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Research Papers

Insights Into Crowding Effects on Protein Stability From a Coarse-Grained Model

[+] Author and Article Information
Vincent K. Shen

Physical and Chemical Properties Division, National Institute of Standards and Technology, Gaithersburg, MD 20899-8380vincent.shen@nist.gov

Jason K. Cheung

Biological and Sterile Product Development, Schering-Plough Research Institute, Summit, NJ 07091jason.cheung@spcorp.com

Jeffrey R. Errington

Department of Chemical and Biological Engineering, The State University of New York at Buffalo, Buffalo, NY 14260-4200jerring@buffalo.edu

Thomas M. Truskett

Department of Chemical Engineering, and Institute for Theoretical Chemistry, The University of Texas at Austin, Austin, TX 78712truskett@che.utexas.edu

J Biomech Eng 131(7), 071002 (Jun 05, 2009) (7 pages) doi:10.1115/1.3127259 History: Received September 25, 2008; Revised January 08, 2009; Published June 05, 2009

Proteins aggregate and precipitate from high concentration solutions in a wide variety of problems of natural and technological interest. Consequently, there is a broad interest in developing new ways to model the thermodynamic and kinetic aspects of protein stability in these crowded cellular or solution environments. We use a coarse-grained modeling approach to study the effects of different crowding agents on the conformational equilibria of proteins and the thermodynamic phase behavior of their solutions. At low to moderate protein concentrations, we find that crowding species can either stabilize or destabilize the native state, depending on the strength of their attractive interaction with the proteins. At high protein concentrations, crowders tend to stabilize the native state due to excluded volume effects, irrespective of the strength of the crowder-protein attraction. Crowding agents reduce the tendency of protein solutions to undergo a liquid-liquid phase separation driven by strong protein-protein attractions. The aforementioned equilibrium trends represent, to our knowledge, the first simulation predictions for how the properties of crowding species impact the global thermodynamic stability of proteins and their solutions.

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Copyright © 2009 by American Society of Mechanical Engineers
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Figures

Grahic Jump Location
Figure 1

Folding curves for the Φ=0.400 protein in the presence of (a) hard-sphere crowders and (b) attractive crowders. The black curve represents the bare protein solution without any crowders at the infinite-dilution midpoint folding temperature. Dimensionless crowder concentrations ρHσNN3 and ρAσNN3 of 0.0137, 0.0412, 0.0686, 0.0960, and 0.137 were studied.

Grahic Jump Location
Figure 2

Folding curves for the Φ=0.455 protein in the presence of (a) hard-sphere crowders and (b) attractive crowders. The black curve represents the bare protein solution without any crowders at the infinite-dilution midpoint folding temperature. Dimensionless crowder concentrations ρHσNN3 and ρAσNN3 of 0.0137, 0.0412, 0.0686, 0.0960, and 0.137 were studied.

Grahic Jump Location
Figure 3

Folding curves for the Φ=0.473 hydrophobicity protein in the presence of (a) hard-sphere crowders and (b) attractive crowders. The black curve represents the bare protein solution without any crowders at the infinite-dilution midpoint folding temperature. Open circles of the same color denote coexisting fluid phases. Dimensionless crowder concentrations ρHσNN3 and ρAσNN3 of 0.0137, 0.0412, 0.0686, 0.0960, and 0.137 were studied.

Grahic Jump Location
Figure 4

Folding curves for the Φ=0.500 hydrophobicity protein in the presence of (a) hard-sphere crowders and (b) attractive crowders. The black curve represents the bare protein solution without any crowders at the infinite-dilution midpoint folding temperature. Open circles of the same color denote coexisting fluid phases. Dimensionless crowder concentrations ρHσNN3 and ρAσNN3 of 0.0137, 0.0412, 0.0686, 0.0960, and 0.137 were studied.

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