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.


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 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.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P07911

UPID:
UROM_HUMAN

ALTERNATIVE NAMES:
Tamm-Horsfall urinary glycoprotein

ALTERNATIVE UPACC:
P07911; B3KP48; B3KRN9; E9PEA4; Q540J6; Q6ZS84; Q8IYG0

BACKGROUND:
The protein Uromodulin, known for its alternative name Tamm-Horsfall urinary glycoprotein, is essential in renal physiology. It facilitates the formation of a complex gel-like structure in the thick ascending limb of Henle's loop, crucial for water permeability. Uromodulin's ability to bind cytokines and facilitate neutrophil migration underscores its role in immune response and renal protection. It also plays a protective role against urinary tract infections by preventing the adhesion of E.coli.

THERAPEUTIC SIGNIFICANCE:
Given Uromodulin's involvement in tubulointerstitial kidney disease and its protective functions in the urinary tract, exploring its mechanisms offers promising avenues for therapeutic interventions. Its role in kidney disease and infection prevention positions it as a key target for developing treatments aimed at enhancing renal and urinary tract health.

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