Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


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
Receptor.AI
 
UPACC
Q9NRY4

UPID:
RHG35_HUMAN

ALTERNATIVE NAMES:
Glucocorticoid receptor DNA-binding factor 1; Glucocorticoid receptor repression factor 1; Rho GAP p190A

ALTERNATIVE UPACC:
Q9NRY4; A7E2A4; Q14452; Q9C0E1

BACKGROUND:
The Rho GTPase-activating protein 35, also referred to as Glucocorticoid receptor repression factor 1, is integral to the regulation of cell morphology and motility. It achieves this through its GAP activity, influencing Rho and Rac GTPases. The protein binds to acidic phospholipids, affecting cell adhesion, migration, and various developmental processes. It is involved in signal transduction from cell-surface adhesion molecules to promote neurite outgrowth and plays a crucial role in polarized cell migration, ciliogenesis, and cilia elongation.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Rho GTPase-activating protein 35 could open doors to potential therapeutic strategies.

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