AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Large ribosomal subunit protein mL43

Available from Reaxense
Predicted by Alphafold

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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q8N983

UPID:

RM43_HUMAN

Alternative names:

39S ribosomal protein L43, mitochondrial; Mitochondrial ribosomal protein bMRP36a

Alternative UPACC:

Q8N983; B1AL06; B1AL07; B1AL09; B1AL10; C9J5Q3; D3DR71; Q5JW06; Q7Z719; Q7Z7H6; Q86XN1; Q9BYC7

Background:

The Large ribosomal subunit protein mL43, also known as 39S ribosomal protein L43, mitochondrial, and mitochondrial ribosomal protein bMRP36a, plays a crucial role in the mitochondrial ribosome. Its primary function is to facilitate protein synthesis within the mitochondria, a process essential for cellular energy production and metabolic functions.

Therapeutic significance:

Understanding the role of Large ribosomal subunit protein mL43 could open doors to potential therapeutic strategies. Its pivotal role in mitochondrial function suggests that insights into its operation could lead to breakthroughs in treating diseases linked to mitochondrial dysfunction.

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