Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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.


Our top-notch dedicated system is used to design specialised 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 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.


PARTNER
Receptor.AI
 
UPACC
Q9NXR8

UPID:
ING3_HUMAN

ALTERNATIVE NAMES:
p47ING3

ALTERNATIVE UPACC:
Q9NXR8; A8K790; O60394; Q567P3; Q6GMT3; Q7Z762; Q969G0; Q96DT4; Q9HC99; Q9P081

BACKGROUND:
The protein Inhibitor of growth protein 3, also known as p47ING3, is integral to the NuA4 histone acetyltransferase complex, contributing to the acetylation of nucleosomal histones H4 and H2A. This modification is pivotal for the transcriptional activation of genes associated with growth induction, apoptosis, and DNA repair. Additionally, p47ING3 is involved in a SWR1-like complex that plays a role in histone replacement, crucial for DNA repair mechanisms.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of p47ING3 could open doors to potential therapeutic strategies, especially in the context of Squamous cell carcinoma of the head and neck. Its direct involvement in processes such as DNA repair and transcriptional regulation makes it a promising target for developing novel cancer therapies.

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