AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Kelch domain-containing protein 2

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.

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.

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 employ our advanced, specialised process to create targeted 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.

partner

Reaxense

upacc

Q9Y2U9

UPID:

KLDC2_HUMAN

Alternative names:

Hepatocellular carcinoma-associated antigen 33; Host cell factor homolog LCP; Host cell factor-like protein 1

Alternative UPACC:

Q9Y2U9; B3KPF9; Q6IAF0; Q86TY9

Background:

Kelch domain-containing protein 2, also known as Hepatocellular carcinoma-associated antigen 33, plays a crucial role in the Cul2-RING E3 ubiquitin-protein ligase complex of the DesCEND pathway. It specifically targets proteins with a diglycine motif at the C-terminus for ubiquitination and degradation. This includes full-length proteins, truncated forms, or proteolytically cleaved variants, such as truncated SELENOK and SELENOS selenoproteins, and the N-terminal fragment of USP1.

Therapeutic significance:

Understanding the role of Kelch domain-containing protein 2 could open doors to potential therapeutic strategies.

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