Abstract:
Streptococcus gallolyticus (Sg) is a non-motile, gram-positive bacterium that causes infective endocarditis (inflammation of the heart lining). Because Sg has gained resistance to existing antibiotics and there is currently no drug available, developing effective anti-Sg drugs is critical. This study combined core proteomics with a subtractive proteomics technique to identify potential therapeutic targets for Sg. Several bioinformatics approaches were used to eliminate non-essential and human-specific homologous sequences from the bacterial proteome. Then, virulence, druggability, subcellular localization, and functional analyses were carried out to specify the participation of significant bacterial proteins in various cellular processes. The pathogen\'s genome contained three druggable proteins, glucosamine-1phosphate N-acetyltransferase (GlmU), RNA polymerase sigma factor (RpoD), and pantetheine-phosphate adenylyltransferase (PPAT) which could serve as effective targets for developing novel drugs. 3D structures of target protein were modeled through Swiss Model. A natural product library containing 10,000 molecules from the LOTUS database was docked against therapeutic target proteins. Following an evaluation of the docking results using the glide gscore, the top 10 compounds docked against each protein receptor were chosen. LTS001632, LTS0243441, and LTS0236112 were the compounds that exhibited the highest binding affinities against GlmU, PPAT, and RpoD, respectively, among the compounds that were chosen. To augment the docking data, molecular dynamics simulations and MM-GBSA binding free energy were also utilized. More in-vitro research is necessary to transform these possible inhibitors into therapeutic drugs, though computer validations were employed in this study. This combination of computational techniques paves the way for targeted antibiotic development, which addresses the critical need for new therapeutic strategies against S. gallolyticus infections.
摘要:
溶胆链球菌(Sg)是一种非活动性的,引起感染性心内膜炎(心脏内膜炎症)的革兰氏阳性细菌。因为Sg已经对现有的抗生素产生了耐药性,而且目前还没有可用的药物,开发有效的抗Sg药物至关重要。这项研究将核心蛋白质组学与减法蛋白质组学技术相结合,以确定Sg的潜在治疗靶标。几种生物信息学方法用于从细菌蛋白质组中消除非必需和人类特异性同源序列。然后,毒力,可药用性,亚细胞定位,并进行了功能分析,以指定重要的细菌蛋白质在各种细胞过程中的参与。病原体的基因组含有三种可药用蛋白质,氨基葡萄糖-1磷酸N-乙酰转移酶(GlmU),RNA聚合酶σ因子(RpoD),泛茶磷酸腺苷酰转移酶(PPAT)可以作为开发新药的有效靶标。通过瑞士模型对靶蛋白的3D结构进行建模。将含有来自LOTUS数据库的10,000个分子的天然产物库与治疗性靶蛋白对接。在使用滑翔gscore评估对接结果之后,选择了与每种蛋白质受体对接的前10种化合物。LTS001632,LTS0243441和LTS0236112是对GlmU表现出最高结合亲和力的化合物,PPAT,还有RpoD,分别,在选择的化合物中。为了增加对接数据,还利用了分子动力学模拟和MM-GBSA结合自由能。需要更多的体外研究将这些可能的抑制剂转化为治疗药物,尽管这项研究采用了计算机验证。这种计算技术的结合为靶向抗生素的开发铺平了道路,这解决了对针对胆溶菌感染的新治疗策略的关键需求。