Daria Gusew
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dariagusew.bsky.social
Daria Gusew
@dariagusew.bsky.social
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PhD student in Computational Biophysics at University of Copenhagen with Kresten Lindorff-Larsen | 👩‍💻🧬🎾
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Reposted by Daria Gusew
lindorfflarsen.bsky.social
Integrative modelling of biomolecular dynamics

Time-dependent and -resolved experiments combined with computation provide a view on molecular dynamics beyond that available from static, ensemble-averaged experiments

Review w @dariagusew.bsky.social & Carl G Henning Hansen
doi.org/10.48550/arX...
Figure 1 from the review. Caption: Comparison of a schematic example showing static, time-dependent, and time-resolved experiments illustrated by a protein folding process. (a) A static experiment measuring the observable O$_{\text{exp}}$ is shown, which can be modelled as a distribution of simulated values, O$_{\text{calc}}$, representing a conformational ensemble of folded and unfolded states. (b) Shows a time-dependent experiment, where the equilibrium dynamics of reversible folding gives rise to measured transition times $\tau_1$ and $\tau_2$. These can be modelled as equilibrium dynamics, illustrated by a free energy (FE) surface along a chosen degree of freedom (D.O.F.) (c) A time-resolved experiment probes a non-equilibrium process, where the system begins at $t_{0}$ in the folded state. During the observation time $t$ the protein unfolds until $t_{\text{max}}$. At each time point, a distinct ensemble average, O$_{\text{exp}}$, can be observed, reflecting the proteins changing structure. This evolution can be modelled as distributions of O$_{\text{calc}}$ at each time point. These are shown together with a FE surface.
October 2, 2025 at 7:54 AM
Reposted by Daria Gusew
cecclementi.bsky.social
Our development of machine-learned transferable coarse-grained models in now on Nat Chem! doi.org/10.1038/s415...
I am so proud of my group for this work! Particularly first authors Nick Charron, Klara Bonneau, Aldo Pasos-Trejo, Andrea Guljas.
Navigating protein landscapes with a machine-learned transferable coarse-grained model - Nature Chemistry
The development of a universal protein coarse-grained model has been a long-standing challenge. A coarse-grained model with chemical transferability has now been developed by combining deep-learning m...
doi.org
July 18, 2025 at 10:45 AM