Computational design of potent dimeric phenylthiazole NS5A inhibitors for hepatitis C virus

Hepatitis C virus (HCV) presents a significant global health issue due to its widespread prevalence and the absence of a reliable vaccine for prevention. While significant progress has been achieved in therapeutic interventions since the disease was first identified, its resurgence underscores the need for innovative strategies to combat it. The nonstructural protein NS5A is crucial in the life cycle of the HCV, serving as a significant factor in both viral replication and assembly processes. This significance is highlighted by its inclusion in all existing approved HCV combination therapies. In this study, a quantitative structure-activity relationship (QSAR) was conducted to design new compounds with enhanced inhibitory activity against HCV. In this context, a set of 82 phenylthiazole derivatives was employed to construct a QSAR model using the Monte Carlo optimization technique. This model offers valuable insights into the specific structural characteristics that either enhance or reduce the inhibitory activity. These findings were used to design novel NS5A inhibitors. Moreover, molecular docking was used to predict the binding affinity of the newly designed inhibitors within the NS5A protein, followed by molecular dynamics simulations to investigate the dynamic interactions over time. Additionally, molecular mechanics generalized born surface area calculations were carried out to estimate the binding free energies of the inhibitor candidates, providing additional insights into their binding affinities and stabilities. Finally, the absorption, distribution, metabolism, excretion, and toxicity analysis were performed to assess the pharmacokinetic and toxicity profiles of the inhibitor candidates. This comprehensive approach provides a detailed understanding of the potential efficacy, stability, and safety of the screened drug candidates, offering valuable insights for their further development as potent therapeutic agents against HCV.

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Publication Details

Journal
Scientific Reports
Published
2024-12-30
DOI
https://doi.org/10.1038/s41598-024-80082-1
Citations
3
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.08
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article

Computational design of potent dimeric phenylthiazole NS5A inhibitors for hepatitis C virus

Ismail Hdoufane, Wissal Liman, Achraf El Allali, Nouhaila Ait Lahcen et al.
3 citations
Scientific Reports
Computational Drug Discovery Methods
1.08
article

Computational design of potent dimeric phenylthiazole NS5A inhibitors for hepatitis C virus

Ismail Hdoufane, Wissal Liman, Achraf El Allali, Nouhaila Ait Lahcen, Rachid Daoud, Driss Cherqaoui, Mehdi Oubahmane
article en
3 citations

Abstract

Hepatitis C virus (HCV) presents a significant global health issue due to its widespread prevalence and the absence of a reliable vaccine for prevention. While significant progress has been achieved in therapeutic interventions since the disease was first identified, its resurgence underscores the need for innovative strategies to combat it. The nonstructural protein NS5A is crucial in the life cycle of the HCV, serving as a significant factor in both viral replication and assembly processes. This significance is highlighted by its inclusion in all existing approved HCV combination therapies. In this study, a quantitative structure-activity relationship (QSAR) was conducted to design new compounds with enhanced inhibitory activity against HCV. In this context, a set of 82 phenylthiazole derivatives was employed to construct a QSAR model using the Monte Carlo optimization technique. This model offers valuable insights into the specific structural characteristics that either enhance or reduce the inhibitory activity. These findings were used to design novel NS5A inhibitors. Moreover, molecular docking was used to predict the binding affinity of the newly designed inhibitors within the NS5A protein, followed by molecular dynamics simulations to investigate the dynamic interactions over time. Additionally, molecular mechanics generalized born surface area calculations were carried out to estimate the binding free energies of the inhibitor candidates, providing additional insights into their binding affinities and stabilities. Finally, the absorption, distribution, metabolism, excretion, and toxicity analysis were performed to assess the pharmacokinetic and toxicity profiles of the inhibitor candidates. This comprehensive approach provides a detailed understanding of the potential efficacy, stability, and safety of the screened drug candidates, offering valuable insights for their further development as potent therapeutic agents against HCV.

Scientific ReportsVol. 14(1)
Cadi Ayyad University (MA), Université Mohammed VI Polytechnique (MA)
Openalex Percentile: Top 19%
Computational Drug Discovery Methods
1.08
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