Communication: Role of explicit water models in the helix folding/unfolding processes

Palazzesi, Ferruccio; Salvalaglio, Matteo; Barducci, Alessandro; Parrinello, Michele

doi:10.1063/1.4963340

Cited by 7 publications

(5 citation statements)

References 70 publications

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“…In the protein simulations community, it is acknowledged that using implicit solvent or TIP3P water model, which has faster diffusion and lower viscosity than real water, enhances sampling of the protein conformational landscape (Braun et al, 2014 ; Palazzesi et al, 2016 ). What if enzyme structures leverage a similar strategy, by maintaining high (bulk-like) mobility in solvation shell waters around regions where more flexibility is required?…”

Section: Discussionmentioning

confidence: 99%

How Does Solvation Layer Mobility Affect Protein Structural Dynamics?

Dahanayake

Mitchell-Koch

2018

Front. Mol. Biosci.

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Solvation is critical for protein structural dynamics. Spectroscopic studies have indicated relationships between protein and solvent dynamics, and rates of gas binding to heme proteins in aqueous solution were previously observed to depend inversely on solution viscosity. In this work, the solvent-compatible enzyme Candida antarctica lipase B, which functions in aqueous and organic solvents, was modeled using molecular dynamics simulations. Data was obtained for the enzyme in acetonitrile, cyclohexane, n-butanol, and tert-butanol, in addition to water. Protein dynamics and solvation shell dynamics are characterized regionally: for each α-helix, β-sheet, and loop or connector region. Correlations are seen between solvent mobility and protein flexibility. So, does local viscosity explain the relationship between protein structural dynamics and solvation layer dynamics? Halle and Davidovic presented a cogent analysis of data describing the global hydrodynamics of a protein (tumbling in solution) that fits a model in which the protein's interfacial viscosity is higher than that of bulk water's, due to retarded water dynamics in the hydration layer (measured in NMR τ2 reorientation times). Numerous experiments have shown coupling between protein and solvation layer dynamics in site-specific measurements. Our data provides spatially-resolved characterization of solvent shell dynamics, showing correlations between regional solvation layer dynamics and protein dynamics in both aqueous and organic solvents. Correlations between protein flexibility and inverse solvent viscosity (1/η) are considered across several protein regions and for a rather disparate collection of solvents. It is seen that the correlation is consistently higher when local solvent shell dynamics are considered, rather than bulk viscosity. Protein flexibility is seen to correlate best with either the local interfacial viscosity or the ratio of the mobility of an organic solvent in a regional solvation layer relative to hydration dynamics around the same region. Results provide insight into the function of aqueous proteins, while also suggesting a framework for interpreting and predicting enzyme structural dynamics in non-aqueous solvents, based on the mobility of solvents within the solvation layer. We suggest that Kramers' theory may be used in future work to model protein conformational transitions in different solvents by incorporating local viscosity effects.

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Section: Discussionmentioning

confidence: 99%

How Does Solvation Layer Mobility Affect Protein Structural Dynamics?

Dahanayake

Mitchell-Koch

2018

Front. Mol. Biosci.

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“…15, 30 Elements of the transition rate matrix can be computed either from unbiased simulations or from metadynamics, depending on the inherent time scale of the process. 31,32 In the case of unbiased simulations, we apply a lifetime-based estimate 33 of the transition rate from state i to state j: k ij = τ i −1 C ij , in which τ i is the total residence time in state i, and C ij is the total number of transitions from state i to state j. Transitions are accounted for only when the so-called core set of state j is reached. By doing so, we avoid including non-Markovian transitions in our analysis.…”

Section: Methodsmentioning

confidence: 99%

“…where P(t) is the vector with the probabilities of each macrostate at time t, and K is a transition rate matrix which has off-diagonal elements k ij ≥ 0 and diagonal elements k ii = − j =i kji < 0 15,30 . Elements of the transition rate matrix can be computed either from unbiased simulations or from metadynamics, depending on the inherent timescale of the process 31 . In the case of unbiased simulations we apply a lifetime-based estimate 32 of the transition rate from state i to state j: k ij = τ i −1 n ij , in which τ i is the total residence time in state i and n ij is the total number of transitions from state i to state j. Transitions were accounted for only when the so-called core set of state j is reached.…”

