Our Assets: University of Kansas

University of Kansas

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Technical Expertise

Brian D. Ackley, PhD

Cell adhesion molecules drive neuronal development. The brain is an amazing network of cells connected by axons and dendrites that form the conduits for our thoughts and actions. One of the fundamental questions of neuroscience is to understand how these connections form. As such these cells and their processes must differentiate appropriate partners from inappropriate targets. Neuroscientists have found that molecules outside the cells instruct all the stages of neural development. For example growth factors secreted from other cells instruct nerve cells to adopt the correct fate, diffusible cues inform neurons where potential synaptic partners might be located and cell surface cues can tell them when they have reached their targets. Work in the Ackley Lab seeks to understand the contribution of cell adhesion molecules to the process of neural development, and we use genetics, cell biology and biochemistry to approach to this problem. Using a bioinformatic approach, Ackley has created a list of all of the genes in the C. elegans genome predicted to be secreted into the extracellular space. This list (The Secretome) includes ~10,000 members. To facilitate understanding how each of these may contribute to development he is creating a library of RNAi clones directed against each member of the list. Ultimately this will provide a valuable rescoure to investigators wanting to probe the contribution of secreted molecules to pathways of interest.

Eric Deeds, PhD

A wide variety of processes in the cell depend on the function of large complexes. Dr. Deed’s research focuses on using computational modeling to understand how macromolecular structures assemble from their component parts. His work is aimed at providing fundamental insights into assembly mechanisms with the ultimate goal of developing strategies that could disrupt or enhance the assembly of medically relevant complexes. The results of his work also provide general rules that can be applied in the design and construction of synthetic complexes that will self-assembly efficiently.

In one set of projects, the Deeds group is considering the assembly dynamics of macromolecular structures that contain rings. Many important complexes, such as the proteasome, the chaperone GroEL, and the apoptosome involved in programmed cell death, consist either of single rings or of multiple rings stacked on top of one another. They have characterized some of the challenges that face simple ring-like structures as they assemble, and have discovered mechanisms that complexes could employ to assemble with optimal efficiency. The team is currently extending this work to the study of stacked rings, with a particular focus on complexes for which there is experimental evidence of self-assembly. The predictions of such models are tested through detailed analysis of the solved structures of complexes containing rings or stacked rings.

In a second set of projects, the Deed’s lab is taking a more systems-wide view and are characterizing assembly challenges that arise in the context of large Protein-Protein Interaction (PPI) networks. Assembly processes occur in the context of a large network in which each of the components of a complex may interact with many potential binding partners. By applying rule- and agent-based modeling techniques, the group has recently conducted the first dynamical simulations of complex formation in the context of a large PPI network. Such large complexes do not reliably assemble in these simulations, indicating that specific mechanisms have evolved to deal with assembly challenges that arise in large PPI networks. The team is currently extending this work to understand how cells have evolved to overcome these problems.

Wonpil Im, PhD

The research programs in the Im group focus on the applications of theoretical/computational methods to chemical and physical problems in biology and material science. Specific research interests and projects include 1) development of efficient and reliable tools for membrane protein modeling and studies of insertion, folding, and assembly of membrane proteins/peptides; 2) NMR & X-ray structure refinement of proteins and protein-DNA complexes using implicit solvent models; 3) ion channel activities such as ion permeation, selectivity, and gating at molecular level; 4) membrane fusion with simplified lipid molecules; and 5) theoretical/methodological developments with particular emphasis on implicit solvent models. In addition, the group is involved in developing the biomolecular simulation program CHARMM.

John Karanicolas, PhD

Dr. Karanicolas’ primary goal is to develop structure-based approaches for modulating protein function using small-molecules. He is exploring two parallel paths towards this overarching goal: the first is re-engineering proteins so that a small-molecule can be used to “turn on” function, and the second is identifying small-molecules that naturally complement and occlude a protein surface such that they can be used to “turn off” function.

In select cases, the ability to activate protein function with a pharmacological agent has already helped elucidate details of protein function in living cells. These cases, however, have been limited either by the fact that the strategy must be catered to a particular protein system or by relatively slow kinetics of activation. Karanicolas seeks to develop a very general approach for engineering small-molecule dependent function into proteins in a way that circumvents these problems. The novel strategy for activating protein function is predicated on adapting a well-known technique – chemical rescue – in an entirely new structure-based context.

