Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by 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 screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
O77932

UPID:
DXO_HUMAN

ALTERNATIVE NAMES:
5'-3' exoribonuclease DXO; Dom-3 homolog Z; NAD-capped RNA hydrolase DXO

ALTERNATIVE UPACC:
O77932; A2CER3; B0UZ80; O15004; O78127; O78128; Q5ST60; Q6IPZ2; Q9NPK4

BACKGROUND:
Decapping and exoribonuclease protein, identified by alternative names such as 5'-3' exoribonuclease DXO, Dom-3 homolog Z, and NAD-capped RNA hydrolase DXO, is pivotal in RNA decay mechanisms. It specifically targets NAD-capped RNAs, removing the NAD moiety and facilitating mRNA decay, a process distinct from the action of canonical decapping enzymes. This protein is responsive to environmental stress, preferentially acting on NAD-capped transcripts. It also plays a role in the quality control of pre-mRNA capping by degrading mRNAs with defective m7G caps, showcasing its versatility in RNA metabolism.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Decapping and exoribonuclease protein could open doors to potential therapeutic strategies.

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