Bias-Deletion Metadynamics Revealing Volume–Rotation Coupling Mechanisms in Metal–Organic Frameworks

Enhanced sampling methods in molecular dynamics simulations often struggle to handle interdependent modes in complex systems. This leads to nonergodic simulations characterized by hysteresis, dependence on initial configurations, and the need for intricate collective variables. We introduce bias-deletion metadynamics, a technique that conditionally deletes biases to enable repeated exploration of transition pathways and systematic refinement of the sampled configurational space. The underlying free-energy surface is accurately recovered by rescaling the resulting probability distribution by the number of repetitions. We benchmark bias-deletion metadynamics on alanine dipeptide, demonstrating its ability to handle recurrent rotational motion where conventional metadynamics can fail. We further show its power by resolving the distinct phases of CAU-13 using only a volume bias, a known challenge for other methods. Finally, by applying this approach to a series of isoreticular metal-organic frameworks (MIL-53(Al), NU-2002, MIL-cub, and NU-2000), we uncover the intricate coupling between linker rotation and framework volume, revealing how linker dimensionality dictates volume-specific rotational preferences.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2026-03-16
DOI
https://doi.org/10.1021/acs.jctc.6c00051
Primary Topic
Metal-Organic Frameworks: Synthesis and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bias-Deletion Metadynamics Revealing Volume–Rotation Coupling Mechanisms in Metal–Organic Frameworks

Konstantin Stracke, J.W. Evans
Journal of Chemical Theory and Computation
Metal-Organic Frameworks: Synthesis and Applications
article

Bias-Deletion Metadynamics Revealing Volume–Rotation Coupling Mechanisms in Metal–Organic Frameworks

Konstantin Stracke, J.W. Evans
article en

Abstract

Enhanced sampling methods in molecular dynamics simulations often struggle to handle interdependent modes in complex systems. This leads to nonergodic simulations characterized by hysteresis, dependence on initial configurations, and the need for intricate collective variables. We introduce bias-deletion metadynamics, a technique that conditionally deletes biases to enable repeated exploration of transition pathways and systematic refinement of the sampled configurational space. The underlying free-energy surface is accurately recovered by rescaling the resulting probability distribution by the number of repetitions. We benchmark bias-deletion metadynamics on alanine dipeptide, demonstrating its ability to handle recurrent rotational motion where conventional metadynamics can fail. We further show its power by resolving the distinct phases of CAU-13 using only a volume bias, a known challenge for other methods. Finally, by applying this approach to a series of isoreticular metal-organic frameworks (MIL-53(Al), NU-2002, MIL-cub, and NU-2000), we uncover the intricate coupling between linker rotation and framework volume, revealing how linker dimensionality dictates volume-specific rotational preferences.

Journal of Chemical Theory and Computation
The University of Adelaide (AU)
Affordable and clean energy
Openalex Percentile: Top 21%
Metal-Organic Frameworks: Synthesis and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Bias-Deletion Metadynamics Revealing Volume–Rotation Coupling Mechanisms in Metal–Organic Frameworks — Konstantin Stracke, J.W. Evans · Journal of Chemical Theory and Computation (2026) | TGRS Research Map | TGRS