Skip to main content
Log in

Computational chemistry at Janssen

  • Published:
Journal of Computer-Aided Molecular Design Aims and scope Submit manuscript

Abstract

Computer-aided drug discovery activities at Janssen are carried out by scientists in the Computational Chemistry group of the Discovery Sciences organization. This perspective gives an overview of the organizational and operational structure, the science, internal and external collaborations, and the impact of the group on Drug Discovery at Janssen.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. 2015 Global 2000: The World’s Largest Drug And Biotech Companies (2015) Forbes. http://www.forbes.com/sites/liyanchen/2015/06/04/2015-global-2000-the-worlds-largest-drug-and-biotech-companies/#5cd9e0cf5768. Accessed 29 Oct 2016

  2. Taking Flight: Pharm Exec’s Top 50 Pharma Companies (2015) PharmExec.com http://www.pharmexec.com/taking-flight-pharm-execs-top-50-pharma-companies. Accessed 29 Oct 2016

  3. http://www.schrodinger.com/. Accessed 29 Oct 2016

  4. http://www.chemcomp.com/. Accessed 29 Oct 2016

  5. Hack MD, Rassokhin DN, Buyck C, Seierstad M, Skalkin A, ten Holte P, Jones TK, Mirzadegan T, Agrafiotis DK (2011) Library enhancement through the wisdom of crowds. J Chem Inf Model 51:3275–3286

    Article  CAS  Google Scholar 

  6. Jacoby E, Tresadern G, Bembenek S, Wroblowski B, Buyck C, Neefs JM, Rassokhin D, Poncelet A, Hunt J, van Vlijmen H (2015) Extending kinome coverage by analysis of kinase inhibitor broad profiling data. Drug Discov Today 20:652–658

    Article  CAS  Google Scholar 

  7. Papadatos G, Davies M, Dedman N, Chambers J, Gaulton A, Siddle J, Koks R, Irvine SA, Pettersson J, Goncharoff N, Hersey A, Overington JP (2016) SureChEMBL: A large-scale, chemically annotated patent document database. Nucleic Acids Res 44(D1):D1220–D1228

    Article  Google Scholar 

  8. Open PHACTS website. http://www.openphacts.org/. Accessed 29 Oct 2016

  9. Linked data, wikipedia. http://en.wikipedia.org/wiki/Linked_data. Accessed 29 Oct 2016

  10. Ratnam J, Zdrazil B, Digles D, Cuadrado-Rodriguez E, Neefs JM, Tipney H, Siebes R, Waagmeester A, Bradley G, Chau CH, Richter L, Brea J, Evelo CT, Jacoby E, Senger S, Loza MI, Ecker GF, Chichester C (2014) The application of the open pharmacological concepts triple store (Open PHACTS) to support drug discovery research. PLoS One 9:e115460

    Article  Google Scholar 

  11. Agrafiotis DK, Alex S, Dai H, Derkinderen A, Farnum M, Gates P, Izrailev S, Jaeger EP, Konstant P, Leung A, Lobanov VS, Marichal P, Martin D, Rassokhin DN, Shemanarev M, Skalkin A, Stong J, Tabruyn T, Vermeiren M, Wan J, Xu XY, Yao X (2007) Advanced biological and chemical discovery (ABCD): Centralizing discovery knowledge in an inherently decentralized world. J Chem Inf Model 47:1999–2014

    Article  CAS  Google Scholar 

  12. Bento AP, Gaulton A, Hersey A, Bellis LJ, Chambers J, Davies M, Krüger FA, Light Y, Mak L, McGlinchey S, Nowotka M, Papadatos G, Santos R, Overington JP (2014) The ChEMBL bioactivity database: An update. Nucleic Acids Res 42:1083–1090

    Article  Google Scholar 

  13. Wishart DS, Knox C, Guo AC, Shrivastava S, Hassanali M, Stothard P, Chang Z, Woolsey J (2006) DrugBank: A comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res 34:D668–D672

    Article  CAS  Google Scholar 

  14. GOSTAR database, GVK Biosciences Private Limited, Hyderabad India. http://www.gostardb.com. Accessed 29 Oct 2016

  15. http://thomsonreuters.com/. Accessed 29 Oct 2016

  16. Euretos corporate website. http://www.euretos.com/. Accessed 29 Oct 2016

  17. Simm J, Arany A, Zakeri P, Haber T, Wegner JK, Chupakhin V, Ceulemans H, Moreau Y (2015) Macau: Scalable Bayesian multi-relational factorization with side information using MCMC. arXiv:1509.04610v2 [stat.ML]. http://arxiv.org/pdf/1509.04610v2.pdf. Accessed 29 Oct 2016

  18. Unterthiner T, Mayr, A, Klambauer, G, Steijaert, M, Wegner, JK, Ceulemans, H, Hochreiter, S (2014) Deep learning as an opportunity in virtual screening. Advances in neural information processing systems, 27. http://www.bioinf.jku.at/publications/2014/NIPS2014a.pdf. Accessed 29 Oct 2016

