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2003.

116. Tripos, www.tripos.com

117. Accelrys, www.accelrys.com

118. Chemical Computing Group, www.chemcomp.com

119. Schrödinger, www.schrodinger.com

120. Open Eye, www.eyesopen.com

121. MDL, http://www.mdli.com

122. Cheminfomatics.org, www.cheminformatics.org

123. W.L. Jorgensen. QSAR/QSPR and Proprietary Data. J. Chem. Inf. Model., 2006, 46, 937-937.

124. Open Babel, http://openbabel.sourceforge.net

125. Murray-Rust, P.; Rzepa, H. S. Chemical Markup, XML, and the Worldwide Web. 1. Basic Principles. J. Chem. Inf. Comput. Sci. 1999, 39, 928-942.

126. Murray-Rust, P.; Rzepa, H. S. Chemical Markup, XML and the World-Wide Web. 2. Information Objects and the CMLDOM J. Chem. Inf. Comput. Sci. 2001, 41, 1113-1123.

127. Gkoutos, G. V.; Murray-Rust, P.; Rzepa, H. S.; Wright, M. Chemical Markup, XML, and the World-Wide Web. 3. Toward a Signed Semantic Chemical Web of Trust. J. Chem. Inf. Comput. Sci. 2001, 41, 1124-1130.

128. Murray-Rust, P.; Rzepa, H. S. Chemical Markup, XML, and the World Wide Web. 4. CML Schema. J. Chem. Inf. Comput. Sci. 2003, 43, 757-772.

129. Murray-Rust, P.; Rzepa, H. S.; Williamson, M. J.; Willighagen, E. L. Chemical Markup, XML, and the World Wide Web. 5. Applications of Chemical Metadata in RSS Aggregators. J. Chem. Inf. Comput. Sci. 2004, 44, 462-469.

130. Holliday, G. L.; Murray-Rust, P.; Rzepa, H. S. Chemical Markup, XML, and the World Wide Web. 6. CMLReact, an XML Vocabulary for Chemical Reactions. J. Chem. Inf. Comput. Sci. 2006, 46, 145-157.

131. Liao, Y.M.; Ghanadan, H. Communicating Chemistry: The Chemical Markup Language. Anal. Chem. 2002, 74, 389-390.

132. Geldenhuys, W.J.; Gaasch, K.E.; Watson, M.; Allen, D.D.; Van der Schyf, C.J. Optimizing the use of open-source software applications in drug discovery. Drug Discov. Today 2006, 11, 127-132.

133. DeLano, W.L. The case for open-source software in drug discovery. Drug Discov. Today 2005, 10, 213-217.

134. Guha, R.; Howard, M.T.; Hutchison, G.R.; Murray-Rust, P.; Rzepa, H.; Steinbeck, C.; Wegner, J.; Willighagen, E.L. The Blue Obelisk-Interoperability in Chemical Informatics. J. Chem. Inf. Model. 2006, 46, 991-998.

135. IBM Archives: Valuable resources on IBM’s history:

http://www-03.ibm.com/ibm/history/history/decade_1950.html

136. MOE, Chemical Computing Group, http://www.chemcomp.com/

137. Arnoult, E. ; Mozziconacci, J. C. ; Baurin, N. ; Marot, C. ; Morin-Allory, L. Structural analysis of molecular databases and selection of drug-like compounds for virtual screening applications. Congrès annuel de la société française de biochimie et biologie moléculaire, 2003, Lyon.

138. Oracle, http://www.oracle.com

139. MySQL AB, http://www.mysql.com

140. SQL Server, Microsoft, www.microsoft.com/sql/

141. Daylight, www.daylight.com

142. Isis/Host and Isis/Base, MDL Information Systems, Inc., www.mdl.com

143. Activity Base, idbs, www.id-bs.com/activitybase/

144. Pipeline Pilot, SciTegic, www.scitegic.com

145. CORINA, Molecular Networks, http://www.mol-net.de/software/corina/

146. Concord, Tripos, http://www.tripos.com

147. Sybyl, Tripos, http://www.tripos.com

148. http://www.eyesopen.com/products/applications/omega.html

149. Schuffenhauer, A.; Popov, M.; Schopfer, U.; Acklin, P.; Stanek, J. Jacoby, E. Molecular Diversity Management Strategies for Building and Enhancement of Diverse and Focused Lead Discovery Compound Screening Collections. Comb Chem High Throughput Screen 2004, 7, 771-781.

150. LigPrep, Schrödinger, http://www.schrodinger.com

151. Molinspiration, http://www.molinspiration.com

152. The IUPAC International Chemical Identifier. http://www.iupac.org/inchi

153. JGoodies, http://www.jgoodies.com

154. JFreeChart, www.jfree.org/jfreechart/

155. EasyPHP, http://www.easyphp.org/

156. Xue, L.; Godden, J.W.; Bajorath, J. Database Searching for Compounds with Similar Biological Activity Using Short Binary Bit String Representations of Molecules. J. Chem. Inf. Comput. Sci. 1999, 39, 881-886.

