Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 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 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
Q8TAE8

UPID:
G45IP_HUMAN

ALTERNATIVE NAMES:
39S ribosomal protein L59, mitochondrial; CKII beta-associating protein; CR6-interacting factor 1; Growth arrest and DNA damage-inducible proteins-interacting protein 1; Papillomavirus L2-interacting nuclear protein 1; p53-responsive gene 6 protein

ALTERNATIVE UPACC:
Q8TAE8; Q8IVM3; Q8TE51; Q969P9; Q9BSM6

BACKGROUND:
The protein known as Large ribosomal subunit protein mL64, or CKII beta-associating protein, is integral to the regulation of the cell cycle and transcriptional activity. It inhibits cyclin-dependent kinases, contributing to cell cycle phase progression control. Furthermore, it serves as a repressor for NR4A1, playing a role in both hormone-mediated regulation and mitochondrial protein synthesis, underscoring its multifaceted biological significance.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Large ribosomal subunit protein mL64 may pave the way for innovative therapeutic approaches.

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