The aqueous environment as an active participant in the protein folding process

Małgorzata Gadzała; Dawid Dułak; Barbara Kalinowska; Zbigniew Baster; Michał Bryliński; Leszek Konieczny; Mateusz Banach; Irena Roterman

doi:10.1016/j.jmgm.2018.12.008

The aqueous environment as an active participant in the protein folding process

J Mol Graph Model. 2019 Mar:87:227-239. doi: 10.1016/j.jmgm.2018.12.008. Epub 2018 Dec 14.

Authors

Małgorzata Gadzała¹, Dawid Dułak², Barbara Kalinowska³, Zbigniew Baster⁴, Michał Bryliński⁵, Leszek Konieczny⁶, Mateusz Banach⁷, Irena Roterman⁸

Affiliations

¹ ACK Cyfronet AGH, Nawojki 11, 30-950, Kraków, Poland.
² ABB Business Services Sp. z o.o. ul. Żegańska 1, 04-713, Warszawa, Poland. Electronic address: dawid.dulak@gmail.com.
³ Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, 11 Łojasiewicza Street, Kraków, Poland; Department of Bioinformatics and Telemedicine, Jagiellonian University - Medical College, Łazarza 16, 31-530, Kraków, Poland.
⁴ Department of Molecular and Interfacial Biophysics, Faculty of Physics, Astronomy, Applied Computer Science Jagiellonian University, 11 Łojasiewicza Street, Kraków, Poland; Markey Cancer Center, University of Kentucky, 789 South Limestone Street, Lexington, KY, USA.
⁵ Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, 70803, USA; Center for Computation & Technology, Louisiana State University, Baton Rouge, LA, 70803, USA.
⁶ Chair of Medical Biochemistry, Jagiellonian University - Medical College, Kopernika 7E, 31-034, Kraków, Poland.
⁷ Department of Bioinformatics and Telemedicine, Jagiellonian University - Medical College, Łazarza 16, 31-530, Kraków, Poland.
⁸ Department of Bioinformatics and Telemedicine, Jagiellonian University - Medical College, Łazarza 16, 31-530, Kraków, Poland. Electronic address: myroterm@cyf-kr.edu.pl.

PMID: 30580160
DOI: 10.1016/j.jmgm.2018.12.008

Abstract

Existing computational models applied in the protein structure prediction process do not sufficiently account for the presence of the aqueous solvent. The solvent is usually represented by a predetermined number of H₂O molecules in the bounding box which contains the target chain. The fuzzy oil drop (FOD) model, presented in this paper, follows an alternative approach, with the solvent assuming the form of a continuous external hydrophobic force field, with a Gaussian distribution. The effect of this force field is to guide hydrophobic residues towards the center of the protein body, while promoting exposure of hydrophilic residues on its surface. This work focuses on the following sample proteins: Engrailed homeodomain (RCSB: 1enh), Chicken villin subdomain hp-35, n68h (RCSB: 1yrf), Chicken villin subdomain hp-35, k65(nle), n68h, k70(nle) (RCSB: 2f4k), Thermostable subdomain from chicken villin headpiece (RCSB: 1vii), de novo designed single chain three-helix bundle (a3d) (RCSB: 2a3d), albumin-binding domain (RCSB: 1prb) and lambda repressor-operator complex (RCSB: 1lmb).

Keywords: External force field; Hydrophobic core; Protein structure prediction.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Hydrophobic and Hydrophilic Interactions
Models, Molecular
Protein Conformation
Protein Folding*
Proteins / chemistry*
Solutions

Substances

Proteins
Solutions