Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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
Q8TCF1

UPID:
ZFAN1_HUMAN

ALTERNATIVE NAMES:
Zinc finger AN1-type-containing protein 1

ALTERNATIVE UPACC:
Q8TCF1; E5RIG0; E5RJ99; Q658R7; Q6IA32; Q6PGQ6; Q9H810

BACKGROUND:
The AN1-type zinc finger protein 1, identified by its alternative name Zinc finger AN1-type-containing protein 1, is integral to the dynamic and transient formation of cytoplasmic ribonucleoprotein assemblies known as stress granules (SGs). These assemblies are crucial under conditions of acute stress for the suspension of protein synthesis, ensuring cellular protein homeostasis. Its involvement in the specific and efficient clearance of SGs post-arsenite stress through key cellular machinery highlights its importance in avoiding aberrant SG degradation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of AN1-type zinc finger protein 1 holds promise for unveiling novel therapeutic avenues.

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