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.


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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening 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 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
P52961

UPID:
NAR1_HUMAN

ALTERNATIVE NAMES:
ADP-ribosyltransferase C2 and C3 toxin-like 1; Mono(ADP-ribosyl)transferase 1

ALTERNATIVE UPACC:
P52961; Q6NTD2; Q96KT9

BACKGROUND:
The protein GPI-linked NAD(P)(+)--arginine ADP-ribosyltransferase 1, with alternative names such as ADP-ribosyltransferase C2 and C3 toxin-like 1 and Mono(ADP-ribosyl)transferase 1, is distinguished by its ADP-ribosyltransferase activity toward GLP1R. This activity underlines the protein's significant role in modulating cellular functions and signaling mechanisms.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of GPI-linked NAD(P)(+)--arginine ADP-ribosyltransferase 1 offers a promising avenue for the development of innovative therapeutic approaches. Given its crucial role in influencing GLP1R, targeting this protein could lead to breakthroughs in the treatment of diseases related to metabolic regulation.

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