Structure-Based Virtual Screening of MT₂ Melatonin Receptor: Influence of Template Choice and Structural Refinement

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

Unbinding Kinetics of Muscarinic M3 Receptor Antagonists Explained by Metadynamics Simulations

The residence time (RT), the time for which a drug remains bound to its biological target, is a critical parameter for drug design. The prediction of this key kinetic property has been proven to be challenging and computationally demanding in the framework of atomistic simulations. In the present work, we setup and applied two distinct metadynamics protocols to estimate the RTs of muscarinic M3 receptor antagonists. In the first method, derived from the conformational flooding approach, the kinetics of unbinding is retrieved from a physics-based parameter known as the acceleration factor α (i.e., the running average over time of the potential deposited in the bound state). Such an approach is expected to recover the absolute RT value for a compound of interest. In the second method, known as the tMETA‑D approach, a qualitative estimation of the RT is given by the time of simulation required to drive the ligand from the binding site to the solvent bulk. This approach has been developed to reproduce the change of experimental RTs for compounds targeting the same target. Our analysis shows that both computational protocols are able to rank compounds in agreement with their experimental RTs. Quantitative structure–kinetics relationship (SKR) models can be identified and employed to predict the impact of a chemical modification on the experimental RT once a calibration study has been performed

Unbinding Kinetics of Muscarinic M3 Receptor Antagonists Explained by Metadynamics Simulations

The residence time (RT), the time for which a drug remains bound to its biological target, is a critical parameter for drug design. The prediction of this key kinetic property has been proven to be challenging and computationally demanding in the framework of atomistic simulations. In the present work, we setup and applied two distinct metadynamics protocols to estimate the RTs of muscarinic M3 receptor antagonists. In the first method, derived from the conformational flooding approach, the kinetics of unbinding is retrieved from a physics-based parameter known as the acceleration factor α (i.e., the running average over time of the potential deposited in the bound state). Such an approach is expected to recover the absolute RT value for a compound of interest. In the second method, known as the tMETA‑D approach, a qualitative estimation of the RT is given by the time of simulation required to drive the ligand from the binding site to the solvent bulk. This approach has been developed to reproduce the change of experimental RTs for compounds targeting the same target. Our analysis shows that both computational protocols are able to rank compounds in agreement with their experimental RTs. Quantitative structure–kinetics relationship (SKR) models can be identified and employed to predict the impact of a chemical modification on the experimental RT once a calibration study has been performed

Unbinding Kinetics of Muscarinic M3 Receptor Antagonists Explained by Metadynamics Simulations

The residence time (RT), the time for which a drug remains bound to its biological target, is a critical parameter for drug design. The prediction of this key kinetic property has been proven to be challenging and computationally demanding in the framework of atomistic simulations. In the present work, we setup and applied two distinct metadynamics protocols to estimate the RTs of muscarinic M3 receptor antagonists. In the first method, derived from the conformational flooding approach, the kinetics of unbinding is retrieved from a physics-based parameter known as the acceleration factor α (i.e., the running average over time of the potential deposited in the bound state). Such an approach is expected to recover the absolute RT value for a compound of interest. In the second method, known as the tMETA‑D approach, a qualitative estimation of the RT is given by the time of simulation required to drive the ligand from the binding site to the solvent bulk. This approach has been developed to reproduce the change of experimental RTs for compounds targeting the same target. Our analysis shows that both computational protocols are able to rank compounds in agreement with their experimental RTs. Quantitative structure–kinetics relationship (SKR) models can be identified and employed to predict the impact of a chemical modification on the experimental RT once a calibration study has been performed

Unbinding Kinetics of Muscarinic M3 Receptor Antagonists Explained by Metadynamics Simulations

The residence time (RT), the time for which a drug remains bound to its biological target, is a critical parameter for drug design. The prediction of this key kinetic property has been proven to be challenging and computationally demanding in the framework of atomistic simulations. In the present work, we setup and applied two distinct metadynamics protocols to estimate the RTs of muscarinic M3 receptor antagonists. In the first method, derived from the conformational flooding approach, the kinetics of unbinding is retrieved from a physics-based parameter known as the acceleration factor α (i.e., the running average over time of the potential deposited in the bound state). Such an approach is expected to recover the absolute RT value for a compound of interest. In the second method, known as the tMETA‑D approach, a qualitative estimation of the RT is given by the time of simulation required to drive the ligand from the binding site to the solvent bulk. This approach has been developed to reproduce the change of experimental RTs for compounds targeting the same target. Our analysis shows that both computational protocols are able to rank compounds in agreement with their experimental RTs. Quantitative structure–kinetics relationship (SKR) models can be identified and employed to predict the impact of a chemical modification on the experimental RT once a calibration study has been performed

