Focused On-demand Library for Phospholipid-transporting ATPase IG

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.


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.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


Our high-tech, dedicated method is applied to construct targeted 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
Q8NB49

UPID:
AT11C_HUMAN

ALTERNATIVE NAMES:
ATPase IQ; ATPase class VI type 11C; P4-ATPase flippase complex alpha subunit ATP11C

ALTERNATIVE UPACC:
Q8NB49; Q5JT69; Q5JT70; Q5JT71; Q5JT72; Q5JT73; Q6ZND5; Q6ZU50; Q6ZUP7; Q70IJ9; Q70IK0; Q8WX24

BACKGROUND:
The Phospholipid-transporting ATPase IG, known under various names including ATPase IQ and ATPase class VI type 11C, is integral to the translocation of phosphatidylserines and phosphatidylethanolamines from the outer to the inner leaflet of the plasma membrane. Its function is vital for the preservation of plasma membrane asymmetry, a key factor in cellular health and signaling.

THERAPEUTIC SIGNIFICANCE:
Given its crucial role in maintaining erythrocyte integrity and preventing premature cell clearance, Phospholipid-transporting ATPase IG is a significant target in the study of congenital X-linked hemolytic anemia. The exploration of this protein's functions and mechanisms offers promising avenues for the development of novel therapeutic interventions for this and potentially other related disorders.

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