Comparison to HTS - Truly direct comparisons between the results of high-throughput screening and virtual screening have not been published. In the final two examples, HTS was conducted on corporate collections, while the virtual screening experiments were carried out using databases of commercially available compounds.

After HTS failed to produce non-quinolone or coumarin lead structures for inhibition of DNA gyrase, researchers at Hoffman-La Roche opted for virtual screening to identify alternatives (46). As the known antibacterial agents bind to the ATP site on the B subunit, the authors opted to use "needle screening" for small fragments (MW < 300). X-ray structures of the known inhibitors showed partially overlapping features, particularly two hydrogen bonds that were retained in the pharmacophore hypothesis. The programs LUDI (47) and Catalyst were used to search the ACD and part of the Roche collection (ca. 350,000 compounds). The LUDI search combined with the molecular weight requirement pared the list to about 200 compounds. The Catalyst search was alternatively used to increase the precision of the required pharmacophore, and resulted in selection of 400 compounds. Initially, these 600 compounds were tested in an assay configured to detect weak binding, and the results were used to select analogues of the first hits. A total of 3000 compounds were screened to find 150 hits that represented 14 structural classes. These hits were 2-3 orders of magnitude less effective than known inhibitors, but were validated by several biophysical methods, including X-ray crystal structures of DNA gyrase with hits such as 26 and 27. These X-ray structures were vital in the optimization process in generating compounds such as 28, which is 10-fold more potent than the known inhibitor novobiocin and is substantially less complex.

Researchers at Pharmacia compared the results of an HTS of their corporate collection (400,000 molecules) against PTP-1B with 365 compounds that were found via virtual screening of 235,000 commercially available compounds (48). The DOCK program was used to select 1000 high-scoring compounds from the ACD, BioSpecs, and Maybridge collections. Selection for testing included compounds that spanned the two phosphotyrosine binding sites that are observed in X-ray crystal structures (49) and a comparable number of non-spanners. Of the 127 active compounds (IC50S < 100jiM), 21 compounds were < 10nM; of these there were 10 spanners and 11 non-spanners. Both charged (e.g., 29; 4.4 nM) and neutral (30; 12.0 nM) hits were represented.


In comparing the results of the HTS and virtual screens, the investigators note that not only was the hit-rate substantially higher for the virtual screen (of 400,000 compounds screened via HTS, 85 had IC50s < 100 jiM; 6 compounds were < 10 uM), a significantly higher proportion passed a variety of filters for "druglikeness" (70% vs. 30%). The authors do emphasize that differences in the assay conditions may have been detrimental to the HTS results, although this does not diminish the value of the compounds found by virtual screening.

Conclusions - Virtual ligand screening with tools such as Catalyst, Unity, GOLD, FlexX, and DOCK provide the ability to select a relatively small number of compounds from large databases for testing. It is notable that most researchers rely heavily upon inspection and intuitive evaluation in addition to software results; in the case of active sites, most try to incorporate knowledge of site flexibility into their selection criteria. In many of the cited examples, the investigators chose a very small proportion of potential ligands for biological testing - frequently fewer than 50. It is likely that many of the best examples of the application of virtual screening have not yet appeared in the literature as they have spurred an optimization program of considerable proprietary value.


  1. R.W. Spencer, Biotech. Bioeng. (Comb. Chem.), 61, 61 (1998).
  2. W.P. Walters, M.T. Stahl, M .A. Murcko, Drug Discov. Today, 3,160 (1998).
  3. O.F. Gùner (Ed.), Pharmacophore Perception, Development and Use in Drug Design, International University Line, La Jolla, CA, 2000.
  4. J. Bajorath, Nature Rev. Drug Discov., 1, 882 (2002).
  5. J. Bajorath, J. Chem. Inf. Comput. Sci., 41, 233 (2001).
  6. Y.C. Martin, M.G. Bures, E.A Danaher, J. DeLazzer, I. Lico, P.A. Pavlik, J. Comput.-Aided Mol. Design, 7, 83(1993).
  7. G. Jones, P. Willett, R.C. Glen, J. Comput.-Aided Mol. Des., 9, 532 (1995).
  8. D. Barnum, J. Greene, A. Smellie, P. Sprague, J. Chem. Inf. Comput. Sci., 36, 563 (1996).
  9. Y. Kurogi, O.F. Guner, Curr. Med, Chem., 8,1035 (2001).
  10. Y. Patel, V.J. Gillet, G. Bravi, A.R. Leach, J. Comput.-Aided Mol. Des., 16,653 (2002).
  11. S. Flohr, M. Kurz, E. Kostenis, A. Brkovlch, A. Fournier, T. Klabunde, J. Med. Chem., 45, 1799(2002).
  12. J. Singh, H.v. Vlijmen, Y. Liao, W. C. Lee, M. Cornebise, M. Harris, I. h. Shu, A. Gill, J.H. Cuervo, W.M. Abraham, S.P. Adams, J. Med. Chem., 45, 2988 (2002).
  13. Available Chemical Directory (ACD) Database; MDL Information Systems Inc.: San Leandro, CA, 1988.
  14. S. Wang, S. Sakamuri, I.J. Enyedy, A.P. Kozikowski, O. Deschaux, B.C. Bandyopadyay, S.R. Telia, W.A. Zaman, K.M. Johnson, J. Med. Chem., 43, 351 (2000).
  15. I.J. Enyedy, W.A. Zaman, S. Sakamuri, A.P. Kozikowski, K.M. Johnson, S. Wang, Bioorg. Med. Chem. Lett., H, 1113 (2001).
  16. I.J. Enyedy, S. Sakamuri, W.A. Zaman, K.M. Johnson, S. Wang, Bioorg. Med. Chem. Lett., 13, 513(2003).
  17. S. Sakamuri, I.J. Enyedy, W.A. Zaman, S.R. Telia, A.P. Kozikowski, J.L. FlippenAnderson, T. Farkas, K.M. Johnson, S. Wang, Bioorg. Med. Chem., Ü, 1123 (2003).
  18. G.W. Milne, M.C. Nicklaus, J.S. Driscoll, S. Wang, D.W. Zaharevitz, J. Chem. Inf. Comput. Sei., 34.1219 (1994).
  19. Chem-X, Accelrys Inc.: San Diego, CA.
  20. D.P. Marriott, I.G. Dougall, P. Meghani, Y. J. Liu, D.R. Flower, J. Med. Chem., 42, 3210


