Algorithms for Complex Network Control and Their Applications for Drug Target Identification from Biomolecular Networks

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Many systems of scientific interests can be modeled as complex networks. The ultimate proof of our understanding of such a complex network is reflected by our ability to steer it from an undesired state to a desired state. On the other hand, it is well acknowledged that a complex disease stems from the malfunction of some complex biomolecular networks that control its pathogenesis. Drugs are essential for steering the biomolecular networks from a disease phenotype (state) to a healthy phenotype (state). A drug target is a biomolecule which is involved in a biomolecular network that controls the pathogenesis of a specific disease and via which states of the network can be changed by combining with suitable drugs. Some drug targets may be more or less efficient than others in biomolecular networks. Identifying the most efficient drug targets is a very early and critical step in the drug design and development process as the costs of late failure are significantly higher than those of early failure in that process. A complex network can be mapped to a dynamic system and thus control issues of the complex network can be studied. As a result, we can view drug targets in a biomolecular network as steering nodes in a controlled dynamic system. By applying control signals (drugs) to steering nodes (drug targets) we desire to steer a malfunctioning biomolecular network from a disease state to a healthy state. We can thus formulate drug target identifications from biomolecular networks as some control issues of dynamic systems. The long-term goal of my proposed research is to develop advanced algorithms for some control issues of complex networks while providing bioinformatics tools for identifying drug targets from biomolecular networks. To achieve my long-term goal, three specific objectives are designed in this proposal. Objective 1: developing algorithms for transittability of complex networks and applying them for identifying drug targets from biomolecular networks; Objective 2: developing algorithms for output controllability/transittability of complex networks and applying them for identifying drug targets from biomolecular networks; and Objective 3: developing optimal control methods for complex networks and applying them for identifying drug targets from biomolecular networks. The successful outcomes of the proposed research will have considerable ramifications for drug target identifications of complex diseases. The proposed research program can foster the multidisciplinary research environment in subjects of computer science, complex network science, control systems, and pharmacology. The proposed research program will also enable effective cross-disciplinary training of high qualified personnel (HQP) in a collaborative research environment to increase knowledge, research skills, and expertise of HQP in multidisciplinary areas of the aforementioned subjects.