AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Phospholipase A and acyltransferase 1

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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

Q9HDD0

UPID:

PLAT1_HUMAN

Alternative names:

HRAS-like suppressor 1; Phospholipid-metabolizing enzyme A-C1

Alternative UPACC:

Q9HDD0; D2KX19; Q6X7C0; Q86WS9; X6R3D1

Background:

Phospholipase A and acyltransferase 1, also known as HRAS-like suppressor 1 and Phospholipid-metabolizing enzyme A-C1, plays a crucial role in lipid metabolism. It exhibits phospholipase A1/2 and acyltransferase activities, catalyzing the release of fatty acids from glycerophospholipids and transferring fatty acyl groups among lipids. This protein's ability to modify phospholipids suggests its importance in cellular processes.

Therapeutic significance:

Understanding the role of Phospholipase A and acyltransferase 1 could open doors to potential therapeutic strategies. Its involvement in lipid metabolism and modification makes it a promising target for drug discovery, aiming to regulate lipid-related disorders.

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