In silico identification and characterization of potent laccase inhibitors against Cryptococcus neoformans: A multi-scale computational study
Abstract
Cryptococcus neoformans is an opportunistic fungal pathogen, especially affecting individuals with weakened immune systems.Laccase enzymes are pivotal in its pathogenicity, making them promising targets for therapeutic intervention.This study aims to identify and characterize potent laccase inhibitors against C. neoformans using advanced in-silico analysis.The laccase protein (UniProt ID: Q55P57) was retrieved via AlphaFold and validated with ProCheck.Pharmacophore-based virtual screening (PBVS) identified 19 potential inhibitors, which were docked using CB-Dock2.The top six compound's pharmacokinetic properties were assessed using SwissADME, PKCSM, and StopTox.Bioactivity was predicted via SwissTargetPrediction.Density Functional Theory (DFT) calculations were conducted using Gauss view 5.0.8.The validated 3D structure of the target protein Q55P57 demonstrated high quality, with 86.5% of residues in favored regions.The molecular docking revealed that L-11 exhibited the highest binding affinity (-13.2 kcal/mol), forming crucial interactions within the active site.L-11 displayed favorable physicochemical properties, including high lipophilicity and good Caco2 permeability, positioning it as a strong candidate for therapeutic development.Toxicity predictions indicated non-toxicity for acute inhalation and oral exposure, while bioactivity analysis highlighted its broad target interactions.DFT analysis demonstrated L-11's enhanced reactivity due to its high dipole moment and low…
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