Focused On-demand Libraries - Receptor.AI 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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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
Receptor.AI
 
UPACC
Q86WG5

UPID:
MTMRD_HUMAN

ALTERNATIVE NAMES:
Inactive phosphatidylinositol 3-phosphatase 13; SET-binding factor 2

ALTERNATIVE UPACC:
Q86WG5; Q3MJF0; Q68DQ3; Q6P459; Q6PJD1; Q7Z325; Q7Z621; Q86VE2; Q96FE2; Q9C097

BACKGROUND:
The protein Myotubularin-related protein 13, known alternatively as Inactive phosphatidylinositol 3-phosphatase 13 and SET-binding factor 2, is crucial for cellular function. It activates RAB21 and RAB28, converting inactive GDP-bound Rab proteins to their active GTP-bound state. Essential in autophagy, it activates RAB21 for endolysosomal transport and autophagosome-lysosome fusion. Additionally, it serves as an adapter for MTMR2, increasing its activity towards specific phosphatidylinositols.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Charcot-Marie-Tooth disease 4B2, a disorder marked by progressive muscle atrophy and weakness, Myotubularin-related protein 13 represents a promising target for therapeutic intervention. Exploring its function and the genetic variants impacting its activity could pave the way for innovative treatments for this debilitating condition.

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