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

Details

Focused On-demand Libraries - Receptor.AI 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 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.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


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
Receptor.AI
 
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, also known as HIV-1 1st-binding protein 1, is crucial for cellular processes including glycolysis, adipogenesis, and the differentiation of lymphoid progenitors. It functions as an androgen receptor corepressor and is involved in the fetal to adult globin expression switch, highlighting its importance in erythroid cell maturation.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in a unique autosomal dominant disease with features like macrocephaly and neurodevelopmental delay, Zinc finger and BTB domain-containing protein 7A represents a significant target for drug discovery. Its role in regulating cell proliferation and differentiation pathways underscores its potential in developing treatments for related genetic disorders.

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