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A COMPUTATIONAL ATLAS OF THE T BRUCEI DEGRADOME AS A GUIDE TO DRUG DISCOVERY

A COMPUTATIONAL ATLAS OF THE T BRUCEI DEGRADOME AS A GUIDE TO DRUG DISCOVERY
布鲁斯氏菌降解组的计算图谱作为药物发现的指南
批准号:
8363620
负责人:
PATRICIA CLEMENT BABBITT
金额:
$1.68万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-07-01 至 2012-06-30

项目摘要

项目成果

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中文摘要
翻译
这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的, 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量, 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 寄生虫布氏锥虫引起非洲昏睡病,每年威胁数百万人,主要是中非最贫穷的农村人口。目前,每年约有5万至7万人受到影响。这是一种致命的疾病,如果不治疗,现有的少数治疗方法有严重的副作用。迫切需要研究开发新药。蛋白酶是切割蛋白质的酶,并且已被证明是“可药物化”的靶点:也就是说,蛋白酶抑制剂已被验证为治疗HIV、糖尿病和高血压的药物。虽然预测的蛋白质序列可以从整个T.然而,在布鲁氏杆菌基因组中,这些数据还没有被注释为那些特异性药物靶标,如蛋白酶。 本项目的目标是进行深入的计算分析,通过创建基于T的序列,结构和活性位点基序的相似性的网络视图来表征布氏锥虫的降解组。布鲁氏菌蛋白酶。
英文摘要
This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The parasite Trypanosoma brucei causes African sleeping sickness and threatens millions of people per year, mostly in the poorest rural populations of Central Africa. Currently, about 50,000-70,000 people are affected per year. This is a fatal disease if untreated and the few existing treatments have serious side effects. Research is urgently needed to develop new drugs. Proteases are enzymes that cleave proteins, and have been proven to be "druggable" targets: that is, protease inhibitors have been validated as drugs to treat HIV, diabetes, and hypertension. Although predicted protein sequences are available from the entire T. brucei genome, these data have not been annotated for those that are specific drug targets, like proteases. The goals of this project are to perform an in-depth computational analysis to characterize the degradome of Trypanosoma brucei by creating network-based views based on similarities of sequence, structure, and active site motifs of T. brucei proteases.
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