Focused On-demand Library for Large ribosomal subunit protein mL42

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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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.

Our library stands out due to several important features:

The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9Y6G3

UPID:

RM42_HUMAN

Alternative names:

39S ribosomal protein L31, mitochondrial; 39S ribosomal protein L42, mitochondrial

Alternative UPACC:

Q9Y6G3; Q6FID1; Q96Q48; Q9P0S1

Background:

The Large ribosomal subunit protein mL42, also known as 39S ribosomal protein L31 and L42, is a mitochondrial protein crucial for protein synthesis within the cell. Its alternative names reflect its role and localization within the mitochondrial ribosome, where it participates in the translation of mitochondrial DNA-encoded proteins.

Therapeutic significance:

Understanding the role of Large ribosomal subunit protein mL42 could open doors to potential therapeutic strategies. Its fundamental role in mitochondrial function suggests that insights into its operation could lead to breakthroughs in treating diseases linked to mitochondrial dysfunction.