ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins

Abstract

Interpretation of genetic variation is required for understanding genotype-phenotype associations, mechanisms of inherited disease, and drivers of cancer. Millions of single nucleotide variants (SNVs) in human genomes are known and thousands are associated with disease. An estimated 20% of diseaseassociated missense SNVs are located in protein sites of post-translational modifications (PTMs), chemical modifications of amino acids that extend protein function. ActiveDriverDB is a comprehensive human proteo-genomics database that annotates disease mutations and population variants using PTMs. We integrated >385,000 published PTM sites with ~3.8 million missense SNVs from The Cancer Genome Atlas (TCGA), the ClinVar database of disease genes, and inter-individual variation from human genome sequencing projects. The database includes interaction networks of proteins, upstream enzymes such as kinases, and drugs targeting these enzymes. We also predicted network-rewiring impact of mutations by analyzing gains and losses of kinase-bound sequence motifs.ActiveDriverDB provides detailed visualization, filtering, browsing and searching options for studying PTM-associated SNVs. Users can upload mutation datasets interactively and use our application programming interface for pipelines. Integrative analysis of SNVs and PTMs helps decipher molecular mechanisms of phenotypes and disease, as exemplified by case studies of disease genes TP53, BRCA2and VHL. The open-source database is available at https://www.ActiveDriverDB.org.

Systems-level differential gene expression analysis reveals new genetic variants of oral cancer

“…Deciphering inter-individual genetic variation is the latest trend in personal genomic era investigations. The interpretation of genomic to proteomic information may integrate the impact of mutations on cellular system-level investigations in the future with a higher magnitude 19 . Human proteomic data analysis uses PTMs to interpret disease mutations and inter-individual genetic variations.…”

“…Human proteomic data analysis uses PTMs to interpret disease mutations and inter-individual genetic variations. PTMs being important regulators of protein function and signaling pathways facilitate the missense mutational analysis investigations 19 .…”

“…Approximately 21% of amino acid substitutions are known to be associated with disease-progression in correspondence with missense single nucleotide variants located at PTM protein sites (post-translation modifications). The chemical modification of the amino acid thus basically extends the functionality of the associated protein 19 .…”

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact

“…We then filtrated the blast results and stored these results in PRISMOID. Aside, it has been reported there are 21% disease-related amino acid substitutions associated with missense single nucleotide variants (SNVs) are located in PTM sites [41]. Accordingly, we additionally extracted and collected PTM-associated disease and population mutations from ActiveDriverDB [41] database, so as to facilitate the investigation of structural properties of PTMs and to encourage construction of bioinformatics tools with structural features.…”

“…Aside, it has been reported there are 21% disease-related amino acid substitutions associated with missense single nucleotide variants (SNVs) are located in PTM sites [41]. Accordingly, we additionally extracted and collected PTM-associated disease and population mutations from ActiveDriverDB [41] database, so as to facilitate the investigation of structural properties of PTMs and to encourage construction of bioinformatics tools with structural features. To this effect, we also calculated secondary structure based features and residue accessibility features of PTM sites using DSSP [42] and NACCESS [43] software, respectively.…”