Conformational assignment of gas phase peptides and their H-bonded complexes using far-IR/THz: IR-UV ion dip experiment, DFT-MD spectroscopy, and graph theory for mode assignment

Galimberti, Daria Ruth; Bougueroua, Sana; Mahé, Jérôme; Tommasini, Matteo; Rijs, Anouk M.; Gaigeot, Marie Pierre

doi:10.1039/c8fd00211h

Cited by 14 publications

(73 citation statements)

References 97 publications

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“…the side chain orientation in the dimer, measurements of the amide A, I and II region are not necessarily sufficient. Thus measurements for Ac-Phe-OMe in the region down to 1000 cm -1 finally lead to the unambiguous assignment of β L (g+); 363 for the dimer structure these measurements were less unambiguous but a gauche(+) side chain orientation in both strands (cf. 397 and Section 12) was proposed.…”

Section: 157mentioning

confidence: 99%

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Neutral Peptides in the Gas Phase: Conformation and Aggregation Issues

et al. 2020

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Combined IR and UV laser spectroscopic techniques in molecular beams merged with theoretical approaches have proven to be an ideal tool to elucidate intrinsic structural properties on a molecular level. It offers the possibility to analyze structural changes by successively adding aggregation partners and thus an environment to a molecule. By this, it further makes these techniques a valuable starting point for a bottom-up approach in understanding the forces shaping larger molecular systems. This bottomup approach was successfully applied to neutral amino acids starting around the 1990s. Ever since experimental and theoretical methods developed further and investigations could be extended to larger peptide systems. Beyond, the review gives an introduction to secondary structures and experimental methods as well as a summary on theoretical approaches. Vibrational frequencies being characteristic probes of molecular structure and interactions are especially addressed. Archetypal biologically relevant secondary structures investigated by molecular beam spectroscopy are described and the influences of specific peptide residues on conformational preferences as well as the competition between secondary structures are discussed. Important influences like microsolvation or aggregation behaviour are presented. Beyond the linear α-peptides the main results of structural analysis on cyclic systems as well as on β-and γ-peptides are summarized. Overall, this contribution addresses current aspects of molecular beam spectroscopy on peptides and related species and provides molecular level insights into manifold issues of chemical and biochemical relevance. 45) , non-protected (cf. e.g. 46-48) and protected amino acids (cf. e.g. 49) up to dipeptide models (cf. e.g. 50).In this context, laser spectroscopic techniques combining IR and UV excitations, that one can consider as belonging to the so-called 'action spectroscopies', provide an isomer-selective method of choice to tackle the 87 ) or immunoglobulins (cf. e.g. 88), but they are also found in context with neurodegenerative diseases (cf. e.g. [89][90][91][92][93][94][95] and Section 12). A further structure associated with these diseases (cf. e.g. 96 ) is the β-helix, which presents a protein structure of several parallel β-strands in a helical arrangement with a frequently repetitive amino acid sequence. The structure is stabilized by H-bonds, sometimes ionic interactions or so called protein-protein interactions, which e.g. include electrostatic and hydrophobic effects. Further aspects of peptide structure in gas phase The role of protection groupsWith the unmodified N-and C-terminus amino acids and peptides can exhibit strong preferences for intramolecular H-bonds involving the N-and C-terminus, and can also form intermolecular H-bonds leading to polymer chains. Nevertheless, in a context where the description of the properties of a protein or a long peptide (with respect to its backbone) by smaller peptides is targeted, the introduction of protecting groups at the N-and...

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Section: 157mentioning

confidence: 99%

“…Later on investigations were also performed in the far IR region. 362,363 Beyond the monomer the homo dimer was investigated 134,284,362,363,397 (cf. Section 12) as well as the aggregation with water as the most important biological solvent 160 (cf.…”

Section: 103398mentioning

confidence: 99%

Neutral Peptides in the Gas Phase: Conformation and Aggregation Issues

et al. 2020

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“…Progress towards machine learning (ML) methods for environmental pollutant analysis has been explored for specific, targeted applications. 9,[15][16][17] Generalizable functional group ML models would increase the utility of FTIR sample screening in environmental and other chemistry applications. 18,19 In this study, we investigate the implementation of convolutional neural networks (CNNs) 20 to identify functional groups present in FTIR spectra.…”

