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

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.

Our top-notch dedicated system is used to design specialised libraries.

Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of 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

Q12857

UPID:

NFIA_HUMAN

Alternative names:

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

Alternative UPACC:

Q12857; B4DRJ3; B4DS53; F5H0R0; F8W8W3; Q8TA97; Q9H3X9; Q9P2A9

Background:

Nuclear factor 1 A-type (NFIA) plays a pivotal role in DNA replication and transcription, recognizing and binding the specific palindromic sequence 5'-TTGGCNNNNNGCCAA-3'. This sequence is found in both viral and cellular promoters as well as in the origin of replication of adenovirus type 2. NFIA, also known as CCAAT-box-binding transcription factor or TGGCA-binding protein, is essential for the activation of transcription and replication processes.

Therapeutic significance:

NFIA is implicated in brain malformations with or without urinary tract defects, a syndrome characterized by corpus callosum hypoplasia or agenesis, hydrocephalus or ventricular enlargement, and developmental delay. Understanding the role of NFIA could open doors to potential therapeutic strategies for these conditions.