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. 2023 Apr 27;127(16):3616-3623.
doi: 10.1021/acs.jpcb.3c00253. Epub 2023 Apr 18.

Optimized OPEP Force Field for Simulation of Crowded Protein Solutions

Stepan Timr  1   2   3 , Simone Melchionna  4   5 , Philippe Derreumaux  1   2   6 , Fabio Sterpone  1   2
Affiliations

Optimized OPEP Force Field for Simulation of Crowded Protein Solutions

Stepan Timr et al. J Phys Chem B. .

Abstract

Macromolecular crowding has profound effects on the mobility of proteins, with strong implications on the rates of intracellular processes. To describe the dynamics of crowded environments, detailed molecular models are needed, capturing the structures and interactions arising in the crowded system. In this work, we present OPEPv7, which is a coarse-grained force field at amino-acid resolution, suited for rigid-body simulations of the structure and dynamics of crowded solutions formed by globular proteins. Using the OPEP protein model as a starting point, we have refined the intermolecular interactions to match the experimentally observed dynamical slowdown caused by crowding. The resulting force field successfully reproduces the diffusion slowdown in homogeneous and heterogeneous protein solutions at different crowding conditions. Coupled with the lattice Boltzmann technique, it allows the study of dynamical phenomena in protein assemblies and opens the way for the in silico rheology of protein solutions.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
(A) Snapshots of crowded BSA solutions simulated using the OPEPv7 force field. BSA molecules belonging to a single unit cell are shown in red while their periodic images are displayed in white. (B) Decrease in the translational diffusion coefficient (relative to a dilute reference) observed for the 0.3–5 ns time window. The simulation results are compared with experimental data published in ref (32). (C) Diffusion slowdown obtained using the OPEPv7 force field for BSA solutions in the 30–50 ns regime, compared with experimental values− characterizing the long-time translational diffusion of BSA.
Figure 2
Figure 2
Concentration-dependent partitioning of BSA molecules into clusters of different sizes in crowded BSA solutions. ”Free” refers to an isolated BSA molecule floating freely in the solution while ”All” denotes a cluster comprising all proteins in the box.
Figure 3
Figure 3
Dynamics of chymotrypsin inhibitor 2 (CI2) in crowded solutions of BSA and lysozyme. (A) Snapshots of the simulation systems. For a single unit cell, CI2 molecules are shown in blue, BSA molecules are shown in red, and lysozyme molecules are shown in green; the periodic images of these molecules are displayed in white. (B) Slowdown of the CI2 translational diffusion obtained with the OPEPv7 force field in the 30–50 ns time window. The results are compared with experimental data from pulsed-field gradient NMR.
Figure 4
Figure 4
Contacts of chymotrypsin inhibitor 2 (CI2) in crowded solutions of BSA and lysozyme. (A) Histograms mapping the number of other CI2 molecules being in contact with a CI2 molecule. The data for the 300 g/L trajectories were presented in the Supporting Information of ref (14). (B) Representative geometries of oligomeric structures formed by CI2 in the 100 g/L CI2/BSA solution. Each CI2 molecule in the given oligomer is depicted using a different color.
Figure 5
Figure 5
Slowdown of the translational diffusion coefficient in a 300 g/L BSA solution: a comparison between the globular CI2 protein and the disordered αSyn. Simulation results obtained with the OPEPv7 force field in the 30–50 ns regime are set side by side with experimental data from pulsed-field-gradient NMR.
Figure 6
Figure 6
Distribution of the protein diffusion coefficients extracted from the simulation of a model of the E. coli cytoplasm (279 g/L concentration) and calculated in the 30–50 ns time interval as a function of protein molecular weight. (A) Data from a simulation based on the earlier version of OPEP but using the ad hoc scaling factor of 1.8/2.1. (B) Results from a simulation based on OPEPv7, i.e., the final optimized version. The distributions are compared with the analytical fit of experimental data reported in ref (42). In the bottom panel of the figure, we show a representation of the cytoplasm system simulated with OPEPv7 at different time frames. Each protein species is represented using a different color.
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