Xmap-An Interpretable Alignment-Free Four-Dimensional Quantitative Structure Activity Relationship Technique Based On Molecular Surface Properties And Conformer Ensembles

A novel alignment-free molecular descriptor called xMaP (flexible MaP descriptor) is introduced., The descriptor is the advancement of the previously published translationally and rotationally invariant threediinensional (3D) descriptor Ma? (mapping property distributions onto the molecular surface) to the fourth dimension (4D). In addition to MaP, xMaP is independent of the chosen starting conformation of the encoded molecules and is therefore entirely alignment-free. This is achieved by using_ensembles of conformers, which are-generated by conformational searches. this step" of the procedure is similar to Hopfinger's 4D, quantitative structure activity -relationship (QSAR). A five-step procedure is used to compute "the xMaP descriptor. First, a conformational search for each Molecule is carried out. Next, for-each of the conformers an approximation to the Molecular surface with equally distributed surface points is computed. Third, molecular properties are projected onto this surface. Fourth, areas of identical properties are clustered to so-called;patches. Fifth, the spatial distribution of the patches is converted into an alignment-free descriptor that is based on the entire conformer ensemble. The resulting descriptor can be interpreted by superimposing the most important descriptor variables and the molecules of the data set. The most important descriptor variables are identified with chemometric regression tools. The novel descriptor was applied to several benchmark data sets and was compared to other descriptors and QSAR techniques comprising a binary fingerprint, a topological pharmacophore descriptor (Cats2D), and the field-based 3D-QSAR technique GRID/PLS which is alignment-dependent. The use of conformer ensembles renders-xMaP very robust. It turns out that tMaP performs very well on (almost) all data sets and that the statistical results are comparable to GRID/PLS. In addition to that, xMaP "can also be used to efficiently visualize the derived quantitative structure activity relationships.