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Volumn 45, Issue 3, 2005, Pages 549-561

Virtual screening of molecular databases using a support vector machine

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATA REDUCTION; DIGITAL LIBRARIES; MOLECULAR STRUCTURE; VIRTUAL REALITY;

EID: 20444410410     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci049641u     Document Type: Article
Times cited : (245)

References (36)
  • 1
    • 0036835460 scopus 로고    scopus 로고
    • Integration of virtual and high throughput screening
    • Bajorath, J. Integration of virtual and high throughput screening. Nat. Rev. Drug Discov. 2002, 1, 882-894.
    • (2002) Nat. Rev. Drug Discov. , vol.1 , pp. 882-894
    • Bajorath, J.1
  • 2
    • 0036214750 scopus 로고    scopus 로고
    • Virtual screening: Methods, expectations, and reality
    • Bajorath, J. Virtual screening: methods, expectations, and reality. Curr. Drug Discovery 2002, 2, 24-28.
    • (2002) Curr. Drug Discovery , vol.2 , pp. 24-28
    • Bajorath, J.1
  • 3
    • 0036740917 scopus 로고    scopus 로고
    • Why do we need so many chemical similarity search methods?
    • Sheridan, R. P.; Kearsley, S. K. Why do we need so many chemical similarity search methods? Drug Discovery Today 2002, 7, 903-911.
    • (2002) Drug Discovery Today , vol.7 , pp. 903-911
    • Sheridan, R.P.1    Kearsley, S.K.2
  • 4
    • 0035438391 scopus 로고    scopus 로고
    • Is there a difference between leads and drugs? a historical perspective
    • Oprea, T. I.; Davis, A. M.; Teague, S. J.; Leeson, P. D. Is there a difference between leads and drugs? A historical perspective. J. Chem. Inf. Comput. Sci. 2001, 41, 1308-1315.
    • (2001) J. Chem. Inf. Comput. Sci. , vol.41 , pp. 1308-1315
    • Oprea, T.I.1    Davis, A.M.2    Teague, S.J.3    Leeson, P.D.4
  • 5
    • 0036589285 scopus 로고    scopus 로고
    • Current trends in lead discovery: Are we looking for the appropriate properties?
    • Oprea, T. I. Current trends in lead discovery: are we looking for the appropriate properties? J. Comput.-Aided Mol. Des. 2002, 16, 325-334.
    • (2002) J. Comput.-aided Mol. Des. , vol.16 , pp. 325-334
    • Oprea, T.I.1
  • 7
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • Burges, C. J. C. A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining Knowl. Discovery 1998, 2, 121-167.
    • (1998) Data Mining Knowl. Discovery , vol.2 , pp. 121-167
    • Burges, C.J.C.1
  • 8
    • 0034740222 scopus 로고    scopus 로고
    • Drug design by machine learning: Support vector machines for pharmaceutical data analysis
    • Burbidge, R.; Trotter, M.; Buxton, B.; Holden, S. Drug design by machine learning: support vector machines for pharmaceutical data analysis. Comput. Chem. 2001, 26, 5-14.
    • (2001) Comput. Chem. , vol.26 , pp. 5-14
    • Burbidge, R.1    Trotter, M.2    Buxton, B.3    Holden, S.4
  • 10
    • 0345117343 scopus 로고    scopus 로고
    • Comparison of linear and nonlinear classification algorithms for the prediction of drug and chemical metabolism by human UDP-glucuronosyltransferase isoforms
    • Sorich, M. J.; Miners, J. O.; McKinnon, R. A.; Winkler, D. A.; Burden, F. R.; Smith, P. A. Comparison of linear and nonlinear classification algorithms for the prediction of drug and chemical metabolism by human UDP- glucuronosyltransferase isoforms. J. Chem. Inf. Comput. Sci. 2003, 43, 2019-2024.