  19. Damm-Ganamet KL, Bembenek SD, Venable JW, Castro GG, Mangelschots L, Peeters DC, Mcallister HM, Edwards JP, Disepio D, Mirzadegan T (2016) A prospective virtual screening study: Enriching hit rates and designing focus libraries to find inhibitors of PI3Kδ and PI3Kγ. J Med Chem 59:4302–4313

    Article  CAS  Google Scholar 

  20. Kuppens T, Bultinck P, Langenaeker W (2004) Determination of absolute configuration via vibrational circular dichroism. Drug Discov Today Technol 1:269–275

    Article  CAS  Google Scholar 

  21. Wang L, Wu Y, Deng Y, Kim B, Pierce L, Krilov G, Lupyan D, Robinson S, Dahlgren MK, Greenwood J, Romero DL, Masse C, Knight JL, Steinbrecher T, Beuming T, Damm W, Harder E, Sherman W, Brewer M, Wester R, Murcko M, Frye L, Farid R, Lin T, Mobley DL, Jorgensen WL, Berne BJ, Friesner RA, Abel R (2015) Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern free-energy calculation protocol and force field. J Am Chem Soc 137:2695–2703

    Article  CAS  Google Scholar 

  22. Ciordia M, Pérez-Benito L, Delgado F, Trabanco AA, Tresadern G (2016) Application of Free Energy Perturbation for the Design of BACE1 Inhibitors. J Chem Inf Model 56:1856–1871

    Article  CAS  Google Scholar 

  23. http://www.eyesopen.com. Accessed 29 Oct 2016

  24. http://accelrys.com/products/collaborative-science/biovia-pipeline-pilot/. Accessed 29 Oct 2016

  25. Moriaud F, Doppelt-Azeroual O, Martin L, Oguievetskaia K, Koch K, Vorotyntsev A, Adcock SA, Delfaud F (2009) Computational fragment-based approach at PDB scale by protein local similarity. J Chem Inf Model 49:280–294

    Article  CAS  Google Scholar 

  26. Wolber G, Langer T (2005) LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J Chem Inf Model 45:160–169

    Article  CAS  Google Scholar 

  27. Case DA, Betz RM, Botello-Smith W, Cerutti DS, Cheatham TE III, Darden TA, Duke RE, Giese TJ, Gohlke H, Goetz AW, Homeyer N, Izadi S, Janowski P, Kaus J, Kovalenko A, Lee TS, LeGrand S, Li P, Lin C, Luchko T, Luo R, Madej B, Mermelstein D, Merz KM, Monard G, Nguyen H, Nguyen HT, Omelyan I, Onufriev A, Roe DR, Roitberg A, Sagui C, Simmerling CL, Swails J, Walker RC, Wang J, Wolf RM, Wu X, Xiao L, York DM, Kollman PA (2016) AMBER 2016. University of California, San Francisco

    Google Scholar 

  28. Boda K, Seidel T, Gasteiger J (2007) Structure and reaction based evaluation of synthetic accessibility. J Comput Aided Mol Des 21:311–325

    Article  CAS  Google Scholar 

  29. Proasis software, Desert Scientific, Norwest, Australia. http://www.desertsci.com/. Accessed 29 Oct 2016

  30. Kinase KnowledgeBase, Eidogen-Sertanty, Oceanside CA. http://www.eidogen-sertanty.com/. Accessed 29 Oct 2016

  31. StarDrop, Optibrium Ltd, Cambridge UK. http://www.optibrium.com/stardrop/. Accessed 29 Oct 2016

  32. Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727–748

    Article  CAS  Google Scholar 

  33. Hendlich M, Bergner A, Günther J, Klebe G (2003) Relibase—design and development of a database for comprehensive analysis of protein–ligand interactions. J Mol Biol 326:607–620

    Article  CAS  Google Scholar 

  34. Kolpak J, Connolly PJ, Lobanov VS, Agrafiotis DK (2009) Enhanced SAR maps: Expanding the data rendering capabilities of a popular medicinal chemistry tool. J Chem Inf Model 49:2221–2230

    Article  CAS  Google Scholar 

  35. Schrödinger web site news (2011) http://www.schrodinger.com/news/schrodinger-signs-research-collaboration. Accessed 29 Oct 2016

  36. Flanders innovation & entrepreneurship. http://www.vlaio.be/english. Accessed 29 Oct 2016

  37. The innovative medicines initiative. http://www.imi.europa.eu/. Accessed 29 Oct 2016

  38. HORIZON 2020: The EU framework programme for research and innovation. http://ec.europa.eu/programmes/horizon2020/. Accessed 29 Oct 2016

