AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Zinc finger and BTB domain-containing protein 7A

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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.

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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

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

Reaxense

upacc

O95365

UPID:

ZBT7A_HUMAN

Alternative names:

Factor binding IST protein 1; Factor that binds to inducer of short transcripts protein 1; HIV-1 1st-binding protein 1; Leukemia/lymphoma-related factor; POZ and Krueppel erythroid myeloid ontogenic factor; TTF-I-interacting peptide 21; Zinc finger protein 857A

Alternative UPACC:

O95365; D6W619; O00456; Q14D41; Q5XG86

Background:

Zinc finger and BTB domain-containing protein 7A, known by alternative names such as Factor binding IST protein 1 and Leukemia/lymphoma-related factor, plays a pivotal role in gene transcription regulation. It represses a wide range of genes involved in cell proliferation, differentiation, and the TGF-beta signaling pathway. This protein binds specifically to a consensus sequence, influencing chromatin organization and the recruitment of transcription factors to gene regulatory regions.

Therapeutic significance:

The protein is linked to Macrocephaly, neurodevelopmental delay, lymphoid hyperplasia, and persistent fetal hemoglobin, a disease characterized by adenoid overgrowth and sleep apnea. Understanding the role of Zinc finger and BTB domain-containing protein 7A could open doors to potential therapeutic strategies for this condition and its related abnormalities in intellectual development and hemoglobin production.

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