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Abstract The electrostatic effects of protein crowding have not been systematically explored. Rather, protein crowding is generally studied with co‐solvents or crowders that are electrostatically neutral, with no methods to measure how the net charge ( Z ) of a crowder affects protein function. For example, can the activity of an enzyme be affected electrostatically by the net charge of its neighbor in crowded milieu? This paper reports a method for crowding proteins of different net charge to an enzyme via semi‐random chemical crosslinking. As a proof of concept, RNase A was crowded (at distances ≤ the Debye length) via crosslinking to different heme proteins with Z = +8.50 ± 0.04, Z = +6.39 ± 0.12, or Z = −10.30 ± 1.32. Crosslinking did not disrupt the structure of proteins, according to amide H/D exchange, and did not inhibit RNase A activity. For RNase A, we found that the electrostatic environment of each crowded neighbor had significant effects on rates of RNA hydrolysis. Crowding with cationic cytochrome c led to increases in activity, while crowding with anionic “supercharged” cytochrome c or myoglobin diminished activity. Surprisingly, electrostatic crowding effects were amplified at high ionic strength ( I = 0.201 M) and attenuated at low ionic strength ( I = 0.011 M). This salt dependence might be caused by a unique set of electric double layers at the dimer interspace (maximum distance of 8 Å, which cannot accommodate four layers). This new method of crowding via crosslinking can be used to search for electrostatic effects in protein crowding.
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Diffusion of proteins in crowded solutions studied by docking-based modeling
The diffusion of proteins is significantly affected by macromolecular crowding. Molecular simulations accounting for protein interactions at atomic resolution are useful for characterizing the diffusion patterns in crowded environments. We present a comprehensive analysis of protein diffusion under different crowding conditions based on our recent docking-based approach simulating an intracellular crowded environment by sampling the intermolecular energy landscape using the Markov Chain Monte Carlo protocol. The procedure was extensively benchmarked, and the results are in very good agreement with the available experimental and theoretical data. The translational and rotational diffusion rates were determined for different types of proteins under crowding conditions in a broad range of concentrations. A protein system representing most abundant protein types in the E. coli cytoplasm was simulated, as well as large systems of other proteins of varying sizes in heterogeneous and self-crowding solutions. Dynamics of individual proteins was analyzed as a function of concentration and different diffusion rates in homogeneous and heterogeneous crowding. Smaller proteins diffused faster in heterogeneous crowding of larger molecules, compared to their diffusion in the self-crowded solution. Larger proteins displayed the opposite behavior, diffusing faster in the self-crowded solution. The results show the predictive power of our structure-based simulation approach for long timescales of cell-size systems at atomic resolution.
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- Award ID(s):
- 2224122
- PAR ID:
- 10593922
- Publisher / Repository:
- American Institute of Physics
- Date Published:
- Journal Name:
- The Journal of Chemical Physics
- Volume:
- 161
- Issue:
- 9
- ISSN:
- 0021-9606
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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