AI-ACCELERATED DRUG DISCOVERY

T-cell surface glycoprotein CD3 epsilon chain

Explore its Potential with AI-Driven Innovation
Predicted by Alphafold

T-cell surface glycoprotein CD3 epsilon chain - 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 T-cell surface glycoprotein CD3 epsilon chain 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 T-cell surface glycoprotein CD3 epsilon chain 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 T-cell surface glycoprotein CD3 epsilon chain, 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 T-cell surface glycoprotein CD3 epsilon chain. 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 T-cell surface glycoprotein CD3 epsilon chain. 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 T-cell surface glycoprotein CD3 epsilon chain 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.

T-cell surface glycoprotein CD3 epsilon chain

partner:

Reaxense

upacc:

P07766

UPID:

CD3E_HUMAN

Alternative names:

T-cell surface antigen T3/Leu-4 epsilon chain

Alternative UPACC:

P07766; A8K997

Background:

The T-cell surface glycoprotein CD3 epsilon chain, known as CD3E, is a crucial component of the TCR-CD3 complex on T-lymphocytes, essential for adaptive immune response. It facilitates signal transduction upon antigen recognition, leading to T-cell activation. CD3E's role extends to T-cell development, initiating TCR-CD3 complex assembly and participating in the complex's internalization and down-regulation.

Therapeutic significance:

Immunodeficiency 18, a primary immunodeficiency with variable severity, is linked to CD3E. This condition underscores the protein's critical role in immune system function, suggesting that targeting CD3E could offer new therapeutic avenues for treating immune disorders.

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