AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ragulator complex protein LAMTOR4

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

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.

We use our state-of-the-art dedicated workflow for designing focused 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.

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.

partner

Reaxense

upacc

Q0VGL1

UPID:

LTOR4_HUMAN

Alternative names:

Late endosomal/lysosomal adaptor and MAPK and MTOR activator 4

Alternative UPACC:

Q0VGL1

Background:

Ragulator complex protein LAMTOR4, also known as Late endosomal/lysosomal adaptor and MAPK and MTOR activator 4, plays a pivotal role in amino acid sensing and the activation of mTORC1. This process is crucial for cell growth in response to various stimuli including growth factors, energy levels, and amino acids. LAMTOR4, as part of the Ragulator complex, facilitates the activation of Rag GTPases and their recruitment to the lysosome membrane, thereby acting as a scaffold for mTORC1 activation.

Therapeutic significance:

Understanding the role of Ragulator complex protein LAMTOR4 could open doors to potential therapeutic strategies.

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