Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by 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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


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
Receptor.AI
 
UPACC
Q13614

UPID:
MTMR2_HUMAN

ALTERNATIVE NAMES:
Phosphatidylinositol-3,5-bisphosphate 3-phosphatase; Phosphatidylinositol-3-phosphate phosphatase

ALTERNATIVE UPACC:
Q13614; A6NN98; Q9UPS9

BACKGROUND:
The Myotubularin-related protein 2, with alternative names such as Phosphatidylinositol-3-phosphate phosphatase, is pivotal in phosphoinositide metabolism. It binds and dephosphorylates various phosphatidylinositols, playing a key role in cellular signaling and membrane dynamics. Its interaction with SBF2/MTMR13 protein highlights its importance in nerve cell stability.

THERAPEUTIC SIGNIFICANCE:
Given its association with Charcot-Marie-Tooth disease 4B1, a genetic neuropathy, the study of Myotubularin-related protein 2 offers promising avenues for therapeutic intervention. Its critical role in nerve function makes it a potential target for novel therapies.

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