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Inte:Ligand GmbH
Industry Life sciences
Founded 2003
Headquarters Vienna, Austria
Area served
Key people
Thierry Langer (Founder) Gerhard Wolber (Founder) Hermann Stuppner (Founder) Sharon D. Bryant (CEO)
Products LigandScout Essential LigandScout Advanced LigandScout Expert KNIME iLib:Diverse PharmacophoreDB

Contract Research, In-Silico Library Design, Lead Optimization Support, Virtual Screening, Activity Profiling, 3D-Pharmacophore Development,

Scientific Software Development

Inte:Ligand Software Entwicklungs und Consulting GmbH supports scientists worldwide with innovative approaches for early drug discovery research by developing and applying computer-aided design (CAD) solutions. Molecular designers including chemists and modelers in the pharmaceutical, cosmetic, nutrition, animal health and crop protection life science industries use the solutions to design and identify novel bioactive molecules. Inte:Ligand develops the most innovative and user friendly modeling software platforms and provides expert consulting to inspire the innovative process of designing molecules, filtering ideas, and de-risking candidates assessed in early discovery projects.[1][1]

Inte:Ligand was founded in Maria Enzersdorf, Lower Austria (Niederösterreich) by Prof. Thierry Langer, Gerhard Wolber and Prof. Hermann Stuppner in 2003.[2] They established the company headquarters on Mariahilferstrasse in Vienna, Austria that same year. Sharon D Bryant joined the team in 2008 to leverage the company's core competencies worldwide.

In 2007 Inte:Ligand was the recipient of the NÖ Innovation prize (Innovationpreis) for the development of the simulation software LigandScout.[3][4][5][6] As of 2017 there were more than 1500 literature, book chapters and review articles published related to InteLigand software technology in the areas of virtual screening,[7][8][9] 3D-pharmacophore modeling,[10][11][12][13] hit identification,[14][15][16][17][18][19] medicinal chemistry decision support,[20][21][22] activity profiling,[23] docking, fragment-based compound design,[24] protein-protein-interactions,[25] drug-repurposing[26] and molecular dynamics simulations.[27][28][29]

Other applications include the discovery of new Myeloperoxidase ligands,[30] HIV reverse transcriptase inhibitors,[31] applications in anti-viral bio-activity profiling,[32] the development of models to predict HIV Protease activity,[33] Cytochrome P450 activity prediction ,[34] and simulation models for the activity on Factor Xa.[35]

Science and Technology[edit]

  • LigandScout Essential, is a scientific software program for de novo molecule design, to derive structure-baed and ligand-based 3D pharmacophores, perform molecular 3D alignments, 3D pharmacophore modeling, virtual screening, create multi-conformational compound libraries for virtual screening, annotate compound libraries and perform filtering and sorting and advanced pharmacophore and molecule editing.
  • LigandScout Advanced, is a scientific software program that has all of the functionality of LigandScout Essential plus docking, Apo site pharmacophore modeling, pocket finding, analysis of molecular dynamics trajectories.
  • LigandScout Expert KNIME Extensions provide more than 45 Inte:Ligand scientific algorithms wrapped into KNIME extensions to be used for designing customized workflows related to computer aided drug design using the platform KNIME.
  • iLib:Diverse is a tool for in-silico fragment based design for compound libraries with advanced filtering capabilities.
  • The Inte:Ligand PharmacophoreDB is a knowledge based tool consisting of 9000 3D pharmacophore models for activity profiling, toxicity prediction, virtual screening, and lead optimization support.

Other companies and institutions providing drug discovery software[edit]

External links[edit]


