Courses Taught
Number | Name | Level |
|---|---|---|
CHEM 4401 | Biochemistry I | Undergraduate |
SCTC 1001 | CST First Year Seminar | Undergraduate |
CHEM 5412 | Structural Bioinformatics II | Graduate |
CHEM 5901 | Responsibility and Ethics in Chemical Research | Graduate |
Selected Publications
Recent
Novack, D., Zhang, S., & Voelz, V.A. (2025). Massively Parallel Free Energy Calculations for In Silico Affinity Maturation of Designed Miniproteins. J Chem Theory Comput, 21(16), 8034-8050. United States. 10.1021/acs.jctc.5c00703
Raddi, R.M., Marshall, T., Ge, Y., & Voelz, V.A. (2025). Model Selection Using Replica Averaging with Bayesian Inference of Conformational Populations. J Chem Theory Comput, 21(12), 5880-5889. United States. 10.1021/acs.jctc.5c00044
Nguyen, T.D., Raddi, R.M., & Voelz, V.A. (2025). High-Resolution Tuning of Non-Natural and Cyclic Peptide Folding Landscapes against NMR Measurements Using Markov Models and Bayesian Inference of Conformational Populations. J Chem Theory Comput, 21(12), 6213-6225. United States. 10.1021/acs.jctc.5c00489
Novack, D., Raddi, R.M., Zhang, S., Hurley, M.F., & Voelz, V.A. (2025). Simple Method to Optimize the Spacing and Number of Alchemical Intermediates in Expanded Ensemble Free Energy Calculations. J Chem Inf Model, 65(12), 6089-6101. United States. 10.1021/acs.jcim.5c00704
Cavender, C.E., Case, D.A., Chen, J.C., Chong, L.T., Keedy, D.A., Lindorff-Larsen, K., Mobley, D.L., Ollila, O.S., Oostenbrink, C., Robustelli, P., Voelz, V.A., Wall, M.E., Wych, D.C., & Gilson, M.K. (2025). Structure-Based Experimental Datasets for Benchmarking Protein Simulation Force Fields [Article v0.1]. ArXiv. United States. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/40196146.
Goold, S.R., Raddi, R.M., & Voelz, V.A. (2025). Expanded ensemble predictions of toluene-water partition coefficients in the SAMPL9 log P challenge. Phys Chem Chem Phys, 27(12), 6005-6013. England. 10.1039/d4cp03621b
Zhang, S., Ge, Y., & Voelz, V.A. (2024). Improved Estimates of Folding Stabilities and Kinetics with Multiensemble Markov Models. Biochemistry, 63(22), 3045-3056. United States. 10.1021/acs.biochem.4c00573
Novack, D., Zhang, S., & Voelz, V.A. (2024). Massively parallel free energy calculations for in silico affinity maturation of designed miniproteins. BioRxiv. United States. 10.1101/2024.05.17.594758
Raddi, R.M. & Voelz, V.A. (2023). Markov State Model of Solvent Features Reveals Water Dynamics in Protein-Peptide Binding. J Phys Chem B, 127(50), 10682-10690. United States. 10.1021/acs.jpcb.3c04775
Hurley, M.F., Raddi, R.M., Pattis, J.G., & Voelz, V.A. (2023). Expanded ensemble predictions of absolute binding free energies in the SAMPL9 host-guest challenge. Phys Chem Chem Phys, 25(47), 32393-32406. England. 10.1039/d3cp02197a
Raddi, R.M., Ge, Y., & Voelz, V.A. (2023). BICePs v2.0: Software for Ensemble Reweighting Using Bayesian Inference of Conformational Populations. J Chem Inf Model, 63(8), 2370-2381. United States. 10.1021/acs.jcim.2c01296
Laye, V.J., Solieva, S., Voelz, V.A., & DasSarma, S. (2022). Effects of Salinity and Temperature on the Flexibility and Function of a Polyextremophilic Enzyme. Int J Mol Sci, 23(24). Switzerland. 10.3390/ijms232415620
Novack, D., Qian, L., Acker, G., Voelz, V.A., & Baxter, R.H. (2022). Oncogenic Mutations in the DNA-Binding Domain of FOXO1 that Disrupt Folding: Quantitative Insights from Experiments and Molecular Simulations. Biochemistry, 61(16), 1669-1682. United States. 10.1021/acs.biochem.2c00224
Ge, Y. & Voelz, V.A. (2022). Estimation of binding rates and affinities from multiensemble Markov models and ligand decoupling. J Chem Phys, 156(13), 134115. United States. 10.1063/5.0088024
Novack, D., Qian, L., Acker, G., Voelz, V.A., & Baxter, R.H. (2022). Oncogenic mutations in the DNA-binding domain of FOXO1 disrupt folding: quantitative insights from experiments and molecular simulations. doi: 10.1101/2022.04.01.486713.
