AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Protein sprouty homolog 4

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 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.

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

Q9C004

UPID:

SPY4_HUMAN

Alternative names:

-

Alternative UPACC:

Q9C004; A4FVB2; A4FVB3; Q6QIX2; Q9C003

Background:

Protein sprouty homolog 4 plays a pivotal role in suppressing the insulin receptor and EGFR-transduced MAPK signaling pathways, crucial for cell growth and differentiation. It uniquely inhibits MAPK activation by a constitutively active mutant Ras, highlighting its specificity in cellular signaling modulation. Additionally, it represses integrin-mediated cell spreading, underscoring its importance in cell migration and adhesion processes.

Therapeutic significance:

Given its involvement in Hypogonadotropic hypogonadism 17 with or without anosmia, a disorder linked to impaired sexual maturation and sensory deficits, Protein sprouty homolog 4 presents a promising target for therapeutic intervention. Understanding its role could open doors to potential therapeutic strategies, especially considering its regulatory impact on critical signaling pathways and cell behavior.

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