An integrated theoretical study on natural alkaloids as SARS-CoV-2 main protease inhibitors: a step toward discovery of potential drug candidates with anti-COVID-19 activity†
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引用次数: 0
Abstract
Background: in the twenty-first century, the emergence of COVID-19 as a highly transmissible pandemic disease caused by SARS-CoV-2 posed a significant threat to humanity. Aims & Objectives: the disease spreads through small respiratory droplets, necessitating the use of various compounds for treatment, with alkaloids being recognized as particularly crucial owing to their diverse pharmaceutical properties. Methodology: in this study, a dataset comprising 100 natural alkaloids obtained from the literature was transformed into 2D chemical structures using Chem Draw 19.1. Subsequently, 3DQSAR studies were conducted on the dataset, resulting in the automatic screening of 50 compounds from the initial pool of 100 compounds. The values of q2 and r2 of the validated field-based 3DQSAR model were 0.7186 and 0.971, respectively. The validated atom-based 3DQSAR model has q2 and r2 scores of 0.6025 and 0.9845, respectively. Based on the obtained results, 10 compounds with exceptionally active predictive IC50 values were selected for further analysis. Docking experiments were then performed on the selected compounds, and the top three compounds with the highest docking scores were identified as diazepinomicin, (+)-N-methylisococlaurine, and hymenocardine-H. After docking, MM–GBSA was performed on the complexes of diazepinomicin, (+)-N-methylisococlaurine and hymenocardine-H with their corresponding proteins, which resulted in the authentication of the molecular docking scores. MD simulations were also performed to check the flexibility, stability and compactness of these complexes for revalidation of docking scores. Results: finally, ADMET experiments revealed that (+)-N-methylisococlaurine exhibited the most favourable properties among these three compounds.
背景:在21世纪,COVID-19作为由SARS-CoV-2引起的高度传染性大流行疾病的出现对人类构成了重大威胁。的目标是,目标:该病通过呼吸道小飞沫传播,需要使用各种化合物进行治疗,生物碱因其多种药物特性而被认为特别重要。方法:在本研究中,使用Chem Draw 19.1将从文献中获得的包含100种天然生物碱的数据集转换为二维化学结构。随后,对数据集进行3DQSAR研究,从最初的100个化合物池中自动筛选出50个化合物。经验证的基于场的3DQSAR模型q2和r2分别为0.7186和0.971。经验证的基于原子的3DQSAR模型q2和r2得分分别为0.6025和0.9845。根据获得的结果,选择10个具有异常活性预测IC50值的化合物进行进一步分析。然后对所选化合物进行对接实验,确定对接得分最高的前3个化合物为:diazepinomicin、(+)- n - methylisococlurine和hymenocardine-H。对接后,对diazepinomicin、(+)- n - methylisococlurine和hymenocardine-H配合物与其对应的蛋白进行MM-GBSA,验证分子对接评分。MD模拟也用于检查这些复合物的灵活性、稳定性和紧凑性,以重新验证对接分数。结果:最后,ADMET实验表明(+)- n -甲基异氯尿在这三种化合物中表现出最有利的性质。
期刊介绍:
An international, peer-reviewed journal covering all of the chemical sciences, including multidisciplinary and emerging areas. RSC Advances is a gold open access journal allowing researchers free access to research articles, and offering an affordable open access publishing option for authors around the world.