Focused On-demand Library for DCN1-like protein 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

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 top-notch dedicated system is used to design specialised 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.







Alternative names:

DCUN1 domain-containing protein 1; Defective in cullin neddylation protein 1-like protein 1; Squamous cell carcinoma-related oncogene

Alternative UPACC:

Q96GG9; B2RB37; Q7L3G9; Q8TEX7; Q9H6M1; Q9HCT3


DCN1-like protein 1, also known as DCUN1 domain-containing protein 1, plays a crucial role in the neddylation process, enhancing the function of E3 ubiquitin ligase complexes. This protein facilitates the nuclear translocation of cullin-RBX1 complexes, optimizing protein orientation for efficient NEDD8 transfer to cullin substrates. Its involvement in releasing CAND1's inhibitory effects on cullin-RING ligase E3 complex assembly underscores its significance in cellular regulation.

Therapeutic significance:

Understanding the role of DCN1-like protein 1 could open doors to potential therapeutic strategies. Its function as an oncogene suggests its involvement in malignant transformation and carcinogenic progression, highlighting its potential as a target in cancer therapy.

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