Zhang, S., Hahn, D.F., Shirts, M.R., & Voelz, V.A. (2021). Expanded Ensemble Methods Can be Used to Accurately Predict Protein-Ligand Relative Binding Free Energies. J Chem Theory Comput, 17(10), 6536-6547. United States. 10.1021/acs.jctc.1c00513
Raddi, R.M. & Voelz, V.A. (2021). Stacking Gaussian processes to improve p K a predictions in the SAMPL7 challenge. J Comput Aided Mol Des, 35(9), 953-961. Netherlands. 10.1007/s10822-021-00411-8
Nigam, A., Pollice, R., Hurley, M.F., Hickman, R.J., Aldeghi, M., Yoshikawa, N., Chithrananda, S., Voelz, V.A., & Aspuru-Guzik, A. (2021). Assigning confidence to molecular property prediction. Expert Opin Drug Discov, 16(9), 1009-1023. England. 10.1080/17460441.2021.1925247
Zimmerman, M.I., Porter, J.R., Ward, M.D., Singh, S., Vithani, N., Meller, A., Mallimadugula, U.L., Kuhn, C.E., Borowsky, J.H., Wiewiora, R.P., Hurley, M.F., Harbison, A.M., Fogarty, C.A., Coffland, J.E., Fadda, E., Voelz, V.A., Chodera, J.D., & Bowman, G.R. (2021). SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome. Nat Chem, 13(7), 651-659. England. 10.1038/s41557-021-00707-0
Hurley, M.F., Northrup, J.D., Ge, Y., Schafmeister, C.E., & Voelz, V.A. (2021). Metal Cation-Binding Mechanisms of Q-Proline Peptoid Macrocycles in Solution. J Chem Inf Model, 61(6), 2818-2828. United States. 10.1021/acs.jcim.1c00447
Ge, Y. & Voelz, V. (2021). Estimation of Binding Rates and Affinities from Multiensemble Markov Models and Ligand Decoupling. doi: 10.26434/chemrxiv.14728206.v1.
Raddi, R. & Voelz, V. (2021). Stacking Gaussian Processes to Improve pKa Predictions in the SAMPL7 Challenge. doi: 10.26434/chemrxiv.14650302.v1.
Ge, Y., Zhang, S., Erdelyi, M., & Voelz, V.A. (2021). Solution-State Preorganization of Cyclic β-Hairpin Ligands Determines Binding Mechanism and Affinities for MDM2. J Chem Inf Model, 61(5), 2353-2367. United States. 10.1021/acs.jcim.1c00029
Northrup, J.D., Wiener, J.A., Hurley, M.F., Hou, C.D., Keller, T.M., Baxter, R.H., Zdilla, M.J., Voelz, V.A., & Schafmeister, C.E. (2021). Metal-Binding Q-Proline Macrocycles. J Org Chem, 86(6), 4867-4876. United States. 10.1021/acs.joc.1c00116
Hurley, M., Northrup, J., Ge, Y., Schafmeister, C., & Voelz, V. (2021). Metal Cation-Binding Mechanisms of Q-Proline Peptoid Macrocycles in Solution. doi: 10.26434/chemrxiv.13567853.v1.
Ge, Y. & Voelz, V.A. (2021). Markov State Models to Elucidate Ligand Binding Mechanism. In 10.1007/978-1-0716-1209-5_14
Voelz, V.A., Ge, Y., & Raddi, R.M. (2021). Reconciling Simulations and Experiments With BICePs: A Review. Front Mol Biosci, 8, 661520. Switzerland. 10.3389/fmolb.2021.661520
Sigg, D., Voelz, V.A., & Carnevale, V. (2020). Microcanonical coarse-graining of the kinetic Ising model. J Chem Phys, 152(8), 084104. United States. 10.1063/1.5139228
Wan, H., Ge, Y., Razavi, A., & Voelz, V.A. (2020). Reconciling Simulated Ensembles of Apomyoglobin with Experimental Hydrogen/Deuterium Exchange Data Using Bayesian Inference and Multiensemble Markov State Models. J Chem Theory Comput, 16(2), 1333-1348. United States. 10.1021/acs.jctc.9b01240
Wan, H. & Voelz, V.A. (2020). Adaptive Markov state model estimation using short reseeding trajectories. J Chem Phys, 152(2), 024103. United States. 10.1063/1.5142457