AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Factor in the germline alpha

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.

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 utilise our cutting-edge, exclusive workflow to develop focused 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

Q6QHK4

UPID:

FIGLA_HUMAN

Alternative names:

Class C basic helix-loop-helix protein 8; Folliculogenesis-specific basic helix-loop-helix protein; Transcription factor FIGa

Alternative UPACC:

Q6QHK4

Background:

Factor in the germline alpha (FIGLA) is a pivotal transcription factor in oocyte-specific gene expression, crucial for folliculogenesis and early embryonic survival. It regulates the expression of zona pellucida genes (ZP1, ZP2, ZP3), essential for fertilization. FIGLA's role extends to maintaining oocytes and forming primordial follicles, with its presence in adult females indicating additional regulatory pathways for normal ovarian development.

Therapeutic significance:

Premature ovarian failure 6, a condition marked by early cessation of ovarian function, is linked to mutations affecting FIGLA. Understanding FIGLA's role could unveil new therapeutic strategies for treating ovarian disorders.

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