Focused On-demand Library for Dipeptidyl peptidase 9

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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.







Alternative names:

Dipeptidyl peptidase IV-related protein 2; Dipeptidyl peptidase IX; Dipeptidyl peptidase-like protein 9

Alternative UPACC:

Q86TI2; O75273; O75868; Q1ZZB8; Q6AI37; Q6UAL0; Q6ZMT2; Q6ZNJ5; Q8N2J7; Q8N3F5; Q8WXD8; Q96NT8; Q9BVR3


Dipeptidyl peptidase 9 (DPP9) exhibits crucial enzymatic activity, cleaving N-terminal dipeptides from proteins with Pro or Ala at position 2. It plays a pivotal role in inhibiting caspase-1-dependent pyroptosis in monocytes and macrophages by blocking NLRP1 and CARD8 activation. DPP9's interaction with these components prevents their oligomerization, crucial for inflammasome activity, highlighting its regulatory function in inflammation.

Therapeutic significance:

Understanding the role of Dipeptidyl peptidase 9 could open doors to potential therapeutic strategies. Its involvement in regulating inflammation and pyroptosis positions it as a target for developing treatments aimed at inflammatory diseases and immune response modulation.

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