Focused On-demand Libraries - Receptor.AI 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.


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 Reaxense.


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.


Our high-tech, dedicated method is applied to construct targeted 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
O14829

UPID:
PPE1_HUMAN

ALTERNATIVE NAMES:
Protein phosphatase with EF calcium-binding domain; Serine/threonine-protein phosphatase 7

ALTERNATIVE UPACC:
O14829; A6NHP4; A8K348; O15253; Q9NU21; Q9UJH0

BACKGROUND:
The protein known as Serine/threonine-protein phosphatase with EF-hands 1, or its alternative names, Protein phosphatase with EF calcium-binding domain and Serine/threonine-protein phosphatase 7, is implicated in essential biological processes. It may play a significant role in photoreceptor recovery and adaptation, as well as in developmental pathways, highlighting its importance in cellular function and signaling.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Serine/threonine-protein phosphatase with EF-hands 1 offers a promising avenue for the development of novel therapeutic approaches. Given its potential roles in critical physiological processes, targeting this protein could lead to breakthroughs in treating diseases related to vision and developmental abnormalities.

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