  1. ^ Wolber, G. "Inte:Ligand: Your partner for in-silico drug discovery". Retrieved 2017-07-02. 
  2. ^ "Inte:Ligand Software-Entwicklungs- und Consulting GmbH - Wien - Telefon - Kontakt - Information und Consulting - Firmen A-Z". (in German). Retrieved 2017-07-02. 
  3. ^ Wolber, Gerhard; Dornhofer, Alois A.; Langer, Thierry (2006-12-01). "Efficient overlay of small organic molecules using 3D pharmacophores". Journal of Computer-Aided Molecular Design. 20 (12): 773–788. ISSN 0920-654X. doi:10.1007/s10822-006-9078-7. 
  4. ^ "Land Niederösterreich und Wirtschaftskammer NÖ verleihen NÖ Innovationspreis 2007". Retrieved 2017-07-02. 
  5. ^ "". Retrieved 2017-07-02. 
  6. ^ Wolber, Gerhard; Langer, Thierry (2005-01-01). "LigandScout:  3-D Pharmacophores Derived from Protein-Bound Ligands and Their Use as Virtual Screening Filters". Journal of Chemical Information and Modeling. 45 (1): 160–169. ISSN 1549-9596. doi:10.1021/ci049885e. 
  7. ^ Karaboga, Arnaud S.; Planesas, Jesús M.; Petronin, Florent; Teixidó, Jordi; Souchet, Michel; Pérez-Nueno, Violeta I. (2013-05-24). "Highly SpecIfic and Sensitive Pharmacophore Model for Identifying CXCR4 Antagonists. Comparison with Docking and Shape-Matching Virtual Screening Performance". Journal of Chemical Information and Modeling. 53 (5): 1043–1056. ISSN 1549-9596. doi:10.1021/ci400037y. 
  8. ^ Sanders, Marijn P. A.; Barbosa, Arménio J. M.; Zarzycka, Barbara; Nicolaes, Gerry A.F.; Klomp, Jan P.G.; de Vlieg, Jacob; Del Rio, Alberto (2012-06-25). "Comparative Analysis of Pharmacophore Screening Tools". Journal of Chemical Information and Modeling. 52 (6): 1607–1620. ISSN 1549-9596. doi:10.1021/ci2005274. 
  9. ^ Kaserer, T.; Obermoser, V.; Weninger, A.; Gust, R.; Schuster, D. (2016-11-29). "Evaluation of selected 3D virtual screening tools for the prospective identification of peroxisome proliferator-activated receptor (PPAR) γ partial agonists". European Journal of Medicinal Chemistry. 124: 49–62. doi:10.1016/j.ejmech.2016.07.072. 
  10. ^ Seidel, Thomas; Bryant, Sharon D.; Ibis, Gökhan; Poli, Giulio; Langer, Thierry (2017). Varnek, Alexandre, ed. Tutorials in Chemoinformatics. John Wiley & Sons, Ltd. pp. 279–309. ISBN 9781119161110. doi:10.1002/9781119161110.ch20. 
  11. ^ Lagarde, Nathalie; Delahaye, Solenne; Zagury, Jean-François; Montes, Matthieu (2016-09-06). "Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores". Journal of Cheminformatics. 8 (1): 43. ISSN 1758-2946. PMC 5011875Freely accessible. PMID 27602059. doi:10.1186/s13321-016-0154-2. 
  12. ^ Liu, Jiyuan; Tian, Zhen; Zhang, Yalin (2016-10-06). "Structure-based discovery of potentially active semiochemicals for Cydia pomonella (L.)". Scientific Reports. 6 (1). ISSN 2045-2322. PMC 5052595Freely accessible. PMID 27708370. doi:10.1038/srep34600. 
  13. ^ Wolber, Gerhard; Kosara, Robert (2006). Langer, Thierry; Hoffmann, Rémy D., eds. Pharmacophores and Pharmacophore Searches. Wiley-VCH Verlag GmbH & Co. KGaA. pp. 131–150. ISBN 9783527609161. doi:10.1002/3527609164.ch6. 
  14. ^ Langer, Thierry; Hoffmann, Rémy; Bryant, Sharon; Lesur, Brigitte. "Hit finding: towards ‘smarter’ approaches". Current Opinion in Pharmacology. 9 (5): 589–593. doi:10.1016/j.coph.2009.06.001. 
