Simulated Epidemics in 3D Protein Structures to Detect Functional Properties

Abstract

The outcome of an epidemic is closely related to the network of interactions between the individuals. Likewise, protein functions depend on the 3D arrangement of their residues and on the underlying energetic interaction network. Borrowing ideas from the theoretical framework that has been developed to address the spreading of real diseases, we study the diffusion of a fictitious epidemic inside the protein non-bonded interaction network. Our approach allowed to probe the overall stability and the capability to propagate information in the complex 3D-structures and proved to be very efficient in addressing different problems, from the assessment of thermal stability to the identification of allosteric sites.

9 pages, 5 figures

References in corpus (6)

• Statistical mechanics of complex networks
• Statistical physics of social dynamics
• Epidemic processes in complex networks
• Hydrophobic, hydrophilic and charged amino acids' networks within Protein
• Prediction of allosteric sites and mediating interactions through bond-to-bond propensities
• Immunization of traffic-driven epidemic spreading

Cited by in corpus (5)

• Investigating the side-chain structural organization behind the stability of protein folding and binding
• Electrostatic complementarity at the interface drives transient protein-protein interactions
• In-Silico evidence for two receptors based strategy of SARS-CoV-2
• Fractional-order susceptible-infected model: definition and applications to the study of COVID-19 main protease
• Compact assessment of molecular surface complementarities enhances neural network-aided prediction of key binding residues