AI-ACCELERATED DRUG DISCOVERY

Cytotoxic T-lymphocyte protein 4

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

Cytotoxic T-lymphocyte protein 4 - 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 Cytotoxic T-lymphocyte protein 4 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 Cytotoxic T-lymphocyte protein 4 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 Cytotoxic T-lymphocyte protein 4, 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 Cytotoxic T-lymphocyte protein 4. 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 Cytotoxic T-lymphocyte protein 4. 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 Cytotoxic T-lymphocyte protein 4 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.

Cytotoxic T-lymphocyte protein 4

partner:

Reaxense

upacc:

P16410

UPID:

CTLA4_HUMAN

Alternative names:

Cytotoxic T-lymphocyte-associated antigen 4

Alternative UPACC:

P16410; A0N1S0; E9PDH0; O95653; Q0PP65; Q52MC1; Q53TD5; Q5S005; Q8WXJ1; Q96P43; Q9UKN9

Background:

Cytotoxic T-lymphocyte protein 4 (CTLA-4), also known as Cytotoxic T-lymphocyte-associated antigen 4, plays a pivotal role in the immune system as a major negative regulator of T-cell responses. Its interaction with natural B7 family ligands, CD80 and CD86, showcases a stronger affinity compared to the stimulatory coreceptor CD28, highlighting its critical function in modulating immune responses.

Therapeutic significance:

CTLA-4's involvement in diseases such as Systemic lupus erythematosus, Type 1 diabetes mellitus 12, Celiac disease 3, and Immune dysregulation with autoimmunity, immunodeficiency, and lymphoproliferation underscores its potential as a therapeutic target. Understanding the role of CTLA-4 could open doors to potential therapeutic strategies, offering hope for patients suffering from these autoimmune disorders.

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