Therapy3 | Main Goals

Organization principles of biochemical networks in health, disease and biotechnology.
This research line will have a strong focus on redox stress and signaling.

Experimentally (collaboration with groups at CNC.IBILI and abroad):
1. Testing predictions 1-4 in Section 9.1.3 (Main achievements).
2. Testing if anticipatory blocking and stress-blocking matching plays a role in neuro-degeneration, aging and chronic inflammation.
3. Applying a synthetic biology platform which we are designing in collaboration with Timothy Lu’s lab (MIT) to quantify the concentrations of reactive chemical species involved in these processes.

1. Exploring the biological scope and evolutionary implications (e.g. prediction 5) of anticipatory blocking and stress-blocking matching through sequence and phylogenetic analyses.
2. Understanding the relationship between design and function in redox signaling. A small network of interacting components that are evolutionarily old, conserved and widespread integrates many functions. How is this accomplished? What are the design principles for effective signaling and integration? Are there specific design vulnerabilities, relevant for disease or exploitable for therapy?
3. Assessing if anticipatory blocking and other aspects of resource allocation to house-keeping activities could be manipulated to either make pathogens more vulnerable to treatment, or “biofactory organisms” more resistant to the stresses of a biochemical reactor. (To be tested experimentally shall results look promising.)

We will collaborate with groups at CNC.IBILI and abroad towards applying our method for profiling S-phase metabolism to clarify if the metabolism of proliferating mammalian cells is also heterogeneous over the mitotic cycle. This would have important implications for cancer metabolism and therapy. Pending on positive results we will work towards extending the method to other stages of the cell cycle and other applications of the same concept.

Modeling the permeation of physiological barriers.
We will improve the mechanistic model for the equilibrium distribution and displacement kinetics of drugs by the blood compartments in order to account for (a) important aspects of the BBB topology and (b) data to be obtained for a tissue-culture model of the human BBB that is being developed by the Stem Cell Biotechnology group. The experimental characterization of the relevant parameters for a large set of pharmacologically active agents by the collaborators at the University of Coimbra will allow the establishment of QSAR for BBB permeation and in this way permit the prediction of the parameters for unknown molecules. The computational skills of the Systems and Computational Biology group are key for optimal experimental design and rational selection of the drugs characterized experimentally, maximizing the value of the work.

Computational tools for biomolecular systems. In support of the activities of the previous two lines, we will focus on:
1. Applying the computational algorithms mentioned in Section 9.1.3 (Main achievements) to improve the performance of molecular dynamics simulations of lipid membranes and the computational tools mentioned below. These algorithms have already been applied to general math functions and equation solving, allowing up to 100-fold acceleration relative to existing software.
2. Improved tools for connecting design of biomolecular reaction networks to performance. We will develop a tool to automatically generate biomolecular circuits that satisfy prescribed performance specifications and mechanistic constraints. This tool will serve as (a) a mechanistic-hypothesis generator, helping identifying potential missing components/interactions in incompletely characterized networks, and (b) a circuit designer which will be able to “invent” potentially very non-intuitive designs for synthetic biology applications.
3. Improved tools for rule-based modeling of complex reaction networks.