Focused On-demand Library for Double-stranded RNA-specific editase 1

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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

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.


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
P78563

UPID:
RED1_HUMAN

ALTERNATIVE NAMES:
RNA-editing deaminase 1; RNA-editing enzyme 1; dsRNA adenosine deaminase

ALTERNATIVE UPACC:
P78563; A6NFK8; A6NJ84; C3TTQ1; C3TTQ2; C9JUP4; G5E9B4; O00395; O00465; O00691; O00692; P78555; Q4AE77; Q4AE79; Q6P0M9; Q8NFA1; Q8NFD1

BACKGROUND:
RNA-editing enzyme 1, with its alternative names RNA-editing deaminase 1 and dsRNA adenosine deaminase, is pivotal in the hydrolytic deamination of adenosine to inosine in dsRNA, affecting RNA virus replication and cellular RNA functions. It has distinct isoforms with varying catalytic activities, influencing the editing efficiency of transcripts encoding key proteins in neurotransmission and cellular signaling.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in a neurodevelopmental disorder characterized by severe developmental delays, seizures, and microcephaly, targeting Double-stranded RNA-specific editase 1 offers a promising avenue for developing novel therapeutic interventions. Understanding the role of this protein could open doors to potential therapeutic strategies.

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