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

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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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