Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment

Abstract

Chemical features of small molecules can be abstracted to 3D pharmacophore models, which are easy to generate, interpret, and adapt by medicinal chemists. Three-dimensional pharmacophores can be used to efficiently match and align molecules according to their chemical feature pattern, which facilitates the virtual screening of even large compound databases. Existing alignment methods, used in computational drug discovery and bio-activity prediction, are often not suitable for finding matches between pharmacophores accurately as they purely aim to minimize RMSD or maximize volume overlap, when the actual goal is to match as many features as possible within the positional tolerances of the pharmacophore features. As a consequence, the obtained alignment results are often suboptimal in terms of the number of geometrically matched feature pairs, which increases the false-negative rate, thus negatively affecting the outcome of virtual screening experiments. We addressed this issue by introducing a new alignment algorithm, Greedy 3-Point Search (G3PS), which aims at finding optimal alignments by using a matching-feature-pair maximizing search strategy while at the same time being faster than competing methods.

NRF2 in dermo‐cosmetic: From scientific knowledge to skin care products

“…The structure of the Keap1 protein has been resolved experimentally: today, more than 30 mutation‐free structures with ligands are present in the Protein Data Bank (PDB), 186 four of which correspond to the Keap1–Nrf2 complex. Our group used five of these structures (PDB entries: 2FLU, 98 3VNG, 187 4IFN, 188 4IN4, 105 4IQK 105 ) to create 21 pharmacophore models 189–191 using Catalyst software integrated into the Discovery Studio platform 192 . These models cover the diversity of Keap1–ligand and Keap1–Nrf2 interactions.…”