Background: Colorectal cancer continues to impose a substantial global health burden, with GLOBOCAN 2022 estimating approximately 1.93 million new cases and 0.90 million deaths. Resistance to therapy remains a major limitation, highlighting the need for strategies that restore apoptosis and target anti-apoptotic Bcl-2 family proteins. Myeloid cell leukemia 1 (Mcl-1), a key pro-survival regulator implicated in chemoresistance, including in colorectal cancer, therefore represents a promising molecular target. Methods: This study evaluated a sesquiterpene-derived candidate (CPD2) from Rolandra fruticosa against Mcl-1 (PDB: 6QFQ) using an integrated in silico workflow. The analyses included molecular docking, molecular dynamics (MD) simulation, MM/GBSA end-point free-energy estimation, ADMET prediction using pkCSM, and density functional theory (DFT)-based electronic descriptors. Fruquintinib, an approved anticancer agent, was used as the reference compound. Results: Docking analysis positioned CPD2 within the canonical BH3-binding groove of Mcl-1 and suggested favorable interactions with hotspot residues, including Arg263. Over 100 ns of MD simulation, the CPD2–Mcl-1 complex exhibited a comparatively restrained conformational ensemble, whereas the fruquintinib complex showed greater deviation during the later stage of the trajectory. MM/GBSA analysis supported favorable binding for both ligands, although fruquintinib displayed a more favorable mean binding free energy under the applied protocol. ADMET prediction indicated that CPD2 had fewer predicted CYP inhibition liabilities and safety-alert signals than fruquintinib, despite showing distinct absorption–clearance trade-offs. DFT descriptors further suggested greater electronic responsiveness for CPD2. Limitations: A key limitation of this study is its reliance on model-dependent assumptions, including the use of a single receptor conformation and limited dynamical sampling. These findings therefore require confirmation through biochemical, cellular, pharmacokinetic, and toxicity studies. Conclusion: Overall, the computational evidence identifies CPD2 as an optimization-relevant scaffold targeting Mcl-1 and supports its prioritization for further experimental validation.

Background: Colorectal cancer continues to impose a substantial global health burden, with GLOBOCAN 2022 estimating approximately 1.93 million new cases and 0.90 million deaths. Resistance to therapy remains a major limitation, highlighting the need for strategies that restore apoptosis and target anti-apoptotic Bcl-2 family proteins. Myeloid cell leukemia 1 (Mcl-1), a key pro-survival regulator implicated in chemoresistance, including in colorectal cancer, therefore represents a promising molecular target. Methods: This study evaluated a sesquiterpene-derived candidate (CPD2) from Rolandra fruticosa against Mcl-1 (PDB: 6QFQ) using an integrated in silico workflow. The analyses included molecular docking, molecular dynamics (MD) simulation, MM/GBSA end-point free-energy estimation, ADMET prediction using pkCSM, and density functional theory (DFT)-based electronic descriptors. Fruquintinib, an approved anticancer agent, was used as the reference compound. Results: Docking analysis positioned CPD2 within the canonical BH3-binding groove of Mcl-1 and suggested favorable interactions with hotspot residues, including Arg263. Over 100 ns of MD simulation, the CPD2–Mcl-1 complex exhibited a comparatively restrained conformational ensemble, whereas the fruquintinib complex showed greater deviation during the later stage of the trajectory. MM/GBSA analysis supported favorable binding for both ligands, although fruquintinib displayed a more favorable mean binding free energy under the applied protocol. ADMET prediction indicated that CPD2 had fewer predicted CYP inhibition liabilities and safety-alert signals than fruquintinib, despite showing distinct absorption–clearance trade-offs. DFT descriptors further suggested greater electronic responsiveness for CPD2. Limitations: A key limitation of this study is its reliance on model-dependent assumptions, including the use of a single receptor conformation and limited dynamical sampling. These findings therefore require confirmation through biochemical, cellular, pharmacokinetic, and toxicity studies. Conclusion: Overall, the computational evidence identifies CPD2 as an optimization-relevant scaffold targeting Mcl-1 and supports its prioritization for further experimental validation.