References

• SWISS-MODEL Workspace/ GMQE
  Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F.T., de Beer, T.A.P., Rempfer, C., Bordoli, L., Lepore, R., Schwede, T. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 46, W296-W303 (2018).
• SWISS-MODEL Repository
  Bienert, S., Waterhouse, A., de Beer, T.A.P., Tauriello, G., Studer, G., Bordoli, L., Schwede, T. The SWISS-MODEL Repository - new features and functionality. Nucleic Acids Res. 45, D313-D319 (2017).
• Swiss-PdbViewer/ DeepView project mode
  Guex, N., Peitsch, M.C., Schwede, T. Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: A historical perspective. Electrophoresis 30, S162-S173 (2009).
• ProMod3
  Studer, G., Tauriello, G., Bienert, S., Biasini, M., Johner, N., Schwede, T. ProMod3 - A versatile homology modelling toolbox. PLOS Comp. Biol. 17(1), e1008667 (2021).
• QMEANDisCo
  Studer, G., Rempfer, C., Waterhouse, A.M., Gumienny, R., Haas, J., Schwede, T. QMEANDisCo - distance constraints applied on model quality estimation. Bioinformatics 36, 1765-1771 (2020).
• QMEANBrane
  Studer, G., Biasini, M., Schwede, T. Assessing the local structural quality of transmembrane protein models using statistical potentials (QMEANBrane), Bioinformatics 30, i505–i511 (2014).
• QMEAN
  Benkert, P., Biasini, M., Schwede, T. Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics 27, 343-350 (2011).
• Quaternary Structure Prediction/ QSQE
  Bertoni, M., Kiefer, F., Biasini, M., Bordoli, L., Schwede, T. Modeling protein quaternary structure of homo- and hetero-oligomers beyond binary interactions by homology. Scientific Reports 7 (2017).
• lDDT
  Mariani, V., Biasini, M., Barbato, A., Schwede, T. lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests. Bioinformatics 29, 2722-2728 (2013).
• Click for a chronological assembly of SWISS-MODEL publications.

  • Studer, G., Tauriello, G., Bienert, S., Waterhouse, A.M., Bertoni, M., Bordoli, L., Schwede, T., Lepore, R. Modeling of Protein Tertiary and Quaternary Structures Based on Evolutionary Information. Methods Mol. Biol. 1851, 301-316 (2019).
  • Biasini, M., Bienert, S., Waterhouse, A., Arnold, K., Studer, G., Schmidt, T., Kiefer, F., Cassarino, T.G., Bertoni, M., Bordoli, L., Schwede, T. SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res. 42, W252-W258 (2014).
  • Mariani, V., Biasini, M., Barbato, A., Schwede, T. lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests. Bioinformatics 29, 2722-2728 (2013).
  • Bordoli, L., Schwede T. Automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal. Methods Mol. Biol. 857, 107-136 (2012).
  • Bordoli, L., Kiefer, F., Arnold, K., Benkert, P., Battey, J., Schwede, T. Protein structure homology modeling using SWISS-MODEL workspace. Nat. Protoc. 4, 1–13 (2009).
  • Kiefer, F., Arnold, K., Kuenzli, M., Bordoli, L., Schwede, T. The SWISS-MODEL Repository and associated resources. Nucleic Acids Res. 37, D387–D392 (2009).
  • Benkert, P., Künzli, M., Schwede, T. QMEAN server for protein model quality estimation. Nucleic Acids Res. 37, W510-W514 (2009).
  • Benkert, P., Schwede, T., Tosatto, S.C.E. QMEANclust: estimation of protein model quality by combining a composite scoring function with structural density information. BMC Struct. Biol. 9, 35 (2009).
  • Arnold, K., Bordoli, L., Kopp, J., Schwede, T. The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22, 95-201 (2006).
  • Kopp, J., Schwede, T. The SWISS-MODEL Repository: new features and functionalities. Nucleic Acids Res. 34, D315–D318 (2006).
