Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus gallolyticus

被引:2
作者
Chao, Peng [1 ]
Zhang, Xueqin [2 ]
Zhang, Lei [1 ]
Yang, Aiping [3 ]
Wang, Yong [1 ]
Chen, Xiaoyang [1 ]
机构
[1] Peoples Hosp Xinjiang Uygur Autonomous Reg, Dept Cardiol, Urumqi, Peoples R China
[2] Peoples Hosp Xinjiang Uygur Autonomous Reg, Dept Nephrol, Urumqi, Peoples R China
[3] Peoples Hosp Xinjiang Uygur Autonomous Reg, Dept Tradit Chinese Med, Urumqi, Peoples R China
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
关键词
Streptococcus gallolyticus; Endocarditis; Core proteomics; Glucosamine-1phosphate N-acetyltransferase (GlmU); RNA polymerase sigma factor (RpoD); Pantetheine-phosphate adenylyltransferase (PPAT); IN-SILICO IDENTIFICATION; INFECTIVE ENDOCARDITIS; DATABASE; SURGERY; STATES;
D O I
10.1038/s41598-024-64769-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:19
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