Hyphenated 3D-QSAR statistical model-scaffold hopping analysis for the identification of potentially potent and selective sigma-2 receptor ligands

A 3D quantitative structure-activity relationship (3D-QSAR) model for predicting the Ï 2receptor affinity has been constructed with the aim of providing a useful tool for the identification, design, and optimization of novel Ï 2receptor ligands. The model has been built using a set of 500 selective Ï 2receptor ligands recovered from the sigma-2 receptor selective ligand database (S2RSLDB) and developed with the software Forge. The present model showed high statistical quality as confirmed by its robust predictive potential and satisfactory descriptive capability. The drawn up 3D map allows for a prompt visual comprehension of the electrostatic, hydrophobic, and shaping features underlying Ï 2receptor ligands interaction. A theoretic approach for the generation of new lead compounds with optimized Ï 2receptor affinity has been performed by means of scaffold hopping analysis. Obtained results further confirmed the validity of our model being some of the identified moieties have already been successfully employed in the development of potent Ï 2receptor ligands. For the first time is herein reported a 3D-QSAR model which includes a number of chemically diverse Ï 2receptor ligands and well accounts for the individual ligands affinities. These features will ensure prospectively advantageous applications to speed up the identification of new potent and selective Ï 2receptor ligands.