AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for PHD finger protein 1

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.

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 our associate Reaxense.

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.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

O43189

UPID:

PHF1_HUMAN

Alternative names:

Polycomb-like protein 1

Alternative UPACC:

O43189; B1AZX2; B1AZX3; O60929; Q5SU07; Q5SU08; Q96KM7

Background:

PHD finger protein 1, also known as Polycomb-like protein 1, plays a crucial role in chromatin remodeling and gene expression regulation. It specifically binds to histone H3 trimethylated at 'Lys-36' (H3K36me3) and recruits the PRC2 complex, influencing DNA damage response and double-strand breaks (DSBs) repair. The protein's interaction with H3K36me3, a marker for transcriptional activation, and its ability to regulate the PRC2 complex's activity, highlights its significance in epigenetic mechanisms.

Therapeutic significance:

Understanding the role of PHD finger protein 1 could open doors to potential therapeutic strategies, especially in the context of DNA repair mechanisms and epigenetic regulation.

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