Specificities of Modeling of Membrane Proteins Using Multi-Template Homology Modeling

Julia Koehler Leman, Richard Bonneau

Research output: Chapter in Book/Report/Conference proceedingChapter


Structures of membrane proteins are challenging to determine experimentally and currently represent only about 2% of the structures in the Protein Data Bank. Because of this disparity, methods for modeling membrane proteins are fewer and of lower quality than those for modeling soluble proteins. However, better expression, crystallization, and cryo-EM techniques have prompted a recent increase in experimental structures of membrane proteins, which can act as templates to predict the structure of closely related proteins through homology modeling. Because homology modeling relies on a structural template, it is easier and more accurate than fold recognition methods or de novo modeling, which are used when the sequence similarity between the query sequence and the sequence of related proteins in structural databases is below 25%. In homology modeling, a query sequence is mapped onto the coordinates of a single template and refined. With the increase in available templates, several templates often cover overlapping segments of the query sequence. Multi-template modeling can be used to identify the best template for local segments and join them into a single model. Here we provide a protocol for modeling membrane proteins from multiple templates in the Rosetta software suite. This approach takes advantage of several integrated frameworks, namely, RosettaScripts, RosettaCM, and RosettaMP with the membrane scoring function.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Number of pages26
StatePublished - 2023

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029


  • Comparative modeling
  • Homology modeling
  • Membrane proteins
  • Multiple templates
  • Protein structure prediction
  • Rosetta

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics


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