AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for SUMO-conjugating enzyme UBC9

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.

We employ our advanced, specialised process to create targeted 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

P63279

UPID:

UBC9_HUMAN

Alternative names:

RING-type E3 SUMO transferase UBC9; SUMO-protein ligase; Ubiquitin carrier protein 9; Ubiquitin carrier protein I; Ubiquitin-conjugating enzyme E2 I; Ubiquitin-protein ligase I; p18

Alternative UPACC:

P63279; D3DU69; P50550; Q15698; Q59GX1; Q86VB3

Background:

The SUMO-conjugating enzyme UBC9, known by various names including RING-type E3 SUMO transferase UBC9 and Ubiquitin carrier protein 9, plays a pivotal role in the sumoylation process. It accepts ubiquitin-like proteins SUMO1-4 and SUMO1P1/SUMO5, catalyzing their covalent attachment to other proteins with E3 ligase assistance. This enzyme is crucial for nuclear architecture, chromosome segregation, and the sumoylation of key proteins such as FOXL2, KAT5, and p53/TP53.

Therapeutic significance:

Understanding the role of SUMO-conjugating enzyme UBC9 could open doors to potential therapeutic strategies.

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