Focused On-demand Library for HLA class I histocompatibility antigen, alpha chain G

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

Several key aspects differentiate our library:

Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P17693

UPID:

HLAG_HUMAN

Alternative names:

HLA G antigen; MHC class I antigen G

Alternative UPACC:

P17693

Background:

HLA class I histocompatibility antigen, alpha chain G (HLA-G) is a non-classical major histocompatibility class Ib molecule playing a pivotal role in immune regulation at the maternal-fetal interface. It forms complexes with B2M/beta-2 microglobulin to bind self-peptides from intracellular proteins, acting as a ligand for various receptors on uterine immune cells. This interaction promotes fetal development while maintaining maternal-fetal tolerance, triggers NK cell senescence, induces pro-inflammatory cytokine production, and supports the differentiation of regulatory T cells and myeloid-derived suppressor cells.

Therapeutic significance:

Understanding the role of HLA-G could open doors to potential therapeutic strategies, particularly in enhancing maternal-fetal tolerance and managing immune-related disorders.