Paper doi abstract bibtex

Abstract: The program SEAL is suited to describe the electrostatic, steric, hydrophobic, and hydrogen bond donor and acceptor similarity of different molecules in a quantitative manner. Similarity scores AF can be calculated for pairs of molecules, using either a certain molecular property or a sum of weighted properties. Alternatively, their mutual similarity can be derived from distances d or covariances c between SEAL-based property fields that are calculated in a regular grid. For a set of N chemically related molecules, such values form an N x N similarity matrix which can be correlated with biological activities, using either regression analysis and an appropriate variable selection procedure or partial least-squares (PLS) analysis. For the Cramer steroid data set, the test set predictivities (r2pred = 0.53-0.84) of different PLS models, based on a weighted sum of molecular properties, are superior to published results of CoMFA and CoMSIA studies (r2pred = 0.31-0.40), regardless of whether a common alignment or individual, pairwise alignments of all molecules are used in the calculation of the similarity matrices. Training and test set selections have a significant influence on the external predictivities of the models. Although the SEAL similarity score between two molecules is a single number, its value is based on the 3D properties of both molecules. The term 3D quantitative similarity-activity analyses (3D QSiAR) is proposed for approaches which correlate 3D structure-derived similarity matrices with biological activities.

@article{Kubinyi:1998aa, Abstract = {Abstract: The program SEAL is suited to describe the electrostatic, steric, hydrophobic, and hydrogen bond donor and acceptor similarity of different molecules in a quantitative manner. Similarity scores AF can be calculated for pairs of molecules, using either a certain molecular property or a sum of weighted properties. Alternatively, their mutual similarity can be derived from distances d or covariances c between SEAL-based property fields that are calculated in a regular grid. For a set of N chemically related molecules, such values form an N x N similarity matrix which can be correlated with biological activities, using either regression analysis and an appropriate variable selection procedure or partial least-squares (PLS) analysis. For the Cramer steroid data set, the test set predictivities (r2pred = 0.53-0.84) of different PLS models, based on a weighted sum of molecular properties, are superior to published results of CoMFA and CoMSIA studies (r2pred = 0.31-0.40), regardless of whether a common alignment or individual, pairwise alignments of all molecules are used in the calculation of the similarity matrices. Training and test set selections have a significant influence on the external predictivities of the models. Although the SEAL similarity score between two molecules is a single number, its value is based on the 3D properties of both molecules. The term 3D quantitative similarity-activity analyses (3D QSiAR) is proposed for approaches which correlate 3D structure-derived similarity matrices with biological activities.}, Author = {Kubinyi, H. and Hamprecht, F.A. and Mietzner, T.}, Date-Added = {2008-04-23 14:56:04 -0400}, Date-Modified = {2008-04-23 14:57:40 -0400}, Doi = {10.1021/jm970732a}, Journal = {J.~Med.~Chem.}, Keywords = {qsar; alignment; similarity; paradox}, Local-Url = {file://localhost/Users/rguha/Documents/articles/jm970732a.pdf}, Number = {14}, Pages = {2553=-2564}, Title = {Three-Dimensional Quantitative Similarity-Activity Relationships ({3D QSiAR}) from {SEAL} Similarity Matrices}, Url = {http://pubs3.acs.org/acs/journals/doilookup?in_doi=10.1021/jm970732a}, Volume = {41}, Year = {1998}, Bdsk-File-1 = {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}, Bdsk-Url-1 = {http://pubs3.acs.org/acs/journals/doilookup?in_doi=10.1021/jm970732a}, Bdsk-Url-2 = {http://dx.doi.org/10.1021/jm970732a}}

Downloads: 0