Focused On-demand Library for Sialidase-2

Focused On-demand Libraries - Receptor.AI 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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q9Y3R4

UPID:
NEUR2_HUMAN

ALTERNATIVE NAMES:
Cytosolic sialidase; N-acetyl-alpha-neuraminidase 2

ALTERNATIVE UPACC:
Q9Y3R4; Q3KNW4; Q6NTB4

BACKGROUND:
Sialidase-2, identified by its alternative names cytosolic sialidase and N-acetyl-alpha-neuraminidase 2, is integral to the breakdown of glycolipids, glycoproteins, and oligosaccharides. It achieves this through the hydrolysis of terminal sialic acids, with a specificity for alpha-(2->3)-sialylated substrates over others. The enzyme's activity is influenced by the type of sialyl linkage and the overall structure of the sialoglycoconjugates it interacts with.

THERAPEUTIC SIGNIFICANCE:
The exploration of Sialidase-2's enzymatic mechanisms offers a promising avenue for drug discovery. Its pivotal role in the metabolism of sialoglycoconjugates underlines its potential as a novel target for the development of therapeutic agents, providing a compelling case for further research.

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