Structural Chemogenomics Group

Laboratoire d'Innovation Therapeutique, UMR7200 CNRS/Universite de Strasbourg

List of Publications

:

2024

220. Revillo Imbernon J, Weibel JM, Ennifar E, Prévost G, Kellenberger E.
Structural analysis of neomycin B and kanamycin A binding Aminoglycosides Modifying Enzymes (AME) and bacterial ribosomal RNA.
Mol. Inf., 2024, 43, e202300339
219. Eguida M, Bret G, Sindt F, Li F, Chau I, Ackloo S, Arrowsmith C, Bolotokova A, Ghiabi P, Gibson E, Halabelian L, Houliston S, Harding RJ, Hutchinson A, Loppnau P, Perveen S, Seitova A, Zeng H, Schapira M, Rognan D.
Subpocket Similarity-Based Hit Identification for Challenging Targets: Application to the WDR Domain of LRRK2
J. Chem. Info. Model., 2024, 64, 5344-5355
218. Urvas L, Chiesa L, Bret G, Jacquemard C, Kellenberger E.
Benchmarking AlphaFold-Generated Structures of Chemokine-Chemokine Receptor Complexes.
J. Chem. Info. Model., 2024, 64, 4587-4600
217. Sindt F., Seyller A., Eguida M, Rognan D.
Protein structure-based organic chemistry-driven ligand design from ultra-large chemical spaces
ACS Cent. Sci., 2024, 10, 615–627

2023

216. Urvas L, Sick, E., Kellenberger E.
Predicting the duration of action of β2-adrenergic receptor agonists: Ligand and structure-based approaches
Mol. Inform., 2023, 42, e202300141
216. Urvas L, Kellenberger E.
Structural Insights into Molecular Recognition and Receptor Activation in Chemokine-Chemokine Receptor Complexes
J. Med. Chem., 2023, 66, 7070-7085

215. Revillo Imbernon J., Chiesa L., Kellenberger E.
Mining the Protein Data Bank to inspire fragment library design.
Front. Chem., 2023, 11, 1089714

2022

214. Chiesa, L. and Kellenberger, E.
One class classification for the detection of β2 adrenergic receptor agonists using single-ligand dynamic interaction data
J. Cheminform., 2022, 14, 74

213. Eguida, M., Schmitt, C., Hibert, M., Villa, P. and Rognan, D.
Target-Focused Library Design by Pocket-Applied Computer Vision and Fragment Deep Generative Linking
J. Med. Chem, 2022, 65, 13771-13783

212. Eguida, M. and Rognan, D.
Estimating the similarity between protein pockets
Int. J. Mol. Sci., 2022, 23, 12462

211. Perebyinis, M. and Rognan, D.
Overlap of on-demand ultra-large combinatorial spaces with on-the-shelf drug-like libraries
Mol. Inf., 2022, 41, 2200163

210. Volkov M, Turk JA, Drizard N, Martin N, Hoffmann B, Gaston-Mathé Y, Rognan D.
On the Frustration to Predict Binding Affinities from Protein-Ligand Structures with Deep Neural Networks.
J. Med. Chem., 2022, 65, 7946-7958

209. Shanina E, Kuhaudomlarp S, Siebs E, Fuchsberger F, Denis M, da Silva Figueiredo Celestino Gomes P, Clausen MH, Seeberger P, Rognan D, Titz A, Imberty A, Rademacher C
Targeting undruggable carbohydrate recognition sites through fragment library design.
Commun. Chem., 2022, 5, 64

208. Hany R, Leyris JP, Bret G, Maillé S, Sar C, Thouaye M, Hamze A, Provot O, Sokoloff P, Valmier J, Villa P, Rognan D.
High-throughput screening for extracellular inhibitors of the FLT3 receptor tyrosine kinase reveals chemically diverse and druggable negative allosteric modulators.
ACS Chem. Biol., 2022, 17, 709-722

207. Siebs E, Shanina E, Kuhaudomlarp S, da Silva Figueiredo Celestino Gomes P, Fortin C, Seeberger PH, Rognan D, Rademacher C, Imberty A, Titz A.
Targeting the Central Pocket of the Pseudomonas aeruginosa lectin LecA.
ChemBioChem 2022, 23, e202100563

206. Jacquemard C, Bret G, Grutter T, Kellenberger E.
Comparing transmembrane protein structures with ATOLL.
Bioinformatics, 2022, 38, 1743-1744
205. Revillo Imbernon J, Jacquemard C, Bret G, Marcou G, Kellenberger E.
Comprehensive analysis of commercial fragment libraries.
RSC Med. Chem., 2022, 13, 300-310

2021

204. Jacquemard C, Koensgen F, Colin P, Lagane B, Kellenberger E.
Modeling of CCR5 Recognition by HIV-1 gp120: How the Viral Protein Exploits the Conformational Plasticity of the Coreceptor.
Viruses, 2021, 18, 1395
203. Eguida M and Rognan D.
Unexpected similarity between HIV-1 reverse transcriptase and tumor necrosis factor binding sites revealed by computer vision.
J Cheminform, 2021, 13, 90
202. Tran-Nguyen VK, Bret G, Rognan D.
True Accuracy of Fast Scoring Functions to Predict High-Throughput Screening Data from Docking Poses: The Simpler the Better.
J Chem Inf Model, 2021, 61, 2788-2797
201. Bollenbach M, Nemska S, Wagner P, Camelin G, Daubeuf F, Obrecht A, Villa P, Rognan D, Bihel F, Bourguignon JJ, Schmitt M and Frossard N.
Design, Synthesis and Biological Evaluation of Arylpyridin-2-yl Guanidine Derivatives and Cyclic Mimetics as Novel MSK1 Inhibitors. An Application in an Asthma Model.
Molecules, 2021, 26, 391
200. Kuhaudomlarp S, Siebs E, Shanina E, Topin J, Joachim I, da Silva Figueiredo Celestino Gomes P, Varrot A, Rognan D, Rademacher C, Imberty A and Titz A.
Non-Carbohydrate Glycomimetics as Inhibitors of Calcium(II)-Binding Lectins.
Angew Chem, 2021, 60, 8104-8114

2020

199. Tran-Nguyen VK, Rognan D.
Benchmarking Data Sets from PubChem BioAssay Data: Current Scenario and Room for Improvement.
Int J Mol Sci, 21, 4380
198. Eguida M and Rognan D.
A computer vision approach to align and compare protein cavities: Application to fragment-based drug design.
J Med Chem, 2020, 63, 7127-7142
197. Tran-Nguyen V-K and Rognan D.
LIT-PCBA: An unbiased dataset for machine learning and virtual screening.
J Chem Inf Model, 2020, 60, 4263–4273

196. Licona C, Delhorme JB, Riegel G, Vidimar V, Ceron-Camacho R, Boff B, Venkatasamy A, Da silva Figueiredo Celestino Gomes P, Rognan D, Le Lagadec R, Freund JN, Pfeffer M, Gross I, Mellitzer G and Gaiddon C.
Anticancer activity of Ruthenium and Osmium Cyclometallated compounds: Identification of ABCB1 and EGFR as resistance mechanisms.
Inorg Chem Front, 2020, 7, 678-688

