Eric S. Dawson

A Model for the Solution Structure of the Rod Arrestin Tetramer

Visual rod arrestin has the ability to self-associate at physiological concentrations. We previously demonstrated that only monomeric arrestin can bind the receptor and that the arrestin tetramer in solution differs from that in the crystal. We employed the Rosetta docking software to generate molecular models of the physiologically relevant solution tetramer based on the monomeric arrestin crystal structure. The resulting models were filtered using the Rosetta energy function, experimental intersubunit distances measured with DEER spectroscopy, and intersubunit contact sites identified by mutagenesis and site-directed spin labeling. This resulted in a unique model for subsequent evaluation. The validity of the model is strongly supported by model-directed crosslinking and targeted mutagenesis that yields arrestin variants deficient in self-association. The structure of the solution tetramer explains its inability to bind rhodopsin and paves the way for experimental studies of the physiological role of rod arrestin self-association.

Community-wide assessment of GPCR structure modelling and ligand docking

Recent breakthroughs in the determination of the crystal structures of G protein-coupled receptors (GPCRs) have provided new opportunities for structure-based drug design strategies targeting this protein family. With the aim of evaluating the current status of GPCR structure prediction and ligand docking, a community-wide, blind prediction assessment — GPCR Dock 2008 — was conducted in coordination with the publication of the crystal structure of the human adenosine A2A receptor bound to the ligand ZM241385. Twenty-nine groups submitted 206 structural models before the release of the experimental structure, which were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure. This analysis highlights important aspects for success and future development, such as accurate modelling of structurally divergent regions and use of additional biochemical insight such as disulphide bridges in the extracellular loops.

Development of a Selective Small-Molecule Inhibitor of Kir1.1, the Renal Outer Medullary Potassium Channel

The renal outer medullary potassium (K+) channel, ROMK (Kir1.1), is a putative drug target for a novel class of loop diuretic that would lower blood volume and pressure without causing hypokalemia. However, the lack of selective ROMK inhibitors has hindered efforts to assess its therapeutic potential. In a high-throughput screen for small-molecule modulators of ROMK, we previously identified a potent and moderately selective ROMK antagonist, 7,13-bis(4-nitrobenzyl)-1,4,10-trioxa-7,13-diazacyclopentadecane (VU590), that also inhibits Kir7.1. Because ROMK and Kir7.1 are coexpressed in the nephron, VU590 is not a good probe of ROMK function in the kidney. Here we describe the development of the structurally related inhibitor 2,2′-oxybis(methylene)bis(5-nitro-1H-benzo[d]imidazole) (VU591), which is as potent as VU590 but is selective for ROMK over Kir7.1 and more than 65 other potential off-targets. VU591 seems to block the intracellular pore of the channel. The development of VU591 may enable studies to explore the viability of ROMK as a diuretic target.

Structural determinants of species-selective substrate recognition in human and Drosophila serotonin transporters revealed through computational docking studies

To identify potential determinants of substrate selectivity in serotonin (5‐HT) transporters (SERT), models of human and Drosophila serotonin transporters (hSERT, dSERT) were built based on the leucine transporter (LeuTAa) structure reported by Yamashita et al. (Nature 2005;437:215–223), PBDID 2A65. Although the overall amino acid identity between SERTs and the LeuTAa is only 17%, it increases to above 50% in the first shell of the putative 5‐HT binding site, allowing de novo computational docking of tryptamine derivatives in atomic detail. Comparison of hSERT and dSERT complexed with substrates pinpoints likely structural determinants for substrate binding. Forgoing the use of experimental transport and binding data of tryptamine derivatives for construction of these models enables us to critically assess and validate their predictive power: A single 5‐HT binding mode was identified that retains the amine placement observed in the LeuTAa structure, matches site‐directed mutagenesis and substituted cysteine accessibility method (SCAM) data, complies with support vector machine derived relations activity relations, and predicts computational binding energies for 5‐HT analogs with a significant correlation coefficient (R = 0.72). This binding mode places 5‐HT deep in the binding pocket of the SERT with the 5‐position near residue hSERT A169/dSERT D164 in transmembrane helix 3, the indole nitrogen next to residue Y176/Y171, and the ethylamine tail under residues F335/F327 and S336/S328 within 4 Å of residue D98. Our studies identify a number of potential contacts whose contribution to substrate binding and transport was previously unsuspected. Proteins 2009.

