Protein Homology Modelling

Manuel C Peitsch, University of Basel, Switzerland
Torsten Schwede, University of Basel, Switzerland

Published online: November 2011

DOI: 10.1002/9780470015902.a0005273.pub2

Protein structure prediction aims to model the three-dimensional (3D) structure of so far structurally uncharacterised proteins from their amino acid sequence. Motivated by the observation that homologous proteins with related amino acid sequences have similar 3D structures, protein homology modelling uses comparative methods to generate models for a target protein based on one or more related proteins with known 3D structure. The coordinates of the model are generated based on alignments between the target's and template's amino acid sequences, which define the correspondence between residues in both proteins. Ultimately, the quality of a computational model determines its usefulness for specific biomedical applications. Therefore, model quality estimation methods are used to identify unreliable or erroneous regions in the resulting models, and to estimate the overall accuracy of a model. Homology modelling (or comparative modelling) is currently the most accurate computational method available to routinely generate models of sufficient quality for various applications in life science research. Comparative protein modelling methods have been completely automated in recent years, and several Internet servers offer protein modelling services which are reliable and easy to use – also for the nonexpert in computational biology.

Key Concepts:

  • Protein structure prediction aims to model the three-dimensional structure of so far structurally uncharacterised proteins (‘target’) based on their amino acid sequence.
  • Homologous proteins with related amino acid sequences have similar three-dimensional structures.
  • Protein homology modelling uses information from one or more related proteins with known three-dimensional structure (‘template’) to generate models for the target protein.
  • Sensitive sequence searching methods are applied to identify template proteins with known structures in large databases.
  • An alignment between the target's and template's amino acid sequences describes the correspondence between residues in both proteins.
  • The coordinates of the model are constructed by extracting positional information from the corresponding structural template.
  • Segments of the target protein not covered by template information (e.g. insertions/deletion in the alignment) have to be constructed using de novo modelling methods.
  • Model quality estimation methods are used to identify unreliable or erroneous regions in the resulting models.
  • Ultimately, the quality of a structural model determines its usefulness for specific biomedical applications.

Keywords: protein structure prediction; protein structure modelling; bioinformatics; computational structural biology; structural genomics; homology modelling; functional genomics

Figure 1. Historical view on the structural coverage of the Escherichia coli proteome by experimental structures and homology models. The plot shows in a retrospective analysis which structure information – experimental structures or models of various levels of target–template sequence identity – was available for the residues in the proteome of the model organism E. coli at a given point in time (Guex et al., 2009).
Figure 2. Schematic homology modelling workflow. The flowchart illustrates the classical steps to construct a homology model. Starting from the sequence of the target protein, one or more related structures (templates) are identified (template selection) within a template library. Target and template sequences are aligned (target–template alignment) and one or more alternative models are then constructed based on alternative target–template alignments. Finally the quality of the obtained models is estimated to rank models by their expected accuracy. If necessary, the procedure can be repeated by selecting different templates and creating alternative target–template alignments until a satisfactory result is obtained.
Figure 3. Model accuracy and modelling errors. In this retrospective analysis, a model of the PAS domain of a transcriptional regulator in the LuxR family from Burkholderia thailandensis (cartoon representation) is shown in comparison with its experimental control structure (3MQO chain B, gray tubes). The model was based on the experimental structure of the homologues protein CPS_1291 from Colwellia psychrerythraea as template (3LYX chain B), sharing an overall 14% sequence identity. In this particular example, the overall fold has been modelled correctly with only one loop deviating significantly from the control structure, illustrating a successful of template-based model despite very low sequence identity. The model has been generated as part of the 9th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction CASP9 (http://predictioncenter.org/casp9/) in the category of template-based modelling.
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Related Sub-Topics:

Protein Structure | Bioinformatics | Biochemical and Biophysical Techniques | Proteins: Structure, Function, Metabolism
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Article Title: Protein Homology Modelling
 
How to Cite close
Peitsch, Manuel C, and Schwede, Torsten(Nov 2011) Protein Homology Modelling. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0005273.pub2]