Focused On-demand Library for Non-homologous end-joining factor 1

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 employ our advanced, specialised process to create targeted libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

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

Q9H9Q4

UPID:

NHEJ1_HUMAN

Alternative names:

Protein cernunnos; XRCC4-like factor

Alternative UPACC:

Q9H9Q4; B8ZZA4; Q4ZFW7; Q6IA64; Q96JS9

Background:

Non-homologous end-joining factor 1, also known as Protein cernunnos or XRCC4-like factor, plays a crucial role in DNA repair. It is pivotal in the DNA non-homologous end joining (NHEJ) process, essential for double-strand break (DSB) repair and V(D)J recombination. This protein promotes the ligation of mismatched and non-cohesive ends, collaborating with PAXX and DNA polymerase lambda to join non-cohesive DNA ends. It forms complexes with XRCC4, bridging broken DNA fragments for repair.

Therapeutic significance:

Severe combined immunodeficiency due to NHEJ1 deficiency highlights the critical role of Non-homologous end-joining factor 1 in immune system development and function. Understanding the role of Non-homologous end-joining factor 1 could open doors to potential therapeutic strategies for genetic disorders characterized by impaired DNA repair mechanisms.