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See detailInsights into protein structural, physicochemical, and functional consequences of missense variants in 1,330 disease-associated human genes 693259
Iqbal, Sumaiya; Jespersen, Jakob B.; Perez-Palma, Eduardo et al

E-print/Working paper (2019)

Inference of the structural and functional consequences of amino acid-altering missense variants is challenging and not yet scalable. Clinical and research applications of the colossal number of ... [more ▼]

Inference of the structural and functional consequences of amino acid-altering missense variants is challenging and not yet scalable. Clinical and research applications of the colossal number of identified missense variants is thus limited. Here we describe the aggregation and analysis of large-scale genomic variation and structural biology data for 1,330 disease-associated genes. Comparing the burden of 40 structural, physicochemical, and functional protein features of altered amino acids with 3-dimensional coordinates, we found 18 and 14 features that are associated with pathogenic and population missense variants, respectively. Separate analyses of variants from 24 protein functional classes revealed novel function-dependent vulnerable features. We then devised a quantitative spectrum, identifying variants with higher pathogenic variant-associated features. Finally, we developed a web resource (MISCAST; http://miscast.broadinstitute.org/) for interactive analysis of variants on linear and tertiary protein structures. The biological impact of missense variants available through the webtool will assist researchers in hypothesizing variant pathogenicity and disease trajectories. [less ▲]

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See detailMolArt: a molecular structure annotation and visualization tool
Hoksza, David UL; Gawron, Piotr UL; Ostaszewski, Marek UL et al

in Bioinformatics (2018)

Summary MolArt fills the gap between sequence and structure visualization by providing a light-weight, interactive environment enabling exploration of sequence annotations in the context of available ... [more ▼]

Summary MolArt fills the gap between sequence and structure visualization by providing a light-weight, interactive environment enabling exploration of sequence annotations in the context of available experimental or predicted protein structures. Provided a UniProt ID, MolArt downloads and displays sequence annotations, sequence-structure mapping and relevant structures. The sequence and structure views are interlinked, enabling sequence annotations being color overlaid over the mapped structures, thus providing an enhanced understanding and interpretation of the available molecular data. Availability and implementation MolArt is released under the Apache 2 license and is available at https://github.com/davidhoksza/MolArt. The project web page https://davidhoksza.github.io/MolArt/ features examples and applications of the tool. [less ▲]

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