From Targets to Disease
Let’s imagine that we have characterized the chemical structure of our molecule (consider it to be an old repurposed key), and we have defined a number of its targets. The next step is to identify which doors the locks may open. While it is desirable to open good doors (i.e., doors that have a positive therapeutic effect) there are also doors that we don’t want to open (i.e., doors harboring adverse events).
This is where a systems biology predictive in silico approach is essential. First, a complex map of protein-to-protein interactions, including signaling pathways, metabolic pathways, physical interactions between proteins, and known mechanisms of action, is created. These maps usually contain thousands of nodes (proteins), these nodes include the known targets and the known mechanisms of action of drugs.
Analysis of the map provides a number of insights, including discovering new therapeutic targets previously not identified; identifying new functions or therapeutic effects related to the known targets; and revealing new functions (new indications) of drugs that have multiple targets (i.e., opening multiple locks).
Map analysis can be facilitated with system biology tools, including mathematical network analysis, artificial intelligence, and genetic algorithms.
Use of systems biology approaches for reprofiling is game-changing for a number of reasons, chiefly that human physiology is complex, blurry, and redundant.
Successful approaches must model and simulate this complexity. In the pharmacological-chemical space, systems biology as applied to drug reprofiling is starting to do just that, and fast and efficient ways to rationally identify and predict the therapeutic performance of already known drugs are the result.