The drug discovery candidate for targeting PARP1 with Onosma. Dichroantha compounds in triple-negative breast cancer: A virtual screening and molecular dynamic simulation

IF 3.1 4区 生物学 Q2 BIOLOGY Computational Biology and Chemistry Pub Date : 2025-04-15 DOI:10.1016/j.compbiolchem.2025.108471
Mohamed J. Saadh , Hanan Hassan Ahmed , Radhwan Abdul Kareem , Muktesh Chandra , Lokesh Verma , G.V. Siva Prasad , Anurag Mishra , Waam Mohammed Taher , Mariem Alwan , Mahmood Jasem Jawad , Atheer Khdyair Hamad
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Abstract

Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by the overexpression of poly-ADP ribose polymerase 1 (PARP1), a key enzyme in DNA repair. Targeting PARP1 with inhibitors presents a promising therapeutic strategy, particularly given the limited treatment options for TNBC. This study employed in silico methodologies to evaluate the pharmacokinetic and inhibitory potential of FDA-approved drugs and compounds derived from Onosma. dichroantha root extracts against PARP1. Virtual screening and molecular docking identified Midazolam, Olaparib, Beta-sitosterol, and 1-Hexyl-4-nitrobenzene as top candidates, exhibiting strong binding affinities of −10.6 kcal/mol, −9.9 kcal/mol, −6.83 kcal/mol, and −5.53 kcal/mol respectively. Molecular dynamics simulations (MDS) over 100 nanoseconds revealed that Beta-sitosterol formed the most stable complex with PARP1, demonstrating minimal structural deviations and robust hydrogen bonding. The Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) analysis further confirmed Beta-Sitosterol and Olaparib superior binding free energy (ΔGbind= −175.43 kcal/mol and –180.8 kcal/mol respectively), highlighting its potential as a potent PARP1 inhibitor. ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling indicated that Beta-Sitosterol adheres to Lipinski's Rule of Five, with high intestinal absorption (95.88 %) and blood-brain barrier permeability (0.824), despite low water solubility. Protein-protein interaction analysis identified key PARP1-associated proteins, including CASP3, CASP7, and XRCC1, suggesting broader therapeutic implications. These findings underscore the potential of Beta-Sitosterol as a novel PARP1 inhibitor for TNBC treatment, combining computational validation with favorable pharmacokinetic properties. The study also highlights the utility of drug repurposing and plant-derived compounds in developing targeted therapies for TNBC, paving the way for further preclinical and clinical investigations.
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Onosma靶向PARP1的候选药物发现。三阴性乳腺癌中的双棘豆化合物:虚拟筛选和分子动力学模拟
三阴性乳腺癌(TNBC)是一种侵袭性亚型,其特征是多adp核糖聚合酶1 (PARP1)过表达,PARP1是DNA修复的关键酶。用抑制剂靶向PARP1是一种很有前景的治疗策略,特别是考虑到TNBC的治疗选择有限。本研究采用计算机方法评估fda批准的Onosma衍生药物和化合物的药代动力学和抑制潜力。双棘根提取物对PARP1的抑制作用。虚拟筛选和分子对接发现,咪达唑兰、奥拉帕尼、β -谷甾醇和1-己基-4-硝基苯是最理想的候选药物,它们的结合亲和度分别为−10.6 kcal/mol、−9.9 kcal/mol、−6.83 kcal/mol和−5.53 kcal/mol。超过100纳秒的分子动力学模拟(MDS)表明,β -谷甾醇与PARP1形成了最稳定的复合物,具有最小的结构偏差和强大的氢键。分子力学-泊松-玻尔兹曼表面积(MM-PBSA)分析进一步证实了β -谷甾醇和奥拉帕尼具有较好的结合自由能(ΔGbind= - 175.43 kcal/mol和-180.8 kcal/mol),突出了其作为PARP1有效抑制剂的潜力。ADMET(吸收、分布、代谢、排泄和毒性)分析表明,β -谷甾醇符合利平斯基五定律,尽管水溶性较低,但具有较高的肠道吸收率(95.88 %)和血脑屏障通透性(0.824)。蛋白-蛋白相互作用分析鉴定出关键的parp1相关蛋白,包括CASP3、CASP7和XRCC1,提示更广泛的治疗意义。这些发现强调了β -谷甾醇作为一种新型PARP1抑制剂治疗TNBC的潜力,结合了计算验证和良好的药代动力学特性。该研究还强调了药物再利用和植物衍生化合物在开发TNBC靶向治疗中的效用,为进一步的临床前和临床研究铺平了道路。
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来源期刊
Computational Biology and Chemistry
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.
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