The IUPHAR/MMV Guide to Malaria Pharmacology

Workshop on Using the Guide to Immunoipharmacology. PDF of slides presented at BPS Pharmacology 2019 by Dr. Simon Harding.

Identification of unknowns in mass spectrometry based non-targeted analyses (NTA) requires the integration of complementary pieces of data to arrive at a confident, consensus structure. Researchers use chemical reference databases, spectral matching, fragment prediction tools, retention time prediction tools, and a variety of other data to arrive at tentative, probable, and confirmed, if possible, identifications. With the diverse, robust data contained within the US EPA’s CompTox Chemistry Dashboard (https://comptox.epa.gov), the goal of this research is to identify and implement a harmonized identification tool and workflow using previously generated chemistry data. Data has been compiled from product use, functional use prediction models, environmental media occurrence prediction models, and PubMed references, among other sources. We will report on our development of a visualization tool whereby users can visualize the relative contribution of identification-based metrics on a list of candidate structures and observe the greatest likelihood of occurrence. These data and visualization tools support NTA identification via the Dashboard and demonstrate an open, accessible tool for all users of HRMS data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

This document summarizes a study comparing different databases of approved drug structures mapped to PubChem identifiers (CIDs). The study found significant discordances between sources, with little consensus on total numbers of approved drugs or their structures. Only 183 structures were common to all 8 sources compared. The sources exhibited extensive structural multiplexing, with the same structure represented by multiple CIDs. This multiplexing extends beyond approved drugs and poses challenges for tasks like QSAR. Improved curation and direct submission of structures from drug developers could help resolve inconsistencies.

The document discusses the content of ligands from the IUPHAR/BPS Guide to PHARMACOLOGY database (GtoPdb) that is contained within PubChem. It finds that GtoPdb ligands have extensive overlap with several other sources within PubChem, including patents, DrugBank, vendor structures, bioassays, and ChEMBL. This overlap allows users to find additional information on GtoPdb ligands from these complementary sources within PubChem.

The document summarizes the IUPHAR/BPS Guide to Pharmacology (GtoPdb) database, which maps relationships between chemistry, data, and protein targets. It has evolved from earlier databases to now include over 1500 human protein targets linked to ligand data. Challenges include resolving relationships across different target hierarchies and filling data gaps. Future plans include expanding the database and linking it to immunopharmacology data through a new Guide to Immunopharmacology portal.

Open Phenotypic Drug Discovery Resource poster, presented at Open PHACTS Conference "Linking Life Science Data", Feb 18-19, 2016, University of Vienna

2018 update poster for the IUPHAR/BPS Guide to PHARMACOLOGY. Giving details of new features and updates. To be presented at Pharmacology Futures, Edinburgh, May 2018; ELIXIR-All Hands, Berlin, June 2018 and World Congress of Pharmacology, Kyoto, Japan, July 2018

High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are advancing the identification of emerging contaminants in environmental matrices, improving the means by which exposure analyses can be conducted. However, confidence in structure identification of unknowns in NTA presents challenges to analytical chemists. Structure identification requires integration of complementary data types such as reference databases, fragmentation prediction tools, and retention time prediction models. The goal of this research is to optimize and implement structure identification functionality within the US EPA’s CompTox Chemistry Dashboard, an open chemistry resource and web application containing data for ~760,000 substances. Rank-ordering the number of sources associated with chemical records within the Dashboard (Data Source Ranking) improves the identification of unknowns by bringing the most likely candidate structures to the top of a search results list. Database searching has been further optimized with the generation of MS-Ready Structures. MS-Ready structures are de-salted, stripped of stereochemistry, and mixture separated to replicate the form of a chemical observed via HRMS. Functionality to conduct batch searching of molecular formulae and monoisotopic masses was designed and released to improve searching efforts. Finally, a scoring-based identification scheme was developed, optimized, and surfaced via the Dashboard using multiple data streams contained within the database underlying the Dashboard. The scoring-based identification scheme improved the identification of unknowns over previous efforts using data source ranking alone. Combining these steps within an open chemistry resource provides a freely available software tool for structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

The document describes the EPA's CompTox Chemistry Dashboard, which provides access to data on over 760,000 chemicals. It focuses on how the Dashboard can be used to access information on chemicals used in hydraulic fracturing. Key features include searching for chemicals by name or formula, viewing associated property and hazard data, and links to other resources. The process of curating chemical lists from sources like EPA's hydraulic fracturing study involves mapping names to CAS numbers and structures through iterative checking. This allows accessing additional screening data, exposure information, and integrating identifiers to support searches.