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Evaluating the accuracy of protein design using native secondary sub-structures

Overview of attention for article published in BMC Bioinformatics, September 2016
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Title
Evaluating the accuracy of protein design using native secondary sub-structures
Published in
BMC Bioinformatics, September 2016
DOI 10.1186/s12859-016-1199-y
Pubmed ID
Authors

Marziyeh Movahedi, Fatemeh Zare-Mirakabad, Seyed Shahriar Arab

Abstract

According to structure-dependent function of proteins, two main challenging problems called Protein Structure Prediction (PSP) and Inverse Protein Folding (IPF) are investigated. In spite of IPF essential applications, it has not been investigated as much as PSP problem. In fact, the ultimate goal of IPF problem or protein design is to create proteins with enhanced properties or even novel functions. One of the major computational challenges in protein design is its large sequence space, namely searching through all plausible sequences is impossible. Inasmuch as, protein secondary structure represents an appropriate primary scaffold of the protein conformation, undoubtedly studying the Protein Secondary Structure Inverse Folding (PSSIF) problem is a quantum leap forward in protein design, as it can reduce the search space. In this paper, a novel genetic algorithm which uses native secondary sub-structures is proposed to solve PSSIF problem. In essence, evolutionary information can lead the algorithm to design appropriate amino acid sequences respective to the target secondary structures. Furthermore, they can be folded to tertiary structures almost similar to their reference 3D structures. The proposed algorithm called GAPSSIF benefits from evolutionary information obtained by solved proteins in the PDB. Therefore, we construct a repository of protein secondary sub-structures to accelerate convergence of the algorithm. The secondary structure of designed sequences by GAPSSIF is comparable with those obtained by Evolver and EvoDesign. Although we do not explicitly consider tertiary structure features through the algorithm, the structural similarity of native and designed sequences declares acceptable values. Using the evolutionary information of native structures can significantly improve the quality of designed sequences. In fact, the combination of this information and effective features such as solvent accessibility and torsion angles leads IPF problem to an efficient solution. GAPSSIF can be downloaded at http://bioinformatics.aut.ac.ir/GAPSSIF/ .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 40%
Professor > Associate Professor 2 13%
Student > Bachelor 2 13%
Researcher 2 13%
Other 1 7%
Other 1 7%
Unknown 1 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 33%
Biochemistry, Genetics and Molecular Biology 4 27%
Computer Science 2 13%
Economics, Econometrics and Finance 1 7%
Chemistry 1 7%
Other 0 0%
Unknown 2 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 September 2016.
All research outputs
#20,340,423
of 22,886,568 outputs
Outputs from BMC Bioinformatics
#6,871
of 7,298 outputs
Outputs of similar age
#292,874
of 335,704 outputs
Outputs of similar age from BMC Bioinformatics
#122
of 132 outputs
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