Department of Biochemistry, Biotechnology, and Bioinformatics, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India.
Department of Chemistry, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India.
J Mol Model. 2023 Jul 20;29(8):258. doi: 10.1007/s00894-023-05647-9.
Staphylococcus aureus is a highly pathogenic organism that is the most common cause of postoperative complications as well as severe infections like bacteremia and infective endocarditis. By mediating the formation of biofilms and the expression of virulent genes, the quorum sensing (QS) mechanism is a major contributor to the development of these diseases. By hindering its QS network, an innovative approach to avoiding this bacterial infection is taken. Targeting the AgrA of the Agr system serves as beneficial in holding the top position in the QS system cascade.
Using known AgrA inhibitors, the machine learning algorithms (artificial neural network, naïve Bayes, random forest, and support vector machine) and pharmacophore model were developed. The potential lead compounds were screened against the Zinc and COCONUT databases using the best pharmacophore hypothesis. The hits were then subjected second screening process using the best machine learning model. The predicted active compounds were then reranked based on the docking score. The stability of AgrA-lead compounds was studied using molecular dynamics approaches, and an ADME profile was also carried out. Five lead compounds, namely, CNP02386963,4,5-trihydroxy-2-[({7,13,14-trihydroxy-3,10-dioxo-2,9-dioxatetracyclo[6.6.2.0,.0,]hexadeca-1(14),4,6,8(16),11(15),12-hexaen-6-yl}oxy)methyl]benzoic acid, CNP0129274 4-(dimethylamino)-1,5,6,10,12,12a-hexahydroxy-6-methyl-3,11-dioxo-3,4,4a,5,5a,6,11,12a-octahydrotetracene-2-carboxamide, CNP0242717 3-Hydroxyasebotin, CNP0361624 3,4,5-trihydroxy-6-[(2,4,5,6,7-pentahydroxy-1-oxooctan-3-yl)oxy]oxane-2-carboxylic acid, and CNP0285058 2-{[4,5-dihydroxy-6-(hydroxymethyl)-3-[(3,4,5-trihydroxy-6-methyloxan-2-yl)oxy]oxan-2-yl]oxy}-2-(4-hydroxyphenyl)acetonitrile were obtained using the two-step virtual screening process. The molecular dynamics study revealed that the CNP0238696 was found to be stable in the binding pocket of AgrA. ADME profiles show that this compound has two Lipinski violations and low bioavailability. Further studies should be performed to assess the anti-biofilm activity of the lead compound in vitro.
金黄色葡萄球菌是一种高度致病性的生物体，是术后并发症以及菌血症和感染性心内膜炎等严重感染的最常见原因。群体感应 (QS) 机制通过介导生物膜的形成和毒力基因的表达，是这些疾病发展的主要因素。通过阻碍其 QS 网络，避免这种细菌感染的创新方法被采用。靶向 Agr 系统的 AgrA 在 QS 系统级联中占据有利地位。
使用已知的 AgrA 抑制剂，开发了机器学习算法（人工神经网络、朴素贝叶斯、随机森林和支持向量机）和药效团模型。使用最佳药效团假设，从 Zinc 和 COCONUT 数据库中筛选潜在的先导化合物。然后，使用最佳机器学习模型对命中物进行第二轮筛选。根据对接评分对预测的活性化合物进行重新排序。使用分子动力学方法研究 AgrA-先导化合物的稳定性，并进行 ADME 分析。得到了五个先导化合物，即 CNP02386963,4,5-三羟基-2-[[（7,13,14-三羟基-3,10-二氧代-2,9-二氧杂-6,6,2.0,.0,]十六烷-1(14)，4,6,8(16)，11(15)，12-六烯-6-基）氧基甲基]苯甲酸、CNP0129274 4-（二甲氨基）-1,5,6,10,12,12a-六氢-6-甲基-3,11-二氧代-3,4,4a,5,5a,6,11,12a-八氢并四苯-2-羧酰胺、CNP0242717 3-羟基酶博丁、CNP0361624 3,4,5-三羟基-6-[[（2,4,5,6,7-五羟基-1-氧代辛烷-3-基）氧基]氧基]六烷-2-羧酸和 CNP0285058 2-[[4,5-二羟基-6-（羟甲基）-3-[[（3,4,5-三羟基-6-甲氧基-2-氧代-2-丁基）氧基]氧基]氧代-2-丁基]氧基]-2-（4-羟基苯基）乙腈，使用两步虚拟筛选过程得到。分子动力学研究表明，CNP0238696 被发现稳定在 AgrA 的结合口袋中。ADME 分析表明，该化合物有两个 Lipinski 违反和低生物利用度。应进一步研究以评估先导化合物在体外的抗生物膜活性。
