'Unknown' proteins and 'orphan' enzymes: the missing half of the engineering parts list - and how to find it

被引:143
作者
Hanson, Andrew D. [1 ]
Pribat, Anne [1 ]
Waller, Jeffrey C. [1 ]
de Crecy-Lagard, Valerie [2 ]
机构
[1] Univ Florida, Dept Hort Sci, Gainesville, FL 32611 USA
[2] Univ Florida, Dept Microbiol & Cell Sci, Gainesville, FL 32611 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
comparative genomics; metabolic reconstruction; orphan enzyme; pathway hole; unknown protein; DIHYDRONEOPTERIN TRIPHOSPHATE; METABOLIC RECONSTRUCTION; CHOLINE MONOOXYGENASE; ESCHERICHIA-COLI; BIOCHEMICAL NETWORKS; NAD BIOSYNTHESIS; GENE CLUSTERS; GENOME; SCALE; EVOLUTION;
D O I
10.1042/BJ20091328
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Like other forms of engineering, metabolic engineering requires knowledge of the components (the 'parts list') of the target system. Lack of such knowledge impairs both national engineering design and diagnosis of the reasons for failures; it also poses problems for the related field of metabolic reconstruction, which uses a cell's parts list to recreate its metabolic activities in silico. Despite spectacular progress in genome sequencing, the parts lists for most organisms that we seek to manipulate remain highly incomplete, due to the dual problem of 'unknown' proteins and 'orphan' enzymes. The former are all the proteins deduced from genome sequence that have no known function, and the latter are all the enzymes described in the literature (and often catalogued in the EC database) for which no cot-responding gene has been reported. Unknown proteins constitute up to about half of the proteins in prokaryotic genomes, and much more than this in higher plants and animals. Orphan enzymes make up more than a third of the EC database. Attacking the 'missing parts list' problem is accordingly one of the great challenges for post-genomic biology, and a tremendous opportunity to discover new facets of life's machinery. Success will require a co-ordinated community-wide attack, sustained over years. lit this attack, comparative genomics is probably the single most effective strategy, for it can reliably predict functions for unknown proteins and genes for orphan enzymes. Furthermore, it is cost-efficient and increasingly straightforward to deploy owing to a proliferation of databases and associated tools,
引用
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页码:1 / 11
页数:11
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