AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Forkhead box protein P3

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

The approach involves in-depth molecular simulations of the target protein by itself and in complex with its primary partner proteins, paired with ensemble virtual screening that factors in conformational mobility in both the unbound and complex states. The tentative binding pockets are identified at the protein-protein interaction interface and in distant allosteric areas, aiming to capture the full range of mechanisms of action.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9BZS1

UPID:

FOXP3_HUMAN

Alternative names:

Scurfin

Alternative UPACC:

Q9BZS1; A5HJT1; B7ZLG0; B9UN80; O60827; Q14DD8; Q4ZH51

Background:

Forkhead box protein P3, also known as FOXP3 or Scurfin, plays a pivotal role in immune system regulation. It is a transcriptional regulator essential for the development and function of regulatory T-cells (Treg), which are crucial for maintaining immune homeostasis. FOXP3 modulates the expansion and function of conventional T-cells and can act as both a transcriptional repressor and activator, influencing the expression of key immune response genes.

Therapeutic significance:

FOXP3's involvement in Immunodeficiency polyendocrinopathy, enteropathy, X-linked syndrome, a condition marked by severe immune dysregulation, underscores its therapeutic potential. Targeting FOXP3's regulatory pathways could lead to innovative treatments for autoimmune diseases and immune deficiencies, highlighting the importance of understanding its mechanisms.

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