157. Reynolds, C. H.; Druker, R.; Pfahle, L. B. Lead Discovery Using Stochastic Cluster Analysis (SCA): A New Method for Clustering Structurally Similar Compounds. J. Chem. Inf. Comput. Sci. 1998, 38, 305-312.

158. Voigt, J. H.; Bienfait, B.; Wang, S.; Nicklaus, M. C. Comparison of the NCI Open Database with Seven Large Chemical Structural Databases J. Chem. Inf. Comput. Sci. 2001, 41, 702-712.

159. Baurin, N.; Aboul-Ela, F.; Barril, X.; Davis, B.; Drysdale, M.; Dymock, B.; Finch, H.; Fromont, C.; Richardson, C.; Simmonite, H.; Hubbard, R. E. Design and Characterization of Libraries of Molecular Fragments for Use in NMR Screening against Protein Targets. J. Chem. Inf. Comput. Sci. 2004, 44, 2157-2166.

160. Bemis, G.W.; Murcko, M.A. The Properties of Known Drugs. 1. Molecular Frameworks. J.Med.Chem 1996, 39, 2887-2893.

161. Bemis GW, Murcko MA. Properties of known drugs. 2. Side chains. J.Med.Chem 1999, 42, 5095-5099.

162. Harper, G.; Bravi, G. S.; Pickett, S. D.; Hussain, J.; Green, D. V. S. The Reduced Graph Descriptor in Virtual Screening and Data-Driven Clustering of High-Throughput Screening Data. J. Chem. Inf. Comput. Sci. 2004, 44, 2145-2156.

163. Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug. Deliv. Rev. 2001, 46, 3-26.

164. Lipinski, C.A. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov. Today 2004, 1, 337-341.

165. Mozziconacci, J.C., Arnoult, E., Baurin, N., Marot, C., Morin-Allory, L., Preparation of a molecular database from a set of 2 million compounds for virtual screening applications : gathering, structural analysis and filtering, 9th Electronic Computational Chemistry Conference, World Wide Web, march 2003.

166. Walters ,W.P.; Murcko M.A. Prediction of ‘drug-likeness’. Adv. Drug. Deliv. Rev. 2002, 54, 255-271.

167. Charifson, P.S.; Walters W.P. Filtering databases and chemical libraries J. Comput. Aided Mol. Des. 2002, 16, 311-323.

168. Wildman, S.A.; Crippen, G.M. Prediction of physicochemical parameters by atomic contributions J. Chem. Inf. Comput. Sci. 1999, 39, 868-873.

169. Hann, M. M.; Oprea, T. I. Pursuing the leadlikeness concept in pharmaceutical research. Curr Opin Chem Biol 2004, 8, 255-263.

170. Wenlock, M.C.; Austin, R.P.; Barton, P.; Davis, A.M.; Leeson P.D. A Comparison of Physiochemical Property Profiles of Development and Marketed Oral Drugs J. Med. Chem. 2003, 46, 1250-1256.

171. The Prestwick Chemical Library, http://www.prestwickchemical.com/chem_lib.htm

172. Hou, T. J.; Xia, K.; Zhang, W.; Xu, X. J. ADME Evaluation in Drug Discovery. 4. Prediction of Aqueous Solubility Based on Atom Contribution Approach. J. Chem. Inf. Comput. Sci. 2004, 44, 266-275.

173. Ertl, P.; Rohde, B.; Selzer, P. Fast Calculation of Molecular Polar Surface Area as a Sum of Fragment-Based Contributions and Its Application to the Prediction of Drug Transport Properties. J. Med. Chem. 2000, 43, 3714-3717.

174. Baurin, N.; Baker, R.; Richardson, C.; Chen, I.; Foloppe, N.; Potter, A.; Jordan, A.; Roughley, S.; Parratt, M.; Greaney, P.; Morley, D.; Hubbard, R.E. Drug-like Annotation and Duplicate Analysis of a 23-Supplier Chemical Database Totalling 2.7 Million Compounds J. Chem. Inf. Comput. Sci. 2004, 44, 643-657.

175. Palm, K.; Stenberg, P.; Luthman, K.; Artursson, P. Polar molecular surface properties predict the intestinal absorption of drugs in humans, Pharm. Res., 1997, 14, 568-571.

176. Oprea, T.I. Property distribution of drug-related chemical databases. J. Comput. Aided Mol. Des. 2000, 14, 251-264.

177. Rishton, G.M. Reactive compounds and in vitro false positives in HTS. Drug Discov. Today 1997, 2, 382-384.

178. Rishton, G.M. Nonleadlikeness and leadlikeness in biochemical screening. Drug Discov. Today 2003, 8, 86-96.

179. Seidler, J.; McGovern, S. L.; Doman, T. N.; Shoichet, B. K.; Identification and Prediction of Promiscuous Aggregating Inhibitors among Known Drugs. J.Med.Chem 2003, 46, 4477-4486.

