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Combining transition path sampling with data-driven collective variables through a reactivity-biased shooting algorithm
Rare event sampling is a central problem in modern computational chemistry research.
Among the existing methods, transition path sampling (TPS) can generate unbiased …
Among the existing methods, transition path sampling (TPS) can generate unbiased …
Descriptor-Free Collective Variables from Geometric Graph Neural Networks
Enhanced sampling simulations make the computational study of rare events feasible. A
large family of such methods crucially depends on the definition of some collective variables …
large family of such methods crucially depends on the definition of some collective variables …
Host–Guest Binding Free Energies à la Carte: An Automated OneOPES Protocol
Estimating absolute binding free energies from molecular simulations is a key step in
computer-aided drug design pipelines, but the agreement between computational results …
computer-aided drug design pipelines, but the agreement between computational results …
Advanced simulations with PLUMED: OPES and machine learning collective variables
Many biological processes occur on time scales longer than those accessible to molecular
dynamics simulations. Identifying collective variables (CVs) and introducing an external …
dynamics simulations. Identifying collective variables (CVs) and introducing an external …
Learning protein–ligand unbinding pathways via single-parameter community detection
Understanding the dynamics of biomolecular complexes, eg, of protein–ligand (un) binding,
requires the comprehension of paths such systems take between metastable states. In MD …
requires the comprehension of paths such systems take between metastable states. In MD …
A graph neural network-state predictive information bottleneck (GNN-SPIB) approach for learning molecular thermodynamics and kinetics
Molecular dynamics simulations offer detailed insights into atomic motions but face
timescale limitations. Enhanced sampling methods have addressed these challenges but …
timescale limitations. Enhanced sampling methods have addressed these challenges but …
A Mode Evolution Metric to Extract Reaction Coordinates for Biomolecular Conformational Transitions
The complex, multidimensional energy landscape of biomolecules makes the extraction of
suitable, nonintuitive collective variables (CVs) that describe their conformational transitions …
suitable, nonintuitive collective variables (CVs) that describe their conformational transitions …
Long-Range Electrostatics in Serine Proteases: Machine Learning-Driven Reaction Sampling Yields Insights for Enzyme Design
Computational enzyme design is a promising technique for producing novel enzymes for
industrial and clinical needs. A key challenge that this technique faces is to consistently …
industrial and clinical needs. A key challenge that this technique faces is to consistently …
[HTML][HTML] DeepLNE++ leveraging knowledge distillation for accelerated multi-state path-like collective variables
Path-like collective variables (CVs) can be very effective for accurately modeling complex
biomolecular processes in molecular dynamics simulations. Recently, we have introduced …
biomolecular processes in molecular dynamics simulations. Recently, we have introduced …