Characterization of Protein–Protein Interfaces through a Protein Contact Network Approach

Abstract

Anthrax toxin comprises three different proteins, jointly acting to exert toxic activity: a non-toxic protective agent (PA), toxic edema factor (EF), and lethal factor (LF). Binding of PA to anthrax receptors promotes oligomerization of PA, binding of EF and LF, and then endocytosis of the complex. Homomeric forms of PA, complexes of PA bound to LF and to the endogenous receptor capillary morphogenesis gene 2 (CMG2) were analyzed. In this work, we characterized protein–protein interfaces (PPIs) and identified key residues at PPIs of complexes, by means of a protein contact network (PCN) approach. Flexibility and global and local topological properties of each PCN were computed. The vulnerability of each PCN was calculated using different node removal strategies, with reference to specific PCN topological descriptors, such as participation coefficient, contact order, and degree. The participation coefficient P, the topological descriptor of the node’s ability to intervene in protein inter-module communication, was the key descriptor of PCN vulnerability of all structures. High P residues were localized both at PPIs and other regions of complexes, so that we argued an allosteric mechanism in protein–protein interactions. The identification of residues, with key role in the stability of PPIs, has a huge potential in the development of new drugs, which would be designed to target not only PPIs but also residues localized in allosteric regions of supramolecular complexes.

The Discovery of a Putative Allosteric Site in the SARS-CoV-2 Spike Protein Using an Integrated Structural/Dynamic Approach

“…The integrated computational approach disclosed active zones in the SARS-CoV and SARS-CoV2 complexes with the ACE2 ectodomain. These active zones, as demonstrated in previous studies 41,60,61 and in the present research by the convergence among different approaches, have an extremely high probability of acting as allosteric sites, which can modulate spike/ACE2 protein binding.…”

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case

“…In case of the protein backbone network (PBN), Cα atoms are generally considered as the representative of nodes and a distance of about 6.5 Å or less (based on the radial distribution of Cα atoms in protein structures) between any two sequentially non-adjacent residues are considered as an edge (Miyazawa and Jernigan, 1985;Patra and Vishveshwara, 2000). The construction and application of PBN have been extensively discussed in earlier reviews (Greene, 2012;Di Paola et al, 2015). Here, our focus is on the technical details of construction and the subsequent application of amino acid side-chain-based protein structure networks denoted as PScN (or PSN).…”

Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case

“…High P residues are spotted in the structure and mostly (but not necessarily) placed in the interchain region. In previous works [ 35 , 37 , 51 , 75 ], we demonstrated that the participation coefficient P addresses the functional role of residues in protein binding and, in general, identifies residues with a key role in protein structural and functional features.…”

“…The analysis was performed by means of a purposed software implemented in Matlab environment v 2014a, including functions from Bioinformatics Toolbox. Heat maps of P variation (comparison between holo and apo forms), Guimerà-Amaral cartography and clusters onto the protein ribbon representation, have been produced by means of a purposed Python script compiled in the embedded Python environment; for further details and application of the method see [ 37 ].…”

“…Both ENM and PCN offer computationally efficient tools to study the structure and function of protein complexes [ 33 , 34 ], from predicting functionally important residues [ 35 , 36 ], to characterize protein-protein interactions [ 37 , 38 ] and allosteric communication paths [ 39 , 40 ]. Of course, both models have strengths and weaknesses and their comparative study is needed.…”