2019

195. Liu M, Karuso P, Feng Y, Kellenberger E, Liu F, Wang C, Quinn RJ
Is it time for artificial intelligence to predict the function of natural products based on 2D-structure
Medchemcomm, 2019, 10,1667-1677
194. Da Silva F, Bret G, Teixeira L, Gonzalez CF and Rognan D.
Exhaustive Repertoire of Druggable Cavities at Protein-Protein Interfaces of Known Three-Dimensional Structure.
J Med Chem, 2019, 62, 9732-9742
193. Fremaux J, Venin C, Mauran L, Zimmer R, Koensgen F, Rognan D, Bitsi S, Lucey MA, Jones B, Tomas A, Guichard G and Goudreau SR
Ureidopeptide GLP-1 analogues with prolonged activity in vivo via signal bias and altered receptor trafficking .
Chem Sci, 2019,10, 9872-9879

192. Koensgen F, Da Silva F, Rognan D, and Kellenberger E.
Unsupervised Classification of G-Protein Coupled Receptors and Their Conformational States Using IChem Intramolecular Interaction Patterns.
J Chem Inf Model, 2019, 59, 3611-3618

191. Jacquemard C, Drwal MN, Desaphy J, and Kellenberger E.
Binding mode information improves fragment docking.
J Cheminform, 2019, 11, 24

190. Jacquemard C, and Kellenberger E.
A bright future for fragment-based drug discovery: what does it hold?
Expert Opin Drug Discov, 2019, 14(5):413-416

189. Jacquemard C, Tran-Nguyen VK, Drwal M, Rognan D and Kellenberger E.
Local Interaction Density (LID), a fast and efficient tool to prioritize docking poses.
Molecules, 2019, 24, 2610

188. Pes L, Koester SD, Magnusson JP, Chercheja S, Medda F, Abu Ajaj K, Rognan D, Daum S, Nollmann FI, Garcia Fernandez J, Perez Galan P, Walter H-K, Warnecke A. and Kratz F.
Novel auristatin E-based albumin-binding prodrugs with compelling anticancer efficacy in vivo.
J Control Release, 2019, 296, 81-92

187. Tran-Nguyen VK, Da Silva F, Bret G and Rognan D.
All in One: Cavity detection, Druggability Estimate, Cavity-Based Pharmacophore Perception and Virtual Screening
J Chem Inf Model, 59, 573-585

2018

186. Da Silva F and Rognan D.
Structure-Based Detection of Orthosteric and Allosteric Pockets at Protein-Protein Interfaces
Methods Mol Biol, 2018, 1825, 281-294

185. Regenass P, Abboud D, Daubeuf F, Lehalle C, Gizzi P, Riché, Hachet-Haas M, Rohmer F, Gasparik V, Boeglin D, Haiech J, Knehans T, Rognan D, Heissler D, Marsol C, Galzi J-L, Hibert M, Frossard N and Bonnet D .
Discovery of a Locally and Orally Active CXCL12 Neutraligand (LIT-927) with Anti-inflammatory Effect in a Murine Model of Allergic Airway Hypereosinophilia.
J Med Chem, 2018, 61, 7671-7686

184. Drwal MN, Bret G, Perez C, Jacquemard C, Desaphy J and Kellenberger E
Structural Insights on Fragment Binding Mode Conservation
J Med Chem, 2018, 61, 5963-5973

183. Jin J, Momboisse F, Boncompain G, Koensgen F, Zhou Z, Cordeiro N, Arenzana-Seisdedos F, Perez F, Lagane B, Kellenberger E and Brelot A.
CCR5 adopts three homodimeric conformations that control cell surface delivery
Sci Signal, 2018, 11, pii: eaal2869

182. Rivat C, Sar C, Mechali I, Dioufoulet L, Leyris JP, Sonrier C, Philipson Y, Lucas O, Maillé S, Haton H, Venteo S, Mezghrani A, Joly W, Mion J, Schmitt M, Pattyn A, Marmigère F, Sokoloff P, Carroll P, Rognan D* and Valmier J*
Inhibition of neuronal FLT3 receptor tyrosine kinase alleviates peripheral neuropathic pain in mice.
Nat Commun, 2018, 1042

181. Sturm N, Quinn RJ, Kellenberger E.
Structural Searching of Biosynthetic Enzymes to Predict Protein Targets of Natural Products
Planta Med, 2018, 84, 304-310.

180. Da Silva F, Desaphy, J and Rognan D.
IChem: A Versatile Toolkit for Detecting, Comparing and Predicting Protein-Ligand Interactions.
ChemMedChem, 2018, 13, 507-510

179. da Silva Figueiredo Celestino Gomes P, Da Silva F, Bret G and Rognan D.
Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2.
J Comput Aided Mol Des, 2018, 32, 75-87.

2017

178. Drwal MN, Bret G and Kellenberger E.
Multi-target Fragments Display Versatile Binding Modes.
Mol Inform, 2017, 36, 1700042
177. Muller-Steffner H, Jacques SA, Kuhn I, Schultz MD, Botta D, Osswald P, Maechling C, Lund FE and Kellenberger E.
Efficient Inhibition of SmNACE by Coordination Complexes Is Abolished by S. mansoni Sequestration of Metal.
ACS Chem Biol, 12, 1787-1795.

176. Drwal MN, Jacquemard C, Perez C, Desaphy J and Kellenberger E
Do Fragments and Crystallization Additives Bind Similarly to Drug-like Ligands?
J Chem Inf Model, 57, 1197-1209.

175. Rognan D.
The impact of in silico screening in the discovery of novel and safer drug candidates.
Pharmacol. Ther., 175, 47-66

2016

174. Varnek A and Rognan D.
5th Strasbourg Summer School in Chemoinformatics.
Mol. Inform., 35, 540

173. Sturm N, Rognan D, Quinn RJ and Kellenberger E.
Comparing atom-based with residue-based descriptors in predicting binding site similarity: do backbone atoms matter?
Future Med. Chem., 8, 1871-1885.

172. Regenass P, Riché, S, Péron F, Rognan D, Hibert M and Bonnet D.
A step-economical multicomponent synthesis of 3D-shaped aza-diketopiperazines and their drug-like chemical space analysis.
Org. Biomol. Chem., 14, 8859-8863

171. Slynko I, Da Silva F, Bret G and Rognan D.
Docking Pose Selection by Interaction Pattern Graph Similarity: Application to the D3R Grand Challenge 2015
J. Comput.-Aided Mol Des., 30, 669-683.

170 Thomson RJ, Garg NK, Yoon TP, Hu JB, Rognan D and Gaunt MJ.
Novartis Chemistry Lectureship 2015-2016
Angew. Chem. Intl. Ed., 55, 1596

169. Boulle F, Velthuis H, Kumar N, Koedam N, Steinbusch HW, van den Hove DLA,Kenis D, Gabriel C, Mocaer E, Franc B, Rognan D, Mongeau R and Lanfumey L.
Behavioral and neurochemical characterization of TrkB-dependent mechanisms of agomelatine in glucocorticoid receptor-impaired mice.
Eur. Psychopharmacol. 26, 65-77

2015

168. Pallandre JR, Borg C, Rognan D, Boibessot T, Luzet V, Yesylevskyy S, Ramseyer C and Pudlo M.
Novel aminotetrazole derivatives as selective STAT3 non-peptide inhibitors.
Eur J Med Chem, 103, 163-174

167. Da Silva F, Desaphy J, Bret G and Rognan D.
IChemPIC: A random forest classifier of biological and crystallographic protein-protein interfaces.
J Chem Inf Model, 55, 2005-2014

166. Garcia-Perez J, Staropoli I, Azoulay S, Heinrich JT, Cascajero A, Colin P, Lortat-Jacob H, Arenzana-Seisdedos F, Alcami J, Kellenberger E and Lagane B.
A single-residue change in the HIV-1 V3 loop associated with maraviroc resistance impairs CCR5 binding affinity while increasing replicative capacity.
Retrovirology, 12, 50

