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Journal articles on the topic 'Solvation Dynamics - Biological Water'

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Author: Grafiati

Published: 7 September 2023

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1

Cao, Simin, Haoyang Li, Zenan Zhao, Sanjun Zhang, Jinquan Chen, Jianhua Xu, Jay R. Knutson, and Ludwig Brand. "Ultrafast Fluorescence Spectroscopy via Upconversion and Its Applications in Biophysics." Molecules 26, no. 1 (January 3, 2021): 211. http://dx.doi.org/10.3390/molecules26010211.

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In this review, the experimental set-up and functional characteristics of single-wavelength and broad-band femtosecond upconversion spectrophotofluorometers developed in our laboratory are described. We discuss applications of this technique to biophysical problems, such as ultrafast fluorescence quenching and solvation dynamics of tryptophan, peptides, proteins, reduced nicotinamide adenine dinucleotide (NADH), and nucleic acids. In the tryptophan dynamics field, especially for proteins, two types of solvation dynamics on different time scales have been well explored: ~1 ps for bulk water, and tens of picoseconds for “biological water”, a term that combines effects of water and macromolecule dynamics. In addition, some proteins also show quasi-static self-quenching (QSSQ) phenomena. Interestingly, in our more recent work, we also find that similar mixtures of quenching and solvation dynamics occur for the metabolic cofactor NADH. In this review, we add a brief overview of the emerging development of fluorescent RNA aptamers and their potential application to live cell imaging, while noting how ultrafast measurement may speed their optimization.

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2

Ren, Pengyu, Jaehun Chun, Dennis G. Thomas, Michael J. Schnieders, Marcelo Marucho, Jiajing Zhang, and Nathan A. Baker. "Biomolecular electrostatics and solvation: a computational perspective." Quarterly Reviews of Biophysics 45, no. 4 (November 2012): 427–91. http://dx.doi.org/10.1017/s003358351200011x.

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AbstractAn understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

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3

Nandi, Nilashis, Kankan Bhattacharyya, and Biman Bagchi. "Dielectric Relaxation and Solvation Dynamics of Water in Complex Chemical and Biological Systems." Chemical Reviews 100, no. 6 (June 2000): 2013–46. http://dx.doi.org/10.1021/cr980127v.

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4

Trofimov, Yury A., Nikolay A. Krylov, and Roman G. Efremov. "Confined Dynamics of Water in Transmembrane Pore of TRPV1 Ion Channel." International Journal of Molecular Sciences 20, no. 17 (September 1, 2019): 4285. http://dx.doi.org/10.3390/ijms20174285.

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Solvation effects play a key role in chemical and biological processes. The microscopic properties of water near molecular surfaces are radically different from those in the bulk. Furthermore, the behavior of water in confined volumes of a nanometer scale, including transmembrane pores of ion channels, is especially nontrivial. Knowledge at the molecular level of structural and dynamic parameters of water in such systems is necessary to understand the mechanisms of ion channels functioning. In this work, the results of molecular dynamics (MD) simulations of water in the pore and selectivity filter domains of TRPV1 (Transient Receptor Potential Vanilloid type 1) membrane channel are considered. These domains represent nanoscale volumes with strongly amphiphilic walls, where physical behavior of water radically differs from that of free hydration (e.g., at protein interfaces) or in the bulk. Inside the pore and filter domains, water reveals a very heterogeneous spatial distribution and unusual dynamics: It forms compact areas localized near polar groups of particular residues. Residence time of water molecules in such areas is at least 1.5 to 3 times larger than that observed for similar groups at the protein surface. Presumably, these water “blobs” play an important role in the functional activity of TRPV1. In particular, they take part in hydration of the hydrophobic TRPV1 pore by localizing up to six waters near the so-called “lower gate” of the channel and reducing by this way the free energy barrier for ion and water transport. Although the channel is formed by four identical protein subunits, which are symmetrically packed in the initial experimental 3D structure, in the course of MD simulations, hydration of the same amino acid residues of individual subunits may differ significantly. This greatly affects the microscopic picture of the distribution of water in the channel and, potentially, the mechanism of its functioning. Therefore, reconstruction of the full picture of TRPV1 channel solvation requires thorough atomistic simulations and analysis. It is important that the naturally occurring porous volumes, like ion-conducting protein domains, reveal much more sophisticated and fine-tuned regulation of solvation than, e.g., artificially designed carbon nanotubes.

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5

Sasmal, Dibyendu Kumar, Shirsendu Ghosh, Atanu Kumar Das, and Kankan Bhattacharyya. "Solvation Dynamics of Biological Water in a Single Live Cell under a Confocal Microscope." Langmuir 29, no. 7 (February 4, 2013): 2289–98. http://dx.doi.org/10.1021/la3043473.

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6

Karataraki, Georgia, Andreas Sapalidis, Elena Tocci, and Anastasios Gotzias. "Molecular Dynamics of Water Embedded Carbon Nanocones: Surface Waves Observation." Computation 7, no. 3 (September 10, 2019): 50. http://dx.doi.org/10.3390/computation7030050.

