Protein rarely works alone but in complex with other molecules, performing in a more coordinated fashion and efficiently. Cellular processes in which protein-protein interactions (PPIs) go awry lead to protein aggregation by turning normally soluble proteins into insoluble neurotoxic proteins, frequently implicated in disorders, most notably neurodegenerative diseases such as Creutzfeldt-Jacob disease (CJD), Alzheimer’s disease (AD), Huntington’s disease (HD), Parkinson’s disease (PD), and multiple sclerosis (MS). In order to gain a better understanding of such neurodegenerative disorders and their diagnosis and treatment, it is thus of utmost importance to identify and characterize PPIs at the submolecular level and their role in the development and progression of neurodegenerative disorders. Here we present a novel and reliable computational tool to automatically detect and visualize H-bond-mediated PPIs in a protein-protein complex (Fig. 1). In order to accurately identify such PPIs, the algorithm was first trained to determine the H-bond donor-acceptor distances in the high-resolution protein crystal structures available in the PDB. This tool also saves its detailed text output for a further profiling of PPIs, e.g., if a PPI is specific based on the covariation pattern between its two interacting amino acid residues.

Identification and visualization of protein-protein interactions in protein-protein complex structure

2019 Fall National Meeting

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