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.


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 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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide 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
Q96T66

UPID:
NMNA3_HUMAN

ALTERNATIVE NAMES:
Nicotinamide-nucleotide adenylyltransferase 3; Nicotinate-nucleotide adenylyltransferase 3; Pyridine nucleotide adenylyltransferase 3

ALTERNATIVE UPACC:
Q96T66; B3KVR6; D3DNF2; D3DNF3; Q8N4G1

BACKGROUND:
The enzyme Nicotinamide/nicotinic acid mononucleotide adenylyltransferase 3, with alternative names such as Pyridine nucleotide adenylyltransferase 3, is pivotal in the formation of NAD(+) from NMN and ATP. It showcases a broad substrate specificity, including the use of triazofurin monophosphate (TrMP), and plays a protective role in axonal degeneration.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Nicotinamide/nicotinic acid mononucleotide adenylyltransferase 3 unveils potential therapeutic avenues. Given its critical involvement in NAD(+) synthesis and axonal protection, it emerges as a promising target in developing treatments for neurodegenerative conditions.

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