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Very little free energy

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I suggest reviewing the sentence "the abnormally folded shape has very little free energy (...)" in the Mad-cow disease section. Maybe the author meant very low free energy? A reference is also missing in this section. — Preceding unsigned comment added by 38.112.100.65 (talk) 19:46, 30 December 2011 (UTC)[reply]

WP:COI review

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I've finished checking through the relevant edits by Sofike68 in June 2010. It was a wikilink addition with no WP:COI issues that was subsequently removed anyway. T.Shafee(Evo﹠Evo)talk 10:52, 3 April 2016 (UTC)[reply]

Assessment comment

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The comment(s) below were originally left at Talk:Protein design/Comments, and are posted here for posterity. Following several discussions in past years, these subpages are now deprecated. The comments may be irrelevant or outdated; if so, please feel free to remove this section.

This article needs serious revision, preferably by an expert in the field of protein engineering. At the moment, this article is complete conjecture because no citations were found. Overall, the article will probably need to be rewritten.

Last edited at 04:20, 29 March 2007 (UTC). Substituted at 03:28, 30 April 2016 (UTC)

WP:NOTDIRECTORY

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The following has turned into a directory of entries some unsourced, the rest sourced to primary/non-independent sources, some blatantly promotional. This needs to be redone sourced to secondary, independent sources. See WP:NOTDIRECTORY and WP:PROMO:

Software

EGAD: A Genetic Algorithm for protein Design.[1] A free, open-source software package for protein design and prediction of mutation effects on protein-folding stabilities and binding affinities. EGAD can also consider multiple structures simultaneously for designing specific binding proteins or locking proteins into specific conformational states. In addition to natural protein residues, EGAD can also consider free-moving ligands with or without rotatable bonds. EGAD can be used with single or multiple processors.

Iterative Protein Redesign and Optimization. IPRO redesigns proteins to increase or give specificity to native or novel substrates and cofactors. This is done by repeatedly randomly perturbing the backbones of the proteins around specified design positions, identifying the lowest-energy combination of rotamers, and determining whether the new design has a lower binding energy than previous ones. The iterative nature of this process allows IPRO to make additive mutations to the protein sequence that collectively improve the specificity toward the desired substrates and/or cofactors. Experimental testing of predictions by IPRO successfully switched the cofactor preference of Candida boidinii xylose reductase from NADPH to NADH.[2]

OSPREY A free, open-source, actively developed protein design program with an emphasis on continuous protein flexibility for the side-chains and backbone, modeling of proteins as thermodynamic ensembles and algorithms with mathematical guarantees on the input. OSPREY has been used in several prospective applications with biomedical relevance, including: enzymes-redesign toward non-cognate substrates,[3] prospective prediction of resistance mutations against novel drugs,[4] drug design to treat leukemia,[5] peptide-drug design to treat cystic fibrosis,[6] and the design of probes of broadly neutralizing HIV antibodies.[7]

PROTDES software for protein design based on CHARMM molecular mechanics package.

Proteus An open source software package for protein design under active development;[8] Proteus uses a molecular mechanics solute energy and a recent implicit solvent treatment. Monte Carlo simulations are used to explore sequence and conformational space, possibly acid/base reactions, in combination with various forms of importance sampling. Proteus has been used for fold recognition applications and aminoacyl-tRNA synthetase engineering.

RosettaDesign. A software package, under active development and free for academic use, that has seen extensive successful use.[9][10][11][12][13][14][15] RosettaDesign is accessible via a web server.[16]

SHARPEN. A permissive open-source library for protein design and structure prediction. SHARPEN offers a variety of combinatorial optimization methods (e.g., Monte Carlo, Simulated Annealing, FASTER[17]) and can score proteins using the successful Rosetta all-atom force field or molecular mechanics force fields (OPLSaa). In addition to the protein modeling library, SHARPEN includes tools for scalable distributed computing.

WHAT IF software for protein modelling, design, validation, and visualisation.

Protein WISDOM. Protein WISDOM[18] is a workbench for in silico De novo Design of BioMolecules. It is an optimization-driven approach to design new sequences for improved stability or binding affinity. The sequence selection stage designs novel protein and peptide sequences based upon a rigid or flexible design template uploaded by the user. Once sequences are generated, they can be validated by either fold specificity or approximate binding affinity calculations.

