Focused On-demand Library for Collectin-12

Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


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 screening 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.


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
Receptor.AI
 
UPACC
Q5KU26

UPID:
COL12_HUMAN

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

BACKGROUND:
Collectin-12, alternatively named Nurse cell scavenger receptor 2 and Scavenger receptor with C-type lectin, is integral to host defense, showcasing its ability to bind and internalize a variety of pathogens and modified lipoproteins. Its capacity to bind to specific carbohydrates, including Gal-type ligands and GalNAc, underscores its role in cellular recognition processes. This protein's involvement in the clearance of amyloid-beta suggests a potential link to neurodegenerative diseases like Alzheimer's.

THERAPEUTIC SIGNIFICANCE:
Exploring the multifunctional role of Collectin-12 offers a promising avenue for the development of novel therapeutic interventions, especially in the fields of infectious disease, cardiovascular health, and potentially neurodegenerative disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.


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