Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer

• Main Authors: Danishuddin (Author), Vikas Kumar (Author), Shraddha Parate (Author), Ashutosh Bahuguna (Author), Gihwan Lee (Author), Myeong Ok Kim (Author), Keun Woo Lee (Author)
• Format: Book
• Published: MDPI AG, 2021-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Disruption of epigenetic processes to eradicate tumor cells is among the most promising interventions for cancer control. EZH2 (Enhancer of zeste homolog 2), a catalytic component of polycomb repressive complex 2 (PRC2), methylates lysine 27 of histone H3 to promote transcriptional silencing and is...