Innovative Peptide Therapeutics for SARS-CoV-2: Design, Docking, and Functional Analysis.

IF 1.8 4区 医学 Q3 PHARMACOLOGY & PHARMACY
Iranian Journal of Pharmaceutical Research Pub Date : 2026-02-15 eCollection Date: 2026-01-01 DOI:10.5812/ijpr-160762
Samaneh Karimkhanilouei, Saeid Ghorbian, Sanaz Mahmazi, Changiz Ahmadizadeh, Keivan Nedaei
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引用次数: 0

Abstract

Background: The continuous emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants necessitates the rapid development of novel therapeutics, particularly those targeting conserved viral proteins. Peptide-based drugs offer high specificity and low toxicity, making them ideal candidates.

Objectives: This study employed an integrated computational approach, combining structural biology, molecular docking, and molecular dynamics (MD) simulations, to design and evaluate novel peptide analogs targeting three key proteins of SARS-CoV-2: the Spike (S) protein, RNA-dependent RNA polymerase (RdRp), and nucleocapsid (N) protein.

Methods: The first step involved preparing a dataset containing anti-SARS-CoV-2 peptides using the DRAVP database and a literature survey. Then, the best inhibitory peptides were screened using the AVPPred tool, and analogous peptides were designed based on the selected lead peptide. The designed peptides were then investigated in terms of their structure, physicochemical properties, and antiviral potency. Additionally, molecular docking, performed using the specialized nCoVDock2 server, showed that all designed analogs exhibited highly favorable binding. Specifically, the best-performing analogs achieved remarkable docking scores in the range of -200 to -300 a.u. (arbitrary units), indicating a strong predicted relative binding affinity for their respective targets. The top-ranked complexes were then subjected to 100 ns explicit solvent MD simulations.

Results: Our findings suggest that peptide W is the most effective analogue for inhibiting S protein, achieving a relative docking score of -303.41 a.u., in contrast to the -284.12 a.u. relative docking score of the EK1 lead peptide. Regarding the inhibition of RdRp protein, the top newly designed analogue is peptide A5, which has a relative docking score of -187.36 a.u., compared to the score of -121.3 a.u. for lead peptide 5, respectively. The leading novel analogue for inhibiting the N protein is A7, which has a relative docking score of -317.69 a.u., surpassing the relative docking score of -255.48 a.u. for Plectasin. The MD results confirmed the high dynamic stability of the W (targeting S protein) and A5 (targeting RdRp) complexes, demonstrating low Root Mean Square Deviation (RMSD) and maintaining critical hydrogen bonds and hydrophobic interactions throughout the trajectory.

Conclusions: The use of bioinformatics algorithms to develop engineered peptides with high affinity for SARS-CoV-2 virulence proteins offers a promising outlook for peptide-based therapies against SARS-CoV-2. It also presents a promising approach for developing therapeutic methods against other viral diseases. Furthermore, these computational insights lay the groundwork for subsequent in vitro and in vivo validation studies to ascertain the therapeutic efficacy and safety profiles of the identified peptide candidates.

针对SARS-CoV-2的创新肽疗法:设计、对接和功能分析
背景:严重急性呼吸综合征冠状病毒2 (SARS-CoV-2)变异的不断出现要求快速开发新的治疗方法,特别是针对保守病毒蛋白的治疗方法。肽基药物具有高特异性和低毒性,是理想的候选药物。目的:本研究采用综合计算方法,结合结构生物学、分子对接和分子动力学(MD)模拟,设计和评估针对SARS-CoV-2的三个关键蛋白:Spike (S)蛋白、RNA依赖性RNA聚合酶(RdRp)和核衣壳(N)蛋白的新型肽类似物。方法:第一步是利用DRAVP数据库和文献调查编制含有抗sars - cov -2肽的数据集。然后,使用AVPPred工具筛选最佳抑制肽,并根据选择的先导肽设计类似肽。然后对设计的肽进行结构,理化性质和抗病毒效力的研究。此外,使用专门的nCoVDock2服务器进行的分子对接表明,所有设计的类似物都表现出高度有利的结合。具体来说,表现最好的类似物在-200到-300 a.u.(任意单位)范围内取得了显著的对接分数,表明它们对各自目标具有很强的预测相对结合亲和力。然后对排名靠前的配合物进行100 ns显式溶剂MD模拟。结果:我们的研究结果表明,肽W是抑制S蛋白最有效的类似物,其相对对接评分为-303.41 a.u.,而EK1先导肽的相对对接评分为-284.12 a.u.。对于RdRp蛋白的抑制作用,新设计的类似物中排名最高的是肽A5,其相对对接评分为-187.36 a.u.,而导肽5的相对对接评分为-121.3 a.u.。抑制N蛋白的主要新类似物是A7,其相对对接分数为-317.69 a.u.,超过了Plectasin的相对对接分数-255.48 a.u.。MD结果证实了W(靶向S蛋白)和A5(靶向RdRp)复合物的高动态稳定性,显示出低均方根偏差(RMSD),并在整个轨迹中保持关键的氢键和疏水相互作用。结论:利用生物信息学算法开发与SARS-CoV-2毒力蛋白高亲和力的工程肽,为基于肽的SARS-CoV-2治疗提供了广阔的前景。它也为开发针对其他病毒性疾病的治疗方法提供了一个有希望的途径。此外,这些计算见解为随后的体外和体内验证研究奠定了基础,以确定已确定的候选肽的治疗功效和安全性。
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
CiteScore
3.40
自引率
6.20%
发文量
52
审稿时长
2 months
期刊介绍: The Iranian Journal of Pharmaceutical Research (IJPR) is a peer-reviewed multi-disciplinary pharmaceutical publication, scheduled to appear quarterly and serve as a means for scientific information exchange in the international pharmaceutical forum. Specific scientific topics of interest to the journal include, but are not limited to: pharmaceutics, industrial pharmacy, pharmacognosy, toxicology, medicinal chemistry, novel analytical methods for drug characterization, computational and modeling approaches to drug design, bio-medical experience, clinical investigation, rational drug prescribing, pharmacoeconomics, biotechnology, nanotechnology, biopharmaceutics and physical pharmacy.
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