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1.
Nat Commun ; 12(1): 3399, 2021 06 07.
Artigo em Inglês | MEDLINE | ID: mdl-34099703

RESUMO

Structures of macromolecular assemblies derived from cryo-EM maps often contain errors that become more abundant with decreasing resolution. Despite efforts in the cryo-EM community to develop metrics for map and atomistic model validation, thus far, no specific scoring metrics have been applied systematically to assess the interface between the assembly subunits. Here, we comprehensively assessed protein-protein interfaces in macromolecular assemblies derived by cryo-EM. To this end, we developed Protein Interface-score (PI-score), a density-independent machine learning-based metric, trained using the features of protein-protein interfaces in crystal structures. We evaluated 5873 interfaces in 1053 PDB-deposited cryo-EM models (including SARS-CoV-2 complexes), as well as the models submitted to CASP13 cryo-EM targets and the EM model challenge. We further inspected the interfaces associated with low-scores and found that some of those, especially in intermediate-to-low resolution (worse than 4 Å) structures, were not captured by density-based assessment scores. A combined score incorporating PI-score and fit-to-density score showed discriminatory power, allowing our method to provide a powerful complementary assessment tool for the ever-increasing number of complexes solved by cryo-EM.


Assuntos
Microscopia Crioeletrônica/métodos , Substâncias Macromoleculares/química , Domínios e Motivos de Interação entre Proteínas , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas , Proteínas/química , Humanos , Aprendizado de Máquina , Substâncias Macromoleculares/metabolismo , Substâncias Macromoleculares/ultraestrutura , Modelos Moleculares , Redes Neurais de Computação , Conformação Proteica , Multimerização Proteica , Proteínas/metabolismo , Proteínas/ultraestrutura , Máquina de Vetores de Suporte , Proteínas não Estruturais Virais/química , Proteínas não Estruturais Virais/metabolismo , Proteínas não Estruturais Virais/ultraestrutura
2.
Methods ; 100: 42-9, 2016 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-26988127

RESUMO

As the resolutions of Three Dimensional Electron Microscopic reconstructions of biological macromolecules are being improved, there is a need for better fitting and refinement methods at high resolutions and robust approaches for model assessment. Flex-EM/MODELLER has been used for flexible fitting of atomic models in intermediate-to-low resolution density maps of different biological systems. Here, we demonstrate the suitability of the method to successfully refine structures at higher resolutions (2.5-4.5Å) using both simulated and experimental data, including a newly processed map of Apo-GroEL. A hierarchical refinement protocol was adopted where the rigid body definitions are relaxed and atom displacement steps are reduced progressively at successive stages of refinement. For the assessment of local fit, we used the SMOC (segment-based Manders' overlap coefficient) score, while the model quality was checked using the Qmean score. Comparison of SMOC profiles at different stages of refinement helped in detecting regions that are poorly fitted. We also show how initial model errors can have significant impact on the goodness-of-fit. Finally, we discuss the implementation of Flex-EM in the CCP-EM software suite.


Assuntos
Imageamento Tridimensional , Software , Adenilato Quinase/química , Adenilato Quinase/ultraestrutura , Chaperonina 60/química , Chaperonina 60/ultraestrutura , Microscopia Crioeletrônica , Proteínas de Escherichia coli/química , Proteínas de Escherichia coli/ultraestrutura , Fatores de Iniciação em Eucariotos/química , Fatores de Iniciação em Eucariotos/ultraestrutura , Modelos Moleculares , Subunidades Ribossômicas Maiores de Eucariotos/química , Subunidades Ribossômicas Maiores de Eucariotos/ultraestrutura
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