Focused On-demand Libraries - Receptor.AI 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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
Q9NR50

UPID:
EI2BG_HUMAN

ALTERNATIVE NAMES:
eIF-2B GDP-GTP exchange factor subunit gamma

ALTERNATIVE UPACC:
Q9NR50; B2RBH8; D3DPZ2; Q5QP89; Q5QP90; Q8NDB5; Q8WV57; Q9H850

BACKGROUND:
The protein known as Translation initiation factor eIF-2B subunit gamma, or eIF-2B GDP-GTP exchange factor subunit gamma, is essential for the initiation of protein synthesis. It facilitates the critical exchange of GDP for GTP on eukaryotic initiation factor 2, a step fundamental to the protein synthesis process.

THERAPEUTIC SIGNIFICANCE:
Mutations in the gene encoding Translation initiation factor eIF-2B subunit gamma are associated with Leukoencephalopathy with vanishing white matter 3, underscoring the protein's potential as a target for therapeutic intervention. The exploration of this protein's function offers promising avenues for the development of treatments for this and possibly other related neurological disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.