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.


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 effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse 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
Receptor.AI
 
UPACC
Q8IWS0

UPID:
PHF6_HUMAN

ALTERNATIVE NAMES:
PHD-like zinc finger protein

ALTERNATIVE UPACC:
Q8IWS0; A8K230; B4E0G4; D3DTG3; E9PC97; Q5JRC7; Q5JRC8; Q96JK3; Q9BRU0

BACKGROUND:
The PHD finger protein 6, with alternative names including PHD-like zinc finger protein, is a transcriptional regulator critical for suppressing ribosomal RNA transcription. This suppression is essential for the balanced production of ribosomal RNA, a key component in protein synthesis and cellular growth.

THERAPEUTIC SIGNIFICANCE:
The direct association of PHD finger protein 6 with Boerjeson-Forssman-Lehmann syndrome underscores its potential as a therapeutic target. By elucidating the mechanisms through which PHD finger protein 6 influences this X-linked recessive disorder, researchers can pave the way for developing treatments that address the underlying genetic causes.

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