Focused On-demand Library for Poly(rC)-binding protein 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening 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.

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.







Alternative names:

Alpha-CP2; Heterogeneous nuclear ribonucleoprotein E2

Alternative UPACC:

Q15366; A8K7X6; B4DXP5; F8VYL7; G3V0E8; I6L8F9; Q32Q82; Q59HD4; Q68Y55; Q6IPF4; Q6PKG5


Poly(rC)-binding protein 2, also known as Alpha-CP2 or Heterogeneous nuclear ribonucleoprotein E2, is a pivotal single-stranded nucleic acid binding protein. It exhibits a strong preference for oligo dC, marking its significance as the major cellular poly(rC)-binding entity. This protein plays a crucial role in negatively regulating antiviral signaling by acting as an adapter between MAVS and the E3 ubiquitin ligase ITCH, facilitating MAVS ubiquitination and degradation. Additionally, it modulates the cGAS-STING pathway and is essential for erythropoiesis alongside PCBP1.

Therapeutic significance:

Understanding the role of Poly(rC)-binding protein 2 could open doors to potential therapeutic strategies.

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