The probability distribution function as a descriptor of hydrogen bond strength

Karingithi, Robert N.; Shaw, Cynthia L.; Roberts, Evan W.; Molina, Pablo A.

doi:10.1016/j.theochem.2007.11.003

Cited by 9 publications

(11 citation statements)

References 33 publications

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“…82 Nevertheless, O• • • H distances are often used. 81,83 The population of the two O• • • H distances is shown in Figure 5. We have chosen four structures: Hstructure I, H-structure III, NO 2 -structure I, and NO 2 -structure III to show the extent of substituent effect on the O• • • H population.…”

Section: Kinetic Analysesmentioning

confidence: 99%

Intramolecular proton transfer reaction dynamics using machine learned ab initio potential energy surfaces

Raghunathan

2021

Preprint

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Hydrogen bonding interactions central to various physicochemical processes are investigated in the present study using ab initio-based machine learning potential energy surfaces. Abnormally strong intramolecular O-H...O hydrogen bonds occurring in beta-diketone enols of malonaldehyde, and its derivatives with substituents ranging from various electron-withdrawing to electron-donating functional groups are studied. Machine learning force fields were constructed by using a kernel-based force learning model employing ab initio molecular dynamics reference data. These models were used for molecular dynamics simulations at finite temperature, and dynamical properties were determined by computing their proton transfer free energy surfaces. Chemical systems studied here show progression towards forming barrierless proton transfer events at an accuracy of highly correlated electronic structure methods. Markov state models of the conformational states indicate shorter intramolecular hydrogen bonds exhibiting higher proton transfer rates. We demonstrate how functional group substitution can modulate the strength of intramolecular hydrogen bonds by studying their thermodynamic and kinetic properties.

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Section: Kinetic Analysesmentioning

confidence: 99%

Intramolecular proton transfer reaction dynamics using machine learned ab initio potential energy surfaces

Raghunathan

2021

Preprint

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“…8. For the rotation of the ellipsoid around x-axis (that is in our case actually the axis σ for the peptide group introduced above) the friction coefficient is given by a formula [68] (γ (24) where r = 2(abc) 1/3 and η is the viscosity of the ellipsoid environment. The required behavior is obtained if we have the condition of the underdamped motion…”

Section: Equation Of Motion and Correlation Function For Crankshaft M...mentioning

confidence: 99%

“…To be more precise we study the effect of this transformation on the backbone dynamics in the antiparallel β-sheet. However it should be stressed that following [24] we believe that there are no well defined boundaries between different types of hydrogen bonds. In fact we investigate the parametric dependence of the backbone dynamics on the hydrogen bond energy from the range 2 ÷ 30 kcal/mol.…”

Section: Introductionmentioning

confidence: 98%

“…The most salient feature of low barrier hydrogen bonds as compared to ordinary hydrogen bonds is their strength and short distance between hydrogen donor and acceptor atoms (dDA). We do not involve ourselves in very intricate classification debates about blurred boundaries between weak, strong, short strong, short ionic, low barrier and very strong hydrogen bonds (see, e.g., [24]). For convenience we freely divide the hydrogen bonds to strong ones (SHB) and weak ones (WHB).…”

Section: Introductionmentioning

confidence: 99%

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Model for crankshaft motion of protein backbone in nonspecific binding site of serine proteases

Sitnitsky

2011

Preprint

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The consequences of recent experimental finding that hydrogen bonds of the antiparallel β-sheet in nonspecific binding site of serine proteases become significantly shorter and stronger synchronously with the catalytic act are examined. We investigate the effect of the transformation of an ordinary hydrogen bond into a low-barrier one on the crankshaft motion a peptide group in the anti-parallel β-sheet. For this purpose we make use of a realistic model of the peptide chain with stringent microscopically derived coupling interaction potential and effective on-site potential. The coupling interaction characterizing the peptide chain rigidity is found to be surprisingly weak and repulsive in character. The effective on-site potential is found to be a hard one, i.e., goes more steep than a harmonic one. At transformation of the ordinary hydrogen bond into the low-barrier one the frequency of crankshaft motion of the corresponding peptide group in the anti-parallel β-sheet is roughly doubled.

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“…in [6], [7], [8], [9]). Besides it is a basic model for the description of ordinary hydrogen bonds (HB) and so-called low-barrier hydrogen bonds (LBHB) [14], [15], [16], [17]. There are heated debates for more than twenty years that the latter may play an important role in biology (in particular in enzyme catalysis) [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Exactly solvable Schrödinger equation with double-well potential for hydrogen bond

Sitnitsky

2017

Chemical Physics Letters

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We construct a double-well potential for which the Schrödinger equation can be exactly solved via reducing to the confluent Heun's one. Thus the wave function is expressed via the confluent Heun's function. The latter is tabulated in Maple so that the obtained solution is easily treated. The potential is infinite at the boundaries of the final interval that makes it to be highly suitable for modeling hydrogen bonds (both ordinary and low-barrier ones). We exemplify theoretical results by detailed treating the hydrogen bond in KHCO 3 and show their good agreement with literature experimental data.

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The probability distribution function as a descriptor of hydrogen bond strength

Cited by 9 publications

References 33 publications

Intramolecular proton transfer reaction dynamics using machine learned ab initio potential energy surfaces

Intramolecular proton transfer reaction dynamics using machine learned ab initio potential energy surfaces

Model for crankshaft motion of protein backbone in nonspecific binding site of serine proteases

Exactly solvable Schrödinger equation with double-well potential for hydrogen bond

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