AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Dipeptidase 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

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

Q9H4A9

UPID:

DPEP2_HUMAN

Alternative names:

-

Alternative UPACC:

Q9H4A9; A0A024R6Y5; B2RCF8; B3KS59; I3L248; Q6UX92; Q8TC95

Background:

Dipeptidase 2, encoded by the gene with accession number Q9H4A9, plays a crucial role in leukotriene metabolism by hydrolyzing leukotriene D4 (LTD4) into leukotriene E4 (LTE4), as reported in PubMed:32325220. Beyond its enzymatic activity, it serves as a regulator of the NF-kappaB inflammatory signaling pathway, influencing macrophage inflammatory responses.

Therapeutic significance:

Understanding the role of Dipeptidase 2 could open doors to potential therapeutic strategies. Its involvement in leukotriene metabolism and regulation of inflammatory responses highlights its potential as a target for treating inflammatory diseases.

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