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

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.

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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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.







Alternative names:

CD209 antigen-like protein 1; DC-SIGN-related protein; Dendritic cell-specific ICAM-3-grabbing non-integrin 2; Liver/lymph node-specific ICAM-3-grabbing non-integrin

Alternative UPACC:

Q9H2X3; A6NKI4; A8K8B3; Q69F40; Q969M4; Q96QP3; Q96QP4; Q96QP5; Q96QP6; Q9BXS3; Q9H2Q9; Q9H8F0; Q9Y2A8


C-type lectin domain family 4 member M, known as CD209 antigen-like protein 1, plays a crucial role in immune surveillance, particularly in the liver. It mediates endocytosis of pathogens for degradation and serves as a receptor for ICAM3. Its ability to bind to mannose-like carbohydrates facilitates the recognition of various pathogens, including Ebolavirus, Hepatitis C virus, HIV-1, and several coronaviruses.

Therapeutic significance:

Understanding the role of C-type lectin domain family 4 member M could open doors to potential therapeutic strategies. Its involvement in the recognition and endocytosis of a wide range of pathogens highlights its potential as a target for developing treatments against infectious diseases.

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