AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ras-related GTP-binding protein A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

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

Q7L523

UPID:

RRAGA_HUMAN

Alternative names:

Adenovirus E3 14.7 kDa-interacting protein 1; FIP-1

Alternative UPACC:

Q7L523; B2R7L1; O00290; Q15347

Background:

Ras-related GTP-binding protein A, also known as Adenovirus E3 14.7 kDa-interacting protein 1 or FIP-1, is a pivotal player in the cellular response to amino acid availability, influencing the mTORC1 signaling cascade. It forms heterodimeric Rag complexes, cycling between GDP-bound and GTP-bound forms, thereby regulating mTORC1's relocalization to lysosomes and activation. Additionally, it contributes to the RCC1/Ran-GTPase pathway and may play a role in TNF-alpha signaling pathways, impacting cell death.

Therapeutic significance:

Understanding the role of Ras-related GTP-binding protein A could open doors to potential therapeutic strategies.

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