165. Jacques SA, Kuhn I, Koniev O, Schuber F, Lund FE, Wagner A, Muller-Steffner H and Kellenberger E.
Discovery of Potent Inhibitors of Schistosoma mansoni NAD+ Catabolizing Enzyme.
J Med Chem, 58, 3582-3592

164. Sturm N, Quinn RJ and Kellenberger E.
Similarity between Flavonoid Biosynthetic Enzymes and Flavonoid Protein Targets Captured by Three-Dimensional Computing Approach.
Planta Med, 81, 467-473

163. Hoch L, Faure H, Roudaut H, Schoenfelder A, Mann A, Girard N, Bihannic L, Ayrault O, Petricci H, Taddei M, Rognan D and Ruat M.
MRT-92 inhibits hedgehog signaling by blocking overlapping binding sites in the transmembrane domain of the Smoothened receptor.
FASEB J, 29, 1817-1829

162. Hounsou C, Margathe J-F, Oueslati N, Belhocine A, Dupuis E, Mann A, Rognan D, Trinquet E, Hibert M, Pin J-P, Bonnet D and Durroux T.
Time-resolved FRET assay to investigate GPCR hetero-oligomer binding properties.
ACS Chem Biol, 10, 466-474

161. Cobret L, De Tauziat M-L, Ferent J, Traiffort E, Hénaoui I, Kellenberger E, Rognan D, Pantel J, Godin F, Bénedetti H and Morisset S.
Targeting the cis-dimerization of Lingo-1 with small molecule affects its donwstream signaling and oligodendrocyte differentation.
Br J Pharmacol, 172, 841-856

160. Desaphy J, Bret G, Rognan D and Kellenberger E.
sc-PDB: a 3D-database of druggable binding sites - 10 years on.
Nucleic Acids Res, 43, D399-D404

159. Rognan D.
Rational design of protein-protein interaction inhibitors
Med Chem Commun, 6, 51-60

2014

158. Rognan D and Bonnet P.
Les chimiotheques et le criblage virtuel
Medecine Sciences, 30, 1142-1160

157. Gabel J, Desaphy J and Rognan D.
Beware of machine learning-based scoring functions - On the danger of developing black boxes.
J Chem Inf Model, 54, 2807-2815

156. Rognan D and Varnek A.
A summer school for structuring the chemoinformatics community.
Mol Inf, 33, 390

155. Horvath D, Lisurek M, Rupp B, Kuhne R, Specker E, von Kries J, Rognan D, Andersson CD, Almqvist F, Elofsson M, Enqvist PA, Gustavsson AL, Remez N, Mestres J, Marcou G, Varnek A, Hibert M, Quintana J, Frank R.
Design of a General-Purpose European Compound Screening Library for EU-OPENSCREEN.
ChemMedChem, 9, 2309-2326

154. Desaphy J, and Rognan, D.
sc-PDB-Frag: a database of protein-ligand interaction patterns for bioisosteric replacements.
J Chem Inf Model, 54, 1908-1918

153. Ray, AM, Schaffner F, Janouskova H, Noulet F, Rognan D, Lelong-Rebel I, Choulier L, Blandin AF, Lehmann M, Martin S, Neubauer S, Rechenmacher F, Kessler H and Dontenwill M.
Single cell tracking assay reveals an opposite effect of selective small non-peptidic a5ß or avß/ß integrin antagonists in U87MG glioma cells
Biochim Biophys Acta., 1840, 2978-2987

152. Kuhn I, Kellenberger E, Cakir-Kiefer C, Muller-Steffner and Schuber F.
Probing the catalytic mechanism of bovine CD38/NAD+glycohydrolase by site directed mutagenesis of key active site residues.
Biochim Biophys Acta., 1844, 1317-1331
151. Ruat M, Hoch L, Faure H and Rognan D.
Targeting Smoothened for therapeutic gain
Trends Pharm Sci, i35, 237-246
150. Noel S, Hoegy F, Rivault F, Rognan D, Schalk IJJ and Mislin GL.
Synthesis and biological properties of thiazole-analogues of pyochelin, a siderophore of Pseudomonas aeruginosa.
Bioorg Med Chem Lett., 24, 132-135.

2013

149. Rousseau A, McEwen AG, Poussin-Courmontagne P, Rognan D, Nominé, Rio MC, Tomasetto C, Alpy F.
TRAF4 is a novel phosphoinositide-binding protein modulating tight junctions and favoring cell migration.
PLOS Biol, 11, e1001726
148. Ruat M, Hoch L, Faure H and Rognan D.
Structure of the Smoothened receptor.
Med Sci (Paris)., 29,855-860.
147. Lagane B and Kellenberger E.
Modeling the allosteric modulation of CCR5 function by Maraviroc.
Drug Discov Today Technol, 10, e297-e305
146. Kuhn I, Kellenberger E, Schuber F and Muller-Steffner H
Schistosoma mansoni NAD(+) catabolizing enzyme: identification of key residues in catalysis.
Biochim Biophys Acta., 1834, 2520-2527
145. Meslamani J, Bhajun R, Martz F and Rognan D.
Computational Profiling of Bioactive Compounds Using a Target-Dependent Composite Workflow.
J Chem Info Model, 53, 2322-2333
144. Daval SB, Kellenberger E, Bonnet D, Utard V, Galzi JL and Ilien B.
Exploration of the Orthosteric/Allosteric Interface in Human M1 Muscarinic Receptors by Bitopic Fluorescent Ligands
Mol Pharmacol, 84, 71-85
143. Chupakhin V., Marcou G., Baskin I., Varnek A. and Rognan D.
Predicting binding modes from neural networks trained on protein-ligand interaction fingerprints
J Chem Inf Model, 53, 763-772
142. Desaphy J., Ducrot P., Raimbaud E. and Rognan D.
Encoding protein-ligand interaction patterns in fingerprints and graphs.
J Chem Inf Model, 53, 623-637
141. Guillemet E., Tran S-L., Cadot C., Rognan D., Lereclus D. and Ramaro N.
Glucose 6P binds and activates HlyIIR to repress Bacillus cereus haemolysin hlyII gene expression.
PLOS One, 8, e55085
140. Rognan D.
Proteome-scale docking: myth and reality
Drug Discovery Today Technol, 10, e403-e409

2012

139. Loison S, Cottet M, Orcel H, Adihou H, Rahmeh R, Lamarque L, Trinquet E, Kellenberger E, Hibert M, Durroux T, Mouillac B and Bonnet D.
Modeling the allosteric modulation of CCR5 function by Maraviroc.
J Med Chem, 55, 8588-8602

138. Lagane B., Garcia-Perez B. and Kellenberger E.
Modeling the allosteric modulation of CCR5 function by Maraviroc.
Drug Discovery Today: Technologies, in press
137. Sturm N., Desaphy J., Queen R-J., Rognan D. and Kellenberger E.
Structural Insights into the Molecular Basis of the Ligand Promiscuity.
J Chem Inf Model, 52, 2410–2421
136. Desaphy J., Azdimousa K., Kellenberger E. and Rognan D.
Comparison and druggability prediction of protein-ligand binding sites from pharmacophore-annotated cavity shapes.
J Chem Inf Model, 52, 2287–2299
135. Rognan D.
Computational approaches to target fishing and ligand profiling.
AIP Conf Proc, 1456, 157-164
134. Daval SB, Valant C, Bonnet D, Kellenberger E, Hibert M, Galzi JL, Ilien B.
Fluorescent derivatives of AC-42 to probe bitopic orthosteric/allosteric binding mechanisms on muscarinic M1 receptors.
J Med Chem,55(5),2125-43
133. Egea PF, Muller-Steffner H, Kuhn I, Cakir-Kiefer C, Oppenheimer NJ, Stroud RM, Kellenberger E, Schuber F.
Insights into the Mechanism of Bovine CD38/NAD+Glycohydrolase from the X-Ray Structures of Its Michaelis Complex and Covalently-Trapped Intermediates.
PLOS One,7(4): e34918
132. Meslamani J., Li J., Sutter J., Stevens A., Bertrand H-O, Rognan D.
Protein–Ligand-Based Pharmacophores: Generation and Utility Assessment in Computational Ligand Profiling
J Chem Inf Model, 52, 943–955

