AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Peptidyl-glycine alpha-amidating monooxygenase

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

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

P19021

UPID:

AMD_HUMAN

Alternative names:

-

Alternative UPACC:

P19021; A6NMR0; A8K293; O43211; O95080; Q16252; Q16253; Q54A45; Q86U53; Q8WVC7; Q9UCG0

Background:

Peptidyl-glycine alpha-amidating monooxygenase plays a pivotal role in the biosynthesis of bioactive peptides through a two-step post-translational modification. This bifunctional enzyme first hydroxylates the C-terminal glycine of peptidylglycine substrates, followed by cleavage to produce alpha-amidated peptides and glyoxylate. Its activity is essential for the maturation of numerous neural and endocrine peptides.

Therapeutic significance:

Understanding the role of Peptidyl-glycine alpha-amidating monooxygenase could open doors to potential therapeutic strategies. Its crucial function in peptide maturation highlights its potential as a target for developing treatments that modulate peptide-mediated biological processes.

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