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

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.

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 our associate Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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.

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

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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