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https://www.selleckchem.com/products/1-4-diaminobutane-dihydrochloride.html Transcriptional enhanced associate domain (TEAD) proteins bind to YAP/TAZ and mediate YAP/TAZ-induced gene expression. TEADs are not only the key transcription factors and final effector of the Hippo signaling pathway, but also the proteins that regulate cell proliferation and apoptosis. Disorders of Hippo signaling pathway occur in liver cancer, breast cancer, colon cancer and other cancers. S-palmitylation can stabilize the structure of TEADs and is also a necessary condition for the binding of TEADs to YAP/TAZ. The absence of TEAD palmitoylation prevents TEADs from binding to chromatin, thereby inhibiting the transcription and expression of downstream target genes in the Hippo pathway through a dominant-negative mechanism. Therefore, disrupting the S-palmitylation of TEADs has become an attractive and very feasible method in cancer treatment. The palmitate binding pockets of TEADs are conservative, and the crystal structures of TEAD2-palmitoylation inhibitor complexes and the potential TEAD2 inhibitors areupplementary materials are available online.S-Adenosyl methionine (SAM), a universal methyl group donor, plays a vital role in biosynthesis and acts as an inhibitor to many enzymes. Due to protein interaction-dependent biological role, SAM has become a favorite target in various therapeutical and clinical studies such as treating cancer, Alzheimer's, epilepsy, and neurological disorders. Therefore, the identification of the SAM interacting proteins and their interaction sites is a biologically significant problem. However, wet-lab techniques, though accurate, to identify SAM interactions and interaction sites are tedious and costly. Therefore, efficient and accurate computational methods for this purpose are vital to the design and assist such wet-lab experiments. In this study, we present machine learning-based models to predict SAM interacting proteins and their interaction sites by us
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