Tomasz Leon Magdziarz, Dr.

Affiliations: 
2008 Faculty of Mathematics, Physics and Chemistry University of Silesia, Katowice 
Area:
organic chemistry
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"Tomasz Magdziarz"
Bio:

Sector Formalism of the Comparative Molecular Surface Analysis (s-CoMSA) - an Application to Structure-Activity Relationships Modelling (2008)

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Publications

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Polanski J, Kucia U, Duszkiewicz R, et al. (2016) Molecular descriptor data explain market prices of a large commercial chemical compound library. Scientific Reports. 6: 28521
Bak A, Wyszomirski M, Magdziarz T, et al. (2014) Structure-based modeling of dye-fiber affinity with SOM-4D-QSAR paradigm: application to set of anthraquinone derivatives. Combinatorial Chemistry & High Throughput Screening. 17: 485-502
Bak A, Magdziarz T, Kurczyk A, et al. (2013) Probing a chemical space for fragmental topology-activity landscapes (FRAGTAL): application for diketo acid and catechol HIV integrase inhibitor offspring fragments. Combinatorial Chemistry & High Throughput Screening. 16: 274-87
Bak A, Magdziarz T, Kurczyk A, et al. (2011) Mapping fragmental drug-likeness in the MoStBioDat environment: intramolecular hydrogen bonding motifs in β-ketoenols. Combinatorial Chemistry & High Throughput Screening. 14: 560-9
Mazur P, Magdziarz T, Bak A, et al. (2010) Does molecular docking reveal alternative chemopreventive mechanism of activation of oxidoreductase by sulforaphane isothiocyanates? Journal of Molecular Modeling. 16: 1205-12
Magdziarz T, Mazur P, Polanski J. (2009) Receptor independent and receptor dependent CoMSA modeling with IVE-PLS: application to CBG benchmark steroids and reductase activators. Journal of Molecular Modeling. 15: 41-51
Polanski J, Bak A, Gieleciak R, et al. (2006) Modeling robust QSAR. Journal of Chemical Information and Modeling. 46: 2310-8
Magdziarz T, Lozowicka B, Gieleciak R, et al. (2006) 3D QSAR study of hypolipidemic asarones by comparative molecular surface analysis. Bioorganic & Medicinal Chemistry. 14: 1630-43
Gieleciak R, Magdziarz T, Bak A, et al. (2005) Modeling robust QSAR. 1. Coding molecules in 3D-QSAR--from a point to surface sectors and molecular volumes. Journal of Chemical Information and Modeling. 45: 1447-55
Polanski J, Bak A, Gieleciak R, et al. (2004) Self-organizing neural networks for modeling robust 3D and 4D QSAR: application to dihydrofolate reductase inhibitors. Molecules (Basel, Switzerland). 9: 1148-59
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