Discovery and In Vitro Characterization of BAY 2686013, an Allosteric Small Molecule Antagonist of the Human Pituitary Adenylate Cyclase-Activating Polypeptide Receptor.

The human pituitary adenylate cyclase-activating polypeptide receptor (hPAC1-R), a class B G-protein-coupled receptor (GPCR) identified almost 30 years ago, represents an important pharmacological target in the areas of neuroscience, oncology, and immunology. Despite interest in this target, only a very limited number of small molecule modulators have been reported for this receptor. We herein describe the results of a drug discovery program aiming for the identification of a potent and selective hPAC1-R antagonist. An initial high-throughput screening (HTS) screen of 3.05 million compounds originating from the Bayer screening library failed to identify any tractable hits. A second, completely revised screen using native human embryonic kidney (HEK)293 cells yielded a small number of hits exhibiting antagonistic properties (4.2 million compounds screened). BAY 2686013 (1) emerged as a promising compound showing selective antagonistic activity in the submicromolar potency range. In-depth characterization supported the hypothesis that BAY 2686013 blocks receptor activity in a noncompetitive manner. Preclinical, pharmacokinetic profiling indicates that BAY 2686013 is a valuable tool compound for better understanding the signaling and function of hPAC1-R. SIGNIFICANCE STATEMENT: Although the human pituitary adenylate cyclase-activating polypeptide receptor (hPAC1-R) is of major significance as a therapeutic target with a well documented role in pain signaling, only a very limited number of small-molecule (SMOL) compounds are known to modulate its activity. We identified and thoroughly characterized a novel, potent, and selective SMOL antagonist of hPAC1-R (acting in an allosteric manner). These characteristics make BAY 2686013 an ideal tool for further studies.

In silico identification of a ß2-adrenoceptor allosteric site that selectively augments canonical ß2AR-Gs signaling and function.

Activation of ß2-adrenoceptors (ß2ARs) causes airway smooth muscle (ASM) relaxation and bronchodilation, and ß2AR agonists (ß-agonists) are front-line treatments for asthma and other obstructive lung diseases. However, the therapeutic efficacy of ß-agonists is limited by agonist-induced ß2AR desensitization and noncanonical ß2AR signaling involving ß-arrestin that is shown to promote asthma pathophysiology. Accordingly, we undertook the identification of an allosteric site on ß2AR that could modulate the activity of ß-agonists to overcome these limitations. We employed the site identification by ligand competitive saturation (SILCS) computational method to comprehensively map the entire 3D structure of in silico-generated ß2AR intermediate conformations and identified a putative allosteric binding site. Subsequent database screening using SILCS identified drug-like molecules with the potential to bind to the site. Experimental assays in HEK293 cells (expressing recombinant wild-type human ß2AR) and human ASM cells (expressing endogenous ß2AR) identified positive and negative allosteric modulators (PAMs and NAMs) of ß2AR as assessed by regulation of ß-agonist-stimulation of cyclic AMP generation. PAMs/NAMs had no effect on ß-agonist-induced recruitment of ß-arrestin to ß2AR- or ß-agonist-induced loss of cell surface expression in HEK293 cells expressing ß2AR. Mutagenesis analysis of ß2AR confirmed the SILCS identified site based on mutants of amino acids R131, Y219, and F282. Finally, functional studies revealed augmentation of ß-agonist-induced relaxation of contracted human ASM cells and bronchodilation of contracted airways. These findings identify a allosteric binding site on the ß2AR, whose activation selectively augments ß-agonist-induced Gs signaling, and increases relaxation of ASM cells, the principal therapeutic effect of ß-agonists.

Functional Group Distributions, Partition Coefficients, and Resistance Factors in Lipid Bilayers Using Site Identification by Ligand Competitive Saturation.

Small molecules such as metabolites and drugs must pass through the membrane of the cell, a barrier primarily comprising phospholipid bilayers and embedded proteins. To better understand the process of passive diffusion, knowledge of the ability of various functional groups to partition across bilayers and the associated energetics would be of utility. In the present study, the site identification by ligand competitive saturation (SILCS) methodology has been applied to sample the distributions of a diverse set of chemical solutes representing the functional groups of small molecules across phospholipid bilayers composed of 0.9:0.1 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine/cholesterol and a mixture of 0.52:0.18:0.3 1,2-dioleoyl-sn-glycero-3-phospho-l-serine/1,2-dioleoyl-sn-glycero-3-phosphocholine/cholesterol used in parallel artificial membrane permeability assay experiments. A combination of oscillating chemical potential grand canonical Monte Carlo and molecular dynamics in the SILCS simulations was applied to achieve solute sampling through the bilayers and surrounding aqueous environment from which the distribution of solutes and the functional groups they represent were obtained. Results show differential distribution of aliphatic versus aromatic groups with the former having increased sampling in the center of the bilayers versus in the region of the glycerol linker for the latter. Variations in the distribution of different polar groups are evident, with large differences between negative acetate and positive methylammonium with accumulation of the polar-neutral and acetate solutes above the bilayer head groups. Conversion of the distributions to absolute free energies allows for a detailed understanding of energetics of functional groups in different regions of the bilayers and for calculation of absolute free-energy profiles of multifunctional drug-like molecules across the bilayers from which partition coefficients and resistance factors suitable for insertion into the homogenous solubility-diffusion equation for calculation of permeability were obtained. Comparisons of the calculated bilayer/solution partition coefficients with 1-octanol/water experimental data for both drug-like molecules and the solutes show overall good agreement, validating the calculated distributions and associated absolute free-energy profiles.

