AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ecto-ADP-ribosyltransferase 5

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our partner 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q96L15

UPID:

NAR5_HUMAN

Alternative names:

ADP-ribosyltransferase C2 and C3 toxin-like 5; Mono(ADP-ribosyl)transferase 5; NAD(P)(+)--arginine ADP-ribosyltransferase 5

Alternative UPACC:

Q96L15; C9IYG7; Q6UX84; Q86W02

Background:

Ecto-ADP-ribosyltransferase 5, known by its alternative names such as ADP-ribosyltransferase C2 and C3 toxin-like 5 and Mono(ADP-ribosyl)transferase 5, plays a crucial role in the ADP-ribosylation process. This modification involves the transfer of ADP-ribose from NAD+ to target proteins, impacting various cellular functions.

Therapeutic significance:

Understanding the role of Ecto-ADP-ribosyltransferase 5 could open doors to potential therapeutic strategies. Its involvement in key biochemical pathways underscores its potential as a target for drug discovery, aiming to modulate its activity for therapeutic benefits.

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