AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Bifunctional UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase

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.

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 our partner Reaxense.

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 use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

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.

partner

Reaxense

upacc

Q9Y223

UPID:

GLCNE_HUMAN

Alternative names:

UDP-GlcNAc-2-epimerase/ManAc kinase

Alternative UPACC:

Q9Y223; A6PZH2; A6PZH3; A7UNU7; B2R6E1; B7Z372; B7Z428; D3DRP7; F5H499; H0YFA7; Q0VA94

Background:

The Bifunctional UDP-N-acetylglucosamine 2-epimerase/N-acetylmannosamine kinase, also known as UDP-GlcNAc-2-epimerase/ManAc kinase, plays a pivotal role in the biosynthesis of N-acetylneuraminic acid (NeuAc), a precursor to sialic acids. These acids are crucial for cell adhesion, signal transduction, and the tumorigenic and metastatic behavior of malignant cells. Its function is essential for early development and normal sialylation in hematopoietic cells.

Therapeutic significance:

The protein's involvement in sialuria and Nonaka myopathy, diseases characterized by developmental delays, muscle weakness, and abnormal sialic acid metabolism, underscores its therapeutic potential. Targeting the protein's activity could lead to innovative treatments for these genetic disorders.

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