Focused On-demand Library for GDP-fucose protein O-fucosyltransferase 1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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 promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal 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 procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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.







Alternative names:

Peptide-O-fucosyltransferase 1

Alternative UPACC:

Q9H488; A8K4R8; E1P5M4; Q14685; Q5W185; Q9BW76


GDP-fucose protein O-fucosyltransferase 1, also known as Peptide-O-fucosyltransferase 1, plays a pivotal role in cellular signaling pathways through its enzymatic activity. It catalyzes the attachment of fucose to serine or threonine residues in EGF domains, a process critical for proper protein function. This fucosylation is essential for NOTCH signaling, a pathway involved in cell differentiation, proliferation, and apoptosis. The protein's activity on AGRN influences acetylcholine receptor clustering, highlighting its importance in neuromuscular junctions.

Therapeutic significance:

The association of GDP-fucose protein O-fucosyltransferase 1 with Dowling-Degos disease 2, a genodermatosis characterized by reticulate hyperpigmentation and hyperkeratotic papules, underscores its clinical relevance. Understanding the role of this protein could open doors to potential therapeutic strategies for treating this disfiguring skin condition.

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