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Inhibition of monoglyceride lipase (MGL), also known as monoacylglycerol lipase (MAGL), has emerged as a promising approach for treating neurological diseases. To gain useful insights in the design of agents with balanced potency and reactivity, we investigated the mechanism of MGL carbamoylation by the reference triazole urea SAR629 (IC

The effects of the neurohormone melatonin are mediated by the activation of the GPCRs MT1 and MT2 in a variety of tissues. Crystal structures suggest ligand access to the orthosteric binding site of MT1 and MT2 receptors through a lateral channel between transmembrane (TM) helices IV and V. We investigated the feasibility of this lipophilic entry route for 2-iodomelatonin, a nonselective agonist with a slower dissociation rate from the MT2 receptor, applying enhanced sampling simulations and free-energy calculations. 2-Iodomelatonin unbinding was investigated with steered molecular dynamics simulations which revealed different trajectories passing through the gap between TM helices IV and V for both receptors. For one of these unbinding trajectories from the MT1 receptor, an umbrella-sampling protocol with path-collective variables provided a calculated energy barrier consistent with the experimental dissociation rate. The side-chain flexibility of Tyr5.38 was significantly different in the two receptor subtypes, as assessed by metadynamics simulations, and during ligand unbinding it frequently assumes an open conformation in the MT1 but not in the MT2 receptor, favoring 2-iodomelatonin egress. Taken together, our simulations are consistent with the possibility that the gap between TM IV and V is a way of connecting the orthosteric binding site and the membrane core for lipophilic melatonin receptor ligands. Our simulations also suggest that the open state of Tyr5.38 generates a small pocket on the surface of MT1 receptor, which could participate in the recognition of MT1-selective ligands and may be exploited in the design of new selective compounds.

Irreversible epidermal growth factor receptor (EGFR) inhibitors can circumvent resistance to first-generation ATP-competitive inhibitors in the treatment of nonsmall-cell lung cancer. They covalently bind a noncatalytic cysteine (Cys797) at the surface of EGFR active site by an acrylamide warhead. Herein, we used a hybrid quantum mechanics/molecular mechanics (QM/MM) potential in combination with umbrella sampling in the path-collective variable space to investigate the mechanism of alkylation of Cys797 by the prototypical covalent inhibitor N-(4-anilinoquinazolin-6-yl) acrylamide. Calculations show that Cys797 reacts with the acrylamide group of the inhibitor through a direct addition mechanism, with Asp800 acting as a general base/general acid in distinct steps of the reaction. The obtained reaction free energy is negative (ΔA = -12 kcal/mol) consistent with the spontaneous and irreversible alkylation of Cys797 by N-(4-anilinoquinazolin-6-yl) acrylamide. Our calculations identify desolvation of Cys797 thiolate anion as a key step of the alkylation process, indicating that changes in the intrinsic reactivity of the acrylamide would have only a minor impact on the inhibitor potency.

The duration of drug efficacy in vivo is a key aspect primarily addressed during the lead optimization phase of drug discovery. Hence, the availability of robust computational approaches that can predict the residence time of a compound at its target would accelerate candidate selection. Nowadays the theoretical prediction of this parameter is still very challenging. Starting from methods reported in the literature, we set up and validated a new metadynamics (META-D)-based protocol that was used to rank the experimental residence times of 10 arylpyrazole cyclin-dependent kinase 8 (CDK8) inhibitors for which target-bound X-ray structures are available. The application of reported methods based on the detection of the escape from the first free energy well gave a poor correlation with the experimental values. Our protocol evaluates the energetics of the whole unbinding process, accounting for multiple intermediates and transition states. Using seven collective variables (CVs) encoding both roto-translational and conformational motions of the ligand, a history-dependent biasing potential is deposited as a sum of constant-height Gaussian functions until the ligand reaches an unbound state. The time required to achieve this state is proportional to the integral of the deposited potential over the CV hyperspace. Average values of this time, for replicated META-D simulations, provided an accurate classification of CDK8 inhibitors spanning short, medium, and long residence times.

Developing GPCR homology models for structure-based virtual screening requires the choice of a suitable template and refinement of binding site residues. We explored this systematically for the MT2 melatonin receptor, with the aim to build a receptor homology model that is optimized for the enrichment of active melatoninergic ligands. A set of 12 MT2 melatonin receptor models was built using different GPCR X-ray structural templates and submitted to a virtual screening campaign on a set of compounds composed of 29 known melatonin receptor ligands and 2560 drug-like decoys. To evaluate the effect of including a priori information in receptor models, 12 representative melatonin receptor ligands were placed into the MT2 receptor models in poses consistent with known mutagenesis data and with assessed pharmacophore models. The receptor structures were then adapted to the ligands by induced-fit docking. Most of the 144 ligand-adapted MT2 receptor models showed significant improvements in screening enrichments compared to the unrefined homology models, with some template/refinement combinations giving excellent enrichment factors. The discriminating ability of the models was further tested on the 29 active ligands plus a set of 21 inactive or low-affinity compounds from the same chemical classes. Rotameric states of side chains for some residues, presumed to be involved in the binding process, were correlated with screening effectiveness, suggesting the existence of specific receptor conformations able to recognize active compounds. The top MT2 receptor model was able to identify 24 of 29 active ligands among the first 2% of the screened database. This work provides insights into the use of refined GPCR homology models for virtual screening.

The EPH receptor A2 (EPHA2) represents an attractive anticancer target. With the aim to identify novel EPHA2 receptor antagonists, a virtual screening campaign, combining shape-similarity and docking calculations, was conducted on a set of commercially available compounds. A combined score, taking into account both ligand- and structure-based results, was then used to identify the most promising candidates. Two compounds, selected among the best-ranked ones, were identified as EPHA2 receptor antagonists with micromolar affinity.