Focused On-demand Library for Phospholipase A and acyltransferase 4

Focused On-demand Libraries - Receptor.AI 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.


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.


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 high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening 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.

PARTNER
Receptor.AI
 
UPACC
Q9UL19

UPID:
PLAT4_HUMAN

ALTERNATIVE NAMES:
HRAS-like suppressor 4; RAR-responsive protein TIG3; Retinoic acid receptor responder protein 3; Retinoid-inducible gene 1 protein; Tazarotene-induced gene 3 protein

ALTERNATIVE UPACC:
Q9UL19; B2R599; B4DDW2; E7ENZ7; O95200

BACKGROUND:
The protein Phospholipase A and acyltransferase 4, with aliases such as Retinoic acid receptor responder protein 3, exhibits multifaceted enzymatic activities. It is involved in the calcium-independent release and transfer of fatty acids within glycerophospholipids, showcasing significant PLA1 and PLA2 activities. Its enzymatic functions are essential for maintaining cellular lipid homeostasis and signaling.

THERAPEUTIC SIGNIFICANCE:
The exploration of Phospholipase A and acyltransferase 4's enzymatic roles offers a promising avenue for therapeutic intervention. Its critical functions in lipid signaling and metabolism position it as a potential target for developing novel treatments, highlighting the importance of further research into its mechanisms.

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