  • Kopp, J., Schwede, T. The SWISS-MODEL Repository of annotated three-dimensional protein structure homology models. Nucleic Acids Res. 32, D230–D234 (2004).
  • Schwede, T., Kopp, J., Guex, N., Peitsch, M.C. SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res. 31, 3381-3385 (2003).
  • Guex, N., Diemand, A., Peitsch, M.C. Protein modelling for all. Trends Biochem. Sci. 24, 364 - 367 (1999).
  • Guex, N., Peitsch, M.C. SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis 18, 2714-2723 (1997).
  • Peitsch, M.C. ProMod and Swiss-Model: Internet-based tools for automated comparative protein modelling. Biochem. Soc. Trans. 24, 274-279 (1996)
  • Peitsch, M.C., Herzyk, P., Wells, T.N., Hubbard, R.E. Automated modelling of the transmembrane region of G-protein coupled receptor by Swiss-model. Recept. Channels 4, 161-4 (1996).
  • Peitsch, M.C., Tschopp, J. Comparative molecular modelling of the Fas-ligand and other members of the TNF family. Mol. Immunol. 32, 761-772 (1995).
  • Peitsch, M.C. Protein Modeling by E-mail. Biotechnology (N.Y.) 13, 658–660 (1995).
  • Peitsch, M.C., Jongeneel, C.V. A 3-D model for the CD40 ligand predicts that it is a compact trimer similar to the tumor necrosis factors. Int. Immunol. 5, 233-238 (1993).

SWISS-MODEL would not be possible without the following resources and tools

• AlphaFold Protein Structure Database
  Varadi, M., Anyango, S., Deshpande, M., Nair, S., Natassia, C., Yordanova, G., Yuan, D., Stroe, O., Wood, G., Laydon, A., Žídek, A., Green, T., Tunyasuvunakool, K., Petersen, S., Jumper, J., Clancy, E., Green, R., Vora, A., Lutfi, M., Figurnov, M., Cowie, A., Hobbs, N., Kohli, P., Kleywegt, G., Birney, E., Hassabis, D., Velankar, S. (2022) AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res., 50, D439–D444.
• BLAST
  Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K. and Madden, T.L. (2009) BLAST+: architecture and applications. BMC Bioinformatics, 10, 421-430.
• BLOSUM62
Henikoff S. and Henikoff J. G. (1992) Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci USA, 89(22): 10915-10919.
• CAMEO - Continuous Automated Model EvaluatiOn
  Haas, J., Barbato, A., Behringer, D., Studer, G., Roth, S., Bertoni, M., Mostaguir, K., Gumienny, R., Schwede, T. (2017) Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12. Proteins.
• CD-HIT
  Li, W., L., Jaroszewski, Godzik, A. (2002). "Sequence clustering strategies improve remote homology recognitions while reducing search times." Protein Eng 15(8): 643-649.
• ClustalW2
  Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG. (2007). Clustal W and Clustal X version 2.0. Bioinformatics, 23, 2947-2948.
• CHARMM22/CMAP
  Mackerell AD Jr, Feig M., Brooks CL 3rd. (2004). "Extending the treatment of backbone energetics in protein force fields: limitations of gas-phase quantum mechanics in reproducing protein conformational distributions in molecular dynamics simulations." J Comput Chem 25(11):1400-15.
• DSSP
  Kabsch, W. and C. Sander (1983). "Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features." Biopolymers 22: 2577-2637.
• Fast Searching of Large Sequence Databases
  Goddard T. (2022) Fast Searching of Large Sequence Databases. https://www.rbvi.ucsf.edu/chimerax/data/kmer-aug2022/kmer_search.html.
