A Fragment-Based Drug Discovery Developed on Ciclopirox for Inhibition of Hepatitis B Virus Core Protein: An in Silico Study Publisher Pubmed



Mohebbi A^{1, 2} ; Ghorbanzadeh T³ ; Naderifar S⁴ ; Khalaj F^{5, 6} ; Askari FS² ; Salehnia Sammak A⁷ Show Affiliations
Source: PLoS ONE Published:2023

Abstract

The Hepatitis B virus (HBV) core protein is an attractive target for preventing capsid assembly and viral replication. Drug repurposing strategies have introduced several drugs targeting HBV core protein. This study used a fragment-based drug discovery (FBDD) approach to reconstruct a repurposed core protein inhibitor to some novel antiviral derivatives. Auto Core Fragment in silico Screening (ACFIS) server was used for deconstruction-reconstruction of Ciclopirox in complex with HBV core protein. The Ciclopirox derivatives were ranked based on their free energy of binding (ΔGB). A quantitative structure affinity relationship (QSAR) was established on the Ciclopirox derivatives. The model was validated by a Ciclopirox- property-matched decoy set. A principal component analysis (PCA) was also assessed to define the relationship of the predictive variable of the QSAR model. 24-derivatives with a ΔGB (-16.56±1.46 Kcal.mol-1) more than Ciclopirox was highlighted. A QSAR model with a predictive power of 88.99% (F-statistics = 9025.78, corrected df(25), Pr > F = 0.0001) was developed by four predictive descriptors (ATS1p, nCs, Hy, F08[C-C]). The model validation showed no predictive power for the decoy set (Q2 = 0). No significant correlation was observed between predictors. By directly attaching to the core protein carboxylterminal domain, Ciclopirox derivatives may be able to suppress HBV virus assembly and subsequent viral replication inhibition. Hydrophobic residue Phe23 is a critical amino acid in the ligand binding domain. These ligands share the same physicochemical properties that lead to the development of a robust QSAR mode. The same strategy may also be used for future drug discovery of viral inhibitors. © 2023 Mohebbi et al.