TY - JOUR
T1 - Targeting plant UBX proteins: AI-enhanced lessons from distant cousins
AU - Zhang, Junrui
AU - Vancea, Alexandra
AU - Arold, Stefan T.
N1 - KAUST Repository Item: Exported on 2022-06-22
Acknowledged KAUST grant number(s): URF/1/4039-01
Acknowledgements: This research was supported by the King Abdullah University of Science and Technology (KAUST) through the baseline fund and award URF/1/4039-01 from the Office of Sponsored Research (OSR). We thank U.S. Farook Hameed for his contributions to the initial stages of this project, and we thank Ł. Jaremko, S. Al-Babili, H. Hirt, B. Zahodnik-Huntington, and A. Sandholu for their constructive comments on the manuscript.
PY - 2022/6/16
Y1 - 2022/6/16
N2 - Across all eukaryotic kingdoms, ubiquitin regulatory X (UBX) domain-containing adaptor proteins control the segregase cell division control protein 48 (CDC48), and thereby also control cellular proteostasis and adaptation. The structures and biological roles of UBX proteins in animals and fungi have garnered considerable attention. However, their counterparts in plants remain markedly understudied. Since 2021, the artificial intelligence (AI)-based algorithm AlphaFold has provided predictions of protein structural features that can be highly accurate. Predictions of the proteomes of all major model organisms are now freely accessible to the entire research community through user-friendly web interfaces. We propose that the combination of cross-kingdom comparison with AF analysis produces a wealth of testable hypotheses to inspire and guide experimental research on plant UBX domain-containing (PUX) proteins.
AB - Across all eukaryotic kingdoms, ubiquitin regulatory X (UBX) domain-containing adaptor proteins control the segregase cell division control protein 48 (CDC48), and thereby also control cellular proteostasis and adaptation. The structures and biological roles of UBX proteins in animals and fungi have garnered considerable attention. However, their counterparts in plants remain markedly understudied. Since 2021, the artificial intelligence (AI)-based algorithm AlphaFold has provided predictions of protein structural features that can be highly accurate. Predictions of the proteomes of all major model organisms are now freely accessible to the entire research community through user-friendly web interfaces. We propose that the combination of cross-kingdom comparison with AF analysis produces a wealth of testable hypotheses to inspire and guide experimental research on plant UBX domain-containing (PUX) proteins.
UR - http://hdl.handle.net/10754/679229
UR - https://linkinghub.elsevier.com/retrieve/pii/S1360138522001522
U2 - 10.1016/j.tplants.2022.05.012
DO - 10.1016/j.tplants.2022.05.012
M3 - Article
C2 - 35718708
SN - 1360-1385
JO - Trends in plant science
JF - Trends in plant science
ER -