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

Details

Focused On-demand Libraries - Receptor.AI 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. Reaxense aids in their synthesis and provision.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening 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
Receptor.AI
 
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:
The protein MID2, with alternative names such as Midline defect 2 and RING finger protein 60, functions as an E3 ubiquitin ligase. It is pivotal in the 'Lys-48'-linked polyubiquitination of LRRK2, facilitating its proteasomal degradation and microtubule association in neuronal cells. This ubiquitination process is critical for controlling LRRK2 kinase activity through inhibition by RAB29.

THERAPEUTIC SIGNIFICANCE:
Linked to the disease Intellectual developmental disorder, X-linked 101, MID2's involvement suggests its potential as a therapeutic target. The disorder manifests with global developmental delay and hyperactivity, pointing to the significance of MID2 in neurological development and function.

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