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 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.


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.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q13488

UPID:
VPP3_HUMAN

ALTERNATIVE NAMES:
Osteoclastic proton pump 116 kDa subunit; T-cell immune regulator 1; T-cell immune response cDNA7 protein; Vacuolar proton translocating ATPase 116 kDa subunit a isoform 3

ALTERNATIVE UPACC:
Q13488; O75877; Q8WVC5

BACKGROUND:
The V-type proton ATPase 116 kDa subunit a 3, known for its alternative names such as T-cell immune regulator 1, is integral to the V-ATPase complex, facilitating proton translocation and intracellular pH regulation. Its expression and function in T-cell activation suggest a broader role in the immune system, beyond its primary function in acidification.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of V-type proton ATPase 116 kDa subunit a 3 could open doors to potential therapeutic strategies. Given its involvement in the pathogenesis of Osteopetrosis, autosomal recessive 1, targeting this protein offers a promising avenue for developing treatments aimed at improving bone density and function in affected individuals.

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