Unbinding Kinetics of Muscarinic M3 Receptor Antagonists Explained by Metadynamics Simulations

The residence time (RT), the time for which a drug remains bound to its biological target, is a critical parameter for drug design. The prediction of this key kinetic property has been proven to be challenging and computationally demanding in the framework of atomistic simulations. In the present work, we setup and applied two distinct metadynamics protocols to estimate the RTs of muscarinic M3 receptor antagonists. In the first method, derived from the conformational flooding approach, the kinetics of unbinding is retrieved from a physics-based parameter known as the acceleration factor α (i.e., the running average over time of the potential deposited in the bound state). Such an approach is expected to recover the absolute RT value for a compound of interest. In the second method, known as the tMETA‑D approach, a qualitative estimation of the RT is given by the time of simulation required to drive the ligand from the binding site to the solvent bulk. This approach has been developed to reproduce the change of experimental RTs for compounds targeting the same target. Our analysis shows that both computational protocols are able to rank compounds in agreement with their experimental RTs. Quantitative structure–kinetics relationship (SKR) models can be identified and employed to predict the impact of a chemical modification on the experimental RT once a calibration study has been performed

Metadynamics Simulations Distinguish Short- and Long-Residence-Time Inhibitors of Cyclin-Dependent Kinase 8

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

Combining Ligand- and Structure-Based Approaches for the Discovery of New Inhibitors of the EPHA2–ephrin-A1 Interaction

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

Atropisomerism and Conformational Equilibria: Impact on PI3Kδ Inhibition of 2‑((6-Amino‑9<i>H</i>‑purin-9-yl)methyl)-5-methyl-3‑(<i>o</i>‑tolyl)quinazolin-4(3<i>H</i>)‑one (IC87114) and Its Conformationally Restricted Analogs

IC87114 [compound <b>1</b>, (2-((6-amino-9<i>H</i>-purin-9-yl)­methyl)-5-methyl-3-(<i>o</i>-tolyl)­quinazolin-4­(3<i>H</i>)-one)] is a potent PI3K inhibitor selective for the δ isoform. As predicted by molecular modeling calculations, rotation around the bond connecting the quinazolin-4­(3<i>H</i>)-one nucleus to the <i>o</i>-tolyl is sterically hampered, which leads to separable conformers with axial chirality (i.e., atropisomers). After verifying that the a<i>S</i> and a<i>R</i> isomers of compound <b>1</b> do not interconvert in solution, we investigated how biological activity is influenced by axial chirality and conformational equilibrium. The a<i>S</i> and a<i>R</i> atropisomers of <b>1</b> were equally active in the PI3Kδ assay. Conversely, the introduction of a methyl group at the methylene hinge connecting the 6-amino-9<i>H</i>-purin-9-yl pendant to the quinazolin-4­(3<i>H</i>)-one nucleus of both a<i>S</i> and a<i>R</i> isomers of <b>1</b> had a critical effect on the inhibitory activity, indicating that modulation of the conformational space accessible for the two bonds departing from the central methylene considerably affects the binding of compound <b>1</b> analogues to PI3Kδ enzyme

Atropisomerism and Conformational Equilibria: Impact on PI3Kδ Inhibition of 2‑((6-Amino‑9<i>H</i>‑purin-9-yl)methyl)-5-methyl-3‑(<i>o</i>‑tolyl)quinazolin-4(3<i>H</i>)‑one (IC87114) and Its Conformationally Restricted Analogs

IC87114 [compound <b>1</b>, (2-((6-amino-9<i>H</i>-purin-9-yl)­methyl)-5-methyl-3-(<i>o</i>-tolyl)­quinazolin-4­(3<i>H</i>)-one)] is a potent PI3K inhibitor selective for the δ isoform. As predicted by molecular modeling calculations, rotation around the bond connecting the quinazolin-4­(3<i>H</i>)-one nucleus to the <i>o</i>-tolyl is sterically hampered, which leads to separable conformers with axial chirality (i.e., atropisomers). After verifying that the a<i>S</i> and a<i>R</i> isomers of compound <b>1</b> do not interconvert in solution, we investigated how biological activity is influenced by axial chirality and conformational equilibrium. The a<i>S</i> and a<i>R</i> atropisomers of <b>1</b> were equally active in the PI3Kδ assay. Conversely, the introduction of a methyl group at the methylene hinge connecting the 6-amino-9<i>H</i>-purin-9-yl pendant to the quinazolin-4­(3<i>H</i>)-one nucleus of both a<i>S</i> and a<i>R</i> isomers of <b>1</b> had a critical effect on the inhibitory activity, indicating that modulation of the conformational space accessible for the two bonds departing from the central methylene considerably affects the binding of compound <b>1</b> analogues to PI3Kδ enzyme