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

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.

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

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's 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.