ArticleMolecular biology and evolution2023
DegronMD: Leveraging Evolutionary and Structural Features for Deciphering Protein-Targeted Degradation, Mutations, and Drug Response to Degrons.
Article in Molecular biology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Oncodrive3D: fast and accurate detection of structural clusters of somatic mutations under positive selection.Nucleic acids research · 2025Article
- Tissue-specific consequences of tag fusions on protein expression in transgenic mice.PLoS genetics · 2025Article
- Reciprocal and non-reciprocal effects of clinically relevant SETBP1 protein dosage changes.Human molecular genetics · 2025Article
- Systematic Analysis of E3 Ligase-Related Genes Identified UBE2L3 as a Prognostic Biomarker Associated With Drug Resistance in Acute Myeloid Leukemia.International journal of general medicine · 2025Article
- MetaDegron: multimodal feature-integrated protein language model for predicting E3 ligase targeted degrons.Briefings in bioinformatics · 2024Article
- DEGRONOPEDIA: a web server for proteome-wide inspection of degrons.Nucleic acids research · 2024Article
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
Protein-targeted degradation is an emerging and promising therapeutic approach. The specificity of degradation and the maintenance of cellular homeostasis are determined by the interactions between E3 ubiquitin ligase and degradation signals, known as degrons. The human genome encodes over 600 E3 ligases; however, only a small number of targeted degron instances have been identified so far. In this study, we introduced DegronMD, an open knowledgebase designed for the investigation of degrons, their associated dysfunctional events, and drug responses. We revealed that degrons are evolutionarily conserved and tend to occur near the sites of protein translational modifications, particularly in the regions of disordered structure and higher solvent accessibility. Through pattern recognition and machine learning techniques, we constructed the degrome landscape across the human proteome, yielding over 18,000 new degrons for targeted protein degradation. Furthermore, dysfunction of degrons disrupts the degradation process and leads to the abnormal accumulation of proteins; this process is associated with various types of human cancers. Based on the estimated phenotypic changes induced by somatic mutations, we systematically quantified and assessed the impact of mutations on degron function in pan-cancers; these results helped to build a global mutational map on human degrome, including 89,318 actionable mutations that may induce the dysfunction of degrons and disrupt protein degradation pathways. Multiomics integrative analysis unveiled over 400 drug resistance events associated with the mutations in functional degrons. DegronMD, accessible at https://bioinfo.uth.edu/degronmd, is a useful resource to explore the biological mechanisms, infer protein degradation, and assist with drug discovery and design on degrons.
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