Computational biology enabling new discoveries to solve complex global problems
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Ask any experienced do-it-yourselfer or professional and they'll tell you the importance of using the "right tool for the right job." At Pacific Northwest National Laboratory's Computational and Information Sciences Directorate (CISD), the right tools are powerful high-speed computer systems that are analyzing vast amounts of data and enabling scientists to discover solutions to many complex global problems. Through computational biology, scientists are gaining new knowledge about proteins, cell membranes in microbes, and genome sequences that will lead to prevention and treatment of disease, new methods for environmental cleanup, and countermeasures against bioterrorism.
Biological systems are complex, and understanding them requires the processing of enormous amounts of data. In computational biology, sophisticated mathematical and equation-based computer models and simulations are created to enable scientists to understand and predict how cells behave, interact and respond to their environments. For example, in proteomics--the study of the structure and function of proteins and how they work and interact with each other inside cells--computer models are being used to identify protein "markers" that can indicate the probable onset of disease, which can lead to new prevention and treatment methods. Scientists also are relying on high-speed data analysis to study a protein complex called Ras. Because a mutant form of this protein is found in 30 percent of all human tumors, scientists are investigating how the Ras protein serves as a "switch" to control when cells develop and grow and how they differentiate from one another--information potentially crucial in the fight against cancer and other diseases.
PNNL scientists also are using computer modeling of proteins found in the membranes of bacteria to discover new methods to fight infections. They currently are developing a computer model of the cell wall of an aggressive bacterium, Pseudomonas aeruginosa, which infects the respiratory systems of cystic fibrosis sufferers. By modeling the cell wall, scientists hope to discover how the membranes and proteins enable the bacterium to elude treatment by traditional antibiotics, potentially leading to new treatment strategies.
New strategies for developing drugs, environmental cleanup, and homeland security measures will be possible through further understanding of complex genome sequences. In the past, genome sequencing required the processing of large sets of data that would take weeks to complete using hundreds or even thousands of processors. PNNL scientists recently developed a new computational tool, Scalablast, which enables large amounts of biological data to be analyzed in manageable fragments on many processors simultaneously, reducing the time needed from weeks to minutes. Scalablast could be used to analyze a microorganism's genome to discover novel genes that allow it to process toxic pollutants, leading to new bioremediation techniques for cleaning up oil spills or removing pollutants from soil or water. It also could be used to further the understanding of bacteria and viruses that might be used as weapons in a terrorist attack, leading to better methods for detection and emergency response.