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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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
Q13432

UPID:
U119A_HUMAN

ALTERNATIVE NAMES:
Retinal protein 4

ALTERNATIVE UPACC:
Q13432; A8K8G4; F1T095; O95126

BACKGROUND:
The Protein unc-119 homolog A, known alternatively as Retinal protein 4, is integral to synaptic functions in photoreceptor cells and immune signal transduction. It activates Src family kinases, aids in endosome recycling, bacteria uptake, endocytosis, and traffics proteins in sensory neurons. It specifically binds to the myristoyl moiety of proteins, playing a key role in their cellular localization and trafficking, particularly in photoreceptor cells and sensory neurons.

THERAPEUTIC SIGNIFICANCE:
Linked to Immunodeficiency 13, a condition marked by a lowered CD4 T-lymphocyte count without HIV infection, Protein unc-119 homolog A's mutation underscores its therapeutic significance. Exploring its functions and interactions offers a promising pathway to novel treatments for this immunodeficiency.

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