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We employed molecular dynamics simulations on the water solvation of conically shaped carbon nanoparticles. We explored the hydrophobic behaviour of the nanoparticles and investigated microscopically the cavitation of water in a conical confinement with different angles. We performed additional molecular dynamics simulations in which the carbon structures do not interact with water as if they were in vacuum. We detected a waving on the surface of the cones that resembles the shape agitations of artificial water channels and biological porins. The surface waves were induced by the pentagonal carbon rings (in an otherwise hexagonal network of carbon rings) concentrated near the apex of the cones. The waves were affected by the curvature gradients on the surface. They were almost undetected for the case of an armchair nanotube. Understanding such nanoscale phenomena is the key to better designed molecular models for membrane systems and nanodevices for energy applications and separation.

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7

Nandi, Nilashis, Kankan Bhattacharyya, and Biman Bagchi. "ChemInform Abstract: Dielectric Relaxation and Solvation Dynamics of Water in Complex Chemical and Biological Systems." ChemInform 31, no. 34 (June 3, 2010): no. http://dx.doi.org/10.1002/chin.200034290.

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8

Pokharel, Sunil, Shyam Prakash Khanal, and N. P. Adhikari. "Solvation free energy of light alkanes in polar and amphiphilic environments." BIBECHANA 16 (November 22, 2018): 92–105. http://dx.doi.org/10.3126/bibechana.v16i0.21136.

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Computer simulations of molecular models are powerful technique that have improved the under- standing of many biochemical phenomena. The method is frequently applied to study the motions of biological macromolecules such as protein and nucleic acids, which can be useful for interpreting the results of certain biophysical experiments. In this work, we have estimated the solvation free energy for light alkane (methane, ethane, propane and n-butane) dissolved in water and methanol respectively over a broad range of temperatures, from 275 K to 375 K, using molecular dynamics simulations. The alkane (methane, ethane, propane and n-butane), and methanol molecules are described by the OPLS-AA (Optimized Potentials for Liquid Simulations-All Atom) potential, while water is modeled by TIP3P (Transferable Intermolecular Potential with 3-Points) model. We have used the free energy perturbation method (Bennett Acceptance Ratio (BAR) method) for the calculation of free energy of solvation. The estimated values of solvation free energy of alkane in the corresponding solvents agree well with the available experimental data.BIBECHANA 16 (2019) 91-104

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9

Brahma, Rupasree, and H. Raghuraman. "Novel insights in linking solvent relaxation dynamics and protein conformations utilizing red edge excitation shift approach." Emerging Topics in Life Sciences 5, no. 1 (January 8, 2021): 89–101. http://dx.doi.org/10.1042/etls20200256.

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Protein hydration dynamics plays an important role in many physiological processes since protein fluctuations, slow solvation, and the dynamics of hydrating water are all intrinsically related. Red edge excitation shift (REES) is a unique and powerful wavelength-selective (i.e. excitation-energy dependent) fluorescence approach that can be used to directly monitor the environment-induced restriction and dynamics around a polar fluorophore in a complex biological system. This review is mainly focused on recent applications of REES and a novel analysis of REES data to monitor the structural dynamics, functionally relevant conformational transitions and to unmask the structural ensembles in proteins. In addition, the novel utility of REES in imaging protein aggregates in a cellular context is discussed. We believe that the enormous potential of REES approach showcased in this review will engage more researchers, particularly from life sciences.

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10

Grotz, Kara K., and Nadine Schwierz. "Magnesium force fields for OPC water with accurate solvation, ion-binding, and water-exchange properties: Successful transfer from SPC/E." Journal of Chemical Physics 156, no. 11 (March 21, 2022): 114501. http://dx.doi.org/10.1063/5.0087292.

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Magnesium plays a vital role in a large variety of biological processes. To model such processes by molecular dynamics simulations, researchers rely on accurate force field parameters for Mg2+ and water. OPC is one of the most promising water models yielding an improved description of biomolecules in water. The aim of this work is to provide force field parameters for Mg2+ that lead to accurate simulation results in combination with OPC water. Using 12 different Mg2+ parameter sets that were previously optimized with different water models, we systematically assess the transferability to OPC based on a large variety of experimental properties. The results show that the Mg2+ parameters for SPC/E are transferable to OPC and closely reproduce the experimental solvation free energy, radius of the first hydration shell, coordination number, activity derivative, and binding affinity toward the phosphate oxygens on RNA. Two optimal parameter sets are presented: MicroMg yields water exchange in OPC on the microsecond timescale in agreement with experiments. NanoMg yields accelerated exchange on the nanosecond timescale and facilitates the direct observation of ion binding events for enhanced sampling purposes.

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11

Batabyal, Subrata, Susobhan Choudhury, Dilip Sao, Tanumoy Mondol, and Samir Kumar Pal. "Dynamical perspective of protein-DNA interaction." BioMolecular Concepts 5, no. 1 (March 1, 2014): 21–43. http://dx.doi.org/10.1515/bmc-2013-0037.

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AbstractThe interactions between protein-DNA are essential for various biological activities. In this review, we provide an overview of protein-DNA interactions that emphasizes the importance of dynamical aspects. We divide protein-DNA interactions into two categories: nonspecific and specific and both the categories would be discussed highlighting some of our relevant work. In the case of nonspecific protein-DNA interaction, solvation studies (picosecond and femtosecond-resolved) explore the role environmental dynamics and change in the micropolarity around DNA molecules upon complexation with histone protein (H1). While exploring the specific protein-DNA interaction at λ-repressor-operator sites interaction, particularly OR1 and OR2, it was observed that the interfacial water dynamics is minimally perturbed upon interaction with DNA, suggesting the labile interface in the protein-DNA complex. Förster resonance energy transfer (FRET) study revealed that the structure of the protein is more compact in repressor-OR2 complex than in the repressor-OR1 complex. Fluorescence anisotropy studies indicated enhanced flexibility of the C-terminal domain of the repressor at fast timescales after complex formation with OR1. The enhanced flexibility and different conformation of the C-terminal domain of the repressor upon complexation with OR1 DNA compared to OR2 DNA were found to have pronounced effect on the rate of photoinduced electron transfer.

