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News from the Protein Mutability Landscape
Authors:Maximilian Hecht  Yana Bromberg  Burkhard Rost
Affiliation:1 Department of Bioinformatics and Computational Biology I12, Technische Universität München, Boltzmannstrasse 3, 85748 Garching, Germany;2 Department of Biochemistry and Microbiology, Rutgers University, 76 Lipman Drive, New Brunswick, NJ 08901, USA;3 Institute of Advanced Study, Technische Universität München, Boltzmannstrasse 3, 85748 Garching, Germany;4 Institute for Food and Plant Sciences, Life Science Center Weihenstephan, Alte Akademie 8, 85354 Freising, Germany
Abstract: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.
Keywords:3D, three-dimensional   hMC4R, human melanocortin 4 receptor   GPCR, G-protein-coupled receptor   nsSNP, non-synonymous SNP   PDB, Protein Data Bank   SAAS, single-amino-acid substitution   SIFT, sorting intolerant from tolerant   SNAP, screening for non-acceptable polymorphisms   SNP, single nucleotide polymorphism
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