2011

131. Ayrolles-Torro A, Imberdis T, Torrent J, Toupet K, Baskakov IV, Poncet-Montange G, Giacue;goire C, Roquet-Baneres F, Lehmann S, Rognan D, Pugnière M, Verdier JM, Perrier V.
Oligomeric-induced activity by thienyl pyrimidine compounds traps prion infectivity.
J neurosci, 31, 14882-14892.

130. Noël S, Gasser V, Pesset B, Hoegy F, Rognan D, Schalk IJ, Mislin GLA.
Synthesis and biological properties of conjugates between fluoroquinolones and a N3"-functionalized pyochelin.
Org Biomol Chem, 9, 8288-8300

129. de Graaf C, Rein C, Piwnica D, Giordanetto F, Rognan D.
Structure-based discovery of allosteric modulators of two related class B G-protein-coupled receptors.
ChemMedChem, 6, 2159-2169

128. Brillet K, Reimmann C, Mislin GLA, Noël S, Rognan D, Schalk IJ, Cobessi D.
Pyochelin enantiomers and their outer-membrane siderophore transporters in fluorescent pseudomonads: Structural bases for unique enantiospecific recognition.
J Am Chem Soc, 133, 16503-16509
127. De Wachter R, de Graaf C, Keresztes A, Vandormael B, Ballet S, Toth G, Rognan D, Tourwé D.
Synthesis, biological evaluation and automated docking of constrained analogues of the opioid peptide H-Dmt-D-Ala-Phe-Gly-NH2 using the 4- or 5-methyl substituted 4-amino-1,2,4,5-tetrahydro-2 benzazepin-3-one scaffold
J Med Chem, 54, 6538-6547
126. Garcia-Perez J, Rueda P, Alcami J, Rognan D, Arenzana-Seisdedos F, Lagane B, Kellenberger E.
Allosteric model of maraviroc binding to CC chemokine receptor 5 (CCR5).
J Biol Chem, 286, 33409-33421
125. Kellenberger E, Hofmann A and Quinn R.J.
Similar interactions of natural products with biosynthetic enzymes and therapeutic targets could explain why nature produces such a large proportion of existing drugs.
Nat Prod Rep, 28, 1483-1492
124. Kellenberger E, Kuhn I, Schuber F and Muller-Steffner H.
Flavonoids as inhibitors of human CD38.
Bioorg & Med Chem Letters, 21(13), 3939-3942
123. Weill N, Valencia C, Gioria S, Villa P, Hibert M and Rognan D.
Identification of Nonpeptide Oxytocin Receptor Ligands by Receptor-Ligand Fingerprint Similarity Search.
Mol Info, 30, 521-526
122. van Loenen PB, de Graaf C, Verzijl D, Leurs R, Rognan D, Peters SL, Alewijnse AE.
Agonist-dependent effects of mutations in the sphingosine-1-phosphate type 1 receptor.
Eur J Pharmacol,667, 105-112

121. Meslamani J., Rognan D.
Enhancing the Accuracy of Chemogenomic Models with a Three-Dimensional Binding Site Kernel.
J Chem Inf Model, 51(7),1593–1603
120. Garcia-Perez J., Rueda P., Staropoli I., Kellenberger E., Alcami J., Arenzana-Seisdedos F. and Lagane B.
New Insights into the Mechanisms whereby Low Molecular Weight CCR5 Ligands Inhibit HIV-1 Infection.
J Biol Chem, 286, 4978-4990
119. Cazorla M., Prémont J., Mann A., Girard N., Kellendonk C. and Rognan D.
Identification of a low–molecular weight TrkB antagonist with anxiolytic and antidepressant activity in mice.
J Clin Invest, 121, 1846-1857
118. Meslamani J., Rognan D. and Kellenberger E.
sc-PDB: a database for identifying variations and multiplicity of “druggable” binding sites in proteins.
Bioinformatics, 27(9), 1324-1326

2010

117. Kuhn I. ,Kellenberger E. ,Said-Hassane F. ,Villa P. ,Rognan D. ,Lobstein A. ,Haiech J. ,Hibert M. ,Schuber F. ,Muller-Steffner H.
Identification by high-throughput screening of inhibitors of Schistosoma mansoni NAD+ catabolizing enzyme.
Bioorg Med Chem,18(22),p7900-10
117. Defranchi E, Schalon C, Messa M, Onofri F, Benfenati F, and Rognan D. (2010)
Binding of Protein Kinase Inhibitors to Synapsin I Inferred from Pair-Wise Binding Site Similarity Measurements.
PLoS ONE, 5 (8),e12214
117. Rognan D. (2010)
Structure-Based Approaches to Target Fishing and Ligand Profiling.
Molecular Informatics, 29 (3),176-187
116. Weill, N. and Rognan, D. (2010)
Alignment-free ultra high throughput comparison of druggable protein-ligand binding sites.
J. Chem. Inf. Model., 50 (1), 123–135
115. Chalopin, M., Tesse, A., Martinez, M.C., Rognan, D., Arnal, J.-F. And Andriantsitohaina, R. (2010).
Estrogen receptor alpha as a key target of red wine polyphenols action on the endothelium.
PLOS One, 5, e8554

2009

114. Faure, H., Gorojankina, T., Rice, N., dauban, P., Dodd, R.H., Bräer-Osborne, H., Rognan, D. and Ruat, M. (2009)
Molecular determinants of non-competitive antagonist binding to the mouse GPRC6A receptor.
Cell Calcium, 46, 323-332.
113. de Graaf, C. and Rognan, D. (2009)
Customizing G Protein-Coupled receptor models for structure-based virtual screening.
Curr. Pharm. Des, 15, 4026-4048.
112. Shamovsky, I., de Graaf, C., Alderin, L., Bengtsson, M., Bladh, A., Bösson, L., Connolly, S., Johansson, H., Josefsson, B.-G. Kristoffersson, A., Linnanen, T., Lisius, A., Mannikko, R., Nordé B., Ripa, L., Rognan, D., Rosendah, A., Skrinjar,M. and Urbahns, K. (2009)
Increasing selectivity of CCR8 antagonists by engineering direct interactions with the intended and off-target binding sites.
J. Med. Chem, 52, 7706-7723.
111. Hoegy, F., Lee, X., Noel, S., Rognan, D., Mislin, G.A., Reimann, C. and Schalk, I.J. (2009)
Stereospecificity of the siderophore pyochelin outer membrane transporters in fluorescent pseudomonads.
J. Biol. Chem., 280, 14949-14957.
110. Guichard, G.; Lena, G.; Boeglin, J.; Muller, P.; Boilard, E.; Lambeau, G.; Rognan, D. and Didierjean, C. (2009)
1,3,5-Triazepan-2,6-diones as conformationally constrained dipeptide mimetics. In silico guided identification of sPLA2 inhibitors.
Adv. Exp. Med. Biol., 611, 201-202
109. Weill, N. and Rognan, D. (2009)
Development and validation of a novel Protein-Ligand Fingerprint to mine chemogenomic space: Application to G Protein-coupled receptors and their ligands.
J. Chem. Info. Model., 49, 1049-1062
108. Ballet, S.; Feytens, D.; De Wachter, R.; De Vlaminck, M.; Marczak, E.D.; Salvadori, S.; de Graaf, C.; Rognan, D.; Negri, L.; Lattanzi, R.; Lazarus, L.H.; Tourwe, D. and Balboni, G. (2009)
Conformationally-constrained opioid ligands: The Dmt-Aba and Dmt-Aia versus Dmt-Tic scaffold
Bioorg. Med. Chem. Lett., 19, 433-337

