Abstract
Protein-water interactions fundamentally shape the structure, stability, dynamics, and functionality of proteins. However, the heterogeneous nature of the protein-water interface and the disparity in their dynamic interplay make it challenging to understand how local water perturbations influence protein structural dynamics over space and time. In this study, we introduce a photochromic molecule, spiropyran, to modify a specific residue of proteins, thereby achieving a reversible, residue-specific, and amplified perturbation on the hydrophobicity of protein surfaces. With the aid of controlled, amplified hydrophobic perturbations, we reveal that even residue-level changes in hydrophobicity induce significant global alterations in protein hydration patterns. These hydration shifts propagate in an amino acid sequence-dependent manner, initiating dramatic influences on overall protein architecture and catalytic performance. Our findings establish that interfacial water networks not only capture the surface physicochemical patterns of proteins but also mediate the propagation of local perturbations into broader structural and functional fluctuations. By shifting the paradigm from “structure-function” to “structure-hydration-function”, our work provides innovative perspectives into understanding protein architecture and guiding future drug design strategies.
Similar content being viewed by others
Data availability
All datasets generated during this study are available in figshare (https://doi.org/10.6084/m9.figshare.29627516). SAXS data have been deposited in the Small Angle Scattering Biological Data Bank (SASBDB) under accession codes SAS7452, SAS7469, SAS7470 and SAS7473. The PDB code of the previously published structure used in this study is 1ED9. All data are also available from the corresponding author upon request. Source data are provided as a Source Data file. Source data are provided with this paper.
Code availability
All custom code central to the conclusions of this study is publicly available at GitHub (https://github.com/iawnix/WatAna). Archived versions of the code are available at Zenodo: CovCom v1.0.0 (https://doi.org/10.5281/zenodo.18617244)65 and WatAna v1.0.0 (https://doi.org/10.5281/zenodo.18617201)66.
References
Ball, P. Water is an active matrix of life for cell and molecular biology. Proc. Natl. Acad. Sci. USA. 114, 13327–13335 (2017).
Chaplin, M. Opinion - do we underestimate the importance of water in cell biology? Nat. Rev. Mol. Cell Bio. 7, 861–866 (2006).
Watson, J. L. et al. Macromolecular condensation buffers intracellular water potential. Nature 623, 842–852 (2023).
Laage, D., Elsaesser, T. & Hynes, J. T. Water dynamics in the hydration shells of biomolecules. Chem. Rev. 117, 10694–10725 (2017).
Qin, Y. Z., Wang, L. J. & Zhong, D. P. Dynamics and mechanism of ultrafast water-protein interactions. Proc. Natl. Acad. Sci. USA. 113, 8424–8429 (2016).
Israelachvili, J. & Wennerstrom, H. Role of hydration and water structure in biological and colloidal interactions. Nature 379, 219–225 (1996).
Fernández, A. & Scheraga, H. A. Insufficiently dehydrated hydrogen bonds as determinants of protein interactions. Proc. Natl. Acad. Sci. USA. 100, 113–118 (2003).
Mondal, S., Mukherjee, S. & Bagchi, B. Protein hydration dynamics: Much ado about nothing? J. Phys. Chem. Lett. 8, 4878–4882 (2017).
Bellissent-Funel, M. C. et al. Water determines the structure and dynamics of proteins. Chem. Rev. 116, 7673–7697 (2016).
Ball, P. Water as an active constituent in cell biology. Chem. Rev. 108, 74–108 (2008).
Rego, N. B., Ferguson, A. L. & Patel, A. J. Learning the relationship between nanoscale chemical patterning and hydrophobicity. Proc. Natl. Acad. Sci. USA. 119, e2200018119 (2022).
Harris, R. C. & Pettitt, B. M. Effects of geometry and chemistry on hydrophobic solvation. Proc. Natl. Acad. Sci. USA. 111, 14681–14686 (2014).
