Oany Arafat Rahman, Mia Mamun, Pervin Tahmina, Hasan Md Nazmul, Hirashima Akinori
1Department of Biotechnology and Genetic Engineering, Life Science Faculty, Mawlana Bhashani Science and Technology University, Tangail, 1902 Bangladesh.
2Biotechnology and Genetic Engineering Discipline, Life Science School, Khulna University, Khulna, Bangladesh.
In Silico Pharmacol. 2018 Jun 4;6(1):11. doi: 10.1007/s40203-018-0048-2. eCollection 2018.
2a is one of the most pathogenic bacteria among the spp., which is responsible for dysentery and causes masses of deaths throughout the world per year. A proper identification of the potential drug targets and inhibitors is crucial for the treatment of the shigellosis due to their emerging multidrug resistance (MDR) patterns. In this study, a systematic subtractive approach was implemented for the identification of novel therapeutic targets of 2a (301) through genome-wide metabolic pathway analysis of the essential genes and proteins. Ligand-based virtual screening and ADMET analyses were also made for the identification of potential inhibitors as well. Initially, we found 70 essential unique proteins as novel targets. After subsequent prioritization, finally we got six unique targets as the potential therapeutic targets and their three-dimensional models were built thereafter. Aspartate-β-semialdehyde dehydrogenase (ASD), was the most potent target among them and used for docking analysis through ligand-based virtual screening. The compound 3 (PubChem CID: 11319750) suited well as the best inhibitor of the ASD through ADMET and enzyme inhibition capacity analysis. To end, we hope that our proposed therapeutic targets and its inhibitors might give some breakthrough to treat shigellosis efficiently in in vitro.
宋内志贺菌2a是志贺菌属中致病性最强的细菌之一,可引发痢疾,每年在全球导致大量死亡。鉴于其新出现的多重耐药模式,正确识别潜在的药物靶点和抑制剂对于治疗志贺菌病至关重要。在本研究中,通过对必需基因和蛋白质进行全基因组代谢途径分析,采用系统的消减方法来识别宋内志贺菌2a(301)的新型治疗靶点。还进行了基于配体的虚拟筛选和ADMET分析以识别潜在抑制剂。最初,我们发现70种必需的独特蛋白质作为新靶点。经过后续的优先级排序,最终我们得到六个独特靶点作为潜在治疗靶点,并随后构建了它们的三维模型。天冬氨酸-β-半醛脱氢酶(ASD)是其中最有效的靶点,并通过基于配体的虚拟筛选用于对接分析。通过ADMET和酶抑制能力分析,化合物3(PubChem CID:11319750)作为ASD的最佳抑制剂表现良好。最后,我们希望我们提出的治疗靶点及其抑制剂可能会为体外有效治疗志贺菌病带来一些突破。