New angle‐dependent potential energy function for backbone–backbone hydrogen bond in protein–protein interactions

Choi, Ho-Jin; Kang, Hongsuk; Park, Hwangseo

doi:10.1002/jcc.21378

Cited by 13 publications

(19 citation statements)

References 34 publications

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“…18,21,22 Currently, there are in general three strategies to tackle this HB directionality problem: 1. The addition of an explicit angle-dependent hydrogen bonding term to take account of the charge transfer effect, in which new parameters can be derived from the analysis of protein structure database 12,19 or fitted to ab initio QM calculations; 16,23,24 2. Going beyond the atomic point charge model by introducing off-center charges to mimic lone pair electrons 25–30 or employing high order distributed multipoles to better describe electrostatics; 31–33 3.…”

Section: Introductionmentioning

confidence: 99%

Directional Dependence of Hydrogen Bonds: A Density-Based Energy Decomposition Analysis and Its Implications on Force Field Development

Zhou

et al. 2011

J. Chem. Theory Comput.

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One well-known shortcoming of widely-used biomolecular force fields is the description of the directional dependence of hydrogen bonding (HB). Here we aim to better understand the origin of this difficulty and thus provide some guidance for further force field development. Our theoretical approaches center on a novel density-based energy decomposition analysis (DEDA) method [J. Chem. Phys., 131, 164112 (2009)], in which the frozen density energy is variationally determined through constrained search. This unique and most significant feature of DEDA enables us to find that the frozen density interaction term is the key factor in determining the HB orientation, while the sum of polarization and charge-transfer components shows very little HB directional dependence. This new insight suggests that the difficulty for current non-polarizable force fields to describe the HB directional dependence is not due to the lack of explicit polarization or charge-transfer terms. Using the DEDA results as reference, we further demonstrate that the main failure coming from the atomic point charge model can be overcome largely by introducing extra charge sites or higher order multipole moments. Among all the electrostatic models explored, the smeared charge distributed multipole model (up to quadrupole), which also takes account of charge penetration effects, gives the best agreement with the corresponding DEDA results. Meanwhile, our results indicate that the van der Waals interaction term needs to be further improved to better model directional hydrogen bonding.

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Section: Introductionmentioning

confidence: 99%

Directional Dependence of Hydrogen Bonds: A Density-Based Energy Decomposition Analysis and Its Implications on Force Field Development

Zhou

et al. 2011

J. Chem. Theory Comput.

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“…Four different hydrogen bonding potentials were used, two based on angular‐dependent potentials, one based on a Morse potential, and one based on a CHARMM potential . As with many of our other energetic features, the potentials were modified to soften the repulsive component at short distances using the following functional form:

\begin{matrix} H B = D_{0} true[5 {true(\frac{r_{0}}{r} true)}^{12} - 6 {true(\frac{r_{0}}{r} true)}^{10} true] f true(θ, φ true) & r > r_{0} + 0.1 \\ H B = D_{0} true[5 {true(\frac{r_{0}}{r_{0} + 1} true)}^{12} - 6 {true(\frac{r_{0}}{r_{0} + 1} true)}^{10} true] f true(θ, φ true) & r_{0} - 0.5 \leq r \leq r_{0} + 0.1 \\ H B = \frac{D_{0}}{64^{2}} true[\frac{5}{64^{2}} {true(\frac{r_{0}}{r} true)}^{12} - \frac{3}{2} {true(\frac{r_{0}}{r} true)}^{10} true] f true(θ, φ true) & r_{0} < r_{0} - 0.5 \end{matrix}

…”

Section: Methodsmentioning

confidence: 99%

“…Finally, the Morse hydrogen bonding potential has the form:

H B = D_{0} {true[1 - e^{- α (r - r_{0})} true]}^{2} f true(θ, φ true)

where D 0 =7.785 is the well‐depth, r 0 =1.912 is the equilibrium donor hydrogen‐acceptor distance (as opposed to the donor heavy atom‐acceptor distance in the 12–10 potentials described above), r is the distance between the donor hydrogen and acceptor, and α is a parameter that determines the curvature of the function. For methyl‐oxygen hydrogen bonds, D 0 = 2.694 and r 0 = 2.252.…”

Section: Methodsmentioning

confidence: 99%

Using physical potentials and learned models to distinguish native binding interfaces from de novo designed interfaces that do not bind

