Analysis of in vitrobioactivity data extracted from drug discovery literature and patents: Ranking 1654 human protein targets by assayed compounds and molecular scaffolds

Abstract

BackgroundSince the classic Hopkins and Groom druggable genome review in 2002, there have been a number of publications updating both the hypothetical and successful human drug target statistics. However, listings of research targets that define the area between these two extremes are sparse because of the challenges of collating published information at the necessary scale. We have addressed this by interrogating databases, populated by expert curation, of bioactivity data extracted from patents and journal papers over the last 30 years.ResultsFrom a subset of just over 27,000 documents we have extracted a set of compound-to-target relationships for biochemical in vitro binding-type assay data for 1,736 human proteins and 1,654 gene identifiers. These are linked to 1,671,951 compound records derived from 823,179 unique chemical structures. The distribution showed a compounds-per-target average of 964 with a maximum of 42,869 (Factor Xa). The list includes non-targets, failed targets and cross-screening targets. The top-278 most actively pursued targets cover 90% of the compounds. We further investigated target ranking by determining the number of molecular frameworks and scaffolds. These were compared to the compound counts as alternative measures of chemical diversity on a per-target basis.ConclusionsThe compounds-per-protein listing generated in this work (provided as a supplementary file) represents the major proportion of the human drug target landscape defined by published data. We supplemented the simple ranking by the number of compounds assayed with additional rankings by molecular topology. These showed significant differences and provide complementary assessments of chemical tractability.

The role of ligand efficiency metrics in drug discovery

“…85 The median ligand efficiencies of the 480 target-assay pairs span a wide range: ~0.2-0.6 for LE and ~ -3-9 for LLE ( Figure 4a). This is a consequence of intrinsic target druggability, combined with the properties of the actual molecules synthesised.…”

SARConnect: A Tool to Interrogate the Connectivity Between Proteins, Chemical Structures and Activity Data

“…The continually expanding range of chemotypes that Chemistry Connect feeds into SARConnect consequently provides a de facto chemical tractability assessment 48. It may even be adequate to iteratively generate results sufficient for disease model testing without the necessity to schedule an HTS.…”

Many InChIs and quite some feat

“…The Open PHACTS discovery platform integrates and links many data sources (see below) so that users can see the relationships between compounds, targets, pathways, diseases and tissues. InChI has also been used in mapping between chemical structures, assay results and targets in multiple databases, in integrating structure and bioactivity data, and in studying database overlap [57-60, [119][120][121][122]. A chemical taxonomy-based search engine, chem-BLAST, for HIV protease-inhibitor complexes uses InChI [108].…”