    • (2003) J. Chem. Inf. Comput. Sci. , vol.43 , pp. 2019-2024
    • Sorich, M.J.1    Miners, J.O.2    McKinnon, R.A.3    Winkler, D.A.4    Burden, F.R.5    Smith, P.A.6
  • 11
    • 0344254815 scopus 로고    scopus 로고
    • Drug discovery using support vector machines. The case studies of drug-likeness, agrochemical-likeness, and enzyme inhibition predictions
    • Zernov, V. V.; Balakin, K. V.; Ivaschenko, A. A.; Savchuk, N. P.; Pletnev, I. V. Drug discovery using support vector machines. The case studies of drug-likeness, agrochemical-likeness, and enzyme inhibition predictions. J. Chem. Inf. Comput. Sci. 2003, 43, 2048-2056.
    • (2003) J. Chem. Inf. Comput. Sci. , vol.43 , pp. 2048-2056
    • Zernov, V.V.1    Balakin, K.V.2    Ivaschenko, A.A.3    Savchuk, N.P.4    Pletnev, I.V.5
  • 13
    • 0003773721 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • Platt, J. Fast Training of Support Vector Machines using Sequential Minimal Optimization; Microsoft Research Technical Report MSR-TR-98-14; 1998.
    • (1998) Microsoft Research Technical Report , vol.MSR-TR-98-14
    • Platt, J.1
  • 15
    • 34249753618 scopus 로고
    • Support vector networks
    • Cortes, C.; Vapnik, V. Support vector networks. Machine Learning 1995, 20, 273-297.
    • (1995) Machine Learning , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 16
    • 0035438388 scopus 로고    scopus 로고
    • Prediction of biological activity for high-throughput screening using binary kernel discrimination
    • Harper, O.; Bradshaw, J.; Gittins, J. C.; Green, D. V.; Leach, A. R. Prediction of biological activity for high-throughput screening using binary kernel discrimination. J. Chem. Inf. Comput. Sci. 2001, 41, 1295-1300.
    • (2001) J. Chem. Inf. Comput. Sci. , vol.41 , pp. 1295-1300
    • Harper, O.1    Bradshaw, J.2    Gittins, J.C.3    Green, D.V.4    Leach, A.R.5
  • 17
    • 0037363598 scopus 로고    scopus 로고
    • Comparison of ranking methods for virtual screening in lead-discovery programs
    • Wilton, D.; Willett, P.; Lawson, K.; Mullier, G. Comparison of ranking methods for virtual screening in lead-discovery programs. J. Chem. Inf. Comput. Sci. 2003, 43, 469-474.
    • (2003) J. Chem. Inf. Comput. Sci. , vol.43 , pp. 469-474
    • Wilton, D.1    Willett, P.2    Lawson, K.3    Mullier, G.4
  • 19
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • Guyon, I.; Weston, W.; Barnhill, S.; Vapnik, V. Gene Selection for Cancer Classification using Support Vector Machines. Machine Learning 2002, 46, 389-422.
    • (2002) Machine Learning , vol.46 , pp. 389-422
    • Guyon, I.1    Weston, W.2    Barnhill, S.3    Vapnik, V.4
  • 21
    • 20444370028 scopus 로고    scopus 로고
    • MDL Information Systems, Inc.
    • IsisDraw 2.4, MDL Information Systems, Inc., 2001.
    • (2001) IsisDraw 2.4
  • 23
    • 84860947089 scopus 로고    scopus 로고
    • http://www.mdl.com/solutions/white_papers/ctfile_formats.jsp.
  • 24
    • 84860943820 scopus 로고    scopus 로고
    • http://dtp.nci.nih.gov/docs/3d_database/Structural_information/ structural_data.html.
  • 25
    • 84860943819 scopus 로고    scopus 로고
    • http://www.maybridge.com.
  • 26
    • 0000490166 scopus 로고
    • From atoms and bonds to three-dimensional atomic coordinates: Automatic model builders
    • Sadowski, J.; Gasteiger, J. From Atoms and Bonds to Three-Dimensional Atomic Coordinates: Automatic Model Builders. Chem. Rev. 1993, 93, 2567-2581.
