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采用反向虚拟筛选方法鉴定灵菌红素治疗乳腺癌的新型蛋白靶标。

Identification of Novel Protein Targets of Prodigiosin for Breast Cancer Using Inverse Virtual Screening Methods.

机构信息

Department of Chemical Engineering, National Institute of Technology, Agartala, 799046, India.

Department of Computer Science and Engineering, National Institute of Technology, Agartala, 799046, India.

出版信息

Appl Biochem Biotechnol. 2023 Dec;195(12):7236-7254. doi: 10.1007/s12010-023-04426-9. Epub 2023 Mar 29.

Abstract

Prodigiosin (PG) is chemically formulated as 4-methoxy-5-[(5-methyl-4-pentyl-2H-pyrrol-2ylidene)methyl]-2,2'-bi-1H-pyrrole and it is an apoptotic agent. Only a few protein targets for PG have been identified so far for regulating various diseases; nevertheless, finding more PG targets is crucial for novel drug discovery research. A bioinformatics method was applied in this work to find additional potential PG targets. Initially, a text mining analysis was conducted to determine the relationship between PG and a variety of metabolic processes. One hundred sixteen proteins from the KEGG pathway were selected for the docking study. Inverse virtual screening was performed by Discovery Studio software 4.1 using CHARMm-based docking tool. Twelve proteins are screened out of 116 because their CDOCKER interaction energy is larger than - 40.22 kcal/mol. The best docking score with PG was reported to be - 44.25 kcal/mol, - 44.99 kcal/mol, and - 40.91 kcal/mol for three novel proteins, such as human epidermal growth factor-2 (HER-2), mitogen-activated protein kinase (MEK), and S6 kinase protein (S6K) respectively. The interactions in the S6K/PG complex are predominantly hydrophobic; however, hydrogen bond interactions can be identified in the MEK/PG and HER-2/PG complexes. The root-mean-square deviation (RMSD) and key interaction score system (KISS) were further used to validate the docking approach. The docking approach employed in this work has a low RMSD value (2.44 Å) and a high KISS score (0.5), indicating that it is significant.

摘要

灵菌红素(PG)的化学式为 4-甲氧基-5-[(5-甲基-4-戊基-2H-吡咯-2-亚基)甲基]-2,2'-联-1H-吡咯,是一种凋亡剂。目前为止,仅发现了少数 PG 调节各种疾病的蛋白质靶标;然而,寻找更多的 PG 靶标对于新药发现研究至关重要。本工作应用生物信息学方法寻找额外的潜在 PG 靶标。首先,进行文本挖掘分析以确定 PG 与多种代谢过程的关系。选择 KEGG 途径中的 116 种蛋白质进行对接研究。使用 Discovery Studio 软件 4.1 中的 CHARMm 基于对接工具进行反向虚拟筛选。从 116 种蛋白质中筛选出 12 种蛋白质,因为它们的 CDOCKER 相互作用能大于-40.22 kcal/mol。与 PG 结合的最佳对接评分分别为-44.25 kcal/mol、-44.99 kcal/mol 和-40.91 kcal/mol,用于三种新蛋白,如人表皮生长因子-2(HER-2)、丝裂原活化蛋白激酶(MEK)和 S6 激酶蛋白(S6K)。S6K/PG 复合物中的相互作用主要是疏水的;然而,在 MEK/PG 和 HER-2/PG 复合物中可以识别氢键相互作用。进一步使用均方根偏差(RMSD)和关键相互作用评分系统(KISS)验证对接方法。本工作中使用的对接方法具有较低的 RMSD 值(2.44 Å)和较高的 KISS 评分(0.5),表明其意义重大。

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