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重新定位大麻素和萜类化合物作为新型表皮生长因子受体酪氨酸激酶抑制剂(EGFR-TKIs)用于癌症靶向治疗的候选物:一种使用计算机辅助药物设计(CADD)和生物物理模拟的虚拟筛选模型

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

作者信息

Daoui Ossama, Mali Suraj N, Elkhattabi Kaouakeb, Elkhattabi Souad, Chtita Samir

机构信息

Laboratory of Engineering, Systems and Applications, National School of Applied Sciences, Sidi Mohamed Ben Abdellah-Fez University, P.O. Box 72, Fez, Morocco.

Department of Pharmaceutical Sciences and Technology, Birla Institute of Technology, Mesra, India, 835215.

出版信息

Heliyon. 2023 Apr 17;9(4):e15545. doi: 10.1016/j.heliyon.2023.e15545. eCollection 2023 Apr.

Abstract

This study examines the potential of 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.

摘要

本研究通过设计杂交表皮生长因子受体酪氨酸激酶抑制剂(EGFR-TKIs),考察了植物乳杆菌重新用作癌症治疗药物的潜力。从大麻素和萜类化合物中选取了一组50种植物化学物质,并采用半柔性和柔性分子对接方法、MM-GBSA自由结合能计算以及药代动力学/药效学(ADME-Tox)预测进行筛选。九种有前景的植物化学物质,大麻二酚酸(CBDA)、大麻二酚(CBD)、四氢大麻酚(THCV)、屈大麻酚(Δ-9-THC)、δ-8-四氢大麻酚(Δ-8-THC)、大麻环醇(CBL)、δ9-四氢大麻酚酸(THCA)、β-石竹烯(BCP)和γ-榄香烯(γ-Ele)被确定为癌症治疗中潜在的EGFR-TKIs天然产物候选物。为了进一步验证这些发现,在200 ns的轨迹上进行了一组分子动力学模拟。这种杂交早期药物发现筛选策略有可能产生基于天然大麻产品的新一代EGFR-TKIs,适用于癌症治疗。此外,这种计算策略在天然和合成化学文库虚拟筛选中的应用可以支持发现广泛的先导药物,以治疗多种疾病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdbb/10148140/c39e97825d36/ga1.jpg

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