Elucidation of structure-properties relationships in carboxylesterases.

在这个后基因组时代，对蛋白质中序列-结构-性质关系的理解从未像现在这样重要。目前，蛋白质纯化和鉴定的速度大大超过了存储在各种数据库中的DNA序列的数量，而我们无法使用基因组序列信息预测蛋白质的行为，这大大减缓了发现的速度。通过提高我们对控制酶特性的序列基序或签名的理解，我们将能够从基因组数据中准确地提取蛋白质特征信息，从而加速各个领域的创新，如医学研究、营养、药物合成和一些水基工业过程。这就是为什么包括我们在内的几个实验室继续进行蛋白质序列编码信息的基础研究。对羧酸酯酶(“脂肪酶”)的研究表明，这种酶可能非常适合于实现我们的基本目标，即阐明蛋白质中序列-结构-性质的关系。由于它们的相关性，芽孢杆菌羧酸酯酶共享非常相似的3D组织，但在性质上显示出很大的差异。 我们的短期目标是确定可能与单个羧酸酯酶的特定性质相关的假定序列基序。然后利用遗传手段对相关的羧酸酯酶进行修饰，以证明推测的基序与酶性质之间的关系。为此，将使用一系列分子生物学和生物信息学工具，以及各种条件下的自动化高通量酶分析。我们的长期目标是阐明序列-结构-性质的关系，以提高我们预测基因组注释所建议的可能的羧酸酯酶，以及更广泛的脂肪酶特征的能力。此外，利用这一新知识，我们希望帮助蛋白质工程师为新的工业应用开发定制的酶。

The understanding of sequence-structure-properties relationships in proteins has never been so important as in this post-genomic era. Currently, protein purification and characterisation is dramatically outpaced by the volume of DNA sequence deposited in various databanks, and our inability to predict protein behaviour using genome sequence information drastically slows the pace of discovery. By improving our understanding of sequence motifs or signatures that control enzymatic properties, we will allow the accurate extraction of protein character information from genomic data, and thus accelerate innovation in various fields, such as medical research, nutrition, drug synthesis and a number of water-based industrial processes. This is why several labs, including ours, continue their basic research on protein sequence encoded information. Investigation of carboxylesterases ("lipase") revealed that such enzymes might be well suited for achieving our fundamental goal which is the elucidation of sequence-structure-properties relationships in proteins. Because of their relatedness, Bacillacae carboxylesterases share a very similar 3D organisation, yet display large differences in their properties. Our short-term objectives are to identify putative sequence motifs that might be associated with a specific property of an individual carboxylesterase. Then related carboxylesterases will be modified by genetic means in order to demonstrate the relationship between the putative motif and the enzyme property. For that an array of molecular biology and bioinformatics tools will be used, along as robotised high-throughput enzymatic analyses under various conditions. Our long term objective is to elucidate sequence-structure-properties relationships in order to improve our ability to predict features of putative carboxylesterases, and more generally lipases, suggested by genomic annotation. Further, with this new knowledge, we hope to help protein engineers in the development of customised enzymes for novel industrial applications.