Abalone program for protein modelling, molecular dynamics folding and visualisation.[19]

PoPMuSiC. Very popular among academics, with more than 400 registered users, PoPMuSiC is a fast and accurate program to design proteins with modified stability.

Role of other protein engineering tools in protein design

Protein design is one of the tools available for protein engineering. When proteins are designed using rational protein design, it is frequently the case that other protein engineering tools are used as part of the process. For example, when David Baker and co-workers designed de novo enzymes for the Kemp-elimination catalysis, these enzymes were then optimized using directed evolution to optimize the catalysts.[11] In fact, directed evolution is considered by Baker's group to be a necessary part of enzyme design, in order to identify sequence features missed by the protein design algorithms.[20]

bit of WP:OR

The following was assembled from primary sources and is a work of OR/SYN. We rely on secondary sources to construct history or pull out highlights.

The design of protein–protein interfaces for affinity has become a productive area of protein design research. Brian Kuhlman and co-workers redesigned a native monomeric protein into a homodimeric protein by designing beta-sheets between the two proteins.[21][22] In 2010 Chris Floudas and co-workers computationally designed peptide inhibitors of HIV entry and successfully validated their inhibitory capacity in cell cultures.[23] The Donald laboratory designed peptide inhibitors of a protein–protein interaction involved in cystic fibrosis, with potential therapeutic applications; these inhibitors formed a beta-sheet with the pdz-binding domain of the inhibited protein.[6] Recently, Amit Jaiswal and others have developed 30 designer peptides based on the affinity of amino-acids for each other, in order to inhibit telomerase recruitment towards telomeres.[24]


