21 research outputs found

    Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A<sub>3</sub> Receptor

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    A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol–1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand’s unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol–1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times

    Free Energy Calculations Reveal the Origin of Binding Preference for Aminoadamantane Blockers of Influenza A/M2TM Pore

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    Aminoadamantane derivatives, such as amantadine and rimantadine, have been reported to block the M2 membrane protein of influenza A virus (A/M2TM), but their use has been discontinued due to reported resistance in humans. Understanding the mechanism of action of amantadine derivatives could assist the development of novel potent inhibitors that overcome A/M2TM resistance. Here, we use Free Energy Perturbation calculations coupled with Molecular Dynamics simulations (FEP/MD) to rationalize the thermodynamic origin of binding preference of several aminoadamantane derivatives inside the A/M2TM pore. Our results demonstrate that apart from crucial protein–ligand intermolecular interactions, the flexibility of the protein, the water network around the ligand, and the desolvation free energy penalty to transfer the ligand from the aqueous environment to the transmembrane region are key elements for the binding preference of these compounds and thus for lead optimization. The high correlation of the FEP/MD results with available experimental data (R<sup>2</sup> = 0.85) demonstrates that this methodology holds predictive value and can be used to guide the optimization of drug candidates binding to membrane proteins

    Interpreting Thermodynamic Profiles of Aminoadamantane Compounds Inhibiting the M2 Proton Channel of Influenza A by Free Energy Calculations

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    The development of novel anti-influenza drugs is of great importance because of the capability of influenza viruses to occasionally cross interspecies barriers and to rapidly mutate. One class of anti-influenza agents, aminoadamantanes, including the drugs amantadine and rimantadine now widely abandoned due to virus resistance, bind to and block the pore of the transmembrane domain of the M2 proton channel (M2TM) of influenza A. Here, we present one of the still rare studies that interprets thermodynamic profiles from isothermal titration calorimetry (ITC) experiments in terms of individual energy contributions to binding, calculated by the computationally inexpensive implicit solvent/implicit membrane molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) approach, for aminoadamantane compounds binding to M2TM of the avian “Weybridge” strain. For all eight pairs of aminoadamantane compounds considered, the trend of the predicted relative binding free energies and their individual components, effective binding energies and changes in the configurational entropy, agrees with experimental measures (ΔΔ<i>G</i>, ΔΔ<i>H</i>, <i>T</i>ΔΔ<i>S</i>) in 88, 88, and 50% of the cases. In addition, information yielded by the MM-PBSA approach about determinants of binding goes beyond that available in component quantities (Δ<i>H</i>, Δ<i>S</i>) from ITC measurements. We demonstrate how one can make use of such information to link thermodynamic profiles from ITC with structural causes on the ligand side and, ultimately, to guide decision making in lead optimization in a prospective manner, which results in an aminoadamantane derivative with improved binding affinity against M2TM<sub>Weybridge</sub>

    Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure−Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations

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    Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]​pyridines L2–L10, A15, and A17 as low-micromolar to low-nanomolar A1R/A3R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]​pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A1R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L2506.51 to alanine increased the binding affinity of A17 at A1R. We explored the structure–activity relationships against A1R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor–membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies

    Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure−Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations

    No full text
    Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]​pyridines L2–L10, A15, and A17 as low-micromolar to low-nanomolar A1R/A3R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]​pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A1R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L2506.51 to alanine increased the binding affinity of A17 at A1R. We explored the structure–activity relationships against A1R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor–membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies

    Discovery of Novel Adenosine Receptor Antagonists through a Combined Structure- and Ligand-Based Approach Followed by Molecular Dynamics Investigation of Ligand Binding Mode

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    An intense effort is made by pharmaceutical and academic research laboratories to identify and develop selective antagonists for each adenosine receptor (AR) subtype as potential clinical candidates for “soft” treatment of various diseases. Crystal structures of subtypes A<sub>2A</sub> and A<sub>1</sub>ARs offer exciting opportunities for structure-based drug design. In the first part of the present work, Maybridge HitFinder library of 14400 compounds was utilized to apply a combination of structure-based against the crystal structure of A<sub>2A</sub>AR and ligand-based methodologies. The docking poses were rescored by CHARMM energy minimization and calculation of the desolvation energy using Poisson–Boltzmann equation electrostatics. Out of the eight selected and tested compounds, five were found positive hits (63% success). Although the project was initially focused on targeting A<sub>2A</sub>AR, the identified antagonists exhibited low micromolar or micromolar affinity against A<sub>2A</sub>/A<sub>3</sub>, ARs, or A<sub>3</sub>AR, respectively. Based on these results, 19 compounds characterized by novel chemotypes were purchased and tested. Sixteen of them were identified as AR antagonists with affinity toward combinations of the AR family isoforms (A<sub>2A</sub>/A<sub>3</sub>, A<sub>1</sub>/A<sub>3</sub>, A<sub>1</sub>/A<sub>2A</sub>/A<sub>3</sub>, and A<sub>3</sub>). The second part of this work involves the performance of hundreds of molecular dynamics (MD) simulations of complexes between the ARs and a total of 27 ligands to resolve the binding interactions of the active compounds, which were not achieved by docking calculations alone. This computational work allowed the prediction of stable and unstable complexes which agree with the experimental results of potent and inactive compounds, respectively. Of particular interest is that the 2-amino-thiophene-3-carboxamides, 3-acylamino-5-aryl-thiophene-2-carboxamides, and carbonyloxycarboximidamide derivatives were found to be selective and possess a micromolar to low micromolar affinity for the A<sub>3</sub> receptor

    Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure−Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations

    No full text
    Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]​pyridines L2–L10, A15, and A17 as low-micromolar to low-nanomolar A1R/A3R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]​pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A1R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L2506.51 to alanine increased the binding affinity of A17 at A1R. We explored the structure–activity relationships against A1R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor–membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies

    Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure−Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations

    No full text
    Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]​pyridines L2–L10, A15, and A17 as low-micromolar to low-nanomolar A1R/A3R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]​pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A1R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L2506.51 to alanine increased the binding affinity of A17 at A1R. We explored the structure–activity relationships against A1R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor–membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies

    Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure−Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations

    No full text
    Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]​pyridines L2–L10, A15, and A17 as low-micromolar to low-nanomolar A1R/A3R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]​pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A1R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L2506.51 to alanine increased the binding affinity of A17 at A1R. We explored the structure–activity relationships against A1R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor–membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies

    Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure−Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations

    No full text
    Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]​pyridines L2–L10, A15, and A17 as low-micromolar to low-nanomolar A1R/A3R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]​pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A1R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L2506.51 to alanine increased the binding affinity of A17 at A1R. We explored the structure–activity relationships against A1R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor–membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies
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