Focused On-demand Library for General transcription and DNA repair factor IIH helicase subunit XPB

Details

Focused On-demand Libraries - Receptor.AI 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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


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.


Our high-tech, dedicated method is applied to construct targeted 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
P19447

UPID:
ERCC3_HUMAN

ALTERNATIVE NAMES:
Basic transcription factor 2 89 kDa subunit; DNA excision repair protein ERCC-3; DNA repair protein complementing XP-B cells; TFIIH basal transcription factor complex 89 kDa subunit; Xeroderma pigmentosum group B-complementing protein

ALTERNATIVE UPACC:
P19447; Q53QM0

BACKGROUND:
General transcription and DNA repair factor IIH helicase subunit XPB, also known as DNA repair protein complementing XP-B cells, is integral to the cell's ability to repair damaged DNA and initiate RNA transcription. This protein's ATPase activity, distinct from its helicase function, is required for DNA opening during repair processes and transcription initiation, highlighting its critical role in maintaining genomic integrity.

THERAPEUTIC SIGNIFICANCE:
The protein's crucial role in disorders such as Xeroderma pigmentosum complementation group B and Trichothiodystrophy 2 underscores the therapeutic potential of targeting its functions. By elucidating the mechanisms of General transcription and DNA repair factor IIH helicase subunit XPB in DNA repair and transcription, novel treatment strategies for these conditions may be developed, offering hope for patients.

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