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.


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.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
P07093

UPID:
GDN_HUMAN

ALTERNATIVE NAMES:
Peptidase inhibitor 7; Protease nexin 1; Protease nexin I; Serpin E2

ALTERNATIVE UPACC:
P07093; B2R6A4; B4DIF2; Q53S15; Q5D0C4

BACKGROUND:
Glia-derived nexin, known under various names such as Serpin E2, Peptidase inhibitor 7, Protease nexin 1, and Protease nexin I, functions as a serine protease inhibitor. It targets thrombin, trypsin, and urokinase, crucial for maintaining protease balance. Its interaction with heparin and role in neurite extension further underscore its biological importance.

THERAPEUTIC SIGNIFICANCE:
The exploration of Glia-derived nexin's functions offers promising pathways for drug discovery. By inhibiting key proteases and facilitating neurite growth, it presents a unique target for developing treatments related to coagulation disorders and neurodegenerative diseases.

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