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12

Warshel, Arieh, and William W. Parson. "Dynamics of biochemical and biophysical reactions: insight from computer simulations." Quarterly Reviews of Biophysics 34, no. 4 (November 2001): 563–679. http://dx.doi.org/10.1017/s0033583501003730.

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1. Introduction 5632. Obtaining rate constants from molecular-dynamics simulations 5642.1 General relationships between quantum electronic structures and reaction rates 5642.2 The transition-state theory (TST) 5692.3 The transmission coefficient 5723. Simulating biological electron-transfer reactions 5753.1 Semi-classical surface-hopping and the Marcus equation 5753.2 Treating quantum mechanical nuclear tunneling by the dispersed-polaron/spin-boson method 5803.3 Density-matrix treatments 5833.4 Charge separation in photosynthetic bacterial reaction centers 5844. Light-induced photoisomerizations in rhodopsin and bacteriorhodopsin 5965. Energetics and dynamics of enzyme reactions 6145.1 The empirical-valence-bond treatment and free-energy perturbation methods 6145.2 Activation energies are decreased in enzymes relative to solution, often by electrostatic effects that stabilize the transition state 6205.3 Entropic effects in enzyme catalysis 6275.4 What is meant by dynamical contributions to catalysis? 6345.5 Transmission coefficients are similar for corresponding reactions in enzymes and water 6365.6 Non-equilibrium solvation effects contribute to catalysis mainly through Δg[Dagger], not the transmission coefficient 6415.7 Vibrationally assisted nuclear tunneling in enzyme catalysis 6485.8 Diffusive processes in enzyme reactions and transmembrane channels 6516. Concluding remarks 6587. Acknowledgements 6588. References 658Obtaining a detailed understanding of the dynamics of a biochemical reaction is a formidable challenge. Indeed, it might appear at first sight that reactions in proteins are too complex to analyze microscopically. At room temperature, even a relatively small protein can have as many as 1034 accessible conformational states (Dill, 1985). In many cases, however, we have detailed structural information about the active site of an enzyme, whereas such information is missing for corresponding chemical systems in solution. The atomic coordinates of the chromophore in bacteriorhodopsin, for example, are known to a resolution of 1–2 Å. In addition, experimental studies of biological processes such as photoisomerization and electron transfer have provided a wealth of detailed information that eventually may make some of these processes classical problems in chemical physics as well as biology.

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13

Stumpe, Martin C., Nikolay Blinov, David Wishart, Andriy Kovalenko, and Vijay S. Pande. "Calculation of Local Water Densities in Biological Systems: A Comparison of Molecular Dynamics Simulations and the 3D-RISM-KH Molecular Theory of Solvation." Journal of Physical Chemistry B 115, no. 2 (January 20, 2011): 319–28. http://dx.doi.org/10.1021/jp102587q.

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14

Schrader, Alex M., Stephen H. Donaldson, Jinsuk Song, Chi-Yuan Cheng, Dong Woog Lee, Songi Han, and Jacob N. Israelachvili. "Correlating steric hydration forces with water dynamics through surface force and diffusion NMR measurements in a lipid–DMSO–H2O system." Proceedings of the National Academy of Sciences 112, no. 34 (August 10, 2015): 10708–13. http://dx.doi.org/10.1073/pnas.1512325112.

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Dimethyl sulfoxide (DMSO) is a common solvent and biological additive possessing well-known utility in cellular cryoprotection and lipid membrane permeabilization, but the governing mechanisms at membrane interfaces remain poorly understood. Many studies have focused on DMSO–lipid interactions and the subsequent effects on membrane-phase behavior, but explanations often rely on qualitative notions of DMSO-induced dehydration of lipid head groups. In this work, surface forces measurements between gel-phase dipalmitoylphosphatidylcholine membranes in DMSO–water mixtures quantify the hydration- and solvation-length scales with angstrom resolution as a function of DMSO concentration from 0 mol% to 20 mol%. DMSO causes a drastic decrease in the range of the steric hydration repulsion, leading to an increase in adhesion at a much-reduced intermembrane distance. Pulsed field gradient NMR of the phosphatidylcholine (PC) head group analogs, dimethyl phosphate and tetramethylammonium ions, shows that the ion hydrodynamic radius decreases with increasing DMSO concentration up to 10 mol% DMSO. The complementary measurements indicate that, at concentrations below 10 mol%, the primary effect of DMSO is to decrease the solvated volume of the PC head group and that, from 10 mol% to 20 mol%, DMSO acts to gradually collapse head groups down onto the surface and suppress their thermal motion. This work shows a connection between surface forces, head group conformation and dynamics, and surface water diffusion, with important implications for soft matter and colloidal systems.

