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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 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.


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
Q9UJX3

UPID:
APC7_HUMAN

ALTERNATIVE NAMES:
Cyclosome subunit 7

ALTERNATIVE UPACC:
Q9UJX3; Q96AC4; Q96GF4; Q9BU24; Q9NT16

BACKGROUND:
The Cyclosome subunit 7, also known as Anaphase-promoting complex subunit 7 (APC7), plays a significant role in the cell cycle, particularly in mitosis and the G1 phase. It is part of the APC/C complex, which is responsible for the ubiquitination and degradation of target proteins. APC7 specifically aids in the processive ubiquitination of targets, contributing to brain development by targeting MKI67 for clearance post-mitosis.

THERAPEUTIC SIGNIFICANCE:
Given its critical function in brain development and its link to Ferguson-Bonni neurodevelopmental syndrome, APC7 presents a promising avenue for research into therapeutic interventions. Exploring APC7's mechanisms could lead to novel treatments for neurodevelopmental disorders, highlighting the importance of continued research in this area.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.