Selective Inhibition of the Kir2 Family of Inward Rectifier Potassium Channels by a Small Molecule Probe: The Discovery, SAR, and Pharmacological Characterization of ML133

The K(ir) inward rectifying potassium channels have a broad tissue distribution and are implicated in a variety of functional roles. At least seven classes (K(ir)1-K(ir)7) of structurally related inward rectifier potassium channels are known, and there are no selective small molecule tools to study their function. In an effort to develop selective K(ir)2.1 inhibitors, we performed a high-throughput screen (HTS) of more than 300,000 small molecules within the MLPCN for modulators of K(ir)2.1 function. Here we report one potent K(ir)2.1 inhibitor, ML133, which inhibits K(ir)2.1 with an IC(50) of 1.8 μM at pH 7.4 and 290 nM at pH 8.5 but exhibits little selectivity against other members of Kir2.x family channels. However, ML133 has no effect on K(ir)1.1 (IC(50) > 300 μM) and displays weak activity for K(ir)4.1 (76 μM) and K(ir)7.1 (33 μM), making ML133 the most selective small molecule inhibitor of the K(ir) family reported to date. Because of the high homology within the K(ir)2 family-the channels share a common design of a pore region flanked by two transmembrane domains-identification of site(s) critical for isoform specificity would be an important basis for future development of more specific and potent K(ir) inhibitors. Using chimeric channels between K(ir)2.1 and K(ir)1.1 and site-directed mutagenesis, we have identified D172 and I176 within M2 segment of K(ir)2.1 as molecular determinants critical for the potency of ML133 mediated inhibition. Double mutation of the corresponding residues of K(ir)1.1 to those of K(ir)2.1 (N171D and C175I) transplants ML133 inhibition to K(ir)1.1. Together, the combination of a potent, K(ir)2 family selective inhibitor and identification of molecular determinants for the specificity provides both a tool and a model system to enable further mechanistic studies of modulation of K(ir)2 inward rectifier potassium channels.

A Conserved Asparagine Residue in Transmembrane Segment 1 (TM1) of Serotonin Transporter Dictates Chloride-coupled Neurotransmitter Transport

Na+- and Cl−-dependent uptake of neurotransmitters via transporters of the SLC6 family, including the human serotonin transporter (SLC6A4), is critical for efficient synaptic transmission. Although residues in the human serotonin transporter involved in direct Cl− coordination of human serotonin transport have been identified, the role of Cl− in the transport mechanism remains unclear. Through a combination of mutagenesis, chemical modification, substrate and charge flux measurements, and molecular modeling studies, we reveal an unexpected role for the highly conserved transmembrane segment 1 residue Asn-101 in coupling Cl− binding to concentrative neurotransmitter uptake.

Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening

Selective potentiators of glutamate response at metabotropic glutamate receptor subtype 5 (mGluR5) have exciting potential for the development of novel treatment strategies for schizophrenia. A total of 1,382 compounds with positive allosteric modulation (PAM) of the mGluR5 glutamate response were identified through high-throughput screening (HTS) of a diverse library of 144,475 substances utilizing a functional assay measuring receptor-induced intracellular release of calcium. Primary hits were tested for concentration-dependent activity, and potency data (EC50 values) were used for training artificial neural network (ANN) quantitative structure−activity relationship (QSAR) models that predict biological potency from the chemical structure. While all models were trained to predict EC50, the quality of the models was assessed by using both continuous measures and binary classification. Numerical descriptors of chemical structure were used as input for the machine learning procedure and optimized in an iterative protocol. The ANN models achieved theoretical enrichment ratios of up to 38 for an independent data set not used in training the model. A database of ∼450,000 commercially available drug-like compounds was targeted in a virtual screen. A set of 824 compounds was obtained for testing based on the highest predicted potency values. Biological testing found 28.2% (232/824) of these compounds with various activities at mGluR5 including 177 pure potentiators and 55 partial agonists. These results represent an enrichment factor of 23 for pure potentiation of the mGluR5 glutamate response and 30 for overall mGluR5 modulation activity when compared with those of the original mGluR5 experimental screening data (0.94% hit rate). The active compounds identified contained 72% close derivatives of previously identified PAMs as well as 28% nontrivial derivatives of known active compounds.

