Focused On-demand Library for Collectin-12

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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.







Alternative names:

Collectin placenta protein 1; Nurse cell scavenger receptor 2; Scavenger receptor class A member 4; Scavenger receptor with C-type lectin

Alternative UPACC:

Q5KU26; Q6P9F2; Q8TCR2; Q8WZA4; Q9BY85; Q9BYH7


Collectin-12, known by alternative names such as Collectin placenta protein 1 and Scavenger receptor class A member 4, plays a pivotal role in host defense mechanisms. It is involved in the binding and phagocytosis of various pathogens, including Gram-positive and Gram-negative bacteria, as well as yeast. Furthermore, it facilitates the recognition, internalization, and degradation of oxidatively modified low-density lipoprotein (oxLDL), crucial for vascular health. Collectin-12 also exhibits specificity in binding to a range of carbohydrates in a calcium-dependent manner, highlighting its versatility in cellular functions.

Therapeutic significance:

Understanding the role of Collectin-12 could open doors to potential therapeutic strategies, particularly in combating infectious diseases and managing vascular health through the clearance of oxLDL.

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