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

Details

Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


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.


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


 

Fig. 1. The screening 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.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

PARTNER
Receptor.AI
 
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:
The enzyme GDP-L-fucose synthase, known for its alternative names such as GDP-4-keto-6-deoxy-D-mannose-3,5-epimerase-4-reductase, is integral to the biochemical pathway that converts GDP-mannose to GDP-fucose. This conversion is essential for the biosynthesis of fucosylated glycoconjugates, playing a significant role in various cellular functions. The protein's alternative names, including Protein FX and Red cell NADP(H)-binding protein, underscore its multifaceted role in biological systems.

THERAPEUTIC SIGNIFICANCE:
The exploration of GDP-L-fucose synthase's function offers a promising avenue for drug discovery and therapeutic intervention. Although direct associations with specific diseases are yet to be established, the enzyme's critical role in the synthesis of key biological molecules positions it as a potential target for the development of treatments aimed at modulating immune responses and cell signaling pathways.

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