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De novo main-chain modeling with MAINMAST in 2015/2016 EM Model Challenge.
Terashi, Genki; Kihara, Daisuke.
Afiliação
  • Terashi G; Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA.
  • Kihara D; Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA; Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA. Electronic address: dkihara@purdue.edu.
J Struct Biol ; 204(2): 351-359, 2018 11.
Article em En | MEDLINE | ID: mdl-30075190
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 ŠRMSD. 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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Proteínas / Microscopia Crioeletrônica Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Proteínas / Microscopia Crioeletrônica Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article