A 3D Similarity Method for Scaffold Hopping from Known Drugs or Natural Ligands to New Chemotypes

Abstract

A primary goal of 3D similarity searching is to find compounds with similar bioactivity to a reference ligand but with different chemotypes, i.e., "scaffold hopping". However, an adequate description of chemical structures in 3D conformational space is difficult due to the high-dimensionality of the problem. We present an automated method that simplifies flexible 3D chemical descriptions in which clustering techniques traditionally used in data mining are exploited to create "fuzzy" molecular representations called FEPOPS (feature point pharmacophores). The representations can be used for flexible 3D similarity searching given one or more active compounds without a priori knowledge of bioactive conformations or pharmacophores. We demonstrate that similarity searching with FEPOPS significantly enriches for actives taken from in-house high-throughput screening datasets and from MDDR activity classes COX-2, 5-HT3A, and HIV-RT, while also scaffold or ring-system hopping to new chemical frameworks. Further, inhibitors of target proteins (dopamine 2 and retinoic acid receptor) are recalled by FEPOPS by scaffold hopping from their associated endogenous ligands (dopamine and retinoic acid). Importantly, the method excels in comparison to commonly used 2D similarity methods (DAYLIGHT, MACCS, Pipeline Pilot fingerprints) and a commercial 3D method (Pharmacophore Distance Triplets) at finding novel scaffold classes given a single query molecule.

Hierarchical Docking of Databases of Multiple Ligand Conformations

“…The MDDR contains drug-like small molecules annotated for biological activity and, like often, molecular target. It is commonly used to train and test cheminformatics methods for library design, [23,24] pharmacophore fingerprinting [25][26][27][28] and determining drug-likeness [29][30][31]. This annotated database provides a list of likeness ligands that we can track.…”

Quantifying the Relationships among Drug Classes

“…18 Daylight fingerprints were generated from an in-house program based on the Daylight toolkit. MDL Keys, ECFP_4, and FCFP_4 descriptors were generated using standard Pipeline Pilot components; ECFP_4 and FCFP_4 representations were subsequently folded to 1024-bitstrings.…”

Similarity-based virtual screening using 2D fingerprints

“…However, the simple 2D fingerprint continues to be the representation of choice for similarity-based VS, not only because of its computational efficiency but also because of its demonstrated effectiveness in the many comparative studies that have been carried out. Indeed, there is a continuing debate as to whether there is any benefit to be gained from the use of more sophisticated approaches to the computation of molecular similarity (see, e.g., [11,12,[23][24][25][26][27][28][29]). Note that we focus here on the use of 2D fingerprints to compute measures of molecular similarity; there is also an extensive literature associated with their use for applications in molecular diversity and in the clustering of chemical databases (see, e.g., [8,9,[30][31][32][33][34]).…”