AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Transcriptional regulator QRICH1

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 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.

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.

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

Q2TAL8

UPID:

QRIC1_HUMAN

Alternative names:

Glutamine-rich protein 1

Alternative UPACC:

Q2TAL8; Q4G0F7; Q7L621; Q8TEA5

Background:

Transcriptional regulator QRICH1, also known as Glutamine-rich protein 1, plays a pivotal role in the integrated stress response (ISR) by regulating protein homeostasis under ER stress conditions. It influences the unfolded protein response (UPR), crucial for cell viability, by modulating transcriptional programs related to protein translation and secretion-mediated proteotoxicity. Additionally, QRICH1 is involved in chondrocyte hypertrophy, essential for longitudinal bone growth.

Therapeutic significance:

Given its central role in ER stress-mediated inflammatory diseases and Ververi-Brady syndrome, targeting QRICH1 offers a promising avenue for therapeutic intervention. Understanding the role of Transcriptional regulator QRICH1 could open doors to potential therapeutic strategies.

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