AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for PHD finger protein 6

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 our partner 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.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q8IWS0

UPID:

PHF6_HUMAN

Alternative names:

PHD-like zinc finger protein

Alternative UPACC:

Q8IWS0; A8K230; B4E0G4; D3DTG3; E9PC97; Q5JRC7; Q5JRC8; Q96JK3; Q9BRU0

Background:

PHD finger protein 6, also known as PHD-like zinc finger protein, plays a pivotal role in cellular processes by associating with ribosomal RNA promoters to suppress ribosomal RNA transcription. This regulatory function is crucial for maintaining cellular homeostasis and ensuring proper protein synthesis rates.

Therapeutic significance:

Given its involvement in Boerjeson-Forssman-Lehmann syndrome, a disorder marked by intellectual disability and metabolic abnormalities, PHD finger protein 6 presents a promising target for therapeutic intervention. Understanding the role of PHD finger protein 6 could open doors to potential therapeutic strategies aimed at mitigating the symptoms of this syndrome.

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