L-shaped PLS analysis of multiple inhibitory activities of adrenergic alpha receptors using ligand and protein matrices

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Recently, chemogenomics has been given high attention in pharmaceutical industry. By definition, chemogenomics data is a two-dimensional matrix, where proteins are usually reported as columns and ligands as rows, and where reported values are usually inhibitory activities. In a straightforward manner, it would be the best choice that the chemogenomics matrix is explained by two matrices that each consists of ligand and protein descriptors. Bi-modal PLS follows this concept and several variants have been proposed. Among them, we focus on the L-shaped PLS (LPLS) method and apply it to aminergic G protein-coupled receptor inhibitory activity data in a previous study.In this study, we have devised both of the ligand and protein matrices in the frame of LPLS analysis for four adrenergic alpha receptors. In the ligand matrix, the similarity matrix derived from the Tanimoto similarity value between the pair of inhibitors was employed. As for the protein matrix, the 3D protein pocket was mapped to the spherical self-organizing map sphere. Then, the lipophilic potential value on each node was used as protein descriptors. Thanks to four plots of LPLS, we could easily identify four selective inhibitors and elucidate structural requirements for selectivity.