AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for ATP-dependent DNA helicase Q4

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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening 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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

O94761

UPID:

RECQ4_HUMAN

Alternative names:

DNA helicase, RecQ-like type 4; RTS; RecQ protein-like 4

Alternative UPACC:

O94761; A0A087WZ30; Q3Y424; Q96DW2; Q96F55

Background:

ATP-dependent DNA helicase Q4, also known as DNA helicase, RecQ-like type 4, RTS, and RecQ protein-like 4, plays a crucial role in DNA repair mechanisms. Its activity as a DNA-dependent ATPase may modulate chromosome segregation, highlighting its importance in maintaining genomic stability.

Therapeutic significance:

The protein is implicated in RAPADILINO syndrome, Baller-Gerold syndrome, and Rothmund-Thomson syndrome 2, all of which are caused by variants affecting its gene. Understanding the role of ATP-dependent DNA helicase Q4 could open doors to potential therapeutic strategies for these genetic disorders.

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