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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's 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.