  1. Unity, Tripos Inc., St. Louis, MO.
  2. Y. Kurogi, K. Miyata, T. Okamura, K. Hasimoto, K. Tsutsumi, M. Nasu, M. Moriyasu, J. Med. Chem., 44,2304(2001).
  3. Maybridge database from Accelrys: San Diego, CA.
  4. Y. Koide, A. Tatsui, T. Hasegawa, A. Murakami, S. Satoh, H. Yamada, S. I. Kazayama, A. Takahashi, Bioorg. Med. Chem. Lett., 13, 25 (2003).
  5. Y. Koide, T. Hasegawa, A. Takashi, A. Endo, N. Mochizuki, M. Nakagawa, A. Nishida, J. Med. Chem., 45,4629 (2002).
  6. M.L. Barreca, R. Gitto, S. Quartarone, L. De Luca, G. De Sarro, A. Chimirri, J. Chem. Inf. Comput. Sei., in press (2003).
  7. R.D. Taylor, P.J. Jewsbury, J.W. Essex, J. Comput.-Aided Mol. Des., 6,1 (2002)
  8. I.D. Kuntz, Science, 25Z, 1078 (1992).
  9. M. Rarey, B. Kramer, T. Lengauer, G. Klebe, J. Mol. Biol., 261.470 (1996)
  10. G. Jones, P. Willett, R.C. Glen, A.R. Leach, R. Taylor, J. Mol. Biol., 2§Z, 727 (1997).
  11. M. Stahl, M. Rarey, J. Med. Chem., 44.1035 (2001).
  12. C.L.M.J. Verlinde, W.G. Hoi, Structure, 2, 577 (1994).
  13. P.S. Charifson, J.J. Corkery, M.A. Murcko, W.P. Walters, J. Med. Chem., 42, 5100 (1999).
  14. R. Wang, S. Wang, J. Chem. Inf. Comput. Sei., 41,1422 (2001)
  15. R.D. Clark, A. Strizhev, J.M. Leonard, J.F. Blake, J.B. Matthews, J. Mol. Graph. Mod., 20, 281 (2002).
  16. C. Bissantz, G. Folkers, D. Regnan, J. Med. Chem., 43, 4759 (2000).
  17. S. Grüneberg, M.T. Stubbs, G. Klebe, J. Med. Chem., 45, 3588 (2002).
  18. LeadQuest Chemical Compound Libraries, Tripos, Inc. St. Louis, MO.
  19. C.A. Lipinski, F. Lombardo, B.W. Dominy, P.J. Feeney, Adv. Drug Delivery Rev., 23, 3 (1997).
  20. T.S. Haque, A.G. Skillman, C.E. Lee, H. Habashita, I.Y. Gluzman, T.J.A. Ewing, D.E. Goldberg, I.D. Kuntz, J.A. Ellman, J. Med. Chem., 42,1428 (1999).
  21. M. Schapira, B.M. Raaka, H.H. Samuels, R. Abagyan, Proc. Natl. Acad. Sei., 97, 1008


  1. MolSoft (1998) ICM 2.7 Program Manual (MolSoft, San Diego).
  2. R. Brenk, L. Naerum, U. Gradler, H. D. Gerber, G.A. Garcia, K. Reuter, M.T. Stubbs, G. Klebe, J. Med. Chem., in press (2003).
  3. Y. Iwata, M. Arisawa, R. Hamada, Y. Kita, M.Y. Mizutani, N. Tomioka, A. Itai, S. Miyamoto, J. Med. Chem., 44.1718 (2001).
  4. J. L. Wang, D. Liu, Z. J. Zhang, S. Shan, X. Han, S.M. Srinivasula, C.M. Croce, E.S. Alnemri, Z. Huang, Proc. Nat. Acad. Sei., 97, 7124 (2000).
  5. H. J. Boehm, M. Boehringer, D. Bur, H. Gmuender, W. Huber, W. Klaus, D. Kostrewa, H. Kuehne, T. Luebbers, N. Meunier-Keller, F. Mueller, J. Med. Chem., 43, 2664 (2000).
  6. H.J. Boehm, J. Comput.-Aided Mol. Des., 6,61 (1992).
  7. T.N. Doman, S.L. McGovern, B.J. Witherbee, T.P. Kasten, R. Kurumbail, W.C. Stallings, D.T. Connolly, B.K. Shoichet, J. Med. Chem., 45,2213 (2002).
  8. Y.A. Pulus, Y. Zhao, M. Sullivan, D.S. Lawrence, S.C. Almo, Z.Y. Zhang, Proc. Natl. Acad. Sei. U.S.A., 94.13420 (1997).

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