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.


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.


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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


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
O75394

UPID:
RM33_HUMAN

ALTERNATIVE NAMES:
39S ribosomal protein L33, mitochondrial

ALTERNATIVE UPACC:
O75394; Q53RZ6; Q5FVE3; Q96Q50

BACKGROUND:
Large ribosomal subunit protein bL33m, alternatively known as 39S ribosomal protein L33, mitochondrial, is integral to mitochondrial ribosomes. This protein's role is indispensable for the synthesis of proteins within mitochondria, underscoring its significance in maintaining mitochondrial health and overall cellular energy homeostasis. The synthesis of mitochondrial DNA-encoded proteins, facilitated by bL33m, is crucial for proper mitochondrial operations.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Large ribosomal subunit protein bL33m holds promise for unveiling novel therapeutic avenues. Given its vital role in mitochondrial protein synthesis, targeting bL33m could offer new strategies for treating mitochondrial-related diseases and enhancing mitochondrial function in various disorders.

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