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Updated: Aug 28, 2025

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
Published on: August 16, 2017
Highly significant improvement of protein sequence alignments with AlphaFold2
Athanasios Baltzis1, Leila Mansouri1, Suzanne Jin1
1Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain.
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.
Availability And Implementation:
All data, analyses and results are available on Zenodo (https://doi.org/10.5281/zenodo.7031286). The code and scripts have been deposited in GitHub (https://github.com/cbcrg/msa-af2-nf) and the various containers in (https://cloud.sylabs.io/library/athbaltzis/af2/alphafold, https://hub.docker.com/r/athbaltzis/pred).
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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