Systems biology is an emerging and multi-disciplinary research area that applies mathematical and computational models to analyze large-scale biological data. Systems biology is very promising to understand the mechanisms of drug reactions at the systems level as well as revolutionize the drug discovery process in the pharmaceutical industry, mainly focusing on the three aspects, drug combinations, drug repurposing and predicting drug side effects. My project aims at predicting new targets for old drugs, correlating targets and relating targets with side effects. The side effects of drugs are caused by on-target and off-target effects. Structurally similar drugs will bind to similar protein targets and cause similar side effects. Through data mining, hierarchical clustering and analyzing drug-target network, I have correlated targets based on their drugs similarities. The target similarity correlation provides a list of potential targets to be aware of when designing drugs for one target. I have also related targets with enriched rare side effects and determined new targets for the old drugs. This study combines both ligand-based similarity approach and atomistic modeling (docking) to validate the predictions.
The Side Effects of Small Molecule Drugs: Connecting Network and Atomistic ModelingMaster's Thesis
|Contributor||Jesus A. Izaguirre, Committee Member|
|Contributor||Nitesh Chawla, Committee Chair|
|Contributor||Olaf Wiest, Committee Member|
|Degree Level||Master's Thesis|
|Degree Discipline||Computer Science and Engineering|
|Departments and Units|