ArticleJournal, genetic engineering & biotechnology2026
Cannabis as a source of novel therapeutics: A computational study combining LBDD and structure-based docking/dynamics to identify novel drug-like compounds for colorectal cancer.
Article in Journal, genetic engineering & biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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9 authors.
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Abstract
Cannabis represents a valuable source of bioactive compounds with significant therapeutic potential, thanks to its rich phytochemical profile, making it a prime candidate for cancer research. Our study investigates the potential of cannabis-derived compounds to inhibit cyclin-dependent kinase 2 (CDK2), a crucial regulator of cell-cycle progression and colorectal cancer cell proliferation. A comprehensive computational workflow integrating 3D-QSAR modeling, molecular docking, molecular dynamics simulations, drug-likeness assessment, and ADMET prediction was employed to investigate a dataset of 33 cannabis-derived compounds. The robustness and predictive performance of the generated CoMFA and CoMSIA models were confirmed through internal and external validation, leave-one-out cross-validation (LOOCV), and Y-randomization tests, yielding excellent statistical parameters for CoMFA (Q
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