    • (1993) Chem. Rev. , vol.93 , pp. 2567-2581
    • Sadowski, J.1    Gasteiger, J.2
  • 28
    • 33749255357 scopus 로고    scopus 로고
    • Milano Chemometrics and QSAR Research Group: Milan, Italy
    • Todeschini, R.; Consonni, V.; Pavan, M. DRAGON 2.1. Milano Chemometrics and QSAR Research Group: Milan, Italy, 2002.
    • (2002) DRAGON 2.1.
    • Todeschini, R.1    Consonni, V.2    Pavan, M.3
  • 29
    • 0001611357 scopus 로고    scopus 로고
    • JChem: Java applets and modules supporting chemical database handling from web browsers
    • Csizmadia F. JChem: Java applets and modules supporting chemical database handling from web browsers. J. Chem. Inf. Comput. Sci. 2000, 40, 323-324.
    • (2000) J. Chem. Inf. Comput. Sci. , vol.40 , pp. 323-324
    • Csizmadia, F.1
  • 31
    • 0035865781 scopus 로고    scopus 로고
    • Improved scoring of ligand-protein interactions using OWFEG free energy grids
    • Pearlman, D. A.; Charifson, P. S. Improved scoring of ligand-protein interactions using OWFEG free energy grids. J. Med. Chem. 2001, 44, 502-511.
    • (2001) J. Med. Chem. , vol.44 , pp. 502-511
    • Pearlman, D.A.1    Charifson, P.S.2
  • 32
    • 1642310340 scopus 로고    scopus 로고
    • Glide: A new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening
    • Halgren, T. A.; Murphy, R. B.; Friesner, R. A.; Beard, H. S.; Frye, L. L.; Pollard, W. T.; Banks, J. L. Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J. Med. Chem. 2004, 47, 1750-1759.
    • (2004) J. Med. Chem. , vol.47 , pp. 1750-1759
    • Halgren, T.A.1    Murphy, R.B.2    Friesner, R.A.3    Beard, H.S.4    Frye, L.L.5    Pollard, W.T.6    Banks, J.L.7
  • 33
    • 0003102354 scopus 로고    scopus 로고
    • Similarity searching in files of three-dimensional chemical structures: Evaluation of the EVA descriptor and combination of rankings using data fusion
    • Ginn, C. M. R.; Turner, D. B.; Willett, P.; Ferguson, A. M.; Heritage, T. W. Similarity Searching in Files of Three-Dimensional Chemical Structures: Evaluation of the EVA Descriptor and Combination of Rankings Using Data Fusion. J. Chem. Inf. Comput. Sci. 1997, 37, 23-37.
    • (1997) J. Chem. Inf. Comput. Sci. , vol.37 , pp. 23-37
    • Ginn, C.M.R.1    Turner, D.B.2    Willett, P.3    Ferguson, A.M.4    Heritage, T.W.5
  • 34
    • 0032474873 scopus 로고    scopus 로고
    • Three-dimensional quantitative similarity-activity relationships (3D QSiAR) from SEAL similarity matrices
    • Kubinyi, H.; Hamprecht, F. A.; Mietzner, T. Three-dimensional quantitative similarity-activity relationships (3D QSiAR) from SEAL similarity matrices. J. Med. Chem. 1998, 41, 2553-2564.
    • (1998) J. Med. Chem. , vol.41 , pp. 2553-2564
    • Kubinyi, H.1    Hamprecht, F.A.2    Mietzner, T.3
  • 36
    • 0042355453 scopus 로고    scopus 로고
    • Rational selection of training and test sets for the development of validated QSAR models
    • Golbraikh, A.; Shen, M.; Xiao, Z.; Xiao, Y. D.; Lee, K. H.; Tropsha, A. Rational selection of training and test sets for the development of validated QSAR models. J. Comput.-Aided Mol. Des. 2003, 17, 241-253.
    • (2003) J. Comput.-aided Mol. Des. , vol.17 , pp. 241-253
    • Golbraikh, A.1    Shen, M.2    Xiao, Z.3    Xiao, Y.D.4    Lee, K.H.5    Tropsha, A.6


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