Laurie Parker
Professor
University of Minnesota
Talk Information
Computational Empowerment in Peptide Science
18 June 2025, 02:10pm - 02:35pm, in the
L44 – Using Experimental Approaches and AI-Based Structural Modeling to Understand Kinase-Substrate Interactions
Professor Laurie L. Parker serves as a Professor in the Department of Biochemistry, Molecular Biology, and Biophysics at the University of Minnesota. She also holds the position of Associate Dean for Undergraduate Education in the College of Biological Sciences. Her research focuses on developing innovative biosensor technologies to study protein phosphorylation, particularly by tyrosine kinases, with applications in cancer diagnostics and therapeutics.
Academic Background
Dr. Parker earned her Ph.D. in Chemistry from the University of Glasgow. She began her academic career as an Assistant Professor at Purdue University in the Department of Medicinal Chemistry and Molecular Pharmacology. In 2014, she joined the University of Minnesota, where she has taken on various leadership roles, including Director of Graduate Studies for the BMBB Graduate Program and Principal Investigator of the HHMI Pathways to Success Inclusive Excellence grant program.
Research Focus
Professor Parker's laboratory develops cell-permeable peptide biosensors to monitor kinase activity in living cells. By employing chemical biology and proteomics approaches, her team designs assays that can rapidly screen for effective kinase inhibitors and assess their efficacy in cancer treatment. This work aims to enhance personalized medicine strategies by providing real-time insights into cellular signaling pathways.
Notable Contributions
Dr. Parker has significantly advanced the field of chemical proteomics through the development of multiplex-compatible biosensors for various kinases. Her research has led to a better understanding of kinase signaling dynamics and has contributed to the identification of novel therapeutic targets. Additionally, she has been instrumental in promoting inclusive excellence in STEM education through mentorship and program development.
Professional Engagements
Beyond her research, Professor Parker is actively involved in educational leadership and curriculum development. As Associate Dean, she oversees undergraduate education initiatives and works to enhance student engagement and success. She is also committed to fostering diversity, equity, and inclusion within the academic community, implementing programs that support underrepresented students in the sciences.
Through her innovative research and dedication to education, Professor Laurie L. Parker continues to make significant contributions to the fields of chemical biology and higher education.
Using Experimental Approaches and AI-Based Structural Modeling to Understand Kinase-Substrate Interactions
Protein phosphorylation is a crucial post-translational modification in all cells, carried out by kinase enzymes and reversed by phosphatase enzymes. It is regulated by a broad range of factors including protein-ligand and protein-protein interactions, scaffolding, and subcellular localization. Dysregulation of kinase activity leads to cellular abnormalities and disease, and thus kinases are a key target for drug discovery. Kinase inhibitor drug discovery depends on kinase assays, but in many cases, especially for understudied kinases, there is not enough information available about the substrate targets of a kinase to develop optimized assays. Optimization requires efficient substrates, appropriate reaction conditions and accessible detection methods.
The Parker lab employs both experimental and computational approaches to develop substrates and detection methods and implement them in kinase assays. We have established phosphoproteomics-based workflows for identifying substrate preferences and peptide sequences to use in tyrosine kinase and serine/threonine kinase assays. We are also using AI structure-based modeling, AlphaFold, to develop prediction criteria and hypotheses about kinase-substrate peptide interactions. While neither of these approaches, experimental or modeling-based, are ideal on their own for predicting novel kinase substrate peptide sequences or recognition selectivity, when used in combination they are valuable tools to streamline the assay design process. Implementing these approaches has also led us to new, and as-yet unanswered, questions about how kinases recognize peptides differentially to achieve selectivity in terms of reaction rates between similar kinase family members and/or substrate peptide sequences.