Focused On-demand Libraries - Receptor.AI 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 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.


Our top-notch dedicated system is used to design specialised 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
Q9BXN2

UPID:
CLC7A_HUMAN

ALTERNATIVE NAMES:
Beta-glucan receptor; C-type lectin superfamily member 12; Dendritic cell-associated C-type lectin 1

ALTERNATIVE UPACC:
Q9BXN2; B2R861; B7Z494; B7Z5A9; B7Z5B9; Q6IPS7; Q96D32; Q96DR9; Q96LD3; Q96PA4; Q96PA5; Q96PA6; Q96PA7; Q96PA8; Q9H1K3

BACKGROUND:
The protein C-type lectin domain family 7 member A, known for its alternative names such as Beta-glucan receptor, is a key player in the body's defense mechanism against bacterial and fungal pathogens. It activates crucial signaling pathways that result in the production of pro-inflammatory cytokines and chemokines, essential for an effective immune response. Additionally, it plays a role in T-cell activation and proliferation.

THERAPEUTIC SIGNIFICANCE:
Exploring the therapeutic potential of C-type lectin domain family 7 member A, especially in the context of its involvement in Candidiasis, familial, 4, opens new avenues for drug discovery. Enhancing our understanding of this protein's function could pave the way for innovative treatments for immune-compromised individuals.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.