TCoCPIn: Unveiling Topological Characteristics of Chemical-Protein Interaction Networks for Discovering Novel Features in Interactions

Abstract

The complexity of drug mechanisms of action, disease pathology, and protein function stems from the intricacies of chemical-protein interaction (CPI) networks. However, the lack of innovative analytical methods has hindered our ability to decipher the organization and function of CPI networks. To this end, we propose a new method, TCoCPIn, to reveal hidden patterns and relationships in CPI networks by applying topological features. By combining network topology with CPI data, TCoCPIn is able to discover new features in interactions, thereby facilitating the development of innovative therapeutic strategies. Through comprehensive analysis of specific datasets, we demonstrate the effectiveness of TCoCPIn in revealing small-world properties, key nodes, and communities in CPI networks, which may be associated with drug efficacy or toxicity. Our pioneering approach highlights the potential of topological analysis to elucidate the organization and function of CPI networks, thereby advancing drug discovery and improving our understanding of disease mechanisms.