VSDMIP: virtual screening data management on an integrated platform


A novel software (VSDMIP) for the virtual screening (VS) of chemical libraries integrated within a MySQL relational database is presented. Two main features make VSDMIP clearly distinguishable from other existing computational tools: (i) its database, which stores not only ligand information but also the results from every step in the VS process, and (ii) its modular and pluggable architecture, which allows customization of the VS stages (such as the programs used for conformer generation or docking), through the definition of a detailed workflow employing user-configurable XML files. VSDMIP, therefore, facilitates the storage and retrieval of VS results, easily adapts to the specific requirements of each method and tool used in the experiments, and allows the comparison of different VS methodologies. To validate the usefulness of VSDMIP as an automated tool for carrying out VS several experiments were run on six protein targets (acetylcholinesterase, cyclin-dependent kinase 2, coagulation factor Xa, estrogen receptor alpha, p38 MAP kinase, and neuraminidase) using nine binary (actives/inactive) test sets. The performance of several VS configurations was evaluated by means of enrichment factors and receiver operating characteristic plots.

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Fig. 1
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Coagulation factor Xa


Cyclic dependant kinase 2


Estrogen receptor a


MAP Kinase P38


Virtual Screening


Enrichment Factor


Receiver Operating Characteristic


  1. 1.

    Smith A (2002) Nature 418:453

    Google Scholar 

  2. 2.

    Lahana R (1999) Drug Discov Today 4:447. doi:10.1016/S1359-6446(99)01393-8

    Article  Google Scholar 

  3. 3.

    Ramesha CS (2000) Drug Discov Today 5:43. doi:10.1016/S1359-6446(99)01444-0

    Article  Google Scholar 

  4. 4.

    Perola E, Walters WP, Charifson PS (2004) Proteins 56:235. doi:10.1002/prot.20088

    Article  CAS  Google Scholar 

  5. 5.

    Warren GL, Andrews CW, Capelli AM et al (2006) J Med Chem 49:5912. doi:10.1021/jm050362n

    Article  CAS  Google Scholar 

  6. 6.

    Kitchen DB, Decornez H, Furr JR et al (2004) Nat Rev Drug Discov 3:935. doi:10.1038/nrd1549

    Article  CAS  Google Scholar 

  7. 7.

    Adcock SA, McCammon JA (2006) Chem Rev 106:1589. doi:10.1021/cr040426m

    Article  CAS  Google Scholar 

  8. 8.

    Brandsdal BO, Osterberg F, Almlof M et al (2003) Adv Protein Chem 66:123. doi:10.1016/S0065-3233(03)66004-3

    Article  CAS  Google Scholar 

  9. 9.

    Shoichet BK (2004) Nature 432:862. doi:10.1038/nature03197

    Article  CAS  Google Scholar 

  10. 10.

    Leach AR, Shoichet BK, Peishoff CE (2006) J Med Chem 49:5851. doi:10.1021/jm060999m

    Article  CAS  Google Scholar 

  11. 11.

    Corina Molecular Networks (2000). GmbH Computerchemie Langemarckplatz 1, Erlangen, Germany. http://www.molecular-networks.com/software/corina/index.html. Accessed 24 Sept 2008

  12. 12.

    Gil-Redondo R (2006) Master Thesis: Implementación de una plataforma para el cribado virtual de quimiotecas. UNED, Madrid

  13. 13.

    Stewart JJ (1990) J Comput Aided Mol Des 4:1. doi:10.1007/BF00128336

    Article  Google Scholar 

  14. 14.

    Kuntz ID, Blaney JM, Oatley SJ et al (1982) J Mol Biol 161:269. doi:10.1016/0022-2836(82)90153-X

    Article  CAS  Google Scholar 

  15. 15.

    McGann MR, Almond HR, Nicholls A et al (2003) Biopolymers 68:76. doi:10.1002/bip.10207

    Article  CAS  Google Scholar 

  16. 16.

    Perez C, Ortiz AR (2001) J Med Chem 44:3768. doi:10.1021/jm010141r

    Article  CAS  Google Scholar 

  17. 17.

