Focused On-demand Library for E3 ubiquitin-protein ligase HACE1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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:

HECT domain and ankyrin repeat-containing E3 ubiquitin-protein ligase 1; HECT-type E3 ubiquitin transferase HACE1

Alternative UPACC:

Q8IYU2; A8K6U5; B3KY89; B4DFM6; B4DTQ4; B7Z9X6; E9PGP0; Q5VU99; Q5VUA0; Q8ND12; Q9P2M6


E3 ubiquitin-protein ligase HACE1 plays a pivotal role in Golgi membrane fusion and the regulation of small GTPases. It is crucial for Golgi membrane dynamics during the cell cycle, mediating ubiquitination for Golgi reassembly post-cell division. HACE1 interacts with GTP-bound RAC1, targeting active RAC1 for ubiquitination and degradation, which is essential for host defense against pathogens. Additionally, it may function as a transcription regulator through its interaction with RARB.

Therapeutic significance:

The involvement of E3 ubiquitin-protein ligase HACE1 in Spastic paraplegia and psychomotor retardation with or without seizures highlights its potential as a target for therapeutic intervention. Understanding the role of HACE1 could open doors to potential therapeutic strategies.

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