Wang XS - Search Results

1

Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening.

Hsieh JH, Wang XS, Teotico D, Golbraikh A, Tropsha A. Hsieh JH, et al. Among authors: wang xs. J Comput Aided Mol Des. 2008 Sep;22(9):593-609. doi: 10.1007/s10822-008-9199-2. Epub 2008 Mar 13. J Comput Aided Mol Des. 2008. PMID: 18338225

2

Application of quantitative structure-activity relationship models of 5-HT1A receptor binding to virtual screening identifies novel and potent 5-HT1A ligands.

Luo M, Wang XS, Roth BL, Golbraikh A, Tropsha A. Luo M, et al. Among authors: wang xs. J Chem Inf Model. 2014 Feb 24;54(2):634-47. doi: 10.1021/ci400460q. Epub 2014 Feb 12. J Chem Inf Model. 2014. PMID: 24410373 Free PMC article.

3

Combinatorial QSAR modeling of specificity and subtype selectivity of ligands binding to serotonin receptors 5HT1E and 5HT1F.

Wang XS, Tang H, Golbraikh A, Tropsha A. Wang XS, et al. J Chem Inf Model. 2008 May;48(5):997-1013. doi: 10.1021/ci700404c. Epub 2008 May 10. J Chem Inf Model. 2008. PMID: 18470978

4

Novel inhibitors of human histone deacetylase (HDAC) identified by QSAR modeling of known inhibitors, virtual screening, and experimental validation.

Tang H, Wang XS, Huang XP, Roth BL, Butler KV, Kozikowski AP, Jung M, Tropsha A. Tang H, et al. Among authors: wang xs. J Chem Inf Model. 2009 Feb;49(2):461-76. doi: 10.1021/ci800366f. J Chem Inf Model. 2009. PMID: 19182860

5

Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.

Hsieh JH, Yin S, Wang XS, Liu S, Dokholyan NV, Tropsha A. Hsieh JH, et al. Among authors: wang xs. J Chem Inf Model. 2012 Jan 23;52(1):16-28. doi: 10.1021/ci2002507. Epub 2011 Dec 14. J Chem Inf Model. 2012. PMID: 22017385 Free PMC article.

6

Comparative Analysis of QSAR-based vs. Chemical Similarity Based Predictors of GPCRs Binding Affinity.

Luo M, Wang XS, Tropsha A. Luo M, et al. Among authors: wang xs. Mol Inform. 2016 Jan;35(1):36-41. doi: 10.1002/minf.201500038. Epub 2015 Oct 23. Mol Inform. 2016. PMID: 27491652

7

Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening?

Tang H, Wang XS, Hsieh JH, Tropsha A. Tang H, et al. Among authors: wang xs. Proteins. 2012 Jun;80(6):1503-21. doi: 10.1002/prot.24035. Epub 2012 Mar 13. Proteins. 2012. PMID: 22275072 Free PMC article.

8

Discovery of geranylgeranyltransferase-I inhibitors with novel scaffolds by the means of quantitative structure-activity relationship modeling, virtual screening, and experimental validation.

Peterson YK, Wang XS, Casey PJ, Tropsha A. Peterson YK, et al. Among authors: wang xs. J Med Chem. 2009 Jul 23;52(14):4210-20. doi: 10.1021/jm8013772. J Med Chem. 2009. PMID: 19537691 Free PMC article.

9

The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.

Xia J, Hsieh JH, Hu H, Wu S, Wang XS. Xia J, et al. Among authors: wang xs. J Chem Inf Model. 2017 Jun 26;57(6):1414-1425. doi: 10.1021/acs.jcim.6b00749. Epub 2017 Jun 1. J Chem Inf Model. 2017. PMID: 28511009 Free PMC article.

10

Pose Filter-Based Ensemble Learning Enables Discovery of Orally Active, Nonsteroidal Farnesoid X Receptor Agonists.

Xia J, Wang Z, Huan Y, Xue W, Wang X, Wang Y, Liu Z, Hsieh JH, Zhang L, Wu S, Shen Z, Zhang H, Wang XS. Xia J, et al. Among authors: wang x, wang xs, wang z, wang y. J Chem Inf Model. 2020 Mar 23;60(3):1202-1214. doi: 10.1021/acs.jcim.9b01030. Epub 2020 Feb 25. J Chem Inf Model. 2020. PMID: 32050066

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