AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ribosome-releasing factor 2, mitochondrial

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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 sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q969S9

UPID:

RRF2M_HUMAN

Alternative names:

Elongation factor G 2, mitochondrial; Elongation factor G2

Alternative UPACC:

Q969S9; A0AR28; Q8N6D8; Q8WYI0; Q9H6Z1

Background:

Ribosome-releasing factor 2, mitochondrial, also known as Elongation factor G2, plays a crucial role in mitochondrial protein biosynthesis. It mediates the disassembly of ribosomes from messenger RNA post-translation, in collaboration with MRRF, ensuring efficient mitochondrial function.

Therapeutic significance:

Linked to Combined oxidative phosphorylation deficiency 39, a disorder stemming from mitochondrial dysfunction, understanding Ribosome-releasing factor 2's role could open doors to potential therapeutic strategies.

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