Yan Shaomin, Wu Guang
Computational Mutation Project, DreamSciTech Consulting, 301, Building 12, Nanyou A-zone, Jiannan Road, Shenzhen, Guangdong Province CN-518054, China.
Protein Pept Lett. 2009;16(7):794-804. doi: 10.2174/092986609788681751.
Since 1999 we have developed three approaches to quantifying each amino acid in a protein as well as a protein in whole based on random mechanisms. With our approaches, we can reliably describe the evolution of a protein family, for example, the hemagglutinins from influenza A viruses along the time course in a 2-dimensional graph, and then we use the fast Fourier transform to find the mutation periodicity in order to time the mutation. In this study, we realize that the changes in quantified randomness in a hemagglutinin family over time is the difference between randomness associated with mutant amino acids and randomness associated with original amino acids. This is a standard mass-balance relationship, by which we can build a differential equation for a hemagglutinin family or a system of differential equations for all hemagglutinins in the family. In this context, the randomness defined by us actually is the entropy, thus we have a general model to describe the evolution, namely, the evolution is the exchange of entropy between protein family and environment through mutations quantified using our approaches.
自1999年以来，我们基于随机机制开发了三种方法来量化蛋白质中的每种氨基酸以及整个蛋白质。通过我们的方法，我们可以可靠地描述蛋白质家族的进化，例如，甲型流感病毒的血凝素在二维图中的时间进程，然后我们使用快速傅里叶变换来找到突变周期，以便确定突变时间。在这项研究中，我们意识到血凝素家族中量化随机性随时间的变化是与突变氨基酸相关的随机性和与原始氨基酸相关的随机性之间的差异。这是一个标准的质量平衡关系，据此我们可以为血凝素家族建立一个微分方程，或者为该家族中的所有血凝素建立一个微分方程组。在这种情况下，我们定义的随机性实际上就是熵，因此我们有一个通用模型来描述进化，即进化是通过我们的方法量化的突变，在蛋白质家族和环境之间进行熵的交换。
