Commentary

* Author for correspondence

Novartis Institutes for Biomedical Research, Global Discovery Chemistry/Oncology, Infectious Diseases, & Exploratory Chemistry, Emeryville, CA 94608, USA.

Email the corresponding author at johanna.jansen@novartis.com

Rommie E Amaro

Department of Chemistry & Biochemistry, University of California, San Diego, La Jolla, CA 92093, USA

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Wendy Cornell

Merck Research Labs, Knowledge Discovery/Knowledge Management, Rahway, NJ 07065, USA

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Y Jane Tseng

Graduate Institute of Biomedical Electronics & Bioinformatics, National Taiwan University, Taipei, Taiwan

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W Patrick Walters

Vertex Pharmaceuticals Inc., Cambridge, MA 02139, USA

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Published Online:22 Oct 2012https://doi.org/10.4155/fmc.12.137

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References

1 Jorgensen WL. The many roles of computation in drug discovery. Science303(5665),1813–1818 (2004).
Medline CASGoogle Scholar
2 Jansen JM, Cornell W, Tseng YJ, Amaro RE. Teach-Discover-Treat (TDT): collaborative drug discovery for neglected diseases. J. Mol. Graph. Model. doi: 10.1016/j.jmgm.2012.07.007 (2012) (In Press).
MedlineGoogle Scholar
3 Guiguemde WA, Shelat AA, Garcia-Bustos JF, Diagana TT, Gamo FJ, Guy RK. Global phenotypic screening for antimalarials. Chem.Biol.19(1),116–129 (2012).
Medline CASGoogle Scholar
4 Lessl M, Bryans JS, Richards D, Asadullah K. Crowd sourcing in drug discovery. Nat. Rev. Drug Discov.10(4),241–242 (2011).
Medline CASGoogle Scholar
5 Norman TC, Bountra C, Edwards AM, Yamamoto KR, Friend SH. Leveraging crowdsourcing to facilitate the discovery of new medicines. Sci. Transl. Med.3(88),88mr1 (2011).
MedlineGoogle Scholar
6 Strauss S. Pharma embraces open source models. Nat. Biotechnol.28(7),631–634 (2010).
Medline CASGoogle Scholar
7 Cross JB, Thompson DC, Rai BK et al. Comparison of several molecular docking programs: pose prediction and virtual screening accuracy. J. Chem. Inf. Model.49(6),1455–1474 (2009).
Medline CASGoogle Scholar
8 McGaughey GB, Sheridan RP, Bayly CI et al. Comparison of topological, shape, and docking methods in virtual screening. J.Chem. Inf. Model.47(4),1504–1519 (2007).
Medline CASGoogle Scholar
9 Cummings MD, DesJarlais RL, Gibbs AC, Mohan V, Jaeger EP. Comparison of automated docking programs as virtual screening tools. J. Med.Chem.48(4),962–976 (2005).
Medline CASGoogle Scholar
10 Perola E, Walters WP, Charifson PS. A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance. Proteins56(2),235–249 (2004).
Medline CASGoogle Scholar
11 Cornell WD. Recent evaluations of high throughput docking methods for pharmaceutical lead finding – consensus and caveats. Annu. Rep. Comput. Chem.2,297–323 (2006).
CASGoogle Scholar
12 Boyd DR. How computational chemistry became important in the pharmaceutical industry. In: Reviews in Computational Chemistry. Lipkowitz DB, Cundari TR (Eds). John Wiley and Sons, Inc., London, UK, 401–451 (2007).
Google Scholar
13 Bourne PE. What do I want from the publisher of the future?. PLoS Comput.Biol.6(5),e1000787 (2010).
MedlineGoogle Scholar
14 Dunbar JB Jr, Smith RD, Yang CY et al. CSAR benchmark exercise of 2010: selection of the protein-ligand complexes. J. Chem. Inf. Model.51(9),2036–2046 (2011).
Medline CASGoogle Scholar
101 Teach-Discover-Treat. www.teach-discover-treat.org
Google Scholar
102 Bill and Melinda Gates foundation. Private and Public Partners Unite to Combat 10 Neglected Tropical Diseases by 2020. www.gatesfoundation.org/press-releases/pages/combating-10-neglected-tropical-diseases-120130.aspx
Google Scholar
103 ChEMBL database. www.ebi.ac.uk/chembldb
Google Scholar
104 Collaborative drug discovery. www.collaborativedrug.com
Google Scholar
105 PubChem. http://pubchem.ncbi.nlm.nih.gov
Google Scholar
106 Source Forge. http://sourceforge.net
Google Scholar
107 Open Babel. http://openbabel.org
Google Scholar
108 Chemistry Development Kit. http://sourceforge.net/apps/mediawiki/cdk
Google Scholar
109 RDKit. Cheminformatics and Machine Learning Software. www.rdkit.org
Google Scholar
110 Indigo toolkit. http://ggasoftware.com/opensource/indigo
Google Scholar
111 Groovy cheminformatics with the chemistry development kit. www.lulu.com/shop/egon-willighagen/groovy-cheminformatics-with-the-chemistry-development-kit/paperback/product-20267607.html
Google Scholar
112 How to use Jmol to study and present molecular structures. http://books.google.com/books?id=59kQFyfbsJMC
Google Scholar
113 Open Babel. Official user guide. www.lulu.com/shop/open-babel-developers/open-babel/paperback/product-14927363.html
Google Scholar
114 Chemistry Toolkit Rosetta Wiki. http://ctr.wikia.com/wiki/Chemistry_Toolkit_Rosetta_Wiki
Google Scholar
115 PLoS journals. www.plos.org/publications/journals
Google Scholar
116 Teach-Discover-Treat. Competition details. www.teach-discover-treat.org/details-for-the-competition
Google Scholar

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Published online 22 October 2012

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Financial & competing interests disclosure

RE Amaro is supported in part by the National Institutes of Health through the NIH Director’s New Innovator Award Program DP2-OD007237. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

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Computational chemistry and drug discovery: a call to action

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