AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for 14-3-3 protein theta

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 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.

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.

Our high-tech, dedicated method is applied to construct targeted 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.

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

Reaxense

upacc

P27348

UPID:

1433T_HUMAN

Alternative names:

14-3-3 protein T-cell; 14-3-3 protein tau; Protein HS1

Alternative UPACC:

P27348; D6W4Z5; Q567U5; Q5TZU8; Q9UP48

Background:

The 14-3-3 protein theta, known alternatively as 14-3-3 protein T-cell, 14-3-3 protein tau, and Protein HS1, plays a pivotal role in cellular processes. It acts as an adapter protein, regulating a broad spectrum of signaling pathways by binding to numerous partners through recognition of phosphoserine or phosphothreonine motifs. This interaction typically modulates the activity of the binding partner and negatively regulates the kinase activity of PDPK1.

Therapeutic significance:

Understanding the role of 14-3-3 protein theta could open doors to potential therapeutic strategies.

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