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The de Rham–Hodge Analysis and Modeling of Biomolecules

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Abstract

Biological macromolecules have intricate structures that underpin their biological functions. Understanding their structure–function relationships remains a challenge due to their structural complexity and functional variability. Although de Rham–Hodge theory, a landmark of twentieth-century mathematics, has had a tremendous impact on mathematics and physics, it has not been devised for macromolecular modeling and analysis. In this work, we introduce de Rham–Hodge theory as a unified paradigm for analyzing the geometry, topology, flexibility, and Hodge mode analysis of biological macromolecules. Geometric characteristics and topological invariants are obtained either from the Helmholtz–Hodge decomposition of the scalar, vector, and/or tensor fields of a macromolecule or from the spectral analysis of various Laplace–de Rham operators defined on the molecular manifolds. We propose Laplace–de Rham spectral-based models for predicting macromolecular flexibility. We further construct a Laplace–de Rham–Helfrich operator for revealing cryo-EM natural frequencies. Extensive experiments are carried out to demonstrate that the proposed de Rham–Hodge paradigm is one of the most versatile tools for the multiscale modeling and analysis of biological macromolecules and subcellular organelles. Accurate, reliable, and topological structure-preserving algorithms for implementing discrete exterior calculus (DEC) have been developed to facilitate the aforementioned modeling and analysis of biological macromolecules. The proposed de Rham–Hodge paradigm has potential applications to subcellular organelles and the structure construction from medium- or low-resolution cryo-EM maps, and functional predictions from massive biomolecular datasets.

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Acknowledgements

This work was supported in part by NSF Grants DMS-1721024, DMS-1761320, and IIS1900473 and NIH Grant GM126189. GWW was also funded by Bristol-Myers Squibb and Pfizer.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, 48824, USA

    Rundong Zhao & Yiying Tong

  2. Department of Mathematics, Michigan State University, East Lansing, MI, 48824, USA

    Menglun Wang, Jiahui Chen & Guo-Wei Wei

  3. Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48824, USA

    Guo-Wei Wei

  4. Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA

    Guo-Wei Wei

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  1. Rundong Zhao
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  2. Menglun Wang
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Zhao, R., Wang, M., Chen, J. et al. The de Rham–Hodge Analysis and Modeling of Biomolecules. Bull Math Biol 82, 108 (2020). https://doi.org/10.1007/s11538-020-00783-2

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