Dixon SL - Search Results

1

Analysis and comparison of 2D fingerprints: insights into database screening performance using eight fingerprint methods.

Duan J, Dixon SL, Lowrie JF, Sherman W. Duan J, et al. Among authors: dixon sl. J Mol Graph Model. 2010 Sep;29(2):157-70. doi: 10.1016/j.jmgm.2010.05.008. Epub 2010 May 25. J Mol Graph Model. 2010. PMID: 20579912

2

Exploring conformational search protocols for ligand-based virtual screening and 3-D QSAR modeling.

Cappel D, Dixon SL, Sherman W, Duan J. Cappel D, et al. Among authors: dixon sl. J Comput Aided Mol Des. 2015 Feb;29(2):165-82. doi: 10.1007/s10822-014-9813-4. Epub 2014 Nov 19. J Comput Aided Mol Des. 2015. PMID: 25408244

3

Large-scale systematic analysis of 2D fingerprint methods and parameters to improve virtual screening enrichments.

Sastry M, Lowrie JF, Dixon SL, Sherman W. Sastry M, et al. Among authors: dixon sl. J Chem Inf Model. 2010 May 24;50(5):771-84. doi: 10.1021/ci100062n. J Chem Inf Model. 2010. PMID: 20450209

4

Rapid shape-based ligand alignment and virtual screening method based on atom/feature-pair similarities and volume overlap scoring.

Sastry GM, Dixon SL, Sherman W. Sastry GM, et al. Among authors: dixon sl. J Chem Inf Model. 2011 Oct 24;51(10):2455-66. doi: 10.1021/ci2002704. Epub 2011 Sep 15. J Chem Inf Model. 2011. PMID: 21870862

5

Kernel-based partial least squares: application to fingerprint-based QSAR with model visualization.

An Y, Sherman W, Dixon SL. An Y, et al. Among authors: dixon sl. J Chem Inf Model. 2013 Sep 23;53(9):2312-21. doi: 10.1021/ci400250c. Epub 2013 Aug 19. J Chem Inf Model. 2013. PMID: 23901898

6

Hole filling and library optimization: application to commercially available fragment libraries.

An Y, Sherman W, Dixon SL. An Y, et al. Among authors: dixon sl. Bioorg Med Chem. 2012 Sep 15;20(18):5379-87. doi: 10.1016/j.bmc.2012.03.037. Epub 2012 Mar 24. Bioorg Med Chem. 2012. PMID: 22503740

7

AutoQSAR: an automated machine learning tool for best-practice quantitative structure-activity relationship modeling.

Dixon SL, Duan J, Smith E, Von Bargen CD, Sherman W, Repasky MP. Dixon SL, et al. Future Med Chem. 2016 Oct;8(15):1825-1839. doi: 10.4155/fmc-2016-0093. Epub 2016 Sep 19. Future Med Chem. 2016. PMID: 27643715

8

PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results.

Dixon SL, Smondyrev AM, Knoll EH, Rao SN, Shaw DE, Friesner RA. Dixon SL, et al. J Comput Aided Mol Des. 2006 Oct-Nov;20(10-11):647-71. doi: 10.1007/s10822-006-9087-6. Epub 2006 Nov 24. J Comput Aided Mol Des. 2006. PMID: 17124629

9

PHASE: a novel approach to pharmacophore modeling and 3D database searching.

Dixon SL, Smondyrev AM, Rao SN. Dixon SL, et al. Chem Biol Drug Des. 2006 May;67(5):370-2. doi: 10.1111/j.1747-0285.2006.00384.x. Chem Biol Drug Des. 2006. PMID: 16784462 No abstract available.

10

QMQSAR: utilization of a semiempirical probe potential in a field-based QSAR method.

Dixon S, Merz KM Jr, Lauri G, Ianni JC. Dixon S, et al. J Comput Chem. 2005 Jan 15;26(1):23-34. doi: 10.1002/jcc.20142. J Comput Chem. 2005. PMID: 15526326

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