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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


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
Receptor.AI
 
UPACC
Q9NR45

UPID:
SIAS_HUMAN

ALTERNATIVE NAMES:
N-acetylneuraminate synthase; N-acetylneuraminate-9-phosphate synthase; N-acetylneuraminic acid phosphate synthase; N-acetylneuraminic acid synthase

ALTERNATIVE UPACC:
Q9NR45; B2RE98; Q8WUV9; Q9BWS6; Q9NVD4

BACKGROUND:
Sialic acid synthase, integral for producing key sialic acids like N-acetylneuraminic acid (Neu5Ac), is essential in various biological processes, including cell signaling and recognition. Its alternative names, such as N-acetylneuraminate-9-phosphate synthase, reflect its functional diversity in synthesizing sialic acids, critical for glycoprotein and glycolipid composition.

THERAPEUTIC SIGNIFICANCE:
Given its association with Spondyloepimetaphyseal dysplasia, Genevieve type, characterized by significant skeletal abnormalities and developmental challenges, Sialic acid synthase represents a promising target for therapeutic intervention. Exploring its function further could lead to novel treatments for this and potentially other related disorders.

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