AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for T-cell surface glycoprotein CD3 gamma chain

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening 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

Reaxense

upacc

P09693

UPID:

CD3G_HUMAN

Alternative names:

T-cell receptor T3 gamma chain

Alternative UPACC:

P09693; Q2HIZ6

Background:

The T-cell surface glycoprotein CD3 gamma chain, also known as T-cell receptor T3 gamma chain, is a crucial component of the TCR-CD3 complex on T-lymphocyte cell surfaces, playing a pivotal role in the adaptive immune response. This protein facilitates signal transduction across the cell membrane upon T-cell receptor (TCR) engagement by antigen presenting cells, through phosphorylation of its immunoreceptor tyrosine-based activation motifs (ITAMs) by protein tyrosine kinases LCK and FYN, leading to downstream signaling pathway activation.

Therapeutic significance:

Given its essential role in T-cell activation and the adaptive immune response, the T-cell surface glycoprotein CD3 gamma chain is implicated in Immunodeficiency 17, a condition with variable clinical severity affecting the immune system. Understanding the role of this protein could open doors to potential therapeutic strategies for managing this immunodeficiency and possibly other related autoimmune diseases.

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