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Mechanisms of secondary structure breakers in soluble proteins.

ABSTRACT: Breaking signals of secondary structure put strong limitations on the tertiary structures of proteins. In addition to proline and glycine clusters, which are well-known secondary structure breakers, clusters of amphiphilic residues were found to be a novel type of secondary structure breaker. These secondary structure breakers were found to depend on specific environmental factors. Such conditions included the average hydrophobicity, the helical periodicity, the density of serine and threonine residues, and the presence of tryptophan and tyrosine clusters. Principal component analysis of environmental factors was conducted in order to identify candidate breakers in the secondary structure breaking regions. Predicted breakers were located in breaking regions with an accuracy of 72%. Taking the loop core into consideration, almost 90% of the predicted breakers were located in the loop segments. When the migration effect of the breaking point was taken into account, the loop segments with the predicted breakers covered two thirds of all loop segments. Herein, the possibility of secondary structure prediction based on secondary structure breakers is discussed. The system of the present method is available at the URL: http://bp.nuap.nagoya-u.ac.jp/sosui/sosuibreaker/sosuibreaker_submit.html.

SUBMITTER: Imai K

PROVIDER: S-EPMC5036629 | biostudies-literature | 2005

REPOSITORIES: biostudies-literature

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Mechanisms of secondary structure breakers in soluble proteins.

Imai Kenichiro K Mitaku Shigeki S

Biophysics (Nagoya-shi, Japan) 20051019

Breaking signals of secondary structure put strong limitations on the tertiary structures of proteins. In addition to proline and glycine clusters, which are well-known secondary structure breakers, clusters of amphiphilic residues were found to be a novel type of secondary structure breaker. These secondary structure breakers were found to depend on specific environmental factors. Such conditions included the average hydrophobicity, the helical periodicity, the density of serine and threonine r ...[more]

PMID: 27857553

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Project description:MotivationThe structure of proteins is organized in a hierarchy among which the secondary structure elements, α-helix, β-strand and loop, are the basic bricks. The determination of secondary structure elements usually requires the knowledge of the whole structure. Nevertheless, in numerous experimental circumstances, the protein structure is partially known. The detection of secondary structures from these partial structures is hampered by the lack of information about connecting residues along the primary sequence.ResultsWe introduce a new methodology to estimate the secondary structure elements from the values of local distances and angles between the protein atoms. Our method uses a message passing neural network, named Sequoia, which allows the automatic prediction of secondary structure elements from the values of local distances and angles between the protein atoms. This neural network takes as input the topology of the given protein graph, where the vertices are protein residues, and the edges are weighted by values of distances and pseudo-dihedral angles generalizing the backbone angles ϕ and ψ. Any pair of residues, independently of its covalent bonds along the primary sequence of the protein, is tagged with this distance and angle information. Sequoia permits the automatic detection of the secondary structure elements, with an F1-score larger than 80% for most of the cases, when α helices and β strands are predicted. In contrast to the approaches classically used in structural biology, such as DSSP, Sequoia is able to capture the variations of geometry at the interface of adjacent secondary structure element. Due to its general modeling frame, Sequoia is able to handle graphs containing only Cα atoms, which is particularly useful on low resolution structural input and in the frame of electron microscopy development.Availability and implementationSequoia source code can be found at https://github.com/Khalife/Sequoia with additional documentation.Supplementary informationSupplementary data are available at Bioinformatics Advances online.

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Mechanisms of secondary structure breakers in soluble proteins.

Publications

Mechanisms of secondary structure breakers in soluble proteins.

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