TY - JOUR
T1 - News from the protein mutability landscape
AU - Hecht, Maximilian
AU - Bromberg, Yana
AU - Rost, Burkhard
N1 - Funding Information:
Thanks to Tim Karl, Guy Yachdav and Laszlo Kajan (Technische Universität München) for invaluable help with hardware and software; to Marlena Drabik (Technische Universität München) for administrative support; and to Thomas Hopf and Laszlo Kajan (both Technische Universität München) for helpful discussions and help with the manuscript. Thanks to the developers of PyMOL [98] ( Fig. 1 d and e) and Matrix2png [99] ( Fig. 1 b and c) for providing great tools. This work was supported by a grant from the Alexander von Humboldt Foundation through the German Ministry for Research and Education (Bundesministerium fuer Bildung und Forschung). Last, not the least, thanks to all those who deposit their experimental data in public databases and to those who maintain these databases.
PY - 2013/11/1
Y1 - 2013/11/1
N2 - Some mutations of protein residues matter more than others, and these are often conserved evolutionarily. The explosion of deep sequencing and genotyping increasingly requires the distinction between effect and neutral variants. The simplest approach predicts all mutations of conserved residues to have an effect; however, this works poorly, at best. Many computational tools that are optimized to predict the impact of point mutations provide more detail. Here, we expand the perspective from the view of single variants to the level of sketching the entire mutability landscape. This landscape is defined by the impact of substituting every residue at each position in a protein by each of the 19 non-native amino acids. We review some of the powerful conclusions about protein function, stability and their robustness to mutation that can be drawn from such an analysis. Large-scale experimental and computational mutagenesis experiments are increasingly furthering our understanding of protein function and of the genotype-phenotype associations. We also discuss how these can be used to improve predictions of protein function and pathogenicity of missense variants.
AB - Some mutations of protein residues matter more than others, and these are often conserved evolutionarily. The explosion of deep sequencing and genotyping increasingly requires the distinction between effect and neutral variants. The simplest approach predicts all mutations of conserved residues to have an effect; however, this works poorly, at best. Many computational tools that are optimized to predict the impact of point mutations provide more detail. Here, we expand the perspective from the view of single variants to the level of sketching the entire mutability landscape. This landscape is defined by the impact of substituting every residue at each position in a protein by each of the 19 non-native amino acids. We review some of the powerful conclusions about protein function, stability and their robustness to mutation that can be drawn from such an analysis. Large-scale experimental and computational mutagenesis experiments are increasingly furthering our understanding of protein function and of the genotype-phenotype associations. We also discuss how these can be used to improve predictions of protein function and pathogenicity of missense variants.
KW - SNP effects
KW - alanine scanning
KW - complete single mutagenesis
KW - exome-wide mutagenesis
KW - in silico mutagenesis
UR - http://www.scopus.com/inward/record.url?scp=85047688149&partnerID=8YFLogxK
U2 - 10.1016/j.jmb.2013.07.028
DO - 10.1016/j.jmb.2013.07.028
M3 - Review article
C2 - 23896297
AN - SCOPUS:85047688149
SN - 0022-2836
VL - 425
SP - 3937
EP - 3948
JO - Journal of Molecular Biology
JF - Journal of Molecular Biology
IS - 21
ER -