Sequence, Structure and Functional space ofDrosophila de novoproteins

Abstract

During de novo emergence, new protein coding genes emerge from previously non-genic sequences. The de novo proteins they encode are dissimilar in composition and predicted biochemical properties to conserved proteins. However, many functional de novo proteins indeed exist. Both identification of functional de novo proteins and their structural characterisation are experimentally laborious. To identify functional and structured de novo proteins in silico, we applied recently developed machine learning based tools and refined the results for de novo proteins. We found that most de novo proteins are indeed different from conserved proteins both in their structure and sequence. However, some de novo proteins are predicted to adopt known protein folds, participate in cellular reactions, and to form biomolecular condensates. Apart from broadening our understanding of de novo protein evolution, our study also provides a large set of testable hypotheses for focused experimental studies on structure and function of de novo proteins in Drosophila.

The Rapid Evolution of De Novo Proteins in Structure and Complex

“…MD (molecular dynamics) simulation studies have revealed that most de novo proteins are flexible in structure and a minority of them adopt well-known protein structures ( Middendorf and Eicholt 2024 ; Peng and Zhao 2024 ). Despite the tendency of de novo proteins to be disordered with few (or no) orthologs, AlphaFold2's predictions reveal that they generally achieve higher-confidence scores per residue (predicted local distance difference test [pLDDT]) than random sequences ( Middendorf et al 2024 ). The AlphaFold2 performs the MD refinement (called “relax” in AlphaFold2 terminology) using OpenMM ( Jumper et al 2021 ).…”