Computational methods in biology have undergone a remarkable transformation over the past several decades to the point where we can now carry out simulations, modeling and analysis of biological interactions on various time and length scales with the expectation of gaining new insights. Traditionally, the connection between computational methods in biology and the actual biology has been driven by experimental observations, in most cases, with the motivation to first establish the veracity of the computations. However, with the growing acceptance of the computations themselves, it is now possible to apply combinations of computational methods as a general, independent, powerful approach to unraveling the hierarchical nature of complex biological interactions.
The Paulaitis lab has adopted this integrative biology approach in applying chemical engineering analytical and computational skills to what has become the most challenging problem in molecular biology and biotechnology: the organization and interpretation of the vast amounts of basic data being generated in the field today from genome sequencing to protein structure determination to the determination of cellular and intercellular processing networks. The goals of my research program are to understand the inherently complex, hierarchical relationships of biological organization and to develop novel approaches to data assimilation and handling, especially as they pertain to protein interactions in aqueous solution and at interfaces, and to the self-assembly and structural organization of biological systems.
Molecular thermodynamics of protein separations
Historically, protein separation and purification process design for pharmaceuticals has been dictated by small production scales, strict regulatory oversight, lower costs for manufacturing relative to the expense of clinical trials and safety evaluations, and the need for rapid process development to prepare for clinical trials. As a result, much of the process design in manufacturing proteins for therapeutic applications has been empirical. As larger-scale applications become more important, the demand for more systematic design approaches has increased. This research focuses on the central role protein interactions play in determining both the thermodynamic properties of protein solutions and the performance of protein separations processes. Our goal is to develop a quantitative molecular thermodynamic basis for designing protein separations comparable to that now routinely applied to conventional chemical engineering separations. Indeed, achieving this goal involves the same components as those that contribute to the design of standard chemical separations:
molecular theories to predict key thermodynamic properties of protein solutions, and thermodynamic models to describe phase behavior and physical properties to predict separation performance for processes, such as protein crystallization and precipitation.
High throughput microarrays for characterizing diverse T-cell populations
Developing quantitative models of the adaptive immune system requires high throughput analytical methods for rapidly scanning and screening diverse cell populations combined with computational methods to interpret the results. In this project, we have molecularly engineered surfaces using novel surface patterning techniques to present on microarray chips ligands that selectively bind to specific receptors on T-cell surfaces. Fabrication of these protein chips is an emerging technology for screening protein-protein interactions with applications in biotechnology, vaccine development, treatment of autoimmune diseases, and the detection of potential agents of bioterrorism. Our focus is on extending current technology to create microarrays for the localization of cells through interactions of their surface receptors with immobilized cognate ligands as a means of characterizing heterogeneous cell populations. Chip development is complemented by the development of several hierarchical computational methods: statistical models of pattern formation on the microarrays, molecular computations/simulations of the binding interactions, and evolution models of clonal expression/proliferation of specific T-cell sub-populations.
Nanoscale engineering of bilaterally accessible biomembrane mimics
Biomembranes are one of the most common structures encountered in living organisms and are indispensable for life functions. The exploitation of their unique properties holds promise for new opportunities in a variety of applications ranging from biosensors to high-speed DNA sequencing. These applications require supporting a lipid bilayer using a monomolecular protein sheet crystal that is reconstituted at the membrane surface. These so-called S-layer proteins are easily isolated, engineered, and recrystallized into monomolecular arrays in suspension and at interfaces. S-layers can thus play a key role as building blocks and patterning elements in nanotechnology. A critical step in this application of S-layer architectures is the use of secondary cell wall polymers (SCWPs) to control S-layer crystallization, and as hydrated cushions to reinforce biological membrane mimics with reconstituted S-layers. To this end, we are applying molecular simulation and modeling of the polymer brush properties of SCWPs to define the design principles for fabricating stratified, hydrated SCWP cushions that can lead to functional, macroscopically stabilized biomembrane mimics.