• Graphviz
  Ellson J., Gansner E., Koutsofios L., North S.C., Woodhull G. (2002) Graphviz— Open Source Graph Drawing Tools. In: Mutzel P., Jünger M., Leipert S. (eds) Graph Drawing. GD 2001. Lecture Notes in Computer Science, vol 2265. Springer, Berlin, Heidelberg

• GISAID
  Elbe S., and Buckland-Merrett G. (2017) "Data, disease and diplomacy: GISAID’s innovative contribution to global health." Global Challenges 1: 33-46
• Gromos
  van Gunsteren, W. F. (1996). Biomolecular Simulations: The GROMOS96 Manual and User Guide. Zürich, VdF Hochschulverlag ETHZ.
  
• HHblits
  Steinegger, M., Meier, M., Mirdita, M., Vöhringer, H., Haunsberger, S. J., Söding, J. (2019). "HH-suite3 for fast remote homology detection and deep protein annotation.", BMC Bioinformatics 20, 473.
• HighCharts
  JavaScript library https://www.highcharts.com
• InterPro
  Jones P., Binns D., Chang H., Fraser M, Li W, McAnulla C, McWilliam H, Maslen J, Mitchell A., Nuka G., Pesseat S., Quinn A.F., Sangrador-Vegas A., Scheremetjew M., Yong S., Lopez R., and Hunter S. (2014). InterProScan 5: genome-scale protein function classification. Bioinformatics, Jan 2014.
• jQuery
  JavaScript Library https://jquery.com/
• Matplotlib
  Hunter, J. D. (2007). "Matplotlib: A 2D graphics environment", Comput Sci Eng 9, 90-95.
• Membrane Prediction
  Lomize, A.L., Pogozheva I.D., Lomize M.A., Mosberg H.I. (2006). Positioning of proteins in membranes: A computational approach. Protein Sci.
• MolProbity:
  Chenn V.B., Arendall W.B., Headd J.J., Keedy D.A., Immormino R.M., Kapral G.J., Murray L.W., Richardson J.S., and Richardson D.C. Acta Cryst. D66, 16-21 (2010). All-atom structure validation for macromolecular crystallography.
• Molscript:
  Per J. Kraulis (1991) MOLSCRIPT: A Program to Produce Both Detailed and Schematic Plots of Protein Structures, Journal of Applied Crystallography24, 946-950.
• NGL
  AS Rose, AR Bradley, Y Valasatava, JM Duarte, A Prlić and PW Rose. Web-based molecular graphics for large complexes. ACM Proceedings of the 21st International Conference on Web3D Technology (Web3D '16): 185-186, 2016.
  AS Rose and PW Hildebrand. NGL Viewer: a web application for molecular visualization. Nucl Acids Res (1 July 2015) 43 (W1): W576-W579 first published online April 29, 2015.
• OpenMM
  Eastman P., Swails J., Chodera J. D., McGibbon R. T., Zhao Y., Beauchamp K. A., Wang L. P., Simmonett A. C., Harrigan M. P., Stern C. D., Wiewiora R. P., Brooks B. R., Pande V. S. (2017). "OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics." PLoS Comput. Biol. 2017.
• OpenStructure (OST)
  Biasini M., Schmidt T., Bienert S., Mariani V., Studer G., Haas J., Johner N., Schenk A.D., Philippsen A. and Schwede T. (2013) "OpenStructure: an integrated software framework for computational structural biology." Acta Cryst 2013.
• PDB
  Berman, H., Westbrook J., Feng Z., Gilliland G., Bhat T. N., Weissig I., Shindyalov I., Bourne P. E. (2000) "The Proten Data Bank". Nucleic Acids Res, 28, 235-242.
  Berman, H., Henrick, K., Nakamura, H. and Markley, J.L. (2007) The worldwide Protein Data Bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acids Res, 35, D301-303.
