A Novel Approach to Predict Core Residues on Cancer-Related DNA-Binding Domains.
Protein-DNA interactions are involved in different cancer pathways. In particular, the DNA-binding domains of proteins can determine where and how gene regulatory regions are bound in different cell lines at different stages. Therefore, it is essential to develop a method to predict and locate the core residues on cancer-related DNA-binding domains. In this study, we propose a computational method to predict and locate core residues on DNA-binding domains. In particular, we have selected the cancer-related DNA-binding domains for in-depth studies, namely, winged Helix Turn Helix family, homeodomain family, and basic Helix-Loop-Helix family. The results demonstrate that the proposed method can predict the core residues involved in protein-DNA interactions, as verified by the existing structural data. Given its good performance, various aspects of the method are discussed and explored: for instance, different uses of prediction algorithm, different protein domains, and hotspot threshold setting.
Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong.
Ka-Chun
KC
Wong
DNA-binding domains; Protein-DNA binding interactions; SNPdryad; applied machine learning; big data analytics; bioinformatics; cancer