Focused On-demand Library for 1-acylglycerol-3-phosphate O-acyltransferase PNPLA3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 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.

We utilise our cutting-edge, exclusive workflow to develop focused 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Acylglycerol transacylase; Adiponutrin; Calcium-independent phospholipase A2-epsilon; Lysophosphatidic acid acyltransferase; Patatin-like phospholipase domain-containing protein 3

Alternative UPACC:

Q9NST1; B0QYI0; B2RCL3; B3KW00; Q6P1A1; Q96CB4


1-acylglycerol-3-phosphate O-acyltransferase PNPLA3, also known as Adiponutrin, plays a crucial role in lipid metabolism. It catalyzes the acylation of lysophosphatidic acid to phosphatidic acid, a key intermediate in the synthesis of triglycerides and glycerophospholipids. This enzyme exhibits specificity for long-chain fatty acyl-CoAs and has additional activities that may influence triglyceride remodeling.

Therapeutic significance:

PNPLA3 is implicated in Non-alcoholic fatty liver disease (NAFLD), a prevalent condition in Western countries characterized by triglyceride accumulation in the liver. Understanding the role of PNPLA3 could open doors to potential therapeutic strategies for NAFLD, aiming to mitigate disease progression and associated metabolic complications.

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