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TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers.
Cao, Han; Ng, Marcus C K; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W I.
Afiliación
  • Cao H; Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau, China.
  • Ng MCK; Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau, China.
  • Jusoh SA; Department of Pharmaceutical Life Sciences, Faculty of Pharmacy, Universiti Teknologi MARA Cawangan Selangor, 42300 Bandar Puncak Alam, Selangor, Malaysia.
  • Tai HK; Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau, China.
  • Siu SWI; Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau, China. shirleysiu@umac.mo.
J Comput Aided Mol Des ; 31(9): 855-865, 2017 Sep.
Article en En | MEDLINE | ID: mdl-28864946
ABSTRACT
[Formula see text]-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https//cbbio.cis.umac.mo/TMDIM . Website is implemented in PHP, MySQL and Apache, with all major browsers supported.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Modelos Moleculares / Proteínas de la Membrana Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Comput Aided Mol Des Asunto de la revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Año: 2017 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Modelos Moleculares / Proteínas de la Membrana Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Comput Aided Mol Des Asunto de la revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Año: 2017 Tipo del documento: Article País de afiliación: China