Investigators used density functional theory calculations at the B3LYP/6-31G* level to characterize the electronic properties of the compounds. Among the screened molecules, ligand L10, identified as cyclohexane-1,2,3,4,5,6-hexaol, had the smallest reported gap between its highest occupied and lowest unoccupied molecular orbitals: 0.36 electronvolts. This value was reported without establishing that it predicts anticancer activity in humans.

The researchers then docked all 14 phytochemicals into the Keap1 Kelch domain, represented by Protein Data Bank structure 1X2J, and the YEATS2 YEATS domain, represented by structure 5XNV. Two docking systems were used: AutoDock Vina through PyRx and Schrödinger Glide. L10 achieved a reported Glide score of −7.789 kcal/mol against Keap1 and formed multiple hydrogen-bonding interactions. Compounds L02, L05 and L07 also displayed promising profiles across parts of the computational workflow, indicating that the screen produced several candidates rather than a single unequivocal lead.

Top-ranked complexes were subjected to 100-nanosecond molecular dynamics simulations in Desmond. The L10–Keap1 complex remained stable during the simulations under the modeled conditions, with a reported root-mean-square deviation of protein alpha-carbon atoms below 3 angstroms. SwissADME and pkCSM were also used to estimate pharmacokinetic and toxicity-related properties; most compounds were reported to comply with Lipinski’s rule of five and to have acceptable predicted ADMET profiles. The results support prioritizing L10 and several other R. mucronata phytochemicals for laboratory evaluation as possible modulators of Keap1 and YEATS2, but they do not demonstrate anticancer effects or establish clinical benefit.

Subject of Research: Computational screening of mangrove phytochemicals against Keap1 and YEATS2

Article Title: Investigating the anticancer potential of phytochemicals from the mangrove Rhizophora mucronata as inhibitors of lung cancer-associated proteins: Insights from multiscale computational and in silico analyses

Article References: Mahdi, Z. A.-A., AlmjalawI, B. S. A., Naimuzzaman, M., Hasan, M. M., Kumer, A., Al-Alaq, F. T., Al-Dahmoshi, H. O. M., Rahman, F., Khan, M. F. A.-H., Al-Khafaji, N. S. K., & Al-Yasiri, S. A. M. (2026). Investigating the anticancer potential of phytochemicals from the mangrove Rhizophora mucronata as inhibitors of lung cancer-associated proteins: Insights from multiscale computational and in silico analyses. PLOS One, 21(10), e0359525. https://doi.org/10.1371/journal.pone.0359525

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0359525

Keywords: mangrove phytochemicals, Rhizophora mucronata, lung cancer, in silico screening, molecular docking, molecular dynamics, Keap1, YEATS2, natural products, drug discovery, Investigating, anticancer