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Evaluation of docking/scoring approaches: A comparative study based on MMP3 inhibitors

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Abstract

An increasing number of docking/scoring programs are available that use different sampling and scoring algorithms. A reliable scoring function is the crucial element of such approaches. Comparative studies are needed to evaluate their current capabilities. DOCK4 with force field and PMF scoring as well as FlexX were used to evaluate the predictive power of these docking/scoring approaches to identify the correct binding mode of 61 MMP-3 inhibitors in a crystal structure of stromelysin and also to rank them according to their different binding affinities. It was found that DOCK4/PMF scoring performs significantly better than FlexX and DOCK4/FF in both ranking ligands and predicting their binding modes. Most notably, DOCK4/PMF was the only scoring/docking approach that found a significant correlation between binding affinity and predicted score of the docked inhibitors. However, comparing only those cases where the correct binding mode was identified (scoring highest among sampled poses), FlexX showed the best `fine tuning' (lowest rmsd) in predicted binding modes. The results suggest that not so much the sampling procedure but rather the scoring function is the crucial element of a docking program.

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References

  1. Greer, J., Erickson, J.W., Baldwin, J.J. and Varney, M.D., J. Med. Chem., 37 (1994) 1035.

    Google Scholar 

  2. Lutz, M.W., Menius, J.A., Choi, T.D., Laskody, R.G., Domanico, P.L., Goetz, A.S. and Saussy, D.L., Drug Discov. Today, 1 (1996) 277.

    Google Scholar 

  3. Dixon, J.S., Proteins, Suppl., 1 (1997) 198.

    Google Scholar 

  4. Kuntz, I.D., Blaney, J.M., Oatley, S.J. and Langridge, R.L., J. Mol. Biol., 161 (1982) 269.

    Google Scholar 

  5. Kuntz, I.D., Science, 257 (1992) 1078.

    Google Scholar 

  6. Ewing, T. and Kuntz, I.D., J. Comput. Chem., 18 (1997) 1175.

    Google Scholar 

  7. Rarey, M., Kramer, B., Lengauer, T. and Klebe, G., J. Mol. Biol., 261 (1996) 470.

    Google Scholar 

  8. Welch, W., Ruppert, J. and Jain, A.N., Chem. Biol., 3 (1996) 449.

    Google Scholar 

  9. Jones, G., Willett, P., Glen, R.C. and Leach, A.R., J. Mol. Biol., 267 (1997) 727.

    Google Scholar 

  10. Goodsell, D.S. and Olson, A.J., Proteins, 8 (1990) 195.

    Google Scholar 

  11. Miller, M.D., Kearsley, S.K., Underwood, D.J. and Sheridan, R.P., J. Comput-Aided Mol. Design, 8 (1994) 153.

    Google Scholar 

  12. Dixon, J.S. and Blaney, J.M., In Martin, Y.C. and Willett, P. (Eds.) Designing Bioactive Molecules. Three-dimensional Techniques and Applications, American Chemical Society, Washington, DC, 1998, p. 175.

    Google Scholar 

  13. Böhm, H.-J., J. Comput.-Aided Mol. Design, 8 (1994) 243.

    Google Scholar 

  14. Aqvist, J., Medina, C. and Samuelsson, J.E., Protein Eng., 7 (1994) 386.

    Google Scholar 

  15. Head, R.D., Smythe, M.L., Oprea, T.L., Waller, C.L., Green, S.M. and Marshall, G.M., J. Am. Chem. Soc., 118 (1996) 3959.

    Google Scholar 

  16. Jain, A.N., J. Comput.-Aided Mol. Design, 10 (1996) 427.

    Google Scholar 

  17. Kollman, P., Chem. Rev., 7 (1993) 2395.

    Google Scholar 

  18. Wallqvist, A., Jernigan, R.L. and Covell, D.G., Protein Sci., 4 (1995) 1881.

    Google Scholar 

  19. Williams, D.H., Cox, J.P.L., Doig, A.J., Gardner, M., Gerhard, U., Kaye, P.T., Lai, A.R., Nicholls, I.A., Salter, C.J. and Mitchell, R.C., J. Am. Chem. Soc., 113 (1991) 7020.

