Biochemoinformatics Screening of Chemical Constituents from Laportea aestuans L. Leaves as Potential Prostate Cancer Inhibitors
DOI:
https://doi.org/10.36733/medicamento.v12i1.12565Keywords:
ADME profiling, CDK2, Laportea aestuans L., molecular docking, natural compounds, prostate cancerAbstract
Background: Prostate cancer remains a major cause of morbidity among men worldwide, with current therapies limited by resistance and toxicity. Natural compounds offer promising alternatives due to their structural diversity and biological compatibility.
Objective: This study evaluated seven bioactive constituents from Laportea aestuans L. leaves as potential inhibitors of prostate cancer-related targets using molecular docking and pharmacokinetic profiling.
Methods: Seven bioactive compounds were identified through phytochemical literature review. Molecular docking simulations were executed using AutoDock4, with interaction analysis validated via PyMOL and UCSF Chimera. Furthermore, pharmacokinetic properties and toxicological profiles were predicted using the ADMETlab webserver to assess drug-likeness and safety parameters.
Results: Docking simulations revealed that LA6 exhibited the strongest affinity toward CDK2 (–9.97 kcal/mol) through hydrogen bonding with Asp145 and Lys33, while Chrysenol bound PDGFRA (–9.12 kcal/mol) at Glu644 and Val658. Compounds LA2, LA4, and LA5 also showed stable interactions with GSK-3β, suggesting modulation of Wnt signaling. ADME analysis indicated high gastrointestinal absorption and compliance with Lipinski’s Rule of Five, whereas LA6 and Chrysenol demonstrated mutagenicity and hepatotoxicity risks. Distribution profiling revealed high plasma protein binding (>90%) and moderate blood-brain barrier permeability, particularly for LA6.
Conclusion: These findings highlight L. aestuans L. derivatives as promising lead candidates for prostate cancer therapy, though further in vitro and in vivo validation is required to confirm efficacy and optimize safety. This integrative computational approach underscores the role of bioinformatics in accelerating natural product-based drug discovery.
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