Focused On-demand Library for Ragulator complex protein LAMTOR2

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.

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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

Endosomal adaptor protein p14; Late endosomal/lysosomal Mp1-interacting protein; Late endosomal/lysosomal adaptor and MAPK and MTOR activator 2; Mitogen-activated protein-binding protein-interacting protein; Roadblock domain-containing protein 3

Alternative UPACC:

Q9Y2Q5; Q5VY97; Q5VY98; Q5VY99


Ragulator complex protein LAMTOR2, also known as Endosomal adaptor protein p14, plays a pivotal role in cell growth by activating mTORC1 in response to amino acids. It functions within the Ragulator complex to sense amino acids and activate mTORC1, a key signaling complex that promotes cell growth under various conditions. LAMTOR2 facilitates the recruitment of mTORC1 to lysosomes, essential for its activation.

Therapeutic significance:

LAMTOR2's involvement in Immunodeficiency due to defect in MAPBP-interacting protein, characterized by congenital neutropenia and B-cell deficiency, highlights its potential as a therapeutic target. Understanding the role of LAMTOR2 could open doors to potential therapeutic strategies for treating primary immunodeficiency syndromes.

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