AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Large neutral amino acids transporter small subunit 1

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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.

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

Q01650

UPID:

LAT1_HUMAN

Alternative names:

4F2 light chain; CD98 light chain; Integral membrane protein E16; L-type amino acid transporter 1; Solute carrier family 7 member 5; y+ system cationic amino acid transporter

Alternative UPACC:

Q01650; Q8IV97; Q9UBN8; Q9UP15; Q9UQC0

Background:

Large neutral amino acids transporter small subunit 1, also known as Solute carrier family 7 member 5 (SLC7A5), plays a pivotal role in cellular functions by mediating the uptake of large neutral amino acids, including phenylalanine, tyrosine, and leucine. It forms a heterodimer with SLC3A2, facilitating the transport of amino acids, thyroid hormones, and even toxic substances like methylmercury across cell membranes. Its involvement in mTORC1 activation and amino acid exchange underscores its critical biological functions.

Therapeutic significance:

Understanding the role of Large neutral amino acids transporter small subunit 1 could open doors to potential therapeutic strategies. Its key function in amino acid transport and mTORC1 signaling activation, especially in the context of hepatitis C virus propagation, highlights its potential as a target for therapeutic intervention.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.