Pairing interacting protein sequences using masked language modeling
Umberto Lupo,
Damiano Sgarbossa,
Anne-Florence Bitbol
Abstract:Predicting which proteins interact together from amino acid sequences is an important task. We develop a method to pair interacting protein sequences which leverages the power of protein language models trained on multiple sequence alignments (MSAs), such as MSA Transformer and the EvoFormer module of AlphaFold. We formulate the problem of pairing interacting partners among the paralogs of two protein families in a differentiable way. We introduce a method called Differentiable Pairing using Alignment-based La… Show more
“…Another direction concerns the study of interacting biomolecules, where the pure ML approach of Alpha-Multimer has not yet proven reliable enough for many applications. The paper by Lupo et al ( 28 ) attempts to address this problem by applying a language model to better align relevant interacting sequences at the protein–protein interface. One should also note the problem of antigen recognition by T cell receptors as a critical part of the adaptive immune system.…”
Section: And the Protein Folding Problemmentioning
“…Another direction concerns the study of interacting biomolecules, where the pure ML approach of Alpha-Multimer has not yet proven reliable enough for many applications. The paper by Lupo et al ( 28 ) attempts to address this problem by applying a language model to better align relevant interacting sequences at the protein–protein interface. One should also note the problem of antigen recognition by T cell receptors as a critical part of the adaptive immune system.…”
Section: And the Protein Folding Problemmentioning
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