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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q7LDG7

UPID:
GRP2_HUMAN

ALTERNATIVE NAMES:
Calcium and DAG-regulated guanine nucleotide exchange factor I; Cdc25-like protein; F25B3.3 kinase-like protein

ALTERNATIVE UPACC:
Q7LDG7; A6NDC7; O00538; Q9UL65

BACKGROUND:
The protein RAS guanyl-releasing protein 2, with aliases such as Cdc25-like protein, functions as a crucial mediator in the exchange of GDP for GTP, activating Rap and several GTPases. Its involvement in platelet aggregation and immune cell adhesion underscores its importance in vascular and immune system functions.

THERAPEUTIC SIGNIFICANCE:
Its association with Bleeding disorder, platelet-type, 18, due to gene variants, underscores the therapeutic potential of targeting RAS guanyl-releasing protein 2 in bleeding disorders. Exploring this protein's mechanisms could lead to novel treatments for platelet dysfunction.

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