References

  1. ^ "User's Manual for EGAD! a Genetic Algorithm for protein Design!". {{cite journal}}: Cite journal requires |journal= (help)
  2. ^ Cite error: The named reference khoury was invoked but never defined (see the help page).
  3. ^ Chen, CY; Georgiev, I; Anderson, AC; Donald, BR (March 10, 2009). "Computational structure-based redesign of enzyme activity". Proceedings of the National Academy of Sciences of the United States of America. 106 (10): 3764–9. Bibcode:2009PNAS..106.3764C. doi:10.1073/pnas.0900266106. PMID 19228942.
  4. ^ Frey, KM; Georgiev, I; Donald, BR; Anderson, AC (August 3, 2010). "Predicting resistance mutations using protein design algorithms". Proceedings of the National Academy of Sciences of the United States of America. 107 (31): 13707–12. Bibcode:2010PNAS..10713707F. doi:10.1073/pnas.1002162107. PMID 20643959.
  5. ^ Gorczynski, MJ; Grembecka, J; Zhou, Y; Kong, Y; Roudaia, L; Douvas, MG; Newman, M; Bielnicka, I; Baber, G; Corpora, T; Shi, J; Sridharan, M; Lilien, R; Donald, BR; Speck, NA; Brown, ML; Bushweller, JH (October 2007). "Allosteric inhibition of the protein–protein interaction between the leukemia-associated proteins Runx1 and CBFbeta". Chemistry & Biology. 14 (10): 1186–97. doi:10.1016/j.chembiol.2007.09.006. PMID 17961830.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  6. ^ a b Roberts, KE; Cushing, PR; Boisguerin, P; Madden, DR; Donald, BR (2012). "Computational design of a PDZ domain peptide inhibitor that rescues CFTR activity". PLOS Computational Biology. 8 (4): e1002477. doi:10.1371/journal.pcbi.1002477. PMID 22532795.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  7. ^ Georgiev, I; Acharya, P; Schmidt, SD; Li, Y; Wycuff, D; Ofek, G; Doria-Rose, N; Luongo, TS; Yang, Y; Zhou, T; Donald, BR; Mascola, JR; Kwong, PD (January 1, 2012). "Design of epitope-specific probes for sera analysis and antibody isolation". Retrovirology. 9 (Suppl 2): P50. doi:10.1186/1742-4690-9-S2-P50.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  8. ^ Simonson, T; et al. (2013). "Computational protein design: the Proteus software and selected applications". Journal of Computational Chemistry. 34: 2472. {{cite journal}}: Explicit use of et al. in: |author2= (help)
  9. ^ Cite error: The named reference kuhlman03 was invoked but never defined (see the help page).
  10. ^ Cite error: The named reference jiang08 was invoked but never defined (see the help page).
  11. ^ a b Cite error: The named reference roth08 was invoked but never defined (see the help page).
  12. ^ Liu, Y; Kuhlman, B (July 2006). "RosettaDesign server for protein design". Nucleic Acids Research. 34 (Web Server issue): W235–8. doi:10.1093/nar/gkl163. PMC 1538902. PMID 16845000.
  13. ^ Dantas, Gautam; Kuhlman, Brian; Callender, David; Wong, Michelle; Baker, David (2003). "A Large Scale Test of Computational Protein Design: Folding and Stability of Nine Completely Redesigned Globular Proteins". Journal of Molecular Biology. 332 (2): 449–60. doi:10.1016/S0022-2836(03)00888-X. PMID 12948494.{{cite journal}}: CS1 maint: postscript (link)
  14. ^ Dobson, N; Dantas, G; Baker, D; Varani, G (2006). "High-Resolution Structural Validation of the Computational Redesign of Human U1A Protein". Structure. 14 (5): 847–56. doi:10.1016/j.str.2006.02.011. PMID 16698546.{{cite journal}}: CS1 maint: postscript (link)
  15. ^ Dantas, G; Corrent, C; Reichow, S; Havranek, J; Eletr, Z; Isern, N; Kuhlman, B; Varani, G; Merritt, E (2007). "High-resolution Structural and Thermodynamic Analysis of Extreme Stabilization of Human Procarboxypeptidase by Computational Protein Design". Journal of Molecular Biology. 366 (4): 1209–21. doi:10.1016/j.jmb.2006.11.080. PMC 3764424. PMID 17196978.{{cite journal}}: CS1 maint: postscript (link)
  16. ^ http://rosettadesign.med.unc.edu/
  17. ^ Desmet, J; Spriet, J; Lasters, I (July 2002). "Fast and accurate side-chain topology and energy refinement (FASTER) as a new method for protein structure optimization". Proteins. 48 (1): 31–43. doi:10.1002/prot.10131. PMID 12012335.
  18. ^ Smadbeck, James; Peterson, Meghan; Khoury, George; Taylor, Martin; Floudas, Christodoulos (July 2013). "Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules". Journal of Visualized Experiments (77): e50476. doi:10.3791/50476.
  19. ^ Example of protein folding by molecular dynamics
  20. ^ Cite error: The named reference baker10 was invoked but never defined (see the help page).
  21. ^ Stranges, PB; Machius, M; Miley, MJ; Tripathy, A; Kuhlman, B (December 20, 2011). "Computational design of a symmetric homodimer using β-strand assembly". Proceedings of the National Academy of Sciences of the United States of America. 108 (51): 20562–7. Bibcode:2011PNAS..10820562S. doi:10.1073/pnas.1115124108. PMID 22143762.
  22. ^ Der, BS; Kuhlman, B (May 31, 2013). "Strategies to control the binding mode of de novo designed protein interactions". Current Opinion in Structural Biology. 23 (4): 639–46. doi:10.1016/j.sbi.2013.04.010. PMID 23731800.
  23. ^ Bellows, ML; Taylor, MS; Cole, PA; Shen, L; Siliciano, RF; Fung, HK; Floudas, CA (November 17, 2010). "Discovery of entry inhibitors for HIV-1 via a new de novo protein design framework". Biophysical Journal. 99 (10): 3445–53. Bibcode:2010BpJ....99.3445B. doi:10.1016/j.bpj.2010.09.050. PMID 21081094.
  24. ^ Jaiswal, Amit (September 9, 2014). "Molecular inhibition of telomerase recruitment using designer peptides: an in silico approach". Journal of biomolecular structure & dynamics: 1–18. doi:10.1080/07391102.2014.953207. PMID 25204447.

-- Jytdog (talk) 17:46, 28 October 2016 (UTC)[reply]

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