AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for GDP-L-fucose synthase

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.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q13630

UPID:

FCL_HUMAN

Alternative names:

GDP-4-keto-6-deoxy-D-mannose-3,5-epimerase-4-reductase; Protein FX; Red cell NADP(H)-binding protein; Short-chain dehydrogenase/reductase family 4E member 1

Alternative UPACC:

Q13630; B2R8Y7; D3DWK5; Q567Q9; Q9UDG7

Background:

GDP-L-fucose synthase, also known as GDP-4-keto-6-deoxy-D-mannose-3,5-epimerase-4-reductase, plays a crucial role in the NADP-dependent conversion of GDP-4-dehydro-6-deoxy-D-mannose to GDP-fucose. This process involves an epimerase and a reductase reaction, highlighting its importance in cellular functions. The protein is also referred to as Protein FX, Red cell NADP(H)-binding protein, and Short-chain dehydrogenase/reductase family 4E member 1, reflecting its diverse roles and activities within biological systems.

Therapeutic significance:

Understanding the role of GDP-L-fucose synthase could open doors to potential therapeutic strategies. Its pivotal function in the synthesis of GDP-fucose, a donor substrate for fucosyltransferases, implicates it in various biological processes, including cell signaling and immune response. Exploring its mechanisms further could unveil novel approaches to modulating these pathways for therapeutic benefit.

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