ESM-Scan - a tool to guide amino acid substitutions

Abstract

Protein structure prediction and (re)design have gone through a revolution in the last three years. The tremendous progress in these fields has been almost exclusively driven by readily available machine-learning algorithms applied to protein folding and sequence design problems. Despite these advancements, predicting site-specific mutational effects on protein stability and function remains an unsolved problem. This is a persistent challenge mainly because the free energy of large systems is very difficult to compute with absolute accuracy and subtle changes to protein structures are also hard to capture with computational models. Here, we describe the implementation and use of ESM-Scan, which uses the ESM zero-shot predictor to scan entire protein sequences for preferential amino acid changes, thus enabling in-silico deep mutational scanning experiments. We benchmark ESM-Scan on its predictive capabilities for stability and functionality of sequence changes using three publicly available datasets and proceed by experimentally evaluating the tools performance on a challenging test case of a blue-light-activated diguanylate cyclase from Methylotenera species (MsLadC). We used ESM-Scan to predict conservative sequence changes in a highly conserved region of this enzyme responsible for allosteric product inhibition. Our experimental results show that the ESM-zero shot model emerges as a robust method for inferring the impact of amino acid substitutions, especially when evolutionary and functional insights are intertwined. ESM-Scan is publicly available at https://huggingface.co/spaces/thaidaev/zsp