AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for V-type proton ATPase catalytic subunit A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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

Reaxense

upacc

P38606

UPID:

VATA_HUMAN

Alternative names:

V-ATPase 69 kDa subunit; Vacuolar ATPase isoform VA68; Vacuolar proton pump subunit alpha

Alternative UPACC:

P38606; B2RBR8; B7Z1R5; D3DN75; Q53YD9; Q96DY6; Q9UHY3

Background:

The V-type proton ATPase catalytic subunit A, also known as V-ATPase 69 kDa subunit, plays a crucial role in acidifying intracellular compartments and the extracellular environment in certain cell types. This protein is integral to various physiological processes, including iron homeostasis and neurite development. Its involvement in synaptic connectivity and virion uncoating during Rabies virus replication highlights its multifaceted role in biological systems.

Therapeutic significance:

Given its association with Cutis laxa, autosomal recessive, 2D, and Epileptic encephalopathy, infantile or early childhood, 3, understanding the V-type proton ATPase catalytic subunit A's function could pave the way for novel therapeutic strategies targeting these conditions. Its role in disease mechanisms offers a promising avenue for drug discovery.

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