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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


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
P61353

UPID:
RL27_HUMAN

ALTERNATIVE NAMES:
60S ribosomal protein L27

ALTERNATIVE UPACC:
P61353; P08526; Q4G0A9

BACKGROUND:
Large ribosomal subunit protein eL27, known as 60S ribosomal protein L27, is integral to the ribosome, facilitating rRNA processing and the maturation of 28S and 5.8S rRNAs. Its function is pivotal for the ribosomal assembly and protein synthesis, reflecting its critical role in cellular mechanisms and the overall process of gene expression.

THERAPEUTIC SIGNIFICANCE:
The association of Large ribosomal subunit protein eL27 with Diamond-Blackfan anemia 16 underscores its potential in disease research. Given its crucial role in ribosomal function and protein synthesis, targeting Large ribosomal subunit protein eL27 could offer new avenues for therapeutic intervention in treating Diamond-Blackfan anemia and possibly other ribosomopathies.

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