Section: B Construction Of a Markov State Modelmentioning

confidence: 99%

Dynamics and Thermodynamics of Ibuprofen Conformational Isomerism at the Crystal/Solution Interface

Marinova

Wood

Marziano

et al. 2018

J. Chem. Theory Comput.

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Conformational flexibility of molecules involved in crystal growth and dissolution is rarely investigated in detail, and usually considered to be negligible in the formulation of mesoscopic models of crystal growth. In this work we set out to investigate the conformational isomerism of ibuprofen as it approaches and is incorporated in the morphologically dominant {100} crystal face, in a range of different solvents -water, 1-butanol, toluene, cyclohexanone, cyclohexane, acetonitrile and trichloromethane. To this end we combine extensive molecular dynamics and well-tempered metadynamics simulations to estimate the equilibrium distribution of conformers, compute conformer-conformer transition rates, and extract the characteristic relaxation time of the conformer population in solution, adsorbed at the solid/liquid interface, incorporated in the crystal in contact with the mother solution, and in the crystal bulk. We find that, while the conformational equilibrium distribution is weakly dependent on the solvent, relaxation times are instead significantly affected by it. Furthermore, differences in the relaxation dynamics are enhanced on the crystal surface, where conformational transitions become slower and specific patways are hindered. This leads to observe that the dominant mechanisms of conformational transition can also change significantly moving from the bulk solution to the crystal interface, even for a small molecule with limited conformational flexibility such as ibuprofen. Our findings suggests that understanding conformational flexibility is key to provide an accurate description of the solid/liquid interface during crystal dissolution and growth, and therefore its relevance should be systematically assessed in the formulation of mesoscopic growth models.

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“…where τ is the scaled time 22 (10) which looks like an ordinary temporal average provided that the time is scaled as in eq 9, and…”

Section: Methodsmentioning

confidence: 99%

“…This is accomplished by periodically adding repulsive Gaussians in such a way that already visited configurations are discouraged from being revisited, and as a result, the CV fluctuations are amplified in a controlled way . Metadynamics has been widely applied in many areas. − Recently, in addition to metadynamics, we have introduced a variationally enhanced sampling (VES) scheme that in many ways can be considered as an offspring of metadynamics. In VES, a functional of the bias is introduced.…”

Section: Introductionmentioning

confidence: 99%

Refining Collective Coordinates and Improving Free Energy Representation in Variational Enhanced Sampling

Yang

Parrinello

2018

J. Chem. Theory Comput.

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Collective variables are used often in many enhanced sampling methods, and their choice is a crucial factor in determining sampling efficiency. However, at times, searching for good collective variables can be challenging. In a recent paper, we combined time-lagged independent component analysis with well-tempered metadynamics in order to obtain improved collective variables from metadynamics runs that use lower quality collective variables [ McCarty, J.; Parrinello, M. J. Chem. Phys. 2017 , 147 , 204109 ]. In this work, we extend these ideas to variationally enhanced sampling. This leads to an efficient scheme that is able to make use of the many advantages of the variational scheme. We apply the method to alanine-3 in water. From an alanine-3 variationally enhanced sampling trajectory in which all the six dihedral angles are biased, we extract much better collective variables able to describe in exquisite detail the protein complex free energy surface in a low dimensional representation. The success of this investigation is helped by a more accurate way of calculating the correlation functions needed in the time-lagged independent component analysis and from the introduction of a new basis set to describe the dihedral angles arrangement.

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Communication: Role of explicit water models in the helix folding/unfolding processes

Cited by 7 publications

References 70 publications

How Does Solvation Layer Mobility Affect Protein Structural Dynamics?

How Does Solvation Layer Mobility Affect Protein Structural Dynamics?

Dynamics and Thermodynamics of Ibuprofen Conformational Isomerism at the Crystal/Solution Interface

Refining Collective Coordinates and Improving Free Energy Representation in Variational Enhanced Sampling

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