THE POTENTIAL OF CALANONE DERIVATIVES AS ANTILEUKEMIA AGENTS VIA AN IN SILICO APPROACH: MOLECULAR DOCKING AND MOLECULAR DYNAMICS ANALYSIS - Firdaus, Irvan Maulana; Hafshah, Mutista; Akbar, Achmad; Faiz, Rijal Akhmad; Iswanto, Ponco; Chasani, Mochammad; Hanafi, Muhammad; Delsy, Eva Vaulina Yulistia (Walisongo Journal of Chemistry, 2025)
Cancer, particularly leukemia, remains a major global health concern with a high mortality rate, necessitating the development of more effective and selective therapeutic agents. This study evaluated the potential of calanone derivatives as antileukemia agents using an in silico approach. The objectives were to (1) analyze the molecular docking interactions between predicted calanone derivatives and commercial leukemia drugs targeting the Bruton’s Tyrosine Kinase (BTK) receptor (PDB ID: 5P9J); (2) predict the ADMET properties (Absorption, Distribution, Metabolism, Excretion, and Toxicity) of the calanone derivatives; and (3) compare the molecular dynamics analysis results of the predicted compounds with those of commercial drugs. The findings revealed that the predicted molecules, including Vaulina2 ((5-hydroxy-2,2-dimethyl-8-oxo-10-phenyl-2H,8H-pyrano[2,3-f]chromen-6-yl)(phenyl)methyl 2-amino-3-(4-hydroxyphenyl)-3-oxopropanoate)), Prediction1 ((8-amino-5-hydroxy-2,2-dimethyl-10-phenyl-2H,8H-pyrano[2,3-f]chromen-6-yl)(phenyl)methanediol)), Prediction2 (6-(dihydroxy(phenyl)methyl)-2,2-dimethyl-10-phenyl-2H,8H-pyrano[2,3-f]chromene-5,8-diol)), Prediction3 (2-amino-9,9-dimethyl-3,7-diphenyl-2,3-dihydro-5H,9H-furo[2,3-f]pyrano[2,3-h]chromen-5-ol)), and Prediction4 (4-(dihydroxy(8-hydroxy-2,2-dimethyl-5-oxo-10-phenyl-6,8-dihydro-2H,5H-pyrano[2,3-f]chromen-6-yl)methyl)benzoic acid)), demonstrated greater stability compared to the reference drug ibrutinib, with Gibbs free energy (ΔG) values of −11.25, −12.50, −10.83, −10.74, and −10.63 kcal/mol, respectively. All compounds also conformed to the predicted ADMET profiles. Molecular dynamics simulations indicated that Vaulina2, Prediction1, and Prediction2 exhibited superior performance based on Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Solvent-Accessible Surface Area (SASA), hydrogen bond occupancy, and Molecular Mechanics–Generalized Born Surface Area (MM-GBSA) parameters.