Scaffold-Hopping from Synthetic Drugs by Holistic Molecular Representation

Abstract

The discovery of novel ligand chemotypes allows to explore uncharted regions in chemical space, thereby potentially improving synthetic accessibility, potency, and the drug-likeness of molecules. Here, we demonstrate the scaffold-hopping ability of the new Weighted Holistic Atom Localization and Entity Shape (WHALES) molecular descriptors compared to seven state-of-the-art molecular representations on 30,000 compounds and 182 biological targets. In a prospective application, we apply WHALES to the discovery of novel retinoid X receptor (RXR) modulators. WHALES descriptors identified four agonists with innovative molecular scaffolds, populating uncharted regions of the chemical space. One of the agonists, possessing a rare non-acidic chemotype, revealed high selectivity on 12 nuclear receptors and comparable efficacy as bexarotene on induction of ATP-binding cassette transporter A1, angiopoietin like protein 4 and apolipoprotein E. The outcome of this research supports WHALES as an innovative tool to explore novel regions of the chemical space and to detect novel bioactive chemotypes by straightforward similarity searching.

Establishing an Analogue Based In Silico Pipeline in the Pursuit of Novel Inhibitory Scaffolds against the SARS Coronavirus 2 Papain-Like Protease

“…The use of GRL-0617 as a reference in the virtual screens facilitated the initial identification of 24 distinct scaffolds. Scaffold hopping has consistently been employed as an important tool in drug discovery and has yielded many active ligands thus far [ 91 , 92 , 93 ]. The availability of more than one scaffold is an advantageous starting point in any drug development process, given that attrition rates are high due to either lack of potency or poor pharmacokinetic profiles.…”

Design of Natural‐Product‐Inspired Multitarget Ligands by Machine Learning

“…(−)‐Galantamine ( 1 ) was used to computationally screen a library of 3 383 942 commercially available compounds. The partial charge distribution and three‐dimensional shape of compounds were captured using the weighted holistic atom localization and entity shape (WHALES) descriptors, which were specifically developed for scaffold‐hopping from natural products to synthetic compounds. WHALES capture the shape and partial charge distributions of a three‐dimensional (3D) molecular conformer in terms of atom‐centered Mahalanobis distances, weighted by atomic partial charges.…”

“…(a) WHALES descriptors were calculated with Python v. 2.7, using in‐house software deposited on GitHub (https://github.com/grisoniFr/whales_descriptors.git, v.1). Gasteiger–Marsili partial charges were used as atomic description, as they resulted the best compromise between enrichment ability and scaffold‐hopping, and were computed using RDKit v. 2015.09.2 (default settings). Commercial library compounds and galantamine WHALES descriptors were normalized (Gaussian normalization) prior to virtual screening; commercial compounds were then sorted according to their Euclidean distance to galantamine (the lower, the better).…”

“…Starting from galantaminea sm ultitarget template,w ed eveloped af ully automated selection and target profiling program to identify natural-product-inspired small molecules with multitarget activity on enzymes and receptors related to Alzheimer'sd isease ( Figure 2). (À)-Galantamine (1)w as used to computationally screen al ibrary of 3383 942 commercially availablec ompounds.T he partial charge distribution and three-dimensional shape of compounds were captured using the weighted holistica toml ocalization and entity shape (WHALES) descriptors, [16,17] which were specifically developed for scaffold-hopping from natural products to synthetic compounds. WHALES [16] capturethe shape and partial chargedistributions of at hree-dimensional( 3D) molecular conformer in terms of atom-centered Mahalanobis distances, [18] weighted by atomic partial charges.…”

[Special Issue for Honor Award dedicating to Prof Kimito Funatsu](Mini-review)Meanings of the Honor Award for Prof Kimito Funatsu

“…From the resulting fine-tuned model, 1,000 SMILES strings were generated by applying fragment growing form from carboxy group and ranked according to the predicted biological target and similarity to know bioactivities. Predicted top-ranking compounds included reasonable activity on PPAR [17][18][19]. Miyao, Funatsu et al suggested a fundamental method for exhaustive structure generation by solving inverse QSAR equations in 2010 [20].…”