Focused On-demand Libraries - Receptor.AI 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.


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 employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening 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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q14147

UPID:
DHX34_HUMAN

ALTERNATIVE NAMES:
DEAH box protein 34; DExH-box helicase 34

ALTERNATIVE UPACC:
Q14147; B4DMY8

BACKGROUND:
Probable ATP-dependent RNA helicase DHX34, identified by its alternative names DEAH box protein 34 and DExH-box helicase 34, is a pivotal component in the regulation of mRNA stability. By requiring ATP for its helicase activity, DHX34 targets mRNA transcripts with premature stop codons for degradation, a process vital for cellular mRNA quality control. Its interaction with UPF1, UPF2, and EIF4A3 is critical for the NMD pathway's efficiency. DHX34's modulation of the RUVBL1-RUVBL2 complex's activity further underscores its importance in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Probable ATP-dependent RNA helicase DHX34 could open doors to potential therapeutic strategies.

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