AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Nuclear factor 1 B-type

Available from Reaxense
Predicted by Alphafold

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 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 utilise our cutting-edge, exclusive workflow to develop focused libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

O00712

UPID:

NFIB_HUMAN

Alternative names:

CCAAT-box-binding transcription factor; Nuclear factor I/B; TGGCA-binding protein

Alternative UPACC:

O00712; G3V1P1; H7BYE8; O00166; Q12858; Q5VW29; Q63HM5; Q6ZNF9; Q96J45

Background:

Nuclear factor 1 B-type, also known as CCAAT-box-binding transcription factor or TGGCA-binding protein, plays a pivotal role in brain development. It acts as a transcriptional activator of GFAP, recognizing and binding specific palindromic sequences in promoters and replication origins. This protein's activity is crucial for the transcription and replication processes in both viral and cellular contexts.

Therapeutic significance:

The protein is linked to Macrocephaly, acquired, with impaired intellectual development, a disorder marked by postnatal macrocephaly and varying degrees of neurodevelopmental issues. Understanding the role of Nuclear factor 1 B-type could open doors to potential therapeutic strategies for this and related neurodevelopmental disorders.

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