AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for NLR family CARD domain-containing protein 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We utilise our cutting-edge, exclusive workflow to develop focused 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.

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

Reaxense

upacc

Q7RTR2

UPID:

NLRC3_HUMAN

Alternative names:

CARD15-like protein; Caterpiller protein 16.2; NACHT, LRR and CARD domains-containing protein 3; Nucleotide-binding oligomerization domain protein 3

Alternative UPACC:

Q7RTR2; Q5EY36; Q8NF48; Q8NI01; Q8NI02; Q8TEL3

Background:

NLR family CARD domain-containing protein 3, also known as Nucleotide-binding oligomerization domain protein 3, plays a crucial role in regulating the innate immune response. It modulates signaling pathways activated by Toll-like receptors and the DNA sensor STING, impacting responses to pathogen-associated molecular patterns and DNA virus infections. This protein also influences the PI3K-AKT-mTOR pathway, affecting cell proliferation, especially in intestinal epithelial cells.

Therapeutic significance:

Understanding the role of NLR family CARD domain-containing protein 3 could open doors to potential therapeutic strategies.

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