摘要：Multitarget datasets that correlate bioactivity landscapes of small-molecules toward diferent 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 .
