In silico Exploration of the Therapeutic Potential of Phytocannabinoids

Plant-derived cannabinoids exhibit remarkable structural diversity and have attracted increasing attention as bioactive compounds. Recent in silico studies have explored how these compounds interact with molecular targets involved in neurodegenerative, metabolic, oncological, and viral diseases. This review summarizes the available data on molecular docking, molecular dynamics (MD), and ADMET analysis published from 2023 to 2026 for selected phytocannabinoids. Analysis of the reviewed publications suggests that compounds such as Δ9-THC, CBN, THCV, and THCA are predicted to bind to numerous proteins implicated in disease pathogenesis, including acetylcholinesterase, butyrylcholinesterase, EGFR, BRAF/TGF-β, α-amylase, and SARS-CoV-2 Mpro. However, the docking scores obtained by different computational protocols are not directly comparable. Similarly, stable MD trajectories and favorable ADMET predictions provide computational evidence but do not guarantee the biological efficacy and safety of the studied compounds. This review highlights the importance of integrating molecular docking, molecular dynamics, pharmacokinetic prediction, and experimental validation. It also identifies methodological gaps and proposes a stepwise experimental strategy to validate the most promising computational hypotheses.