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Unravelling the Adaptation Mechanisms to High Pressure in Proteins
Open accessPublished version of a preprint
Abstract
Life is thought to have appeared in the depth of the sea under high hydrostatic pressure. Nowadays, it is known that the deep biosphere hosts a myriad of life forms thriving under high-pressure conditions. However, the evolutionary mechanisms leading to their adaptation are still not known. Here, we show the molecular bases of these mechanisms through a joint structural and dynamical study of two orthologous proteins. We observed that pressure adaptation involves the decoupling of protein–water dynamics and the elimination of cavities in the protein core. This is achieved by rearranging the charged residues on the protein surface and using bulkier hydrophobic residues in the core. These findings will be the starting point in the search for a complete genomic model explaining high-pressure adaptation.
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![Figure 4 Total MSD (full circles) and MSD into the single wells (Δx0², open circles) for Tba PMI (a) and Tko PMI (b), lines are a guide to the eye. The absolute value of the MSD reports on the amplitude of hydrogen atoms motion, while the slope of the curve as a function of temperature indicates how much energy is necessary to increase said amplitude, i.e., the resilience of the protein [32].](/paper-figures/33f5b1856a5d49b1b23f0d97fc7f2096/unravelling-the-adaptation-mechanisms-to-high-pressure-in-proteins-figure-4.jpg)





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VMD: visual molecular dynamics
Humphrey, W., Dalke, A., & Schulten, K. (1996) · Journal of Molecular Graphics · doi:10.1016/0263-7855(96)00018-5 · Cited by 66,952
UCSF Chimera—A visualization system for exploratory research and analysis
Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20084 · Cited by 45,828
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
Features and development of Coot
Emsley, P., Lohkamp, B., Scott, W. G., & Cowtan, K. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444910007493 · Cited by 29,915
Phaser crystallographic software
McCoy, A. J., Grosse-Kunstleve, R. W., Adams, P. D., Winn, M. D., Storoni, L. C., & Read, R. J. (2007) · Journal of Applied Crystallography · doi:10.1107/s0021889807021206 · Cited by 20,612
Kabsch, W. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909047337 · Cited by 16,463
SWISS-MODEL: homology modelling of protein structures and complexes
Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., de Beer, T. A. P., Rempfer, C., Bordoli, L., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky427 · Cited by 13,067
CHARMM‐GUI: A web‐based graphical user interface for CHARMM
Jo, S., Kim, T., Iyer, V. G., & Im, W. (2008) · Journal of Computational Chemistry · doi:10.1002/jcc.20945 · Cited by 9,284
Liebschner, D., Afonine, P. V., Baker, M. L., Bunkóczi, G., Chen, V. B., Croll, T. I., Hintze, B., Hung, L.-W., Jain, S., McCoy, A. J., et al. (2019) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798319011471 · Cited by 7,953
Use of bacteriophage T7 RNA polymerase to direct selective high-level expression of cloned genes
Studier, F. W., & Moffatt, B. A. (1986) · Journal of Molecular Biology · doi:10.1016/0022-2836(86)90385-2 · Cited by 6,405
Research works printed but not linked: 1
- 1884, Sur un Énoncé gènèral des lois des Équilibres chimiques, C. R. Acad. Sci., 99, 786
Metadata
- Authors
- Caliò, A., Dubois, C., Fontanay, S., Koza, M. M., Hoh, F., Roumestand, C., Oger, P., & Peters, J.
- Affiliations
- Lyon 1 Université (FR)
- Centre National de la Recherche Scientifique (FR)
- Institut Laue-Langevin (FR)
- Corresponding author
- Oger, Philippe
- Peters, Judith
- ORCID
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2022-07-30
- Volume
- 23
- Issue
- 15
- Pages
- 8469
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC9369236
- OpenAlex
- W4289175460
- Cited by
- 12
- References
- 84
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 4 · 2022: 1
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Molecular Sciences (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- HAL (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- French National Research Agency (ANR 17-CE11-0012-01)
- Mission pour les Initiatives Transverses et Interdisciplinaires of the CNRS (ANR 17-CE11-0012-01)
- French Ministry of Science and Technology (ANR 17-CE11-0012-01)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Physical Sciences › Earth and Planetary Sciences › Geophysics › High-pressure geophysics and materials
- Keywords
- high-pressure adaptation, deep-sea fauna, deep biosphere, protein cavities, charged residues, hydrophobic core, protein structure and dynamics, orthologous proteins, adaptive evolution
- MeSH terms
- Acclimatization, Adaptation, Physiological, Hydrostatic Pressure
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- CoChat. (2026). Citation check: Unravelling the Adaptation Mechanisms to High Pressure in Proteins. https://app.cochat.ai/papers/10.3390/ijms23158469
- The paper
- Caliò, A., Dubois, C., Fontanay, S., Koza, M. M., Hoh, F., Roumestand, C., Oger, P., & Peters, J. (2022). Unravelling the Adaptation Mechanisms to High Pressure in Proteins. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms23158469
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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