    Google Scholar 

  20. Eldridge, M.D., Murray, C.W., Auton, T.R., Paolini, G.V. and Mee, R.P., J. Comput.-Aided Mol. Design, 11 (1997) 425.

    Google Scholar 

  21. DeWitte, R.S. and Shakhnovich, E.I., J. Am. Chem. Soc., 118 (1996) 11733.

    Google Scholar 

  22. Muegge, I. and Martin, Y.C., J. Med. Chem., 42 (1999) 791.

    Google Scholar 

  23. Böhm, H.-J., J. Comput.-Aided Mol. Design, 8 (1998) 243.

    Google Scholar 

  24. Weiner, S.J., Kollman, P.A., Case, D.A., Singh, U.C., Ghio, C., Alagona, G., Profeta Jr., S. and Weiner, P., J. Am. Chem. Soc., 106 (1984) 765.

    Google Scholar 

  25. Weiner, S.J., Kollman, P.A., Nguyen, D.T. and Case, D.A., J. Comput. Chem., 7 (1986) 230.

    Google Scholar 

  26. Muegge, I., Martin, Y.C., Hajduk, P.J. and Fesik, S.W., J. Med. Chem., 42 (1999) 2498.

    Google Scholar 

  27. Muegge, I., Med. Chem. Res., 9 (1999) 490.

    Google Scholar 

  28. Birkedal-Hansen, H., Moore, W.G.I., Bodden, M.K., Windsor, L.J., Birkedal-Hansen, B., DeCarlo, A. and Engler, J.A., Crit. Rev. Oral Biol. Med., 4 (1993) 197.

    Google Scholar 

  29. Woessner, J.F.J., FASEB J., 5 (1991) 2145.

    Google Scholar 

  30. Dhanaraj, V., Ye, Q.Z., Johnson, L.L., Hupe, D.J., Ortwine, D.F., Dunbar, J.B., Rubin, J.R., Pavolvski, A., Humblet, C. and Blundell, T.L., Structure, 4 (1996) 466.

    Google Scholar 

  31. Stockman, B.J., Watson, D.J., Gates, J.A., Scahill, T.A., Kloosterman, D.A., Miszak, S.A., Jacobsen, E.J., Belonga, K.L., Mitchell, M.A., Mao, B., Petke, J.D., Goodman, L. and Powers, E.A., Protein Sci., 7 (1998) 2281.

    Google Scholar 

  32. Marcy, A.I., Eiberger, L.L., Harrison, R., Chan, H.K., Hutchinson, N.L., Hagman, W.K., Cameron, P.M., Boulton, D.A. and Hermes, J.D., Biochemistry, 30 (1991) 6476.

    Google Scholar 

  33. Howard, A.J., Nielsen, C. and Xuong, N.H., Methods Enzymol., 114 (1985) 452.

    Google Scholar 

  34. Furey, W.F. and Swaminathan, S., Methods Enzymol., 227 (1997) 590.

    Google Scholar 

  35. Wang, B.C., Methods Enzymol., 114 (1985) 90.

    Google Scholar 

  36. Jones, T.A., J. Appl. Crystallogr., 115 (1975) 157.

    Google Scholar 

  37. Brünger, A.T., X-PLOR Manual, Version 3.1, Yale University Press, New Haven, CT, 1992.

    Google Scholar 

  38. Sippl, M.J., J. Mol. Biol., 213 (1990) 859.

    Google Scholar 

  39. Sippl, M.J., J. Comput.-Aided Mol. Design, 7 (1993) 473.

    Google Scholar 

  40. Sippl, M.J., Ortner, M., Jaritz, M., Lackner, P. and Flöckner, H., Folding Design, 1 (1996) 289.

    Google Scholar 

  41. Warshel, A., Papazyan, A. and Muegge, I., J. Biol. Inorg. Chem., 2 (1997) 143.

    Google Scholar 

  42. Muegge, I., Qi, X.P., Wand, A.J., Chu, Z.T. and Warshel, A., J. Phys. Chem. B, 101 (1997) 825.

    Google Scholar 

  43. Muegge, I., Tao, H. and Warshel, A., Protein Eng., 10 (1997) 1363.

    Google Scholar 

  44. Muegge, I., Perspect. Drug Discov. Des., accepted for publication.

  45. Gohlke, H., Hendlich, M. and Klebe, G., J. Mol. Biol., 295 (2000) 337.

    Google Scholar 

  46. Walters, W.P., Stahl, M.T. and Murcko, M.A., Drug Discov. Today, 3 (1998) 160.

    Google Scholar 

  47. Kluender, H.C.E., Dixon, B.R., VanZandt, M.C., Willhelm, S.M., Wolanin, D.J. and Wood, J.E., U.S. Patent No. 5,861,428, 1999.

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Ha, S., Andreani, R., Robbins, A. et al. Evaluation of docking/scoring approaches: A comparative study based on MMP3 inhibitors. J Comput Aided Mol Des 14, 435–448 (2000). https://doi.org/10.1023/A:1008137707965

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