To help us develop, improve, and support Proteus, we encourage you to
register by sending an email to us
when you download the software.
The software is provided without warranty of any kind.
Comments and criticism are welcome. Send email to firstname.lastname@example.org
Proteus documentation (preliminary)
XPLOR 3.8 with local modifications
The two main references for Proteus are:
T. Simonson, T. Gaillard, D. Mignon, M. Schmidt am Busch, A. Lopes, N. Amara, S. Polydorides, A. Sedano, K. Druart & G. Archontis (2013) Journal of Computational Chemistry, in press, 0000. Computational protein design: the Proteus software and selected applications
M. Schmidt am Busch, A. Lopes, D. Mignon & T. Simonson (2008) Journal of Computational Chemistry, 29, 1092-1102. Computational protein design: software implementation, parameter optimization, and performance of a simple method
Other related publications from our lab
S. Polydorides & T. Simonson (2013) Journal of Computational Chemistry , in press, 0000. Monte Carlo simulations of proteins at constant pH with generalized Born solvent.
T. Simonson (2013) Journal of Chemical Theory and Computation , in press, 0000. What is the dielectric constant of a protein when its backbone is fixed?
T. Simonson (2013) Current Pharmaceutical Design, 19, 4241-56. Protein:ligand recognition: simple models for electrostatic effects.
M. Schmidt am Busch, A. Lopes, D. Mignon, T. Gaillard & T. Simonson (2012) In Quantum Simulations of Materials and Biological Systems (editors: J. Zeng, R. Zhang, H. Treutlein), Springer Verlag, New York. Pages 121-140. The inverse protein folding problem: protein design and structure prediction in the genomic era.
S. Polydorides, N. Amara, T. Simonson & G. Archontis (2011) Proteins, 79, 3448-3468. Computational protein design with a generalized Born solvent model: application to asparaginyl-tRNA synthetase.
A. Aleksandrov, S. Polydorides, G. Archontis & T. Simonson (2010) Journal of Physical Chemistry B, 114, 10634-10648. Predicting the acid/base behavior of proteins: a constant-pH Monte Carlo approach with generalized Born solvent.
M. Schmidt am Busch, A. Sedano & T. Simonson (2010) Plos One, 5(5), e10410. Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.
A. Lopes, M. Schmidt am Busch & T. Simonson (2010) Journal of Computational Chemistry, 31, 1273-1286. Computational design of protein:ligand binding: modifying the specificity of asparaginyl-tRNA synthetase.
M. Schmidt am Busch, D. Mignon & T. Simonson (2009) Proteins, 77, 139â158. Computational protein design as a tool for fold recognition.
J. Noirel & T. Simonson (2008) Journal of Chemical Physics, 129, 185104-185112. Neutral evolution of proteins: the superfunnel in sequence space and its relation to mutational robustness.
M. Schmidt am Busch, A. Lopes, N. Amara, C. Bathelt & T. Simonson (2008) BMC Bioinformatics, 9, 148-163. Testing the Coulomb/Accessible Surface Area solvent model for protein stability, ligand binding, and protein design.
J. Noirel & T. Simonson (2007) BMC Structural Biology, 7, 79-93. Neutral evolution of protein-protein interactions: a computational study using simple models.
A. Lopes, A. Alexandrov, C. Bathelt, G. Archontis & T. Simonson (2007) Proteins, 67, 853-867. Computational sidechain placement and protein mutagenesis with implicit solvent models.
G. Archontis & T. Simonson (2005) Journal of Physical Chemistry B, 109, 22667-22673. A residue-pairwise Generalized Born model suitable for protein design calculations.