In silico identification and characterization of potent laccase inhibitors against Cryptococcus neoformans: A multi-scale computational study
Muharib Alruwaili1*†, Sonia Younas 2,3†, Muhammad Umer Khan4*, Hammad Saleem5,Yasir Alruwaili1,6, Abualgasim Elgaili Abdalla1, Bi Bi Zainab Mazhari7, Khalid Abosalif1, Hasan Ejaz1
1Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Sakaka 72388, Saudi Arabia
2Centre for Immunology and Infection (C2i), Hong Kong Science and Technology Park, Hong Kong, SAR China
3HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
4Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, 54590, Pakistan
5Institute of Pharmaceutical Sciences (IPS), University of Veterinary & Animal Sciences (UVAS), Lahore, Pakistan
6Sustainable Development Research and Innovation Center, Deanship of Graduate Studies and Scientific Research, Jouf University, Sakaka 72388, Saudi Arabia
7Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Qurayyat 75911, Saudi Arabia
Received: 30 November 2024 / Accepted: 27 January 2025 / Published Online: 06 March 2025
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 HOMO-LUMO energy gap. The identification of L-11 (8-[4-[9,9-Dimethyl-7-(2,3,4,5,6,7,8,9,10-nonahydroxypyren-1-yl)fluoren-2-yl]phenyl]pyrene-1,2,3,4,5,6,7,9,10-nonol) as a potent inhibitor of C. neoformans laccase represents a novel approach to antifungal drug discovery, marking a significant step to combat fungal infections and a way forward to perform in-vitro and in-vivo studies and ultimately its clinical application.