    Morris GM, Goodsell DS, Halliday RS et al (1998) J Comput Chem 19:1639. doi:10.1002/(SICI)1096-987X(19981115)19:14<1639::AID-JCC10>3.0.CO;2-B

    Article  CAS  Google Scholar 

  18. 18.

    Rocchia W, Sridharan S, Nicholls A et al (2002) J Comput Chem 23:128. doi:10.1002/jcc.1161

    Article  CAS  Google Scholar 

  19. 19.

    Morreale A, Gil-Redondo R, Ortiz AR (2007) Proteins 67:606. doi:10.1002/prot.21269

    Article  CAS  Google Scholar 

  20. 20.

    Lipinski CA, Lombardo F, Dominy BW et al (2001) Adv Drug Deliv Rev 46:3. doi:10.1016/S0169-409X(00)00129-0

    Article  CAS  Google Scholar 

  21. 21.

    Triballeau N, Acher F, Brabet I et al (2005) J Med Chem 48:2534. doi:10.1021/jm049092j

    Article  CAS  Google Scholar 

  22. 22.

    Weininger D (1988) J Chem Inf Comput Sci 28:31. doi:10.1021/ci00057a005

    CAS  Google Scholar 

  23. 23.

    Ctfile Formats MDL (2007). Symyx, California. http://www.mdl.com/solutions/white_papers/ctfile_formats.jsp. Accessed 24 Sept 2008

  24. 24.

    Dewar MJS, Thiel W (1977) J Am Chem Soc 99:2338. doi:10.1021/ja00449a053

    Article  CAS  Google Scholar 

  25. 25.

    Maignan S, Guilloteau JP, Pouzieux S et al (2000) J Med Chem 43:3226. doi:10.1021/jm000940u

    Article  CAS  Google Scholar 

  26. 26.

    Murcia M, Ortiz AR (2004) J Med Chem 47:805. doi:10.1021/jm030137a

    Article  CAS  Google Scholar 

  27. 27.

    Jacobsson M, Liden P, Stjernschantz E et al (2003) J Med Chem 46:5781. doi:10.1021/jm030896t

    Article  CAS  Google Scholar 

  28. 28.

    Kryger G, Silman I, Sussman JL (1999) Structure 7:297. doi:10.1016/S0969-2126(99)80040-9

    Article  CAS  Google Scholar 

  29. 29.

    Arris CE, Boyle FT, Calvert AH et al (2000) J Med Chem 43:2797. doi:10.1021/jm990628o

    Article  CAS  Google Scholar 

  30. 30.

    Thomas MP, McInnes C, Fischer PM (2006) J Med Chem 49:92. doi:10.1021/jm050554i

    Article  CAS  Google Scholar 

  31. 31.

    Bissantz C, Folkers G, Rognan D (2000) J Med Chem 43:4759. doi:10.1021/jm001044l

    Article  CAS  Google Scholar 

  32. 32.

    Shiau AK, Barstad D, Loria PM et al (1998) Cell 95:927. doi:10.1016/S0092-8674(00)81717-1

    Article  CAS  Google Scholar 

  33. 33.

    Burmeister WP, Henrissat B, Bosso C et al (1993) Structure 1:19. doi:10.1016/0969-2126(93)90005-2

    Article  CAS  Google Scholar 

  34. 34.

    Murray CW, Baxter CA, Frenkel AD (1999) J Comput Aided Mol Des 13:547. doi:10.1023/A:1008015827877

    Article  CAS  Google Scholar 

  35. 35.

    Cavasotto CN, Abagyan RA (2004) J Mol Biol 337:209. doi:10.1016/j.jmb.2004.01.003

    Article  CAS  Google Scholar 

  36. 36.

    Wang Z, Harkins PC, Ulevitch RJ et al (1997) Proc Natl Acad Sci USA 94:2327. doi:10.1073/pnas.94.6.2327

    Article  CAS  Google Scholar 

  37. 37.

    Canutescu AA, Shelenkov AA, Dunbrack RL Jr (2003) Protein Sci 12:2001. doi:10.1110/ps.03154503

    Article  CAS  Google Scholar 

  38. 38.

