Literature DB >> 31228295

Gene-specific features enhance interpretation of mutational impact on acid α-glucosidase enzyme activity.

Aashish N Adhikari1.   

Abstract

We present a computational model for predicting mutational impact on enzymatic activity of human acid α-glucosidase (GAA), an enzyme associated with Pompe disease. Using a model that combines features specific to GAA with other general evolutionary and physiochemical features, we made blind predictions of enzymatic activity relative to wildtype human GAA for >300 GAA mutants, as part of the Critical Assessment of Genome Interpretation 5 GAA challenge. We found that gene-specific features can improve the performance of existing impact prediction tools that mostly rely on general features for pathogenicity prediction. Majority of the poorly predicted mutants that lower wildtype GAA enzyme activity occurred on the surface of the GAA protein. We also found that gene-specific features were uncorrelated with existing methods and provided orthogonal information for interpreting the origin of pathogenicity, particular in variants that are poorly predicted by existing general methods. Specific variants in GAA, when investigated in the context of its protein structure, suggested gene-specific information like the disruption of local backbone torsional geometry and disruption of particular sidechain-sidechain hydrogen bonds as some potential sources for pathogenicity.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  Pompe disease; acid α-glucosidase; enzyme activity prediction; gene-specific variant effect prediction; variant interpretation

Mesh:

Substances:

Year:  2019        PMID: 31228295      PMCID: PMC7329270          DOI: 10.1002/humu.23846

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  35 in total

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Review 4.  Objective assessment of the evolutionary action equation for the fitness effect of missense mutations across CAGI-blinded contests.

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Authors:  Gene Yeo; Christopher B Burge
Journal:  J Comput Biol       Date:  2004       Impact factor: 1.479

6.  The angiotensin-converting enzyme insertion/deletion polymorphism modifies the clinical outcome in patients with Pompe disease.

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Journal:  Genet Med       Date:  2010-04       Impact factor: 8.822

7.  ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures.

Authors:  Meytal Landau; Itay Mayrose; Yossi Rosenberg; Fabian Glaser; Eric Martz; Tal Pupko; Nir Ben-Tal
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8.  The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity.

Authors:  Dominik G Grimm; Chloé-Agathe Azencott; Fabian Aicheler; Udo Gieraths; Daniel G MacArthur; Kaitlin E Samocha; David N Cooper; Peter D Stenson; Mark J Daly; Jordan W Smoller; Laramie E Duncan; Karsten M Borgwardt
Journal:  Hum Mutat       Date:  2015-03-26       Impact factor: 4.878

9.  ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules.

Authors:  Haim Ashkenazy; Shiran Abadi; Eric Martz; Ofer Chay; Itay Mayrose; Tal Pupko; Nir Ben-Tal
Journal:  Nucleic Acids Res       Date:  2016-05-10       Impact factor: 16.971

10.  Analysis of protein-coding genetic variation in 60,706 humans.

Authors:  Monkol Lek; Konrad J Karczewski; Eric V Minikel; Kaitlin E Samocha; Eric Banks; Timothy Fennell; Anne H O'Donnell-Luria; James S Ware; Andrew J Hill; Beryl B Cummings; Taru Tukiainen; Daniel P Birnbaum; Jack A Kosmicki; Laramie E Duncan; Karol Estrada; Fengmei Zhao; James Zou; Emma Pierce-Hoffman; Joanne Berghout; David N Cooper; Nicole Deflaux; Mark DePristo; Ron Do; Jason Flannick; Menachem Fromer; Laura Gauthier; Jackie Goldstein; Namrata Gupta; Daniel Howrigan; Adam Kiezun; Mitja I Kurki; Ami Levy Moonshine; Pradeep Natarajan; Lorena Orozco; Gina M Peloso; Ryan Poplin; Manuel A Rivas; Valentin Ruano-Rubio; Samuel A Rose; Douglas M Ruderfer; Khalid Shakir; Peter D Stenson; Christine Stevens; Brett P Thomas; Grace Tiao; Maria T Tusie-Luna; Ben Weisburd; Hong-Hee Won; Dongmei Yu; David M Altshuler; Diego Ardissino; Michael Boehnke; John Danesh; Stacey Donnelly; Roberto Elosua; Jose C Florez; Stacey B Gabriel; Gad Getz; Stephen J Glatt; Christina M Hultman; Sekar Kathiresan; Markku Laakso; Steven McCarroll; Mark I McCarthy; Dermot McGovern; Ruth McPherson; Benjamin M Neale; Aarno Palotie; Shaun M Purcell; Danish Saleheen; Jeremiah M Scharf; Pamela Sklar; Patrick F Sullivan; Jaakko Tuomilehto; Ming T Tsuang; Hugh C Watkins; James G Wilson; Mark J Daly; Daniel G MacArthur
Journal:  Nature       Date:  2016-08-18       Impact factor: 49.962

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  2 in total

Review 1.  Opportunities and challenges for the computational interpretation of rare variation in clinically important genes.

Authors:  Gregory McInnes; Andrew G Sharo; Megan L Koleske; Julia E H Brown; Matthew Norstad; Aashish N Adhikari; Sheng Wang; Steven E Brenner; Jodi Halpern; Barbara A Koenig; David C Magnus; Renata C Gallagher; Kathleen M Giacomini; Russ B Altman
Journal:  Am J Hum Genet       Date:  2021-04-01       Impact factor: 11.025

Review 2.  Computational approaches for predicting variant impact: An overview from resources, principles to applications.

Authors:  Ye Liu; William S B Yeung; Philip C N Chiu; Dandan Cao
Journal:  Front Genet       Date:  2022-09-29       Impact factor: 4.772

  2 in total

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