2014/07/23 by Gilad Poker, Poker, Gilad, Yoram Zarai +5 · 2 citations
Biochemistry, Genetics and Molecular Biology · #FOS: Biological sciences #Genomics (q-bio.GN) #RNA Research and Splicing #RNA and protein synthesis mechanisms #RNA modifications and cancer
paper · pdf · doi:10.48550/arxiv.1407.6340
openalex publication_date 2014/07/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Translation is an important stage in gene expression. During this stage,\nmacro-molecules called ribosomes travel along the mRNA strand linking\namino-acids together in a specific order to create a functioning protein. An\nimportant question is how to maximize protein production. Indeed, translation\nis known to consume most of the cell's energy and it is natural to assume that\nevolution shaped this process so that it maximizes the protein production rate.\nIf this is indeed so then one can estimate various parameters of the\ntranslation machinery by solving an appropriate mathematical optimization\nproblem. The same problem also arises in the context of synthetic biology,\nnamely, re-engineer heterologous genes in order to maximize their translation\nrate in a host organism. We consider the problem of maximizing the protein\nproduction rate using a computational model for translation-elongation called\nthe ribosome flow model (RFM). This model describes the flow of the ribosomes\nalong an mRNA chain of length n using a set of n first-order nonlinear ODEs. It\nalso includes n+1 positive parameters: the ribosomal initiation rate into the\nmRNA chain, and n elongation rates along the chain sites. We show that the\nsteady-state translation rate in the RFM is a strictly concave function of its\nparameters. This means that the problem of maximizing the translation rate\nunder a suitable constraint always admits a unique solution, and that this\nsolution can be determined using highly-efficient algorithms for solving convex\noptimization problems even for large values of n. Furthermore, our analysis\nshows that the optimal translation rate can be computed based only on the\noptimal initiation rate and the elongation rate of the codons near the\nbeginning of the ORF. We discuss some applications of the theoretical results\nto synthetic biology, molecular evolution, and functional genomics.\n