Targeting non-structural proteins of Hepatitis C virus for predicting repurposed drugs using QSAR and machine learning approaches

Targeting non-structural proteins of Hepatitis C virus for predicting repurposed drugs using QSAR and machine learning approaches

Hepatitis C virus (HCV) infection causes viral hepatitis leading to hepatocellular carcinoma. Despite the clinical use of direct-acting antivirals (DAAs) still there is treatment failure in 5–10% cases. Therefore, it is crucial to develop new antivirals against HCV. In this endeavor, we developed th...

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Bibliographic Details
Main Authors: Kamboj, S. (Author), Kumar, M. (Author), Rajput, A. (Author), Rastogi, A. (Author), Thakur, A. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2022
Subjects:
Antiviral
Antivirals
Binding energy
Chemical analysis
Computational chemistry
Correlation methods
Decision trees
Drug repurposing
Forecasting
Hepatitis C virus
Hepatitis C Virus
Machine learning
Machine-learning
Nearest neighbor search
Neural networks
Non-structural
Non-structural protein
NS3-NS3/NS4A-NS5A-NS5B
Prediction
Proteins
QSAR
Quantitative structure activity relationship
Repurposing
Structural proteins
Support vector machines
Viruses
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