Focused On-demand Library for Methyltransferase-like protein 17, mitochondrial

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.

Our top-notch dedicated system is used to design specialised libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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

Q9H7H0

UPID:

MET17_HUMAN

Alternative names:

False p73 target gene protein; Methyltransferase 11 domain-containing protein 1; Protein RSM22 homolog, mitochondrial

Alternative UPACC:

Q9H7H0; Q9BSH1; Q9BZH2; Q9BZH3

Background:

Methyltransferase-like protein 17, mitochondrial, known as Q9H7H0, plays a crucial role in mitochondrial function. It acts as a probable S-adenosyl-L-methionine-dependent RNA methyltransferase, essential for stabilizing the mitochondrial small ribosomal subunit (mt-SSU). This stabilization is vital for protein translation within mitochondria, highlighting its significance in cellular energy production and overall mitochondrial health.

Therapeutic significance:

Understanding the role of Methyltransferase-like protein 17 could open doors to potential therapeutic strategies. Its pivotal function in mitochondrial protein synthesis positions it as a key target for interventions aimed at mitochondrial disorders and diseases with mitochondrial dysfunction components.