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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are 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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening 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.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q8WTT0

UPID:
CLC4C_HUMAN

ALTERNATIVE NAMES:
Blood dendritic cell antigen 2; C-type lectin superfamily member 7; Dendritic lectin

ALTERNATIVE UPACC:
Q8WTT0; D3DUU3; Q3T1C3; Q6UXS8; Q8WXX8

BACKGROUND:
The protein C-type lectin domain family 4 member C, known alternatively as Dendritic lectin, is pivotal in antigen recognition and immune response modulation. It recognizes specific trisaccharide epitopes and efficiently targets antigens for presentation to T-cells, playing a role in the immune surveillance. Additionally, it may mediate inhibition of IFN-alpha/beta in dendritic cells and activate intracellular signaling pathways, highlighting its significance in immune regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of C-type lectin domain family 4 member C unveils potential avenues for therapeutic intervention.

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