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Singh A, Kundrotas PJ, Vakser IA. Diffusion of proteins in crowded solutions studied by docking-based modeling. J Chem Phys 2024; 161:095101. [PMID: 39225532 PMCID: PMC11374379 DOI: 10.1063/5.0220545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Accepted: 08/13/2024] [Indexed: 09/04/2024] Open
Abstract
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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Affiliation(s)
- Amar Singh
- Computational Biology Program, The University of Kansas, Lawrence, Kansas 66045, USA
| | - Petras J Kundrotas
- Computational Biology Program, The University of Kansas, Lawrence, Kansas 66045, USA
| | - Ilya A Vakser
- Computational Biology Program, The University of Kansas, Lawrence, Kansas 66045, USA
- Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas 66045, USA
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Gulotta A, Bucciarelli S, Roosen-Runge F, Holderer O, Schurtenberger P, Stradner A. Testing mixing rules for structural and dynamical quantities in multi-component crowded protein solutions. APL Bioeng 2024; 8:026116. [PMID: 38827499 PMCID: PMC11143939 DOI: 10.1063/5.0204201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/14/2024] [Indexed: 06/04/2024] Open
Abstract
Crowding effects significantly influence the phase behavior and the structural and dynamic properties of the concentrated protein mixtures present in the cytoplasm of cells or in the blood serum. This poses enormous difficulties for our theoretical understanding and our ability to predict the behavior of these systems. While the use of course grained colloid-inspired models allows us to reproduce the key physical solution properties of concentrated monodisperse solutions of individual proteins, we lack corresponding theories for complex polydisperse mixtures. Here, we test the applicability of simple mixing rules in order to predict solution properties of protein mixtures. We use binary mixtures of the well-characterized bovine eye lens proteins α and γB crystallin as model systems. Combining microrheology with static and dynamic scattering techniques and observations of the phase diagram for liquid-liquid phase separation, we show that reasonably accurate descriptions are possible for macroscopic and mesoscopic signatures, while information on the length scale of the individual protein size requires more information on cross-component interaction.
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Affiliation(s)
- Alessandro Gulotta
- Division for Physical Chemistry, Lund University, Naturvetarvägen 14, 22100 Lund, Sweden
| | - Saskia Bucciarelli
- Division for Physical Chemistry, Lund University, Naturvetarvägen 14, 22100 Lund, Sweden
| | | | - Olaf Holderer
- Jülich Centre for Neutron Science (JCNS) at Heinz Maier-Leibnitz Zentrum (MLZ), Forschungszentrum Jülich GmbH, Garching, Germany
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Hirschmann F, Lopez H, Roosen-Runge F, Seydel T, Schreiber F, Oettel M. Effects of flexibility in coarse-grained models for bovine serum albumin and immunoglobulin G. J Chem Phys 2023; 158:084112. [PMID: 36859072 DOI: 10.1063/5.0132493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023] Open
Abstract
We construct a coarse-grained, structure-based, low-resolution, 6-bead flexible model of bovine serum albumin (BSA, PDB: 4F5S), which is a popular example of a globular protein in biophysical research. The model is obtained via direct Boltzmann inversion using all-atom simulations of a single molecule, and its particular form is selected from a large pool of 6-bead coarse-grained models using two suitable metrics that quantify the agreement in the distribution of collective coordinates between all-atom and coarse-grained Brownian dynamics simulations of solutions in the dilute limit. For immunoglobulin G (IgG), a similar structure-based 12-bead model has been introduced in the literature [Chaudhri et al., J. Phys. Chem. B 116, 8045 (2012)] and is employed here to compare findings for the compact BSA molecule and the more anisotropic IgG molecule. We define several modified coarse-grained models of BSA and IgG, which differ in their internal constraints and thus account for a variation of flexibility. We study denser solutions of the coarse-grained models with purely repulsive molecules (achievable by suitable salt conditions) and address the effect of packing and flexibility on dynamic and static behavior. Translational and rotational self-diffusivity is enhanced for more elastic models. Finally, we discuss a number of effective sphere sizes for the BSA molecule, which can be defined from its static and dynamic properties. Here, it is found that the effective sphere diameters lie between 4.9 and 6.1 nm, corresponding to a relative spread of about ±10% around a mean of 5.5 nm.
