In the post-genomic era, computational modeling, simulations and genomics play a critical role in the next revolution in cancer research. Computational biology is an interdisciplinary field that uses the techniques of computer science, applied mathematics, and statistics to address problems in biology. The supercomputer is widely used in computational biology. We have applied supercomputers in cancer prevention research and have made progress in the following areas:

1) Mapping protein interaction networks in cancer cells (e.g., to study protein kinase interactions with other protein kinases, transcription factors, or other proteins)

2) Computational screening of chemical libraries against target proteins, identification of available chemical libraries (NCI; natural compounds, etc.), crystal structures or homology screening

3) Reverse docking and screening of protein structures against a chemical to identify its molecular target(s)

4) Drug target discovery by supercomputer and in vitro and in vivo validation of computer-identified potential targets using:

a) kinase assays

b) site mutagenesis

c) animal studies

5) Identifying key protein/DNA interactions

6) Modeling cancer promotion and progression in order to study cancer promotion, progression, and therapeutic effectiveness to predict success (i.e. predicting drug resistance)

Citation Format: Zigang Dong. Computerized approaches to molecularly designed drugs and target identification for cancer prevention. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr CN08-01.

©2012 American Association for Cancer Research.
2012