INFORMATION COMPLEXITY OF PROTEIN FOLDING

蛋白质折叠的信息复杂性

基本信息

批准号：
2024459
负责人：
GREGORY T DEWEY
金额：
$ 6.24万
依托单位：
UNIVERSITY OF DENVER (COLORADO SEMINARY)
依托单位国家：
美国
项目类别：
财政年份：
1997
资助国家：
美国
起止时间：
1997-06-01 至 1999-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/2024459
关键词：
X ray chemical models information theory mathematical model model design /development nuclear magnetic resonance spectroscopy protein folding protein sequence structural biology

项目摘要

DESCRIPTION: A basic tenet of the protein folding problem is that the information contained in the amino acid sequence is sufficient to dictate the three-dimensional, folded structure of a protein. The goal of the present study is to understand and quantify this idea using techniques of information and complexity theory. Potential applications of these approaches to protein structure determination and prediction will also be explored. From an information theoretical point of view, protein folding can be envisioned as a communication process by which the sequence information is transmitted to the three-dimensional structure. There are a number of questions one can ask regarding such information transfer. How much information is transferred from sequence to structure? How redundant is the information? Is information transfer via protein folding, a "noisy or noiseless" communication channel? These questions are approached by taking advantages of recent advances in our understanding of the relationship between thermodynamic entropy, information entropy and algorithmic complexity. The information content of the sequence is determined from the information entropy, and the content of the three-dimensional structure is related to the algorithmic complexity. The algorithmic complexity is a measure of the shortest computational representation of a structure. With these quantities, the information content (or data compression) of sequence and structural data will be determined. Using maximum entropy techniques, the shared or mutual information between sequence and structure will also be determined. Knowledge of this shared information will be used to develop models of the "communication channel" of protein folding. This approach can also be used to quantitatively compare structure prediction algorithms. A long term goal is to incorporate this shared information into a maximum entropy algorithm for X-ray and NMR structure determination. This approach will also provide an algorithm for determining structures by jointly optimizing X-ray and NMR data.

描述：蛋白质折叠问题的基本原理是氨基酸序列中包含的信息足以决定蛋白质的三维折叠结构。的目标目前的研究是使用以下技术来理解和量化这个想法信息与复杂性理论。这些的潜在应用蛋白质结构测定和预测的方法也将是探索过。从信息论的角度来看，蛋白质折叠可以被设想为一个通信过程，通过该过程，序列信息被传输到三维结构。有一个人们可以就此类信息传输提出许多问题。如何有多少信息从序列转移到结构？多么多余是信息吗？通过蛋白质折叠进行的信息传递是“嘈杂的”吗？或无噪音”的沟通渠道？这些问题是通过利用我们在理解上的最新进展热力学熵、信息熵和热力学熵之间的关系算法复杂度。序列的信息内容为由信息熵和内容确定三维结构与算法复杂度有关。这算法复杂度是最短计算时间的衡量标准结构的表示。有了这些数量，信息序列和结构数据的内容（或数据压缩）将是决定。使用最大熵技术，共享或相互序列和结构之间的信息也将被确定。这些共享信息的知识将用于开发模型蛋白质折叠的“通讯通道”。这个方法也可以用定量比较结构预测算法。长期目标就是将这些共享信息合并到最大熵算法中用于 X 射线和 NMR 结构测定。这种方法还将提供通过联合优化 X 射线和 NMR 确定结构的算法数据。