Towards quantitative prediction of proteasomal digestion patterns of proteins

TL;DR

This paper presents a stochastic model for proteasomal protein degradation, enabling quantitative predictions of digestion patterns by integrating physical mechanisms and experimental data analysis.

Contribution

It introduces a first-principles-based stochastic model that predicts proteasomal digestion patterns and includes methods to infer cleavage specificity and translocation rates from mass spectrometry data.

Findings

Developed a mathematical master-equation model for proteasomal degradation.

Established techniques to reconstruct cleavage specificity and translocation rates from experimental data.

Designed an experimental setup for reliable measurement of translocation rates.

Abstract

We discuss the problem of proteasomal degradation of proteins. Though proteasomes are important for all aspects of the cellular metabolism, some details of the physical mechanism of the process remain unknown. We introduce a stochastic model of the proteasomal degradation of proteins, which accounts for the protein translocation and the topology of the positioning of cleavage centers of a proteasome from first principles. For this model we develop the mathematical description based on a master-equation and techniques for reconstruction of the cleavage specificity inherent to proteins and the proteasomal translocation rates, which are a property of the proteasome specie, from mass spectroscopy data on digestion patterns. With these properties determined, one can quantitatively predict digestion patterns for new experimental set-ups. Additionally we design an experimental set-up for a synthetic polypeptide with a periodic sequence of amino acids, which enables especially reliable determination of translocation rates.