Identification and characterization of fragment binding sites for allosteric ligand design using the site identification by ligand competitive saturation hotspots approach (SILCS-Hotspots).

BACKGROUND: Fragment-based ligand design is used for the development of novel ligands that target macromolecules, most notably proteins. Central to its success is the identification of fragment binding sites that are spatially adjacent such that fragments occupying those sites may be linked to create drug-like ligands. Current experimental and computational approaches that address this problem typically identify only a limited number of sites as well as use a limited number of fragment types. METHODS: The site-identification by ligand competitive saturation (SILCS) approach is extended to the identification of fragment bindings sites, with the method termed SILCS-Hotspots. The approach involves precomputation of the SILCS FragMaps following which the identification of Hotspots, performed by identifying of all possible fragment binding sites on the full 3D structure of the protein followed by spatial clustering. RESULTS: The SILCS-Hotspots approach identifies a large number of sites on the target protein, including many sites not accessible in experimental structures due to low binding affinities and binding sites on the protein interior. The identified sites are shown to recapitulate the location of known drug-like molecules in both allosteric and orthosteric binding sites on seven proteins including the androgen receptor, the CDK2 and Erk5 kinases, PTP1B phosphatase and three GPCRs; the ß2-adrenergic, GPR40 fatty-acid binding and M2-muscarinic receptors. Analysis indicates the importance of considering all possible fragment binding sites, and not just those accessible to experimental methods, when identifying novel binding sites and performing ligand design versus just considering the most favorable sites. The approach is shown to identify a larger number of known binding sites of drug-like molecules versus the commonly used FTMap and Fpocket methods. GENERAL SIGNIFICANCE: The present results indicate the potential utility of the SILCS-Hotspots approach for fragment-based rational design of ligands, including allosteric modulators.

Free energy calculations of RNA interactions.

This review discusses the use of molecular dynamics free energy calculations for characterizing RNA interactions, with particular emphasis on molecular recognition events involved in mRNA translation on the ribosome. The general methodology for efficient free energy calculations is outlined and our specific implementation for binding free energy changes due to base mutations in mRNA and tRNA is described. We show that there are a number of key problems related to the accuracy of protein synthesis that can be addressed with this type of computational approach and several such examples are discussed in detail. These include the decoding of mRNA during peptide chain elongation, initiation and termination of translation, as well as the energetic effects of base tautomerization and tRNA modifications. It is shown that free energy calculations can be made sufficiently reliable to allow quantitative conclusions to be drawn regarding the energetics of cognate versus non-cognate interactions and its structural origins.

Complementary charge-based interaction between the ribosomal-stalk protein L7/12 and IF2 is the key to rapid subunit association.

The interaction between the ribosomal-stalk protein L7/12 (L12) and initiation factor 2 (IF2) is essential for rapid subunit association, but the underlying mechanism is unknown. Here, we have characterized the L12-IF2 interaction on Escherichia coli ribosomes using site-directed mutagenesis, fast kinetics, and molecular dynamics (MD) simulations. Fifteen individual point mutations were introduced into the C-terminal domain of L12 (L12-CTD) at helices 4 and 5, which constitute the common interaction site for translational GTPases. In parallel, 15 point mutations were also introduced into IF2 between the G4 and G5 motifs, which we hypothesized as the potential L12 interaction sites. The L12 and IF2 mutants were tested in ribosomal subunit association assay in a stopped-flow instrument. Those amino acids that caused defective subunit association upon substitution were identified as the molecular determinants of L12-IF2 interaction. Further, MD simulations of IF2 docked onto the L12-CTD pinpointed the exact interacting partners-all of which were positively charged on L12 and negatively charged on IF2, connected by salt bridges. Lastly, we tested two pairs of charge-reversed mutants of L12 and IF2, which significantly restored the yield and the rate of formation of the 70S initiation complex. We conclude that complementary charge-based interaction between L12-CTD and IF2 is the key for fast subunit association. Considering the homology of the G domain, similar mechanisms may apply for L12 interactions with other translational GTPases.

Origin of the omnipotence of eukaryotic release factor 1.

