Abstract
The native conformation of structured proteins is stabilized by a complex network of interactions. We analyzed the elementary patterns that constitute such network and ranked them according to their importance in sha** protein sequence design. To achieve this goal, we employed a cluster expansion of the partition function in the space of sequences and evaluated numerically the statistical importance of each cluster. An important feature of this procedure is that it is applied to a dense finite system. We found that patterns that contribute most to the partition function are cycles with even numbers of nodes, while cliques are typically detrimental. Each cluster also gives a contribute to the sequence entropy, which is a measure of the evolutionary designability of a fold. We compared the entropies associated with different interaction patterns to their abundances in the native structures of real proteins.
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Data Availability Statement
All data and codes used in this work can be downloaded from https://github.com/guidotiana/cluster-expansion.
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MT performed the numerical calculations and helped to develop the theoretical calculations; AT and GT developed the theoretical calculations; GT wrote the manuscript with the help of MT and AT.
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Tajana, M., Trovato, A. & Tiana, G. Key interaction patterns in proteins revealed by cluster expansion of the partition function. Eur. Phys. J. E 45, 95 (2022). https://doi.org/10.1140/epje/s10189-022-00250-x
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DOI: https://doi.org/10.1140/epje/s10189-022-00250-x