Demerdash

Mitchell

2013

Proteins

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Protein-protein interactions are a fundamental aspect of many biological processes. The advent of recombinant protein and computational techniques has allowed for the rational design of proteins with novel binding capabilities. It is therefore desirable to predict which designed proteins are capable of binding in vitro. To this end, we have developed a learned classification model that combines energetic and non-energetic features. Our feature set is adapted from specialized potentials for aromatic interactions, hydrogen bonds, electrostatics, shape, and desolvation. A binding model built on these features was initially developed for CAPRI Round 21, achieving top results in the independent assessment. Here, we present a more thoroughly trained and validated model, and compare various support-vector machine kernels. The Gaussian kernel model classified both high-resolution complexes and designed nonbinders with 79-86% accuracy on independent test data. We also observe that multiple physical potentials for dielectric-dependent electrostatics and hydrogen bonding contribute to the enhanced predictive accuracy, suggesting that their combined information is much greater than that of any single energetics model. We also study the change in predictive performance as the model features or training data are varied, observing unusual patterns of prediction in designed interfaces as compared with other data types.

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“…Acceptors Donors Level of theory Geometric parameters a Lamas et al 70 1992 71 1996 72 1997 13,68 2004 formamide formamide PBE96/aug-cc-pVDZ f (θ), f (φ) Nanda et al 73 2007 - 20 2008 74 2009 -OH(sp 3 ) CH(sp,sp 2 ) IMPT/6-31G** f (φ) Choi et al 75 2009 N-methylacetamide N-methylacetamide B3LYP/6-311G** f (φ) Choi et al 76 2010 69 2011 78 2016 79 2017 Dataset molecules. The molecules we selected for our dataset are depicted in Supplementary Figs.…”

Section: Supplementary Informationmentioning

confidence: 99%

“…To assess the quality of directionality profiles calculated with B3LYP/cc-pVDZ we used MP2/aug-cc-pVTZ to compute domes for donor and acceptor sites of water (15,75), imidazole (25,92), methyl-acetamide (18,90), methyl-thioacetamide (not numbered as donor; compound 62 as acceptor), phenol (26,55), and TMAO (97). Results are summarized in Supplementary Table S2…”

Section: Supplementary Informationmentioning

confidence: 99%

Charting Hydrogen Bond Anisotropy

Santos-Martins¹,

Forli

2019

Preprint

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Hydrogen bond (HB) is an essential interaction in countless phenomena, and regulates the chemistry of life. HBs are characterized by two main features, strength and directionality, with a high degree of heterogeneity across different chemical groups. These characteristics are dependent on the electronic configuration of the atoms involved in the interaction, which, in turn, is influenced strongly by the molecular environment where they are found. Studies based on the analysis of HB in solid phase, such as X-ray crystallography, suffer from significant biases due to the packing forces. These will tend to better describe strong HBs at the expenses of weak ones, which are either distorted or under-represented. Using quantum mechanics (QM), we calculated interaction energies for about a hundred acceptor and donors, in a rigorously defined set of geometries. We performed about 180,000 independent QM calculations, covering all relevant angular components, and mapping strength and directionality in a context free from external biases, with both single-site and cooperative HBs. We show that by quantifying directionality, there is not correlation with strength, and therefore these two components need to be addressed separately. Results demonstrate that there are very strong HB acceptors (e.g., DMSO) with nearly isotropic interactions, and weak ones (e.g., thioacetone) with a sharp directional profile. Similarly, groups can have comparable directional propensity, but be very distant in the strength spectrum (e.g., thioacetone and pyridine). These findings have implications for biophysics and molecular recognition, providing new insight for chemical biology, protein engineering, and drug design. The results require rethinking the way directionality is described, with implications for the thermodynamics of HB. hydrogen bond | drug design | force field | non-covalent interaction Correspondence: forli@scripps.edu ResultsThe dataset contains 34 donors ( Fig.S1) and 67 acceptors ( Fig.S2, Methods). For the entire dataset, calculations were performed using B3LYP density functional with the cc-pVDZ basis set and the counterpoise correction, while MP2/aug-cc-pVTZ with counterpoise correction was used for smaller subsets of complexes. The validation of these two methods, their differences and their effect on the results has been discussed in Supplementary Methods. Strength.We measured the strength of HBs on the 34 donors ( Fig.S1) and 67 acceptors, performing B3LYP/cc-pVDZ calculations of donor-acceptor dimers interacting in optimal ge-July 5, 2019 | 1-20

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New angle‐dependent potential energy function for backbone–backbone hydrogen bond in protein–protein interactions

Cited by 13 publications

References 34 publications

Directional Dependence of Hydrogen Bonds: A Density-Based Energy Decomposition Analysis and Its Implications on Force Field Development

Directional Dependence of Hydrogen Bonds: A Density-Based Energy Decomposition Analysis and Its Implications on Force Field Development

Using physical potentials and learned models to distinguish native binding interfaces from de novo designed interfaces that do not bind

Charting Hydrogen Bond Anisotropy

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