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

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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 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.

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

Q15366

UPID:

PCBP2_HUMAN

Alternative names:

Alpha-CP2; Heterogeneous nuclear ribonucleoprotein E2

Alternative UPACC:

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

Background:

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.