ExploreTurns: A web tool for the exploration and analysis of beta turns and their contexts in proteins; application to beta-bulge and Schellman loops, Asx helix caps, and other hydrogen-bonded motifs
The most common type of protein secondary structure after the alpha helix and beta sheet is the four-residue beta turn, which plays many key structural and functional roles. Existing tools for the study of beta turns operate almost exclusively in backbone dihedral-angle (Ramachandran) space, which presents challenges for the visualization, comparison and analysis of the wide range of turn conformations. A recent study has introduced a turn-local Euclidean-space coordinate system and global alignment for turns, along with geometric parameters describing their backbone shapes, and these features and others are incorporated here into ExploreTurns, a web facility for the exploration, analysis, geometric tuning and retrieval of beta turns and their structural contexts which combines the advantages of Ramachandran- and Euclidean-space representations. Due to the widespread occurrence of beta turns in proteins, this facility, supported by its interpreter for a new general nomenclature for short H-bonded loops, can serve as an exploratory browser and analysis tool for most loop structure. ExploreTurns is applied here to detect new H-bonded loops, including a "short Schellman loop" and a large family of motifs satisfying a generalized definition of the beta-bulge loop, map Asx N-cap sequence preferences, profile Schellman loop/beta-turn conformations, and investigate the depth dependence of turn geometry. The tool, available at www.betaturn.com, should prove useful in research, education, and applications such as protein design, in which an enhanced Euclidean-space picture of turn/motif structure and the ability to identify and tune structures suited to particular requirements may improve performance..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 27. Apr. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Newell, Nicholas E [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2024.01.01.573820 |
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| PPN (Katalog-ID): |
XBI042073715 |
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| 245 | 1 | 0 | |a ExploreTurns: A web tool for the exploration and analysis of beta turns and their contexts in proteins; application to beta-bulge and Schellman loops, Asx helix caps, and other hydrogen-bonded motifs |
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| 520 | |a The most common type of protein secondary structure after the alpha helix and beta sheet is the four-residue beta turn, which plays many key structural and functional roles. Existing tools for the study of beta turns operate almost exclusively in backbone dihedral-angle (Ramachandran) space, which presents challenges for the visualization, comparison and analysis of the wide range of turn conformations. A recent study has introduced a turn-local Euclidean-space coordinate system and global alignment for turns, along with geometric parameters describing their backbone shapes, and these features and others are incorporated here into ExploreTurns, a web facility for the exploration, analysis, geometric tuning and retrieval of beta turns and their structural contexts which combines the advantages of Ramachandran- and Euclidean-space representations. Due to the widespread occurrence of beta turns in proteins, this facility, supported by its interpreter for a new general nomenclature for short H-bonded loops, can serve as an exploratory browser and analysis tool for most loop structure. ExploreTurns is applied here to detect new H-bonded loops, including a "short Schellman loop" and a large family of motifs satisfying a generalized definition of the beta-bulge loop, map Asx N-cap sequence preferences, profile Schellman loop/beta-turn conformations, and investigate the depth dependence of turn geometry. The tool, available at www.betaturn.com, should prove useful in research, education, and applications such as protein design, in which an enhanced Euclidean-space picture of turn/motif structure and the ability to identify and tune structures suited to particular requirements may improve performance. | ||
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