Watermelon: setup and validation of an in silico fragment-based approach.

We present a new computational approach, named Watermelon, designed for the development of pharmacophore models based on receptor structures. The methodology involves the sampling of potential hotspots for ligand interactions within a protein target's binding site, utilising molecular fragments as probes. By employing docking and molecular dynamics (MD) simulations, the most significant interactions formed by these probes within distinct regions of the binding site are identified. These interactions are subsequently transformed into pharmacophore features that delineates key anchoring sites for potential ligands. The reliability of the approach was experimentally validated using the monoacylglycerol lipase (MAGL) enzyme. The generated pharmacophore model captured features representing ligand-MAGL interactions observed in various X-ray co-crystal structures and was employed to screen a database of commercially available compounds, in combination with consensus docking and MD simulations. The screening successfully identified two new MAGL inhibitors with micromolar potency, thus confirming the reliability of the Watermelon approach.

Identification of New GSK3ß Inhibitors through a Consensus Machine Learning-Based Virtual Screening.

Glycogen synthase kinase-3 beta (GSK3ß) is a serine/threonine kinase that plays key roles in glycogen metabolism, Wnt/ß-catenin signaling cascade, synaptic modulation, and multiple autophagy-related signaling pathways. GSK3ß is an attractive target for drug discovery since its aberrant activity is involved in the development of neurodegenerative diseases such as Alzheimer's and Parkinson's disease. In the present study, multiple machine learning models aimed at identifying novel GSK3ß inhibitors were developed and evaluated for their predictive reliability. The most powerful models were combined in a consensus approach, which was used to screen about 2 million commercial compounds. Our consensus machine learning-based virtual screening led to the identification of compounds G1 and G4, which showed inhibitory activity against GSK3ß in the low-micromolar and sub-micromolar range, respectively. These results demonstrated the reliability of our virtual screening approach. Moreover, docking and molecular dynamics simulation studies were employed for predicting reliable binding modes for G1 and G4, which represent two valuable starting points for future hit-to-lead and lead optimization studies.

1-Acetoxypinoresinol, a Lignan from Olives: Insight into Its Characterization, Identification, and Nutraceutical Properties.

Extra virgin olive oil (EVOO) is a symbol of the Mediterranean diet, constituting its primary source of fat. The beneficial effect of EVOO is strictly related to the presence of fatty acids and polyphenols, bioactive compounds endowed with nutraceutical properties. Among EVOO polyphenols, lignans possess a steroid-like chemical structure and are part of the phytoestrogen family, which is renowned for its health properties. The natural lignans (+)-pinoresinol and 1-acetoxypinoresinol (1-AP) are commonly present in olives and in EVOO. Although (+)-pinoresinol is found in different edible plants, such as flaxseed, beans, whole-grain cereals, sesame seeds, and certain vegetables and fruit, 1-AP was exclusively identified in olives in 2000. So far, the scientific literature has extensively covered different aspects of (+)-pinoresinol, including its isolation and nutraceutical properties. In contrast, less is known about the olive lignan 1-AP. Therefore, this review aimed to comprehensively evaluate the more important aspects of 1-AP, collecting all the literature from 2016 to the present, exploring its distribution in different cultivars, analytical isolation and purification, and nutraceutical properties.

Design, synthesis and biological evaluation of arylsulfonamides as ADAMTS7 inhibitors.

The proteolytic activity of the enzyme ADAMTS7 was recently shown to enhance the progression of atherosclerosis, in line with human genetic findings suggesting that ADAMTS7 has a role in the pathophysiology of coronary heart disease. Targeting the active site of ADAMTS7 with a small molecule inhibitor, therefore, has therapeutic potential. Here, we report the design and synthesis of a novel hydroxamate-based arylsulfonamide that is a potent and selective ADAMTS7 inhibitor. In silico studies guided the hit optimization process aiming to improve selectivity of the previously reported (non-selective) inhibitor EDV33. Our lead compound is a p-trifluoromethyl biphenyl sulfonamide, which displayed a 12-fold selectivity for ADAMTS7 (K i = 9 nM) over ADAMTS5 (K i = 110 nM) and an 8-fold increase in inhibition of ADAMTS7 compared to EDV33 (K i = 70 nM). The substitutions switched selectivity and produced a new potent ADAMTS7 inhibitor that can be taken forward for further characterisation.