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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening 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.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P00488

UPID:
F13A_HUMAN

ALTERNATIVE NAMES:
Protein-glutamine gamma-glutamyltransferase A chain; Transglutaminase A chain

ALTERNATIVE UPACC:
P00488; Q59HA7; Q8N6X2; Q96P24; Q9BX29

BACKGROUND:
The Coagulation factor XIII A chain, known for its alternative names Protein-glutamine gamma-glutamyltransferase A chain and Transglutaminase A chain, is essential in the blood clotting process. It acts as a transglutaminase, facilitating gamma-glutamyl-epsilon-lysine cross-links between fibrin chains, thereby stabilizing the fibrin clot. This action is vital for the maintenance of clots, preventing excessive bleeding.

THERAPEUTIC SIGNIFICANCE:
The significance of Coagulation factor XIII A chain extends to its involvement in Factor XIII subunit A deficiency, an autosomal recessive disorder characterized by bleeding tendencies and impaired wound healing. The exploration of this protein's function and its genetic variants could lead to innovative treatments for affected individuals, underscoring the importance of research in this area.

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