AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Myotubularin-related protein 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

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

Q13615

UPID:

MTMR3_HUMAN

Alternative names:

FYVE domain-containing dual specificity protein phosphatase 1; Phosphatidylinositol-3,5-bisphosphate 3-phosphatase; Phosphatidylinositol-3-phosphate phosphatase; Zinc finger FYVE domain-containing protein 10

Alternative UPACC:

Q13615; A5PL26; A7MD32; Q9NYN5; Q9NYN6; Q9UDX6; Q9UEG3

Background:

Myotubularin-related protein 3, also known as Phosphatidylinositol-3,5-bisphosphate 3-phosphatase, plays a crucial role in lipid signaling pathways by dephosphorylating phosphoinositides. It specifically targets phosphatidylinositol 3-phosphate and phosphatidylinositol 3,5-bisphosphate, and may also act on proteins phosphorylated on Ser, Thr, and Tyr residues. This protein is encoded by the gene with the UniProt accession number Q13615.

Therapeutic significance:

Understanding the role of Myotubularin-related protein 3 could open doors to potential therapeutic strategies. Its involvement in lipid signaling pathways suggests a pivotal role in cellular processes, making it a target of interest in drug discovery.

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