Focused On-demand Library for RING finger and CHY zinc finger domain-containing protein 1
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.
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.
Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.
This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.
Our library is unique due to several crucial aspects:
- Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
- By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
- The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
- Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.
Receptor.AI
Q96PM5
UPID:
ZN363_HUMAN
ALTERNATIVE NAMES:
Androgen receptor N-terminal-interacting protein; CH-rich-interacting match with PLAG1; E3 ubiquitin-protein ligase Pirh2; RING finger protein 199; RING-type E3 ubiquitin transferase RCHY1; Zinc finger protein 363; p53-induced RING-H2 protein
ALTERNATIVE UPACC:
Q96PM5; B3KRG3; C7E541; C7E542; C7E543; D3YRV2; E7EMC8; E7ETW5; J3KPI0; Q2KN33; Q59GN7; Q86X26; Q96PR5