Focused On-demand Library for DNA polymerase lambda

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner 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.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

Our library distinguishes itself through several key aspects:

The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9UGP5

UPID:

DPOLL_HUMAN

Alternative names:

DNA polymerase beta-2; DNA polymerase kappa

Alternative UPACC:

Q9UGP5; D3DR76; Q5JQP5; Q6NUM2; Q9BTN8; Q9HA10; Q9HB35

Background:

DNA polymerase lambda, also known as DNA polymerase beta-2 or kappa, plays a pivotal role in DNA repair pathways, including base excision repair (BER) and DNA double-strand break repair through non-homologous end joining and homologous recombination. It exhibits both template-dependent and template-independent DNA polymerase activities, alongside a 5'-deoxyribose-5-phosphate lyase activity, crucial for maintaining genomic stability.

Therapeutic significance:

Understanding the role of DNA polymerase lambda could open doors to potential therapeutic strategies. Its involvement in key DNA repair mechanisms makes it a promising target for enhancing the efficacy of cancer treatments that induce DNA damage, potentially leading to innovative approaches in cancer therapy.