Focused On-demand Library for Regulator of G-protein signaling 1

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.

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 use our state-of-the-art dedicated workflow for designing focused libraries.

Fig. 1. The sreening 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.

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

Q08116

UPID:

RGS1_HUMAN

Alternative names:

B-cell activation protein BL34; Early response protein 1R20

Alternative UPACC:

Q08116; B2RDM9; B4DZY0; Q07918; Q9H1W2

Background:

Regulator of G-protein signaling 1 (RGS1), also known as B-cell activation protein BL34 and Early response protein 1R20, plays a crucial role in modulating G protein-coupled receptor signaling pathways. It achieves this by enhancing the GTPase activity of G protein alpha subunits, leading them to their inactive GDP-bound form, thus inhibiting signal transduction. This regulatory mechanism is vital in various cellular processes, including those downstream of the N-formylpeptide chemoattractant receptors and leukotriene receptors.

Therapeutic significance:

Understanding the role of Regulator of G-protein signaling 1 could open doors to potential therapeutic strategies. Its ability to inhibit B cell chemotaxis toward CXCL12 suggests its potential in modulating immune responses, making it a target of interest in the development of treatments for immune-related disorders.