Section: Introductionmentioning

confidence: 99%

Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

et al. 2021

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Fourier Transform Infrared Spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. We develop a generalizable model via a machine learning (ML) algorithm using Convolutional Neural Networks (CNNs) to identify the presence of functional groups in gas phase FTIR spectra. The ML models will reduce the amount of time required to analyze functional groups and facilitate interpretation of FTIR spectra. Through web scraping, we acquire intensity-frequency data from 8728 gas phase organic molecules within the NIST spectral database and transform the data into images. We successfully train models for 15 of the most common organic functional groups, which we then determine via identification from previously untrained spectra. These models serve to expand the application of FTIR measurements for facile analysis of organic samples. Our approach was done such that we have broad functional group models that inference in tandem to provide full interpretation of a spectrum. We present the first implementation of ML using image-based CNNs for predicting functional groups from a spectroscopic method. File list (2) download file view on ChemRxiv ML functional group ID in FTIR spectra.docx (545.84 KiB) download file view on ChemRxiv ML functional group ID in FTIR spectra.pdf (645.08 KiB) Functional group identification for FTIR spectra using image-based machine learning models

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“…Current quantum chemistry computer codes can be used very reliably to assign the features observed in molecular spectra to electronic or vibrational transitions, with increasingly accurate levels of theory [2][3][4][5][6][7][8][9]. Notable advances in tools available for computational spectroscopy have appeared in the recent literature [10][11][12][13][14][15][16][17][18][19]. These are commonly based on existing quantum chemistry engines, and their development often enhances the accuracy of the existing approaches.…”

Section: Introductionmentioning

confidence: 99%

“…Equation (18) shows that the dipole strength of a given vibrational transition (0 a → 1 a ) is a quadratic form in the coefficients of the nuclear displacement of the associated normal mode (L ia ). Clearly, Torii's approach to ICM [33] seeks the eigenvalues of the M IR matrix (Equation (16)), which is exactly the matrix of the quadratic form associated to the dipole strength reported in Equation (18). This observation justifies a similar approach for IR and VCD, provided that a suitable M matrix is defined also for the latter case.…”

Section: Introducing Intensity-carrying Modes In Vcdmentioning

confidence: 99%

Evaluation of Molecular Polarizability and of Intensity Carrying Modes Contributions in Circular Dichroism Spectroscopies

et al. 2019

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We re-examine the theory of electronic and vibrational circular dichroism spectroscopy in terms of the formalism of frequency-dependent molecular polarizabilities. We show the link between Fermi’s gold rule in circular dichroism and the trace of the complex electric dipole–magnetic dipole polarizability. We introduce the C++ code polar to compute the molecular polarizability complex tensors from quantum chemistry outputs, thus simulating straightforwardly UV-visible absorption (UV-Vis)/electronic circular dichroism (ECD) spectra, and infrared (IR)/vibrational circular dichroism (VCD) spectra. We validate the theory and the code by referring to literature data of a large group of chiral molecules, showing the remarkable accuracy of density functional theory (DFT) methods. We anticipate the application of this methodology to the interpretation of vibrational spectra in various measurement conditions, even in presence of metal surfaces with plasmonic properties. Our theoretical developments aim, in the long run, at embedding the quantum-mechanical details of the chiroptical spectroscopic response of a molecule into the simulation of the electromagnetic field distribution at the surface of plasmonic devices. Such simulations are also instrumental to the interpretation of the experimental spectra measured from devices designed to enhance chiroptical interactions by the surface plasmon resonance of metal nanostructures.

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Conformational assignment of gas phase peptides and their H-bonded complexes using far-IR/THz: IR-UV ion dip experiment, DFT-MD spectroscopy, and graph theory for mode assignment

Abstract: Graph theory based vibrational modes as new entities for vibrational THz spectroscopy.

Cited by 14 publications

References 97 publications

Neutral Peptides in the Gas Phase: Conformation and Aggregation Issues

Neutral Peptides in the Gas Phase: Conformation and Aggregation Issues

Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

Evaluation of Molecular Polarizability and of Intensity Carrying Modes Contributions in Circular Dichroism Spectroscopies

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