Focused On-demand Library for Broad substrate specificity ATP-binding cassette transporter ABCG2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







Alternative names:

ATP-binding cassette sub-family G member 2; Breast cancer resistance protein; CDw338; Mitoxantrone resistance-associated protein; Placenta-specific ATP-binding cassette transporter; Urate exporter

Alternative UPACC:

Q9UNQ0; A0A1W3; A8K1T5; O95374; Q4W5I3; Q53ZQ1; Q569L4; Q5YLG4; Q86V64; Q8IX16; Q96LD6; Q96TA8; Q9BY73; Q9NUS0


The Broad substrate specificity ATP-binding cassette transporter ABCG2, known by various names including Breast cancer resistance protein and Urate exporter, plays a crucial role in cellular defense. It actively extrudes a wide array of compounds, including dietary toxins, xenobiotics, and physiological compounds, ensuring cellular homeostasis. Its ability to transport a diverse range of substances, from porphyrins and heme to sphingosine-1-P and steroids, underscores its versatility and importance in biological systems.

Therapeutic significance:

Understanding the role of Broad substrate specificity ATP-binding cassette transporter ABCG2 could open doors to potential therapeutic strategies. Its involvement in drug resistance, particularly in cancer, and in the regulation of urate levels, highlights its potential as a target for therapeutic intervention. Enhancing or inhibiting its activity could lead to novel treatments for cancer and gout, respectively.

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