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Cargo Recognition Mechanisms of Yeast Myo2 Revealed by AlphaFold2-Powered Protein Complex Prediction.
Liu, Yong; Li, Lingxuan; Yu, Cong; Zeng, Fuxing; Niu, Fengfeng; Wei, Zhiyi.
Afiliação
  • Liu Y; SUSTech-HIT Joint PhD Program, Harbin Institute of Technology, Harbin 150001, China.
  • Li L; Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
  • Yu C; Brain Research Center, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
  • Zeng F; Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
  • Niu F; Brain Research Center, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
  • Wei Z; Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
Biomolecules ; 12(8)2022 07 26.
Article em En | MEDLINE | ID: mdl-35892342
Myo2, a yeast class V myosin, transports a broad range of organelles and plays important roles in various cellular processes, including cell division in budding yeast. Despite the fact that several structures of Myo2/cargo adaptor complexes have been determined, the understanding of the versatile cargo-binding modes of Myo2 is still very limited, given the large number of cargo adaptors identified for Myo2. Here, we used ColabFold, an AlphaFold2-powered and easy-to-use tool, to predict the complex structures of Myo2-GTD and its several cargo adaptors. After benchmarking the prediction strategy with three Myo2/cargo adaptor complexes that have been determined previously, we successfully predicted the atomic structures of Myo2-GTD in complex with another three cargo adaptors, Vac17, Kar9 and Pea2, which were confirmed by our biochemical characterizations. By systematically comparing the interaction details of the six complexes of Myo2 and its cargo adaptors, we summarized the cargo-binding modes on the three conserved sites of Myo2-GTD, providing an overall picture of the versatile cargo-recognition mechanisms of Myo2. In addition, our study demonstrates an efficient and effective solution to study protein-protein interactions in the future via the AlphaFold2-powered prediction.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Cadeias Pesadas de Miosina / Miosina Tipo V / Proteínas de Saccharomyces cerevisiae Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Cadeias Pesadas de Miosina / Miosina Tipo V / Proteínas de Saccharomyces cerevisiae Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article