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15

Mchedlov-Petrossyan, Nikolay O., Nika N. Kriklya, Anna N. Laguta, and Eiji Ōsawa. "Stability of Detonation Nanodiamond Colloid with Respect to Inorganic Electrolytes and Anionic Surfactants and Solvation of the Particles Surface in DMSO–H2O Organo-Hydrosols." Liquids 2, no. 3 (August 22, 2022): 196–209. http://dx.doi.org/10.3390/liquids2030013.

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In this article, the stability of sols of detonated nanodiamonds, DND, with positively charged colloidal particles, is studied in different salt solutions in water–dimethyl sulfoxide (DMSO) binary systems containing 95 vol.% organic solvent. Additionally, several CCC values are determined in 95 vol.% acetonitrile for comparison. The critical coagulation concentrations (CCC) are determined using the dynamic light scattering technique and the Fuchs function. As coagulators, NaCl, NaBr, NaNO3, NaClO4, Nan-C8H17SO3, and Nan-C12H25OSO3 are used. Comparison of the CCC values in DMSO–H2O and CH3CN–H2O with those obtained in water allows us to make some conclusions. The variations of these values in different solvents are explained in terms of good and poor interfacial solvation of colloidal particles, “structural” contribution to the interparticle interaction energy, lyotropic series for anions, and more or less pronounced adsorption of surfactants. The study of the stability of DND hydrosol in solutions of anionic surfactants with different hydrocarbon tail length demonstrated the crucial role of adsorption in the coagulation process.

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16

Dzubiella, Joachim. "Explicit and implicit modeling of nanobubbles in hydrophobic confinement." Anais da Academia Brasileira de Ciências 82, no. 1 (March 2010): 3–12. http://dx.doi.org/10.1590/s0001-37652010000100002.

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Water at normal conditions is a fluid thermodynamically close to the liquid-vapor phase coexistence and features a large surface tension. This combination can lead to interesting capillary phenomena on microscopic scales. Explicit water molecular dynamics (MD) computer simulations of hydrophobic solutes, for instance, give evidence of capillary evaporation on nanometer scales, i.e., the formation of nanometer-sized vapor bubbles (nanobubbles) between confining hydrophobic surfaces. This phenomenon has been exemplified for solutes with varying complexity, e.g., paraffin plates, coarse-grained homopolymers, biological and solid-state channels, and atomistically resolved proteins. It has been argued that nanobubbles strongly impact interactions in nanofluidic devices, translocation processes, and even in protein stability, function, and folding. As large-scale MD simulations are computationally expensive, the efficient multiscale modeling of nanobubbles and the prediction of their stability poses a formidable task to the'nanophysical' community. Recently, we have presented a conceptually novel and versatile implicit solvent model, namely, the variational implicit solvent model (VISM), which is based on a geometric energy functional. As reviewed here, first solvation studies of simple hydrophobic solutes using VISM coupled with the numerical level-set scheme show promising results, and, in particular, capture nanobubble formation and its subtle competition to local energetic potentials in hydrophobic confinement.

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17

Roux, Benoît, Toby Allen, Simon Bernèche, and Wonpil Im. "Theoretical and computational models of biological ion channels." Quarterly Reviews of Biophysics 37, no. 1 (February 2004): 15–103. http://dx.doi.org/10.1017/s0033583504003968.

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1. Introduction 172. Dynamics of many-body systems 192.1 Effective dynamics of reduced systems 212.2 The constraint of thermodynamic equilibrium 242.3 Mean-field theories 253. Solvation free energy and electrostatics 273.1 Microscopic view of the Born model 273.2 Ion–Ion interactions in bulk solution 293.3 Continuum electrostatics and the PB equation 293.4 Limitations of continuum dielectric models 323.5 The dielectric barrier 333.6 The transmembrane potential and the PB-V equation 354. Statistical mechanical equilibrium theory 404.1 Multi-ion PMF 404.2 Equilibrium probabilities of occupancy 434.3 Coupling to the membrane potential 444.4 Ionic selectivity 484.5 Reduction to a one-dimensional (1D) free-energy profile 495. From MD toI–V: a practical guide 505.1 Extracting the essential ingredients from MD 515.1.1 Channel conductance from equilibrium and non-equilibrium MD 515.1.2 PMF techniques 525.1.3 Friction and diffusion coefficient techniques 535.1.4 About computational times 555.2 Ion permeation models 565.2.1 The 1D-NP electrodiffusion theory 565.2.2 Discrete-state Markov chains 575.2.3 The GCMC/BD algorithm 585.2.4 PNP electrodiffusion theory 626. Computational studies of ion channels 636.1 Computational studies of gA 656.1.1 Free-energy surface for K+ permeation 666.1.2 Mean-force decomposition 696.1.3 Cation-binding sites 696.1.4 Channel conductance 706.1.5 Selectivity 726.2 Computational studies of KcsA 726.2.1 Multi-ion free-energy surface and cation-binding sites 736.2.2 Channel conductance 746.2.3 Mechanism of ion conduction 776.2.4 Selectivity 786.3 Computational studies of OmpF 796.3.1 The need to compare the different level of approximations 796.3.2 Equilibrium protein fluctuations and ion distribution 806.3.3 Non-equilibrium ion fluxes 806.3.4 Reversal potential and selectivity 846.4 Successes and limitations 876.4.1 Channel structure 876.4.2 Ion-binding sites 876.4.3 Ion conduction 886.4.4 Ion selectivity 897. Conclusion 908. Acknowledgments 939. References 93The goal of this review is to establish a broad and rigorous theoretical framework to describe ion permeation through biological channels. This framework is developed in the context of atomic models on the basis of the statistical mechanical projection-operator formalism of Mori and Zwanzig. The review is divided into two main parts. The first part introduces the fundamental concepts needed to construct a hierarchy of dynamical models at different level of approximation. In particular, the potential of mean force (PMF) as a configuration-dependent free energy is introduced, and its significance concerning equilibrium and non-equilibrium phenomena is discussed. In addition, fundamental aspects of membrane electrostatics, with a particular emphasis on the influence of the transmembrane potential, as well as important computational techniques for extracting essential information from all-atom molecular dynamics (MD) simulations are described and discussed. The first part of the review provides a theoretical formalism to ‘translate’ the information from the atomic structure into the familiar language of phenomenological models of ion permeation. The second part is aimed at reviewing and contrasting results obtained in recent computational studies of three very different channels; the gramicidin A (gA) channel, which is a narrow one-ion pore (at moderate concentration), the KcsA channel from Streptomyces lividans, which is a narrow multi-ion pore, and the outer membrane matrix porin F (OmpF) from Escherichia coli, which is a trimer of three β-barrel subunits each forming wide aqueous multi-ion pores. Comparison with experiments demonstrates that current computational models are approaching semi-quantitative accuracy and are able to provide significant insight into the microscopic mechanisms of ion conduction and selectivity. We conclude that all-atom MD with explicit water molecules can represent important structural features of complex biological channels accurately, including such features as the location of ion-binding sites along the permeation pathway. We finally discuss the broader issue of the validity of ion permeation models and an outlook to the future.

