On the convergence of the conformational coordinates basis set obtained by the essential dynamics analysis of proteins' molecular dynamics simulations

Amadei, Andrea; Ceruso, Marc A.; Nola, Alfredo Di

doi:10.1002/(sici)1097-0134(19990901)36:4<419::aid-prot5>3.3.co;2-l

Cited by 73 publications

(129 citation statements)

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“…To look for large-scale, slow protein motions that might account for slow convergence of the mean energy, we applied principal component analysis (PCA) to the simulated trajectories of the complexes and free ligands. PCA is commonly used to determine the essential dynamics of a simulation [43,44] by reducing the dimensionality of the trajectory motions. Principle components, or PCs, are the eigenvectors obtained from diagonalizing the covariance matrix of a trajectory, and the eigenvector with the largest eigenvalue is the linear combination of Cartesian coordinates that captures the most variance.…”

Section: Principal Component Analysismentioning

confidence: 99%

Protein-Ligand Binding Enthalpies from Near-Millisecond Simulations: Analysis of a Preorganization Paradox

Gilson

2018

Preprint

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Calorimetric studies of protein-ligand binding often yield thermodynamic data that are difficult to explain in physical terms. Today, explicit solvent molecular dynamics simulations are fast enough that we can begin to use them to look for explanations of such thermodynamic puzzles. Additionally, when such simulations generate results that do not agree well with experiment, this may motivate further development of computational methods and force fields. Here, we apply near-millisecond duration simulations to compute and analyze the binding of four peptidic ligands with the Grb2 SH2 domain, focusing on relative binding enthalpies. The ligands fall into matched pairs, which differ only in the presence or absence of a conformationally constraining bond, which preorganizes two of the ligands for binding. Prior experimental work had revealed, unexpectedly, that binding of the constrained ligands is favored enthalpically, rather than entropically, relative to their flexible<br>analogs. However, the present calculations yield the opposite trend. On further analysis, the computed relative binding enthalpies are found to be small balances of much larger underlying differences in the mean energies of structural components, such as the ligand and the binding site residues. As a consequence, the deviations from experiment in the relative binding enthalpies represent small differences between these large numbers. We also computed first order estimates of changes in configurational entropy on binding. These suggest that the more rigid constrained ligands reduce the entropy of binding site residues more than their flexible analogs do. The implications of these calculations for the use of simulations to understand the thermodynamics of molecular recognition, and for the computational analysis of binding thermodynamics, are discussed.

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Section: Principal Component Analysismentioning

confidence: 99%

Protein-Ligand Binding Enthalpies from Near-Millisecond Simulations: Analysis of a Preorganization Paradox

Gilson

2018

Preprint

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“…It has been shown that the neutral replica statistics are approximately canonical (58) and serve as a good reference for testing convergence of the BEMD simulation (56). The low-index PCs, corresponding to the eigenvectors of the covariance matrix with highest eigenvalues, have previously been shown to characterize protein conformational changes on a low-dimensional surface(s) (60)(61)(62)(63)(64). A set of low-index PCs can therefore serve as a good set of reaction coordinates for exploring the protein foldingunfolding transition (65)(66)(67)(68).…”

Section: Metadynamics Simulationsmentioning

confidence: 99%

Equilibrium Ensembles for Insulin Folding from Bias-Exchange Metadynamics

Bansal

Rathore

Goel

2017

Biophysical Journal

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Earliest events in the aggregation process, such as single molecule reconfiguration, are extremely important and the most difficult to characterize in experiments. To this end, we have used well-tempered bias exchange metadynamics simulations to determine the equilibrium ensembles of an insulin molecule under amyloidogenic conditions of low pH and high temperature. A bin-based clustering method that uses statistics accumulated in bias exchange metadynamics trajectories was employed to construct a detailed thermodynamic and kinetic model of insulin folding. The highest lifetime, lowest free-energy ensemble identified consisted of native conformations adopted by a folded insulin monomer in solution, namely, the R-, the R-, and the T-states of insulin. The lowest free-energy structure had a root mean square deviation of only 0.15 nm from native x-ray structure. The second longest-lived metastable state was an unfolded, compact monomer with little similarity to the native structure. We have identified three additional long-lived, metastable states from the bin-based model. We then carried out an exhaustive structural characterization of metastable states on the basis of tertiary contact maps and per-residue accessible surface areas. We have also determined the lowest free-energy path between two longest-lived metastable states and confirm earlier findings of non-two-state folding for insulin through a folding intermediate. The ensemble containing the monomeric intermediate retained 58% of native hydrophobic contacts, however, accompanied by a complete loss of native secondary structure. We have discussed the relative importance of nativelike versus nonnative tertiary contacts for the folding transition. We also provide a simple measure to determine the importance of an individual residue for folding transition. Finally, we have compared and contrasted this intermediate with experimental data obtained in spectroscopic, crystallographic, and calorimetric measurements during early stages of insulin aggregation. We have also determined stability of monomeric insulin by incubation at a very low concentration to isolate protein-protein interaction effects.

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“…5, c and d). However, the DB loop (40)(41)(42)(43)(44)(45)(46)(47)(48) is separated into an additional domain in the ED-CG seven-site model (38-51; Figs. 4 d and 5 d, red).…”

Section: Coarse-grained Models Of Atp-bound G-actinmentioning

confidence: 99%

A Systematic Methodology for Defining Coarse-Grained Sites in Large Biomolecules

Zhang

Noid³

et al. 2008

Biophysical Journal

168

242

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Coarse-grained (CG) models of biomolecules have recently attracted considerable interest because they enable the simulation of complex biological systems on length-scales and timescales that are inaccessible for atomistic molecular dynamics simulation. A CG model is defined by a map that transforms an atomically detailed configuration into a CG configuration. For CG models of relatively small biomolecules or in cases that the CG and all-atom models have similar resolution, the construction of this map is relatively straightforward and can be guided by chemical intuition. However, it is more challenging to construct a CG map when large and complex domains of biomolecules have to be represented by relatively few CG sites. This work introduces a new and systematic methodology called essential dynamics coarse-graining (ED-CG). This approach constructs a CG map of the primary sequence at a chosen resolution for an arbitrarily complex biomolecule. In particular, the resulting ED-CG method variationally determines the CG sites that reflect the essential dynamics characterized by principal component analysis of an atomistic molecular dynamics trajectory. Numerical calculations illustrate this approach for the HIV-1 CA protein dimer and ATP-bound G-actin. Importantly, since the CG sites are constructed from the primary sequence of the biomolecule, the resulting ED-CG model may be better suited to appropriately explore protein conformational space than those from other CG methods at the same degree of resolution.

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On the convergence of the conformational coordinates basis set obtained by the essential dynamics analysis of proteins' molecular dynamics simulations

Cited by 73 publications

References 0 publications

Protein-Ligand Binding Enthalpies from Near-Millisecond Simulations: Analysis of a Preorganization Paradox

Protein-Ligand Binding Enthalpies from Near-Millisecond Simulations: Analysis of a Preorganization Paradox

Equilibrium Ensembles for Insulin Folding from Bias-Exchange Metadynamics

A Systematic Methodology for Defining Coarse-Grained Sites in Large Biomolecules

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