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 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 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.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


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
Receptor.AI
 
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:
The Forkhead box protein P2, with aliases such as CAG repeat protein 44 and Trinucleotide repeat-containing gene 10 protein, is integral to speech and language development. It acts as a transcriptional repressor, aiding in the differentiation of lung epithelium and the development of neural, gastrointestinal, and cardiovascular tissues. It also plays a role in synapse formation by modulating SRPX2 levels.

THERAPEUTIC SIGNIFICANCE:
As a key player in Speech-language disorder 1, characterized by severe orofacial dyspraxia, Forkhead box protein P2 offers a promising avenue for therapeutic exploration. Delving into its function could unlock new therapeutic strategies for addressing speech and language impairments.

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