AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Amino acid transporter heavy chain SLC3A1

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.

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 our partner Reaxense.

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.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

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

Q07837

UPID:

SLC31_HUMAN

Alternative names:

D2h; Neutral and basic amino acid transport protein; Solute carrier family 3 member 1; b(0,+)-type amino acid transporter-related heavy chain

Alternative UPACC:

Q07837; A8K0S1; O00658; Q15295; Q4J6B4; Q4J6B5; Q4J6B6; Q4J6B7; Q4J6B8; Q4J6B9; Q52M92; Q52M94

Background:

The Amino acid transporter heavy chain SLC3A1, also known as D2h, plays a crucial role in the biogenesis and trafficking of transporter heteromers, particularly in facilitating the exchange between cationic and neutral amino acids across cell membranes. Its association with SLC7A9 forms a transporter complex vital for the reabsorption of L-cystine and dibasic amino acids, key in maintaining amino acid balance.

Therapeutic significance:

SLC3A1's involvement in Cystinuria and Hypotonia-cystinuria syndrome underscores its therapeutic significance. Targeting the SLC3A1-SLC7A9 transporter complex offers a promising strategy for treating these genetic disorders, highlighting the importance of understanding SLC3A1's function and regulation.

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