Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
P54317

UPID:
LIPR2_HUMAN

ALTERNATIVE NAMES:
Cytotoxic T lymphocyte lipase; Galactolipase; Triacylglycerol lipase

ALTERNATIVE UPACC:
P54317; A0A075B781; A8K627; Q6IB55

BACKGROUND:
The enzyme Pancreatic lipase-related protein 2, with aliases such as Cytotoxic T lymphocyte lipase, is integral to fat digestion and metabolism. It efficiently processes triglycerides and galactosylglycerides, releasing essential fatty acids. Beyond neonatal nutrition, it contributes to cell lysis in cytotoxic T cells and plays a role in neuronal development by facilitating the localization of specific phospholipids to neurite tips. Its broad substrate specificity allows it to act on medium- to long-chain fatty acyls in both triglycerides and galactolipids.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Pancreatic lipase-related protein 2 could open doors to potential therapeutic strategies.

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