2008

106. de Graaf, C. and Rognan, D. (2008)
Selective structure-based virtual screening for full and partial agonists of the beta2 adrenergic receptor
J. Med. Chem., 51 ,4978-4985

 Erratum
107. Kellenberger, E.; Schalon, C. and Rognan, D. (2008)
How to measure the similarity between protein-ligand binding sites
Curr. Comput.-Aided , 4 ,209-220
105. Jimenez, M.; Andre, S.; Barillari, C.; Romero, A.; Rognan, D.; Gabius, H.J. and Solis, D. (2008)
Domain versatility in plant AB-toxins: mapping the 2gamma lectin site of the mistletoe toxin/agglutinin at physiological pH by ligand derivatives and modeling
FEBS Lett., 582 ,2309-2312
104. Barillari, C.; MLarcou, G. and Rognan, D. (2008)
Hot spots-guided receptor-based pharmacophores (HS-Pharm): a knowledge-based approach to identify ligand-anchoring atoms in protein caviities and prioritize structure-based pharmacophores
J. Chem. Info. Model., 48, 1396-1410
103. Kellenberger, E.; Foata, N. and Rognan, D. (2008)
Ranking targets in structure-based virtual screening of 3-D protein libraries: Methods and problems
J. Chem. Info. Model., 48, 1014-1025
102. Schalon, C.; Surgand, J.S. and Rognan, D. (2008)
A simple and fuzzy method to align and compare druggable protein binding sites
Proteins, 71, 1755-1778
101. de Graaf, C.; Foata, N.; Engkvist, O. and Rognan, D. (2008)
Molecular modelling of the second extracellular loop of G Protein-coupled receptors and its implication on structure-based virtual screening
Proteins, 71, 599-620

2007

100. Rognan, D. (2007)
Chemogenomic approaches to rational drug design
Br. J. Pharmacol., 152, 38-52
99. Rognan, D.
Criblage virtuel par docking moleculaire en Chemogenmique, des petites molecules pour explorer le vivant, Edition EDP Sciences, Collection Genoble Sciences, ISBN 978 2 7598 0005 6
98. Zoffmann, S.; Bertand, S.; Do, Q.T.; Bertrand, D.; Rognan, D.; Hibert, M. and Galzi, J.L. (2007)
Topological analysis of the complex formed between NKA and the NK2 tachykinin receptor by FRET
J. Neurochem., 101,506-512
97. Kemper, A.; Rognan, D. and Lengauer, T. (2007)
Lead identification y virtual screening
in Bioinformatics: From genomes to drugs, T. Lengauer ed., Wiley-VCH,pp.651-704

95. Rodrigo, J.; Pena, A.; Murat, B.; Trueba, M.; Durroux, T.; Guillon, G. and Rognan, D. (2007)
Mapping the Binding Site of Arginine Vasopressin to V1a and V1b Vasopressin Receptors
Mol. Endocrinol., 21(2),512-523
94. Marcou, G. and Rognan, D. (2007)
Optimizing Fragment and Scaffold Docking by Use of Molecular Interaction Fingerprints
J. Chem. Inf. Model., 47, 195-207

2006

93. Muller, P.; Lena, G.; Boilard, E.; Bezzine, S.; Lambeau, G.; Guichard, G. and Rognan, D. (2006)
In Silico-Guided Target Identification of a Scaffold-Focused Library:
1,3,5-Triazepan-2,6-diones as Novel Phospholipase A2 Inhibitors
J. MEd. Chem., 49, 6768-6778
92. Gerber, S.; Krasky, A.; Rohwer, A.; Lindauer, S.; Closs, H.; Rognan, D.; Gunkel, N.; Selzer, P. M. and Wolf, C. (2006)
Identification and characterisation of the dopamine receptor II from the cat flea Ctenocephalides felis (CfDopRII)
Insect Biochemistry and Molecular Biology, 36, 749-758
91. Kuhn, I.; Kellenberger, E.; Rognan, D.; Lund, F. E.; Muller-Steffner, H. and Schuber, F. (2006)
Redesign of Schistosoma mansoni NAD+ Catabolizing Enzyme: Active Site H103W
Mutation Restores ADP-Ribosyl Cyclase Activity
Biochemistry, 45, 11867-11878
90. Kessler, A.; Faure, H.; Petrel, C.; Rognan, D.; Césario, M.; Ruat, M.; Dauban, P. and Dodd, R.H. (2006)
N1-Benzoyl-N2-[1-(1-naphthyl)ethyl]-1,2-diaminocyclohexanes : Development of Calhex 231 as a New Calcium Sensing Receptor (CaSR) Ligand Demonstrating Potent Calcilytic Activity
J. Med. Chem., 49, 5119-5128
89. Saparpakorn, P.; Hannongbua, S. and Rognan D. (2006)
Design of nevirapine derivatives insensitive to the K103N and Y181C HIV-1 reverse transcriptase mutantsdagger.
SAR QSAR Environ Res. 2, 183-194.
88. Mislin, G.; Hoegy, F.; Cobessi, D.; Poole, K.; Rognan, D. and Schalk, I. (2006)
The structure-activity relationship of pyochelin and analogues to FptA in Pseudomonas aeruginosa.
J. Mol. Biol., 357, 1437-1448
87. Rognan, D. (2006)
Development and virtual screening of target libraries.
J. Physiol. Paris, 99, 232-244.
86. Krier M., Bret, G. and Rognan, D. (2006)
Assessing the scaffold diversity of commercially available screening collections.
J. Chem. Inf. Model., 46, 512-524
85. Kellenberger, E., Müller, P., Schalon
sc-PDB: An annotated database of druggable binding sites from the Protein Data Bank.
J. Chem. Inf. Model., 46, 717-727
84. Rognan, D. (2005)
BioinfoDB: un inventaire de molécules commercialement disponibles à des fins de criblage biologique.
La Gazette du CINES, Déc. 2005, 1-4.
83. Rognan, D. ed. (2006)
Ligand design for G Protein-coupled Receptors.
Wiley-VCH Verlag GmbH & Co, KGA (ISBN 3-257-21284-6)
82. Rognan, D. (2006)
In silico screening of the protein structure repertoire and of protein families (2005) In Chemogenomics : An emerging strategy for rapid target and drug discovery.
E. Jacoby, ed., Imperial College Press, pp.109-132

81. Surgand, J.-S.; Rodrigo, J.; Kellenberger, E. and Rognan, D. (2006)
A chemogenomic analysis of the transmembrane binding cavity of human G-protein-coupled receptors.
Proteins: Struct., Fonct., and Bioinf., 62(2): 509-538
80. Mourot, A.; Rodrigo, J.; Kotzyba-Hibert, F.; Bertrand, S.; Bertrand, D.; Goeldner M. (2006)
Probing the reorganization of the nicotinic acetylcholine receptor during desensitization by time-resolved covalent labeling using [3H]AC5, a photoactivatable agonist.
Mol Pharmacol., 69, 452-461.

