AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Large ribosomal subunit protein mL64

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted 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.

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

Reaxense

upacc

Q8TAE8

UPID:

G45IP_HUMAN

Alternative names:

39S ribosomal protein L59, mitochondrial; CKII beta-associating protein; CR6-interacting factor 1; Growth arrest and DNA damage-inducible proteins-interacting protein 1; Papillomavirus L2-interacting nuclear protein 1; p53-responsive gene 6 protein

Alternative UPACC:

Q8TAE8; Q8IVM3; Q8TE51; Q969P9; Q9BSM6

Background:

Large ribosomal subunit protein mL64, also known as 39S ribosomal protein L59, mitochondrial, plays a crucial role in cellular processes. It acts as a negative regulator of G1 to S cell cycle phase progression by inhibiting cyclin-dependent kinases. Its inhibitory effects are additive with GADD45 proteins, highlighting its significance in cell cycle control. Additionally, it represses the orphan nuclear receptor NR4A1, indicating its involvement in hormone-mediated regulation and mitochondrial protein synthesis.

Therapeutic significance:

Understanding the role of Large ribosomal subunit protein mL64 could open doors to potential therapeutic strategies.

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