By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Investigators discuss new findings in Molecular Informatics. According to news reporting from Chapel Hill, North Carolina, by VerticalNews journalists, research stated, "In this paper we offer a novel approach for the structural interpretation of QSAR models. The major advantage of our developed methodology is its universality, i.e., it can be applied to any QSAR/QSPR model irrespective of chemical descriptors and machine learning methods applied."
The news correspondents obtained a quote from the research from the University of North Carolina, "This universality was achieved by using only the information obtained from substructures of the compounds of interest to interpret model outcomes. Reliability of the offered approach was confirmed by the results of three case studies, including end-points of different types (continuous and binary classification) and nature (solubility, mutagenicity, and inhibition of Transglutaminase 2), various fragment and whole-molecule descriptors (Simplex and Dragon), and multiple modeling techniques (partial least squares, random forest, and support vector machines). We compared the global contributions of molecular fragments obtained using our methodology with known SAR rules derived experimentally. In all cases high concordance between our interpretation and results published by others was observed. Although the proposed interpretation approach could be easily extended to any type of descriptors, we would recommend using Simplex descriptors to achieve a larger variety of investigated molecular fragments. The developed approach is a good tool for interpretation of such 'black box' models like random forest, neural networks, etc. Analysis of fragment global contributions and their deviation across a dataset could be useful for the identification of key fragments and structural alerts."
According to the news reporters, the research concluded: "This information could be helpful to maximize the positive influence of structural surroundings on the given fragment and to decrease the negative effects."
For more information on this research see: Universal Approach for Structural Interpretation of QSAR/QSPR Models. Molecular Informatics, 2013;32(9-10):843-853. Molecular Informatics can be contacted at: Wiley-V C H Verlag Gmbh, Boschstrasse 12, D-69469 Weinheim, Germany. (Wiley-Blackwell - www.wiley.com/; Molecular Informatics - onlinelibrary.wiley.com/journal/10.1002/(ISSN)1868-1751)
Our news journalists report that additional information may be obtained by contacting P.G. Polishchuk, University of North Carolina, Lab Mol Modeling, Div Med Chem & Nat Prod, Eshelman Sch Pharm, Chapel Hill, NC 27599, United States. Additional authors for this research include V.E. Kuz'min, A.G. Artemenko and E.N. Muratov.
Keywords for this news article include: Chapel Hill, United States, North Carolina, Molecular Informatics, North and Central America
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