Comparative Protein Structure Modeling Using MODELLER

By Narayanan Eswar, Ben M. Webb, Marc A. Martí-Renom, Mallur Srivatsan Madhusudhan, David Eramian, Min-Yi Shen, Ursula Pieper, Andrej Sali. Current Protocols in Protein Science, 2007

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Functional characterization of a protein sequence is a common goal in biology, and is usually facilitated by having an accurate three‐dimensional (3‐D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3‐D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3‐D 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 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. Curr. Protoc. Protein Sci. 50:2.9.1‐2.9.31. © 2007 by John Wiley & Sons, Inc.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1e3cb9166a0714fbc9525f29e93adb81f89a751f

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Citations in the corpus

MEDELLER: homology-based coordinate generation for membrane proteins (2010, methodology): “Received on July 1, 2010; revised on September 21, 2010; accepted on September 25, 2010”
Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints (2018, methodology): “The representative structure of the largest cluster is taken, selected by estimated model accuracy using a combination of MODCHECK [38] Cβ potentials of mean force and all atom MODELLER [39] DOPE-HR scores, and this model used to seed the next iteration.”
ElliPro: a new structure-based tool for the prediction of antibody epitopes (2008, methodology): “Here we present ElliPro (derived from Ellipsoid and Protrusion), a web-tool that implements a modified version of Thornton's method [9] and, together with a residue clustering algorithm, the MODELLER program [10] and the Jmol viewer, allows the prediction and visualization of antibody epitopes in pr”
De novo computational RNA modeling into cryoEM maps of large ribonucleoprotein complexes (2018, methodology): “…fit into the map for all helical parts of the three regions modeled: the U5 snRNA three-way junction (residues 35–53, 62–91, and 103–119), the U5 snRNA internal loop II (residues 4–40, 114–144), and the U4/U6 snRNA three-way junction consisting of U4 snRNA residues 1–64 and U6 snRNA residues 55–80.”
Template-based structure modeling of protein-protein interactions (2013, methodology): “In several methods such as HOMCOS [45,49] and Interactome3D [65 ], and HOMBACOP [25], the monomerbased comparative modeling programs MODELLER [66] and NEST [67] are used to build complete complex models.”
Assessment of the CASP14 Assembly Predictions (2021, methodology): “44 These predictions came from a classical template-based approach (established by the consecutive use of HHPred 28,29 and Modeller 45 ).”