K current

Liver cancer is one of the leading malignancies which occupies the second position in cancer deaths worldwide, becoming serious threat to human health. Hepatocellular carcinoma (HCC), also known as hepatoma is the most common type accounting for approximately 90% of all liver cancers.

Current evidence indicates that during hepatocarcinogenesis, two main pathogenic mechanisms prevail: (1) cirrhosis associated with hepatic regeneration after tissue damage caused by hepatitis infection, toxins or metabolic influences, and (2) mutations occurring in single or multiple oncogenes or tumor suppressor genes. Both mechanisms have been linked with alterations in several important cellular signaling pathways. These include the RAF/MEK/ERK pathway, PI3K/AKT/mTOR pathway, WNT/b-catenin pathway, insulin-like growth factor pathway, c-MET/HGFR pathway , etc.

MCE offers a unique collection of 3,003 compounds with identified and potential anti-liver cancer activity. MCE anti-liver cancer compound library is a useful tool for anti-liver cancer drugs screening and other related research.

Ion channels are key proteins on the cell membrane that regulate the flow of ions across membranes. They participate in nearly all physiological processes, including nerve conduction, muscle contraction, heart rhythm, and pain perception. Abnormalities in their function can lead to various serious diseases such as arrhythmia, epilepsy, hypertension, neuropathic pain, and cancer. Therefore, ion channels are highly valuable drug targets—over 15% of approved drugs target ion channels currently, demonstrating their irreplaceable therapeutic value in cardiovascular, neurological, and analgesic fields.

MCE has collected a library of over 5,000 reported ion channel-related bioactive compounds targeting major sites such as Na+ channels, K+ channels, Ca2+ channels, GABA receptors, iGluRs, and others. Using AI models, these compounds are characterized through both 2D representations (molecular fingerprints, pharmacophores) and 3D representations (3D conformation) to screen for a collection of lead-like compounds highly similar to known active molecules. Additionally, an hERG channel prediction algorithm integrating XGB and ISE mapping strategy is employed to assess and exclude potential cardiotoxicity in the library.. This step significantly reduces safety risks in subsequent screenings, particularly for ion channel drug development related to cardiovascular systems (e.g., Nav1.5, Cav1.2), effectively minimizing failures due to hERG inhibition and serving as a valuable tool for ion channel drug screening.