Focused On-demand Library for Large ribosomal subunit protein uL24m

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening 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 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.







Alternative names:

39S ribosomal protein L24, mitochondrial

Alternative UPACC:

Q96A35; D3DVC8; Q53G65; Q53HT0; Q5SYZ9; Q5SZ00; Q5SZ02; Q96Q70; Q9H7G3


The Large ribosomal subunit protein uL24m, also known as 39S ribosomal protein L24, mitochondrial, plays a crucial role in the mitochondrial ribosome. It is part of the 39S large ribosomal subunit and is involved in protein synthesis within mitochondria. The protein's structure and function are essential for the mitochondrial ribosome's ability to translate mitochondrial mRNA into functional proteins, which is vital for mitochondrial energy production and cellular metabolism.

Therapeutic significance:

Understanding the role of Large ribosomal subunit protein uL24m could open doors to potential therapeutic strategies. Its pivotal function in mitochondrial protein synthesis makes it an intriguing target for research aimed at addressing mitochondrial disorders and diseases linked to mitochondrial dysfunction.

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