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.


Our top-notch dedicated system is used to design specialised 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.


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
O00206

UPID:
TLR4_HUMAN

ALTERNATIVE NAMES:
hToll

ALTERNATIVE UPACC:
O00206; A8K1Y8; A9XLP9; A9XLQ0; A9XLQ1; B4E194; D1CS52; D1CS53; Q5VZI8; Q5VZI9; Q9UK78; Q9UM57

BACKGROUND:
Toll-like receptor 4, known as hToll, functions as a pattern recognition receptor, essential for initiating innate immune responses. It cooperates with other molecules to mediate responses to bacterial lipopolysaccharide and other stimuli, leading to cytokine production and inflammation. TLR4's role extends to LPS-independent pathways and the activation of MYD88-independent signaling, contributing to interferon production.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Toll-like receptor 4 offers insights into novel therapeutic avenues. Its critical role in immune response modulation and inflammation highlights its potential as a therapeutic target in managing immune-related disorders.

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