Focused On-demand Libraries - Receptor.AI 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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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 employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Receptor.AI
 
UPACC
Q9H4A9

UPID:
DPEP2_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q9H4A9; A0A024R6Y5; B2RCF8; B3KS59; I3L248; Q6UX92; Q8TC95

BACKGROUND:
The protein Dipeptidase 2, with the unique identifier Q9H4A9, is instrumental in the breakdown of leukotriene D4 to leukotriene E4, a process vital for leukotriene signaling as detailed in PubMed:32325220. It also independently modulates the macrophage inflammatory response by acting on the NF-kappaB pathway.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Dipeptidase 2 offers a promising avenue for the development of new therapeutic approaches. Its dual role in leukotriene metabolism and inflammation modulation makes it a compelling target for drug discovery in managing inflammatory conditions.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.