Structural and Physico-Chemical Interpretation (SPCI) of QSAR Models and Its Comparison with Matched Molecular Pair Analysis
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu srovnávací studie, časopisecké články, práce podpořená grantem
PubMed
27419846
DOI
10.1021/acs.jcim.6b00371
Knihovny.cz E-zdroje
- MeSH
- aplikace orální MeSH
- chemické jevy * MeSH
- data mining MeSH
- hematoencefalická bariéra metabolismus MeSH
- krysa rodu Rattus MeSH
- kvantitativní vztahy mezi strukturou a aktivitou * MeSH
- oligopeptidy chemie MeSH
- peptidomimetika chemie metabolismus farmakologie toxicita MeSH
- permeabilita MeSH
- racionální návrh léčiv MeSH
- receptory fibrinogenu antagonisté a inhibitory MeSH
- software MeSH
- testy toxicity MeSH
- uživatelské rozhraní počítače MeSH
- výpočetní biologie metody MeSH
- zvířata MeSH
- Check Tag
- krysa rodu Rattus MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- srovnávací studie MeSH
- Názvy látek
- arginyl-glycyl-aspartic acid MeSH Prohlížeč
- oligopeptidy MeSH
- peptidomimetika MeSH
- receptory fibrinogenu MeSH
This paper describes the Structural and Physico-Chemical Interpretation (SPCI) approach, which is an extension of a recently reported method for interpretation of quantitative structure-activity relationship (QSAR) models. This approach can efficiently be used to reveal structural motifs and the major physicochemical factors affecting the investigated properties. Its efficacy was demonstrated both on the classical Free-Wilson data set and on several data sets with different end points (permeability of the blood-brain barrier, fibrinogen receptor antagonists, acute oral toxicity). Structure-activity patterns extracted from QSAR models with SPCI were in good correspondence with experimentally observed relationships and molecular docking, regardless of the machine learning method used. Comparison of SPCI with the matched molecular pair (MMP) method clearly shows an advantage of our approach over MMP, especially for small or structurally diverse data sets. The developed approach has been implemented in the SPCI software tool with a graphical user interface, which is publicly available at http://qsar4u.com/pages/sirms_qsar.php .
Citace poskytuje Crossref.org
Benchmarks for interpretation of QSAR models