AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Nephrocystin-3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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 sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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

Reaxense

upacc

Q7Z494

UPID:

NPHP3_HUMAN

Alternative names:

-

Alternative UPACC:

Q7Z494; Q5JPE3; Q5JPE6; Q68D99; Q6NVH3; Q7Z492; Q7Z493; Q8N9R2; Q8NCM5; Q96N70; Q96NK2

Background:

Nephrocystin-3 plays a crucial role in ciliary development and function, acting as a molecular switch between canonical and non-canonical Wnt signaling pathways. This protein is essential for proper cell movements during convergent extension, highlighting its significance in cellular organization and tissue morphology.

Therapeutic significance:

Linked to diseases such as Nephronophthisis 3, Renal-hepatic-pancreatic dysplasia 1, and Meckel syndrome 7, Nephrocystin-3's involvement in these conditions underscores its potential as a target for therapeutic intervention. Understanding the role of Nephrocystin-3 could open doors to potential therapeutic strategies.

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