Abstract
The rapidly increasing amount of data on human genetic variation has resulted in a growing demand to identify pathogenic mutations computationally, as their experimental validation is currently beyond reach. Here we show that alpha helices and beta strands differ significantly in their ability to tolerate mutations: helices can accumulate more mutations than strands without change, due to the higher numbers of inter-residue contacts in helices. This results in two patterns: a) the same number of mutations causes less structural change in helices than in strands; b) helices diverge more rapidly in sequence than strands within the same domains. Additionally, both helices and strands are significantly more robust than coils. Based on this observation we show that human missense mutations that change secondary structure are more likely to be pathogenic than those that do not. Moreover, inclusion of predicted secondary structure changes shows significant utility for improving upon state-of-the-art pathogenicity predictions.
Highlights
In recent years, genome sequencing studies have uncovered an enormous amount of human genetic variation, both in coding and noncoding regions of the human genome
Our results indicate that alpha helices can accumulate significantly more mutations than beta strands without change in the structure (Fig 2), and both helices and strands change slower than coils (S3 Fig)
As residues close to the surface accumulate mutations and change faster than the core [19,20], we calculated secondary structure similarity for residues with different relative solvent accessibility (RSA), using the pairwise structural alignments where sequence similarity falls between 10–20% (Fig 2, panels D-F), as this bin contains the highest number of pairwise alignments
Summary
The factors that determine the robustness and evolvability of proteins are still largely unknown. In this work the authors show that different secondary structure elements of proteins (helices and strands) differ in their ability to tolerate mutations, and demonstrate that it is caused by differences in the number of non-covalent residue interactions within these secondary structure units. The results suggest that engineering de novo all-alpha proteins should be easier than all-beta ones, as more sequences can to fold to the same topology. Secondary structure can be used to improve current methods of pathogenicity predictions; mutations that change secondary structure are more likely to be pathogenic than mutations that do not, due to their strong destabilizing effect on protein structure. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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