AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable E3 ubiquitin-protein ligase makorin-3

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

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

Q13064

UPID:

MKRN3_HUMAN

Alternative names:

RING finger protein 63; RING-type E3 ubiquitin transferase makorin-3; Zinc finger protein 127

Alternative UPACC:

Q13064

Background:

Probable E3 ubiquitin-protein ligase makorin-3, also known as RING finger protein 63, RING-type E3 ubiquitin transferase makorin-3, and Zinc finger protein 127, plays a crucial role in protein ubiquitination. This process involves the attachment of ubiquitin moieties onto substrate proteins, marking them for various cellular processes including degradation, signaling, and trafficking.

Therapeutic significance:

The protein is implicated in Precocious puberty, central 2, a condition characterized by the early onset of puberty due to premature activation of the hypothalamic-pituitary-gonadal axis. Understanding the role of makorin-3 in this condition could pave the way for novel therapeutic strategies targeting early puberty onset.

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