Literature DB >> 32191470

Rethinking Metadynamics: From Bias Potentials to Probability Distributions.

Michele Invernizzi1,2, Michele Parrinello3,4,5.   

Abstract

Metadynamics is an enhanced sampling method of great popularity, based on the on-the-fly construction of a bias potential that is a function of a selected number of collective variables. We propose here a change in perspective that shifts the focus from the bias to the probability distribution reconstruction while retaining some of the key characteristics of metadynamics, such as flexible on-the-fly adjustments to the free energy estimate. The result is an enhanced sampling method that presents a drastic improvement in convergence speed, especially when dealing with suboptimal and/or multidimensional sets of collective variables. The method is especially robust and easy to use and in fact requires only a few simple parameters to be set, and it has a straightforward reweighting scheme to recover the statistics of the unbiased ensemble. Furthermore, it gives more control of the desired exploration of the phase space since the deposited bias is not allowed to grow indefinitely and it does not push the simulation to uninteresting high free energy regions. We demonstrate the performance of the method in a number of representative examples.

Year:  2020        PMID: 32191470     DOI: 10.1021/acs.jpclett.0c00497

Source DB:  PubMed          Journal:  J Phys Chem Lett        ISSN: 1948-7185            Impact factor:   6.475


  11 in total

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4.  Exploration vs Convergence Speed in Adaptive-Bias Enhanced Sampling.

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Review 5.  Enhanced-Sampling Simulations for the Estimation of Ligand Binding Kinetics: Current Status and Perspective.

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7.  The role of water in host-guest interaction.

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8.  Complete inhibition of a polyol nucleation by a micromolar biopolymer additive.

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Review 9.  Computational methods for exploring protein conformations.

Authors:  Jane R Allison
Journal:  Biochem Soc Trans       Date:  2020-08-28       Impact factor: 5.407

Review 10.  Collective variable-based enhanced sampling and machine learning.

Authors:  Ming Chen
Journal:  Eur Phys J B       Date:  2021-10-20       Impact factor: 1.500

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