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11 Publications visible to you, out of a total of 11
Temperature-Annealed Boltzmann Generators

Abstract

Not specified

Authors: Henrik Schopmans, Pascal Friederich

Date Published: 2025

Publication Type: Journal

Multiresolution molecular dynamics simulations reveal the interplay between conformational variability and functional interactions in membrane-bound cytochrome 2B4

Abstract (Expand)

Cytochrome P450 2B4 (CYP 2B4) is one of the best characterized CYPs and serves as a key model system for understanding the mechanisms of microsomal class II CYPs, which metabolize most known drugs. The …n drugs. The highly flexible nature of CYP 2B4 is apparent from crystal structures that show the active site with either a wide open or a closed heme binding cavity. Here, we investigated the conformational ensemble of the full-length CYP 2B4 in a phospholipid bilayer, using multiresolution molecular dynamics (MD) simulations. Coarse-grained MD simulations revealed two predominant orientations of CYP 2B4's globular domain with respect to the bilayer. Their refinement by atomistic resolution MD showed adaptation of the enzyme's interaction with the lipid bilayer, leading to open configurations that facilitate ligand access to the heme binding cavity. CAVER analysis of enzyme tunnels, AquaDuct analysis of water routes, and Random Acceleration Molecular Dynamics simulations of ligand dissociation support the conformation-dependent passage of molecules between the active site and the protein surroundings. Furthermore, simulation of the re-entry of the inhibitor bifonazole into the open conformation of CYP 2B4 resulted in binding at a transient hydrophobic pocket within the active site cavity that may play a role in substrate binding or allosteric regulation. Together, these results show how the open conformation of CYP 2B4 facilitates binding of substrates from and release of products to the membrane, whereas the closed conformation prolongs the residence time of substrates or inhibitors and selectively allows the passage of smaller reactants via the solvent and water channels.

Authors: Sungho Bosco Han, Jonathan Teuffel, Goutam Mukherjee, Rebecca C. Wade

Date Published: 1st Oct 2024

Publication Type: Journal

EDITORIAL: Chemical Compound Space Exploration by Multiscale High-Throughput Screening and Machine Learning

Abstract

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Authors: Ganna Gryn’ova, Tristan Bereau, Carolin Müller, Pascal Friederich, Rebecca C. Wade, Ariane Nunes-Alves, Thereza A. Soares, Kenneth Merz

Date Published: 12th Aug 2024

Publication Type: Journal

Non-adiabatic molecular dynamics simulations provide new insights into the exciton transfer in the Fenna–Matthews–Olson complex

Abstract (Expand)

A trajectory surface hopping approach, which uses machine learning to speed up the most time-consuming steps, has been adopted to investigate the exciton transfer in light-harvesting systems. The present … neural networks achieve high accuracy in predicting both Coulomb couplings and excitation energies. The latter are predicted taking into account the environment of the pigments. Direct simulation of exciton dynamics through light-harvesting complexes on significant time scales is usually challenging due to the coupled motion of nuclear and electronic degrees of freedom in these rather large systems containing several relatively large pigments. In the present approach, however, we are able to evaluate a statistically significant number of non-adiabatic molecular dynamics trajectories with respect to exciton delocalization and exciton paths. The formalism is applied to the Fenna–Matthews–Olson complex of green sulfur bacteria, which transfers energy from the light-harvesting chlorosome to the reaction center with astonishing efficiency. The system has been studied experimentally and theoretically for decades. In total, we were able to simulate non-adiabatically more than 30 ns, sampling also the relevant space of parameters within their uncertainty. Our simulations show that the driving force supplied by the energy landscape resulting from electrostatic tuning is sufficient to funnel the energy towards site 3, from where it can be transferred to the reaction center. However, the high efficiency of transfer within a picosecond timescale can be attributed to the rather unusual properties of the BChl a molecules, resulting in very low inner and outer-sphere reorganization energies, not matched by any other organic molecule, e.g., used in organic electronics. A comparison with electron and exciton transfer in organic materials is particularly illuminating, suggesting a mechanism to explain the comparably high transfer efficiency.

Authors: Monja Sokolov, David S. Hoffmann, Philipp M. Dohmen, Mila Krämer, Sebastian Höfener, Ulrich Kleinekathöfer, Marcus Elstner

Date Published: 9th Jul 2024

Publication Type: Journal

Nonadiabatic Simulation of Exciton Dynamics in Organic Semiconductors Using Neural Network-Based Frenkel Hamiltonian and Gradients

Abstract

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Authors: Farhad Ghalami, Philipp M. Dohmen, Mila Krämer, Marcus Elstner, Weiwei Xie

Date Published: 8th Jul 2024

Publication Type: Journal

Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins

Abstract (Expand)

Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. … Here, we present a machine learning model based on graph neural networks for the prediction of energy barriers of HAT reactions in proteins. As input, the model uses exclusively non-optimized structures as obtained from classical simulations. It was trained on more than 17 000 energy barriers calculated using hybrid density functional theory. We built and evaluated the model in the context of HAT in collagen, but we show that the same workflow can easily be applied to HAT reactions in other biological or synthetic polymers. We obtain for relevant reactions (small reaction distances) a model with good predictive power (R2 ∼ 0.9 and mean absolute error of <3 kcal mol−1). As the inference speed is high, this model enables evaluations of dozens of chemical situations within seconds. When combined with molecular dynamics in a kinetic Monte-Carlo scheme, the model paves the way toward reactive simulations.

Authors: Kai Riedmiller, Patrick Reiser, Elizaveta Bobkova, Kiril Maltsev, Ganna Gryn’ova, Pascal Friederich, Frauke Gräter

Date Published: 16th Jan 2024

Publication Type: Journal

PAL – Parallel active learning for machine-learned potentials

Abstract

Not specified

Authors: Chen Zhou, Marlen Neubert, Yuri Koide, Yumeng Zhang, Van-Quan Vuong, Tobias Schlöder, Stefanie Dehnen, Pascal Friederich

Date Published: 2024

Publication Type: Journal

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