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.

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 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 sreening 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

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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