Protein Structure Prediction

Ambrish Roy, University of Michigan, Ann Arbor, Michigan, USA
Yang Zhang, University of Michigan, Ann Arbor, Michigan, USA

Published online: August 2012

DOI: 10.1002/9780470015902.a0003031.pub2

The goal of protein structure prediction is to estimate the spatial position of every atom of protein molecules from the amino acid sequence by computational methods. Depending on the availability of homologous templates in the PDB library, structure prediction approaches are categorised into template‐based modelling (TBM) and free modelling (FM). While TBM is by far the only reliable method for high‐resolution structure prediction, challenges in the field include constructing the correct folds without using template structures and refining the template models closer to the native state when templates are available. Nevertheless, the usefulness of various levels of protein structure predictions have been convincingly demonstrated in biological and medical applications.

Key Concepts:

  • Evolution is a general principle to guide protein structure and function predictions.
  • Proteins of similar sequence have similar 3D structure.
  • Function of protein is decided by the 3D structure.
  • TBM using homologous templates has the highest accuracy.
  • Template structure can be refined by combining multiple templates.
  • Current physics‐based ab initio folding can only fold small proteins.
  • Threading is an efficient tool for detecting distantly homologous templates.
  • Membrane protein structure prediction is challenging due to the lack of templates.
  • Disordered regions exist in protein which does not possess stable structure but has important function implications.

Keywords: ab initio folding; fold recognition; comparative modelling; structure‐based function annotation; membrane protein; CASP

Figure 1. Pipeline of a typical composite protein structure prediction approach.
Figure 2. An example of the template‐based modelling by I‐TASSER server for PAS domain from Burkholderia thailandensis (PDBID: 3mqo). (a) Initial target model built by copying Cα coordinates from a nonhomology template (PDBID: 3lyx) identified by MUSTER, which contains multiple gaps; (b) full‐length model constructed by the I‐TASSER Monte Carlo assembly simulations; (c) final atomic structural model after atomic structural refinement. The grey background cartoon shows the X‐ray structure.
Figure 3. Approximate correspondence of the structure prediction algorithms, model accuracy, and the biological usefulness.
Figure 4. Predicted protein–ligand complexes using I‐TASSER and BSP‐SLIM in GPCR‐Dock 2010. (a) Dopamine D3/eticlopride complex; (b) CXCR4 chemokine receptor with compound IT1t; and (c) CXCR receptor with peptide CVX15. The native ligand binding pose is shown in green and the predicted ligand pose in red.
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Related Sub-Topics:

Protein Structure | Protein Folding, Evolution and Degradation | Bioinformatics | Computational Molecular Biology
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Article Title: Protein Structure Prediction
 
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Roy, Ambrish, and Zhang, Yang(Aug 2012) Protein Structure Prediction. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0003031.pub2]