AI-ACCELERATED DRUG DISCOVERY

Collectin-12

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Collectin-12 - Focused Library Design

Available from Reaxense

This protein is integrated into the Receptor.AI ecosystem as a prospective target with high therapeutic potential. We performed a comprehensive characterization of Collectin-12 including:

1. LLM-powered literature research

Our custom-tailored LLM extracted and formalized all relevant information about the protein from a large set of structured and unstructured data sources and stored it in the form of a Knowledge Graph. This comprehensive analysis allowed us to gain insight into Collectin-12 therapeutic significance, existing small molecule ligands, relevant off-targets, and protein-protein interactions.

 Fig. 1. Preliminary target research workflow

2. AI-Driven Conformational Ensemble Generation

Starting from the initial protein structure, we employed advanced AI algorithms to predict alternative functional states of Collectin-12, including large-scale conformational changes along "soft" collective coordinates. Through molecular simulations with AI-enhanced sampling and trajectory clustering, we explored the broad conformational space of the protein and identified its representative structures. Utilizing diffusion-based AI models and active learning AutoML, we generated a statistically robust ensemble of equilibrium protein conformations that capture the receptor's full dynamic behavior, providing a robust foundation for accurate structure-based drug design.

 Fig. 2. AI-powered molecular dynamics simulations workflow

3. Binding pockets identification and characterization

We employed the AI-based pocket prediction module to discover orthosteric, allosteric, hidden, and cryptic binding pockets on the protein’s surface. Our technique integrates the LLM-driven literature search and structure-aware ensemble-based pocket detection algorithm that utilizes previously established protein dynamics. Tentative pockets are then subject to AI scoring and ranking with simultaneous detection of false positives. In the final step, the AI model assesses the druggability of each pocket enabling a comprehensive selection of the most promising pockets for further targeting.

 Fig. 3. AI-based binding pocket detection workflow

4. AI-Powered Virtual Screening

Our ecosystem is equipped to perform AI-driven virtual screening on Collectin-12. With access to a vast chemical space and cutting-edge AI docking algorithms, we can rapidly and reliably predict the most promising, novel, diverse, potent, and safe small molecule ligands of Collectin-12. This approach allows us to achieve an excellent hit rate and to identify compounds ready for advanced lead discovery and optimization.

 Fig. 4. The screening workflow of Receptor.AI

Receptor.AI, in partnership with Reaxense, developed a next-generation technology for on-demand focused library design to enable extensive target exploration.

The focused library for Collectin-12 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.

Collectin-12

partner:

Reaxense

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, 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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