The identification of physiologically relevant quaternary structures (QSs) in crystal lattices is challenging. To predict the physiological relevance of a particular QS, QSalign searches for homologous structures in which subunits interact in the same geometry. This approach proved accurate but was limited to structures already present in the Protein Data Bank (PDB). Here, we introduce a webserver (www.QSalign.org) allowing users to submit homo-oligomeric structures of their choice to the QSalign pipeline. Given a user-uploaded structure, the sequence is extracted and used to search homologs based on sequence similarity and PFAM domain architecture. If structural conservation is detected between a homolog and the user-uploaded QS, physiological relevance is inferred. The web server also generates alternative QSs with PISA and processes them the same way as the query submitted to widen the predictions. The result page also shows representative QSs in the protein family of the query, which is informative if no QS conservation was detected or if the protein appears monomeric. These representative QSs can also serve as a starting point for homology modeling.
QSalignWeb: A Server to Predict and Analyze Protein Quaternary Structure
Sucharita Dey,J. Prilusky,E. Levy
Published 2022 in Frontiers in Molecular Biosciences
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- Publication year
2022
- Venue
Frontiers in Molecular Biosciences
- Publication date
2022-01-05
- Fields of study
Biology, Medicine, Computer Science
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- Source metadata
Semantic Scholar, PubMed
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