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Updated: Aug 11, 2025

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
Published on: August 16, 2017
Sequence and structure alignments in post-AlphaFold era
Sandun Rajapaksa1, Arun S Konagurthu1, Arthur M Lesk2
1Department of Data Science and Artificial Intelligence, Faculty of Information Technology, Monash University, Clayton, 3800, Victoria, Australia.
Abstract:
Sequence alignment is fundamental for analyzing protein structure and function. For all but closely-related proteins, alignments based on structures are more accurate than alignments based purely on amino-acid sequences. However, the disparity between the large amount of sequence data and the relative paucity of experimentally-determined structures has precluded the general applicability of structure alignment. Based on the success of AlphaFold (and its likes) in producing high-quality structure predictions, we suggest that when aligning homologous proteins, lacking experimental structures, better results can be obtained by a structural alignment of predicted structures than by an alignment based only on amino-acid sequences. We present a quantitative evaluation, based on pairwise alignments of sequences and structures (both predicted and experimental) to support this hypothesis.
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