Focused On-demand Library for Kremen protein 1

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our top-notch dedicated system is used to design specialised libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

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:

Dickkopf receptor; Kringle domain-containing transmembrane protein 1; Kringle-containing protein marking the eye and the nose

Alternative UPACC:

Q96MU8; B0QY46; B0QY47; B1AJR5; Q5TIB9; Q6P3X6; Q9BY70; Q9UGS5; Q9UGU1


Kremen protein 1, also known as Dickkopf receptor, plays a pivotal role in the Wnt signaling pathway. It acts as a receptor for Dickkopf proteins, modulating Wnt/beta-catenin signaling through the endocytosis of Wnt receptors LRP5 and LRP6. This protein is crucial in limb development, bone formation, and cell fate decisions in the developing cochlea, showcasing its inhibitory role in hair cell fate specification.

Therapeutic significance:

Kremen protein 1's involvement in Ectodermal dysplasia 13, hair/tooth type, underscores its potential as a therapeutic target. Understanding the role of Kremen protein 1 could open doors to potential therapeutic strategies for treating abnormalities in hair, tooth development, and other ectodermal structures.

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