  15. ^ Takimoto, Seisuke; Sugiura, Airi; Minami, Saki; Tasaka, Tomohiko; Nakagawa, Yoshiaki; Miyagawa, Hisashi (2016-04-01). "In silico exploration for agonists/antagonists of brassinolide". Bioorganic & Medicinal Chemistry Letters. 26 (7): 1709–1714. doi:10.1016/j.bmcl.2016.02.054. 
  16. ^ Vuorinen, Anna; Engeli, Roger; Meyer, Arne; Bachmann, Fabio; Griesser, Ulrich J.; Schuster, Daniela; Odermatt, Alex (2014-07-24). "Ligand-Based Pharmacophore Modeling and Virtual Screening for the Discovery of Novel 17β-Hydroxysteroid Dehydrogenase 2 Inhibitors". Journal of Medicinal Chemistry. 57 (14): 5995–6007. ISSN 0022-2623. PMC 4111740Freely accessible. PMID 24960438. doi:10.1021/jm5004914. 
  17. ^ Perdih, Andrej; Kovač, Andreja; Wolber, Gerhard; Blanot, Didier; Gobec, Stanislav; Solmajer, Tom (2009-05-15). "Discovery of novel benzene 1,3-dicarboxylic acid inhibitors of bacterial MurD and MurE ligases by structure-based virtual screening approach". Bioorganic & Medicinal Chemistry Letters. 19 (10): 2668–2673. doi:10.1016/j.bmcl.2009.03.141. 
  18. ^ Waltenberger, Birgit; Garscha, Ulrike; Temml, Veronika; Liers, Josephine; Werz, Oliver; Schuster, Daniela; Stuppner, Hermann (2016-04-25). "Discovery of Potent Soluble Epoxide Hydrolase (sEH) Inhibitors by Pharmacophore-Based Virtual Screening". Journal of Chemical Information and Modeling. 56 (4): 747–762. ISSN 1549-9596. doi:10.1021/acs.jcim.5b00592. 
  19. ^ Voet, Arnout R. D.; Kumar, Ashutosh; Berenger, Francois; Zhang, Kam Y. J. (2014-04-01). "Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4". Journal of Computer-Aided Molecular Design. 28 (4): 363–373. ISSN 0920-654X. doi:10.1007/s10822-013-9702-2. 
  20. ^ DeBonis, Salvatore; Skoufias, Dimitrios A.; Indorato, Rose-Laure; Liger, François; Marquet, Bernard; Laggner, Christian; Joseph, Benoît; Kozielski, Frank (2008-03-01). "Structure–Activity Relationship of S-Trityl-l-Cysteine Analogues as Inhibitors of the Human Mitotic Kinesin Eg5". Journal of Medicinal Chemistry. 51 (5): 1115–1125. ISSN 0022-2623. doi:10.1021/jm070606z. 
  21. ^ Polishchuk, Pavel G.; Samoylenko, Georgiy V.; Khristova, Tetiana M.; Krysko, Olga L.; Kabanova, Tatyana A.; Kabanov, Vladimir M.; Kornylov, Alexander Yu.; Klimchuk, Olga; Langer, Thierry (2015-10-08). "Design, Virtual Screening, and Synthesis of Antagonists of αIIbβ3 as Antiplatelet Agents". Journal of Medicinal Chemistry. 58 (19): 7681–7694. ISSN 0022-2623. doi:10.1021/acs.jmedchem.5b00865. 
  22. ^ Barreca, Maria Letizia; De Luca, Laura; Iraci, Nunzio; Rao, Angela; Ferro, Stefania; Maga, Giovanni; Chimirri, Alba (2007-03-01). "Structure-Based Pharmacophore Identification of New Chemical Scaffolds as Non-Nucleoside Reverse Transcriptase Inhibitors". Journal of Chemical Information and Modeling. 47 (2): 557–562. ISSN 1549-9596. doi:10.1021/ci600320q. 
  23. ^ Langer, Thierry; Bryant, Sharon D (2013-10-01). In Silico Drug Discovery and Design. Future Science Book Series. Future Science Ltd. pp. 178–188. doi:10.4155/ebo.13.417. 
  24. ^ Deyon-Jung, Laurence; Morice, Christophe; Chéry, Florence; Gay, Julie; Langer, Thierry; Frantz, Marie-Céline; Rozot, Roger; Dalko-Csiba, Maria (2016-03-16). "Fragment pharmacophore-based in silico screening: a powerful approach for efficient lead discovery". Med. Chem. Commun. 7 (3): 506–511. ISSN 2040-2511. doi:10.1039/c5md00444f. 
