In Vitro Cytotoxicity and In Silico Drug-Likeness of Secondary Metabolites from Endophytic Aspergillus spp. Isolated from Brownlowia tersa

Background: Mangrove-associated endophytic fungi are prolific producers of bioactive secondary metabolites with promising therapeutic applications. Brownlowia tersa, a medicinal mangrove species, harbors fungal endophytes that remain largely unexplored for their pharmacological potential. Objective: This study aimed to isolate endophytic fungi from B. tersa, characterize their secondary metabolites, and evaluate their cytotoxic, antibacterial, and antioxidant potentials through in vitro and silico approaches. Methods: Endophytic fungi were isolated from B. tersa leaves collected from the Sundarbans and identified morphologically and through ITS rDNA sequencing. Fungal crude extracts were screened for cytotoxicity against MCF-7 and SK-LU-1 human cancer cell lines using the SRB assay. Bioactive compounds were subjected to drug-likeness analysis via Lipinski’s Rule of Five. Molecular docking was performed to assess the binding affinity of compounds previously reported in these species against bacterial DNA gyrase (GyrB) and the antioxidant enzyme Cu/Zn-SOD using AutoDock Vina. Results: Four Aspergillus species were isolated, among which Aspergillus fumigatus extracts (BTL-1, BTS-2) exhibited strong cytotoxic activity with IC50 values of 17.06 ± 0.58 μg/mL and 14.35 ± 0.32 μg/mL. Chlorogenic acid, ar-turmerone, and lupenol were identified as promising compounds. Chlorogenic acid showed the highest docking affinities against GyrB (–8.1 kcal/mol) and Cu/Zn-SOD (–5.7 kcal/mol), with multiple stable hydrogen bonds, indicating strong antibacterial and antioxidant potential. Conclusion: The study highlights the therapeutic potential of B. tersa-associated endophytic fungi, particularly Aspergillus fumigatus, as a source of multi-target bioactive metabolites. Chlorogenic acid emerged as a promising lead for further development. These findings warrant subsequent in vivo validation and lead optimization for drug development.