Investigating Unsequenced Enzymatic Activities: A Preliminary to Enzyme Genomics

对ENZYME数据库内容的分析表明，初步看来，1400多种酶活性（相当于38%的酶分类（EC）编号）没有已知的基因或蛋白质序列。如此大部分酶活性的序列数据的缺乏阻碍了从基因组注释到代谢工程和途径预测的许多领域的研究和生物技术。幸运的是，最近大量的完全测序的基因组的可用性，使最终识别的基因编码这些酶使用文献中的数据，结合计算和实验分析。该项目的总体目标是对与孤儿活动相关的文献进行调查，以进一步证实它们的存在不是人为的，并从这些文献中获取数据，这将有助于识别编码这些活动的基因。因此，该项目将：1）验证孤儿活性; 2）采集和传播数据，以便能够识别与孤儿活性相关的酶的编码基因; 3）将文献中发现的任何序列数据提交至UniProt数据库。调查将被应用到一个随机选择的子集孤儿活动足够大，以提供合理的坚实的结论相对于宇宙的孤儿activity.Intellectual MeritsAssessment孤儿活动的真实性：确定一个上限的人为原因孤儿活动的比率将通知决定是否继续酶基因组学计划。同样，从与孤儿活动相关的文献中提取分子特性和其他数据将有助于确定这种倡议的必要程度。基因和蛋白质序列编码以前孤儿活动的可用性将提高我们的能力，注释基因组方面的覆盖面（可识别基因的分数）和准确性（正确的预测基因功能的分数）。增强的途径预测：来自先前孤立活动的序列数据的可用性也将提高我们通过计算预测生物体代谢途径组分的能力，因为这种预测通常依赖于已知酶活性的序列数据。增强的代谢工程：这些序列数据也将增强代谢工程的实践，这也是因为它依赖于已知酶活性的序列。更广泛的影响提高数据库准确性：这项工作的成果将导致UniProt数据库（一个主要的蛋白质信息数据库）中酶序列的扩展。这项工作的结果将增加价值的酶学，其全部价值目前还没有实现，因为缺乏序列数据，并将进一步利用系统的基因组测序。

An analysis of the contents of the ENZYME database has revealed that prima facia, no gene or protein sequence is known for more than 1400 enzyme activities, corresponding to 38% of enzyme classification (EC) numbers. This lack of sequence data for such a large fraction of enzyme activities hinders research and biotechnology in a number of areas ranging from genome annotation to metabolic engineering and pathway prediction. Fortunately, the recent availability of large numbers of completely sequenced genomes enables the eventual identification of the genes encoding these enzymes using data available in the literature, combined with computational and experimental analyses. The overall goals of the project are to perform a survey of the literature associated with orphan activities to further substantiate that their existence is not artifactual, and to capture data from this literature, which would facilitate the identification of the genes encoding these activities. Thus, the project will 1) authenticate orphan activities; 2) capture and disseminate data that could enable the identification of the genes coding for enzymes associated with orphan activities; and 3) submit any sequence data found in the literature to the UniProt database. The survey will be applied to a randomly selected subset of orphan activities large enough to provide reasonably solid conclusions relative to the universe of orphan activities.Intellectual MeritsAssessment of the authenticity of orphan activities: Determining an upper bound on the rate of artifactual causes for orphan activities will inform the decision as to whether to proceed with an Enzyme Genomics Initiative. Similarly, extracting molecular properties and other data from the literature associated with orphan activities will help determine the extent to which such an Initiative is warranted.Enhanced genome annotation: The availability of gene and protein sequences encoding previously orphan activities will enhance our ability to annotate genomes in terms of both coverage (fraction of genes that can be recognized), and accuracy (fraction of predicted gene functions that are correct).Enhanced pathway prediction: The availability of sequence data from previously orphaned activities will also increase our ability to predict computationally the metabolic pathway component of organisms, since such predictions typically rely upon sequence data from known enzymatic activities.Enhanced metabolic engineering: These sequence data will also enhance the practice of metabolic engineering, again because of its dependency upon sequences from known enzymatic activities.Broader ImpactsIncreased database accuracy: The outcome of this work will result in the expansion of enzyme sequences in the UniProt Database, a major protein information database.Increased value of existing data: The results of this work will add value to a large body of enzymology whose full value is not realized currently because of the absence of sequence data, and will further leverage systematic genome sequencing.