2005

79. Silve, C.; Petrel, C.; Leroy, C.; Buel, H.; Mallet, R.; Rognan, D. and Ruat, M. (2005)
Delineating the Ca2+ binding pocket within the venus fly trap module of the human calcium sensing receptor.
J. Biol. Chem., 280, 37917-37923
78. Krier, M.; de Arujo-Junior, J. X.; Schmitt, M.; Duranton, J.; Justioano-Barasan, H.; Lugnier, C.; Bourguignon, J.-J.; Rognan, D.(2005)
Design of small-sized libraries by combinatorial assembly of linkers and functional groups to a given scaffold: Application to the structure-based optimization of a phosphodiesterase 4 inhibitor.
J. Med. Chem.; 48; 3816-3822.
77. Violette, A.; Averlant-Petit, M. C.; Semetey, V.; Hemmerlin, C.; Casimir, R.; Graff, R.; Marraud, M.; Briand, J.-P.; Rognan, D.; Guichard, G. (2005)
N-N'-Linked Oligoureas as Foldamers: Chain Lenght Requirements for Helix Formation in Protic Solvent Investigated by Circular Dichroism, NMR Spectroscopy, and Molecular Dynamics
J. Am. Chem. Soc.; 127; 2156-2164.
76. Morris, M.-A.; Caron, A. Z.; Guillemette, G.; Rognan, D.; Schmitt, M.; Schlewer, G. (2005)
Synthesis of -2-O-[4'-(N-9"-Purinyl)butyl] myo-Inositol 1,4,5-Tris(phosphate), a potent full agonist at the D-myo-Inositol 1,4,5-Tris(phosphate) Receptor
J. Med. Chem; 48; 1251-1255.

2004

75. Voisin, S.; Rognan, D.; Gros, C.; Ouimet, T. (2004)
A Three-dimensional model of the Neprelysin 2 Active Site Based on the X-ray Structure of Neprelysin. Identification of residues involved in substrate hydrolysis and inhibitor binding of neprelysin 2
J. Biol. Chem; 279(44); 46172-47181.
74. Stote, R. H.; Kellenberger, E.; Muller, H.; Bombarda, E.; Roques, B. P.; Kieffer, B.; Mely, Y. (2004)
Structure of the His44 Ala Single Point Mutant of the Distal Finger Motif of HIV-1 Nucleocapsid Protein: A Combined NMR, Molecular Dynamics Simulation, and Fluorescence Study
Biochemistry; 43(24); 7687-7697.
73. Traiffort, E., Dubourg, C., Faure, H., Rognan, D., Odent, S., Durou, M.R., David, V. and Ruat, M. (2004)
Design and synthesis of fluorescent ligands for FRET experiments with an EGFP-dopamine D3 receptor chimera.
J. Biol. Chem., 279, 42889-42897
72. Derrick, S., Pena, A., Wagon, J., Serraideil- Le Gal, C., Durroux, T., Hibert, M., Rognan, C. and Guillon, G. (2004)
Key amino acids located in transmembrane domains V and VII account for the pharmacological specificity of the human V1b vasopressin receptor.
Mol Endocrinol., 18, 2777-2789.

  
71. Petrel, C., Kessler, A., Dauban, P., Dodd, R. H., Rognan, D. and Ruat, M. (2004)
Positive and negative allosteric modulators of the Ca2+ sensing receptor interact within overlapping but not identical binding sites in the transmembrane domain.
J. Biol. Chem., 279, 18990-18997
70. Bissantz, C., Logean, A., Rognan, D. (2004)
High-throughput modeling of human G-Protein coupled receptors: Amino acid sequence alignment, three-dimensional model building, and receptor library screening.
J. Chem. Inf. Comput. Sys., 44,1162-1176.
69. Hibert, M., Barberis, C., Galzi J.L., Haiech J., Ilien B., Klotz P., Mouillac B., Parrot I., Rognan D., Tahtaoui C., Thomas C (2004)
Post-genomic medicinal chemistry.
Act. Chim. Thér., 30eème série, 15-24.

  
68. Rognan, D. (2004)
Synergistic use of chemical databases and target libraries in the context of high-throughput virtual screening.
Act. Chim. Thér., 2004, 30e seérie, 113-130.

  
67. Kellenberger, E., Rodrigo, J., Müller, P. and Rognan, D. (2004)
Comparative evaluation of eight docking tools for docking and virtual screening accuracy.
Proteins, 57, 225-242.
66. Paul, N., Bret, G., Kellenberger, E., Müller, P., Rognan, D. (2004)
Recovering the true targets of selective ligands by virtual screening of the Protein Data Bank.
Proteins, 54, 671-680.

2003

65. Petrel, C., Kessler, A., Dauban, P., Dodd, R., Maslah, F., Rognan, D. and Ruat, M. (2003)
Modeling and mutagenesis of the allosteric binding site of Calhex 231, a novel negative allosteric modulator of the extracellular Ca2+ sensing receptor
J. Biol. Chem., 278, 49487-49494.
64. Tahtaoui, C., Balestre, M.N., Klotz, P., Rognan, D., Barberis, C., Mouillac, B. and Hibert, M. (2003)
Identification of the binding sites of the SR49059 nonpeptide antagonist into the V1a vasopressin receptor using sulfydryl-reactive ligands and cysteine mutants as chemical sensors.
J. Biol. Chem., 278, 40010-40019
63. Rognan D. (2003)
Application of three-dimensional (3D) models of G protein-coupled receptors (GPCRs) to drug discovery.
Curr. Opin. Drug. Discov. Devel. ,6,434.
62. Höltje, H..D., Sippl, W., Rognan, D., Folkers, G. (2003)
Molecular Modeling. Basic principles and applications. 2nd Edition.
Wiley-VCH GmbH & Co. KgaA, Wenheim.

  
61. Bissantz, C., Bernard, P., Hibert, M. and Rognan, D. (2003)
Protein-based virtual screening of chemical databases. 2. Are homology models of G-Protein coupled receptors suitable targets?
Proteins, 50, 5-25.
60. Kratz, F., Warnecke, A., Scheuermann, K, Stockmar, C., Schwab, J., Lazar, P., Drà¼ckes, P., Esser, N., Drevs, J., Rognan, D., Bissantz, C., Hinderling, C., Folkers, G., Fichtner, I., and Unger, C. (2002)
Probing the Cysteine-34 Position of Endogenous Serum Albumin with Thiol-binding Doxorubicin Derivatives: Improved Efficacy of an Acid-sensitive Doxorubicin Derivative with Specific Albumin-binding Properties Compared to the Parent Compound. J. Med.
Chem., 45, 5523-5533.

2002

59. Hemmerlin, C., Marraud, M., Rognan, D., Graff, R., Semetey, V., Briand, J.-P. and Guichard, G. (2002)
Helix-Forming Oligoureas: Temperature Dependent NMR, Structure Determination and Circular Dichroism of a Nonamer with Functionalized Side Chains.
Helvetica Chimica Acta., 11, 3692-3711.

