2012
DOI: 10.1002/wcms.1099
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Essential dynamics: foundation and applications

Abstract: Collective coordinates, as obtained by a principal component analysis of atomic fluctuations, are commonly used to predict a low-dimensional subspace in which essential protein motion is expected to take place. The definition of such an essential subspace allows to characterize protein functional, and folding, motion, to provide insight into the (free) energy landscape, and to enhance conformational sampling in molecular dynamics simulations. Here, we provide an overview on the topic, giving particular attenti… Show more

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Cited by 107 publications
(119 citation statements)
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References 63 publications
(78 reference statements)
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“…According to essential dynamics (ED) approach (Amadei, Ceruso, & Di Nola, 1999;Amadei, Linssen, & Berendsen, 1993;Chan & Mulet, 1999;Daidone & Amadei, 2012) For the simulations of both tmRBP and ecRBP, only Cα atoms were comprise in the computation of the covariance matrices. The root mean square inner product (RMSIP) was compute to estimate the degree of overlap between the essential subspaces of the two simulated systems at both the same and different temperatures.…”
Section: Essential Dynamics Analysismentioning
confidence: 99%
“…According to essential dynamics (ED) approach (Amadei, Ceruso, & Di Nola, 1999;Amadei, Linssen, & Berendsen, 1993;Chan & Mulet, 1999;Daidone & Amadei, 2012) For the simulations of both tmRBP and ecRBP, only Cα atoms were comprise in the computation of the covariance matrices. The root mean square inner product (RMSIP) was compute to estimate the degree of overlap between the essential subspaces of the two simulated systems at both the same and different temperatures.…”
Section: Essential Dynamics Analysismentioning
confidence: 99%
“…The Principal Component Analysis (PCA) [61] was performed with GROMACS using C α atoms coordinates of snapshots extracted from the production trajectory every 100 ps. The trajectories were then projected onto the PCs associated with the two largest eigenvalues (PC1 and PC2).…”
Section: Analysis Of MD Trajectoriesmentioning
confidence: 99%
“…Such a technique is based on the possibility to guide the sampling towards a target and to reject movements (in the conformational space) which are not in the desired direction. With respect to other enhancing sampling methodologies (for a brief overview on the subject, see for examples the review of Tai (Daidone & Amadei, 2012;Tai, 2004) and references therein), the advantages of the EDS technique are that the system moves along its own essential eigenvectors as provided by free (unbiased) molecular dynamics (MD) and no ad hoc terms are introduced in the Hamiltonian. Moreover, the contraction procedure guarantees -by construction -that the system goes from an initial state to a final state, being only slightly constrained.…”
Section: Introductionmentioning
confidence: 99%