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.
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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.
We use our state-of-the-art dedicated workflow for designing focused libraries for ion channels.
It features detailed molecular simulations of the ion channel in its native membrane environment across its open, closed, and inactivated forms, coupled with ensemble virtual screening considering conformational mobility in these states. Potential binding sites are explored within the pore, in the gating region, and at allosteric locations to encompass all potential mechanisms of action.
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
Q9Y6J6
UPID:
KCNE2_HUMAN
ALTERNATIVE NAMES:
MinK-related peptide 1; Minimum potassium ion channel-related peptide 1; Potassium channel subunit beta MiRP1
ALTERNATIVE UPACC:
Q9Y6J6; A5H1P3; D3DSF8; Q52LJ5