Targeting TNBC metastasis: In-silico identification of natural origin ROCK inhibitors via virtual screening, ADMET profiling, MM-GBSA, DFT, and molecular dynamics

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry Pub Date : 2025-09-05 DOI:10.1016/j.compbiolchem.2025.108671

Krishna Shevate , Kalirajan Rajagopal , Gowramma Byran , Apsara Unni , Justin Antony

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引用次数: 0

Abstract

Objective

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by lower survival and over 90 % of deaths from metastases. Rho-associated coiled-coil kinase (ROCK) plays a key role in TNBC progression by regulating cell motility and invasion. This study aims to identify novel ROCK inhibitors of natural origin that may suppress metastasis in TNBC, leveraging a computational drug discovery approach.

Methods

The Coconut database (1,23,971 natural compounds) was utilized for virtual screening. Further pharmacokinetic and pharmacodynamic properties were predicted using the SMARTCyp web server and the Schrodinger suite QikProp module. The top-ranking hits were further investigated using MM-GBSA binding free energy calculations, DFT analysis for electronic property evaluation, and MD simulations to assess structural stability and dynamic behavior of the ligand–protein complexes.

Results

Natural compounds (CNP0115371, CNP0232719, CNP0328678, CNP0182511, and CNP0108029) predicted to exhibit strong ROCK binding affinity (-13.18 to −12.04 kcal/mol), favorable ADMET properties, and stable interaction profiles. DFT calculations revealed high chemical reactivity and electron distribution suitable for biological interaction. MD simulations confirmed stable protein-ligand interactions over a 100-ns trajectory, supporting the compounds' potential as ROCK inhibitors. The study identified five promising naturally origin compounds as potential ROCK inhibitors with anti-metastatic relevance for TNBC treatment. These findings need further experimental validation to confirm their therapeutic efficacy and develop novel anti-TNBC agents from natural origins.

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靶向TNBC转移：通过虚拟筛选、ADMET分析、MM-GBSA、DFT和分子动力学来识别天然来源的ROCK抑制剂

目的：三阴性乳腺癌（TNBC）是一种侵袭性乳腺癌亚型，其特点是生存率较低，90%以上的患者死于转移。rho相关的卷曲卷曲激酶（ROCK）通过调节细胞运动和侵袭在TNBC的进展中起关键作用。本研究旨在利用计算药物发现方法，鉴定可能抑制TNBC转移的天然来源的新型ROCK抑制剂。方法利用Coconut数据库（1,23,971个天然化合物）进行虚拟筛选。进一步的药代动力学和药效学性质预测使用SMARTCyp web服务器和薛定谔套件QikProp模块。利用MM-GBSA结合自由能计算、DFT分析评估电子性质、MD模拟评估配体-蛋白质复合物的结构稳定性和动力学行为，对排名靠前的命中物进行了进一步研究。结果天然化合物CNP0115371、CNP0232719、CNP0328678、CNP0182511和CNP0108029具有较强的ROCK结合亲和力（-13.18 ~−12.04 kcal/mol）、良好的ADMET性质和稳定的相互作用谱。DFT计算显示出高的化学反应性和适合生物相互作用的电子分布。MD模拟证实了在100-ns的轨道上稳定的蛋白质-配体相互作用，支持了化合物作为ROCK抑制剂的潜力。该研究确定了五种有希望的天然来源化合物作为潜在的ROCK抑制剂，与TNBC治疗的抗转移相关。这些发现需要进一步的实验验证，以确认其治疗效果，并从天然来源开发新的抗tnbc药物。

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

Computational Biology and Chemistry 生物-计算机：跨学科应用

CiteScore

6.10

自引率

3.20%

发文量

142

审稿时长

24 days

期刊介绍： Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.