Multi-level Protein Representation Learning for Blind Mutational Effect Prediction

Understand

Directed evolution plays an indispensable role in protein engineering that revises existing protein sequences to attain new or enhanced functions.

• Accurately predicting the effects of protein variants necessitates an in-depth understanding of protein structure and function.
• Although large self-supervised language models have demonstrated remarkable performance in zero-shot inference using only protein sequences, these models inherently do not interpret the spatial characteristics of protein structures, which are crucial for comprehending protein folding stability and internal molecular interactions.
• This paper introduces a novel pre-training framework that cascades sequential and geometric analyzers for protein primary and tertiary structures.