title: Modeling robust QSAR.
abstract: Quantitative Structure Activity Relationship (QSAR) is a term describing a variety of approaches that are of substantial interest for chemistry. This method can be defined as indirect molecular design by the iterative sampling of the chemical compounds space to optimize a certain property and thus indirectly design the molecular structure having this property. However, modeling the interactions of chemical molecules in biological systems provides highly noisy data, which make predictions a roulette risk. In this paper we briefly review the origins for this noise, particularly in multidimensional QSAR. This was classified as the data, superimposition, molecular similarity, conformational, and molecular recognition noise. We also indicated possible robust answers that can improve modeling and predictive ability of QSAR, especially the self-organizing mapping of molecular objects, in particular, the molecular surfaces, a method that was brought into chemistry by Gasteiger and Zupan.
authors.affiliation: Department of Organic Chemistry, Institute of Chemistry, University of Silesia, PL-40-006 Katowice, Poland. polanski@us.edu.pl
authors.forename: Jaroslaw
authors.initials: J
authors.lastname: Polanski
authors.forename: Andrzej
authors.initials: A
authors.lastname: Bak
authors.forename: Rafal
authors.initials: R
authors.lastname: Gieleciak
authors.forename: Tomasz
authors.initials: T
authors.lastname: Magdziarz
mesh_terms: D000465:Algorithms; D002621:Chemistry / Q000379:methods*; D003198:Computer Simulation; D016208:Databases, Factual; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D008962:Models, Theoretical; D008968:Molecular Conformation; D016571:Neural Networks, Computer; D021281:Quantitative Structure-Activity Relationship; D012984:Software; D013269:Stochastic Processes