Paul Nerenberg, Ph.D.

Kravis Associate Professor of Integrated Sciences: Computational Science


Kravis Department of Integrated Sciences

Areas of Expertise



I am a computational scientist who uses physics-based simulation methods and machine learning methods to study molecular systems (usually of the biomolecular “flavor”). I am also interested in the development of new molecular dynamics (MD) simulation methodologies and force fields that improve the accuracy and computational efficiency of MD simulations. And last, but not least, I use statistics, machine learning, and mathematical modeling to tackle other challenging problems in a variety of scientific fields.



Ph.D., Massachusetts Institute of Technology

B.S., Johns Hopkins University

Research and Publications

Lee BU, Papoutsis BM, Wong NY, Piacentini J, Kearney C, Huggins NA#, Cruz N#, Ng TT#, Hao KH, Kramer JS, Fenlon EE, Nerenberg PS, Phillips-Piro CM, and Brewer SH. Unraveling Complex Local Protein Environments with 4-Cyano-L-phenylalanine. Journal of Physical Chemistry B 2022; 126:8957-8969.

Stoppelman JP, Ng TT#, Nerenberg PS, and Wang L-P. Development and Validation of AMBER-FB15-compatible Force Field Parameters for Phosphorylated Amino Acids. Journal of Physical Chemistry B 2021; 125:11927-11942.

Leal JA*, Estrada-Tober ZM*, Wade F%, Mendiola AJP, Meza A, Mendoza M, Nerenberg PS, and Zurita-Lopez CI. Phosphoserine Inhibits Neighboring Arginine Methylation in the RKS Motif of Histone H3. Archives of Biochemistry and Biophysics 2021; 698: 108716.

McDonald AR, Nash JA, Nerenberg PS, Ball KA, Sode O, Foley JJ, Windus TL, and Crawford TD. Building Capacity for Undergraduate Education and Training in Computational Molecular Science: A Collaboration between the MERCURY Consortium and the Molecular Sciences Software Institute. International Journal of Quantum Chemistry 2020; 120:e26359.

Menezes GB, Nerenberg PS, Li N, and Allen EL. Results of an Intro to Mechanics Course Designed to Support Student Success in Physics I and Foundational Engineering Courses. ASEE Virtual Conference 2020.

Schauperl M, Nerenberg PS, Jang H, Wang L-P, Bayly CI, Mobley DL, and Gilson MK. Non-bonded Force Field Model with Advanced Restrained Electrostatic Potential Charges (RESP2). Nature Communications Chemistry 2020; 3:44.

Mondays, 2:00-3:00 pm
Tuesdays, 1:45-3:15 pm