• PISCES
  Wang G, Dunbrack RL Jr. (2003) PISCES: A protein sequence culling server. Bioinformatics 19:1589–1591.(2016)
• PFAM
  R.D. Finn, P. Coggill, R.Y. Eberhardt, S.R. Eddy, J. Mistry, A.L. Mitchell, S.C. Potter, M. Punta, M. Qureshi, A. Sangrador-Vegas, G.A. Salazar, J. Tate, A. Bateman (2016) The Pfam protein families database: towards a more sustainable future. Nucleic Acids Research (2016) Database Issue 44:D279-D285
• PLIP
  M.F. Adasme, K.L. Linnemann, S.N. Bolz, F. Kaiser, S. Salentin, V.J. Haupt, M. Schroeder (2021) PLIP 2021: expanding the scope of the protein–ligand interaction profiler to DNA and RNA. Nucleic Acids Research 49 (Web Server issue):W530-W534. doi:10.1093/nar/gkab294.
• PsiPred
  Jones, D. T. (1999). "Protein secondary structure prediction based on position-specific scoring matrices." J Mol Biol 292(2): 195-202.
• PV
  Biasini, M. (2014). "PV - WebGL-based Protein Viewer."
• InterPro
  Mulder, N. J., Apweiler, R., Attwood, T. K., Bairoch, A., Bateman, A., Binns, D., Bradley, P., Bork, P., Bucher, P., Cerutti, L., Copley, R., Courcelle, E., Das, U., Durbin, R., Fleischmann, W., Gough, J., Haft, D., Harte, N., Hulo, N., Kahn, D., Kanapin, A., Krestyaninova, M., Lonsdale, D., Lopez, R., Letunic, I., Madera, M., Maslen, J., McDowall, J., Mitchell, A., Nikolskaya, A. N., Orchard, S., Pagni, M., Ponting, C. P., Quevillon, E., Selengut, J., Sigrist, C. J., Silventoinen, V., Studholme, D. J., Vaughan, R., Wu, C. H. (2005). "InterPro, progress and status in 2005." Nucleic Acids Res 33 Database Issue: D201-205.
• Raphaël JS
  JavaScript Library htts://dmitrybaranovskiy.github.io/raphael/
• Raster3D
  Merritt E. A., Bacon D. J. (1997). "Raster3D Photorealistic Molecular Graphics." Methods in Enzymology 1997, 277 505-524
• SCRWL4
  Krivov G. G., Shapovalov M. V., Dunbrack R. L. Jr. (2009). "Improved prediction of protein side-chain conformations with SCWRL4." Proteins 2009.
• SIFTS
  Velankar, S., Dana, J.M., Jacobsen, J., van Ginkel, G., Gane, P.J., Luo, J., Oldfield, T.J., O'Donovan, C., Martin, M.J. and Kleywegt, G.J. (2013) "SIFTS: Structure Integration with Function, Taxonomy and Sequences resource." Nucleic acids research, 41, D483-489.
• SSpro / ACCpro
  Cheng J, Randall AZ, Sweredoski MJ, Baldi P. (2005) SCRATCH: a Protein Structure and Structural Feature Prediction Server, Nucleic Acids Research, vol. 33 (web server issue), w72-76, 2005.
• STRING
  Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ, von Mering C. (2015). "STRING v10: protein-protein interaction networks, integrated over the tree of life." Nucleic Acids Res, 43, D447-52.
• SwissDock
  Grosdidier A, Zoete V, Michielin O. (2011). "SwissDock, a protein-small molecule docking web service based on EADock DSS." Nucleic Acids Res, 39, W270-7
  Grosdidier A, Zoete V, Michielin O. (2011). "Fast docking using the CHARMM force field with EADock DSS." J Comput Chem. 32(10), 2149-59.
• TreePack
  Xu J, Jiao F, Berger B. (2005). "A tree-decomposition approach to protein structure prediction." Proc IEEE Comput Syst Bioinform Conf, 247-56
• Uniclust
  Mirdita, M., von den Driesch, L., Galiez, C., Martin, M.J., Söding, J., Steinegger, M. (2016) Uniclust databases of clustered and deeply annotated protein sequences and alignments. Nucleic Acids Res, 45, D170–D176.
• UniProtKB
  The UniProt Consortium. (2017) UniProt: the universal protein knowledgebase. Nucleic Acids Res, 45, D158-D169.