AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for DNA-directed DNA/RNA polymerase mu

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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.

partner

Reaxense

upacc

Q9NP87

UPID:

DPOLM_HUMAN

Alternative names:

Terminal transferase

Alternative UPACC:

Q9NP87; D3DVK4; Q6P5X8; Q86WQ9

Background:

DNA-directed DNA/RNA polymerase mu, also known as Terminal transferase, plays a crucial role in the repair of DNA double-strand breaks through non-homologous end joining (NHEJ). It is instrumental in the immunoglobulin light chain gene rearrangement during V(D)J recombination, a process vital for the diversity of the immune response.

Therapeutic significance:

Understanding the role of DNA-directed DNA/RNA polymerase mu could open doors to potential therapeutic strategies. Its involvement in DNA repair and immune system development positions it as a key target for enhancing genomic stability and treating immunodeficiencies.

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