ArticleBioinformatics (Oxford, England)2024
MapTurns: mapping the structure, H-bonding, and contexts of beta turns in proteins.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- ExploreTurns: A web tool for the exploration, analysis, and classification of beta turns and structured loops in proteins; application to beta-bulge and Schellman loops, Asx helix caps, beta hairpins, and other hydrogen-bonded motifs.Protein science : a publication of the Protein Society · 2025Article
- Geometric descriptors for beta turns.Protein science : a publication of the Protein Society · 2024Article
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1 author.
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Abstract
motivationBeta turns are the most common type of secondary structure in proteins after alpha helices and beta sheets and play many key structural and functional roles. Turn backbone (BB) geometry has been classified at multiple levels of precision, but the current picture of side chain (SC) structure and interaction in turns is incomplete, because the distribution of SC conformations associated with each sequence motif has commonly been represented only by a static image of a single, typical structure for each turn BB geometry, and only motifs which specify a single amino acid (e.g. aspartic acid at turn position 1) have been systematically investigated. Furthermore, no general evaluation has been made of the SC interactions between turns and their BB neighborhoods. Finally, the visualization and comparison of the wide range of turn conformations has been hampered by the almost exclusive characterization of turn structure in BB dihedral-angle (Ramachandran) space.
resultsThis work introduces MapTurns, a web server for motif maps, which employ a turn-local Euclidean-space coordinate system and a global turn alignment to comprehensively map the distributions of BB and SC structure and H-bonding associated with sequence motifs in beta turns and their local BB contexts. Maps characterize many new SC motifs, provide detailed rationalizations of sequence preferences, and support mutational analysis and the general study of SC interactions, and they should prove useful in applications such as protein design. AVAILABILITY AND IMPLEMENTATION: MapTurns is available at www.betaturn.com. Sample code is available at: https://github.com/nenewell/MapTurns/tree/main.
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