AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Serine protease inhibitor Kazal-type 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 for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.

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

P00995

UPID:

ISK1_HUMAN

Alternative names:

Pancreatic secretory trypsin inhibitor; Tumor-associated trypsin inhibitor

Alternative UPACC:

P00995

Background:

Serine protease inhibitor Kazal-type 1, also known as Pancreatic secretory trypsin inhibitor and Tumor-associated trypsin inhibitor, plays a crucial role in the pancreas by preventing trypsin-catalyzed premature activation of zymogens. Additionally, it modulates sperm capacitance in the male reproductive tract by inhibiting calcium uptake and nitrogen oxide production.

Therapeutic significance:

Linked to hereditary pancreatitis and tropical calcific pancreatitis, understanding the role of Serine protease inhibitor Kazal-type 1 could open doors to potential therapeutic strategies for these conditions, emphasizing its importance in disease susceptibility.

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