Focused On-demand Library for Toll-like receptor 4

Focused On-demand Libraries - Reaxense 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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

Fig. 1. The sreening 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.

Key features that set our library apart include:

The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

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 (TLR4), also known as hToll, is a pivotal transmembrane receptor in the innate immune system. It recognizes pathogen- and damage-associated molecular patterns to trigger immune responses. TLR4's activation involves signaling pathways leading to NF-kappa-B activation and cytokine secretion, crucial for the inflammatory response. It also plays a role in LPS-independent responses and influences the NLRP3 inflammasome and autophagy.

Therapeutic significance:

Understanding the role of Toll-like receptor 4 could open doors to potential therapeutic strategies. Its involvement in innate immunity and inflammatory processes makes it a target for developing treatments for inflammatory diseases.