Focused On-demand Library for Ectodysplasin-A

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.

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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

 Fig. 1. The sreening 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 is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

Ectodermal dysplasia protein

Alternative UPACC:

Q92838; A0AUZ2; A2A337; B7ZLU2; B7ZLU4; O75910; Q5JS00; Q5JUM7; Q9UP77; Q9Y6L0; Q9Y6L1; Q9Y6L2; Q9Y6L3; Q9Y6L4


Ectodysplasin-A, also known as Ectodermal dysplasia protein, plays a pivotal role in the development of ectodermal organs through epithelial-mesenchymal signaling. It activates the DEATH-domain containing receptors EDAR and EDA2R, essential for morphogenesis. Additionally, it may contribute to cell adhesion processes.

Therapeutic significance:

Ectodysplasin-A is crucial in understanding Ectodermal dysplasia 1, hypohidrotic, X-linked, and selective tooth agenesis, X-linked, 1. These conditions, caused by gene variants affecting Ectodysplasin-A, highlight its potential as a target for therapeutic intervention, promising advancements in treatment strategies.

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