Xi, E. T. et al. Hydrophobicity of proteins and nanostructured solutes is governed by topographical and chemical context. Proc. Natl. Acad. Sci. Usa. 114, 13345–13350 (2017).
Chandler, D. Interfaces and the driving force of hydrophobic assembly. Nature 437, 640–647 (2005).
Davis, J. G., Gierszal, K. P., Wang, P. & Ben-Amotz, D. Water structural transformation at molecular hydrophobic interfaces. Nature 491, 582–585 (2012).
Bandyopadhyay, S., Chakraborty, S. & Bagchi, B. Secondary structure sensitivity of hydrogen bond lifetime dynamics in the protein hydration layer. J. Am. Chem. Soc. 127, 16660–16667 (2005).
Nickels, J. D. et al. Dynamics of protein and its hydration water: Neutron scattering studies on fully deuterated gfp. Biophys. J. 103, 1566–1575 (2012).
Kyte, J. & Doolittle, R. F. A simple method for displaying the hydropathic character of a protein. J. Mol. Bio. 157, 105–132 (1982).
Wimberger, L. et al. Large, tunable, and reversible ph changes by merocyanine photoacids. J. Am. Chem. Soc. 143, 20758–20768 (2021).
Corbella, M., Pinto, G. P. & Kamerlin, S. C. L. Loop dynamics and the evolution of enzyme activity. Nat. Rev. Chem. 7, 536–547 (2023).
Zinovjev, K. et al. Activation and friction in enzymatic loop opening and closing dynamics. Nat. Commun. 15, 2490 (2024).
Stec, B., Holtz, K. M. & Kantrowitz, E. R. A revised mechanism for the alkaline phosphatase reaction involving three metal ions. J. Mol. Biol. 299, 1303–1311 (2000).
Chin, J. W. S. et al. Addition of p-azido-l-phenylalanine to the genetic code of Escherichia coli. J. Am. Chem. Soc. 124, 9026–9027 (2002).
Becker, W. et al. Fluorescence lifetime imaging by time-correlated single-photon counting. Microsc. Res. Tech. 63, 58–66 (2004).
Bai, Y. L. et al. Derivatizing merocyanine dyes to balance their polarity and viscosity sensitivities for protein aggregation detection. Chem. Commun. 57, 13313–13316 (2021).
Hou, G. H. & Cui, Q. Stabilization of different types of transition states in a single enzyme active site: QM/MM analysis of enzymes in the alkaline phosphatase superfamily. J. Am. Chem. Soc. 135, 10457–10469 (2013).
Mattea, C., Qvist, J. & Halle, B. Dynamics at the protein-water interface from 17O spin relaxation in deeply supercooled solutions. Biophys. J. 95, 2951–2963 (2008).
Zheng, C. et al. A two-directional vibrational probe reveals different electric field orientations in solution and an enzyme active site. Nat. Chem. 14, 891–897 (2022).
Liu, J. F., He, X., Zhang, J. Z. H. & Qi, L. W. Hydrogen-bond structure dynamics in bulk water: Insights from simulations with coupled cluster theory. Chem. Sci. 9, 2065–2073 (2018).
Dai, D. H. et al. Room-temperature dynamic nuclear polarization enhanced NMR spectroscopy of small biological molecules in water. Nat. Commun. 12, 6880 (2021).
Noll, N. & Würthner, F. Bioinspired water preorganization in confined space for efficient water oxidation catalysis in metallosupramolecular ruthenium architectures. Acc. Chem. Res. 57, 1538–1549 (2024).
Rego, N. B. & Patel, A. J. Understanding hydrophobic effects: Insights from water density fluctuations. Annu. Rev. Condens. Matter Phys. 13, 303–324 (2022).
Gonella, G. et al. Water at charged interfaces. Nat. Rev. Chem. 5, 466–485 (2021).
Qiao, B. F., Jiménez-Angeles, F., Nguyen, T. D. & de la Cruz, M. O. Water follows polar and nonpolar protein surface domains. Proc. Natl. Acad. Sci. USA. 116, 19274–19281 (2019).
