Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of 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
Q8TCC3

UPID:
RM30_HUMAN

ALTERNATIVE NAMES:
39S ribosomal protein L28, mitochondrial; 39S ribosomal protein L30, mitochondrial

ALTERNATIVE UPACC:
Q8TCC3; A6NIC6; D3DVI0; D3DVI3; Q0D2Q7; Q6ZTP4; Q96Q69; Q9P0N0

BACKGROUND:
Large ribosomal subunit protein uL30m, identified by its alternative names 39S ribosomal protein L28 and L30, mitochondrial, is integral to mitochondrial protein synthesis. This protein is a component of the 39S large ribosomal subunit, where it facilitates the translation of mitochondrial DNA-encoded proteins. These proteins are vital for mitochondrial function and, by extension, cellular energy metabolism, highlighting the protein's importance in maintaining cellular health and function.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Large ribosomal subunit protein uL30m offers a promising avenue for developing novel therapeutic approaches. Given its central role in mitochondrial protein synthesis, targeting this protein could lead to breakthroughs in treating conditions associated with mitochondrial dysfunction, offering hope for innovative treatments.

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