ArticleJournal of structural biology2018
De novo main-chain modeling with MAINMAST in 2015/2016 EM Model Challenge.
Article in Journal of structural biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Enhancing cryo-EM maps with 3D deep generative networks for assisting protein structure modeling.Bioinformatics (Oxford, England) · 2023Article
- Protein Structural Modeling for Electron Microscopy Maps Using VESPER and MAINMAST.Current protocols · 2022Article
- Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design.Frontiers in pharmacology · 2022Review
- CryoFold: determining protein structures and data-guided ensembles from cryo-EM density maps.Matter · 2021Article
- VESPER: global and local cryo-EM map alignment using local density vectors.Nature communications · 2021Article
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Current approaches for automated model building into cryo-EM maps using Buccaneer with CCP-EM.Acta crystallographica. Section D, Structural biology · 2020Article
- MAINMASTseg: Automated Map Segmentation Method for Cryo-EM Density Maps with Symmetry.Journal of chemical information and modeling · 2020Article
- Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps.Molecules (Basel, Switzerland) · 2019Review
- Comparing cryo-EM structures.Journal of structural biology · 2018Article
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Authors and funding
2 authors.
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Abstract
Protein tertiary structure modeling is a critical step for the interpretation of three dimensional (3D) election microscopy density. Our group participated the 2015/2016 EM Model Challenge using the MAINMAST software for a de novo main chain modeling. The software generates local dense points using the mean shifting algorithm, and connects them into Cα models by calculating the minimum spanning tree and the longest path. Subsequently, full atom structure models are generated, which are subject to structural refinement. Here, we summarize the qualities of our submitted models and examine successful and unsuccessful models, including 3D models we did not submit to the Challenge. Our protocol using the MAINMAST software was sometimes able to build correct conformations with 3.4-5.1 Å RMSD. Unsuccessful models had failure of chain traces, however, their Cα positions and some local structures were quite correctly built. For evaluate the quality of the models, the MAINMAST software provides a confidence score for each Cα position from the consensus of top 100 scoring models.
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