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Biased agonists, which selectively stimulate certain signaling pathways controlled by a G protein-coupled receptor (GPCR), hold great promise as drugs that maximize efficacy while minimizing dangerous side effects. Biased agonists of the μ-opioid receptor (μOR) are of particular interest as a means to achieve analgesia through G protein signaling without dose-limiting side effects such as respiratory depression and constipation. Rational structure-based design of biased agonists remains highly challenging, however, because the ligand-mediated interactions that are key to activation of each signaling pathway remain unclear. We identify several compounds for which the R- and S-enantiomers have distinct bias profiles at the μOR. These compounds serve as excellent comparative tools to study bias because the identical physicochemical properties of enantiomer pairs ensure that differences in bias profiles are due to differences in interactions with the μOR binding pocket. Atomic-level simulations of compounds at μOR indicate that R- and S-enantiomers adopt different poses that form distinct interactions with the binding pocket. A handful of specific interactions with highly conserved binding pocket residues appear to be responsible for substantial differences in arrestin recruitment between enantiomers. Our results offer guidance for rational design of biased agonists at μOR and possibly at related GPCRs.

Allostery describes the functional coupling between sites in biomolecules. Recently, the role of changes in protein dynamics for allosteric communication has been highlighted. A quantitative and predictive description of allostery is fundamental for understanding biological processes. Here, we integrate an ensemble-based perturbation approach with the analysis of biomolecular rigidity and flexibility to construct a model of dynamic allostery. Our model, by definition, excludes the possibility of conformational changes, evaluates static, not dynamic, properties of molecular systems, and describes allosteric effects due to ligand binding in terms of a novel free-energy measure. We validated our model on three distinct biomolecular systems: eglin c, protein tyrosine phosphatase 1B, and the lymphocyte function-associated antigen 1 domain. In all cases, it successfully identified key residues for signal transmission in very good agreement with the experiment. It correctly and quantitatively discriminated between positively or negatively cooperative effects for one of the systems. Our model should be a promising tool for the rational discovery of novel allosteric drugs.

The discovery and selection of a highly potent and selective NaV1.7 inhibitor PF-06456384, designed specifically for intravenous infusion, is disclosed. Extensive in vitro pharmacology and ADME profiling followed by in vivo preclinical PK and efficacy model data are discussed. A proposed protein-ligand binding mode for this compound is also provided to rationalise the high levels of potency and selectivity over inhibition of related sodium channels. To further support the proposed binding mode, potent conjugates are described which illustrate the potential for development of chemical probes to enable further target evaluation.

The development of G protein-biased agonists for the μ-opioid receptor (MOR) offers a clear drug discovery rationale for improved analgesia and reduced side-effects of opiate pharmacotherapy. However, our understanding of the molecular mechanisms governing ligand bias is limited, which hinders our ability to rationally design biased compounds. We have investigated the role of MOR binding site residues W320 and Y328 in controlling bias, by receptor mutagenesis. The pharmacology of a panel of ligands in a cAMP and a β-arrestin2 assay were compared between the wildtype and mutated receptors, with bias factors calculated by operational analysis using ΔΔlog(τ/KA) values. [3H]diprenorphine competition binding was used to estimate affinity changes. Introducing the mutations W320A and Y328F caused changes in pathway bias, with different patterns of change between ligands. For example, DAMGO increased relative β-arrestin2 activity at the W320A mutant, whilst its β-arrestin2 response was completely lost at Y328F. In contrast, endomorphin-1 gained activity with Y328F but lost activity at W320A, in both pathways. For endomorphin-2 there was a directional shift from cAMP bias at the wildtype towards more β-arrestin2 bias at W320A. We also observe clear uncoupling between mutation-driven changes in function and binding affinity. These findings suggest that the mutations influenced the balance of pathway activation in a ligand-specific manner, thus identifying residues in the MOR binding pocket that govern ligand bias. This increases our understanding of how ligand/receptor binding interactions can be translated into agonist-specific pathway activation.

Valproic acid (VPA) is an anticonvulsant drug that is also used to treat migraines and bipolar disorder. Its proposed biological targets include human voltage-gated sodium channels, among other membrane proteins. We used the prokaryotic NavMs sodium channel, which has been shown to be a good exemplar for drug binding to human sodium channels, to examine the structural and functional interactions of VPA. Thermal melt synchrotron radiation circular dichroism spectroscopic binding studies of the full-length NavMs channel (which includes both pore and voltage sensor domains), and a pore-only construct, undertaken in the presence and absence of VPA, indicated that the drug binds to and destabilizes the channel, but not the pore-only construct. This is in contrast to other antiepileptic compounds that have previously been shown to bind in the central hydrophobic core of the pore region of the channel, and that tend to increase the thermal stability of both pore-only constructs and full-length channels. Molecular docking studies also indicated that the VPA binding site is associated with the voltage sensor, rather than the hydrophobic cavity of the pore domain. Electrophysiological studies show that VPA influences the block and inactivation rates of the NavMs channel, although with lower efficacy than classical channel-blocking compounds. It thus appears that, while VPA is capable of binding to these voltage-gated sodium channels, it has a very different mode and site of action than other anticonvulsant compounds.

