Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

Abstract

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed.

Biophysics of protein evolution and evolutionary protein biophysics

“…For the G A /G B system, a mutationinduced gradual stabilization of one structure over another was demonstrated using a common software for DDG prediction ( §2.1) [178]. However, the mutation-induced G A /G B conformational switching was not reproduced in atomistic molecular dynamics simulations [67], even though a part of the simulated energetics is consistent with experiment [68].…”

“…However, it can also be argued that evolution of certain IDPs/IDRs may be subject to even more restrictive constraints because of their requirement to bind to multiple partners. As a result, these IDP/IDRs may suffer from low mutational robustness similar to that of bi-stable globular proteins that play the role of an evolutionary bridge between two folded structures [178,239]. Nevertheless, even in such cases, IDPs/IDRs in a neutral net might only need to conserve certain functional residues that are compatible with multiple binding partners while imposing few constraints on mutations at amino acid sites in the rest of the protein.…”

“…The latter observation may bear on the question of whether the currently known set of globular protein folds is nearly complete in its coverage of all physically possible compact folds, as discussed in §3.1 [286][287][288][289][290], but one has to also keep in mind that the HP model interaction potential is less heterogeneous, and thus entails fewer encodable structures, than model potentials that contain repulsive interactions or otherwise more heterogeneous interactions [158,322,323]. Fourth, the 2D HP lattice model provides sequences that act like evolutionary bridges [161, 178,204,239,299] (see §3.5), encode for autonomous folding units [292,316,324], and exhibit homology-like behaviours [295], all similar to properties observed in real proteins. Two likely physical reasons underlie the similarity between the sequence -structure mapping of the 2D HP model and that of real globular proteins.…”

A polymetamorphic protein

“…55 In general, however, it may be more common for bridge sequences to have lower native state stability than sequences with a single native structure. 23 …”

“…14 Limited mutagenesis of small natural proteins populates alternate folds in certain cases, [15][16][17] and accumulation of simple mutations can lead to evolution of new folds. [17][18][19] Some modeling studies have found numerous close approaches or paths between different structures in sequence space [20][21][22][23] and even sequence ''supernetworks'' 24,25 that span many protein folds. In addition, sequences with two folds or functions may confer a fitness advantage under certain models of adaptive evolution.…”