    Fiser A, Sali A (2003) Methods Enzymol 374:461. doi:10.1016/S0076-6879(03)74020-8

    Article  CAS  Google Scholar 

  39. 39.

    Case DA, Darden TA, Cheatham TE et al (2004) AMBER 8. University of California, San Francisco

    Google Scholar 

  40. 40.

    Wang J, Cieplak P, Kollman PA (2000) J Comput Chem 21:1049. doi:10.1002/1096-987X(200009)21:12<1049::AID-JCC3>3.0.CO;2-F

    Article  CAS  Google Scholar 

  41. 41.

    Gordon JC, Myers JB, Folta T et al (2005) Nucleic Acids Res 33:W368. doi:10.1093/nar/gki464

    Article  CAS  Google Scholar 

  42. 42.

    Honig B, Nicholls A (1995) Science 268:1144. doi:10.1126/science.7761829

    Article  CAS  Google Scholar 

  43. 43.

    Tishmack PA, Bashford D, Harms E et al (1997) Biochemistry 36:11984. doi:10.1021/bi9712448

    Article  CAS  Google Scholar 

  44. 44.

    Hawkins GD, Cramer CJ, Truhlar DG (1995) Chem Phys Lett 246:122. doi:10.1016/0009-2614(95)01082-K

    Article  CAS  Google Scholar 

  45. 45.

    Hawkins GD, Cramer CJ, Truhlar DG (1996) J Phys Chem 100:19824. doi:10.1021/jp961710n

    Article  CAS  Google Scholar 

  46. 46.

    Tsui V, Case DA (2000) Biopolymers 56:275. doi:10.1002/1097-0282(2000)56:4<275::AID-BIP10024>3.0.CO;2-E

    Article  CAS  Google Scholar 

  47. 47.

    Golebiowski A, Townes JA, Laufersweiler MJ et al (2005) Bioorg Med Chem Lett 15:2285. doi:10.1016/j.bmcl.2005.03.007

    Article  CAS  Google Scholar 

  48. 48.

    Mehler EL, Solmajer T (1991) Protein Eng 4:903. doi:10.1093/protein/4.8.903

    Article  CAS  Google Scholar 

  49. 49.

    Wang K, Murcia M, Constans P et al (2004) J Comput Aided Mol Des 18:101. doi:10.1023/B:jcam.0000030033.26053.40

    Article  CAS  Google Scholar 

  50. 50.

    Wang R, Lai L, Wang S (2002) J Comput Aided Mol Des 16:11. doi:10.1023/A:1016357811882

    Article  CAS  Google Scholar 

  51. 51.

    Tripos Mol2 File Format (2007). Tripos LP, Missouri. http://www.tripos.com/tripos_resources/fileroot/mol2_format_Dec07.pdf. Accessed 24 Sept 2008

  52. 52.

    Sitkoff D, Sharp KA, Honig B (1994) J Phys Chem 98:1978. doi:10.1021/j100058a043

    Article  CAS  Google Scholar 

  53. 53.

    Molecular Modeling Package TINKER (2004). http://dasher.wustl.edu/tinker. Accessed 24 Sept 2008

  54. 54.

    DeLano WL (2002). The PyMOL Molecular Graphics System DeLano Scientific, Palo Alto, CA. http://pymol.sourceforge.net. Accessed 24 Sept 2008

  55. 55.

    Kollman PA, Massova I, Reyes C et al (2000) Acc Chem Res 33:889. doi:10.1021/ar000033j

    Article  CAS  Google Scholar 

  56. 56.

    SciTegic, Inc. 10188 Telesis Court, Suite 100, San Diego, CA 92121, USA, http://accelrys.com/products/scitegic. Accesed 24 Sept 2008

  57. 57.

    Hassan M, Brown RD, Varma-O’brien S (2006) Mol Divers 10:283. doi:10.1007/s11030-006-9041-5

    Article  CAS  Google Scholar 

  58. 58.

