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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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
P49768

UPID:
PSN1_HUMAN

ALTERNATIVE NAMES:
Protein S182

ALTERNATIVE UPACC:
P49768; B2R6D3; O95465; Q14762; Q15719; Q15720; Q96P33; Q9UIF0

BACKGROUND:
The enzyme Presenilin-1 functions as the catalytic core of the gamma-secretase complex, facilitating the cleavage of proteins critical for cell signaling pathways, including Notch and Wnt. It plays a key role in the regulation of synaptic function and neuronal health, impacting processes from cell adhesion to apoptosis. Its involvement in calcium leakage from the endoplasmic reticulum further underscores its importance in cellular homeostasis.

THERAPEUTIC SIGNIFICANCE:
Presenilin-1's aberrant activity is a cornerstone in the pathophysiology of several neurodegenerative diseases, notably Alzheimer's disease, by influencing amyloid plaque formation. It is also associated with cardiomyopathy and skin disorders, making it a focal point for therapeutic intervention. Targeting Presenilin-1 could revolutionize treatment strategies for these diseases, offering hope for improved patient outcomes.

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