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| Main Authors: | , , |
|---|---|
| Format: | Artículo científico |
| Language: | en |
| Published: |
Biology
2026
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| Online Access: | https://pubmed.ncbi.nlm.nih.gov/41823820/ |
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Table of Contents:
- Structure-Based Screening of Deep-Sea Microbial Metabolites Against Dihydroorotate Dehydrogenase. Singh, Avtar Rengasamy, Kannan R R Benjakul, Soottawat Malaria is a major global health concern caused by parasites, among which is responsible for the most severe and fatal cases. The emergence of drug resistance to existing antimalarial therapies necessitates the discovery of novel molecular targets and chemically distinct inhibitors. Current study employed an integrated in silico drug discovery pipeline combining high-throughput structure-based virtual screening of 1549 deep-sea marine microbial metabolites with MM-GBSA binding free-energy estimation, QikProp-based ADME/Tox profiling, and 100 ns molecular dynamics (MD) simulations to link rapid screening with dynamic verification of binding stability. Molecular docking against dihydroorotate dehydrogenase (PfDHODH; PDB ID: 7KZ4) yielded five top-ranked compounds with Glide scores ranging from -12.02 to -10.61 kcal·mol, which is higher than the Primaquine (-6.920 kcal·mol; a clinically approved antimalarial reference compound). MM-GBSA analysis further refined hit selection, producing binding free energies (ΔG_bind) between -63.28 and -31.37 kcal·mol. The selected lead compounds included (±)-puniceusine P, aspergilol F, tersaphilone C, 4-carbglyceryl-3,3'-dihydroxy-5,5'-dimethyldiphenyl ether, and 15-O-methyl ML-236A. The top hits were subjected to 100 ns MD simulations in Desmond, demonstrating stable protein-ligand complexes, particularly for (±)-puniceusine P and 15-O-methyl ML-236A (protein backbone root mean square deviation (RMSD; ~0.8-1.0 Å). ADME profiling indicated acceptable predicted physicochemical and pharmacokinetic properties. Overall, these in silico findings highlight deep-sea marine microbial metabolites as promising PfDHODH inhibitor candidates requiring experimental validation.