Summary Small conductance potassium (SK) ion channels define neuronal firing rates by conducting the after-hyperpolarization current. They are key targets in developing therapies where neuronal firing rates are dysfunctional, such as in epilepsy, Parkinson's, and amyotrophic lateral sclerosis (ALS). Here, we characterize a binding pocket situated at the intracellular interface of SK2 and calmodulin, which we show to be shared by multiple small-molecule chemotypes. Crystallization of this complex revealed that riluzole (approved for ALS) and an analog of the anti-ataxic agent (4-chloro-phenyl)-[2-(3,5-dimethyl-pyrazol-1-yl)-pyrimidin-4-yl]-amine (CyPPA) bind to and allosterically modulate via this site. Solution-state nuclear magnetic resonance demonstrates that riluzole, NS309, and CyPPA analogs bind at this bipartite pocket. We demonstrate, by patch-clamp electrophysiology, that both classes of ligand interact with overlapping but distinct residues within this pocket. These data define a clinically important site, laying the foundations for further studies of the mechanism of action of riluzole and related molecules.

Selective modulators of the γ-amino butyric acid (GABAA) family of receptors have the potential to treat a range of disease states related to cognition, pain, and anxiety. While the development of various α subunit-selective modulators is currently underway for the treatment of anxiety disorders, a mechanistic understanding of the correlation between their bioactivity and efficacy, based on ligand–target interactions, is currently still lacking. In order to alleviate this situation, in the current study we have analyzed, using ligand- and structure-based methods, a data set of 5440 GABAA modulators. The Spearman correlation (ρ) between binding activity and efficacy of compounds was calculated to be 0.008 and 0.31 against the α1 and α2 subunits of GABA receptor, respectively; in other words, the compounds had little diversity in structure and bioactivity, but they differed significantly in efficacy. Two compounds were selected as a case study for detailed interaction analysis due to the small difference in their structures and affinities (ΔpKi(comp1_α1 – comp2_α1) = 0.45 log units, ΔpKi(comp1_α2 – comp2_α2) = 0 log units) as compared to larger relative efficacies (ΔRE(comp1_α1 – comp2_α1) = 1.03, ΔRE(comp1_α2 – comp2_α2) = 0.21). Docking analysis suggested that His-101 is involved in a characteristic interaction of the α1 receptor with both compounds 1 and 2. Residues such as Phe-77, Thr-142, Asn-60, and Arg-144 of the γ chain of the α1γ2 complex also showed interactions with heterocyclic rings of both compounds 1 and 2, but these interactions were disturbed in the case of α2γ2 complex docking results. Binding pocket stability analysis based on molecular dynamics identified three substitutions in the loop C region of the α2 subunit, namely, G200E, I201T, and V202I, causing a reduction in the flexibility of α2 compared to α1. These amino acids in α2, as compared to α1, were also observed to decrease the vibrational and dihedral entropy and to increase the hydrogen bond content in α2 in the apo state. However, freezing of both α1 and α2 was observed in the ligand-bound state, with an increased number of internal hydrogen bonds and increased entropy. Therefore, we hypothesize that the amino acid differences in the loop C region of α2 are responsible for conformational changes in the protein structure compared to α1, as well as for the binding modes of compounds and hence their functional signaling.

