Guo Hao-Bo, Ma Yue, Tuskan Gerald A, Qin Hong, Yang Xiaohan, Guo Hong
Department of Computer Science and Engineering, SimCenter, University of Tennessee, Chattanooga, TN 37403, USA.
Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA.
Entropy (Basel). 2019 Jun 14;21(6):591. doi: 10.3390/e21060591.
We propose a framework to convert the protein intrinsic disorder content to structural entropy () using Shannon's information theory (IT). The structural capacity (), which is the sum of and structural information (), is equal to the amino acid sequence length of the protein. The structural entropy of the residues expands a continuous spectrum, ranging from 0 (fully ordered) to 1 (fully disordered), consistent with Shannon's IT, which scores the fully-determined state 0 and the fully-uncertain state 1. The intrinsically disordered proteins (IDPs) in a living cell may participate in maintaining the high-energy-low-entropy state. In addition, under this framework, the biological functions performed by proteins and associated with the order or disorder of their 3D structures could be explained in terms of information-gains or entropy-losses, or the reverse processes.
我们提出了一个框架,利用香农信息论(IT)将蛋白质内在无序含量转换为结构熵()。结构容量()是和结构信息()的总和,等于蛋白质的氨基酸序列长度。残基的结构熵扩展为一个连续谱,范围从0(完全有序)到1(完全无序),这与香农信息论一致,香农信息论将完全确定状态记为0,将完全不确定状态记为1。活细胞中的内在无序蛋白质(IDP)可能参与维持高能量低熵状态。此外,在此框架下,蛋白质执行的与其三维结构的有序或无序相关的生物学功能可以用信息增益或熵损失,或相反过程来解释。