- Research Overview
- Chemical Biology and Medicinal Chemistry
- Chemical Biology and Medicinal Chemistry Overview
- Discovering Enzyme Substrates and Functions
- Discovering Protein Ligands to Probe and Alter Function
- Discovering Enzyme Activators
- Analyzing Mechanisms of Drug Resistance via Chemical Biology
- Analyzing Enzyme Conformational Dynamics, Substrate Binding, and Catalysis
- Effective Drug Targeting of Pathogens via Medicinal Chemistry
- Computational Chemistry and Biology
- Computational Chemistry and Biology Overview
- Modeling protein regulation via allostery and post-translational modifications
- Visualizing and integrating bioinformatics and biomolecular data
- Modeling membrane permeation to optimize pharmacokinetics
- Determining enzyme function by predicting substrate specificity
- Physical Biology
- Protein and Cellular Engineering
- Protein and Cellular Engineering Overview
- Monitoring enzyme activity and disease biomarkers
- Generating human proteome antibodies via phage display and directed evolution
- Globally analyzing and dissecting apoptosis
- Proximity tagging of protein-protein interactions
- Investigating cellular interactions in tissues
- Creating fluorescent probes targeting the genome and key bio-pathways
- De novo design of catalytic and membrane proteins
- Probing and modulating membrane proteins
Monitoring enzyme activity and disease biomarkers
Examples of our research and methods include
Redesigning enzymes to label cleaved proteins
Department scientists engineer proteins that monitor the activity of many enzymes, but especially proteases, which cleave the peptide bonds that link amino acids in other proteins (proteolysis), irreversibly changing them.
With about 550 types, proteases are the largest class of enzymes performing post-translational modifications in the human proteome. Their activity is vital to health (e.g., food digestion, immune response, blood coagulation) and their dysregulation underlies numerous diseases. A subset of one protease family, caspases, cleaves myriad cell proteins to bring about apoptosis, the normal programmed self-destruction of aberrant cells that fails to occur in cancers.
One approach used by researchers here is to generate antibodies via phage display that selectively bind to specific types of active proteases. The antibodies, in turn, can be linked to fluorescent compounds (immunofluorescence) so that the levels of active target proteases can be quantified by microarray (microchip-based assays).
Department scientists have also rationally redesigned a bacterial enzyme (from subtilisin to subtiligase) so that it selectively and covalently attaches biotin affinity labels to the exposed alpha amines (N-termini) of protein fragments generated by proteolytic cleavage. Thus, the fragments and their parent substrates can be globally affinity-purified, identified, and quantified via mass spectrometry.
Nathan Thomsen, PhD
Such protein-based methods can be used to determine the roles of specific proteases in vital biological pathways as well as to diagnose disease by detecting and quantifying levels of biomarker enzyme activity. The latter can, in turn, help to rapidly determine, at the molecular level, if a given treatment is effective.
Our applications of such protein engineering include
Tracking blood-borne biomarkers
Using the rationally re-designed enzyme subtiligase to label N-terminal peptides from substrates cleaved by apoptotic caspases in three different blood cancer cell types treated with three different cytotoxic drugs. This approach potentially provides cell-type specific biomarkers of drug action and efficacy. In addition, common caspase substrates among different cells and in response to different drugs suggest key apoptotic nodes for further drug targeting.
Ongoing research seeks to develop a quantitative platform to monitor caspase proteolytic output in patients being treated for blood cancers. The hypothesis is that certain cell-type malignancy-specific protein fragments released when cancer cells are driven to apoptosis by chemotherapy will allow for rapid, real-time monitoring of serum biomarkers of a given treatment’s efficacy. Creating antibodies for the proteolytic fragments via phage display would enable high-throughput quantification of such biomarkers.