AI-ACCELERATED DRUG DISCOVERY

C-C motif chemokine 18

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

C-C motif chemokine 18 - 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 C-C motif chemokine 18 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 C-C motif chemokine 18 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 C-C motif chemokine 18, 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 C-C motif chemokine 18. 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 C-C motif chemokine 18. 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 C-C motif chemokine 18 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.

C-C motif chemokine 18

partner:

Reaxense

upacc:

P55774

UPID:

CCL18_HUMAN

Alternative names:

Alternative macrophage activation-associated CC chemokine 1; CC chemokine PARC; Dendritic cell chemokine 1; Macrophage inflammatory protein 4; Pulmonary and activation-regulated chemokine; Small-inducible cytokine A18

Alternative UPACC:

P55774; B5BUM2; Q53X71

Background:

C-C motif chemokine 18, known by alternative names such as Alternative macrophage activation-associated CC chemokine 1, CC chemokine PARC, and Pulmonary and activation-regulated chemokine, plays a pivotal role in immune responses. It acts as a chemotactic factor, attracting lymphocytes and influencing the migration of B-cells into follicles in lymph nodes. Its ability to attract naive T-lymphocytes toward dendritic cells and activated macrophages highlights its significance in both humoral and cell-mediated immunity.

Therapeutic significance:

Understanding the role of C-C motif chemokine 18 could open doors to potential therapeutic strategies. Its involvement in directing immune cell traffic suggests its potential as a target in modulating immune responses, offering pathways for innovative treatments in immune-related disorders.

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