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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
Q9P202

UPID:
WHRN_HUMAN

ALTERNATIVE NAMES:
Autosomal recessive deafness type 31 protein

ALTERNATIVE UPACC:
Q9P202; A0A0C4DFT9; A5PKU1; A5PKZ9; Q5TAU9; Q5TAV0; Q5TAV1; Q5TAV2; Q96MZ9; Q9H9F4; Q9UFZ3

BACKGROUND:
The protein Whirlin, alternatively named Autosomal recessive deafness type 31 protein, is integral to sensory functions, particularly in hearing and vision. It is a critical member of the USH2 complex, necessary for the development and maintenance of stereocilia in the inner ear and for supporting the periciliary membrane complex in the retina, which is crucial for protein transport regulation.

THERAPEUTIC SIGNIFICANCE:
Given Whirlin's role in critical sensory diseases such as Deafness, autosomal recessive, 31, and Usher syndrome 2D, understanding its function could open doors to potential therapeutic strategies. This highlights the importance of research into Whirlin's mechanisms for developing novel treatments.

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