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BYKHOVSKI, ALEXEI, TATIANA GLOBUS, TATYANA KHROMOVA, BORIS GELMONT, and DWIGHT WOOLARD. "AN ANALYSIS OF THE THZ FREQUENCY SIGNATURES IN THE CELLULAR COMPONENTS OF BIOLOGICAL AGENTS." International Journal of High Speed Electronics and Systems 17, no. 02 (June 2007): 225–37. http://dx.doi.org/10.1142/s012915640700445x.

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The development of an effective biological (bio) agent detection capability based upon terahertz (THz) frequency absorption spectra will require insight into how the constituent cellular components contribute to the overall THz signature. In this work, the specific contribution of ribonucleic acid (RNA) to THz spectra is analyzed in detail. Previously, it has only been possible to simulate partial fragments of the RNA (or DNA) structures due to the excessive computational demands. For the first time, the molecular structure of the entire transfer RNA (tRNA) molecule of E. coli was simulated and the associated THz signature was derived theoretically. The tRNA that binds amino acid tyrosine (tRNAtyr) was studied. Here, the molecular structure was optimized using the potential energy minimization and molecular dynamical (MD) simulations. Solvation effects (water molecules) were also included explicitly in the MD simulations. To verify that realistic molecular signatures were simulated, a parallel experimental study of tRNAs of E. coli was also conducted. Two very similar molecules, valine and tyrosine tRNA were investigated experimentally. Samples were prepared in the form of water solutions with the concentrations in the range 0.01-1 mg/ml. A strong correlation of the measured THz signatures associated with valine tRNA and tyrosine tRNA was observed. These findings are consistent with the structural similarity of the two tRNAs. The calculated THz signature of the tyrosine tRNA of E. coli reproduces many features of our measured spectra, and, therefore, provides valuable new insights into bio-agent detection.

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Fingerhut, Benjamin P., Jakob Schauss, Achintya Kundu, and Thomas Elsaesser. "Aqueous Contact Ion Pairs of Phosphate Groups with Na+, Ca2+ and Mg2+ – Structural Discrimination by Femtosecond Infrared Spectroscopy and Molecular Dynamics Simulations." Zeitschrift für Physikalische Chemie 234, no. 7-9 (August 27, 2020): 1453–74. http://dx.doi.org/10.1515/zpch-2020-1614.

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AbstractThe extent of contact and solvent shared ion pairs of phosphate groups with Na+, Ca2+ and Mg2+ ions in aqueous environment and their relevance for the stability of polyanionic DNA and RNA structures is highly debated. Employing the asymmetric phosphate stretching vibration of dimethyl phosphate (DMP), a model system of the sugar-phosphate backbone of DNA and RNA, we present linear infrared, femtosecond infrared pump-probe and absorptive 2D-IR spectra that report on contact ion pair formation via the presence of blue shifted spectral signatures. Compared to the linear infrared spectra, the nonlinear spectra reveal contact ion pairs with increased sensitivity because the spectra accentuate differences in peak frequency, transition dipole moment strength, and excited state lifetime. The experimental results are corroborated by long time scale MD simulations, benchmarked by density functional simulations on phosphate-ion-water clusters. The microscopic interpretation reveals subtle structural differences of ion pairs formed by the phosphate group and the ions Na+, Ca2+ and Mg2+. Intricate properties of the solvation shell around the phosphate group and the ion are essential to explain the experimental observations. The present work addresses a challenging to probe topic with the help of a model system and establishes new experimental data of contact ion pair formation, thereby underlining the potential of nonlinear 2D-IR spectroscopy as an analytical probe of phosphate-ion interactions in complex biological systems.

