AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Serine/threonine-protein kinase/endoribonuclease IRE1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

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.

partner

Reaxense

upacc

O75460

UPID:

ERN1_HUMAN

Alternative names:

Endoplasmic reticulum-to-nucleus signaling 1; Inositol-requiring protein 1; Ire1-alpha

Alternative UPACC:

O75460; A1L457; A8K8N8; A8MXS7; Q59EE2

Background:

Serine/threonine-protein kinase/endoribonuclease IRE1, also known as Endoplasmic reticulum-to-nucleus signaling 1, plays a pivotal role in the endoplasmic reticulum unfolded protein response (UPR). This protein acts as a key sensor for UPR, transitioning from an inactive monomeric state to an active homodimer that promotes autophosphorylation and endoribonuclease activity upon accumulation of misfolded proteins.

Therapeutic significance:

Understanding the role of Serine/threonine-protein kinase/endoribonuclease IRE1 could open doors to potential therapeutic strategies.

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