Title:
Improved Methods for Sampling the Configurational Space of Flexible Biomolecules
Improved Methods for Sampling the Configurational Space of Flexible Biomolecules
Time:
04/24 (Sat.) 8 pm PDT, 9 pm MDT, 10 pm CDT, 11 pm EDT
04/25 (Sun.) 5 am CEST, 11 am Taiwan
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04/24 (Sat.) 8 pm PDT, 9 pm MDT, 10 pm CDT, 11 pm EDT
04/25 (Sun.) 5 am CEST, 11 am Taiwan
Time zone conversion tool
Keywords:
Computational biophysics, molecular dynamics, molecular dynamics, free energy calculations, advanced sampling methods, deep learning, biophysics
Computational biophysics, molecular dynamics, molecular dynamics, free energy calculations, advanced sampling methods, deep learning, biophysics
Abstract:
Molecular simulations, including molecular dynamics and Monte Carlo simulations, have been widely used to gain insights into the transformation processes of condensed matter,including phase transitions, chemical reactions, and conformational changes of biomolecules. However, the usefulness of classical molecular simulations is severely restricted by kinetic bottlenecks in systems with a rough free energy surface. Metastable states separated by numerous free energy barriers are far from each other in the phasespace and have no probability overlap, leading to prohibitive computational cost for computational sampling. To address this challenge, various advanced sampling methods have been developed in the past decades. These methods, such as replica exchange,expanded ensemble, and metadynamics, greatly accelerate configurational sampling by either modifying the underlying free energy surface along selected slow degrees of freedom or bridging the gap between metastable states with a series of intermediate states. In this study, we provide an overview of the most commonly used methods. In light of the limitations of the existing methods, we also propose a variation of metadynamics, where alchemical variables can be biased as an allowed collective variable.
Molecular simulations, including molecular dynamics and Monte Carlo simulations, have been widely used to gain insights into the transformation processes of condensed matter,including phase transitions, chemical reactions, and conformational changes of biomolecules. However, the usefulness of classical molecular simulations is severely restricted by kinetic bottlenecks in systems with a rough free energy surface. Metastable states separated by numerous free energy barriers are far from each other in the phasespace and have no probability overlap, leading to prohibitive computational cost for computational sampling. To address this challenge, various advanced sampling methods have been developed in the past decades. These methods, such as replica exchange,expanded ensemble, and metadynamics, greatly accelerate configurational sampling by either modifying the underlying free energy surface along selected slow degrees of freedom or bridging the gap between metastable states with a series of intermediate states. In this study, we provide an overview of the most commonly used methods. In light of the limitations of the existing methods, we also propose a variation of metadynamics, where alchemical variables can be biased as an allowed collective variable.
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