Termination of protein synthesis on the ribosome requires that mRNA stop codons are recognized with high fidelity. This is achieved by specific release factor proteins that are very different in bacteria and eukaryotes. Hence, while there are two release factors with overlapping specificity in bacteria, the single omnipotent eRF1 release factor in eukaryotes is able to read all three stop codons. This is particularly remarkable as it is able to select three out of four combinations of purine bases in the last two codon positions. With recently determined 3D structures of eukaryotic termination complexes, it has become possible to explore the origin of eRF1 specificity by computer simulations. Here, we report molecular dynamics free energy calculations on these termination complexes, where relative eRF1 binding free energies to different cognate and near-cognate codons are evaluated. The simulations show a high and uniform discrimination against the near-cognate codons, that differ from the cognate ones by a single nucleotide, and reveal the structural mechanisms behind the precise decoding by eRF1.

A close-up view of codon selection in eukaryotic initiation.

When given an option to choose among a set of alternatives and only one selection is right, one might stop and reflect over which one is best. However, the ribosome has no time to stop and make such reflections, proteins need to be produced and very fast. Eukaryotic translation initiation is an example of such a conundrum. Here, scanning for the correct codon match must be fast, efficient and accurate. We highlight our recent computational findings, which show how the initiation machinery manages to recognize one specific codon among many possible challengers, by fine-tuning the energetic landscape of base-pairing with the aid of the initiation factors eIF1 and eIF1A. Using a recent 3-dimensional structure of the eukaryotic initiation complex we have performed simulations of codon recognition in atomic detail. These calculations provide an in-depth energetic and structural view of how discrimination against near-cognate codons is achieved by the initiation complex.

Principles of start codon recognition in eukaryotic translation initiation.

Selection of the correct start codon during initiation of translation on the ribosome is a key event in protein synthesis. In eukaryotic initiation, several factors have to function in concert to ensure that the initiator tRNA finds the cognate AUG start codon during mRNA scanning. The two initiation factors eIF1 and eIF1A are known to provide important functions for the initiation process and codon selection. Here, we have used molecular dynamics free energy calculations to evaluate the energetics of initiator tRNA binding to different near-cognate codons on the yeast 40S ribosomal subunit, in the presence and absence of these two initiation factors. The results show that eIF1 and eIF1A together cause a relatively uniform and high discrimination against near-cognate codons. This works such that eIF1 boosts the discrimination against a first position near-cognate G-U mismatch, and also against a second position A-A base pair, while eIF1A mainly acts on third codon position. The computer simulations further reveal the structural basis of the increased discriminatory effect caused by binding of eIF1 and eIF1A to the 40S ribosomal subunit.

Binding site preorganization and ligand discrimination in the purine riboswitch.

The progress of RNA research has suggested a wide variety of RNA molecules as possible targets for pharmaceutical drug molecules. Structure-based computational methods for predicting binding modes and affinities are now important tools in drug discovery, but these methods have mainly been focused on protein targets. Here we employ molecular dynamics free-energy perturbation calculations and the linear interaction energy method to analyze the energetics of ligand binding to purine riboswitches. Calculations are carried out for 14 different purine complexes with the guanine and adenine riboswitches in order to examine their ligand recognition principles. The simulations yield binding affinities in good agreement with experimental data and rationalize the selectivity of the riboswitches for different ligands. In particular, it is found that these receptors have an unusually high degree of electrostatic preorganization for their cognate ligands, and this effect is further quantified by explicit free-energy calculations, which show that the standard electrostatic linear interaction energy parametrization is suboptimal in this case. The adenine riboswitch specifically uses the electrostatic preorganization to discriminate against guanine by preventing the formation of a G-U wobble base pair.

Codon-reading specificities of mitochondrial release factors and translation termination at non-standard stop codons.

A key feature of mitochondrial translation is the reduced number of transfer RNAs and reassignment of codons. For human mitochondria, a major unresolved problem is how the set of stop codons are decoded by the release factors mtRF1a and mtRF1. Here we present three-dimensional structural models of human mtRF1a and mtRF1 based on their homology to bacterial RF1 in the codon recognition domain, and the strong conservation between mitochondrial and bacterial ribosomal RNA in the decoding region. Sequence changes in the less homologous mtRF1 appear to be correlated with specific features of the mitochondrial rRNA. Extensive computer simulations of the complexes with the ribosomal decoding site show that both mitochondrial factors have similar specificities and that neither reads the putative vertebrate stop codons AGA and AGG. Instead, we present a structural model for a mechanism by which the ICT1 protein causes termination by sensing the presence of these codons in the A-site of stalled ribosomes.

Bridging the gap between ribosome structure and biochemistry by mechanistic computations.

The wealth of structural and biochemical data now available for protein synthesis on the ribosome presents major new challenges for computational biochemistry. Apart from technical difficulties in modeling ribosome systems, the complexity of the overall translation cycle with a multitude of different kinetic steps presents a formidable problem for computational efforts where we have only seen the beginning. However, a range of methodologies including molecular dynamics simulations, free energy calculations, molecular docking and quantum chemical approaches have already been put to work with promising results. In particular, the combined efforts of structural biology, biochemistry, kinetics and computational modeling can lead towards a quantitative structure-based description of translation.