AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Toll-like receptor 2

Available from Reaxense
Predicted by Alphafold

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.

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 our associate Reaxense.

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.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening 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 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

Reaxense

upacc

O60603

UPID:

TLR2_HUMAN

Alternative names:

Toll/interleukin-1 receptor-like protein 4

Alternative UPACC:

O60603; B3Y612; D1CS45; D1CS48; D1CS49; O15454; Q8NI00

Background:

Toll-like receptor 2 (TLR2), also known as Toll/interleukin-1 receptor-like protein 4, plays a pivotal role in the innate immune response to bacterial lipoproteins and other microbial components. It cooperates with LY96, TLR1, or TLR6, activating pathways like NF-kappa-B through MYD88 and TRAF6, leading to cytokine secretion and inflammatory responses. TLR2 is crucial for recognizing various microbial lipoproteins and promoting immune cell activation and apoptosis in response to pathogens.

Therapeutic significance:

Understanding the role of Toll-like receptor 2 could open doors to potential therapeutic strategies, especially in modulating the immune response to bacterial infections and inflammation.

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