AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for dTDP-D-glucose 4,6-dehydratase

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 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 top-notch dedicated system is used to design specialised libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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

Reaxense

upacc

O95455

UPID:

TGDS_HUMAN

Alternative names:

-

Alternative UPACC:

O95455; Q05DQ3; Q2TU31; Q5T3Z2; Q9H1T9

Background:

The protein dTDP-D-glucose 4,6-dehydratase, encoded by the gene with accession number O95455, plays a crucial role in the biosynthesis of dTDP-L-rhamnose, a sugar essential for the cell wall integrity in bacteria and plant cells. Its enzymatic activity is pivotal in converting dTDP-D-glucose into dTDP-4-keto-6-deoxy-D-glucose, a precursor in the synthesis of dTDP-L-rhamnose.

Therapeutic significance:

Understanding the role of dTDP-D-glucose 4,6-dehydratase could open doors to potential therapeutic strategies. Specifically, its involvement in Catel-Manzke syndrome, a genetic disorder characterized by unique skeletal abnormalities and cleft palate, highlights its potential as a target for therapeutic intervention. Developing inhibitors for this enzyme could offer a novel approach to treat this syndrome.

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