Focused On-demand Library for Ribosomal protein uL3-like

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.

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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal 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 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.

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.







Alternative names:

60S ribosomal protein L3-like; Large ribosomal subunit protein uL3-like

Alternative UPACC:



The Ribosomal protein uL3-like, known alternatively as 60S ribosomal protein L3-like or Large ribosomal subunit protein uL3-like, plays a pivotal role in the synthesis of proteins within the cell. Specifically, it is a heart- and skeletal muscle-specific component of the ribosome, crucial for regulating muscle function. This protein uniquely replaces the RPL3 paralog in the ribosome of striated muscle cells, highlighting its specialized function in muscle tissue.

Therapeutic significance:

Given its involvement in Cardiomyopathy, dilated, 2D, a severe disorder marked by ventricular dilation, impaired systolic function, and an elevated risk of premature death, the Ribosomal protein uL3-like represents a significant target for therapeutic intervention. Understanding the role of Ribosomal protein uL3-like could open doors to potential therapeutic strategies, particularly for treating severe forms of cardiomyopathy with neonatal onset.

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