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Ahmed, Mustapha Carab, Elena Papaleo, and Kresten Lindorff-Larsen. "How well do force fields capture the strength of salt bridges in proteins?" PeerJ 6 (June 11, 2018): e4967. http://dx.doi.org/10.7717/peerj.4967.

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Salt bridges form between pairs of ionisable residues in close proximity and are important interactions in proteins. While salt bridges are known to be important both for protein stability, recognition and regulation, we still do not have fully accurate predictive models to assess the energetic contributions of salt bridges. Molecular dynamics simulation is one technique that may be used study the complex relationship between structure, solvation and energetics of salt bridges, but the accuracy of such simulations depends on the force field used. We have used NMR data on the B1 domain of protein G (GB1) to benchmark molecular dynamics simulations. Using enhanced sampling simulations, we calculated the free energy of forming a salt bridge for three possible lysine-carboxylate ionic interactions in GB1. The NMR experiments showed that these interactions are either not formed, or only very weakly formed, in solution. In contrast, we show that the stability of the salt bridges is overestimated, to different extents, in simulations of GB1 using seven out of eight commonly used combinations of fixed charge force fields and water models. We also find that the Amber ff15ipq force field gives rise to weaker salt bridges in good agreement with the NMR experiments. We conclude that many force fields appear to overstabilize these ionic interactions, and that further work may be needed to refine our ability to model quantitatively the stability of salt bridges through simulations. We also suggest that comparisons between NMR experiments and simulations will play a crucial role in furthering our understanding of this important interaction.

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Parkin, Dan, and Mitsunori Takano. "The Intrinsic Radius as a Key Parameter in the Generalized Born Model to Adjust Protein-Protein Electrostatic Interaction." International Journal of Molecular Sciences 24, no. 5 (February 28, 2023): 4700. http://dx.doi.org/10.3390/ijms24054700.

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The generalized Born (GB) model is an extension of the continuum dielectric theory of Born solvation energy and is a powerful method for accelerating the molecular dynamic (MD) simulations of charged biological molecules in water. While the effective dielectric constant of water that varies as a function of the separation distance between solute molecules is incorporated into the GB model, adjustment of the parameters is indispensable for accurate calculation of the Coulomb (electrostatic) energy. One of the key parameters is the lower limit of the spatial integral of the energy density of the electric field around a charged atom, known as the intrinsic radius ρ. Although ad hoc adjustment of ρ has been conducted to improve the Coulombic (ionic) bond stability, the physical mechanism by which ρ affects the Coulomb energy remains unclear. Via energetic analysis of three differently sized systems, here, we clarify that the Coulomb bond stability increases with increasing ρ and that the increased stability is caused by the interaction energy term, not by the self-energy (desolvation energy) term, as was supposed previously. Our results suggest that the use of larger values for the intrinsic radii of hydrogen and oxygen atoms, together with the use of a relatively small value for the spatial integration cutoff in the GB model, can better reproduce the Coulombic attraction between protein molecules.

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Leckband, Deborah, and Jacob Israelachvili. "Intermolecular forces in biology." Quarterly Reviews of Biophysics 34, no. 2 (May 2001): 105–267. http://dx.doi.org/10.1017/s0033583501003687.

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0. Abbreviations 1061. Introduction: overview of forces in biology 1081.1 Subtleties of biological forces and interactions 1081.2 Specific and non-specific forces and interactions 1131.3 van der Waals (VDW) forces 1141.4 Electrostatic and ’double-layer‘ forces (DLVO theory) 1221.4.1 Electrostatic and double-layer interactions at very small separation 1261.5 Hydration and hydrophobic forces (structural forces in water) 1311.6 Steric, bridging and depletion forces (polymer-mediated and tethering forces) 1371.7 Thermal fluctuation forces: entropic protrusion and undulation forces 1421.8 Comparison of the magnitudes of the major non-specific forces 1461.9 Bio-recognition 1461.10 Equilibrium and non-equilibrium forces and interactions 1501.10.1 Multiple bonds in parallel 1531.10.2 Multiple bonds in series 1552. Experimental techniques for measuring forces between biological molecules and surfaces 1562.1 Different force-measuring techniques 1562.2 Measuring forces between surfaces 1612.3 Measuring force–distance functions, F(D) 1612.4 Relating the forces between different geometries: the ‘Derjaguin Approximation’ 1622.5 Adhesion forces and energies 1642.5.1 An example of the application of adhesion mechanics of biological adhesion 1662.6 Measuring forces between macroscopic surfaces: the surface forces apparatus (SFA) 1672.7 The atomic force microscope (AFM) and microfiber cantilever (MC) techniques 1732.8 Micropipette aspiration (MPA) and the bioforce probe (BFP) 1772.9 Osmotic stress (OS) and osmotic pressure (OP) techniques 1792.10 Optical trapping and the optical tweezers (OT) 1812.11 Other optical microscopy techniques: TIRM and RICM 1842.12 Shear flow detachment (SFD) measurements 1872.13 Cell locomotion on elastically deformable substrates 1893. Measurements of equilibrium (time-independent) interactions 1913.1 Long-range VDW and electrostatic forces (the two DVLO forces) between biosurfaces 1913.2 Repulsive short-range steric–hydration forces 1973.3 Adhesion forces due to VDW forces and electrostatic complementarity 2003.4 Attractive forces between surfaces due to hydrophobic interactions: membrane adhesion and fusion 2093.4.1 Hydrophobic interactions at the nano- and sub-molecular levels 2113.4.2 Hydrophobic interactions and membrane fusion 2123.5 Attractive depletion forces 2133.6 Solvation (hydration) forces in water: forces associated with water structure 2153.7 Forces between ‘soft-supported’ membranes and proteins 2183.8 Equilibrium energies between biological surfaces 2194. Non-equilibrium and time-dependent interactions: sequential events that evolve in space and time 2214.1 Equilibrium and non-equilibrium time-dependent interactions 2214.2 Adhesion energy hysteresis 2234.3 Dynamic forces between biomolecules and biomolecular aggregates 2264.3.1 Strengths of isolated, noncovalent bonds 2274.3.2 The strengths of isolated bonds depend on the activation energy for unbinding 2294.4 Simulations of forced chemical transformations 2324.5 Forced extensions of biological macromolecules 2354.6 Force-induced versus thermally induced chemical transformations 2394.7 The rupture of bonds in series and in parallel 2424.7.1 Bonds in series 2424.7.2 Bonds in parallel 2444.8 Dynamic interactions between membrane surfaces 2464.8.1 Lateral mobility on membrane surfaces 2464.8.2 Intersurface forces depend on the rate of approach and separation 2494.9 Concluding remarks 2535. Acknowledgements 2556. References 255While the intermolecular forces between biological molecules are no different from those that arise between any other types of molecules, a ‘biological interaction’ is usually very different from a simple chemical reaction or physical change of a system. This is due in part to the higher complexity of biological macromolecules and systems that typically exhibit a hierarchy of self-assembling structures ranging in size from proteins to membranes and cells, to tissues and organs, and finally to whole organisms. Moreover, interactions do not occur in a linear, stepwise fashion, but involve competing interactions, branching pathways, feedback loops, and regulatory mechanisms.

