AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Target of EGR1 protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.

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.

Our top-notch dedicated system is used to design specialised 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.

partner

Reaxense

upacc

Q96GM8

UPID:

TOE1_HUMAN

Alternative names:

-

Alternative UPACC:

Q96GM8; B4DEM6; Q6IA35; Q8IWN5; Q9H846

Background:

The Target of EGR1 protein 1 plays a pivotal role in cellular processes, inhibiting cell growth rate and cell cycle. It is instrumental in inducing CDKN1A and TGF-beta expression, thereby mediating the inhibitory growth effect of EGR1. Additionally, it is involved in the maturation of snRNAs and their 3'-tail processing, highlighting its multifaceted role in biological systems.

Therapeutic significance:

Linked to Pontocerebellar hypoplasia 7, a disorder characterized by underdevelopment of the pons and cerebellum, the Target of EGR1 protein 1's involvement in this disease underscores its potential as a therapeutic target. Understanding the role of this protein could open doors to potential therapeutic strategies, offering hope for interventions in pontocerebellar hypoplasia and related conditions.

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