Intermolecular β-strand networks avoid hub residues and favor low interconnectedness: a potential protection mechanism against chain dissociation upon mutation

Topology Results on Adjacent Amino Acid Networks of Oligomeric Proteins

In this chapter, we focus on topology measurements of the adjacent amino acid networks for a data set of oligomeric proteins and some of its subnetworks. The aim is to present many mathematical tools in order to understand the structures of proteins implicitly coded in such networks and subnetworks. We mainly investigate four important networks by computing the number of connected components, the degree distribution, and assortativity measures. We compare each result in order to prove that the four networks have quite independent topologies.

Coil conversion to β-strand induced by dimerization

Most molecular processes in living organisms rely on protein-protein interactions, many of which are mediated by β-sheet interfaces; this study investigates the formation of β-sheet interfaces through the conversion of coils into β-strands. Following an exhaustive search in the Protein Data Bank, the corresponding structural dimorphic fragments were extracted, characterized, and analyzed. Their short strand lengths and specific amino acid profiles indicate that dimorphic β-strand interfaces are likely to be less stable than standard ones and could even convert to coil interfaces if their environment changes. Moreover, the construction of a simple classifier able to discriminate between the sequences of dimorphic and standard β-strand interfaces suggests that the nature of those dimorphic sequences could be predicted, providing a novel means of identifying proteins capable of forming dimers.

In proteins, the structural responses of a position to mutation rely on the Goldilocks principle: not too many links, not too few

A disease has distinct genetic and molecular hallmarks such as sequence variants that are likely to produce the alternative protein structures accountable for individual responses to drugs and disease development.

Protein structural robustness to mutations: an in silico investigation

Proteins possess qualities of robustness and adaptability to perturbations such as mutations, but occasionally fail to withstand them, resulting in loss of function. Herein, the structural impact of mutations is investigated independently of the functional impact. Primarily, we aim at understanding the mechanisms of structural robustness pre-requisite for functional integrity. The structural changes due to mutations propagate from the site of mutation to residues much more distant than typical scales of chemical interactions, following a cascade mechanism. This can trigger dramatic changes or subtle ones, consistent with a loss of function and disease or the emergence of new functions. Robustness is enhanced by changes producing alternative structures, in good agreement with the view that proteins are dynamic objects fulfilling their functions from a set of conformations. This result, robust alternative structures, is also coherent with epistasis or rescue mutations, or more generally, with non-additive mutational effects and compensatory mutations. To achieve this study, we developed the first algorithm, referred to as Amino Acid Rank (AAR), which follows the structural changes associated with mutations from the site of the mutation to the entire protein structure and quantifies the changes so that mutations can be ranked accordingly. Assessing the paths of changes opens the possibility of assuming secondary mutations for compensatory mechanisms.