  
58. Ramos, M., Alvarez, I., Sesma, L., Logean, A., Rognan, D., Lopez De Castro, J.A. (2002)
Molecular mimicry of an HLA-B27-derived ligand of arthritis-linked subtypes with chlamydial proteins.
J. Biol. Chem., 277, 37573-37581.
57. Logean, A. and Rognan, D. (2002)
Recovery of known T-cell epitopes by computational scanning of a viral genome.
J. Comput.-Aided Mol. Design, 16, 229-243.
56. Semetey, V., Rognan, D., Hemmerlin, C., Graff, R., Briand, J.P., Marraud, M. and Guichard, G. (2002)
Stable helical secondary structure in short chain N,N-linked oligoureas bearing proteinogenic side chains.
Angew. Chem., 41, 1893-1895.
55. Paul, N. and Rognan, D. (2002)
ConsDock: a new program for the consensus analysis of protein-ligand interactions.
Proteins, 47, 521-533.

2001

54. Demuth, C., Zerbe, O., Rognna, D., Söll, R., Beck-Sickinger, A., Folkers, G. and Spichiger, U.E. (2001)
A rationally designed oligopeptide show significant conformational changes upon binding to sulphate ions.
Bios. Bioelel., 16, 783-789.
53. Dédier, S., Reinelt, S., Rion,S. , Folkers, G., and Rognan, D. (2001)
Use of fluorescence polarization to monitor MHC-peptide interactions in solution.
J. Immunol. Methods., 255, 57-66.
52. Reinelt, S., Marti, M., Dédier, S., Reitinger, T., Folkers, G., Lopez de Castro, J.A. and Rognan, D. (2001)
?-amino acid scan of a class I MHC-restricted alloreactive T-cell epitope.
J. Biol.Chem., 276, 24525-24530.
51. Reinelt, S., Dédier, S., Asuni, G., Folkers, G. and Rognan, D. (2001)
Mutation of Cys67 alters the thermodynamic stability of the human leukocyte antigen HLA-B*2705.
J. Biol. Chem., 276, 18472-18477
50. Logean, A., Sette, A. and Rognan, D. (2001)
Customized Versus Universal Scoring Functions: Application to class I MHC-peptide binding free energy predictions.
Bioorg. Med. Chem. Lett.,11, 675-679.
49. Rognan,D. , Mukhija, S., Folkers, G. and Zerbe, O. (2001)
NMR-restrained docking of a peptidic inhibitor to the N-terminal domain of the phosphoenolpyruvate:sugar phosphotransferase enzyme I.
J. Comput.-Aided Mol. Design , 15, 103-115.

2000

48. Bissantz, C., Folkers, G. and Rognan, D. (2000)
Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations.
J. Med. Chem., 43, 4759-4767.
47. Rognan, D., Bissantz, C., Dédier, S., Logean, A. and Reinelt, S. (2000)
Synergistic use of virtual screening and biophysical methods for the protein-based design of peptidomimetics.
Chimia, 54, 658-662.

  
46. Dédier, S., Reinelt, S., Reitinger, T. , Folkers, G. and Rognan, D. (2000)
Thermodynamic Stability of HLA-B*2705/Peptide Complexes: Effect of Peptide and MHC Protein mutations.
J. Biol. Chem., 275, 27055-27061.
45. Yagà¼e, J., Alvarez, I., Rognan, D., Ramos, M., Vasquez, J and Là³pez de Castro, J.A. (2000)
An N-acetylated natural ligand of HLA-B39: classical class I MHC proteins bind peptides with blocked N-terminus in vivo.
J. Exp. Med., 191, 2083-2092.v
44. Garcà­a-Peydrà³, M., Rognan, D. and Là³pez de Castro, J.A. (2000)
Limited plasticity in the recognition of peptide epitope variants by alloreactive CTL correlates directly with conservation of critical residues and inversely with peptide length.
Tissue Antigens., 55, 289-295.

  
43. Rognan, D., Stryhn, A., Fugger, L., Engberg, J., Andersen, P.S. and Buus, S. (2000)
Modelling the interaction of a peptide-major histocompatibility complex with its receptors. II. Crossreaction between a monoclonal antibody and two ?? T cell receptors.
J. Comput-Aided Mol. Design, 14, 71-82 (2000)

  
42. Rognan, D., Stryhn, A., Fugger, L., Engberg, J., Andersen, P.S. and Buus, S. (2000)
Modelling the interaction of a peptide-major histocompatibility complex with its receptors. I. Recognition by two ?? T cell receptors.
J. Comput-Aided Mol. Design, 14, 53-69 (2000).

  

1999

41. Rognan D., Lauemà¸ller, S.L., Holm, A., Buus, S. and Tschinke, V. (1999)
Predicting binding affinities of protein ligands from three-dimensional coordinates: Application to peptide binding to class I major histocompatibility proteins.
J. Med. Chem., 42, 4650-4658.
40. Krebs, S., Rognan, D. and Là³pez de Castro, J.A. (1999)
Long-range effects in protein-ligand interactions. Effect of HLA-B27 polymorphism on antigen presentation.
Protein Science, 8, 1393-1399.
39. Poenaru, S., Lamas, J.R., Folkers, G., Là³pez de Castro, J.A., Seebach, D. and Rognan, D. (1999)
Nonapeptide analogues containing ?-Homoalanine oligomers: Synthesis and binding affinity to a class I MHC Protein.
J. Med. Chem., 13, 2318-2331.
38. Dédier, S., Krebs, S., Lamas, J.R., Poenaru, S., Folkers, G., Lopez de Castro, J.A., Seebach, D. and Rognan, D. (1999)
Structure-based design of nonnatural ligands for the HLA-B27 protein.
J. Receptor & Signal. Transd. Res., 19, 645-657.

  

1998

37. Paradela, A., Garcia-Peydro, M., Và¡squez, J., Rognan, D. and Là³pez de Castro, J.A. (1998)
The same natural ligand is involved in allorecognition of multiple HLA-B27 subtypes by a single T-cell clone: Role of peptide and the MHC molecule in alloreactivity.
J. Immunol., 161, 5481-5490.
36. Krebs, S. and Rognan, D. (1998)
From peptides to peptidomimetics- Design of nonpeptide ligands for major histocompatibility proteins.
Pharma. Helv. Acta., 73, 173-181.

  
35. Forstner, M., Müller, A., Rognan, D., Kriechbaum, M. and Wallimann, T. (1998)
Mutation of cis-proline 207 in mitochondrial creatine kinase to alanine leads to increased acid stability.
Prot. Eng., 11, 563-568.
34. Seebach, D., Poenaru, S., Folkers, G. and Rognan, D., (1998) Synthesis of Oligo(3-hydroxybutanoate)(OHB) containing peptides with high binding affinity to a class I MHC protein.
Helv. Chim. Acta. 81, 1181-1200.

  
33. Krebs, S., Poenaru, S., Lamas, J.R., Là³pez de Castro, J.A., Seebach, D., Folkers, G. and Rognan, D. (1998)
Substituting organic spacers for the T-cell receptor binding part of class I MHC-restricted peptides.
J. Biol. Chem. 273, 19072-19079.
32. Krebs, S. , Folkers, G. and Rognan, D. (1998)
Binding of rationally-designed non-natural peptides to the human leukocyte antigen HLA-B*2705.
J. Pept. Sci., 4,378-388.
31. Rognan, D. (1998)
Molecular Dynamics Simulations: A Tool for Drug Design.
Perspectives in Drug Discovery and Design 9/10/11, 181-209.
30. Garcà­a, F., Rognan, D., Marina, A. and Là³pez de Castro, J.A. (1998)
An HLA-B27 polymorphism (B*2710) that is critical for T-cell recognition has limited effets on peptide specificity.
Tissue Antigens, 51,1-9.