Pezzotti, S. et al. Terahertz calorimetry spotlights the role of water in biological processes. Nat. Rev. Chem. 1–14 (2025).
Böhm, F., Schwaab, G. & Havenith, M. Mapping hydration water around alcohol chains by THz calorimetry. Angew. Chem. Int. Ed. 56, 9981–9985 (2017).
Pezzotti, S. et al. Spectroscopic fingerprints of cavity formation and solute insertion as a measure of hydration entropic loss and enthalpic gain. Angew. Chem. Int. Ed. 61, e202203893 (2022).
Lorenz-Fonfria, V. A. Infrared difference spectroscopy of proteins: From bands to bonds. Chem. Rev. 120, 3466–3576 (2020).
Rupley, J. A. & Careri, G. Protein hydration and function. Adv. Protein Chem. 41, 37–172 (1991).
Woods, D. A. & Bain, C. D. Total internal reflection spectroscopy for studying soft matter. Soft Matter 10, 1071–1096 (2014).
Bakulin, A. A., Pshenichnikov, M. S., Bakker, H. J. & Petersen, C. Hydrophobic molecules slow down the hydrogen-bond dynamics of water. J. Phys. Chem. A 115, 1821–1829 (2011).
Laage, D. & Hynes, J. T. A molecular jump mechanism of water reorientation. Science 311, 832–835 (2006).
Brünig, F. N., Rammler, M., Adams, E. M., Havenith, M. & Netz, R. R. Spectral signatures of excess-proton waiting and transfer-path dynamics in aqueous hydrochloric acid solutions. Nat. Commun. 13, 4210 (2022).
Heyden, M. et al. Dissecting the THz spectrum of liquid water from first principles via correlations in time and space. Proc. Natl. Acad. Sci. USA. 107, 12068–12073 (2010).
Paesani, F., Zhang, W., Case, D. A., Cheatham, T. E. 3rd & Voth, G. A. An accurate and simple quantum model for liquid water. J. Chem. Phys. 125, 184507 (2006).
Michaud-Agrawal, N., Denning, E. J., Woolf, T. B. & Beckstein, O. Software news and updates mdanalysis: A toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 32, 2319–2327 (2011).
Du, Z. W. et al. The sequence-structure-function relationship of intrinsic erα disorder. Nature 638, 1130–1138 (2025).
Lee, Y. et al. Ultrafast coherent motion and helix rearrangement of homodimeric hemoglobin visualized with femtosecond x-ray solution scattering. Nat. Commun. 12, 3677 (2021).
Gomez, A., Thompson, W. H. & Laage, D. Neural-network-based molecular dynamics simulations reveal that proton transport in water is doubly gated by sequential hydrogen-bond exchange. Nat. Chem. 16, 1838–1844 (2024).
Giubertoni, G., Bonn, M. & Woutersen, S. D2o as an imperfect replacement for H2O: Problem or opportunity for protein research. J. Phys. Chem. B 127, 8086–8094 (2023).
Grossman, M. et al. Correlated structural kinetics and retarded solvent dynamics at the metalloprotease active site. Nat. Struct. Mol. Biol. 18, 1102–U1113 (2011).
Li, C., Iscen, A., Palmer, L. C., Schatz, G. C. & Stupp, S. I. Light-driven expansion of spiropyran hydrogels. J. Am. Chem. Soc. 142, 8447–8453 (2020).
Kang, E. et al. Specific adsorption of histidine-tagged proteins on silica surfaces modified with Ni2+/NTA-derivatized poly(ethylene glycol). Langmuir 23, 6281–6288 (2007).
Cha, T., Guo, A. & Zhu, X. Y. Enzymatic activity on a chip: The critical role of protein orientation. Proteomics 5, 416–419 (2005).
Maier, J. A. et al. ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB. J. Chem. Theory Comput. 11, 3696–3713 (2015).