Potassium channels are of paramount physiological and pathological importance and therefore constitute significant drug targets. One of the keys to rationalize the way drugs modulate ion channels is to understand the ability of such small molecules to access their respective binding sites, from which they can exert an activating or inhibitory effect. Many computational studies have probed the energetics of ion permeation, and the mechanisms of voltage gating, but little is known about the role of fenestrations as possible mediators of drug entry in potassium channels. To explore the existence, structure, and conformational dynamics of transmembrane fenestrations accessible by drugs in potassium channels, molecular dynamics simulation trajectories were analyzed from three potassium channels: the open state voltage-gated channel Kv1.2, the G protein-gated inward rectifying channel GIRK2 (Kir3.2), and the human two-pore domain TWIK-1 (K2P1.1). The main results of this work were the identification of the sequence identity of four main lateral fenestrations of similar length and with bottleneck radius in the range of 0.9-2.4 Å for this set of potassium channels. It was found that the fenestrations in Kv1.2 and Kir3.2 remain closed to the passage of molecules larger than water. In contrast, in the TWIK-1 channel, both open and closed fenestrations are sampled throughout the simulation, with bottleneck radius shown to correlate with the random entry of lipid membrane molecules into the aperture of the fenestrations. Druggability scoring function analysis of the fenestration regions suggests that Kv and Kir channels studied are not druggable in practice due to steric constraining of the fenestration bottleneck. A high (>50%) fenestration sequence identity was found in each potassium channel subfamily studied, Kv1, Kir3, and K2P1. Finally, the reported fenestration sequence of TWIK-1 compared favorably with another channel, K2P channel TREK-2, reported to possess open fenestrations, suggesting that K2P channels could be druggable via fenestrations, for which we reported atomistic detail of the fenestration region, including the flexible residues M260 and L264 that interact with POPC membrane in a concerted fashion with the aperture and closure of the fenestrations.

Regulation of transcription is fundamental to development and physiology, and occurs through binding of transcription factors to specific DNA sequences in the genome. CSL (CBF1/Suppressor of Hairless/LAG-1), a core component of the Notch signaling pathway, is one such transcription factor that acts in concert with co-activators or co-repressors to control the activity of associated target genes. One fundamental question is how CSL can recognize and select among different DNA sequences available in vivo and whether variations between selected sequences can influence its function. We have therefore investigated CSL-DNA recognition using computational approaches to analyze the energetics of CSL bound to different DNAs and tested the in silico predictions with in vitro and in vivo assays. Our results reveal novel aspects of CSL binding that may help explain the range of binding observed in vivo. In addition, using molecular dynamics simulations, we show that domain-domain correlations within CSL differ significantly depending on the DNA sequence bound, suggesting that different DNA sequences may directly influence CSL function. Taken together, our results, based on computational chemistry approaches, provide valuable insights into transcription factor-DNA binding, in this particular case increasing our understanding of CSL-DNA interactions and how these may impact on its transcriptional control.

Metabolism of xenobiotic and endogenous compounds is frequently complex, not completely elucidated, and therefore often ambiguous. The prediction of sites of metabolism (SoM) can be particularly helpful as a first step toward the identification of metabolites, a process especially relevant to drug discovery. This paper describes a reactivity approach for predicting SoM whereby reactivity is derived directly from the ground state ligand molecular orbital analysis, calculated using Density Functional Theory, using a novel implementation of the average local ionization energy. Thus each potential SoM is sampled in the context of the whole ligand, in contrast to other popular approaches where activation energies are calculated for a predefined database of molecular fragments and assigned to matching moieties in a query ligand. In addition, one of the first descriptions of molecular dynamics of cytochrome P450 (CYP) isoforms 3A4, 2D6, and 2C9 in their Compound I state is reported, and, from the representative protein structures obtained, an analysis and evaluation of various docking approaches using GOLD is performed. In particular, a covalent docking approach is described coupled with the modeling of important electrostatic interactions between CYP and ligand using spherical constraints. Combining the docking and reactivity results, obtained using standard functionality from common docking and quantum chemical applications, enables a SoM to be identified in the top 2 predictions for 75%, 80%, and 78% of the data sets for 3A4, 2D6, and 2C9, respectively, results that are accessible and competitive with other recently published prediction tools.

Fibroblast growth factors (FGFs) are recognized targets for the development of therapies against angiogenesis-driven diseases, including cancer. The formation of a ternary complex with the transmembrane tyrosine kinase receptors (FGFRs), and heparan sulphate proteoglycans (HSPGs) is required for FGF2 pro-angiogenic activity. Here by using a combination of techniques including Nuclear Magnetic Resonance, Molecular Dynamics, Surface Plasmon Resonance and cell-based binding assays we clarify the molecular mechanism of inhibition of an angiostatic small molecule, sm27, mimicking the endogenous inhibitor of angiogenesis, thrombospondin-1. NMR and MD data demonstrate that sm27 engages the heparin-binding site of FGF2 and induces long-range dynamics perturbations along FGF2/FGFR1 interface regions. The functional consequence of the inhibitor binding is an impaired FGF2 interaction with both its receptors, as demonstrated by SPR and cell-based binding assays. We propose that sm27 antiangiogenic activity is based on a twofold-direct and allosteric-mechanism, inhibiting FGF2 binding to both its receptors.