Focused On-demand Library for ADP-ribose glycohydrolase MACROD1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.

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.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.

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.







Alternative names:

MACRO domain-containing protein 1; O-acetyl-ADP-ribose deacetylase MACROD1; Protein LRP16; [Protein ADP-ribosylaspartate] hydrolase MACROD1; [Protein ADP-ribosylglutamate] hydrolase MACROD1

Alternative UPACC:

Q9BQ69; Q9UH96


ADP-ribose glycohydrolase MACROD1, also known as O-acetyl-ADP-ribose deacetylase MACROD1 or Protein LRP16, plays a crucial role in cellular processes by removing ADP-ribose from specific amino acids in proteins and deacetylating O-acetyl-ADP ribose. This protein is involved in estrogen signaling, enhances androgen receptor function, and may influence hormone-dependent cancer progression through a feed-forward mechanism that activates ESR1 transactivation. It also participates in invasive growth regulation by modulating CDH1 expression in endometrial cancer cells.

Therapeutic significance:

Understanding the role of ADP-ribose glycohydrolase MACROD1 could open doors to potential therapeutic strategies, especially in the context of hormone-dependent cancers and invasive growth regulation.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.