Focused On-demand Library for Immunoglobulin heavy constant gamma 1

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.

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 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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







Alternative names:

Ig gamma-1 chain C region; Ig gamma-1 chain C region EU; Ig gamma-1 chain C region KOL; Ig gamma-1 chain C region NIE

Alternative UPACC:

P01857; A0A0A0MS08


The Immunoglobulin heavy constant gamma 1 (IGHG1) protein, known by alternative names such as Ig gamma-1 chain C region, plays a pivotal role in the immune response. It is a crucial component of immunoglobulins or antibodies, produced by B lymphocytes. These antibodies have a unique ability to bind specific antigens, triggering immune reactions that target and eliminate the antigens. The variable domains of these antibodies undergo a sophisticated process of V-(D)-J rearrangement, allowing for a highly specific immune response.

Therapeutic significance:

IGHG1's involvement in multiple myeloma, a malignant tumor of plasma cells, underscores its therapeutic significance. The disease is characterized by skeletal system involvement, hyperglobulinemia, and renal failure, among other symptoms. Genetic aberrations affecting IGHG1, such as chromosomal translocations, are pivotal in the disease's pathogenesis. Understanding the role of IGHG1 could open doors to potential therapeutic strategies targeting these genetic anomalies.

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