Evaluation of the Biosynthetic Proposal for the Synthesis of Marineosins A and B

The first synthetic efforts toward marineosins A and B, novel spiroaminals from a Streptomyces actinomycete, are described by evaluation of the proposed biosynthesis. The hypothesized biosynthetic C1-C25 Diels-Alder substrate was prepared in 8 steps in 5.1% overall yield; however, the proposed biomimetic inverse-electron-demand hetero-Diels-Alder reaction failed to deliver the marineosin core. Molecular mechanics supports this observation.

Discovery of 2‐(2‐Benzoxazoyl amino)‐4‐Aryl‐5‐Cyanopyrimidine as Negative Allosteric Modulators (NAMs) of Metabotropic Glutamate Receptor 5 (mGlu5): From an Artificial Neural Network Virtual Screen to an In Vivo Tool Compound

Glutamate, the major excitatory neurotransmitter, functions in the brain via activation of ligand gated cation channels and also the eight subtypes of Class C G protein-coupled metabotropic glutamate receptors (mGlus).[1] Selective allosteric modulation of mGlu5 has been shown to have potential for treatment of a variety of neurological disorders[2,3] including anxiety disorders[4,5], Parkinson’s disease[6–8], Fragile X syndrome[9] and schizophrenia.[10–14] The majority of mGlu5 negative allosteric modulators (NAMs) developed to date either contain an alkyne moiety 1–4 or employ the alkyne topology as basis for ligand design,[15] as in 5–8 (Figure 1). Only recently have mGlu5 NAM chemotypes been identified, through high-throughput screening (HTS) campaigns, that are structurally unrelated to the classical acetylenic derivatives, such as 9–12 (Figure 1).[16] Due to the prevalence of ‘molecular switch‘phenomenon in MPEP related scaffolds, our interest focused on the discovery and development of novel mGlu5 NAM chemotypes, by both HTS and Artificial Neural Network (ANN) virtual screens.

An Overview of the Challenges in Designing, Integrating, and Delivering BARD: A Public Chemical-Biology Resource and Query Portal for Multiple Organizations, Locations, and Disciplines

Recent industry–academic partnerships involve collaboration among disciplines, locations, and organizations using publicly funded “open-access” and proprietary commercial data sources. These require the effective integration of chemical and biological information from diverse data sources, which presents key informatics, personnel, and organizational challenges. The BioAssay Research Database (BARD) was conceived to address these challenges and serve as a community-wide resource and intuitive web portal for public-sector chemical-biology data. Its initial focus is to enable scientists to more effectively use the National Institutes of Health Roadmap Molecular Libraries Program (MLP) data generated from the 3-year pilot and 6-year production phases of the Molecular Libraries Probe Production Centers Network (MLPCN), which is currently in its final year. BARD evolves the current data standards through structured assay and result annotations that leverage BioAssay Ontology and other industry-standard ontologies, and a core hierarchy of assay definition terms and data standards defined specifically for small-molecule assay data. We initially focused on migrating the highest-value MLP data into BARD and bringing it up to this new standard. We review the technical and organizational challenges overcome by the interdisciplinary BARD team, veterans of public- and private-sector data-integration projects, who are collaborating to describe (functional specifications), design (technical specifications), and implement this next-generation software solution.