AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable ATP-dependent RNA helicase DDX59

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

Reaxense

upacc

Q5T1V6

UPID:

DDX59_HUMAN

Alternative names:

DEAD box protein 59; Zinc finger HIT domain-containing protein 5

Alternative UPACC:

Q5T1V6; Q6PJL2; Q8IVW3; Q9H0W3

Background:

The Probable ATP-dependent RNA helicase DDX59, also known as DEAD box protein 59 and Zinc finger HIT domain-containing protein 5, plays a crucial role in RNA processing and modification, essential for cellular function and integrity. Its involvement in the intricate mechanisms of RNA metabolism positions it as a key player in cellular biology.

Therapeutic significance:

DDX59's association with Orofaciodigital syndrome 5, characterized by cleft palate, lobulated tongue, and polydactyly, underscores its clinical relevance. Understanding the role of DDX59 could open doors to potential therapeutic strategies for managing this complex disorder.

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