    Watson P, Verdonk M, Hartshorn MJ (2003) J Mol Graph Model 22:71. doi:10.1016/S1093-3263(03)00137-2

    Article  CAS  Google Scholar 

  59. 59.

    Lehtovuori PT, Nyronen TH (2006) J Chem Inf Model 46:620. doi:10.1021/ci050388n

    Article  CAS  Google Scholar 

  60. 60.

    Vaque M, Arola A, Aliagas C et al (2006) Bioinformatics 22:1803. doi:10.1093/bioinformatics/btl197

    Article  CAS  Google Scholar 

  61. 61.

    Zhang S, Kumar K, Jiang X et al (2008) BMC Bioinformatics 9:126. doi:10.1186/1471-2105-9-126

    Article  Google Scholar 

  62. 62.

    Yang JM, Chen YF, Shen TW et al (2005) J Chem Inf Model 45:1134. doi:10.1021/ci050034w

    Article  CAS  Google Scholar 

  63. 63.

    Maiorov V, Sheridan RP (2005) J Chem Inf Model 45:1017. doi:10.1021/ci050089y

    Article  CAS  Google Scholar 

  64. 64.

    Miteva MA, Lee WH, Montes MO et al (2005) J Med Chem 48:6012. doi:10.1021/jm050262h

    Article  CAS  Google Scholar 

  65. 65.

    Knox AJ, Meegan MJ, Carta G et al (2005) J Chem Inf Model 45:1908. doi:10.1021/ci050185z

    Article  CAS  Google Scholar 

  66. 66.

    Teague SJ (2003) Nat Rev Drug Discov 2:527. doi:10.1038/nrd1129

    Article  CAS  Google Scholar 

  67. 67.

    Huang N, Kalyanaraman C, Irwin JJ (2006) J Chem Inf Model 46:243. doi:10.1021/ci0502855

    Article  CAS  Google Scholar 

  68. 68.

    Kuhn B, Gerber P, Schulz-Gasch T (2005) J Med Chem 48:4040. doi:10.1021/jm049081q

    Article  CAS  Google Scholar 

  69. 69.

    Ruiz FM, Gil-Redondo R, Morreale A (2008) J Chem Inf Model 48:844. doi:10.1021/ci700447r

    Article  CAS  Google Scholar 

  70. 70.

    Irwin JJ, Shoichet BK (2005) J Chem Inf Model 45:177. doi:10.1021/ci049714+

    Article  CAS  Google Scholar 

  71. 71.

    Gil-Redondo R, Estrada J, Morreale A, et al. (2008). VSDMIP. CBM “Severo Ochoa” (CSIC-UAM) and Universidad de Zaragoza, Spain. http://ub.cbm.uam.es/VSDMIP.htm. Accessed 24 Sept 2008

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Work at the CBM-SO was partially supported by a grant from “Comunidad de Madrid” thorough BIPEDD project (SBIO-0214–2006) and from “Ministerio de Educación y Ciencia” (BIO2005–0576). J.S. and J.E. were funded by grants BFU2007–61476/BMC (MEC, Spain) and PM076/2006 (DGA, Spain). J.E.’s research stage at CBM “Severo Ochoa” was funded by grants DGA (CONSI + D)/CAI (Spain) and FPU (MEC, Spain). J.E. is recepient of an FPU grant (MEC, Spain). J.E. thanks Alejandra Leo-Macías for help in using the MODELLER software. A.M. and R.G.-R. thank David Abia and Rubén Muñoz for technical support. We also acknowledge the generous allocation of computer time at the Barcelona Supercomputing Center. This work would not have been possible without the encouraging help of Ángel R. Ortiz, to whose memory this article is dedicated.

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Correspondence to Antonio Morreale.

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Ángel R. Ortiz deceased on May 5, 2008.

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Gil-Redondo, R., Estrada, J., Morreale, A. et al. VSDMIP: virtual screening data management on an integrated platform. J Comput Aided Mol Des 23, 171–184 (2009). https://doi.org/10.1007/s10822-008-9249-9

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  • Docking
  • Virtual screening
  • Drug design
  • Database
  • Platform