The variability of protein structure with respect to the hydrophobic core

• Autorzy: Banach M. , Wiśniowski Z. , Kalinowska B. , Konieczny L. , Roterman I.

Identyfikatory

DOI

10.1515/bams-2017-0004

• Języki publikacji: EN

Abstrakty

EN

The application of the fuzzy oil drop model to the analysis of protein structure is shown using two proteins. The selection of these two examples is due to their opposite character. Two proteins were selected representing very high order and very high disorder with respect to the organized uni-central hydrophobic core in proteins (one centrally localized concentration of high hydrophobicity). These two cases are to show examples of the large spectrum of variability of local organization of the hydrophobic core in proteins. The importance of the observation presented in this paper is significant with respect to large sets of proteins discussed in separate publications.

Słowa kluczowe

EN

fuzzy oil drop model; hydrophobic core; protein structure

• Wydawca: Uniwersytet Jagielloński - Collegium Medicum ; De Gruyter
• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2017
• Tom: Vol. 13, no. 2
• Strony: 63--67
• Opis fizyczny: Bibliogr. 21 poz., rys., wykr.

Twórcy

autor

Banach M.

• Department of Bioinformatics and Telemedicine, Jagiellonian University – Medical College, 31-530 Krakow, Łazarza 16, Poland

autor

Wiśniowski Z.

• Department of Bioinformatics and Telemedicine, Jagiellonian University – Medical College, 31-530 Krakow, Łazarza 16, Poland

autor

Kalinowska B.

• Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University – Łojasiewicza, Krakow, Poland

autor

Konieczny L.

• Chair of Medical Biochemistry, Jagiellonian University – Medical College, 31-034 Krakow, Poland

autor

Roterman I.

• Department of Bioinformatics and Telemedicine, Jagiellonian University-Medical College, 31- 530 Krakow, Lazarza 16, Poland

Bibliografia

• 1. http://predictioncenter.org/. Accessed: January, 2017.
• 2. Moult J, Fidelis K, Kryshtafovych A, Schwede T, Tramontano A. Critical assessment of methods of protein structure prediction (CASP) — round x. Proteins 2014;82:1–6.
• 3. Drozdetskiy A, Cole C, Procter J, Barton GJ. JPred4: a protein secondary structure prediction server. Nucl Acids Res 2015;43:W389–94.
• 4. https://prabi.ibcp.fr/htm/site/web/home. Accessed: January, 2017.
• 5. Lin K, Simossis VA, Taylor WR, Heringa J. A simple and fast secondary structure prediction method using hidden neural networks. Bioinformatics 2005;21:152–9.
• 6. http://molbiol-tools.ca/Protein_secondary_structure.htm. Accessed: January, 2017.
• 7. Yachdav G, Kloppmann E, Kajan L, Hecht M, Goldberg T, Hamp T, et al. PredictProtein–an open resource for online prediction of protein structural and functional features. Nucleic Acids Res 2014;42:W337–43.
• 8. Khoury GA, Liwo A, Khatib F, Zhou H, Chopra G, Bacardit J, et al. Foldit players. WeFold: a competition for protein structure prediction. Proteins 2014;82:1850–68.
• 9. Konieczny L, Bryliński M, Roterman I. Gauss-function-based model of hydrophobicity density in proteins. In Silico Biol 2006;6:15–22.
• 10. Kalinowska B, Banach M, Konieczny L. Roterman I. Application of divergence entropy to characterize the structure of the hydrophobic core in DNA interacting proteins. Entropy 2015;17:1477–507.
• 11. Banach M, Konieczny L, Roterman I. The fuzzy oil drop model, based on hydrophobicity density distribution, generalizes the influence of water environment on protein structure and function. J Theor Biol 2014;359:6–17.
• 12. Banach M, Konieczny L, Roterman I. Can the structure of hydrophobic core determine the complexation site? In: Roterman-Konieczna I, editor. Identification of ligand binding site and protein-protein interaction area. Dordrecht, Heidelberg, New York, London: Springer, 2013; 41–54.
• 13. Banach M, Konieczny L, Roterman I. Use of the “fuzzy oil drop” model to identify the complexation area in protein homodimers. In: Roterman-Konieczna I, editor. Protein folding in silico. Oxford: Woodhead Publishing, 2012:95–122.
• 14. Kalinowska B, Banach M, Konieczny L, Marchewka D, Roterman I. Intrinsically disordered proteins – relation to general model expressing the active role of the water environment. Adv Protein Chem Struct Biol 2014;94:315–46.
• 15. Naganuma M, Sekine SI, Fukunaga R, Yokoyama S. Unique protein architecture of alanyl-tRNA synthetase for aminoacylation, editing, and dimerization. Proc Natl Acad Sci USA 2009;106:8489–94.
• 16. de Beer TA, Berka K, Thornton JM, Laskowski RA. PDBsum additions. Nucleic Acids Res 2014;42:D292–6.
• 17. Sillitoe I, Lewis TE, Cuff AL, Das S, Ashford P, Dawson NL, et al. CATH: comprehensive structural and functional annotations for genome sequences. Nucleic Acids Res 2015;43:D376–81.
• 18. de Beer TA, Berka K, Thornton JM, Laskowski RA. PDBsum additions. Nucleic Acids Res 2014;42:D292–6.
• 19. Levitt MA. A simplified representation of protein conformations for rapid simulation of protein folding. J. Mol Biol 1976;104:59–107.
• 20. Kullback S, Leibler RA. On information and sufficiency. Ann Math Stat 1951;22:79–86.
• 21. Banach M, Kalinowska B, Konieczny L, Roterman I. Role of disulfide bonds in stabilizing the conformation of selected enzymes – an approach based on divergence entropy applied to the structure of hydrophobic core in proteins. Entropy 2016;18:67.