AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Myotubularin-related protein 1

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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

Reaxense

upacc

Q13613

UPID:

MTMR1_HUMAN

Alternative names:

Phosphatidylinositol-3,5-bisphosphate 3-phosphatase; Phosphatidylinositol-3-phosphate phosphatase

Alternative UPACC:

Q13613; A0A024RC07; Q9UBX6; Q9UEM0; Q9UQD5

Background:

Myotubularin-related protein 1, known for its specificity towards phosphatidylinositol 3-phosphate, plays a crucial role in lipid phosphatase activity, distinguishing itself by not acting on other phosphatidylinositols. This protein, alternatively named Phosphatidylinositol-3,5-bisphosphate 3-phosphatase and Phosphatidylinositol-3-phosphate phosphatase, is pivotal in cellular processes.

Therapeutic significance:

Understanding the role of Myotubularin-related protein 1 could open doors to potential therapeutic strategies, offering new avenues for drug discovery and development in targeting lipid-related disorders.

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