Algorithmic assignment of probable function to proteins of previously unknown fun

将可能功能分配给先前未知的蛋白质的算法

基本信息

批准号：
8898934
负责人：
Herbert J. Bernstein
金额：
$ 1.58万
依托单位：
DOWLING COLLEGE
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-08-01 至 2015-08-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Algorithmic assignment of probable function to proteins of previously unknown function Objectives and Specific Aims: The goal of this project is to extend and apply algorithms that show promise in assigning a probable function for PDB entries of currently unknown function. This should contribute to deriving benefit from the Protein Structure Initiative by "help[ing] researchers illuminate structure-function relationships and thus formulate better hypotheses and design better experiments." Research Design and Methods: New protein structures are being determined at a rate faster than their biological function can be assigned. There are currently 2939 entries in the Protein Data Bank with the classification "Unknown Function". A number of computational methods have been developed to provide rapid, inexpensive means of function prediction for these structures, including those that focus on alignment of entire backbones and others that focus on identification and alignment of active site residues based on the unusual charge distributions in protein structures. We have developed a software plug-in for the PyMOL molecular graphics environment called ProMOL that relies on the geometric relationships conserved in enzyme catalytic sites. Motifs in ProMOL were created from the active site specifications found in the Catalytic Site Atlas (CSA) (http://www.ebi.ac.uk/thornton-srv/databases/CSA/). Our approach explicitly searches for CSA- defined catalytic site residues according to specific atomic geometry, similar in concept to the CSA JESS templates. This dispenses with the need to filter out confounding elements such as conserved folding domains or ligand binding regions. Extensive testing of structural files from the serine protease and peroxidase families confirmed that the geometric relationships of catalytic residues alone are effective and sufficient for function prediction in protein structures. In addition to extensive characterization of serine proteases and peroxidases, we also performed a preliminary study of 39 PDB entries classified as "Structural Genomics, Unknown Function" using the Motif Finder in ProMOL, which contains 22 "native" ProMOL motifs, along with the corresponding CSA JESS C1C2 motifs and CSA Functional Atom motifs. Of the 39 entries studied, 26 (67%) yielded prediction values of 1 (exact match to an existing template). An active site lacking one residue or containing an extra (outlier) residue was identified for 36 (92%) of the structures. No match was reported in only three of the test cases. We will extend the number of motifs in ProMOL's Motif Finder, using both newly created ProMOL motifs and existing JESS motifs to include representatives from the most prominent protein families, increase automation of the process and then evaluate all PDB entries described as having "unknown function". Entries that show positive correlation will then be further explored using sequence and structure alignment tools. Both software and results will be openly released to the community.

描述（由申请人提供）：对先前未知功能的蛋白质进行可能功能的算法分配目标和具体目标：该项目的目标是扩展和应用算法，这些算法有望为当前未知功能的 PDB 条目分配可能的功能。通过“帮助研究人员阐明结构与功能的关系，从而制定更好的假设并设计更好的实验”，这应该有助于从蛋白质结构计划中获益。研究设计和方法：新蛋白质结构的确定速度快于其生物学功能的确定速度。目前蛋白质数据库中有 2939 个条目，分类为“未知功能”。已经开发了许多计算方法来为这些结构提供快速、廉价的功能预测方法，包括那些专注于整个主链对齐的方法和其他专注于基于蛋白质中不寻常电荷分布的活性位点残基的识别和对齐的方法结构。我们为 PyMOL 分子图形环境开发了一个名为 ProMOL 的软件插件，它依赖于酶催化位点中保守的几何关系。 ProMOL 中的主题是根据 Catalytic Site Atlas (CSA) (http://www.ebi.ac.uk/thornton-srv/databases/CSA/) 中的活动位点规范创建的。我们的方法根据特定的原子几何形状明确搜索 CSA 定义的催化位点残基，其概念与 CSA JESS 模板类似。这样就无需过滤掉保守的折叠结构域或配体结合区域等混杂元素。对丝氨酸蛋白酶和过氧化物酶家族的结构文件的广泛测试证实，仅催化残基的几何关系对于蛋白质结构的功能预测来说是有效且充分的。除了对丝氨酸蛋白酶和过氧化物酶进行广泛表征之外，我们还使用 ProMOL 中的基序查找器对归类为“结构基因组学，未知功能”的 39 个 PDB 条目进行了初步研究，其中包含 22 个“天然”ProMOL 基序以及相应的CSA JESS C1C2 基序和 CSA 功能原子基序。在研究的 39 个条目中，26 个 (67%) 产生的预测值为 1（与现有模板完全匹配）。 36 个（92%）的结构被鉴定为缺乏一个残基或含有额外（异常）残基的活性位点。只有三个测试用例没有报告匹配。我们将使用新创建的 ProMOL 基序和现有的 JESS 基序来扩展 ProMOL 基序查找器中的基序数量，以包括来自最著名的蛋白质家族的代表，提高过程的自动化程度，然后评估所有被描述为具有“未知功能”的 PDB 条目。然后，将使用序列和结构比对工具进一步探索显示正相关的条目。软件和结果都将向社区公开发布。

项目成果

期刊论文数量（13）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Efficient molecular surface rendering by linear-time pseudo-Gaussian approximation to Lee-Richards surfaces (PGALRS).

通过 Lee-Richards 表面的线性时间伪高斯近似 (PGALRS) 进行高效的分子表面渲染。

DOI：
发表时间：
2010-04-01
期刊：
影响因子：
6.1
作者：
Bernstein, Herbert J;Craig, Paul A
通讯作者：
Craig, Paul A

NearTree, a data structure and a software toolkit for the nearest-neighbor problem.

NearTree，一种用于最近邻问题的数据结构和软件工具包。

DOI：
发表时间：
2016-06-01
期刊：
影响因子：
6.1
作者：
Andrews, Lawrence C;Bernstein, Herbert J
通讯作者：
Bernstein, Herbert J

Annotation of proteins of unknown function: initial enzyme results.

未知功能蛋白质的注释：初始酶结果。

DOI：
发表时间：
2015-03
期刊：
影响因子：
0
作者：
McKay, Talia;Hart, Kaitlin;Horn, Alison;Kessler, Haeja;Dodge, Greg;Bardhi, Keti;Bardhi, Kostandina;Mills, Jeffrey L;Bernstein, Herbert J;Craig, Paul A
通讯作者：
Craig, Paul A

Lessons from my undergraduate research students.

我的本科研究生的经验教训。