AI-ACCELERATED DRUG DISCOVERY

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

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.

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.

 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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's 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.

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