MolShaCS: A free and open source tool for ligand similarity identification based on Gaussian descriptors

Molecular similarity evaluation is an important step in most drug development strategies, since molecular similarity is usually related to functional similarity. Here, we developed a method based on the Gaussian description of molecular shape and charge distribution for molecular similarity identification. The method was evaluated using the Directory of Useful Decoys (DUD) and a retrospective test. Enrichment factors computed for DUD targets showed that the proposed method performs very well in recognizing molecules with similar physicochemical properties and dissimilar topologies, reaching an average AUC of 0.63 and enrichment factor of 10 at 0.5% of decoys. A retrospective test also showed that nine mineralocorticoid ligands were ranked among the top ten molecules in a search of a database of approved drugs for molecules similar to aldosterone. Altogether, these data show that the Gaussian-based description of molecular shape and charge distribution implemented in the program MolShaCS is an efficient method for molecular similarity identification. The program is publicly available at the address http://www.ifsc.usp.br/biotechmol.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► A Gaussian description of molecular shape and charge is proposed. ► A computational tool was developed and tested against the DUD database. ► MolShaCS was found to be very efficient in recovering active molecules. ►MolShaCS ranked 9 real ligands among the top 10 ligands in the DrugBank dataset.