AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable E3 SUMO-protein ligase RNF212

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.

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.

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

Q495C1

UPID:

RN212_HUMAN

Alternative names:

Probable E3 SUMO-protein transferase RNF212; RING finger protein 212

Alternative UPACC:

Q495C1; C9J8N0; Q495C0; Q86W82; Q8IY99; Q8N8U7

Background:

The Probable E3 SUMO-protein ligase RNF212 plays a pivotal role in meiosis, specifically in crossing-over, a critical process for genetic diversity. It acts as a SUMO E3 ligase, regulating the formation of crossover-specific recombination complexes by stabilizing key meiosis-specific factors such as MSH4, MSH5, and TEX11. Its activity is crucial for coupling chromosome synapsis to recombination, ensuring accurate genetic exchange and cell division.

Therapeutic significance:

RNF212's involvement in Spermatogenic failure 62, a disorder leading to male infertility due to non-obstructive azoospermia, highlights its potential as a target for therapeutic intervention. Understanding the role of RNF212 could open doors to potential therapeutic strategies, offering hope for treating infertility issues linked to meiotic failures.

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