Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation.

The Annotation Query (AnnoQ) (http://annoq.org/) is designed to provide comprehensive and up-to-date functional annotations for human genetic variants. The system is supported by an annotation database with ∼39 million human variants from the Haplotype Reference Consortium (HRC) pre-annotated with sequence feature annotations by WGSA and functional annotations to Gene Ontology (GO) and pathways in PANTHER. The database operates on an optimized Elasticsearch framework to support real-time complex searches. This implementation enables users to annotate data with the most up-to-date functional annotations via simple queries instead of setting up individual tools. A web interface allows users to interactively browse the annotations, annotate variants and search variant data. Its easy-to-use interface and search capabilities are well-suited for scientists with fewer bioinformatics skills such as bench scientists and statisticians. AnnoQ also has an API for users to access and annotate the data programmatically. Packages for programming languages, such as the R package, are available for users to embed the annotation queries in their scripts. AnnoQ serves researchers with a wide range of backgrounds and research interests as an integrated annotation platform.

Structure-activity relationship of ipglycermide binding to phosphoglycerate mutases.

Catalysis of human phosphoglycerate mutase is dependent on a 2,3-bisphosphoglycerate cofactor (dPGM), whereas the nonhomologous isozyme in many parasitic species is cofactor independent (iPGM). This mechanistic and phylogenetic diversity offers an opportunity for selective pharmacologic targeting of glycolysis in disease-causing organisms. We previously discovered ipglycermide, a potent inhibitor of iPGM, from a large combinatorial cyclic peptide library. To fully delineate the ipglycermide pharmacophore, herein we construct a detailed structure-activity relationship using 280 substituted ipglycermide analogs. Binding affinities of these analogs to immobilized Caenorhabditis elegans iPGM, measured as fold enrichment relative to the index residue by deep sequencing of an mRNA display library, illuminated the significance of each amino acid to the pharmacophore. Using cocrystal structures and binding kinetics, we show that the high affinity of ipglycermide for iPGM orthologs, from Brugia malayi, Onchocerca volvulus, Dirofilaria immitis, and Escherichia coli, is achieved by a codependence between (1) the off-rate mediated by the macrocycle Cys14 thiolate coordination to an active-site Zn2+ in the iPGM phosphatase domain and (2) shape complementarity surrounding the macrocyclic core at the phosphotransferase-phosphatase domain interface. Our results show that the high-affinity binding of ipglycermide to iPGMs freezes these structurally dynamic enzymes into an inactive, stable complex.

qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data.

High throughput screening (HTS) is widely used in drug discovery and chemical biology to identify and characterize agents having pharmacologic properties often by evaluation of large chemical libraries. Standard HTS data can be simply plotted as an x-y graph usually represented as % activity of a compound tested at a single concentration vs compound ID, whereas quantitative HTS (qHTS) data incorporates a third axis represented by concentration. By virtue of the additional data points arising from the compound titration and the incorporation of logistic fit parameters that define the concentration-response curve, such as EC50 and Hill slope, qHTS data has been challenging to display on a single graph. Here we provide a flexible solution to the rapid plotting of complete qHTS data sets to produce a 3-axis plot we call qHTS Waterfall Plots. The software described here can be generally applied to any 3-axis dataset and is available as both an R package and an R shiny application.

In vivo quantitative high-throughput screening for drug discovery and comparative toxicology.

Quantitative high-throughput screening (qHTS) pharmacologically evaluates chemical libraries for therapeutic uses, toxicological risk and, increasingly, for academic probe discovery. Phenotypic high-throughput screening assays interrogate molecular pathways, often relying on cell culture systems, historically less focused on multicellular organisms. Caenorhabditis elegans has served as a eukaryotic model organism for human biology by virtue of genetic conservation and experimental tractability. Here, a paradigm enabling C. elegans qHTS using 384-well microtiter plate laser-scanning cytometry is described, in which GFP-expressing organisms revealing phenotype-modifying structure-activity relationships guide subsequent life-stage and proteomic analyses, and Escherichia coli bacterial ghosts, a non-replicating nutrient source, allow compound exposures over two life cycles, mitigating bacterial overgrowth complications. We demonstrate the method with libraries of anti-infective agents, or substances of toxicological concern. Each was tested in seven-point titration to assess the feasibility of nematode-based in vivo qHTS, and examples of follow-up strategies were provided to study organism-based chemotype selectivity and subsequent network perturbations with a physiological impact. We anticipate that this qHTS approach will enable analysis of C. elegans orthologous phenotypes of human pathologies to facilitate drug library profiling for a range of therapeutic indications.

Genome-Edited Coincidence and PMP22-HiBiT Fusion Reporter Cell Lines Enable an Artifact-Suppressive Quantitative High-Throughput Screening Strategy for PMP22 Gene-Dosage Disorder Drug Discovery.

Charcot-Marie-Tooth 1A (CMT1A) is the most common form of hereditary peripheral neuropathies, characterized by genetic duplication of the critical myelin gene Peripheral Myelin Protein 22 (PMP22). PMP22 overexpression results in abnormal Schwann cell differentiation, leading to axonal loss and muscle wasting. Since regulation of PMP22 expression is a major target of therapeutic discovery for CMT1A, we sought to establish unbiased approaches that allow the identification of therapeutic agents for this disease. Using genome editing, we generated a coincidence reporter assay that accurately monitors Pmp22 transcript levels in the S16 rat Schwann cell line, while reducing reporter-based false positives. A quantitative high-throughput screen (qHTS) of 42 577 compounds using this assay revealed diverse novel chemical classes that reduce endogenous Pmp22 transcript levels. Moreover, some of these classes show pharmacological specificity in reducing Pmp22 over another major myelin-associated gene, Mpz (Myelin protein zero). Finally, to investigate whether compound-mediated reduction of Pmp22 transcripts translates to reduced PMP22 protein levels, we edited the S16 genome to generate a reporter assay that expresses a PMP22-HiBiT fusion protein using CRISPR/Cas9. Overall, we present a screening platform that combines genome edited cell lines encoding reporters that monitor transcriptional and post-translational regulation of PMP22 with titration-based screening (e.g., qHTS), which could be efficiently incorporated into drug discovery campaigns for CMT1A.