非均匀核糖体流模型中蛋白质翻译速率最大化的凸优化方法
Maximizing Protein Translation Rate in the Nonhomogeneous Ribosome Flow Model: A Convex Optimization Approach
摘要：
翻译是基因表达的重要阶段。在这个阶段，被称为核糖体的大分子沿着mRNA链移动，以特定的顺序将氨基酸连接在一起，以产生功能蛋白质。一个重要的问题是如何最大限度地提高蛋白质产量。事实上，翻译消耗了细胞的大部分能量，人们很自然地认为进化塑造了这一过程，使蛋白质生产率最大化。如果确实如此，则可以通过求解适当的数学优化问题来估计翻译机器的各种参数。同样的问题也出现在合成生物学的背景下，即，重新设计异源基因以使它们在宿主生物体中的翻译速率最大化。我们考虑的问题，最大限度地提高蛋白质的生产率使用的计算模型称为核糖体流模型（RFM）的折叠延长。该模型描述了核糖体沿着长度为n的mRNA链的流动，使用一组n阶非线性常微分方程。它还包括n+1个正参数：核糖体进入mRNA链的起始速率和沿链位点的n个延伸速率。我们表明，在RFM的稳态翻译率是一个严格的凹函数的参数。这意味着在适当的约束下最大化翻译速率的问题总是允许唯一的解，并且即使对于大的n值，也可以使用用于求解凸优化问题的高效算法来确定该解。此外，我们的分析表明，最佳的翻译速率可以计算的基础上，只有最佳的起始速率和延伸率的密码子附近的ORF的开始。我们讨论了理论结果在合成生物学、分子进化和功能基因组学中的应用。
英文摘要：
Translation is an important stage in gene expression. During this stage, macro-molecules called ribosomes travel along the mRNA strand linking amino-acids together in a specific order to create a functioning protein. An important question is how to maximize protein production. Indeed, translation is known to consume most of the cell's energy and it is natural to assume that evolution shaped this process so that it maximizes the protein production rate. If this is indeed so then one can estimate various parameters of the translation machinery by solving an appropriate mathematical optimization problem. The same problem also arises in the context of synthetic biology, namely, re-engineer heterologous genes in order to maximize their translation rate in a host organism. We consider the problem of maximizing the protein production rate using a computational model for translation-elongation called the ribosome flow model (RFM). This model describes the flow of the ribosomes along an mRNA chain of length n using a set of n first-order nonlinear ODEs. It also includes n+1 positive parameters: the ribosomal initiation rate into the mRNA chain, and n elongation rates along the chain sites. We show that the steady-state translation rate in the RFM is a strictly concave function of its parameters. This means that the problem of maximizing the translation rate under a suitable constraint always admits a unique solution, and that this solution can be determined using highly-efficient algorithms for solving convex optimization problems even for large values of n. Furthermore, our analysis shows that the optimal translation rate can be computed based only on the optimal initiation rate and the elongation rate of the codons near the beginning of the ORF. We discuss some applications of the theoretical results to synthetic biology, molecular evolution, and functional genomics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
