AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Regulator of G-protein signaling 17

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q9UGC6

UPID:

RGS17_HUMAN

Alternative names:

-

Alternative UPACC:

Q9UGC6; Q5TF49; Q8TD61; Q9UJS8

Background:

Regulator of G-protein signaling 17 (RGS17) plays a pivotal role in modulating G protein-coupled receptor (GPCR) signaling pathways. It specifically regulates signaling via muscarinic acetylcholine receptor CHRM2 and dopamine receptor DRD2 by increasing the GTPase activity of G protein alpha subunits, leading them into their inactive GDP-bound form. This protein has a selective affinity for GNAZ and GNAI2 subunits, enhancing their GTPase activity and modulating their signaling activities. Additionally, RGS17 negatively impacts mu-opioid receptor-mediated G-protein activation.

Therapeutic significance:

Understanding the role of Regulator of G-protein signaling 17 could open doors to potential therapeutic strategies, particularly in disorders related to GPCR signaling such as neurological diseases and addiction.

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