Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 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 use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
Q9HDD0

UPID:
PLAT1_HUMAN

ALTERNATIVE NAMES:
HRAS-like suppressor 1; Phospholipid-metabolizing enzyme A-C1

ALTERNATIVE UPACC:
Q9HDD0; D2KX19; Q6X7C0; Q86WS9; X6R3D1

BACKGROUND:
The protein Phospholipase A and acyltransferase 1, with alternative names HRAS-like suppressor 1 and Phospholipid-metabolizing enzyme A-C1, is pivotal in lipid metabolism. It demonstrates both phospholipase A1/2 and acyltransferase activities, crucial for the calcium-independent release and transfer of fatty acids in glycerophospholipids. Its enzymatic functions highlight its significance in cellular lipid management.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Phospholipase A and acyltransferase 1 holds the key to unlocking new therapeutic avenues. Given its central role in lipid metabolism, targeting this protein could lead to innovative treatments for metabolic diseases.

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