Focused On-demand Library for DNA polymerase lambda

Focused On-demand Libraries - Receptor.AI 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. Reaxense aids in their synthesis and provision.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


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


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost 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
Receptor.AI
 
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, with alternative names DNA polymerase beta-2 and kappa, is integral to DNA repair, functioning in base excision repair (BER) and contributing to the repair of DNA double-strand breaks via non-homologous end joining and homologous recombination. It possesses template-dependent and independent polymerase activities and a dRP lyase activity, essential for correcting DNA lesions and preserving genomic integrity.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of DNA polymerase lambda unveils potential therapeutic avenues. Given its critical role in DNA repair processes, targeting DNA polymerase lambda could offer novel strategies in the development of therapies for diseases characterized by DNA repair deficiencies, including certain cancers.

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