AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Proprotein convertase subtilisin/kexin type 7

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.

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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

partner

Reaxense

upacc

Q16549

UPID:

PCSK7_HUMAN

Alternative names:

Lymphoma proprotein convertase; Prohormone convertase 7; Proprotein convertase 7; Proprotein convertase 8; Subtilisin/kexin-like protease PC7

Alternative UPACC:

Q16549; B0YJ60; Q3C1X1; Q53GM4; Q96FK8; Q9UL57

Background:

Proprotein convertase subtilisin/kexin type 7 (PCSK7), also known as Prohormone convertase 7, Proprotein convertase 7, and Subtilisin/kexin-like protease PC7, is a serine endoprotease. It plays a crucial role in the processing of various proproteins by cleavage at paired basic amino acids, specifically recognizing the RXXX[KR]R consensus motif. PCSK7 is likely involved in the constitutive secretory pathway, indicating its pivotal role in protein maturation and regulation.

Therapeutic significance:

Understanding the role of Proprotein convertase subtilisin/kexin type 7 could open doors to potential therapeutic strategies. Its involvement in the processing of proproteins suggests a fundamental role in cellular mechanisms, which, if modulated, could offer new avenues for treating diseases.

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