Focused On-demand Library for HLA class II histocompatibility antigen, DR alpha chain

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal 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

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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

MHC class II antigen DRA

Alternative UPACC:

P01903; A2BET4; Q30160; Q6IAZ1; Q861I2; Q9TP70


The HLA class II histocompatibility antigen, DR alpha chain (HLA-DRA), is a crucial component of the immune system. It forms a complex with HLA-DRB beta chain, presenting antigenic peptides on antigen-presenting cells for recognition by CD4-positive T cells. This interaction is vital for initiating T-helper cell-mediated immune responses against pathogens and transformed cells. The protein is involved in presenting both extracellular and intracellular peptides, playing a key role in immune surveillance and tolerance.

Therapeutic significance:

Understanding the role of HLA class II histocompatibility antigen, DR alpha chain, could open doors to potential therapeutic strategies. Its involvement in antigen presentation and immune response modulation makes it a promising target for developing treatments aimed at enhancing immune recognition of tumors or modulating immune responses in autoimmune diseases.

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