2024/08/28 by Francesco Pesce, Anne Bremer, Giulio Tesei +4 · 1 voice · 57 citations
Biochemistry, Genetics and Molecular Biology · #Biological system #Biology #Biophysics #Computational biology #Computer science #Exploit #Genetics #Intrinsically disordered proteins #Materials science #Protein Structure and Dynamics #Protein design #Protein structure #RNA Research and Splicing #RNA and protein synthesis mechanisms #Range (aeronautics) #Sequence (biology) #Toolbox
paper · pdf · doi:10.1126/sciadv.adm9926
published in Science Advances 10(35), eadm9926 (American Association for the Advancement of Science)
openalex publication_date 2024/08/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Intrinsically disordered proteins (IDPs) perform a broad range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Computational design of IDPs with specific conformational properties has, however, been difficult because of their substantial dynamics and structural complexity. We describe a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs that differ in compaction, long-range contacts, and propensity to phase separate. We experimentally tested and validated our designs and analyzed the sequence features that determine conformations. We show how our results are captured by a machine learning model, enabling us to speed up the algorithm. Our work expands the toolbox for computational protein design and will facilitate the design of proteins whose functions exploit the many properties afforded by protein disorder.