AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein POF1B

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated 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.

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

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

Q8WVV4

UPID:

POF1B_HUMAN

Alternative names:

Premature ovarian failure protein 1B

Alternative UPACC:

Q8WVV4; A8K2U5; Q5H9E9; Q5H9F0; Q8NG12; Q9H5Y2; Q9H738; Q9H744

Background:

Protein POF1B, also known as Premature ovarian failure protein 1B, plays a pivotal role in the organization of epithelial monolayers by regulating the actin cytoskeleton. Its involvement in ovary development is crucial, suggesting a significant function in reproductive biology.

Therapeutic significance:

Linked to Premature ovarian failure 2B, a disorder causing cessation of ovarian function before 40 years, Protein POF1B's genetic variants highlight its critical role. Understanding the role of Protein POF1B could open doors to potential therapeutic strategies for ovarian disorders.

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