AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Cytosolic phospholipase A2 gamma

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

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

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening 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

Reaxense

upacc

Q9UP65

UPID:

PA24C_HUMAN

Alternative names:

Cytosolic lysophospholipase; Cytosolic lysophospholipid O-acyltransferase; Phospholipase A2 group IVC

Alternative UPACC:

Q9UP65; B2RB71; B4DI40; O75457; Q6IBI8; Q9UG68

Background:

Cytosolic phospholipase A2 gamma, also known as cytosolic lysophospholipase and cytosolic lysophospholipid O-acyltransferase, plays a crucial role in phospholipid remodeling, impacting endoplasmic reticulum membrane homeostasis and lipid droplet biogenesis. This enzyme preferentially targets the sn-2 position of phospholipids, facilitating the production of lysophospholipids crucial for deacylation-reacylation cycles. It also participates in the formation of various glycerophospholipids through the transfer of sn-1 fatty acyl groups.

Therapeutic significance:

Understanding the role of Cytosolic phospholipase A2 gamma could open doors to potential therapeutic strategies. Its involvement in lipid metabolism and membrane dynamics suggests its potential as a target in diseases related to lipid dysregulation and membrane-associated disorders.

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