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

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.

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.

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.

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

 Fig. 1. The sreening 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

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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