AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ribosomal oxygenase 1

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.

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.

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 high-tech, dedicated method is applied to construct targeted 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

Q9H6W3

UPID:

RIOX1_HUMAN

Alternative names:

60S ribosomal protein L8 histidine hydroxylase; Bifunctional lysine-specific demethylase and histidyl-hydroxylase NO66; Myc-associated protein with JmjC domain; Nucleolar protein 66; Ribosomal oxygenase NO66

Alternative UPACC:

Q9H6W3; B4DT02

Background:

Ribosomal oxygenase 1, known for its roles as a histone lysine demethylase and ribosomal histidine hydroxylase, is pivotal in histone code regulation and ribosome biogenesis. It specifically targets 'Lys-4' and 'Lys-36' of histone H3, influencing osteoblast differentiation and non-histone protein functions, such as CGAS demethylation. This protein is also identified by names like 60S ribosomal protein L8 histidine hydroxylase and Nucleolar protein 66.

Therapeutic significance:

Understanding the role of Ribosomal oxygenase 1 could open doors to potential therapeutic strategies.

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