Highly significant improvement of protein sequence alignments with AlphaFold2

Motivation Protein sequence alignments are essential to structural, evolutionary and functional analysis, but their accuracy is often limited by sequence similarity unless molecular structures are available. Protein structures predicted at experimental grade accuracy, as achieved by AlphaFold2, could therefore have a major impact on sequence analysis. Results Here, we find that multiple sequence alignments estimated on AlphaFold2 predictions are almost as accurate as alignments estimated on experimental structures and significantly closer to the structural reference than sequence-based alignments. We also show that AlphaFold2 structural models of relatively low quality can be used to obtain highly accurate alignments. These results suggest that, besides structure modeling, AlphaFold2 encodes higher-order dependencies that can be exploited for sequence analysis.

Automated summary

This study found that protein sequence alignments estimated on AlphaFold2 predictions are nearly as accurate as those estimated on experimental structures, and they are significantly closer to the structural reference than sequence-based alignments. Furthermore, even low-quality AlphaFold2 structural models can be used to obtain highly accurate alignments. This suggests that AlphaFold2 encodes higher-order dependencies that can be utilized for sequence analysis.