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.


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 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


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
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:
The Nuclear factor 1 A-type, alternatively named CCAAT-box-binding transcription factor or TGGCA-binding protein, is a key regulator of viral and cellular promoter activation and DNA replication. It specifically binds to the sequence 5'-TTGGCNNNNNGCCAA-3', facilitating transcription and replication activities essential for cellular function and viral replication.

THERAPEUTIC SIGNIFICANCE:
Linked to the development of brain malformations and urinary tract defects, NFIA's involvement in such diseases underscores its potential as a target for therapeutic intervention. Exploring NFIA's function further could lead to novel treatments for these complex conditions.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.