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Affiliation(s)
- Frank Hirschmann
- Institute for Applied Physics, University of Tübingen, Auf der Morgenstelle 10, 72076 Tübingen, Germany
| | - Hender Lopez
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Grangegorman D07 ADY7, Ireland
| | - Felix Roosen-Runge
- Department of Biomedical Sciences and Biofilms-Research Center for Biointerfaces (BRCB), Malmö University, 20506 Malmö, Sweden
| | - Tilo Seydel
- Institut Max von Laue-Paul Langevin, 71 Avenue des Martyrs, 38042 Grenoble, France
| | - Frank Schreiber
- Institute for Applied Physics, University of Tübingen, Auf der Morgenstelle 10, 72076 Tübingen, Germany
| | - Martin Oettel
- Institute for Applied Physics, University of Tübingen, Auf der Morgenstelle 10, 72076 Tübingen, Germany
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Schvartz M, Saudrais F, Devineau S, Aude JC, Chédin S, Henry C, Millán-Oropeza A, Perrault T, Pieri L, Pin S, Boulard Y, Brotons G, Renault JP. A proteome scale study reveals how plastic surfaces and agitation promote protein aggregation. Sci Rep 2023; 13:1227. [PMID: 36681766 PMCID: PMC9867740 DOI: 10.1038/s41598-023-28412-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 01/18/2023] [Indexed: 01/22/2023] Open
Abstract
Protein aggregation in biotherapeutics can reduce their activity and effectiveness. It may also promote immune reactions responsible for severe adverse effects. The impact of plastic materials on protein destabilization is not totally understood. Here, we propose to deconvolve the effects of material surface, air/liquid interface, and agitation to decipher their respective role in protein destabilization and aggregation. We analyzed the effect of polypropylene, TEFLON, glass and LOBIND surfaces on the stability of purified proteins (bovine serum albumin, hemoglobin and α-synuclein) and on a cell extract composed of 6000 soluble proteins during agitation (P = 0.1-1.2 W/kg). Proteomic analysis revealed that chaperonins, intrinsically disordered proteins and ribosomes were more sensitive to the combined effects of material surfaces and agitation while small metabolic oligomers could be protected in the same conditions. Protein loss observations coupled to Raman microscopy, dynamic light scattering and proteomic allowed us to propose a mechanistic model of protein destabilization by plastics. Our results suggest that protein loss is not primarily due to the nucleation of small aggregates in solution, but to the destabilization of proteins exposed to material surfaces and their subsequent aggregation at the sheared air/liquid interface, an effect that cannot be prevented by using LOBIND tubes. A guidance can be established on how to minimize these adverse effects. Remove one of the components of this combined stress - material, air (even partially), or agitation - and proteins will be preserved.
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Affiliation(s)
- Marion Schvartz
- Université Paris-Saclay, CEA, CNRS, NIMBE, LIONS, 91191, Gif-Sur-Yvette, France.
- Institut des Molécules et Matériaux du Mans (IMMM), UMR 6283 CNRS, Le Mans Université, Avenue Olivier Messiaen, 72085, Le Mans Cedex, France.
| | - Florent Saudrais
- Université Paris-Saclay, CEA, CNRS, NIMBE, LIONS, 91191, Gif-Sur-Yvette, France
| | - Stéphanie Devineau
- Université Paris Cité, CNRS, Unité de Biologie Fonctionnelle et Adaptative, 75013, Paris, France
| | - Jean-Christophe Aude
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-Sur-Yvette, France
| | - Stéphane Chédin
- Université Paris-Saclay, CEA, CNRS, NIMBE, LIONS, 91191, Gif-Sur-Yvette, France
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-Sur-Yvette, France
| | - Céline Henry
- Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, PAPPSO, 78350, Jouy-en-Josas, France
| | - Aarón Millán-Oropeza
- Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, PAPPSO, 78350, Jouy-en-Josas, France
| | - Thomas Perrault
- Institut des Molécules et Matériaux du Mans (IMMM), UMR 6283 CNRS, Le Mans Université, Avenue Olivier Messiaen, 72085, Le Mans Cedex, France
| | - Laura Pieri
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-Sur-Yvette, France
| | - Serge Pin
- Université Paris-Saclay, CEA, CNRS, NIMBE, LIONS, 91191, Gif-Sur-Yvette, France
| | - Yves Boulard
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198, Gif-Sur-Yvette, France
| | - Guillaume Brotons
- Institut des Molécules et Matériaux du Mans (IMMM), UMR 6283 CNRS, Le Mans Université, Avenue Olivier Messiaen, 72085, Le Mans Cedex, France
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Beck C, Pounot K, Mosca I, H Jalarvo N, Roosen-Runge F, Schreiber F, Seydel T. Notes on Fitting and Analysis Frameworks for QENS Spectra of (Soft) Colloid Suspensions. EPJ WEB OF CONFERENCES 2022. [DOI: 10.1051/epjconf/202227201004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
With continuously improving signal-to-noise ratios, a statistically sound analysis of quasi-elastic neutron scattering (QENS) spectra requires to fit increasingly complex models which poses several challenges. Simultaneous fits of the spectra for all recorded values of the momentum transfer become a standard approach. Spectrometers at spallation sources can have a complicated non-Gaussian resolution function which has to be described most accurately. At the same time, to speed up the fitting, an analytical convolution with this resolution function is of interest. Here, we discuss basic concepts to efficient approaches for fits of QENS spectra based on standard MATLAB and Python fit algorithms. We illustrate the fits with example data from IN16B, BASIS, and BATS.
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