Parveen Shagufta, Shahbaz Laiba, Shafiq Nusrat, Rashid Maryam, Mohany Mohamed, Zhu Mingkun
Synthetic and Natural Products Discovery (SNPD) Laboratory, Department of Chemistry, Government College Women University Faisalabad-38000 Pakistan
Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University P.O. Box 55760 Riyadh 11451 Saudi Arabia
RSC Adv. 2025 Jan 22;15(3):2045-2065. doi: 10.1039/d4ra06536k. eCollection 2025 Jan 16.
: 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. : 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. : 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 and of the validated field-based 3DQSAR model were 0.7186 and 0.971, respectively. The validated atom-based 3DQSAR model has and scores of 0.6025 and 0.9845, respectively. Based on the obtained results, 10 compounds with exceptionally active predictive IC 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, (+)--methylisococlaurine, and hymenocardine-H. After docking, MM-GBSA was performed on the complexes of diazepinomicin, (+)--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. : finally, ADMET experiments revealed that (+)--methylisococlaurine exhibited the most favourable properties among these three compounds.
在21世纪,由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的新型冠状病毒肺炎(COVID-19)作为一种高传染性大流行病的出现,对人类构成了重大威胁。该疾病通过微小呼吸道飞沫传播,因此需要使用各种化合物进行治疗,生物碱因其多样的药学性质而被认为尤为关键。在本研究中,利用Chem Draw 19.1将从文献中获取的包含100种天然生物碱的数据集转化为二维化学结构。随后,对该数据集进行了三维定量构效关系(3DQSAR)研究,从最初的100种化合物中自动筛选出50种化合物。经过验证的基于场的3DQSAR模型的 和 值分别为0.7186和0.971。经过验证的基于原子的3DQSAR模型的 和 分数分别为0.6025和0.9845。根据所得结果,选择了10种预测IC值异常活跃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,对接分数最高的前三种化合物被确定为重氮霉素、(+)-去甲异紫堇定和海膜心卡品-H。对接后,对重氮霉素、(+)-去甲异紫堇定和海膜心卡品-H与其相应蛋白质的复合物进行了MM-GBSA计算,从而验证了分子对接分数。还进行了分子动力学(MD)模拟,以检查这些复合物的灵活性、稳定性和紧密性,从而重新验证对接分数。最后,药物代谢及药物动力学(ADMET)实验表明,(+)-去甲异紫堇定在这三种化合物中表现出最有利的性质。