Title

Chris A. Kieslich

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Chris A. Kieslich
Title/Position
Assistant Professor
Contact

Contact

UAW 4108Georgia Tech
404-894-9852
Education

Education

  • B.S. Biomedical Engineering, Saint Louis University, 2007
  • Ph.D. Bioengineering, University of California, Riverside, 2012
Research Interests

Research Interests

Dr. Kieslich’s research group, the Biomolecular Systems Modelling and Design Group, develops tools for therapeutic design to accelerate discovery and enable personalized medicine. Our work integrates molecular and systems modeling, AI/machine learning, and global optimization to develop multi-scale models of biomolecular systems, and then leverages these models for the design of novel therapeutics. Our applied research focuses on Immunoengineering and the development of Cancer Technologies, and our current projects include: i) development of tools for accounting for host and pathogen variability in prediction of T-cell epitopes, ii) design of membranolytic anti-cancer peptides, and iii) development of tools for multi-scale simulations of biomolecular self-assembly.

Publications

Publications

JA Torres, CA Kieslich, RJ Pantazes (2025) A Paired Database of Predicted and Experimental Protein Peptide Binding Information. Sci. Data. 12, 1455.
M Fakhraei, CA Kieslich, M Howard (2025) Approximation of anisotropic pair potentials using multivariate interpolation. J. Phys. Chem. B, 129, 6985–6996.
CA Kieslich, F Alimirzaei, H Song, M Do, P Hall (2021) Data-driven prediction of antiviral peptides based on periodicities of amino acid properties. CACE, 50, 2019-2024.
MC Ferrall-Fairbanks, CA Kieslich, MO Platt (2020) Reassessing enzyme kinetics: Considering protease-as-substrate interactions in proteolytic networks. PNAS, 117 (6), 3307-3318.
C Keasar, … (WeFold collaborators – 73 total authors), CA Kieslich, …, D Baker, J Cheng, C Czaplewski, ACB Delbem, CA Floudas, A Kloczkowski, S Ołdziej, M Levitt, H Scheraga, C Seok, J Söding, S Vishveshwara, D Xu, SN Crivelli (2018) An analysis and evaluation of the WeFold collaborative for protein structure prediction in CASP11 and CASP12. Sci. Rep., 8 (1), 9939.