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Information 2017, 8(1), 29; doi:10.3390/info8010029

Structural and Functional Modeling of Artificial Bioactive Proteins

1
Center for Nuclear Magnetic Resonance, Ruđer Bošković Institute, Bijenička cesta 54, 10002 Zagreb, Croatia
2
Laboratory for Epigenomics, Division of Molecular Medicine, Ruđer Bošković Institute, Bijenička Cesta 54, 10002 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Academic Editors: Abir U. Igamberdiev, Pedro C. Marijuán and Lin Bi
Received: 5 November 2016 / Revised: 27 February 2017 / Accepted: 1 March 2017 / Published: 5 March 2017
(This article belongs to the Special Issue Symmetry and Information)

Abstract

A total of 32 synthetic proteins designed by Michael Hecht and co-workers was investigated using standard bioinformatics tools for the structure and function modeling. The dataset consisted of 15 artificial α-proteins (Hecht_α) designed to fold into 102-residue four-helix bundles and 17 artificial six-stranded β-sheet proteins (Hecht_β). We compared the experimentally-determined properties of the sequences investigated with the results of computational methods for protein structure and bioactivity prediction. The conclusion reached is that the dataset of Michael Hecht and co-workers could be successfully used both to test current methods and to develop new ones for the characterization of artificially-designed molecules based on the specific binary patterns of amino acid polarity. The comparative investigations of the bioinformatics methods on the datasets of both de novo proteins and natural ones may lead to: (1) improvement of the existing tools for protein structure and function analysis; (2) new algorithms for the construction of de novo protein subsets; and (3) additional information on the complex natural sequence space and its relation to the individual subspaces of de novo sequences. Additional investigations on different and varied datasets are needed to confirm the general applicability of this concept. View Full-Text
Keywords: synthetic protein; structure prediction; function prediction; de novo design synthetic protein; structure prediction; function prediction; de novo design
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Štambuk, N.; Konjevoda, P. Structural and Functional Modeling of Artificial Bioactive Proteins. Information 2017, 8, 29.

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