Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Pakistan.
Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Pakistan.
Microb Pathog. 2019 Mar;128:28-35. doi: 10.1016/j.micpath.2018.12.015. Epub 2018 Dec 11.
Acinetobacter baumannii, the gram-negative bacteria emerged as an extremely critical pathogen causing nosocomial and different kinds of infections. A. baumannii exhibit resistivity towards various classes of antibiotics that shows that there is a dire need to search more drug targets by exploiting the full genome of the bacteria. In doing so, a strategy is made with the combination of computational biology, pathogen informatics and cheminformatics. Comparative genomics analysis, modeling and docking studies have been performed for the prediction of non-host essential genes and novel drug candidates against A. baumannii. Among 37 unique and 82 common metabolic pathways, 92 genes were predicted as non-host genes. Similarly, using homology search between A. baumannii genome and essential genes of different bacteria, 293 genes were predicted as essential genes of A. baumannii. Among these predicted non-host and essential genes, 86 genes were predicted as non-host essential genes which could serve as potential novel drug and vaccine targets. Additional drug-target like physicochemical properties were estimated such as the molecular weight, subcellular localization and druggability potential. On the structural part, the crystal structures of all the non-host essential genes of A. baumannii were found except the three genes. Out of these three, a homology model of Undecaprenyl-diphosphatase was built using a PDB template by MODELLER [version 9.18]. The quality of the model was assessed by the ProSA and RAMPAGE. The built model was subjected as a receptor for the molecular docking with Adenosine diphosphate (ADP) as a ligand. The molecular docking was performed by AutoDock4 and the best conformation with lowest binding energy (-4.39 kcal/mol) was obtained. The LigPlot was used to identify the close interactions between the ligand the receptor's residues. This study will further aid for the selection of putative inhibitors against a novel drug target identified against A. baumannii and hence could lead to the better therapeutics.
鲍曼不动杆菌是一种革兰氏阴性细菌，已成为引起医院感染和各种感染的极其重要的病原体。鲍曼不动杆菌对各种类别的抗生素具有耐药性，这表明迫切需要通过利用细菌的全基因组来寻找更多的药物靶点。为此，采用计算生物学、病原体信息学和化学信息学相结合的策略。已经对比较基因组学分析、建模和对接研究进行了研究，以预测非宿主必需基因和针对鲍曼不动杆菌的新型药物候选物。在 37 个独特和 82 个共同代谢途径中，预测了 92 个基因是非宿主基因。同样，通过鲍曼不动杆菌基因组与不同细菌必需基因之间的同源性搜索，预测了 293 个基因是鲍曼不动杆菌的必需基因。在这些预测的非宿主和必需基因中，预测了 86 个基因是非宿主必需基因，它们可以作为潜在的新型药物和疫苗靶点。还估计了额外的药物靶点，如物理化学性质，如分子量、亚细胞定位和药物开发潜力。在结构部分，除了三个基因外，还找到了所有鲍曼不动杆菌非宿主必需基因的晶体结构。在这三个基因中，使用 PDB 模板通过 MODELLER [版本 9.18] 构建了 Undecaprenyl-diphosphatase 的同源模型。使用 ProSA 和 RAMPAGE 评估模型的质量。将构建的模型作为受体，与腺苷二磷酸 (ADP) 作为配体进行分子对接。使用 AutoDock4 进行分子对接，并获得具有最低结合能 (-4.39 kcal/mol) 的最佳构象。使用 LigPlot 识别配体与受体残基之间的紧密相互作用。这项研究将进一步有助于针对鲍曼不动杆菌新型药物靶点选择潜在抑制剂，从而为更好的治疗方法奠定基础。
