AI-ACCELERATED DRUG DISCOVERY

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 comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q9UNQ0

UPID:

ABCG2_HUMAN

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

Background:

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.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.