Richard A. Friesner

Richard A. Friesner

Research Interest


The research in my group is focused on the following major areas:

Development and application of novel methods for ab initio electronic structure calculations, including mixed quantum mechanics/molecular mechanics (QM/MM) methods;

Development of a new generation of molecular mechanics force fields, including explicit incorporation of polarizability;

Investigation and improvement of continuum treatments of aqueous solvation;

Computational models and algorithms for protein structure prediction;

Modeling of protein-active site chemistry using quantum chemical and QM/MM methods;

Electron transfer theory; and

Quantum chemical modeling of the interactions of small molecules with surfaces and nanostructures.

Projects typically include a combination of analytical theory, algorithm and software development, and applications of new methods to biology or materials science.

Some highlights of our recent research are as follows:

  • We have developed accurate quantum chemical models for intermediates and transition states of the catalytic cycle of the enzyme methane monooxygenase (MMO). MMO is a bacterial enzyme, containing a di-iron core, that catalyzes the conversion methane and dioxygen into methanol. Our density functional theory (DFT) calculations use approximately 100 atoms to describe the enzyme-active site and are in good agreement with experimentally available structures, energies, spin states, and other observable properties. Inclusion of the second coordination shell around the two metal atoms is essential in understanding how the protein controls the states in the catalytic cycle.
  • We have developed a QM/MM methodology specifically designed to model protein-active sites. The method has been extensively benchmarked against fully quantum chemical data for a series of peptides. We are currently applying the method to a variety of protein-active site modeling problems, including cytochrome P450, beta-lactamases, and penicillin-binding proteins, and reversible oxygen binding in hemerythrin.
  • We have developed an automated methodology for constructing a polarizable force field for arbitrary organic molecules based on ab initio quantum chemical calculations. We have applied this approach to small-molecule gas phase and condensed phase calculations and, more recently, have assembled a complete protein force field.
  • We have entered the most recent protein structure prediction contest (CASP4) and demonstrated considerable success in carrying out fold recognition for homologous proteins with low sequence identity. We are also engaged in obtaining accurate alignments for low sequence identity homologs and in performing high resolution structural refinement for homology modeling.

Shee, J ; Arthur, EJ; Zhang, SW; Reichman, DR; Friesner, RA. Phaseless Auxiliary-Field Quantum Monte Carlo on Graphical Processing Units. Journal Of Chemical Theory And Computation. 14, 8, 4109-4121. (2018) DOI: 10.1021/acs.jctc.8b00342

Abel, R.; Mondal, S.; Masse, C.; Greenwood, J.; Harriman, G.; Ashwell, M.A.; Bhat, S.; Wester, S.; Frye, L.; Kapeller, R.; Friesner, R.A. Accelerating drug discovery through tight integration of expert molecular design and predictive scoring,Current Opinion In Structural Biology (2017) 43, 38-44 DOI: 10.1016/

Clark, AJ; Gindin, T; Zhang, BS; Wang, LL; Abel, R; Murret, CS; Xu, F; Bao, A; Lu, NJ; Zhou, TQ; Kwong, PD.; Shapiro, L.; Honig, B; Friesner RA. Free Energy Perturbation Calculation of Relative Binding Free Energy between Broadly Neutralizing Antibodies and the gp120 Glycoprotein of HIV-1. Journal Of Molecular Biology. 429, 7, 930-947 (2017) DOI: 10.1016/j.jmb.2016.11.021

Jacobson, LD; Bochevarov, AD; Watson, MA; Hughes, TF; Rinaldo, D; Ehrlich, S; Steinbrecher, TB; Vaitheeswaran, S; Philipp, DM; Halls, MD; Friesner, RA. Automated Transition State Search and Its Application to Diverse Types of Organic Reactions. Journal Of Chemical Theory And Computation. 13, 11, 5780-5797 (2017) DOI: 10.1021/acs.jctc.7b00764

Harder, E., D. Wolfgang, J. Maple, S. Wu, M. Rboul, J.Y. Xiang, L. Wang, D. Lupyan, M.K. Dahlgren, J.L. Knight, J.W. Kaus, D.S. Cerutti, G. Krilov, W.L, Jorgensen, R. Abel, R.A. Friesner, OPLS3: A Force Field Providing Broad Coverage of Drug-like Small Molecules and Proteins. Journal Of Chemical Theory And Computation, 12, 1, 281-296 (2016). PMID: 26584231

Murphy, R.B., M.P. Repansky, J.R. Greenwood, I. Tubert-Brohman, S. Jerome, R. Annabhimoju, N.A. Boyles, C.D. Schmitz, R. Abel, R. Farid, R.A. Friesner,  WScore: A Flexible and Accurate Treatment of Explicit Water Molecules in Ligand-Receptor Docking. J. Med. Chem., 59, 9, 4364-4384 (2016).  PMID: 27054459

Clark, A.J., R. Tiwary, K. Borrelli, S. Feng, E.B. Miller, R. Abel, R.A. Friesner, B.J. Berne, Prediction of Protein Ligand Binding Poses via a Combination of Induced Fit Docking and Metadynamics Simulations, J. chem. Theor. Comput. 12, 6, 2990-2998 (2016).  PMID: 27145262

Wang, L., YJ. Wu, Y.Q. Deng, B. Kim, L. Pierce, G. Krilov, D. Lupyan, S. Robinson, M.K. Dahlgren, J. Greenwood, D.L. Romero, C. Masse, J.L. Knight, T. Steinbrecher, T. Beuming, W. Damm, E. Harder, W. Sherman, M. Brewer, R. Wester, M. Murcko, L. Frye, R. Farid, T. Lin, D.L Mobley, W.L. Jorgensen, B.J. Berne, R.A. Friesner, R. Abel, Robert, Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field, J. Am. Chem. Soc., 137, 7, 2695-2703 (2015). PMID: 25625324

Miller, Edward B., Colleen S. Murrett, Kai Zhu, Suwen Zhao, Dahlia A. Goldfeld, Joseph H. Bylund, and Richard A. Friesner, Prediction of Long Loops with Embedded Secondary Structure using the Protein Local Optimization Program, J. Chem. Theo. Comput., 9, 1846-1864 (2013).

Hughes, Thomas F., and Richard A. Friesner, Development of Accurate DFT Methods for Computing Redox Potentials of Transition Metal Complexes:  Results for Model Complexes and Application to Cytochrome P450, J. Chem. Theor. and Comput., 8, 442-459 (2012) DOE