AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Extracellular tyrosine-protein kinase PKDCC

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.

Our top-notch dedicated system is used to design specialised 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q504Y2

UPID:

PKDCC_HUMAN

Alternative names:

Protein kinase domain-containing protein, cytoplasmic; Protein kinase-like protein SgK493; Sugen kinase 493; Vertebrate lonesome kinase

Alternative UPACC:

Q504Y2; D6W5A0; Q96I09

Background:

Extracellular tyrosine-protein kinase PKDCC, also known as Sugen kinase 493, plays a pivotal role in organogenesis through the phosphorylation of extracellular and endogenous proteins in the secretory pathway. It is essential for longitudinal bone growth, mediating chondrocyte differentiation and possibly involved in protein transport from the Golgi to the plasma membrane.

Therapeutic significance:

Linked to Rhizomelic limb shortening with dysmorphic features, PKDCC's understanding could pave the way for innovative treatments targeting skeletal dysplasia, offering hope for affected individuals.

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