AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Large ribosomal subunit protein uL16m

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our associate Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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

Reaxense

upacc

Q9NX20

UPID:

RM16_HUMAN

Alternative names:

39S ribosomal protein L16, mitochondrial

Alternative UPACC:

Q9NX20; Q9BYD0; Q9HB70

Background:

The Large ribosomal subunit protein uL16m, also known as 39S ribosomal protein L16, mitochondrial, plays a crucial role in the mitochondrial ribosome. It is involved in the synthesis of proteins within mitochondria, essential for cellular energy production and metabolic processes. This protein's structure and function are vital for the proper assembly and functioning of the mitochondrial ribosome, making it a key player in cellular health and homeostasis.

Therapeutic significance:

Understanding the role of Large ribosomal subunit protein uL16m could open doors to potential therapeutic strategies. Its critical function in protein synthesis within mitochondria suggests that targeting this protein could offer new avenues for treating diseases related to mitochondrial dysfunction.

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