Optimal Down Regulation of mRNA Translation

TL;DR

This paper develops an efficient mathematical approach to optimally down regulate mRNA translation by adjusting transition rates in the ribosome flow model, with implications for biomedical applications like vaccine development.

Contribution

It introduces an optimization framework for down regulation of mRNA translation using the ribosome flow model, identifying key transition rates affecting protein production.

Findings

Optimal solutions can be efficiently computed under certain conditions.

The most influential transition rate is not necessarily the slowest one.

Focusing on specific mRNA sites can maximize down regulation effectiveness.

Abstract

Down regulation of mRNA translation is an important problem in various bio-medical domains ranging from developing effective medicines for tumors and for viral diseases to developing attenuated virus strains that can be used for vaccination. Here, we study the problem of down regulation of mRNA translation using a mathematical model called the ribosome flow model (RFM). In the RFM, the mRNA molecule is modeled as a chain of $n$ sites. The flow of ribosomes between consecutive sites is regulated by $n+1$ transition rates. Given a set of feasible transition rates, that models the outcome of all possible mutations, we consider the problem of maximally down regulating the translation rate by altering the rates within this set of feasible rates. Under certain conditions on the feasible set, we show that an optimal solution can be determined efficiently. We also rigorously analyze two special cases of the down regulation optimization problem. Our results suggest that one must focus on the position along the mRNA molecule where the transition rate has the strongest effect on the protein production rate. However, this rate is not necessarily the slowest transition rate along the mRNA molecule. We discuss some of the biological implications of these results.