AlphaFind: discover structure similarity across the proteome in AlphaFold DB
AlphaFind is a web-based search engine that provides fast structure-based retrieval in the entire set of AlphaFold DB structures. Unlike other protein processing tools, AlphaFind is focused entirely on tertiary structure, automatically extracting the main 3D features of each protein chain and using...
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Published in: | Nucleic acids research Vol. 52; no. W1; pp. W182 - W186 |
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Main Authors: | , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
England
Oxford University Press
05-07-2024
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Subjects: | |
Online Access: | Get full text |
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Summary: | AlphaFind is a web-based search engine that provides fast structure-based retrieval in the entire set of AlphaFold DB structures. Unlike other protein processing tools, AlphaFind is focused entirely on tertiary structure, automatically extracting the main 3D features of each protein chain and using a machine learning model to find the most similar structures. This indexing approach and the 3D feature extraction method used by AlphaFind have both demonstrated remarkable scalability to large datasets as well as to large protein structures. The web application itself has been designed with a focus on clarity and ease of use. The searcher accepts any valid UniProt ID, Protein Data Bank ID or gene symbol as input, and returns a set of similar protein chains from AlphaFold DB, including various similarity metrics between the query and each of the retrieved results. In addition to the main search functionality, the application provides 3D visualizations of protein structure superpositions in order to allow researchers to instantly analyze the structural similarity of the retrieved results. The AlphaFind web application is available online for free and without any registration at https://alphafind.fi.muni.cz. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 The first two authors should be regarded as Joint First Authors. |
ISSN: | 0305-1048 1362-4962 1362-4962 |
DOI: | 10.1093/nar/gkae397 |