In silico analysis of the interaction of de novo peptides derived from Salvia hispanica with anticancer targets

生物信息学 保健品 化学 计算生物学 对接(动物) 体内 癌症 癌细胞 生物 生物化学 医学 生物技术 遗传学 基因 护理部
作者
Nidia del Carmen Quintal Bojórquez,Luis Fernando Morales-Mendoza,Sergio Hidalgo‐Figueroa,Alan Javier Hernández‐Álvarez,Maira Rubí Segura Campos
出处
期刊:Journal of Biomolecular Structure & Dynamics [Taylor & Francis]
卷期号:42 (12): 6119-6135 被引量:2
标识
DOI:10.1080/07391102.2023.2232045
摘要

Cancer is one of the leading causes of death worldwide. Conventional cancer therapies are not selective to cancer cells resulting in serious side effects on patients. Thus, the need for complementary treatments that improve the patient's response to cancer therapy is highly important. To predict and evaluate the physicochemical characteristics and potential anticancer activity of the peptides identified from S. hispanica protein fraction <1 kDa through the use of in silico tools. Peptides derived from Salvia hispanica's protein fraction <1 kDa were identified and analyzed for the prediction of their physicochemical properties. The characterized peptide sequences were then submitted to a multi-criteria decision analysis to identify the peptides that possess the characteristics to potentially exert anticancer activity. Through molecular docking analysis, the potential anticancer activity of the Potentially Anticancer Peptide (PAP)-1, PAP-2, PAP-3, PAP-4, and PAP-5 was estimated by their binding interactions with cancer and apoptosis-related molecules. All five evaluated PAPs exhibited strong binding interactions (< −100 kcal/mol). However, PAP-3 showed the lowest binding free energies with several of the targets. Thus, PAP-3 shows potential to be used as a nutraceutical or ingredient for functional foods that adjuvate in cancer treatment. Conclusions: Through the molecular docking studies, the binding of the PAPs to target molecules of interest for cancer treatment was successfully simulated, from which PAP-3 exhibited the lowest binding free energies. Further in vitro and in vivo studies are required to validate the predictions obtained by the in silico analysis.Communicated by Ramaswamy H. Sarma
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