Focused On-demand Libraries - Receptor.AI 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 Reaxense.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We use our state-of-the-art dedicated workflow for designing focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
A1Z1Q3

UPID:
MACD2_HUMAN

ALTERNATIVE NAMES:
MACRO domain-containing protein 2; O-acetyl-ADP-ribose deacetylase MACROD2; [Protein ADP-ribosylaspartate] hydrolase MACROD2; [Protein ADP-ribosylglutamate] hydrolase MACROD2

ALTERNATIVE UPACC:
A1Z1Q3; A6NFF7; B0QZ39; B3KWV0; Q0P6D5; Q495E0; Q5W199; Q6ZN71

BACKGROUND:
The protein ADP-ribose glycohydrolase MACROD2, with alternative names such as O-acetyl-ADP-ribose deacetylase MACROD2, plays a pivotal role in the post-translational modification of proteins. By specifically targeting proteins with a single ADP-ribose moiety for de-ADP-ribosylation, MACROD2 regulates important cellular functions and maintains protein stability and function.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of ADP-ribose glycohydrolase MACROD2 holds significant promise for the development of novel therapeutic approaches. Given its critical role in protein modification and cellular signaling, targeting MACROD2 could lead to innovative treatments for diseases where these processes are disrupted.

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