Template CoMFA, a novel alignment methodology for training or test set structures in 3D-QSAR, is introduced. Its two most significant advantages are its complete automation and its ability to derive a single combined model from multiple structural series affecting a biological target. Its only two inputs are one or more “template” structures having 3D coordinates that share some Cartesian space, as may result from X-ray crystallography or pharmacophoric hypothesis, and one or more connectivity-only SAR tables associated with a common target. Template CoMFA also overcomes the major disadvantages of both existing 3D-QSAR alignment methodologies, specifically the tedium and subjectivity of familiar ad hoc approaches, and the awkwardness, occasional physicochemical heresies, and structural scope limitations of the purely topomer approach. The template CoMFA algorithms are described, and two of its application classes are presented. The first class, general models of binding to factor Xa and P38 map kinase, uses crystallographic structures as templates, with the encouraging result that the statistical qualities of each of these two combined models are equivalent to those of their constituent individual series models. The second, 15 data sets originally collected for validation of topomer CoMFA, with arbitrary structures as templates, confirms that the modeling power of template CoMFA resembles that of its predecessors.
January 19, 2014
Author(s): Richard Cramer, Bernd Wendt
Year: January 19, 2014