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 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 screening 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.


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
Q9Y6R1

UPID:
S4A4_HUMAN

ALTERNATIVE NAMES:
Na(+)/HCO3(-) cotransporter; Solute carrier family 4 member 4; kNBC1

ALTERNATIVE UPACC:
Q9Y6R1; C4B714; O15153; Q8NEJ2; Q9H262; Q9NRZ1; Q9UIC0; Q9UIC1; Q9UP50

BACKGROUND:
The Electrogenic sodium bicarbonate cotransporter 1, known variably as Na(+)/HCO3(-) cotransporter, kNBC1, and Solute carrier family 4 member 4, is integral for bicarbonate transport across cell membranes. Its function in adjusting the Na(+):HCO3(-) stoichiometry from 1:2 to 1:3 is essential for cellular pH homeostasis.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Electrogenic sodium bicarbonate cotransporter 1 could open doors to potential therapeutic strategies. Its involvement in a rare syndrome characterized by renal tubular acidosis and ocular abnormalities highlights its therapeutic relevance, offering a promising avenue for research and drug development.

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