AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for AP-1 complex subunit sigma-3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of 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

Q96PC3

UPID:

AP1S3_HUMAN

Alternative names:

Adaptor protein complex AP-1 subunit sigma-1C; Adaptor-related protein complex 1 subunit sigma-1C; Clathrin assembly protein complex 1 sigma-1C small chain; Golgi adaptor HA1/AP1 adaptin sigma-1C subunit; Sigma 1C subunit of AP-1 clathrin; Sigma-adaptin 1C; Sigma1C-adaptin

Alternative UPACC:

Q96PC3; B4DQZ1; Q8WTY1; Q96DD1

Background:

The AP-1 complex subunit sigma-3, known by various names such as Adaptor protein complex AP-1 subunit sigma-1C, plays a crucial role in protein sorting within the late-Golgi/trans-Golgi network and/or endosomes. It is a part of the clathrin-associated adaptor protein complex 1, essential for the recruitment of clathrin to membranes and the recognition of sorting signals in transmembrane cargo molecules. Additionally, it is involved in TLR3 trafficking, highlighting its significance in cellular processes.

Therapeutic significance:

Given its association with Psoriasis 15, pustular, a severe form of psoriasis characterized by sudden flares and systemic symptoms, understanding the role of AP-1 complex subunit sigma-3 could open doors to potential therapeutic strategies. Its involvement in protein sorting and immune response pathways suggests it could be a target for innovative treatments.

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