Focused On-demand Library for eIF-2-alpha kinase GCN2

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


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


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

PARTNER
Receptor.AI
 
UPACC
Q9P2K8

UPID:
E2AK4_HUMAN

ALTERNATIVE NAMES:
Eukaryotic translation initiation factor 2-alpha kinase 4; GCN2-like protein

ALTERNATIVE UPACC:
Q9P2K8; C9JEC4; Q69YL7; Q6DC97; Q96GN6; Q9H5K1; Q9NSQ3; Q9NSZ5; Q9UJ56

BACKGROUND:
eIF-2-alpha kinase GCN2, identified for its pivotal function in the cellular response to amino acid depletion, phosphorylates EIF2S1/eIF-2-alpha, leading to a global reduction in protein synthesis. This kinase is essential for activating the integrated stress response, promoting cell cycle arrest, and supporting memory formation and synaptic plasticity. It also plays a role in the immune response to yellow fever virus by enhancing dendritic cell autophagy and antigen presentation.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Pulmonary venoocclusive disease 2, an autosomal recessive condition causing pulmonary hypertension, eIF-2-alpha kinase GCN2 presents a promising target for therapeutic intervention. Understanding the role of eIF-2-alpha kinase GCN2 could open doors to potential therapeutic strategies.

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