Investigation of the pH-dependent aggregation mechanisms of GCSF using low resolution protein characterization techniques and advanced molecular dynamics simulations

Ko, Suk Kyu; Berner, Carolin; Kulakova, Alina; Schneider, Markus; Antes, Iris; Winter, Gerhard; Harris, Pernille und Peters, Gunther H. J. (2022): Investigation of the pH-dependent aggregation mechanisms of GCSF using low resolution protein characterization techniques and advanced molecular dynamics simulations. In: Computational and Structural Biotechnology Journal, Bd. 20: S. 1439-1455

Abstract

Granulocyte-colony stimulating factor (GCSF) is a widely used therapeutic protein to treat neutropenia. GCSF has an increased propensity to aggregate if the pH is increased above 5.0. Although GCSF is very well experimentally characterized, the exact pH-dependent aggregation mechanism of GCSF is still under debate. This study aimed to model the complex pH-dependent aggregation behavior of GCSF using state -of-the-art simulation techniques. The conformational stability of GCSF was investigated by performing metadynamics simulations, while the protein-protein interactions were investigated using coarse-grained (CG) simulations of multiple GCSF monomers. The CG simulations were directly compared with small-angle X-ray (SAXS) data. The metadynamics simulations demonstrated that the orientations of Trp residues in GCSF are dependent on pH. The conformational change of Trp residues is due to the loss of Trp-His interactions at the physiological pH, which in turn may increase protein flexibility. The helical structure of GCSF was not affected by the pH conditions of the simulations. Our CG simulations indicate that at pH 4.0, the colloidal stability may be more important than the conformational stability of GCSF. The electrostatic potential surface and CG simulations suggested that the basic residues are mainly responsible for colloidal stability as deprotonation of these residues causes a reduction of the highly pos-itively charged electrostatic barrier close to the aggregation-prone long loop regions. (C) 2022 Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Bio -technology.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Chemie und Pharmazie > Department für Pharmazie - Zentrum für Pharmaforschung
• Themengebiete: 500 Naturwissenschaften und Mathematik > 540 Chemie
• ISSN: 2001-0370
• Sprache: Englisch