Galectin-8N-Selective 4-Halophenylphthalazinone-Galactals Double π-Stack in a Unique Pocket.

Galectin-8 contains two different carbohydrate recognition domains (CRDs). Selective inhibitors for at least one CRD are desirable for galectin-8 biology studies and potentially for pharmacological purposes. Structure-guided design led to the discovery of potent and selective glycomimetic-heterocycle hybrid ligands, with a 4-(p-bromophenyl)phthalazinone derivative displaying a 34 µM K d for galectin-8N (N-terminal CRD), no binding to galectin-8C (C-terminal CRD), -1, -3, -4N, -7, -9C, or -9N, and >40-fold selectivity over galectin-4C. Selectivity was achieved with the halogenated 4-phenylphthalazinone moiety occupying a galectin-8N-specific sub-pocket. A 1.30 Å resolution X-ray structure revealed the phthalazinone moiety stacking with Arg45 and the 4-bromophenyl moiety stacking both Arg59 and Tyr141 of galectin-8N. Physicochemical and in vitro ADME studies revealed a desirable LogD, which also translated to good passive permeability. The chemical, microsome, and plasma stability support these compounds as promising tool compounds and candidates for hit-to-lead optimization.

Prospective de novo drug design with deep interactome learning.

De novo drug design aims to generate molecules from scratch that possess specific chemical and pharmacological properties. We present a computational approach utilizing interactome-based deep learning for ligand- and structure-based generation of drug-like molecules. This method capitalizes on the unique strengths of both graph neural networks and chemical language models, offering an alternative to the need for application-specific reinforcement, transfer, or few-shot learning. It enables the "zero-shot" construction of compound libraries tailored to possess specific bioactivity, synthesizability, and structural novelty. In order to proactively evaluate the deep interactome learning framework for protein structure-based drug design, potential new ligands targeting the binding site of the human peroxisome proliferator-activated receptor (PPAR) subtype gamma are generated. The top-ranking designs are chemically synthesized and computationally, biophysically, and biochemically characterized. Potent PPAR partial agonists are identified, demonstrating favorable activity and the desired selectivity profiles for both nuclear receptors and off-target interactions. Crystal structure determination of the ligand-receptor complex confirms the anticipated binding mode. This successful outcome positively advocates interactome-based de novo design for application in bioorganic and medicinal chemistry, enabling the creation of innovative bioactive molecules.

Discovery of the Selective and Orally Available Galectin-1 Inhibitor GB1908 as a Potential Treatment for Lung Cancer.

We have previously described a new series of selective and orally available galectin-1 inhibitors resulting in the thiazole-containing glycomimetic GB1490. Here, we show that the introduction of polar substituents to the thiazole ring results in galectin-1-specific compounds with low nM affinities. X-ray structural analysis of a new ligand-galectin-1 complex shows changes in the binding mode and ligand-protein hydrogen bond interactions compared to the GB1490-galectin-1 complex. These new high affinity ligands were further optimized with respect to affinity and ADME properties resulting in the galectin-1-selective GB1908 (Kd galectin-1/3 0.057/6.0 µM). In vitro GB1908 inhibited galectin-1-induced apoptosis in Jurkat cells (IC50 = 850 nM). Pharmacokinetic experiments in mice revealed that a dose of 30 mg/kg b.i.d. results in free levels of GB1908 in plasma over galectin-1 Kd for 24 h. GB1908 dosed with this regimen reduced the growth of primary lung tumor LL/2 in a syngeneic mouse model.