AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ecto-ADP-ribosyltransferase 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 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

Reaxense

upacc

Q13508

UPID:

NAR3_HUMAN

Alternative names:

ADP-ribosyltransferase C2 and C3 toxin-like 3; Mono(ADP-ribosyl)transferase 3; NAD(P)(+)--arginine ADP-ribosyltransferase 3

Alternative UPACC:

Q13508; Q53XW3; Q6FHT7; Q8WVJ7; Q93069; Q96HL1

Background:

Ecto-ADP-ribosyltransferase 3, known by its alternative names such as ADP-ribosyltransferase C2 and C3 toxin-like 3 and Mono(ADP-ribosyl)transferase 3, plays a crucial role in the ADP-ribosylation process, a post-translational modification involving the addition of ADP-ribose moieties to arginine residues on target proteins. This enzymatic activity is pivotal in cellular signaling and regulation.

Therapeutic significance:

Understanding the role of Ecto-ADP-ribosyltransferase 3 could open doors to potential therapeutic strategies. Its involvement in key cellular processes underscores its potential as a target for drug discovery, aiming to modulate its activity for therapeutic benefits.

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