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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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.


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
Q96MN2

UPID:
NALP4_HUMAN

ALTERNATIVE NAMES:
Cancer/testis antigen 58; PAAD and NACHT-containing protein 2; PYRIN and NACHT-containing protein 2; PYRIN-containing APAF1-like protein 4; Ribonuclease inhibitor 2

ALTERNATIVE UPACC:
Q96MN2; Q86W87; Q96AY6

BACKGROUND:
The protein NACHT, LRR, and PYD domains-containing protein 4, with aliases such as PYRIN-containing APAF1-like protein 4, is implicated in the body's defense mechanisms against pathogens. It serves as an adapter to facilitate the ubiquitination and subsequent degradation of activated TBK1, negatively regulating the type I interferon signaling pathway. Additionally, it plays a role in suppressing NF-kappaB activation in response to cytokines TNFA and IL1B.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of NACHT, LRR, and PYD domains-containing protein 4 holds promise for identifying novel therapeutic approaches.

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