Paul Nerenberg, Ph.D.
Department
Areas of Expertise
Biography
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.
Education
Ph.D., Massachusetts Institute of Technology
B.S., Johns Hopkins University
Research and Publications
Risheh A, Rebel A, Nerenberg PS, and Forouzesh N. Calculation of Protein-Ligand Binding Entropies using a Rule-based Molecular Fingerprint. Biophysical Journal 2024; 123:2839-2848.
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.