Repositioning Cannabinoids and Terpenes as Novel EGFR-TKIs Candidates for Targeted Therapy Against Cancer: A virtual screening model using CADD and biophysical simulations. Issue 4 (April 2023)

• Record Type: Journal Article
• Authors: Daoui, Ossama; Mali, Suraj N.; Elkhattabi, Kaouakeb; Elkhattabi, Souad; Chtita, Samir
• Is Part Of: Heliyon. Volume 9:Issue 4(2023)
• Publication Date: 2023-04
• Subjects: Cannabis sativa L. -- Virtual Screening -- CADD -- Semi-flexible & Flexible Molecular Docking -- MM-GBSA free Binding energy -- The inhibition constant (Ki) -- Molecular Dynamics -- EGFR-TKIs -- Breast & Lung Cancer -- Cannabinoids & Terpenes; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2023.e15545
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: This study examines the potential of Cannabis sativa L. plants to be repurposed as therapeutic agents for cancer treatment through designing of hybrid Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). A set of 50 phytochemicals was taken from Cannabinoids and Terpenes and subjected for screening using Semi-flexible and Flexible Molecular Docking methods, MM-GBSA free binding energy computations, and pharmacokinetic/pharmacodynamic (ADME-Tox) predictions. Nine promising phytochemicals, Cannabidiolic acid (CBDA), Cannabidiol (CBD), Tetrahydrocannabivarin (THCV), Dronabinol (Δ-9-THC), Delta-8-Tetrahydrocannabinol (Δ-8-THC), Cannabicyclol (CBL), Delta9-tetrahydrocannabinolic acid (THCA), Beta-Caryophyllene (BCP), and Gamma-Elemene (γ-Ele) were identified as potential EGFR-TKIs natural product candidates for cancer therapy. To further validate these findings, a set of Molecular Dynamics simulations were conducted over a 200 ns trajectory. This hybrid early drug discovery screening strategy has the potential to yield a new generation of EGFR-TKIs based on natural cannabis products, suitable for cancer therapy. In addition, the application of this computational strategy in the virtual screening of both natural and synthetic chemical libraries could support the discovery of a wide range of lead drug agents to address numerous diseases. Graphical abstract: Image 1 Highlights: Cannabinoids & Terpenes derived from Cannabis sativa L. screened in silico for targeting cancer via inhibiting the EGFR-TKD enzyme. Hybrid approach of structure-based & biophysical simulations to identify EGFR-TKIs.. Semi-flexible & Flexible Molecular Docking methods, Drug-like, ADME-Tox, MM-GBSA and MD used to identify stable EGFR-TKIs. The amino acid residues of Leucine, Phenylalanine, Valine, Lysine, Cysteine, & Threonine targeted for cancer cell line inhibition. In silico drug discovery identified new generation of EGFR-TKIs as candidates for target therapy. Natural substances from Cannabis sativa L. repurposed for therapeutics.