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23

Jimenez, Ralph, Graham R. Fleming, P. V. Kumar, and M. Maroncelli. "Femtosecond solvation dynamics of water." Nature 369, no. 6480 (June 1994): 471–73. http://dx.doi.org/10.1038/369471a0.

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Biswas, Ranjit, and Biman Bagchi. "Ion solvation dynamics in supercritical water." Chemical Physics Letters 290, no. 1-3 (June 1998): 223–28. http://dx.doi.org/10.1016/s0009-2614(98)00460-6.

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Re, Mario, and Daniel Laria. "Dynamics of Solvation in Supercritical Water." Journal of Physical Chemistry B 101, no. 49 (December 1997): 10494–505. http://dx.doi.org/10.1021/jp971691x.

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Bizimana, Laurie A., Jordan Epstein, and Daniel B. Turner. "Inertial water response dominates protein solvation dynamics." Chemical Physics Letters 728 (August 2019): 1–5. http://dx.doi.org/10.1016/j.cplett.2019.04.069.

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Rey, Rossend, and James T. Hynes. "Solvation Dynamics in Water. 4. On the Initial Regime of Solvation Relaxation." Journal of Physical Chemistry B 124, no. 35 (July 31, 2020): 7668–81. http://dx.doi.org/10.1021/acs.jpcb.0c05706.

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Skaf, Munir S., and Branka M. Ladanyi. "Molecular Dynamics Simulation of Solvation Dynamics in Methanol−Water Mixtures." Journal of Physical Chemistry 100, no. 46 (January 1996): 18258–68. http://dx.doi.org/10.1021/jp961634o.

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29

Martins, Lucimara R., Munir S. Skaf, and Branka M. Ladanyi. "Solvation Dynamics at the Water/Zirconia Interface: Molecular Dynamics Simulations†." Journal of Physical Chemistry B 108, no. 51 (December 2004): 19687–97. http://dx.doi.org/10.1021/jp0470896.

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Rinne, Klaus F., Stephan Gekle, and Roland R. Netz. "Ion-Specific Solvation Water Dynamics: Single Water versus Collective Water Effects." Journal of Physical Chemistry A 118, no. 50 (December 4, 2014): 11667–77. http://dx.doi.org/10.1021/jp5066874.

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31

Day, Tyler J. F., and G. N. Patey. "Ion solvation dynamics in water–methanol and water– dimethylsulfoxide mixtures." Journal of Chemical Physics 110, no. 22 (June 8, 1999): 10937–44. http://dx.doi.org/10.1063/1.479030.

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32

Sen, Pratik, Subrata Pal, Kankan Bhattacharyya, and Biman Bagchi. "Solvation Dynamics in Biological Systems and Organized Assemblies." Journal of the Chinese Chemical Society 53, no. 1 (February 2006): 169–80. http://dx.doi.org/10.1002/jccs.200600019.

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Nandi, Nilashis, Srabani Roy, and Biman Bagchi. "Ionic and dipolar solvation dynamics in liquid water." Proceedings / Indian Academy of Sciences 106, no. 6 (November 1994): 1297–306. http://dx.doi.org/10.1007/bf02840686.

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34

Biswas, Ranjit, and Biman Bagchi. "Solvation dynamics of a charge bubble in water." Proceedings / Indian Academy of Sciences 109, no. 5 (October 1997): 347–52. http://dx.doi.org/10.1007/bf02875977.

