Focused On-demand Libraries - Receptor.AI 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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive 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
O75348

UPID:
VATG1_HUMAN

ALTERNATIVE NAMES:
V-ATPase 13 kDa subunit 1; Vacuolar proton pump subunit G 1; Vacuolar proton pump subunit M16

ALTERNATIVE UPACC:
O75348; Q6IB33

BACKGROUND:
V-type proton ATPase subunit G 1, alternatively named Vacuolar proton pump subunit G 1, is integral to the V-ATPase complex, which hydrolyzes ATP and translocates protons across membranes. This action is essential for maintaining the pH balance within intracellular compartments and, in specific cell types, the extracellular matrix. The protein's involvement in iron homeostasis through the regulation of PHD enzymes and HIF1A degradation underlines its significance in cellular metabolism and response to oxygen levels.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of V-type proton ATPase subunit G 1 unveils promising avenues for the development of novel therapeutic interventions.

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