Computational Insights into Molecular Activation and Positive Cooperative Mechanisms of FFAR1 Modulators

Assessing the role of residue Phe108 of cytochrome P450 3A4 in allosteric effects of midazolam metabolism

Cytochrome P450 3A4 (CYP3A4) is involved in the metabolism of more drugs in clinical use than any other xenobiotic-metabolizing enzyme. CYP3A4-mediated drug metabolism is usually allosterically modulated by substrate concentration (homotropic allostery) and other drugs (heterotropic allostery), exhibiting unusual kinetic profiles and regiospecific metabolism. Recent studies suggest that residue Phe108 (F108) of CYP3A4 may have an important role in drug metabolism. In this work, residue mutations were coupled with well-tempered metadynamics simulations to assess the importance of F108 in the allosteric effects of midazolam metabolism. Comparing the simulation results of the wild-type and mutation systems, we identify that the π-π interaction and steric effect between the F108 side chain and midazolam is favorable for the stable binding of substrate in the active site. F108 also plays an important role in the transition of substrate binding mode, which mainly induces the transition of substrate binding mode by forming π-π interactions with multiple aromatic rings of the substrate. Moreover, the side chain of F108 is closely related to the radius and depth of the 2a and 2f channels, and F108 may further regulate drug metabolism by affecting the pathway, orientation, or time of substrate entry into the CYP3A4 active site or product egress from the active site. Altogether, we suggest that F108 affects drug metabolism and regulatory mechanisms by affecting substrate binding stability, binding mode transition, and channel characteristics of CYP3A4. Our findings could promote the understanding of complicated allosteric mechanisms in CYP3A4-mediated drug metabolism, and the knowledge could be used for drug development and disease treatment.

Intermolecular Interactions in G Protein-Coupled Receptor Allosteric Sites at the Membrane Interface from Molecular Dynamics Simulations and Quantum Chemical Calculations

Allosteric modulators are called promising candidates in G protein-coupled receptor (GPCR) drug development by displaying subtype selectivity and more specific receptor modulation. Among the allosteric sites known to date, cavities at the receptor-lipid interface represent an uncharacteristic binding location that raises many questions about the ligand interactions and stability, the binding site structure, and how all of these are affected by lipid molecules. In this work, we analyze interactions in the allosteric sites of the PAR2, C5aR1, and GCGR receptors in three lipid compositions using molecular dynamics simulations. In addition, we performed quantum chemical calculations involving the symmetry-adapted perturbation theory (SAPT) and the natural population analysis to quantify the strength of intermolecular interactions. We show that besides classical hydrogen bonds, weak polar interactions such as O-HC, O-Br, and long-range electrostatics with the backbone amides contribute to the stability of allosteric modulators at the receptor-lipid interface. The allosteric cavities are detectable in various membrane compositions. The availability of polar atoms for interactions in such cavities can be assessed by water molecules from simulations. Although ligand-lipid interactions are weak, lipid tails play a role in ligand binding pose stability and the size of allosteric cavities. We discuss physicochemical aspects of ligand binding at the receptor-lipid interface and suggest a compound library enriched by weak donor groups for ligand search in such sites.

Mechanistic Studies on the Stereoselectivity of FFAR1 Modulators

Free fatty acid receptor 1 (FFAR1) is a potential therapeutic target for the treatment of type 2 diabetes (T2D). It has been validated that agonists targeting FFAR1 can achieve the initial therapeutic endpoints of T2D, and the epimer agonists (R,S) AM-8596 can activate FFAR1 differently, with one acting as a partial agonist and the other as a full agonist. Up to now, the origin of the stereoselectivity of FFAR1 agonists remains elusive. In this work, we used molecular simulation methods to elucidate the mechanism of the stereoselectivity of the FFAR1 agonists (R)-AM-8596 and (S)-AM-8596. We found that the full agonist (R)-AM-8596 disrupts the residue interaction network around the receptor binding pocket and promotes the opening of the binding site for the G-protein, thereby resulting in the full activation of FFAR1. In contrast, the partial agonist (S)-AM-8596 forms stable electrostatic interactions with FFAR1, which stabilizes the residue network and hinders the conformational transition of the receptor. Our work thus clarifies the selectivity and underlying molecular activation mechanism of FFAR1 agonists.

In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study

Free fatty acid receptor 1 (FFA1) stimulates insulin secretion in pancreatic β-cells. An advantage of therapies that target FFA1 is their reduced risk of hypoglycemia relative to common type 2 diabetes treatments. In this work, quantitative structure–activity relationship (QSAR) approach was used to construct models to identify possible FFA1 agonists by applying four different machine-learning algorithms. The best model (M2) meets the Tropsha’s test requirements and has the statistics parameters R² = 0.843, Q²_CV = 0.785, and Q²_ext = 0.855. Also, coverage of 100% of the test set based on the applicability domain analysis was obtained. Furthermore, a deep analysis based on the ADME predictions, molecular docking, and molecular dynamics simulations was performed. The lipophilicity and the residue interactions were used as relevant criteria for selecting a candidate from the screening of the DiaNat and DrugBank databases. Finally, the FDA-approved drugs bilastine, bromfenac, and fenofibric acid are suggested as potential and lead FFA1 agonists.

Ensemble-based screening of natural products and FDA-approved drugs identified potent inhibitors of SARS-CoV-2 that work with two distinct mechanisms

The recent outbreak of SARS-CoV-2 is responsible for high morbidity and mortality rate across the globe. This requires an urgent identification of drugs and other interventions to overcome this pandemic. Computational drug repurposing represents an alternative approach to provide a more effective approach in search for COVID-19 drugs. Selected natural product known to have antiviral activities were screened, and based on their hits; a similarity search with FDA approved drugs was performed using computational methods. Obtained drugs from similarity search were assessed for their stability and inhibition against SARS-CoV-2 targets. Diosmin (DB08995) was found to be a promising drug that works with two distinct mechanisms, preventing viral replication and viral fusion into the host cell. Isoquercetin (DB12665) and rutin (DB01698) work by inhibiting viral replication and preventing cell entry, respectively. Our analysis based on molecular dynamics simulation and MM-PBSA binding free energy calculation suggests that diosmin, isoquercetin, rutin and other similar flavone glycosides could serve as SARS-CoV-2 inhibitor, hence an alternative solution to treat COVID-19 upon further clinical validation.

Addressing free fatty acid receptor 1 (FFAR1) activation using supervised molecular dynamics

The free fatty acid receptor 1 (FFAR1, formerly GPR40), is a potential G protein-coupled receptor (GPCR) target for the treatment of type 2 diabetes mellitus (T2DM), as it enhances glucose-dependent insulin secretion upon activation by endogenous long-chain free fatty acids. The presence of two allosterically communicating binding sites and the lack of the conserved GPCR structural motifs challenge the general knowledge of its activation mechanism. To date, four X-ray crystal structures are available for computer-aided drug design. In this study, we employed molecular dynamics (MD) and supervised molecular dynamics (SuMD) to deliver insights into the (un)binding mechanism of the agonist MK-8666, and the allosteric communications between the two experimentally determined FFAR1 binding sites. We found that FFAR1 extracellular loop 2 (ECL2) mediates the binding of the partial agonist MK-8666. Moreover, simulations showed that the agonists MK-8666 and AP8 are reciprocally stabilized and that AP8 influences MK-8666 unbinding from FFAR1.