Computer-based discovery of SIRT7 inhibitors from Nigella sativa for cancer treatment

IF 3 4区生物学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of molecular graphics & modelling Pub Date : 2025-09-16 DOI:10.1016/j.jmgm.2025.109176

Ashik Sharfaraz , Aysha Ferdoushi , Md Arju Hossain , Abida Sultana Nupur , Umme Salma , Md. Fazlul Karim

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引用次数: 0

Abstract

Background

SIRT7, a nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase, is implicated in tumorigenesis, making it a promising therapeutic target for cancer treatment.

Aim

This study aims to identify potent and selective bioactive candidate inhibitors of SIRT7 by virtually screening small-molecule compounds derived from Nigella sativa (N. sativa) and evaluating their drug-likeness and physical stability using computational methods.

Methods

The structure of SIRT7 was retrieved from the RCSB Protein Data Bank (PDB), and N. sativa-derived small molecules were obtained from the PubChem database. Molecular docking was performed using PyRx 0.8 and PyMOL version 2.3.3. Pharmacokinetic parameters and antitumor effects were assessed using SwissADME, pkCSM, and PASS analysis. Furthermore, binding stability was checked through Molecular Dynamics (MD) Simulationusing Schrödinger's Desmond v3.6 program for 100 ns.

Results

From 159 N. sativa-derived compounds, Chrysin, Pinocembrin, Nigellidine, Nigellicine, and Epicatechin showed high binding affinities (−9.3 to −8.7 kcal/mol) and favorable oral bioavailability with low toxicity. Chrysin (CID: 5281607) exhibited the strongest binding score (−9.3 kcal/mol), stable hydrogen bonding, and robust pharmacokinetic properties. PASS analysis highlighted predicted anticancer activities including TP53 activation, apoptosis induction, and antimutagenic effects, particularly for Chrysin, Pinocembrin, and Epicatechin. MD simulation confirmed stable SIRT7–Chrysin interactions, supported by favorable MM/GBSA free energy (−77.11 kcal/mol).

Conclusion

This study highlights N. sativa phytochemicals as potential SIRT7 inhibitors, with Chrysin as the lead candidate and Pinocembrin and Nigellidine as additional promising compounds. The findings offer a computational framework for future validation and development of selective SIRT7-targeted anticancer therapeutics.

Abstract Image

查看原文本刊更多论文

基于计算机的黑草SIRT7抑制剂的癌症治疗发现。

背景：SIRT7是一种烟酰胺腺嘌呤二核苷酸（NAD+）依赖的去乙酰化酶，与肿瘤发生有关，使其成为癌症治疗的一个有希望的治疗靶点。目的：本研究旨在通过虚拟筛选从黑草（Nigella sativa）中提取的小分子化合物，并使用计算方法评估其药物相似性和物理稳定性，来鉴定有效的、选择性的SIRT7候选生物活性抑制剂。方法：从RCSB蛋白数据库（PDB）中检索SIRT7的结构，从PubChem数据库中获取sativa衍生小分子。使用PyRx 0.8和PyMOL 2.3.3版本进行分子对接。采用SwissADME、pkCSM和PASS分析评估药代动力学参数和抗肿瘤作用。此外，使用Schrödinger的Desmond v3.6程序通过分子动力学（MD）模拟来检查100 ns的结合稳定性。结果：从159个植物源化合物中发现，金菊素、匹诺诺素、奈格里丁、奈格里丁和表儿茶素具有较高的结合亲和力（-9.3 ~ -8.7 kcal/mol），具有良好的口服生物利用度和低毒性。Chrysin （CID: 5281607）结合分数最高（-9.3 kcal/mol），氢键稳定，药代动力学性能良好。PASS分析强调了预测的抗癌活性，包括TP53激活、细胞凋亡诱导和抗诱变作用，特别是对菊花素、匹诺曹蛋白和表儿茶素。MD模拟证实SIRT7-Chrysin相互作用稳定，具有良好的MM/GBSA自由能（-77.11 kcal/mol）。结论：本研究强调了油菜植物化学物质可能是SIRT7的潜在抑制剂，其中Chrysin是主要候选化合物，pinpinembrin和Nigellidine是其他有前景的化合物。这些发现为未来验证和开发选择性sirt7靶向抗癌疗法提供了一个计算框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of molecular graphics & modelling 生物-计算机：跨学科应用

CiteScore

5.50

自引率

6.90%

发文量

216

审稿时长

35 days

期刊介绍： The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design. As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.