Interpretable machine learning approach to predict Hepatitis C virus NS5B inhibitor activity using voting-based LightGBM and SHAP

Interpretable machine learning approach to predict Hepatitis C virus NS5B inhibitor activity using voting-based LightGBM and SHAP

Hepatitis C is a pressing global health issue that urgently requires the development of effective antiviral medications. In this study, we focus on targeting the Hepatitis C virus non-structural protein 5B (NS5B) polymerase, a key enzyme in viral RNA replication, to hinder the viral life cycle and r...

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Bibliographic Details
Main Authors: Teuku Rizky Noviandy, Aga Maulana, Irvanizam Irvanizam, Ghazi Mauer Idroes, Nur Balqis Maulydia, Trina Ekawati Tallei, Muhammad Subianto, Rinaldi Idroes
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Intelligent Systems with Applications
Subjects:
Bayesian optimization
SHAP
Molecular descriptors
QSAR
Online Access:http://www.sciencedirect.com/science/article/pii/S2667305325000079
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