Focused On-demand Library for 2-5A-dependent ribonuclease

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 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 employ our advanced, specialised process to create targeted 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.

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.







Alternative names:

Ribonuclease 4; Ribonuclease L

Alternative UPACC:

Q05823; Q5W0L2; Q6AI46


2-5A-dependent ribonuclease, also known as Ribonuclease L, plays a pivotal role in the interferon (IFN) antiviral response. It mediates its antiviral effects through various mechanisms, including direct cleavage of viral RNAs, degradation of rRNA to inhibit protein synthesis, induction of apoptosis, and activation of other antiviral genes. Its ability to cleave at specific RNA sequences and regulate mRNA turnover underscores its importance in cellular defense mechanisms.

Therapeutic significance:

Given its crucial role in the antiviral response and regulation of apoptosis, Ribonuclease L is directly associated with hereditary prostate cancer. Understanding the intricate functions of Ribonuclease L could pave the way for innovative therapeutic strategies targeting viral infections and cancer, particularly in developing treatments for hereditary prostate cancer.

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