@article {352,
	title = {Intensification: A Resource for Amplifying Population-Genetic Signals with Protein Repeats.},
	journal = {J Mol Biol},
	volume = {429},
	year = {2017},
	month = {2017 02 03},
	pages = {435-445},
	abstract = {<p>Large-scale genome sequencing holds great promise for the interpretation of protein structures through the discovery of many, rare functional variants in the human population. However, because protein-coding regions are under high selective constraints, these variants occur at low frequencies, such that there is often insufficient statistics for downstream calculations. To address this problem, we develop the Intensification approach, which uses the modular structure of repeat protein domains to amplify signals of selection from population genetics and traditional interspecies conservation. In particular, we are able to aggregate variants at the codon level to identify important positions in repeat domains that show strong conservation signals. This allows us to compare conservation over different evolutionary timescales. It also enables us to visualize population-genetic measures on protein structures. We make available the Intensification results as an online resource (http://intensification.gersteinlab.org) and illustrate the approach through a case study on the tetratricopeptide repeat.</p>},
	keywords = {Amino Acid Sequence, Chromosome Mapping, Codon, Computational Biology, Databases, Genetic, Evolution, Molecular, Genetics, Population, Humans, Internet, Molecular Structure, Protein Conformation, Proteins, Signal Processing, Computer-Assisted, X-Rays},
	issn = {1089-8638},
	doi = {10.1016/j.jmb.2016.12.003},
	author = {Chen, Jieming and Wang, Bo and Regan, Lynne and Gerstein, Mark}
}
@article {535,
	title = {Localized structural frustration for evaluating the impact of sequence variants.},
	journal = {Nucleic Acids Res},
	volume = {44},
	year = {2016},
	month = {2016 12 01},
	pages = {10062-10073},
	abstract = {<p>Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype-genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.</p>},
	keywords = {Computational Biology, Databases, Protein, Evolution, Molecular, Genes, Tumor Suppressor, Genetic Variation, Humans, Neoplasms, Oncogenes, Polymorphism, Single Nucleotide, Proteins, Workflow},
	issn = {1362-4962},
	doi = {10.1093/nar/gkw927},
	author = {Kumar, Sushant and Clarke, Declan and Gerstein, Mark}
}
