Work

Computational discovery of glioblastoma multiforme inhibitors from medicinal fungi: An integrated approach combining virtual screening, DFT, and toxicity profiling

Year: 2025

Type: article

Abstract: Glioblastoma multiforme (GBM) is one of the deadliest brain cancers, notorious for its resistance to current treatments. To explore new therapeutic options, we turned to nature’s pharmacy - medicinal fungi. Using a comprehensive in silico pipeline, we screened 1,830 fungal metabolites from the MEFSAT database against a key GBM target protein (PDB ID: 5HJB). Promising candidates were refined through molecular docking, MM-GBSA energy profiling, and Density Functional Theory (DFT) calculations. Further analysis using QTAIM, SwissADME, and ProTox 3.0 helped predict stability, drug-likeness, and safety. Gallicynoic acid F (Ligand A3) stood out for its strong binding, low predicted toxicity, and favorable pharmacokinetics, making it a compelling lead for further exploration. Our findings suggest that fungal metabolites hold real potential as future GBM therapeutics.

Source: In Silico Research in Biomedicine

DOI: 10.1016/j.insi.2025.100023

Author: Avni Berisha

Institution: University of Prishtina

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,000