  39. European Lead Factory. http://www.europeanleadfactory.eu. Accessed 29 Oct 2016

  40. Kinetics for drug discovery. http://www.k4dd.eu/. Accessed 29 Oct 2016

  41. Structural genomics consortium. http://www.thesgc.org/. Accessed 29 Oct 2016

  42. Phenomics discovery initiative. http://npsc.ac.uk/pdi. Accessed 29 Oct 2016

  43. Zhang X, Song F, Kuo GH, Xiang A, Gibbs AC, Abad MC, Sun W, Kuo LC, Sui Z (2011) Optimization of a pyrazole hit from FBDD into a novel series of indazoles as ketohexokinase inhibitors. Bioorg Med Chem Lett 21:4762–4767

    Article  CAS  Google Scholar 

  44. Desjarlais RL (2011) Using computational techniques in fragment-based drug discovery. Methods Enzymol 493:137–155

    Article  CAS  Google Scholar 

  45. Keith JM, Tichenor MS, Apodaca RL, Xiao W, Jones WM, Seierstad M, Pierce JM, Palmer JA, Webb M, Karbarz MJ, Scott BP, Wilson SJ, Wennerholm ML, Rizzolio M, Rynberg R, Chaplan SR, Breitenbucher JG (2016) The SAR of brain penetration for a series of heteroaryl urea FAAH inhibitors. Bioorg Med Chem Lett 26:3109–3114

    Article  CAS  Google Scholar 

  46. Blevitt JM, Hack MD, Herman K, Chang L, Keith JM, Mirzadegan T, Rao NL, Lebsack AD, Milla ME (2016) A single amino acid difference between mouse and human 5-lipoxygenase activating protein (FLAP) explains the speciation and differential pharmacology of novel FLAP inhibitors. J Biol Chem 291:12724–12731

    Article  CAS  Google Scholar 

  47. Cummings MD, Lin TI, Hu L, Tahri A, McGowan D, Amssoms K, Last S, Devogelaere B, Rouan MC, Vijgen L, Berke JM, Dehertogh P, Fransen E, Cleiren E, van der Helm L, Fanning G, Nyanguile O, Simmen K, Van Remoortere P, Raboisson P, Vendeville S (2014) Discovery and early development of TMC647055, a non-nucleoside inhibitor of the hepatitis C virus NS5B polymerase. J Med Chem 57:1880–1892

    Article  CAS  Google Scholar 

  48. DesJarlais R, Tummino PJ (2016) Role of histone-modifying enzymes and their complexes in regulation of chromatin biology. BioChemistry 55:1584–1599

    Article  CAS  Google Scholar 

  49. Battles MB, Langedijk JP, Furmanova-Hollenstein P, Chaiwatpongsakorn S, Costello HM, Kwanten L, Vranckx L, Vink P, Jaensch S, Jonckers TH, Koul A, Arnoult E, Peeples ME, Roymans D, McLellan JS (2015) Molecular mechanism of respiratory syncytial virus fusion inhibitors. Nat Chem Biol 12:87–93

    Article  Google Scholar 

  50. Rombouts FJ, Tresadern G, Delgado O, Martínez-Lamenca C, Van Gool M, García-Molina A, Alonso de Diego SA, Oehlrich D, Prokopcova H, Alonso JM, Austin N, Borghys H, Van Brandt S, Surkyn M, De Cleyn M, Vos A, Alexander R, Macdonald G, Moechars D, Gijsen H, Trabanco AA (2015) 1,4-Oxazine β-secretase 1 (BACE1) inhibitors: From hit generation to orally bioavailable brain penetrant leads. J Med Chem 58:8216–8235

    Article  CAS  Google Scholar 

  51. Bosc N, Wroblowski B, Aci-Sèche S, Meyer C, Bonnet P (2015) A proteometric analysis of human kinome: Insight into discriminant conformation-dependent residues. ACS Chem Biol 10:2827–2840

    Article  CAS  Google Scholar 

  52. Alonso A, Milanzi E, Molenberghs G, Buyck C, Bijnens L (2015) Impact of selection bias on the evaluation of clusters of chemical compounds in the drug discovery process. Pharm Stat 14:129–138

    Article  Google Scholar 

  53. Pande V (2016) Understanding the complexity of epigenetic target space. J Med Chem 59:1299–1307

    Article  CAS  Google Scholar 

  54. Koul A, Vranckx L, Dhar N, Göhlmann HW, Özdemir E, Neefs JM, Schulz M, Lu P, Mørtz E, McKinney JD, Andries K, Bald D (2014) Delayed bactericidal response of Mycobacterium tuberculosis to bedaquiline involves remodelling of bacterial metabolism. Nat Commun 5:3369

    Article  Google Scholar 

  55. Tresadern G, Cid JM, Trabanco AA (2014) QSAR design of triazolopyridine mGlu2 receptor positive allosteric modulators. J Mol Graph Model 53:82–91

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Herman van Vlijmen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

van Vlijmen, H., Desjarlais, R.L. & Mirzadegan, T. Computational chemistry at Janssen. J Comput Aided Mol Des 31, 267–273 (2017). https://doi.org/10.1007/s10822-016-9998-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10822-016-9998-9

Keywords

Navigation