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. 2016 Jun 20:54:5.6.1-5.6.37.
doi: 10.1002/cpbi.3.

Comparative Protein Structure Modeling Using MODELLER

Affiliations

Comparative Protein Structure Modeling Using MODELLER

Benjamin Webb et al. Curr Protoc Bioinformatics. .

Abstract

Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. © 2016 by John Wiley & Sons, Inc.

Keywords: MODELLER; ModBase; comparative modeling; protein fold; protein structure; structure prediction.

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Figures

Figure 5.6.1
Figure 5.6.1
Steps in comparative protein structure modeling. See text for details.
Figure 5.6.2
Figure 5.6.2
File TvLDH.ali. Sequence file in PIR format.
Figure 5.6.3
Figure 5.6.3
File build_profile.py. Input script file that searches for templates against a database of nonredundant PDB sequences.
Figure 5.6.4
Figure 5.6.4
An excerpt from the file build_profile.prf. The aligned sequences have been removed for clarity.
Figure 5.6.5
Figure 5.6.5
Script file compare.py.
Figure 5.6.6
Figure 5.6.6
Excerpts from the log file compare.log.
Figure 5.6.7
Figure 5.6.7
The script file align2d.py, used to align the target sequence against the template structure.
Figure 5.6.8
Figure 5.6.8
The alignment between sequences TvLDH and 1bdmA, in the MODELLER PAP format. File TvLDH-1bmdA.pap.
Figure 5.6.9
Figure 5.6.9
Script file, model-single.py, that generates five models.
Figure 5.6.10
Figure 5.6.10
File evaluate_model.py, used to generate a pseudo-energy profile for a single model.
Figure 5.6.11
Figure 5.6.11
A comparison of the pseudo-energy profiles of the model (red) and the template (green) structures.
Figure 5.6.12
Figure 5.6.12
Excerpt of ModBase Sequence Overview page for TvLDH. For this sequence, coverage is shown (the fraction of the sequence for which a model is available, and its quality) together with any annotations available. In this case, the entire sequence was modeled with a good quality (>=30% sequence identity) template.
Figure 5.6.13
Figure 5.6.13
Excerpt of ModBase Model Details page for TvLDH. Metadata about the model are shown on the left side of the page; these data include the part of the sequence that was modeled, the template used, the date when the modeling was performed, and a set of assessment scores. The actual 3-D models are shown on the right side of the page. The "Perform action on this model" menu allows for the models themselves or modeling alignments to be downloaded.
Figure 5.6.14
Figure 5.6.14
Typical errors in comparative modeling. (A) Errors in side chain packing. The Trp 109 residue in the crystal structure of mouse cellular retinoic acid binding protein I (red) is compared with its model (green). (B) Distortions and shifts in correctly aligned regions. A region in the crystal structure of mouse cellular retinoic acid binding protein I (red) is compared with its model (green) and with the template fatty acid binding protein (blue). (C) Errors in regions without a template. The Cα trace of the 112-117 loop is shown for the X-ray structure of human eosinophil neurotoxin (red), its model (green), and the template ribonuclease A structure (residues 111-117; blue). (D) Errors due to misalignments. The N-terminal region in the crystal structure of human eosinophil neurotoxin (red) is compared with its model (green). The corresponding region of the alignment with the template ribonuclease A is shown. The red lines show correct equivalences, that is, residues whose Cα atoms are within 5 Å of each other in the optimal least-squares superposition of the two X-ray structures. The "a" characters in the bottom line indicate helical residues and "b" characters, the residues in sheets. (E) Errors due to an incorrect template. The X-ray structure of α-trichosanthin (red) is compared with its model (green) that was calculated using indole-3-glycerophosphate synthase as the template.
Figure 5.6.15
Figure 5.6.15
Accuracy and application of protein structure models. The vertical axis indicates the different ranges of applicability of comparative protein structure modeling, the corresponding accuracy of protein structure models, and their sample applications. (A) The docosahexaenoic fatty acid ligand (violet) was docked into a high accuracy comparative model of brain lipid-binding protein (right), modeled based on its 62% sequence identity to the crystallographic structure of adipocyte lipid-binding protein (PDB code 1adl). A number of fatty acids were ranked for their affinity to brain lipid-binding protein consistently with site-directed mutagenesis and affinity chromatography experiments (Xu et al., 1996), even though the ligand specificity profile of this protein is different from that of the template structure. Typical overall accuracy of a comparative model in this range of sequence similarity is indicated by a comparison of a model for adipocyte fatty acid binding protein with its actual structure (left). (B) A putative proteoglycan binding patch was identified on a medium-accuracy comparative model of mouse mast cell protease 7 (right), modeled based on its 39% sequence identity to the crystallographic structure of bovine pancreatic trypsin (2ptn) that does not bind proteoglycans. The prediction was confirmed by site-directed mutagenesis and heparin-affinity chromatography experiments (Matsumoto et al., 1995). Typical accuracy of a comparative model in this range of sequence similarity is indicated by a comparison of a trypsin model with the actual structure. (C) A molecular model of the whole yeast ribosome (right) was calculated by fitting atomic rRNA and protein models into the electron density of the 80S ribosomal particle, obtained by electron microscopy at 15 Å resolution (Spahn et al., 2001). Most of the models for 40 out of the 75 ribosomal proteins were based on template structures that were approximately 30% sequentially identical. Typical accuracy of a comparative model in this range of sequence similarity is indicated by a comparison of a model for a domain in L2 protein from B. stearothermophilus with the actual structure (1rl2).

References

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Internet Resources

    1. http://salilab.org/modeller/

    2. Webb B, Madhusudhan MS, Shen M-Y, Dong GQ, Marti-Renom MA, Eswar N, Alber F, Topf M, Oliva B, Fiser A, Sanchez R, Yerkovich B, Badretdinov A, Melo F, Overington JP, Feyfant E, Sali A. MODELLER, A Protein Structure Modeling Program, Release 9.15 2015

    1. http://salilab.org/modbase/

    2. Pieper U, Webb B, Dong GQ, Schneidman-Duhovny D, Fan H, Kim SJ, Khuri N, Spill YG, Weinkam P, Hammel M, Tainer JA, Nilges M, Sali A. MODBASE, a database of annotated comparative protein structure models 2015 - PMC - PubMed

    1. http://salilab.org/modeval/

    2. Eramian D, Shen M-Y, Melo F, Pieper U, Webb B, Eswar N, Sanchez R, Sali A. ModEval, a web server for evaluating protein structure models 2015

    1. http://salilab.org/modloop/

    2. Fiser A, Do R, Webb B, Pieper U, Sali A. ModLoop, a web server for modeling of loops in protein structures 2003

    1. http://salilab.org/allosmod/

    2. Weinkam P, Pons J, Webb B, Pieper U, Tjioe E, Sali A. AllosMod, a web server to set up and run simulations based on modeled energy landscapes 2012
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