Focused On-demand Libraries - Receptor.AI 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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library 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.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening 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.


PARTNER
Receptor.AI
 
UPACC
P79483

UPID:
DRB3_HUMAN

ALTERNATIVE NAMES:
MHC class II antigen DRB3

ALTERNATIVE UPACC:
P79483; A0ZXY9; A7MA46; B5AU12; B5AU13; B5AU14; B8YAC6; C6H115; C6H116; O02875; O19590; O46701; O46794; O78049; O78162; P01913; P79663; Q29721; Q29809; Q2PPD0; Q30144; Q507L8; Q5SP44; Q5STE0; Q6YJU6; Q70M87; Q7YQ62; Q860I9; Q8SP69; Q8WLT7; Q8WLT8; Q95359; Q95HM8; Q95IE5; Q96H16; Q9BCP3; Q9BD18; Q9MYA4; Q9MYH3; Q9MYH4; Q9TP01; Q9TP02; Q9TPB5; Q9TQ21; Q9UIN3; Q9UIN5

BACKGROUND:
MHC class II antigen DRB3, alternatively named HLA class II histocompatibility antigen, DR beta 3 chain, is essential for antigen presentation on professional antigen-presenting cells. It facilitates the recognition of antigenic peptides by T cell receptors on CD4-positive T cells, driving both antibody-mediated immune responses and macrophage activation. The protein's role in presenting peptides from endocytosed antigens and intracellular proteins trapped in autolysosomes underscores its importance in immune response and tolerance.

THERAPEUTIC SIGNIFICANCE:
The exploration of HLA class II histocompatibility antigen, DR beta 3 chain's function offers promising avenues for therapeutic intervention. Its involvement in presenting a wide array of antigenic peptides to the immune system positions it as a critical target for the development of novel immunotherapies and vaccines aimed at combating infectious diseases, malignancies, and managing autoimmune disorders.

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