AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Small ubiquitin-related modifier 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.

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.

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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

P63165

UPID:

SUMO1_HUMAN

Alternative names:

GAP-modifying protein 1; SMT3 homolog 3; Sentrin; Ubiquitin-homology domain protein PIC1; Ubiquitin-like protein SMT3C; Ubiquitin-like protein UBL1

Alternative UPACC:

P63165; A8MUS8; B2R4I5; P55856; Q6FGG0; Q6NZ62; Q93068

Background:

Small ubiquitin-related modifier 1 (SUMO1) plays a pivotal role in various cellular processes, including nuclear transport, DNA replication, and signal transduction, through its post-translational modification of proteins. Known by alternative names such as Sentrin and Ubiquitin-like protein UBL1, SUMO1's ability to covalently attach to proteins influences cellular mechanisms critical for maintaining homeostasis and responding to stress.

Therapeutic significance:

SUMO1's involvement in Non-syndromic orofacial cleft 10, a birth defect characterized by cleft lips, highlights its potential as a therapeutic target. Understanding the role of SUMO1 could open doors to potential therapeutic strategies for managing and possibly preventing conditions associated with its dysfunction.

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