Focused On-demand Libraries - Receptor.AI 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.


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.


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 employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of 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
Q49AG3

UPID:
ZBED5_HUMAN

ALTERNATIVE NAMES:
Transposon-derived Buster1 transposase-like protein

ALTERNATIVE UPACC:
Q49AG3; B2RCC1; Q05D82; Q86WW3; Q9NT24; Q9UBJ4

BACKGROUND:
The Zinc finger BED domain-containing protein 5, with its alternative identity as Transposon-derived Buster1 transposase-like protein, is pivotal in DNA interaction and gene regulatory mechanisms. This protein's architecture, featuring a zinc finger BED domain, is integral for its function in the intricate network of gene expression control, impacting cellular processes and organismal development.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Zinc finger BED domain-containing protein 5 paves the way for innovative therapeutic approaches. Given its central role in controlling gene expression, targeting this protein could lead to breakthroughs in treating diseases by manipulating pathological gene expressions.

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