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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9H4B8

UPID:
DPEP3_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q9H4B8; B3KQ48; Q6PEZ5; Q6UXE4

BACKGROUND:
The enzyme Dipeptidase 3, with the unique identifier Q9H4B8, exhibits a distinct lack of dipeptidase activity. This is due to its inability to activate the nucleophilic water/hydroxide, a consequence of having asparagine at position 359 instead of the typical aspartate, and a reduced affinity for the beta zinc caused by a tyrosine at position 269. These structural peculiarities hinder its ability to hydrolyze certain substrates, including cystinyl-bis-glycine, leukotriene D4, and imipenem.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionality of Dipeptidase 3 offers a pathway to uncovering new therapeutic avenues. The enzyme's specific structural and functional nuances highlight its potential as a target for drug discovery, aiming to manipulate its activity for therapeutic gain in diseases where its activity modulation could be advantageous.

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