Focused On-demand Library for Immunoglobulin heavy constant mu

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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:

Ig mu chain C region; Ig mu chain C region BOT; Ig mu chain C region GAL; Ig mu chain C region OU

Alternative UPACC:

P01871; A0A075B6N9; A0A0G2JQL4; P04220; P20769


The Immunoglobulin heavy constant mu (IgM) plays a pivotal role in the immune system as a primary defender against pathogens. It is a key component of the humoral immune response, facilitating the recognition and elimination of antigens through its unique antigen-binding sites. IgM's structure allows for the assembly of its variable domains through V-(D)-J rearrangement, enabling somatic hypermutations for affinity maturation against specific antigens.

Therapeutic significance:

Agammaglobulinemia 1, an autosomal recessive disorder, underscores the critical role of IgM in immune defense. This condition, characterized by low or absent serum antibodies and B cells, highlights the potential of targeting IgM pathways for therapeutic interventions to restore immune function and prevent severe infections.

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