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

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

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.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.