  25. ^ Golestanian, Sahand; Sharifi, Amirhossein; Popowicz, Grzegorz M.; Azizian, Homa; Foroumadi, Alireza; Szwagierczak, Aleksandra; Holak, Tad A.; Amanlou, Massoud (2016-01-15). "Discovery of novel dual inhibitors against Mdm2 and Mdmx proteins by in silico approaches and binding assay". Life Sciences. 145: 240–246. doi:10.1016/j.lfs.2015.12.047. 
  26. ^ Wei, Yinxiang; Ma, Yuanfang; Zhao, Qing; Ren, Zhiguang; Li, Yan; Hou, Tingjun; Peng, Hui (2012-08-01). "New Use for an Old Drug: Inhibiting ABCG2 with Sorafenib". Molecular Cancer Therapeutics. 11 (8): 1693–1702. ISSN 1535-7163. PMID 22593228. doi:10.1158/1535-7163.MCT-12-0215. 
  27. ^ Shirgahi Talari, Faezeh; Bagherzadeh, Kowsar; Golestanian, Sahand; Jarstfer, Michael; Amanlou, Massoud (2015-12-28). "Potent Human Telomerase Inhibitors: Molecular Dynamic Simulations, Multiple Pharmacophore-Based Virtual Screening, and Biochemical Assays". Journal of Chemical Information and Modeling. 55 (12): 2596–2610. ISSN 1549-9596. doi:10.1021/acs.jcim.5b00336. 
  28. ^ Rakers, Christin; Schumacher, Fabian; Meinl, Walter; Glatt, Hansruedi; Kleuser, Burkhard; Wolber, Gerhard (2016-01-01). "In Silico Prediction of Human Sulfotransferase 1E1 Activity Guided by Pharmacophores from Molecular Dynamics Simulations". Journal of Biological Chemistry. 291 (1): 58–71. ISSN 0021-9258. PMC 4697188Freely accessible. PMID 26542807. doi:10.1074/jbc.M115.685610. 
  29. ^ Wieder, Marcus; Perricone, Ugo; Boresch, Stefan; Seidel, Thomas; Langer, Thierry (2016-02-12). "Evaluating the stability of pharmacophore features using molecular dynamics simulations". Biochemical and Biophysical Research Communications. 470 (3): 685–689. doi:10.1016/j.bbrc.2016.01.081. 
  30. ^ Malle, E.; Furtmüller P. G.; Sattler, W.; Obinger C. Myeloperoxidase: a target for new drug development? British Journal of Pharmacology; 2007; 152, 838-854. doi:10.1038/sj.bjp.0707358
  31. ^ Barreca, M. L.; De Luca, L.; Iraci, N.; Rao, A.; Ferro, S.; Maga, G.; Chimirri, A; Structure-Based Pharmacophore Identification of New Chemical Scaffolds as Non-Nucleoside Reverse Transcriptase Inhibitors J. Chem. Inf. Model; 2007; 47(2); 557-562. doi:10.1021/ci600320q
  32. ^ Steindl, T. M; Schuster, D.; Wolber, G.; Laggner, C.; Langer, T.; High-throughput structure-based pharmacophore modelling as a basis for successful parallel virtual screening J. Comput. Aided Mol. Des.; 2007; 20(12); 703-715. doi:10.1007/s10822-006-9066-y
  33. ^ Steindl, T. M; Schuster, Laggner, C.; Chuang, K.; Hoffmann, R.; Langer, T.; Parallel Screening and Activity Profiling with HIV Protease Inhibitor Pharmacophore Models J. Chem. Inf. Model; 2007; 47(2); 563-571. doi:10.1021/ci600321m
  34. ^ Schuster, D.; Laggner, C.; Steindl, T. M.; Langer, T.; Development and validation of an in silico P450 profiler based on pharmacophore models Curr. Drug Discov. Technol.; 2006; 3(1); 1-48.
  35. ^ Krovat, E. M.; Fruhwirth, K. H.; Langer, T.; Pharmacophore Identification, in Silico Screening, and Virtual Library Design for Inhibitors of the Human Factor Xa J. Chem. Inf. Model; 2005; 45(1); 146-159. doi:10.1021/ci049778k