AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Zinc finger protein 423

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.

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.

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.

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

Q2M1K9

UPID:

ZN423_HUMAN

Alternative names:

Olf1/EBF-associated zinc finger protein; Smad- and Olf-interacting zinc finger protein

Alternative UPACC:

Q2M1K9; O94860; Q76N04; Q9NZ13

Background:

Zinc finger protein 423, also known as Olf1/EBF-associated zinc finger protein or Smad- and Olf-interacting zinc finger protein, plays a pivotal role in BMP signaling and olfactory neurogenesis. It functions as a transcription factor that can act as an activator or repressor. It is crucial in the transition from differentiation to maturation in olfactory receptor neurons and in the formation of the cerebellar vermis.

Therapeutic significance:

Zinc finger protein 423 is implicated in Nephronophthisis 14 and Joubert syndrome 19, diseases characterized by kidney disorders and cerebellar vermis hypoplasia. Understanding the role of Zinc finger protein 423 could open doors to potential therapeutic strategies for these conditions.

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