Sequence, Structure, and Functional Space of Drosophila De Novo Proteins

Middendorf, Lasse; Iyengar Ravi, Bharat; Eicholt, Lars A.

Research article (journal) | Peer reviewed

Abstract

De novo proteins emerge from formerly noncoding regions of genomic DNA. While a few de novo proteins have been shown to perform essential functions in different organisms, it is experimentally laborious to discover the structure and the function of de novo proteins, especially at a large scale. To help address this problem, we used machine learning based computational tools to predict the structure and the function of ∼1,500 Drosophila de novo proteins, thereby providing a dataset for a focused experimental validation.

Details about the publication

JournalGenome Biology and Evolution
Volume16
Issue8
Article numberevae176
StatusPublished
Release year2024 (30/08/2024)
Language in which the publication is writtenEnglish
DOI10.1093/gbe/evae176
Link to the full texthttps://academic.oup.com/gbe/article/16/8/evae176/7745839?searchresult=1
Keywordsde novo proteins, protein function, structural comparison, protein structure, structure predictions, sequence space

Authors from the University of Münster

Eicholt, Lars Albert
Research Group Evolutionary Bioinformatics
Ravi, Bharat
Research Group Evolutionary Bioinformatics