Focused On-demand Library for Probable ATP-dependent RNA helicase DDX6

Details

Focused On-demand Libraries - Receptor.AI 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. Reaxense helps in synthesizing and delivering these compounds.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening 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.


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
Receptor.AI
 
UPACC
P26196

UPID:
DDX6_HUMAN

ALTERNATIVE NAMES:
ATP-dependent RNA helicase p54; DEAD box protein 6; Oncogene RCK

ALTERNATIVE UPACC:
P26196; Q5D048

BACKGROUND:
The Probable ATP-dependent RNA helicase DDX6, known under various names such as ATP-dependent RNA helicase p54, DEAD box protein 6, and Oncogene RCK, is crucial for RNA metabolism. It facilitates the formation of P-bodies, which are involved in the coordinated storage of mRNAs encoding regulatory functions. DDX6's role extends to preventing the degradation of translationally inactive mRNAs and participating in mRNA decapping. It also inhibits autophagy under nutrient-rich conditions by targeting ATG-related gene transcripts for degradation.

THERAPEUTIC SIGNIFICANCE:
Linked to Intellectual developmental disorder with impaired language and dysmorphic facies, DDX6's dysfunction manifests in significant developmental and physical anomalies. The exploration of DDX6's functions and mechanisms offers a promising avenue for developing targeted therapies for affected individuals.

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