180. DeSimone, R.W.; Currie, K.S.; Mitchell, S.A.; Darrow, J.W.; Pippin, D.A. Privileged Structures: Applications in Drug Discovery. Comb Chem High Throughput Screen 2004, 7, 473-493.

181. Horton, D.A.; Bourne, G.T.; Smythe, M.L. The Combinatorial Synthesis of Bicyclic Privileged Structures or Privileged Substructures. Chem. Rev. 2003, 103, 893-930.

182. Sheridan, R.P. Finding Multiactivity Substructures by Mining Databases of Drug-Like Compounds. J. Chem. Inf. Comput. Sci. 2003, 43, 1037-1050.

183. Zhou, C.; Guo, L.; Morriello, G.; Pasternak, A.; Pan, Y.; Rohrer, S.P.; Birzin, E.T.; Huskey, S.E.; Jacks, T.; Schleim, K.D.; Cheng, K.; Schaeffer, J.M.; Patchett, A.A.; Yang, L. Nipecotic and iso-nipecotic amides as potent and selective somatostatin subtype-2 receptor agonists. Bioorg. Med. Chem. Lett. 2001, 11, 415-417.

184. Gurrath, M. Peptide-Binding G Protein-Coupled Receptors: New Opportunities for Drug Design. Curr. Med. Chem. 2001, 8, 1605-1648.

185. Mason, J.S.; Morize, I.; Menard, P.R.; Cheney, D.L.; Hulme, C. Labaudiniere, R.F. New 4-Point Pharmacophore Method for Molecular Similarity and Diversity Applications: Overview of the Method and Applications, Including a Novel Approach to the Design of Combinatorial Libraries Containing Privileged Substructures. J.Med.Chem 1999, 42, 3251-3264.

186. Barakat, K.J.; Cheng, K.; Chan, W.W.; Butler, B.S.; Jacks, T.M.; Schleim, K.D.; Hora, D.F.; Hickey, G.J.; Smith, R.G.; Patchett, A.A.; Nargund, R.P. Synthesis and biological activities of phenyl piperazine-based peptidomimetic growth hormone secretagogues. Bioorg. Med. Chem. Lett. 1998, 8, 1431-1436.

187. Omega, http://www.eyesopen.com/

188. Parallel Virtual Machine, http://www.csm.ornl.gov/pvm/pvm_home.html

189. Jim Farley, Java Distributed Computing, O’Reilly & Associates.

190. Bradley, M.P. An overview of the diversity represented in commercially-available databases J. Comput. Aided Mol. Des. 2002, 16, 299-300.

191. Voigt, J. H.; Bienfait, B.; Wang, S.; Nicklaus, M. C. Comparison of the NCI Open Database with Seven Large Chemical Structural Databases J. Chem. Inf. Comput. Sci. 2001, 41, 702-712.

192. Mozziconacci, J.C., Arnoult, E., Baurin, N., Marot, C., Morin-Allory, L., Preparation of a molecular database from a set of 2 million compounds for virtual screening applications : gathering, structural analysis and filtering, 9th Electronic Computational Chemistry Conference, World Wide Web, march 2003.

193. Baurin, N.; Baker, R.; Richardson, C.; Chen, I.; Foloppe, N.; Potter, A.; Jordan, A.; Roughley, S.; Parratt, M.; Greaney, P.; Morley, D.; Hubbard, R.E. Drug-like Annotation and Duplicate Analysis of a 23-Supplier Chemical Database Totalling 2.7 Million Compounds J. Chem. Inf. Comput. Sci. 2004, 44, 643-657.

194. Sirois, S.; Hatzakis, G.; Wei, D.; Du, Q.; Chou, K.C. Assessment of chemical libraries for their druggability. Comput. Biol. Chem. 2005, 29, 55-67.

195. Cummins, D.J.; Andrews, C.W.; Bentley, J.A.; Cory, M. Molecular Diversity in Chemical Databases: Comparison of Medicinal Chemistry Knowledge Bases and Databases of Commercially Available Compounds. J. Chem. Inf. Comput. Sci. 1996, 36, 750-763.

196. Krier, M.; Bret, G.; Rognan, D. Assessing the Scaffold Diversity of Screening Libraries. J. Chem. Inf. Model. 2006, 46, 512-524.

197. Baurin, N., Etude et développement de techniques QSAR pour la recherche de molécules d'intérêt thérapeutique , Texte imprimé : criblage virtuel et analyse de chimiothèques, Thèse, Université d’Orléans, France, 2002.

198. Monge, A. Arrault, A., Marot, C, Morin-Allory, L. Managing, Profiling and Analyzing a Library of 2.6 Million Compounds Gathered from 32 Chemical Providers. Mol. Divers. 2006, DOI : 10.1007/s11030-006-9033-5

199. MACCS II Manual. MDL Information Systems, Inc.

200. Lewell, X. Q.; Judd, D. B.; Watson, S. P.; Hann, M. M. RECAP-Retrosynthetic Combinatorial Analysis Procedure: A Powerful New Technique for Identifying Privileged Molecular Fragments with Useful Applications in Combinatorial Chemistry. J. Chem. Inf. Comput. Sci.
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