Dresden 2026 – scientific programme

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BP: Fachverband Biologische Physik

BP 2: Computational Biophysics I

BP 2.5: Talk

Monday, March 9, 2026, 10:30–10:45, BAR/0106

Multi-Scale Computational Framework for Modeling Metabolic Pathways — •Miljan Dašić, Ashwathi Poolamanna, Mehrnoosh Khodam Hazrati, and Štěpán Timr — J. Heyrovský Institute of Physical Chemistry of the Czech Academy of Sciences, Dolejškova 2155/3, 182 00 Prague 8, Czech Republic

Spatial organization of enzymes (clustering, assemblies, and substrate channeling) has been increasingly recognized as a key determinant of metabolic efficiency. Recent studies suggest that non-specific enzyme-substrate interactions and molecular crowding can further impact the performance of metabolic pathways. However, the combined effect of these factors remains insufficiently quantified.

To address this gap, we developed a multi-scale computational framework connecting molecular-level enzyme-substrate interactions with emergent pathway-level kinetics. We first perform extensive coarse-grained Molecular Dynamics (MD) simulations with LAMMPS to quantify substrate transition kinetics at varying crowding levels. Resulting trajectories are analyzed using Markov State Models (MSMs) to extract the relevant states and transition rates. These kinetic parameters are then used to parameterize stochastic Reaction-Diffusion (RD) simulations in Smoldyn, enabling the study of large enzyme assemblies, different reaction orders, and multi-step metabolic pathways.

Our results reveal how molecular interaction strengths, crowding conditions as well as enzyme spatial organization impact pathway efficiency across scales: from nanometers and nanoseconds (MD) to micrometers and seconds (RD).

Keywords: coarse-grained molecular dynamics; stochastic reaction-diffusion simulations; enzymes; substrates; metabolic pathways