Explore the Potential with AI-Driven Innovation
This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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 our associate Reaxense.
The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.
We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.
Fig. 1. The sreening workflow of Receptor.AI
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 stands out due to several important features:
partner
Reaxense
upacc
Q5SGD2
UPID:
PPM1L_HUMAN
Alternative names:
Protein phosphatase 1-like; Protein phosphatase 2C isoform epsilon
Alternative UPACC:
Q5SGD2; Q2M3J2; Q96NM7
Background:
Protein phosphatase 1L, also known as Protein phosphatase 1-like and Protein phosphatase 2C isoform epsilon, plays a crucial role in cellular signaling by deactivating MAP3K7/TAK1 and MAP3K5 through dephosphorylation. This action suppresses the SAPK signaling pathways, pivotal in cell stress responses.
Therapeutic significance:
Understanding the role of Protein phosphatase 1L could open doors to potential therapeutic strategies by modulating stress response pathways in cells.