AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Forkhead box protein P2

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 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.

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

O15409

UPID:

FOXP2_HUMAN

Alternative names:

CAG repeat protein 44; Trinucleotide repeat-containing gene 10 protein

Alternative UPACC:

O15409; A0AUV6; A4D0U8; A6NNW4; B4DLD9; Q6ZND1; Q75MJ3; Q8IZE0; Q8N0W2; Q8N6B7; Q8N6B8; Q8NFQ1; Q8NFQ2; Q8NFQ3; Q8NFQ4; Q8TD74

Background:

Forkhead box protein P2, also known as CAG repeat protein 44 or Trinucleotide repeat-containing gene 10 protein, plays a pivotal role in the development of speech and language. It functions as a transcriptional repressor, crucial for lung epithelium differentiation, and contributes to neural, gastrointestinal, and cardiovascular tissue development. Additionally, it regulates synapse formation by controlling SRPX2 levels.

Therapeutic significance:

Linked to Speech-language disorder 1, Forkhead box protein P2's involvement in orofacial dyspraxia and language processing deficits highlights its potential as a target for therapeutic intervention. Understanding its role could pave the way for novel treatments for speech and language disorders.

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