AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Pancreatic lipase-related 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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q17RR3

UPID:

LIPR3_HUMAN

Alternative names:

-

Alternative UPACC:

Q17RR3

Background:

Pancreatic lipase-related protein 3, encoded by the gene with the accession number Q17RR3, plays a crucial role in lipid metabolism. This enzyme is part of the lipase family, which is essential for the digestion and absorption of dietary fats in the gastrointestinal tract. Its specific functions and interactions within the lipid metabolism pathways highlight its importance in maintaining lipid homeostasis.

Therapeutic significance:

Understanding the role of Pancreatic lipase-related protein 3 could open doors to potential therapeutic strategies. Its pivotal role in lipid metabolism makes it a potential target for addressing disorders related to lipid digestion and absorption. Investigating this protein further could lead to breakthroughs in treating metabolic diseases.

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