Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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 screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q9BQ69

UPID:
MACD1_HUMAN

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

BACKGROUND:
The protein ADP-ribose glycohydrolase MACROD1, with alternative names such as MACRO domain-containing protein 1 and Protein LRP16, is pivotal in protein modification processes. It specifically targets proteins for ADP-ribosylation and acts on O-acetyl-ADP ribose, a key signaling molecule. MACROD1's interaction with estrogen and androgen receptors underscores its significance in hormone signaling pathways. It amplifies androgen receptor activity and may serve as an ESR1 coactivator, suggesting a critical role in the progression of hormone-dependent cancers and possibly in endometrial cancer cell invasiveness.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions and mechanisms of ADP-ribose glycohydrolase MACROD1 holds promise for unveiling novel therapeutic avenues, particularly in the treatment and management of hormone-related cancers.

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