Literature DB >> 27915290

Localized structural frustration for evaluating the impact of sequence variants.

Sushant Kumar1,2, Declan Clarke1,2,3, Mark Gerstein4,2,5.   

Abstract

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.
© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Year:  2016        PMID: 27915290      PMCID: PMC5137452          DOI: 10.1093/nar/gkw927

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  58 in total

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Authors:  Zhe Zhang; Lin Wang; Yang Gao; Jie Zhang; Maxim Zhenirovskyy; Emil Alexov
Journal:  Bioinformatics       Date:  2012-01-11       Impact factor: 6.937

3.  The energy landscapes and motions of proteins.

Authors:  H Frauenfelder; S G Sligar; P G Wolynes
Journal:  Science       Date:  1991-12-13       Impact factor: 47.728

4.  Evolution and functional impact of rare coding variation from deep sequencing of human exomes.

Authors:  Jacob A Tennessen; Abigail W Bigham; Timothy D O'Connor; Wenqing Fu; Eimear E Kenny; Simon Gravel; Sean McGee; Ron Do; Xiaoming Liu; Goo Jun; Hyun Min Kang; Daniel Jordan; Suzanne M Leal; Stacey Gabriel; Mark J Rieder; Goncalo Abecasis; David Altshuler; Deborah A Nickerson; Eric Boerwinkle; Shamil Sunyaev; Carlos D Bustamante; Michael J Bamshad; Joshua M Akey
Journal:  Science       Date:  2012-05-17       Impact factor: 47.728

5.  Protein frustratometer: a tool to localize energetic frustration in protein molecules.

Authors:  Michael Jenik; R Gonzalo Parra; Leandro G Radusky; Adrian Turjanski; Peter G Wolynes; Diego U Ferreiro
Journal:  Nucleic Acids Res       Date:  2012-05-29       Impact factor: 16.971

6.  COSMIC: exploring the world's knowledge of somatic mutations in human cancer.

Authors:  Simon A Forbes; David Beare; Prasad Gunasekaran; Kenric Leung; Nidhi Bindal; Harry Boutselakis; Minjie Ding; Sally Bamford; Charlotte Cole; Sari Ward; Chai Yin Kok; Mingming Jia; Tisham De; Jon W Teague; Michael R Stratton; Ultan McDermott; Peter J Campbell
Journal:  Nucleic Acids Res       Date:  2014-10-29       Impact factor: 16.971

7.  A global reference for human genetic variation.

Authors:  Adam Auton; Lisa D Brooks; Richard M Durbin; Erik P Garrison; Hyun Min Kang; Jan O Korbel; Jonathan L Marchini; Shane McCarthy; Gil A McVean; Gonçalo R Abecasis
Journal:  Nature       Date:  2015-10-01       Impact factor: 49.962

8.  An integrated map of genetic variation from 1,092 human genomes.

Authors:  Goncalo R Abecasis; Adam Auton; Lisa D Brooks; Mark A DePristo; Richard M Durbin; Robert E Handsaker; Hyun Min Kang; Gabor T Marth; Gil A McVean
Journal:  Nature       Date:  2012-11-01       Impact factor: 49.962

9.  ClinVar: public archive of relationships among sequence variation and human phenotype.

Authors:  Melissa J Landrum; Jennifer M Lee; George R Riley; Wonhee Jang; Wendy S Rubinstein; Deanna M Church; Donna R Maglott
Journal:  Nucleic Acids Res       Date:  2013-11-14       Impact factor: 16.971

10.  The real cost of sequencing: scaling computation to keep pace with data generation.

Authors:  Paul Muir; Shantao Li; Shaoke Lou; Daifeng Wang; Daniel J Spakowicz; Leonidas Salichos; Jing Zhang; George M Weinstock; Farren Isaacs; Joel Rozowsky; Mark Gerstein
Journal:  Genome Biol       Date:  2016-03-23       Impact factor: 13.583

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  6 in total

Review 1.  Frustration, function and folding.

Authors:  Diego U Ferreiro; Elizabeth A Komives; Peter G Wolynes
Journal:  Curr Opin Struct Biol       Date:  2017-11-05       Impact factor: 6.809

Review 2.  Insights into genetics, human biology and disease gleaned from family based genomic studies.

Authors:  Jennifer E Posey; Anne H O'Donnell-Luria; Jessica X Chong; Tamar Harel; Shalini N Jhangiani; Zeynep H Coban Akdemir; Steven Buyske; Davut Pehlivan; Claudia M B Carvalho; Samantha Baxter; Nara Sobreira; Pengfei Liu; Nan Wu; Jill A Rosenfeld; Sushant Kumar; Dimitri Avramopoulos; Janson J White; Kimberly F Doheny; P Dane Witmer; Corinne Boehm; V Reid Sutton; Donna M Muzny; Eric Boerwinkle; Murat Günel; Deborah A Nickerson; Shrikant Mane; Daniel G MacArthur; Richard A Gibbs; Ada Hamosh; Richard P Lifton; Tara C Matise; Heidi L Rehm; Mark Gerstein; Michael J Bamshad; David Valle; James R Lupski
Journal:  Genet Med       Date:  2019-01-18       Impact factor: 8.822

3.  Leveraging protein dynamics to identify cancer mutational hotspots using 3D structures.

Authors:  Sushant Kumar; Declan Clarke; Mark B Gerstein
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-28       Impact factor: 11.205

4.  SVFX: a machine learning framework to quantify the pathogenicity of structural variants.

Authors:  Sushant Kumar; Arif Harmanci; Jagath Vytheeswaran; Mark B Gerstein
Journal:  Genome Biol       Date:  2020-11-09       Impact factor: 13.583

5.  Structural bioinformatics enhances mechanistic interpretation of genomic variation, demonstrated through the analyses of 935 distinct RAS family mutations.

Authors:  Swarnendu Tripathi; Nikita R Dsouza; Raul Urrutia; Michael T Zimmermann
Journal:  Bioinformatics       Date:  2021-06-16       Impact factor: 6.937

6.  "Infostery" analysis of short molecular dynamics simulations identifies highly sensitive residues and predicts deleterious mutations.

Authors:  Yasaman Karami; Tristan Bitard-Feildel; Elodie Laine; Alessandra Carbone
Journal:  Sci Rep       Date:  2018-10-31       Impact factor: 4.379

  6 in total

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