Focused On-demand Libraries - Receptor.AI 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.


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.


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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening 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.


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
Receptor.AI
 
UPACC
Q13219

UPID:
PAPP1_HUMAN

ALTERNATIVE NAMES:
Insulin-like growth factor-dependent IGF-binding protein 4 protease; Pregnancy-associated plasma protein A

ALTERNATIVE UPACC:
Q13219; B1AMF9; Q08371; Q68G52; Q9UDK7

BACKGROUND:
Pappalysin-1, identified by its alternative names Insulin-like growth factor-dependent IGF-binding protein 4 protease and Pregnancy-associated plasma protein A, is a metalloproteinase that regulates the availability of insulin-like growth factors by cleaving IGFBP-4 and IGFBP-5. This action is crucial for the proper functioning of IGF, with the cleavage of IGFBP-4 being notably increased by IGF presence, indicating a feedback mechanism that fine-tunes IGF activity.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Pappalysin-1 offers a pathway to innovative therapeutic approaches. Given its central role in controlling IGF levels, which are vital for growth, development, and metabolic regulation, targeting Pappalysin-1 could lead to breakthrough treatments in areas such as diabetes management, growth disorders, and wound healing.

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