Computational Biomolecular Chemistry Group

Table of contents

Research group type
Research group
Core fields of research
Basic natural phenomena and mathematical thinking
Research areas
Computational Science
Nanoscience Center
Department of Chemistry - Research areas
Chemical Nanoscience
Faculty
Faculty of Mathematics and Science
Department
Department of Chemistry

Research group description

Our aim is to understand and ultimately tailor the chemical properties of biomolecular systems. To achieve our goals we develop new strategies to combine advanced molecular dynamics techniques with high-level quantum chemistry approaches. Our developments are made available to other researchers in the molecular dynamics program package Gromacs.

Interaction between biology, physics, and chemistry is presently providing a window into the exciting new era of biotechnology. Enzymes, in particular, that can catalyze chemical reactions with a high efficiency and under very mild conditions, provide valuable templates for artificial devices that we will need to meet the challenges of the 21st century. Mimicking biochemical processes however, requires complete understanding of the underlying molecular dynamics. As the relevant time and spatial resolution are notoriously hard to access experimentally, computer simulations are the methods of choice to deepen our understanding of how proteins have evolved to mediate chemical reactions and to use these insight to create devices that mimic biological function.

Publications

Publication
2025
Available through Open Access
Journal of Chemical Theory and Computation.
Bauman, Nicholas
Cunha, Leonardo A.
DePrince, A. Eugene
Flick, Johannes
Foley, Jonathan J.
Govind, Niranjan
Groenhof, Gerrit
Hoffmann, Norah
Kowalski, Karol
Li, Xiaosong
Liebenthal, Marcus
Maitra, Neepa T.
Manderna, Ruby
Matoušek, Mikuláš
Mazin, Ilia M.
Mejia-Rodriguez, Daniel
Panyala, Ajay
Peng, Bo
Peyton, Benjamin
Veis, Libor
Vu, Nam
Weidman, Jared D.
Wilson, Angela K.
Zarotiadis, Rhiannon A.
Zhang, Yu

Research group