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针对潜在药物靶点对伯克霍尔德菌基因组序列进行计算机分析。

In silico analysis of Burkholderia pseudomallei genome sequence for potential drug targets.

作者信息

Chong Chan-Eng, Lim Boon-San, Nathan Sheila, Mohamed Rahmah

机构信息

School of Biosciences and Biotechnology, Faculty of Science and Technology, University Kebangsaan Malaysia, 43600 Bangi, Malaysia.

出版信息

In Silico Biol. 2006;6(4):341-6.

PMID:16922696
Abstract

Recent advances in DNA sequencing technology have enabled elucidation of whole genome information from a plethora of organisms. In parallel with this technology, various bioinformatics tools have driven the comparative analysis of the genome sequences between species and within isolates. While drawing meaningful conclusions from a large amount of raw material, computer-aided identification of suitable targets for further experimental analysis and characterization, has also led to the prediction of non-human homologous essential genes in bacteria as promising candidates for novel drug discovery. Here, we present a comparative genomic analysis to identify essential genes in Burkholderia pseudomallei. Our in silico prediction has identified 312 essential genes which could also be potential drug candidates. These genes encode essential proteins to support the survival of B. pseudomallei including outer-inner membrane and surface structures, regulators, proteins involved in pathogenenicity, adaptation, chaperones as well as degradation of small and macromolecules, energy metabolism, information transfer, central/intermediate/miscellaneous metabolism pathways and some conserved hypothetical proteins of unknown function. Therefore, our in silico approach has enabled rapid screening and identification of potential drug targets for further characterization in the laboratory.

摘要

DNA测序技术的最新进展使得人们能够阐明众多生物体的全基因组信息。与这项技术同步发展的是,各种生物信息学工具推动了物种间以及分离株内部基因组序列的比较分析。在从大量原始数据得出有意义结论的同时,通过计算机辅助识别适合进一步实验分析和表征的靶点,还促成了对细菌中非人类同源必需基因的预测,这些基因有望成为新型药物发现的候选对象。在此,我们进行了一项比较基因组分析,以鉴定伯克霍尔德菌属假鼻疽杆菌中的必需基因。我们的计算机模拟预测已确定了312个必需基因,它们也可能是潜在的药物候选对象。这些基因编码支持假鼻疽杆菌生存的必需蛋白质,包括外膜和内膜及表面结构、调节因子、参与致病性、适应性的蛋白质、伴侣蛋白以及小分子和大分子的降解蛋白、能量代谢、信息传递、中心/中间/其他代谢途径,还有一些功能未知的保守假设蛋白。因此,我们的计算机模拟方法能够快速筛选和鉴定潜在的药物靶点,以便在实验室中进行进一步表征。

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