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 utilise our cutting-edge, exclusive workflow to develop focused 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q9NP92

UPID:
RT30_HUMAN

ALTERNATIVE NAMES:
39S ribosomal protein S30, mitochondrial; Large ribosomal subunit protein mS30; Programmed cell death protein 9

ALTERNATIVE UPACC:
Q9NP92; Q96I91; Q96Q19; Q9H0P8; Q9NSF9; Q9NZ76

BACKGROUND:
Large ribosomal subunit protein mL65, known alternatively as Large ribosomal subunit protein mS30 and Programmed cell death protein 9, is integral to mitochondrial protein synthesis and apoptosis regulation. This protein's function underscores the intricate relationship between mitochondrial health and programmed cell death, both of which are vital for maintaining cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Large ribosomal subunit protein mL65 holds the promise of unveiling novel therapeutic avenues. Given its central role in mitochondrial biogenesis and apoptosis, targeting this protein could lead to breakthroughs in the treatment of diseases linked to mitochondrial dysfunction and aberrant apoptosis.

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