Focused On-demand Library for Tumor protein 63

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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 use our state-of-the-art dedicated workflow for designing focused 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.

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.







Alternative names:

Chronic ulcerative stomatitis protein; Keratinocyte transcription factor KET; Transformation-related protein 63; Tumor protein p73-like; p40; p51

Alternative UPACC:

Q9H3D4; O75080; O75195; O75922; O76078; Q6VEG2; Q6VEG3; Q6VEG4; Q6VFJ1; Q6VFJ2; Q6VFJ3; Q6VH20; Q7LDI3; Q7LDI4; Q7LDI5; Q96KR0; Q9H3D2; Q9H3D3; Q9H3P8; Q9NPH7; Q9P1B4; Q9P1B5; Q9P1B6; Q9P1B7; Q9UBV9; Q9UE10; Q9UP26; Q9UP27; Q9UP28; Q9UP74


Tumor protein 63, known by various names such as p63, plays a pivotal role in epithelial development and has been implicated in a range of ectodermal dysplasia syndromes. It functions as a transcriptional activator or repressor, influencing cell cycle regulation and epithelial morphogenesis. The protein's involvement in Notch signaling and limb formation underscores its significance in cellular differentiation and tissue development.

Therapeutic significance:

Given its crucial role in ectodermal dysplasia syndromes such as Acro-dermato-ungual-lacrimal-tooth syndrome and Ankyloblepharon-ectodermal defects-cleft lip/palate, understanding the function of p63 could pave the way for innovative therapeutic approaches. Targeting the pathways regulated by p63 may offer new strategies for treating these complex disorders.

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