kahumba Byanga, Aganze Gloire-Aimé Mushebenge, Samuel Chima Ugbaja, Nonkululeko Avril Mbatha, Manimbulu Nlooto, Bakari Amuri, Tambwe Willy Muzumbukilwa, Nonjabulo Ntombikhona Magwaza, Ntabaza Ndage, Riziki Ghislain Manimani, Fave Yohanna Tata, Mthokosizi Bongani Nxumalo
article en
3 citations

Abstract

The main proteinase (Mpro), or 3CLpro, is a critical enzyme in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lifecycle and is responsible for breaking down and releasing vital functional viral proteins crucial for virus development and transmission. As a catalytically active dimer, its dimerization interface has become an attractive target for antiviral drug development. Recent research has extensively investigated the enzymatic activity of Mpro, focusing on its role in regulating the coronavirus replication complex and its significance in virus maturation and infectivity. Computational investigations have identified four druggable pockets, suggesting potential allosteric sites beyond the substrate-binding region. Empirical validation through site-directed alanine mutagenesis has targeted residues in both the active and allosteric regions and corroborated these predictions. Structural studies of drug target proteins can inform therapeutic approaches, with metadynamics simulations shedding light on the role of H163 in regulating Mpro function and providing insights into its dynamic equilibrium to the wild-type enzyme. Despite the efficacy of vaccines and drugs in mitigating SARS-CoV-2 spread, its ongoing viral evolution, selective pressures, and continued transmission pose challenges, potentially leading to resistant mutations. Phylogenetic analyses have indicated the existence of several resistant variations predating drug introduction to the human population, emphasizing the likelihood of drug spread. Hydrogen/deuterium-exchange mass spectrometry reveals the structural influence of the mutation. At the same time, clinical trials on 3CLPro inhibitors underscore the clinical significance of reduced enzymatic activity and offer avenues for future therapeutic exploration. Understanding the implications of 3CLPro mutations holds promise for shaping forthcoming therapeutic strategies against COVID-19. This review delves into factors influencing mutation rates and identifies areas warranting further investigation, providing a comprehensive overview of Mpro mutations, categorization, and terminology. Moreover, we examine their associations with clinical outcomes, illness severity, unresolved issues, and future research prospects, including their impact on vaccine efficacy and potential therapeutic targeting.

Future PharmacologyVol. 4(4)
University of Lubumbashi (CD), Africa Health Research Institute (ZA), University of Limpopo (ZA), University of KwaZulu-Natal (ZA)
Inyuvesi Yakwazulu-Natali
Good health and well-being
Openalex Percentile: Top 19%
Computational Drug Discovery Methods
1.08
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