Focused On-demand Library for DNA excision repair protein ERCC-5

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


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


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
P28715

UPID:
ERCC5_HUMAN

ALTERNATIVE NAMES:
DNA repair protein complementing XP-G cells; Xeroderma pigmentosum group G-complementing protein

ALTERNATIVE UPACC:
P28715; A6NGT4; Q5JUS4; Q5JUS5; Q7Z2V3; Q8IZL6; Q8N1B7; Q9HD59; Q9HD60

BACKGROUND:
ERCC-5, known for its alternative names such as Xeroderma pigmentosum group G-complementing protein, is essential for maintaining genomic stability. It executes this by participating in various DNA repair pathways including NER, BER, TCR, and HRR. ERCC-5's unique ability to stabilize DNA replication forks under stress and its involvement in lesion removal from active genes underscore its critical role in cellular repair processes.

THERAPEUTIC SIGNIFICANCE:
Mutations in ERCC-5 contribute to severe disorders like Xeroderma pigmentosum complementation group G and Cerebro-oculo-facio-skeletal syndrome 3, highlighting its therapeutic significance. Targeting ERCC-5's function in DNA repair pathways offers a promising avenue for developing treatments for these genetic diseases.

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