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35

Moakes, Greg, and Jiri Janata. "Slow Solvation Dynamics of a Water–Nitrobenzene System." Accounts of Chemical Research 40, no. 8 (August 2007): 720–28. http://dx.doi.org/10.1021/ar700067e.

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Dang, Liem X., Julia E. Rice, James Caldwell, and Peter A. Kollman. "Ion solvation in polarizable water: molecular dynamics simulations." Journal of the American Chemical Society 113, no. 7 (March 1991): 2481–86. http://dx.doi.org/10.1021/ja00007a021.

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37

Kropman, M. F. "Dynamics of Water Molecules in Aqueous Solvation Shells." Science 291, no. 5511 (March 16, 2001): 2118–20. http://dx.doi.org/10.1126/science.1058190.

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Zimdars, David, Jerry I. Dadap, Kenneth B. Eisenthal, and Tony F. Heinz. "Femtosecond dynamics of solvation at the air/water interface." Chemical Physics Letters 301, no. 1-2 (February 1999): 112–20. http://dx.doi.org/10.1016/s0009-2614(99)00017-2.

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Schwenk, Christian F., Hannes H. Loeffler, and Bernd M. Rode. "Dynamics of the solvation process of Ca2+ in water." Chemical Physics Letters 349, no. 1-2 (November 2001): 99–103. http://dx.doi.org/10.1016/s0009-2614(01)01188-5.

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40

Assel, M., R. Laenen, and A. Laubereau. "Femtosecond solvation dynamics of solvated electrons in neat water." Chemical Physics Letters 317, no. 1-2 (January 2000): 13–22. http://dx.doi.org/10.1016/s0009-2614(99)01369-x.

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Zolotov, B., A. Gan, B. D. Fainberg, and D. Huppert. "Solvation dynamics of rhodamine 800 in water and D2O." Journal of Luminescence 72-74 (June 1997): 842–44. http://dx.doi.org/10.1016/s0022-2313(97)00023-9.

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42

Mukherjee, Saptarshi, Kalyanasis Sahu, Durba Roy, Sudip Kumar Mondal, and Kankan Bhattacharyya. "Solvation dynamics of 4-aminophthalimide in dioxane–water mixture." Chemical Physics Letters 384, no. 1-3 (January 2004): 128–33. http://dx.doi.org/10.1016/j.cplett.2003.11.098.

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Hara, Kimihiko, Naoki Baden, and Okitsugu Kajimoto. "Pressure effect on water solvation dynamics in micellar media." Journal of Physics: Condensed Matter 16, no. 14 (March 26, 2004): S1207—S1214. http://dx.doi.org/10.1088/0953-8984/16/14/032.

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Palchowdhury, Sourav, and B. L. Bhargava. "Solvation of Methyl Lactate in Water: Molecular Dynamics Studies." Journal of Physical Chemistry B 122, no. 7 (February 8, 2018): 2113–20. http://dx.doi.org/10.1021/acs.jpcb.7b12248.

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Rey, Rossend, and James T. Hynes. "Solvation Dynamics in Liquid Water. 1. Ultrafast Energy Fluxes." Journal of Physical Chemistry B 119, no. 24 (January 30, 2015): 7558–70. http://dx.doi.org/10.1021/jp5113922.

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Rey, Rossend, and James T. Hynes. "Translational versus rotational energy flow in water solvation dynamics." Chemical Physics Letters 683 (September 2017): 483–87. http://dx.doi.org/10.1016/j.cplett.2017.02.064.

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47

Remsing, Richard C., and Michael L. Klein. "Solvation dynamics in water confined within layered manganese dioxide." Chemical Physics Letters 683 (September 2017): 478–82. http://dx.doi.org/10.1016/j.cplett.2017.02.082.

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Martins, Lucimara R., Alejandro Tamashiro, Daniel Laria, and Munir S. Skaf. "Solvation dynamics of coumarin 153 in dimethylsulfoxide–water mixtures: Molecular dynamics simulations." Journal of Chemical Physics 118, no. 13 (April 2003): 5955–63. http://dx.doi.org/10.1063/1.1556296.

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Khanal, S. P., B. Poudel, R. P. Koirala, and N. P. Adhikari. "Solvation Free Energy of Protonated Lysine: Molecular Dynamics Study." Journal of Nepal Physical Society 7, no. 2 (August 6, 2021): 69–75. http://dx.doi.org/10.3126/jnphyssoc.v7i2.38625.

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In the present work, we have used an alchemical approach for calculating solvation free energy of protonated lysine in water from molecular dynamics simulations. These approaches use a non-physical pathway between two end states in order to compute free energy difference from the set of simulations. The solute is modeled using bonded and non-bonded interactions described by OPLS-AA potential, while four different water models: TIP3P, SPC, SPC/E and TIP4P are used. The free energy of solvation of protonated lysine in water has been estimated using thermodynamic integration, free energy perturbation, and Bennett acceptance ratio methods at 310 K temperature. The contributions to the free energy due to van der Waals and electrostatics parameters are also separately computed. The estimated values of free energy of solvation using different methods are in well agreement with previously reported experimental value within 14 %.

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50

Gavrilov, Yulian, Jessica D. Leuchter, and Yaakov Levy. "On the coupling between the dynamics of protein and water." Physical Chemistry Chemical Physics 19, no. 12 (2017): 8243–57. http://dx.doi.org/10.1039/c6cp07669f.

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