Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


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
Q13191

UPID:
CBLB_HUMAN

ALTERNATIVE NAMES:
Casitas B-lineage lymphoma proto-oncogene b; RING finger protein 56; RING-type E3 ubiquitin transferase CBL-B; SH3-binding protein CBL-B; Signal transduction protein CBL-B

ALTERNATIVE UPACC:
Q13191; A8K9S7; B7WNM4; Q13192; Q13193; Q3LIC0; Q63Z43; Q8IVC5

BACKGROUND:
The protein E3 ubiquitin-protein ligase CBL-B, with alternative names such as RING finger protein 56 and Signal transduction protein CBL-B, is crucial for ubiquitination processes affecting TCR, BCR, and FCER1 pathways. It negatively regulates these pathways, influencing T-cell activation, proliferation, and anergy, as well as B-cell receptor signaling.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of E3 ubiquitin-protein ligase CBL-B holds promise for uncovering novel therapeutic approaches. Its regulatory role in immune signaling pathways positions it as a potential target for developing treatments for autoimmune diseases and other immune-related conditions.

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