Focused On-demand Libraries - Receptor.AI 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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


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
Receptor.AI
 
UPACC
Q08116

UPID:
RGS1_HUMAN

ALTERNATIVE NAMES:
B-cell activation protein BL34; Early response protein 1R20

ALTERNATIVE UPACC:
Q08116; B2RDM9; B4DZY0; Q07918; Q9H1W2

BACKGROUND:
The protein Regulator of G-protein signaling 1, with alternative names B-cell activation protein BL34 and Early response protein 1R20, is pivotal in regulating G protein-coupled receptor signaling cascades. It notably inhibits B cell chemotaxis toward CXCL12 and signal transduction by driving G protein alpha subunits into their inactive GDP-bound form. This action is critical for the proper functioning of signaling pathways involved in cellular responses to external stimuli.

THERAPEUTIC SIGNIFICANCE:
The exploration of Regulator of G-protein signaling 1's function offers promising avenues for therapeutic intervention. Given its regulatory role in signal transduction and immune cell migration, targeting RGS1 could lead to innovative treatments for diseases where these processes are dysregulated.

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