AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Sodium- and chloride-dependent transporter XTRP3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 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.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q9NP91

UPID:

S6A20_HUMAN

Alternative names:

Sodium/imino-acid transporter 1; Solute carrier family 6 member 20; Transporter rB21A homolog

Alternative UPACC:

Q9NP91; A1A4F2; O75590; Q8TF10; Q9NPQ2; Q9NQ77

Background:

The Sodium- and chloride-dependent transporter XTRP3, also known as Sodium/imino-acid transporter 1, Solute carrier family 6 member 20, and Transporter rB21A homolog, plays a crucial role in the Na(+)- and Cl(-)-dependent uptake of imino acids such as L-proline, N-methyl-L-proline, and pipecolate, as well as N-methylated amino acids. It is pivotal in regulating proline and glycine homeostasis in the brain, influencing NMDAR currents.

Therapeutic significance:

XTRP3's involvement in conditions like Hyperglycinuria and Iminoglycinuria, due to gene variants affecting its function, highlights its therapeutic potential. Targeting XTRP3 could lead to innovative treatments for these renal and metabolic disorders, emphasizing the importance of understanding its role in disease mechanisms.

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