AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for C-type lectin domain family 4 member K

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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 our partner Reaxense.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9UJ71

UPID:

CLC4K_HUMAN

Alternative names:

Langerin

Alternative UPACC:

Q9UJ71

Background:

C-type lectin domain family 4 member K, also known as Langerin, is a calcium-dependent lectin with a specific affinity for mannose-binding. It plays a crucial role in the formation of Birbeck granules, essential for membrane dynamics and antigen presentation. Langerin's ability to bind to a variety of glycans, including keratan sulfate and beta-glucans, facilitates antigen uptake and processing, crucial for T cell activation. It serves as a primary receptor for several Candida and Saccharomyces species, as well as Malassezia furfur, and offers protection against HIV-1 by targeting the virus for degradation.

Therapeutic significance:

Given its pivotal role in immune response and protection against pathogens, including HIV-1, Langerin presents a promising target for therapeutic intervention. Understanding the role of Langerin could open doors to potential therapeutic strategies, particularly in enhancing immune defense mechanisms and developing treatments for infectious diseases.

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