A curated binary pattern multitarget dataset of focused ATP-binding cassette transporter inhibitors

Sci Data. 2022 Jul 26;9(1):446. doi: 10.1038/s41597-022-01506-z.


Multitarget datasets that correlate bioactivity landscapes of small-molecules toward different related or unrelated pharmacological targets are crucial for novel drug design and discovery. ATP-binding cassette (ABC) transporters are critical membrane-bound transport proteins that impact drug and metabolite distribution in human disease as well as disease diagnosis and therapy. Molecular-structural patterns are of the highest importance for the drug discovery process as demonstrated by the novel drug discovery tool 'computer-aided pattern analysis' ('C@PA'). Here, we report a multitarget dataset of 1,167 ABC transporter inhibitors analyzed for 604 molecular substructures in a statistical binary pattern distribution scheme. This binary pattern multitarget dataset (ABC_BPMDS) can be utilized for various areas. These areas include the intended design of (i) polypharmacological agents, (ii) highly potent and selective ABC transporter-targeting agents, but also (iii) agents that avoid clearance by the focused ABC transporters [e.g., at the blood-brain barrier (BBB)]. The information provided will not only facilitate novel drug prediction and discovery of ABC transporter-targeting agents, but also drug design in general in terms of pharmacokinetics and pharmacodynamics.

Publication types

  • Dataset

MeSH terms

  • ATP-Binding Cassette Transporters* / antagonists & inhibitors
  • Drug Design
  • Drug Discovery
  • Humans
  • Pharmaceutical Preparations*


  • ATP-Binding Cassette Transporters
  • Pharmaceutical Preparations