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 use our state-of-the-art dedicated workflow for designing 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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q96F07

UPID:
CYFP2_HUMAN

ALTERNATIVE NAMES:
p53-inducible protein 121

ALTERNATIVE UPACC:
Q96F07; A6NLT2; D3DQJ3; Q53EN5; Q9NTK4; Q9ULQ2; Q9UN29

BACKGROUND:
The Cytoplasmic FMR1-interacting protein 2, alternatively named p53-inducible protein 121, is involved in crucial cellular processes including T-cell adhesion and the induction of apoptosis via p53/TP53. It is integral to the WAVE1 complex, facilitating BDNF-NTRK2 signaling necessary for endocytic trafficking from early endosomes.

THERAPEUTIC SIGNIFICANCE:
Linked to Developmental and Epileptic Encephalopathy 65, a condition characterized by intractable seizures and profound developmental delays, Cytoplasmic FMR1-interacting protein 2's function suggests its potential as a target for therapeutic intervention in DEE65.

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