- Physical Review Journals
All JournalsPhysics Magazine

Physical Review Research

Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Letter
  • Open Access

Anisotropic van der Waals dispersion forces in polymers: Structural symmetry breaking leads to enhanced conformational search

Mario Galante* and Alexandre Tkatchenko†

  • Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg

  • *mario.galante@uni.lu
  • †Corresponding author: alexandre.tkatchenko@uni.lu
PDF

Phys. Rev. Research 5, L012028 – Published 27 February, 2023

DOI: https://doi.org/10.1103/PhysRevResearch.5.L012028

Abstract

The modeling of conformations and dynamics of (bio)polymers is of primary importance for understanding the physicochemical properties of soft matter. Although short-range interactions such as covalent and hydrogen bonding control the local arrangement of polymers, noncovalent interactions play a dominant role in determining the global conformations. Here, we focus on how the inclusion of many-body effects in van der Waals (vdW) dispersion influences the molecular dynamics of model polymers and a polyalanine chain studied with semiempirical quantum mechanics. We show that delocalized force contributions are key to exploring the conformational landscape, as they induce an anisotropic polarization response which efficiently guides the conformation towards globally optimized structures. This is in contrast with the commonly used pairwise interatomic Lennard-Jones-like potentials, which result in structures that optimize local regularity rather than global symmetries. The many-body vdW formalism results in a significant reduction in the roughness of the energy landscape and drives the conformational search towards geometries that are consistent with global spatial symmetries.

View figure in article

Physics Subject Headings (PhySH)

Article Text

References (37)

