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.
For more information, please head over to my research group website.
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.