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.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


Our top-notch dedicated system is used to design specialised 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
Q99497

UPID:
PARK7_HUMAN

ALTERNATIVE NAMES:
Maillard deglycase; Oncogene DJ1; Parkinsonism-associated deglycase; Protein DJ-1; Protein/nucleic acid deglycase DJ-1

ALTERNATIVE UPACC:
Q99497; B2R4Z1; O14805; Q6DR95; Q7LFU2

BACKGROUND:
The multifunctional protein Parkinson disease protein 7, known as Protein DJ-1, is integral to cell protection mechanisms against oxidative stress. It acts as a sensor and chaperone, modulating cell death and survival pathways. PARK7's role extends to neuroprotection, fertility, and cellular growth, highlighting its importance in maintaining cellular homeostasis. Its ability to repair glycated proteins and nucleotides positions it as a key player in preventing cellular damage.

THERAPEUTIC SIGNIFICANCE:
Given PARK7's critical role in Parkinson disease 7, characterized by early-onset neurodegeneration and a good initial response to levodopa, its study is paramount. The protein's neuroprotective and antioxidative functions make it a promising target for developing novel therapeutic approaches to combat Parkinson's disease and potentially other neurodegenerative disorders.

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.