1997

29. Rognan, D. (1997)
Molecular Dynamics Simulations: A Tool for Drug Design.
In, 3D QSAR in Drug design: Vol. II. Ligand-Protein Interactions and Molecular Similarity, H. Kubinyi, G. Folkers, Y.C. Martin, Eds., Kluwer Academic Publishers, Dordrecht, The Netherlands, pp 181-209.
28. Rognan, D., Krebs, S., Kuonen, O., Lamas, J.R., Là³pez de Castro, J.A. and Folkers, G. (1997)
Fine specificity of antigen binding to two class I major histocompatibility proteins (B*2705 and B*2703) differing in a single amino acid residue.
J. Comput-Aided Mol. Design 11, 463-478
27. Lang, V.B., Langguth, P., Ottiger, C., Wunderli-Allenspach, H., Rognan, D., Rothenrutishauser, B., Perriard, J.C., Lang, S., Biber, J. and Merkle, H.P. (1997)
Stucture-permeation relations of Met-Enkephalin peptide analogues on absorbtion and secretion mechanisms in caco-2 monolayers.
J. Pharm. Sci. 86, 846-853.
26. Rognan, D. (1997)
AS and immunotherapy: future considerations, in HLA-B27 in the developement of spondyloarthropathies, C. Lopez-Larrea ed. , R.G. Lands. Co.
Georgetwon, USA., pp.325-241.

1996

25. Kern, P., Brunne, R. Rognan, D. and Folkers, G. (1996)
A pseudo-particle approach for studying protein-ligand models truncated to their active sites.
Biopolymers, 38, 619-637

1995-1987

24. Kern, P., Rognan, D. and Folkers, G. (1995)
MD simulations in pseudo-particle fluids: Applications to active-site protein complexes.
Quant.Struct.Act.Relat.14, 229-241.
23. Scapozza, L., Rognan, D., Folkers, G. and Daser, A. (1995)
Molecular dynamics and structure-based drug design for predicting nonnatural nonapeptide binding to a class I MHC protein.
Acta. Cryst. D51, 541-549.
22. Rognan, D., Scapozza, L., Folkers, G. and Daser, A. (1995)
Rational design of class I MHC ligands, in AIP Conference Proceedings 330, (F. Bernardi, J.L. Rivail, eds.)
AIP Press, New-York, pp. 367-375.
21. Rognan, D., Scapozza, L., Folkers, G. and Daser A. (1995)
Rational design of nonnatural peptides as high affinity ligands for the HLA-B*2705 human leukocyte antigen Proct.
Natl. Acad. Sci. U.S.A. 92, 753-757.
20. Rognan, D., Scappozza, L., Folkers, G. and Daser, A. (1994)
Molecular dynamics simulation of MHC-peptide complexes as a tool for predicting T cell epitopes.
Biochemistry 33, 11476-11485.
19. Thibaut, U., Folkers, G., Klebe, G.,Kubinyi, H., Merz, A. and Rognan, D. (1994)
Recommendations for CoMFA studies and 3D-QSAR publications.
Quant.Struct.Act.Relat. 13, 1-3.
18. Folkers, G. and Rognan, D. (1993)
Prediction of an influenza virus derived nonapeptide-MHC interaction confirmed by crystal structure, in Molecular modeling in the discovery of new drugs.
ACS satellite television seminars, March 16, pp31-36.
17. Rognan, D. und Folkers, G. (1992)
Antigene Erkennung von viralen Peptiden.
Deutsche Apotheker Zeitung 28, 26-28.
16. Folkers, G., Rognan, D. and Merz, A. (1993)
Scope and limitations of CoMFA, in 3D QSAR in Drug Design.
Theory, Methods and Applications, (H. Kubinyi, Ed.), ESCOM Science Publishers B.V., Leiden, pp.583-618.
15. Folkers, G., Merz, A. and Rognan, D. (1992)
CoMFA as a tool for active site modelling, in Trends in QSAR and Molecular Modeling'92. (C.G. Wermuth, Ed.),
ESCOM Science Publishers B.V., Leiden, pp.223-244.
14. Rognan, D. and Folkers, G. (1992) Molecular Modelling of viral peptides bound to class I MHC proteins, in Trends in QSAR and Molecular Modeling 92 (C.G. Wermuth, Ed.),
ESCOM Science Publishers B.V., Leiden, pp.186-192.
13. Rognan, D., Zimmermann, N., Jung, G. and Folkers, G. (1992)
Molecular dynamics study of the complex between the human histocompatibility antigen HLA-A2 and the IMP58-66 nonapeptide from Influenza virus matrix protein.
Eur. J. Biochem. 208, 101-113.
12. Zimmermann, N., Rötzschke, O., Falk, K., Rognan, D., Folkers, G., Rammensee, H.-G. and Jung, G. (1992)
Molekà¼ldynamiksimulation fà¼r ein allelspezifisches virales Nonapeptid aus dem Influenza Matrix Protein in der Bindungstasche eines menschlischen MHC-Klasse I Proteins.
Angew. Chem. 104, 928-931, Angew. Chem. Int. Ed. Engl. 31, 886-890.

11. Rognan, D., Boulanger, T., Hoffmann, R., Vercauteren, D., Andre, J.M., Durant, F. and Wermuth, C.G. (1992)
Structure and molecular modeling of GABA-A antagonists.
J. Med. Chem. 35, 1969-1977.
10. Rognan, D., Reddehase, M.J., Koszinowski, U.H. and Folkers, G. (1992)
Molecular modeling of an antigenic complex between a viral peptide and a class I major histocompatibility glycoprotein.
Proteins: Struct., Funct., Genet. 13, 70-85.
9. Folkers, G., Rognan, D.
Computer-Aided Drug Design und Molecular Modeling.
Teil 6. (1991) GITZ Fachz. Lab. 7, 800-802.
8. Folkers, G., Rognan, D.
Computer-Aided Drug Design und Molecular Modeling.
Teil 4. (1991) GIT Fachz. Lab. 6, 673-680.
7. Folkers, G. und Rognan, D.
Computer-Aided Drug Design und Molecular Modeling.
Teil 3. (1991) GIT Fachz. Lab. 5, 477-482.
6. Folkers, G. und Rognan, D.
Computer-Aided Drug Design und Molecular Modeling.
Teil 2. (1991) GIT Fachz. Lab. 4, 329-334.
5. Folkers, G. und Rognan, D. Computer-Aided Drug Design und Molecular Modeling.
Teil 1. (1991) GIT Fachz. Lab. 3, 224-227.
4. Rognan, D., Aubry, A., Folkers, G., Boussard, G. and Marraud, M. (1990)
Intramolecular interactions in the tripeptide sequence coding for N-glycosylation: an experimental and MD theoretical approach.
in Peptides 1990 (E. Giralt and D. Andreu, eds.), ESCOM Science Publishers B.V., Leiden, pp493-494.
3. Rognan, D., Sokoloff, P., Mann, A., Martres, M.P., Schwartz, J.C., Costentin, J. and Wermuth, C.G. (1990)
Optically active sulpiride derivatives as predictive tools for mapping the dopamine D-2 receptor.
Eur. J. Pharmacol.-Mol. Pharmacol. sect. 189, 59-70.
2. Wermuth, C.G. et Rognan, D. (1987)
Modélisation d'antagonistes des récepteurs GABA-A.
Actualités de Chimie Thérapeutique 14, 215-233.
1. Rognan D, Mann A, Hamdi P, Wermuth CG, Sokoloff P, Schwartz JC, Roy J and Morgat JL.
Synthesis of S-[3H]-DO-710, a benzamide ligand of the dopamine D-2 receptor and of S-[3H]-azidosulpride, its photoactivable analog J Lab Comp Radiopharm 24,1361-1372