Frisch, M. J. et al. Gaussian 16, Revision A.03 (Gaussian, Inc., Wallingford, CT, 2016).
Wang, J., Wolf, R. M., Caldwell, J. W., Kollman, P. A. & Case, D. A. Development and testing of a general amber force field. J. Comput. Chem. 25, 1157–1174 (2004).
Panteva, M. T., Giambasu, G. M. & York, D. M. Comparison of structural, thermodynamic, kinetic and mass transport properties of Mg2+ ion models commonly used in biomolecular simulations. J. Comput. Chem. 36, 970–982 (2015).
Li, P. F. & Merz, K. M. Taking into account the ion-induced dipole interaction in the nonbonded model of ions. J. Chem. Theory Comput. 10, 289–297 (2014).
Case, D. A. et al. AMBER 23 (University of California, San Francisco, 2023).
Cock, P. J. A. et al. Biopython: Freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25, 1422–1423 (2009).
Rdkit/rdkit: 2024_09_5 (q3 2024) release (release_2024_09_5) v. 2024_09_5 (Zenodo, 2025).
Tosco, P., Stiefl, N. & Landrum, G. Bringing the MMFF force field to the RDKit: implementation and validation. J. Cheminform. 6, 37 (2014).
Berens, P. H., White, S. R. & Wilson, K. R. Molecular dynamics and spectra II. Diatomic Raman. J. Chem. Phys. 75, 515–529 (1981).
iawnix. iawnix/CovCom: v10 (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.18617244 (2026).
iawnix. iawnix/WatAna: v10 (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.18617201 (2026).
Acknowledgements
This work was supported by the National Key R&D Program of China (2024YFA1700050, 2019YFA0905200), the National Natural Science Foundation of China (22225403, 22204053, 92477103, 22273023), Shanghai Municipal Science and Technology Commission with Grant (25511102400), Shanghai Municipal Natural Science Foundation (23ZR1418200), Natural Science Foundation of Chongqing, China (CSTB2023NSCQ-MSX0616), Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, Shanghai Future Discipline Program (Quantum Science and Technology), Shanghai Municipal Education Commission’s “Artificial Intelligence-Driven Research Paradigm Reform and Discipline Advancement Program”, and the Fundamental Research Funds for the Central Universities. East China Normal University “Artificial Intelligence” Seed Grant Program (40500-20101-222438). We acknowledge the Shanghai Synchrotron Radiation Facility (SSRF) BL06B beamline (https://cstr.cn/31124.02.SSRF.BL06B) for experimental measurement assistance, and the BL19U2 beamline (https://cstr.cn/31129.02.NFPS.BL19U2) at the National Facility for Protein Science in Shanghai (NFPS, https://cstr.cn/31129.02.NFPS) for technical support with data collection and analysis. We also thank the Supercomputer Center of East China Normal University (ECNU Multifunctional Platform for Innovation 001) for providing computer resources.
Author information
Authors and Affiliations
Contributions
Y.Y.L. and D.L. conceived the study and designed experiments. J.H.Z. and X.H. performed and analyzed molecular dynamics simulations. Y.Y.L. conducted THz spectroscopy, SAXS measurements, and enzymatic activity assays. J.J.G. and H.Y.G. carried out fluorescence lifetime experiments and analyzed the corresponding data. S.S.C. and D.M. engineered, expressed, and purified mutant ALP variants. H.W.Z. optimized data visualization. B.S. guided the analysis for THz data interpretation. Y.Y.L. and D.L. prepared the manuscript draft and created key figures, with critical revisions from all authors. D.L., D.M., and X.H. supervised the project. Y.Y.L. and J.H.Z. contributed equally to this work.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work. A peer review file is available.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Source data
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Liu, Y., Zhai, J., Cao, S. et al. Single-engineered-residue solvation perturbations regulate global protein architecture and function. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70155-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41467-026-70155-2
