This paper proposes a novel application of cohomology to protein structure analysis. Since proteins interact each other by forming transient protein complexes, their shape (e.g., shape complementarity) plays an important role in their functions. In our mathematical toy models, proteins are represented as a loop of triangles (2D model) or tetrahedra (3D model), where their interactions are defined as fusion of loops. The purpose of this paper is to describe the conditions for loop fusion using the language of cohomology. In particular, this paper uses cohomology to describe the conditions for “allosteric regulation”, which has been attracted attention in safer drug discovery. I hope that this paper will provide a new perspective on the mechanism of allosteric regulation. Advantages of the model include its topological nature. That is, we can deform the shape of loops by deforming the shape of triangles (or tetrahedra) as long as their folded structures are preserved. Another advantage is the simplicity of the “allosteric regulation” mechanism of the model. Furthermore, the effect of the “post-translational modification” can be understood as a resolution of singularities of a flow of triangles (or tetrahedra). No prior knowledge of either protein science, exterior calculus, or cohomology theory is required. The author hopes that this paper will facilitate the interaction between mathematics and protein science.
References
[1]
Morikawa, N. (2017) Discrete Differential Geometry and the Structural Study of Protein Complexes. Open Journal of Discrete Mathematics, 7, 148-164. https://doi.org/10.4236/ojdm.2017.73014
[2]
Morikawa, N. (2018) Global Geometrical Constraints on the Shape of Proteins and Their Influence on Allosteric Regulation. Applied Mathematics, 9, 1116-1155. https://doi.org/10.4236/am.2018.910076
[3]
Liu, J. and Nussinov, R. (2016) Allostery: An Overview of Its History, Concepts, Methods, and Applications. PLOS Computational Biology, 12, e1004966. https://doi.org/10.1371/journal.pcbi.1004966
[4]
Pinčák, R., Kanjamapornkul, K. and Bartoš, E. (2020) Cohomology Theory for Biological Time Series. Mathematical Methods in the Applied Sciences, 43, 552-579. https://doi.org/10.1002/mma.5906
[5]
Grover, A.K. (2013) Use of Allosteric Targets in the Discovery of Safer Drugs. Medical Principles and Practice, 22, 418-426. https://doi.org/10.1159/000350417
[6]
Wu, N., Strőmich, L. and Yaliraki, N.Y. (2022) Prediction of Allosteric Sites and Signaling: Insights from Benchmarking Datasets. Patterns, 3, 100408. https://doi.org/10.1016/j.patter.2021.100408
[7]
Xu, H., Wang, Y., Lin, S., Deng, W., Peng, D., Cui, Q. and Xue, Y. (2018) PTMD: A Database of Human Disease-Associated Post-Translational Modifications. Genomics, Proteomics & Bioinformatics, 16, 244-251. https://doi.org/10.1016/j.gpb.2018.06.004
[8]
Crane, C. (2021, Feb 24). Lecture 9: Discrete Exterior Calculus (Discrete Differential Geometry) [Video]. YouTube. https://www.youtube.com/watch?v=-cUhuzwW-_A
[9]
Crane, C. (2022, May 2) Discreet Differential Geometry: An Applied Introduction. 1-172. https://www.cs.cmu.edu/~kmcrane/Projects/DDG/paper.pdf
[10]
Morikawa, N. (2021) Two Mathematical Approaches to Inferring the Internal Structure of Proteins from Their Shape. Global Journal of Science Frontier Research: F, 21, 1-25. https://doi.org/10.34257/GJSFRFVOL21IS3PG1