Intermolecular β-Strand Networks Avoid Hub Residues and Favor Low Interconnectedness: A Potential Protection Mechanism against Chain Dissociation upon Mutation

Abstract

Altogether few protein oligomers undergo a conformational transition to a state that impairs their function and leads to diseases. But when it happens, the consequences are not harmless and the so-called conformational diseases pose serious public health problems. Notorious examples are the Alzheimer's disease and some cancers associated with a conformational change of the amyloid precursor protein (APP) and of the p53 tumor suppressor, respectively. The transition is linked with the propensity of β-strands to aggregate into amyloid fibers. Nevertheless, a huge number of protein oligomers associate chains via β-strand interactions (intermolecular β-strand interface) without ever evolving into fibers. We analyzed the layout of 1048 intermolecular β-strand interfaces looking for features that could provide the β-strands resistance to conformational transitions. The interfaces were reconstructed as networks with the residues as the nodes and the interactions between residues as the links. The networks followed an exponential decay degree distribution, implying an absence of hubs and nodes with few links. Such layout provides robustness to changes. Few links per nodes do not restrict the choices of amino acids capable of making an interface and maintain high sequence plasticity. Few links reduce the “bonding” cost of making an interface. Finally, few links moderate the vulnerability to amino acid mutation because it entails limited communication between the nodes. This confines the effects of a mutation to few residues instead of propagating them to many residues via hubs. We propose that intermolecular β-strand interfaces are organized in networks that tolerate amino acid mutation to avoid chain dissociation, the first step towards fiber formation. This is tested by looking at the intermolecular β-strand network of the p53 tetramer.

From local to global changes in proteins: a network view

“…Moreover, the changes observed for the N239Y p53 mutant resemble a domino effect. We have observed a similar domino effect upon the single mutation G334V in the p53 tetramerization domain [19].…”

“…A degree ratio of 100 would imply an amino acid with a 10 Å radius. Thus amino acid hubs must have a degree moderately higher than the average network degree, as reported [19,21,33].…”

“…Graph signatures are also used to predict enzyme promiscuity [18]. Likewise, we reported changes of links and nodes in the entire p53 network upon a single mutation [19]. Here the links in the networks are chemical bonds, possibly monitored by different measures (distance, accessible surface area, etc.)…”

“…acid networks that report simultaneous measures of degree distributions, mean path length and clustering coefficients [33]. Second, amino acid networks have random, exponential or power law degree distribution [19,21,33,44]. In other networks, hubs have hundred or more times as many connections as non-hubs; in proteins however the difference in connectedness is much smaller.…”

“…In other networks, hubs have hundred or more times as many connections as non-hubs; in proteins however the difference in connectedness is much smaller. Out of twenty-two amino acids only R, W, Y, F and H are frequently observed with a degree above three or four, arguing against the existence of hubs in proteins, at least if we define them as nodes with a degree exceeding significantly the average degree [19,21]. Thus, there is no log scale differences in the degree of amino acids in contrast, for example to a web network, for example, 300,000 nodes and hubs ranging from degree 100 to 1000 [45].…”