• Director of the Center for High Performance Computing, College Of Pharmacy
  • Professor, Medicinal Chemistry
  • Adjunct Professor, Biomedical Engineering


  • NRC Research Associate, Biophysical Chemistry, NHLBI, NIH
  • PhD, Pharmaceutical Chemistry, UCSF
  • BA, Chemistry (honors), Middlebury College
  • BA, Mathematics and Computer Science, Middlebury College

Research Interests

The people in our lab use and develop molecular dynamics, free energy simulation, and trajectory analysis methodologies in applications aimed at better understanding biomolecular structure, dynamics and interactions on large scale computational resources. A strong focus of our funded efforts centers on the reliable representation of nucleic acid systems (DNA and RNA) in solution. We can now apply CADD methods and simulation to better understand and design potential new Hepatitis C and COVID-19 therapeutics.

In addition, large efforts are underway to better characterize RNA structure and force fields through simulation of a large number of commonly observed RNA structural motifs and a large variety of NMR and crystal structures. We are also involved with international collaborative efforts to understand DNA structure, for example through the ABC consortium and long simulations of DNA ... Critical to reliable representation of the structure, dynamics and interactions is not only trying to simulate the biomolecules in their native solution environment but to also both critically assess and validate the simulation results with experiment. Our group focuses on both brute-force and enhanced sampling/ensemble-based simulation using available high performance computational resources at the University of Utah ( and elsewhere. With these resources we also are able to expose and overcome limitations in the methods and force fields. Our group also collaborates on a number of design projects with various experimental groups in the College of Pharmacy.

  • R Galindo-Murillo*, L Winkler*, J Ma, F Hanelli, A Fleming, C Burrows, and T Cheatham “Riboflavin Stabilizes Abasic, Oxidized G-Quadruplex Structures”. Biochemistry 61, 265-275 (2022).
  • OD Love, MCP Lima, CH Clark, S Cornillie, SM Roalstad, TE Cheatham III. “Evaluating the accuracy of the AMBER protein force fields in modeling dihydrofolate reductase structures: Misbalance in the conformational arrangements of the flexible loop domains”. J. Biomol. Struct. Dyn. (2022). R Galindo-Murillo and TE Cheatham III. “Transient Hoogsteen Base Pairs Observed in Unbiased Molecular Dynamics Simulations of DNA” J. Phys. Chem. Lett 13, 6283-6287 (2022).
  • T Hacker, P Smith, D Brunson, L Arafune, T Cheatham, and E Deelman. “Building the research innovation workforce: Challenges and recommendations from a virtual workshop to advance the research computing community.” In Practice and Experience in Advanced Research Computing (PEARC '22), July 10–14, 2022, Boston, MA, USA. ACM, New York, NY, USA 7 Pages.
  • T Rajasekaran, G Freestone, R Galindo-Murillo, B Lugato, H Gaus, M Migawa, E Swayze, TE Cheatham, III, P Seth and S Hanessian. “Systematic investigation of tether length and phosphorous configuration in backbone constrained macrocyclic nucleic acids to modulate binding kinetics for RNA”. J. Organic Chem. 88, 3599-3614 (2023).
  • L Winkler, R Galindo-Murillo and TE Cheatham, III. “The structures and dynamics of DNA mini-dumbbells are force field dependent”. J. Chem. Theory Comp. 19, 2198-2212 (2023).
  • L Winkler and TE Cheatham, III. “Benchmarking the Drude polarizable force field using the r(GACC) tetranucleotide.” J. Chem. Info. Modeling 63, 2505-2511 (2023).
  • O Love, R Galindo-Murillo, M Zgarbová, J Šponer, P Jurečka and TE Cheatham, III. “Assessing the Current State of Amber Force Field Modifications for DNA─2023 Edition.” J. Chem. Theory Comput. 19, 4299-4307. (2023)
  • J Cutcher-Gershenfeld, T Middelkoop, D Brunson, T Cheatham, J Fosso Tande, D Jennewein, T Battelle, J Ma, LA Michael, H Neeman and P Schmitz. “Professionalization of Research Computing and Data: An Expanded Agenda” PEARC23 (2023). Won Best Paper in the Workforce Development Track.
  • DA Case, HM Aktulga, K Belfon, DS Cerutti, GA Cisneros, VWD Cruzeiro, N Forouzesh, TJ Giese, AW Gotz, H Gohlke, S Izadi, K Kasavajhala, MC Kaymak, E King, T Kurtzman, TS Lee, P Li, J Liu, T Luchko. R Luo, M Manathinga, MR Machado, HM Nguyen, KA O’Hearn, A Onufriev, F Pan, S Pantano, R Qi, A Rahnamoun, A Risheh, S Schott-Verdugo, A Shajan, J Swails, J Wang, H Wei, X Wu, S Zhang, S Zhao, Q Zu, TE Cheatham, III, DR Roe, A Roitberg, C Simmerling, DM York, MC Nagan and KM Merz, Jr. “AmberTools”. J. Chem Info Modeling (2023) [in press].