Focused On-demand Libraries - Receptor.AI 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 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.


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 screening 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.


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
Receptor.AI
 
UPACC
P01877

UPID:
IGHA2_HUMAN

ALTERNATIVE NAMES:
Ig alpha-2 chain C region; Ig alpha-2 chain C region BUT; Ig alpha-2 chain C region LAN

ALTERNATIVE UPACC:
P01877; A0A075B6N7; A0A286YEY5

BACKGROUND:
The Immunoglobulin heavy constant alpha 2, known alternatively as Ig alpha-2 chain C region, is crucial for the effector phase of humoral immunity. Produced by B lymphocytes, these antibodies bind specific antigens, leading to their elimination. The process involves V-(D)-J rearrangement for assembling the variable domains, which are then fine-tuned by somatic hypermutations to enhance antigen affinity. Ig alpha is notably the predominant immunoglobulin class in body secretions.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Immunoglobulin heavy constant alpha 2 unveils potential pathways for innovative therapeutic interventions.

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