title: wKinMut-2: Identification and Interpretation of Pathogenic Variants in Human Protein Kinases.
abstract: Most genomic alterations are tolerated while only a minor fraction disrupts molecular function sufficiently to drive disease. Protein kinases play a central biological function and the functional consequences of their variants are abundantly characterized. However, this heterogeneous information is often scattered across different sources, which makes the integrative analysis complex and laborious. wKinMut-2 constitutes a solution to facilitate the interpretation of the consequences of human protein kinase variation. Nine methods predict their pathogenicity, including a kinase-specific random forest approach. To understand the biological mechanisms causative of human diseases and cancer, information from pertinent reference knowledge bases and the literature is automatically mined, digested, and homogenized. Variants are visualized in their structural contexts and residues affecting catalytic and drug binding are identified. Known protein-protein interactions are reported. Altogether, this information is intended to assist the generation of new working hypothesis to be corroborated with ulterior experimental work. The wKinMut-2 system, along with a user manual and examples, is freely accessible at http://kinmut2.bioinfo.cnio.es, the code for local installations can be downloaded from https://github.com/Rbbt-Workflows/KinMut2.
authors.affiliation: Structural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, 28029, Spain.
authors.forename: Miguel
authors.initials: M
authors.lastname: Vazquez
authors.affiliation: Structural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, 28029, Spain.
authors.forename: Tirso
authors.initials: T
authors.lastname: Pons
authors.affiliation: Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen 2200, Denmark.|Center for Biological Sequence Analysis (CBS), Systems Biology Department, Technical University of Denmark (DTU), Kongens Lyngby 2800, Denmark.
authors.forename: Søren
authors.initials: S
authors.lastname: Brunak
authors.affiliation: Structural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, 28029, Spain.
authors.forename: Alfonso
authors.initials: A
authors.lastname: Valencia
authors.affiliation: Center for Biological Sequence Analysis (CBS), Systems Biology Department, Technical University of Denmark (DTU), Kongens Lyngby 2800, Denmark.
authors.forename: Jose M G
authors.initials: JM
authors.lastname: Izarzugaza
mesh_terms: D019295:Computational Biology / Q000379:methods*; D057225:Data Mining; D030541:Databases, Genetic; D016220:Fibroblast Growth Factor 1 / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D056726:Genetic Association Studies / Q000379:methods*; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D023281:Genomics / Q000379:methods*; D006801:Humans; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D011494:Protein Kinases / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D048493:Proto-Oncogene Proteins B-raf / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D051498:Receptor, Fibroblast Growth Factor, Type 3 / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D012984:Software; D013329:Structure-Activity Relationship; D064878:Web Browser
chemical_list: D016220:Fibroblast Growth Factor 1; D011494:Protein Kinases; D051498:Receptor, Fibroblast Growth Factor, Type 3; D048493:Proto-Oncogene Proteins B-raf
keywords: functional impact; pathogenicity prediction; protein kinase; variant annotation; variants