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 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.


 

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
Q93050

UPID:
VPP1_HUMAN

ALTERNATIVE NAMES:
Clathrin-coated vesicle/synaptic vesicle proton pump 116 kDa subunit; Vacuolar adenosine triphosphatase subunit Ac116; Vacuolar proton pump subunit 1; Vacuolar proton translocating ATPase 116 kDa subunit a isoform 1

ALTERNATIVE UPACC:
Q93050; B7Z3B7; Q8N5G7; Q9NSX0

BACKGROUND:
The protein V-type proton ATPase 116 kDa subunit a 1, with alternative names such as Vacuolar adenosine triphosphatase subunit Ac116, is essential for the acidification of intracellular compartments and extracellular spaces in certain cell types. Its role in neuronal development and integrity underscores its importance in cellular physiology.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in severe neurological disorders like Developmental and epileptic encephalopathy 104 and progressive myoclonus epilepsy, targeting V-type proton ATPase 116 kDa subunit a 1 offers a promising avenue for therapeutic intervention in these debilitating diseases.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.