Meanwhile, the ability to identify a small-molecule to inhibit a particular protein-protein interaction has long represented a promising avenue for therapeutic intervention in a variety of settings. The relative lack of success in this pursuit has led to a collective view that protein interactions represent a challenging therapeutic target. Karanicolas seeks to understand the root cause of these difficulties unlocking the vast potential associated with pharmacological inhibitors of protein interactions, and translate this understanding into new methods for identifying inhibitors with therapeutic potential. He developed a computational structure-based approach for distinguishing between sites that are suitable for small-molecule binding and those that are not.

Christian Ray, PhD

Physiological responses in growing organisms display tradeoffs between cost and benefit. In microbial metabolism, organismal fitness (often characterized by population growth rate) depends on networks of well-balanced metabolic fluxes. In gene regulation and signaling networks, physical limits on information flow play a decisive role in evolution. In either type of network, small-scale molecular mechanisms can have a powerful effect on larger-scale emergent physiology, creating critical transitions that determine cellular phenotypes and thus fitness.

Dr. Ray uses complementary theoretical and experimental methods to understand the relationship between the properties of critical transitions in single cells and evolutionary fitness. He uses mathematical and computational methods to predict cellular dynamics and guide the design of experiments with bacteria. Specifically, he directly measure the relationship between network dynamics and fitness, using either natural networks (such as the well-studied lac operon in E. coli) or synthetic constructs designed to test specific predictions.

Joanna Slusky, PhD

The Slusky lab is cross-disciplinary, bringing together computational biology, protein design, and molecular biology approaches.  The team assess the structural bioinformatics of OMPs and apply the results to de novo OMP protein design and to native OMP manipulation.  OMPs are a ripe target for cancer therapeutics. Mitochondria have recently become a focus of cancer therapies due to the fact that mitochondrial outer membrane permeabilization leads to apoptosis or necrosis. Dr. Slusky explores mitochondrial membrane permeabilization through manipulation of the OMP pores that already exist in the mitochondrial outer membrane. This may have pharmaceutical consequences because tumorigenic mitochondrial membranes can be selectively targeted in themselves as they have been shown to accumulate lipophilic cations.

Beyond this mechanistic understanding, knowledge of the relationship between OMP chemistry and structure will allow new OMPs to be designed for use in vaccines and will facilitate manipulation of native bacterial OMPs for custom tailored drug delivery systems that could shorten bacterial infections.  Outer membrane proteins have been used for the development of vaccines in three distinct ways: as antigens, as adjuvants and as fasteners to conjugate soluble antigens to outer membrane vesicles. Finally, because OMPs are the bacterial import machinery, drugs could be designed in such a way to manipulate OMPs such that those drugs can facilitate their own import into bacteria.

Ilya Vakser, PhD

Dr. Vakser’s research focuses on molecular modeling in the context of structural genomics and bioinformatics. The major goals are to develop approaches to the modeling of protein interactions and to design procedures for reconstruction of the network of connections between proteins in a genome. The number of protein-protein interactions in a genome is significantly larger than the number of individual proteins. Moreover, most protein structures will be models of limited accuracy. Thus the structure-based methods for building this network have to be (a) fast, and (b) insensitive to significant inaccuracies of modeled structures. The precision of these methods may be correlated with the precision of the protein structures – lower for less accurate models and higher for more exact models.

Vakser’s long-term goals are to understand the fundamental principles of protein interaction and to create a structure-based description of genomes. The primary current objectives are: development of methodology for an accurate prediction of the structure of protein complexes, docking in genome-wide databases of modeled protein structures, and development of the integrated environment for docking studies.


KU Gene Mapping: Genotype Mapping and Structural Genomics

  • Genome Sequencing Core lab in Haworth
  • KINBRE Bioinformatics facility in Haworth

KU RNAi: The Natural History museum DNA sequencing lab, the COBRE genomics sequencing lab and the Genomics center have capabilities in this area.

KU Transcriptomics: Gene expression

  • Genome Sequencing Core lab in Haworth
  • KINBRE Bioinformatics facility in Haworth

KU Epigenomics

  • Genome Sequencing Core lab in Haworth
  • KINBRE Bioinformatics facility in Haworth

KU Biostatistics: The CRMDA quantitative psych facility/core fulfills this function.

KU Applied Bioinformatic Core: The molecular graphics core, CRMDA, and Luke Huan’s laboratory make up about a 75% rating.

KU Large Dataset Capabilities: We have large dataset storage and handling capabilities in the Center for Research Computing and with the Research File Storage system.