Evidence map›Paper›PMID 35892342›Full record

ArticleBiomolecules2022

Cargo Recognition Mechanisms of Yeast Myo2 Revealed by AlphaFold2-Powered Protein Complex Prediction.

Yong Liu, Lingxuan Li, Cong Yu, Fuxing Zeng, Fengfeng Niu, Zhiyi Wei

Abstract read
In one paragraph

Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. AlphaFold3: A Transformer in Life Sciences.Current medicinal chemistry · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. AlphaFold2 and its applications in the fields of biology and medicine.Signal transduction and targeted therapy · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yong LiuSUSTech-HIT Joint PhD Program, Harbin Institute of Technology, Harbin 150001, China.ORCID 0000-0002-8165-8845
Lingxuan LiDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
Cong YuDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.ORCID 0000-0003-2912-6347
Fuxing ZengDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.ORCID 0000-0003-0790-0151
Fengfeng NiuDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.ORCID 0000-0001-7029-4989
Zhiyi WeiDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.ORCID 0000-0002-4446-6502

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Myosin Heavy ChainsMyosin Type VSaccharomyces cerevisiae ProteinsReceptors, Cell SurfaceSaccharomyces cerevisiaeVesicular Transport ProteinsMYO2 protein, S cerevisiaeMyosin Heavy ChainsMyosin Type VReceptors, Cell SurfaceSaccharomyces cerevisiae ProteinsVAC17 protein, S cerevisiaeVesicular Transport Proteinscytoskeletonglobular tail domain (GTD)molecular motorMyo2porganelle transportprotein–protein interactionprotein structure prediction

Identifiers

PMID35892342
PMCPMC9330073

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.