Department of Chemical Engineering, National Institute of Technology, Agartala, 799046, India.
Department of Computer Science and Engineering, National Institute of Technology, Agartala, 799046, India.
Appl Biochem Biotechnol. 2023 Dec;195(12):7236-7254. doi: 10.1007/s12010-023-04426-9. Epub 2023 Mar 29.
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.
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。