ActiveDriverDB: Interpreting Genetic Variation in Human and Cancer Genomes Using Post-translational Modification Sites and Signaling Networks (2021 Update)

Abstract

Deciphering the functional impact of genetic variation is required to understand phenotypic diversity and the molecular mechanisms of inherited disease and cancer. While millions of genetic variants are now mapped in genome sequencing projects, distinguishing functional variants remains a major challenge. Protein-coding variation can be interpreted using post-translational modification (PTM) sites that are core components of cellular signaling networks controlling molecular processes and pathways. ActiveDriverDB is an interactive proteo-genomics database that uses more than 260,000 experimentally detected PTM sites to predict the functional impact of genetic variation in disease, cancer and the human population. Using machine learning tools, we prioritize proteins and pathways with enriched PTM-specific amino acid substitutions that potentially rewire signaling networks via induced or disrupted short linear motifs of kinase binding. We then map these effects to site-specific protein interaction networks and drug targets. In the 2021 update, we increased the PTM datasets by nearly 50%, included glycosylation, sumoylation and succinylation as new types of PTMs, and updated the workflows to interpret inherited disease mutations. We added a recent phosphoproteomics dataset reflecting the cellular response to SARS-CoV-2 to predict the impact of human genetic variation on COVID-19 infection and disease course. Overall, we estimate that 16-21% of known amino acid substitutions affect PTM sites among pathogenic disease mutations, somatic mutations in cancer genomes and germline variants in the human population. These data underline the potential of interpreting genetic variation through the lens of PTMs and signaling networks. The open-source database is freely available at www.ActiveDriverDB.org.

dbPTM in 2022: an updated database for exploring regulatory networks and functional associations of protein post-translational modifications

“…The dbPTM has integrated comprehensive PTM sites from public biological databases, including UniProtKB/Swiss-Prot ( 41 ), PhosphoSitePlus ( 42 ), ActiveDriverDB ( 43 ), etc. In addition, PTM-related articles were systematically retrieved by query of PTM-related keywords, such as phosphorylation, ubiquitination, or acetylation, in the fields ‘Title’ and ‘Abstract’ from PubMed.…”

Human phospho-signaling networks of SARS-CoV-2 infection are rewired by population genetic variants

“…Protein phosphosites significantly differentially phosphorylated in SARS-CoV-2 infection were retrieved from the phospho-proteomics study by Bouhaddou et al 9 . We mapped the phosphosites to canonical protein isoforms (hg19) using the ActiveDriverDB 44 database. SARS-CoV-2 associated phosphosites detected at the 24h timepoint were filtered for significance ( FDR < 0.05 in infected cells; FDR > 0.05 in controls).…”

“…We mapped the phosphosites to canonical protein isoforms (hg19) using the ActiveDriverDB 44 database. SARS-CoV-2 associated phosphosites detected at the 24h timepoint were filtered for significance (FDR < 0.05 in infected cells; FDR > 0.05 in controls).…”

“…We included 30 physical PPIs of the 77 top human proteins, and 139 PPIs of SARS-CoV-2 proteins interacting with the top human proteins collected in the BioGRID database 43 . We also included 29 high-confidence kinase-substrate interactions with specific SARS-CoV-2-associated phosphosites, using data from the ActiveDriverDB database 44 . Kinase-substrate interactions were limited to phosphosites with at least one pSNV.…”

Functional analysis of the stable phosphoproteome reveals cancer vulnerabilities

“…Recent advances in mass spectrometry-based technologies ( Choudhary and Mann, 2010 ) and the growing accumulation of phosphorylation-specific resources ( Gnad et al , 2007 ; Hornbeck et al , 2015 ; Krassowski et al , 2021 ) and databases ( Bodenmiller et al , 2008 ; Yu et al , 2019 ) offer a great opportunity to investigate the stable phosphoproteome. Previously, we identified a set of stably phosphorylated sites (SPSs) by using four mouse phosphoproteomics datasets and demonstrated the utility of the stable sites for data normalization and integration ( Kim et al , 2021 ).…”