SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information

By Marco Biasini, Stefan Bienert, Andrew M. Waterhouse, Konstantin Arnold, Gabriel Studer, Tobias Schmidt, Florian Kiefer, Tiziano Gallo Cassarino, Martino Bertoni, Lorenza Bordoli and 1 more. 2014

4,664 citations recorded by the source corpus.

Protein structure homology modelling has become a routine technique to generate 3D models for proteins when experimental structures are not available. Fully automated servers such as SWISS-MODEL with user-friendly web interfaces generate reliable models without the need for complex software packages or downloading large databases. Here, we describe the latest version of the SWISS-MODEL expert system for protein structure modelling. The SWISS-MODEL template library provides annotation of quaternary structure and essential ligands and co-factors to allow for building of complete structural models, including their oligomeric structure. The improved SWISS-MODEL pipeline makes extensive use of model quality estimation for selection of the most suitable templates and provides estimates of the expected accuracy of the resulting models. The accuracy of the models generated by SWISS-MODEL is continuously evaluated by the CAMEO system. The new web site allows users to interactively search for templates, cluster them by sequence similarity, structurally compare alternative templates and select the ones to be used for model building. In cases where multiple alternative template structures are available for a protein of interest, a user-guided template selection step allows building models in different functional states. SWISS-MODEL is available at http://swissmodel.expasy.org/.

Subfields: Materials Chemistry, Molecular Biology, Computational Biology & Bioinformatics

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Citations in the corpus

SWISS-MODEL: homology modelling of protein structures and complexes (2018, positive): “SWISS-MODEL https://swissmodel.expasy.org was the first fully automated protein homology modelling server and has been continuously improved during the last 25 years (25–30).”
The SWISS-MODEL Repository—new features and functionality (2016, methodology): “In brief, the SMTL is searched to identify suitable template structures using BLAST (20) and HHBlits (16) and templates are ranked by a predicted global quality estimate (13).”
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model (2016, methodology): “Nevertheless, the CAMEO participants include some well-known servers such as Robetta[34], Phyre[35], RaptorX[36], Swiss-Model[37] and HHpred[38].”
Folding membrane proteins by deep transfer learning (2017, methodology): “However, the CAMEO participants include some well-known servers such as Robetta(Kim et al., 2004) and its test version Server19(Ovchinnikov et al., 2017), Phyre(Kelley et al., 2015), RaptorX(Källberg et al., 2012), Swiss-Model(Biasini et al., 2014) and HHpred(Remmert et al., 2012).”
Computer-Aided Drug Design Methods (2017, methodology): “Alternatively, a 3D structure may be constructed using homology modeling methods with a program such as MODELLER (33) or an on-line web server such as SWISS-MODEL (34).”
ProViz—a web-based visualization tool to investigate the functional and evolutionary features of protein sequences (2016, background): “The query protein sequence is also annotated with protein feature data from numerous resources (Figure 2A and Supplementary Table S3) (3,9,10,12– 15, 18 , 19 , 22 , 35 , 36 ).”
Structural Insights into the Mammalian Late-Stage Initiation Complexes (2020, methodology): “Eukaryotic Initiation factor 1A (eIF1A) template was extracted fromSaccharomyces cerevisiae 48S pre-initiation complex (PDB ID: 3JAP chain i) (Llácer et al., 2015) and thread into Oryctolagus cuniculus in Swiss-model.”
Protein Structure and Function Prediction Using I-TASSER (2015, methodology): “Both EC and GO ( UNIT 7.2 ; Blake and Harris, 2008) predictions are generated by CO-FACTOR (Roy et al., 2012), by global and local structural comparisons of the I-TASSER models with known proteins in the BioLiP function library.”
Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120 and Gag (2020, methodology): “The three dimensional structure of 2019-nCoV glycoprotein was generated by using SWISS-MODEL online server (Biasini et al., 2014) and the structure was marked and visualized by using PyMol (DeLano, 2002).”
Electron-Microscopy-Based Epitope Mapping Defines Specificities of Polyclonal Antibodies Elicited during HIV-1 BG505 Envelope Trimer Immunization (2018, methodology): “, 2007) with homology models for Fab 10A (SWISS-MODEL; Arnold et al., 2006; Biasini et al., 2014; Bordoli et al., 2009) as search models and further refined using phenix.”
Cryo-EM structure of the SARS coronavirus spike glycoprotein in complex with its host cell receptor ACE2 (2018, methodology): “The homologous model of the SARS-CoV S glycoprotein in postfusion state was calculated using the MHV S glycoprotein in the postfusion state (PDB ID: 6b3o) as reference model with SWISS-MODEL [39] .”
Structure and Dynamics of a 197 bp Nucleosome in Complex with Linker Histone H1. (2017, methodology): “…Adams et al., 2010 https://www.phenix-online.org Coot Emsley et al., 2010 https://www2.mrc-lmb.cam.ac.uk/personal/ pemsley/coot/ SWISS-MODEL server Biasini et al., 2014 https://swissmodel.expasy.org/ SBGrid (compilation of crystallographic analysis software) Morin et al., 2013…”