Abstract
Amino acid substitutions in protein structures often require subtle backbone adjustments that are difficult to model in atomic detail. An improved ability to predict realistic backbone changes in response to engineered mutations would be of great utility for the blossoming field of rational protein design. One model that has recently grown in acceptance is the backrub motion, a low-energy dipeptide rotation with single-peptide counter-rotations, that is coupled to dynamic two-state sidechain rotamer jumps, as evidenced by alternate conformations in very high-resolution crystal structures. It has been speculated that backrubs may facilitate sequence changes equally well as rotamer changes. However, backrub-induced shifts and experimental uncertainty are of similar magnitude for backbone atoms in even high-resolution structures, so comparison of wildtype-vs.-mutant crystal structure pairs is not sufficient to directly link backrubs to mutations. In this study, we use two alternative approaches that bypass this limitation. First, we use a quality-filtered structure database to aggregate many examples for precisely defined motifs with single amino acid differences, and find that the effectively amplified backbone differences closely resemble backrubs. Second, we directly apply a provably-accurate, backrub-enabled protein design algorithm to idealized versions of these motifs, and discover that the lowest-energy computed models match the average-coordinate experimental structures. These results support the hypothesis that backrubs participate in natural protein evolution and validate their continued use for design of synthetic proteins.
Highlights
Proteins routinely incorporate amino acid changes over evolutionary time by adapting their conformation to the new sidechain
It remains a difficult task to predict such a conformational response, especially when subtle backbone adjustments are involved. This issue is of central importance to the burgeoning field of computational protein design, which has recently enjoyed a string of exciting developments [1,2,3,4]
Anticorrelated ‘‘crankshaft’’ adjustments of the y(i21) and Q(i) torsions [5] are evident from order parameters derived from molecular dynamics (MD) simulations, but unrealistically distort the ends of the peptide if employed in isolation
Summary
Proteins routinely incorporate amino acid changes over evolutionary time by adapting their conformation to the new sidechain. Peptide fragments [8] implicitly reflect local protein energetics because they are extracted from experimental structures, but can be computationally inefficient because most random fragment insertion attempts are incompatible with a given local structural context and will be rejected. This being the case, it may be prudent to let nature inform our notion of backbone motion by using a move set based on empirical observations, which may encode aspects of protein energetics and sidechain/backbone coupling that are difficult to handle explicitly
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