  1. Z. Bu and D. J. E. Callaway, Proteins move! Protein dynamics and long-range allostery in cell signaling, in Protein Structure and Diseases, edited by R. Donev, Advances in Protein Chemistry and Structural Biology Vol. 83 (Academic, Cambridge, MA, 2011), Chap. 5, pp. 163–221.
  2. B. Adhikari and S. Majumdar, Polymers in sensor applications, Prog. Polym. Sci. 29, 699 (2004).
  3. R. Dersch, M. Steinhart, U. Boudriot, A. Greiner, and J. H. Wendorff, Nanoprocessing of polymers: applications in medicine, sensors, caralysis, photonics, Polym. Adv. Technol. 16, 276 (2005).
  4. B. D. Ulery, L. S. Nair, and C. T. Laurencin, Biomedical applications of biodegradable polymers, J. Polym. Sci., Part B: Polym. Phys. 49, 832 (2011).
  5. S. Napolitano, Non-Equilibrium Phenomena in Confined Soft Matter (Springer, Berlin, 2015).
  6. J. S. Fraser, M. W. Clarkson, S. C. Degnan, R. Erion, D. Kern, and T. Alber, Hidden alternative structures of proline isomerase essential for catalysis, Nature (London) 462, 669 (2009).
  7. V. N. Uversky, Intrinsic disorder in proteins associated with neurodegenerative diseases, in Protein Folding and Misfolding: Neurodegenerative Diseases, edited by J. Ovádi and F. Orosz (Springer, Berlin, 2009), pp. 21–75.
  8. P. C. T. Souza, R. Alessandri, J. Barnoud, S. Thallmair, I. Faustino, F. Grünewald, I. Patmanidis, H. Abdizadeh, B. M. H. Bruininks, T. A. Wassenaar, P. C. Kroon et al., Martini 3: a general purpose force field for coarse-grained molecular dynamics, Nat. Methods 18, 382 (2021).
  9. O. T. Unke, S. Chmiela, M. Gastegger, K. T. Schütt, H. E. Sauceda, and K.-R. Müller, Spookynet: Learning force fields with electronic degrees of freedom and nonlocal effects, Nat. Commun. 12, 7273 (2021).
  10. O. T. Unke, S. Chmiela, H. E. Sauceda, M. Gastegger, I. Poltavsky, K. T. Schütt, A. Tkatchenko, and K.-R. Müller, Machine learning force fields, Chem. Rev. 121, 10142 (2021).
  11. H. D. Tran and R. Ramprasad, Polymer structure prediction from first principles, J. Phys. Chem. Lett. 11, 10081 (2020).
  12. S. Abeln, K. A. Feenstra, and J. Heringa, Protein three-dimensional structure prediction, in Encyclopedia of Bioinformatics and Computational Biology, edited by S. Ranganathan (Elsevier, Amsterdam, 2019), Vol. 2, p. 497.
  13. J. Hermann, R. A. DiStasio, Jr., and A. Tkatchenko, First-principles models for van der Waals interactions in molecules and materials: Concepts, theory, and applications, Chem. Rev. 117, 4714 (2017).
  14. M. Stöhr and A. Tkatchenko, Quantum mechanics of proteins in explicit water, Sci. Adv. 5, eaax0024 (2019).
  15. A. Tkatchenko and M. Scheffler, Accurate Molecular van der Waals Interactions from Ground-State Electron Density and Free-Atom Reference Data, Phys. Rev. Lett. 102, 073005 (2009).
  16. T. Sato and H. Nakai, Density functional method including weak interactions: Dispersion coefficients based on the local response approximation, J. Chem. Phys. 131, 224104 (2009).
  17. S. Grimme, J. Antony, S. Ehrlich, and H. Krieg, A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu, J. Chem. Phys. 132, 154104 (2010).
  18. J. F. Dobson, Beyond pairwise additivity in London dispersion interactions, Int. J. Quantum Chem. 114, 1157 (2014).
  19. A. Ambrosetti, N. Ferri, R. A. DiStasio, Jr., and A. Tkatchenko, Wavelike charge density fluctuations and van der Waals interactions at the nanoscale, Science 351, 1171 (2016).
  20. P. Hauseux, T. Nguyen, A. Ambrosetti, K. S. Ruiz, S. P. A. Bordas, and A. Tkatchenko, From quantum to continuum mechanics in the delamination of atomically-thin layers from substrates, Nat. Commun. 11, 1651 (2020).
  21. A. Tkatchenko, A. Ambrosetti, and R. A. DiStasio, Jr., Interatomic methods for the dispersion energy derived from the adiabatic connection fluctuation-dissipation theorem, J. Chem. Phys. 138, 074106 (2013).
  22. A. Tkatchenko, R. A. DiStasio Jr., R. Car, and M. Scheffler, Accurate and Efficient Method for Many-Body van der Waals Interactions, Phys. Rev. Lett. 108, 236402 (2012).
  23. P. Hauseux, A. Ambrosetti, S. P. A. Bordas, and A. Tkatchenko, Colossal Enhancement of Atomic Force Response in van der Waals Materials Arising from Many-Body Electronic Correlations, Phys. Rev. Lett. 128, 106101 (2022).
  24. M. R. Hoare and J. McInnes, Statistical mechanics and morphology of very small atomic clusters, Faraday Discuss. Chem. Soc. 61, 12 (1976).
  25. M. R. Hoare and J. McInnes, Morphology and statistical statics of simple microclusters, Adv. Phys. 32, 791 (1983).
  26. J. P. K. Doye and D. J. Wales, On potential energy surfaces and relaxation to the global minimum, J. Chem. Phys. 105, 8428 (1996).
  27. M. C. Rechtsman, F. H. Stillinger, and S. Torquato, Optimized Interactions for Targeted Self-Assembly: Application to a Honeycomb Lattice, Phys. Rev. Lett. 95, 228301 (2005).
  28. M. C. Rechtsman, F. H. Stillinger, and S. Torquato, Designed interaction potentials via inverse methods for self-assembly, Phys. Rev. E 73, 011406 (2006).
  29. L. Milanesi, J. P. Waltho, C. A. Hunter, D. J. Shaw, G. S. Beddard, G. D. Reid, S. Dev, and M. Volk, Measurement of energy landscape roughness of folded and unfolded proteins, Proc. Natl. Acad. Sci. USA 109, 19563 (2012).
  30. B. Hourahine, B. Aradi, V. Blum, F. Bonafé, A. Buccheri, C. Camacho, C. Cevallos, M. Y. Deshaye, T. Dumitrică, A. Dominguez, S. Ehlert, M. Elstner, T. van der Heide, J. Hermann, S. Irle, J. J. Kranz, C. Köhler, T. Kowalczyk, T. Kubař, I. S. Lee et al., DFTB+, a software package for efficient approximate density functional theory based atomistic simulations, J. Chem. Phys. 152, 124101 (2020).
  31. D. Osmanovic and Y. Rabin, Effect of non-specific interactions on formation and stability of specific complexes, J. Chem. Phys. 144, 205104 (2016).
  32. A. Chakrabartty and R. L. Baldwin, Stability of α-helices, Adv. Protein Chem. 46, 141 (1995).
  33. B. M. P. Huyghues-Despointes, T. M. Klinger, and R. L. Baldwin, Measuring the strength of side-chain hydrogen bonds in peptide helices: the Gln·Asp (i,i+4) interaction, Biochemistry 34, 13267 (1995).
  34. S.-S. Sung, Dielectric screening effect of electronic polarization and intramolecular hydrogen bonding, Protein Sci. 26, 2003 (2017).
  35. O. T. Unke et al., Accurate machine learned quantum-mechanical force fields for biomolecular simulations, arXiv:2205.08306.
  36. A. M. Reilly and A. Tkatchenko, Role of Dispersion Interactions in the Polymorphism and Entropic Stabilization of the Aspirin Crystal, Phys. Rev. Lett. 113, 055701 (2014).
  37. See https://hpc.uni.lu/.

Outline

Information

Phys. Rev. Research 5, L012028– Published 27 February, 2023
  • Received 15 October 2021
  • Revised 24 August 2022
  • Accepted 17 January 2023
Crossmark - Check for updates button
Creative Commons Logo

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation