Creative elements: network-based predictions of active centres in proteins, cellular and social networks

TL;DR

This paper proposes a network-based approach to predict active centres in proteins, cells, social networks, and ecosystems, highlighting the role of 'creative elements' in system adaptability and evolution.

Contribution

It extends residue network analysis from proteins to broader complex systems, introducing the concept of 'creative elements' as active centres across various networks.

Findings

Network properties enable prediction of active centres.

Active centres are linked to system adaptability.

Method applicable across biological and social systems.

Abstract

Active centres and hot spots of proteins have a paramount importance in enzyme action, protein complex formation and drug design. Recently a number of publications successfully applied the analysis of residue networks to predict active centres in proteins. Most real-world networks show a number of properties, such as small-worldness or scale-free degree distribution, which are rather general features of networks, from molecules to society at large. Using analogy I propose that existing findings and methodology already enable us to detect active centres in cells, and can be expanded to social networks and ecosystems. Members of these active centres are termed here as creative elements of their respective networks, which may help them to survive unprecedented, novel challenges, and play a key role in the development, survival and evolvability of complex systems.