AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Membrane primary amine oxidase

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

Q16853

UPID:

AOC3_HUMAN

Alternative names:

Copper amine oxidase; HPAO; Semicarbazide-sensitive amine oxidase; Vascular adhesion protein 1

Alternative UPACC:

Q16853; B2RCI5; K7ESB3; L0L8N9; Q45F94

Background:

Membrane primary amine oxidase, also known as Copper amine oxidase, HPAO, Semicarbazide-sensitive amine oxidase, and Vascular adhesion protein 1, plays a crucial role in cell adhesion, facilitating lymphocyte extravasation and recirculation. This protein's activity includes semicarbazide-sensitive monoamine oxidase functionality, contributing to its involvement in adipogenesis.

Therapeutic significance:

Understanding the role of Membrane primary amine oxidase could open doors to potential therapeutic strategies. Its involvement in lymphocyte function and adipogenesis highlights its potential as a target for therapeutic intervention in immune and metabolic disorders.

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