{"id":"doi:10.1016/j.cell.2022.11.010","kind":"article","title":"IFT-A structure reveals carriages for membrane protein transport into cilia","authors":["Sophie J. Hesketh","Aakash Gautam Mukhopadhyay","Dai Nakamura","Katerina Toropova","Anthony J. Roberts"],"author_count":5,"year":2022,"published":"2022-12-01","venue":"Cell","cited_by":83,"doi":"10.1016/j.cell.2022.11.010","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.cell.2022.11.010","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.cell.2022.11.010","updated":null,"pmid":"36462505","pmcid":null,"openalex_id":"W4310668128","pdf_url":"http://www.cell.com/article/S0092867422014222/pdf","abstract":"Intraflagellar transport (IFT) trains are massive molecular machines that traffic proteins between cilia and the cell body. Each IFT train is a dynamic polymer of two large complexes (IFT-A and -B) and motor proteins, posing a formidable challenge to mechanistic understanding. Here, we reconstituted the complete human IFT-A complex and obtained its structure using cryo-EM. Combined with AlphaFold prediction and genome-editing studies, our results illuminate how IFT-A polymerizes, interacts with IFT-B, and uses an array of β-propeller and TPR domains to create \"carriages\" of the IFT train that engage TULP adaptor proteins. We show that IFT-A⋅TULP carriages are essential for cilia localization of diverse membrane proteins, as well as ICK-the key kinase regulating IFT train turnaround. These data establish a structural link between IFT-A's distinct functions, provide a blueprint for IFT-A in the train, and shed light on how IFT evolved from a proto-coatomer ancestor.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Genetic and Kidney Cyst Diseases"],"details":null,"provenance":"openalex","attribution":"Abstract of \"IFT-A structure reveals carriages for membrane protein transport into cilia\" by Sophie J. Hesketh, Aakash Gautam Mukhopadhyay, Dai Nakamura et al., https://doi.org/10.1016/j.cell.2022.11.010, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"protein-design","name":"AI Protein Design & Structure Prediction","domain_slug":"biotech"}],"cited_in_dossiers":[]}