AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable E3 ubiquitin-protein ligase MID2

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.

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 includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

Q9UJV3

UPID:

TRIM1_HUMAN

Alternative names:

Midin-2; Midline defect 2; Midline-2; RING finger protein 60; RING-type E3 ubiquitin transferase MID2; Tripartite motif-containing protein 1

Alternative UPACC:

Q9UJV3; A6NEL8; A6PVI5; Q5JYF5; Q8WWK1; Q9UJR9

Background:

Probable E3 ubiquitin-protein ligase MID2, also known as Midin-2, plays a crucial role in microtubule stabilization. It achieves this by mediating the 'Lys-48'-linked polyubiquitination of LRRK2, which not only drives its localization to microtubules but also its proteasomal degradation in neurons. This process is essential for inhibiting LRRK2 kinase activation by RAB29.

Therapeutic significance:

MID2 is linked to Intellectual developmental disorder, X-linked 101, characterized by intellectual deficiency, developmental delays, and in some cases, seizures. Understanding the role of MID2 could open doors to potential therapeutic strategies for this disorder.

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