AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Immunoglobulin-binding protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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

Reaxense

upacc

P78318

UPID:

IGBP1_HUMAN

Alternative names:

B-cell signal transduction molecule alpha 4; CD79a-binding protein 1; Protein phosphatase 2/4/6 regulatory subunit; Renal carcinoma antigen NY-REN-16

Alternative UPACC:

P78318; Q8TAB2

Background:

Immunoglobulin-binding protein 1, also known as B-cell signal transduction molecule alpha 4, CD79a-binding protein 1, Protein phosphatase 2/4/6 regulatory subunit, and Renal carcinoma antigen NY-REN-16, plays a crucial role in immune response. It is associated with surface IgM-receptor and may be involved in signal transduction. Furthermore, it regulates the catalytic activity of phosphatases PP2A, PP4, and PP6, protecting their catalytic subunits from degradation.

Therapeutic significance:

This protein is linked to Intellectual developmental disorder, X-linked, syndromic 28, characterized by agenesis of the corpus callosum and severe intellectual deficit. Understanding the role of Immunoglobulin-binding protein 1 could open doors to potential therapeutic strategies for this disorder.

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