AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for V-type proton ATPase 21 kDa proteolipid subunit c''

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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 use our state-of-the-art dedicated workflow for designing focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse 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

Reaxense

upacc

Q99437

UPID:

VATO_HUMAN

Alternative names:

Vacuolar proton pump 21 kDa proteolipid subunit c''; hATPL

Alternative UPACC:

Q99437; D3DPY5; Q6IB32

Background:

The V-type proton ATPase 21 kDa proteolipid subunit c'', also known as Vacuolar proton pump 21 kDa proteolipid subunit c'' and hATPL, plays a pivotal role in cellular processes. It forms the proton-conducting pore of the V0 complex of vacuolar(H+)-ATPase (V-ATPase), a key enzyme for acidifying intracellular compartments and, in certain cells, the extracellular environment. This acidification is crucial for various cellular functions, including nutrient processing and intracellular trafficking.

Therapeutic significance:

Understanding the role of V-type proton ATPase 21 kDa proteolipid subunit c'' could open doors to potential therapeutic strategies.

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