Optimization of Model Parameters for Describing the Amide I Spectrum of a Large Set of Proteins

A new computational methodology for the characterization of complex molecular environments using IR spectroscopy: bridging the gap between experiments and computations

The molecular interactions and dynamics of complex liquid solutions are now routinely measured using IR and 2DIR spectroscopy. In particular, the use of the latter allows the determination of the frequency fluctuation correlation function (FFCF), while the former provides us with the average frequency. In turn, the FFCF can be used to quantify the vibrational dynamics of a molecule in a solution, and the center frequency provides details about the chemical environment, solvatochromism, of the vibrational mode. In simple solutions, the IR methodology can be used to unambiguously assign the interactions and dynamics observed by a molecule in solution. However, in complex environments with molecular heterogeneities, this assignment is not simple. Therefore, a method that allows for such an assignment is essential. Here, a parametrization free method, called Instantaneous Frequencies of Molecules or IFM, is presented. The IFM method, when coupled to classical molecular simulations, can predict the FFCF of a molecule in solutions. Here, N-methylacetamide (NMA) in seven different chemical environments, both simple and complex, is used to test this new method. The results show good agreement with experiments for the NMA solvatochromism and FFCF dynamics, including characteristic times and amplitudes of fluctuations. In addition, the new method shows equivalent or improved results when compared to conventional frequency maps. Overall, the use of the new method in conjunction with molecular dynamics simulations allows unlocking the full potential of IR spectroscopy to generate molecular maps from vibrational observables, capable of describing the interaction landscape of complex molecular systems.

Refining protein amide I spectrum simulations with simple yet effective electrostatic models for local wavenumbers and dipole derivative magnitudes

Analysis of the amide I band of proteins is probably the most wide-spread application of bioanalytical infrared spectroscopy. Although highly desirable for a more detailed structural interpretation, a quantitative description of this absorption band is still difficult. This work optimized several electrostatic models with the aim to reproduce the effect of the protein environment on the intrinsic wavenumber of a local amide I oscillator. We considered the main secondary structures - α-helices, parallel and antiparallel β-sheets - with a maximum of 21 amide groups. The models were based on the electric potential and/or the electric field component along the CO bond at up to four atoms in an amide group. They were bench-marked by comparison to Hessian matrices reconstructed from density functional theory calculations at the BPW91, 6-31G** level. The performance of the electrostatic models depended on the charge set used to calculate the electric field and potential. Gromos and DSSP charge sets, used in common force fields, were not optimal for the better performing models. A good compromise between performance and the stability of model parameters was achieved by a model that considered the electric field at the positions of the oxygen, nitrogen, and hydrogen atoms of the considered amide group. The model describes also some aspects of the local conformation effect and performs similar on its own as in combination with an explicit implementation of the local conformation effect. It is better than a combination of a local hydrogen bonding model with the local conformation effect. Even though the short-range hydrogen bonding model performs worse, it captures important aspects of the local wavenumber sensitivity to the molecular surroundings. We improved also the description of the coupling between local amide I oscillators by developing an electrostatic model for the dependency of the dipole derivative magnitude on the protein environment.

2D-IR spectroscopy of proteins in H2O-A Perspective

The form of the amide I infrared absorption band provides a sensitive probe of the secondary structure and dynamics of proteins in the solution phase. However, the frequency coincidence of the amide I band with the bending vibrational mode of H₂O has necessitated the widespread use of deuterated solvents. Recently, it has been demonstrated that ultrafast 2D-IR spectroscopy allows the detection of the protein amide I band in H₂O-based fluids, meaning that IR methods can now be applied to study proteins in physiologically relevant solvents. In this perspective, we describe the basis of the 2D-IR method for observing the protein amide I band in H₂O and show how this development has the potential to impact areas ranging from our fundamental appreciation of protein structural dynamics to new applications for 2D-IR spectroscopy in the analytical and biomedical sciences. In addition, we discuss how the spectral response of water, rather than being a hindrance, now provides a basis for new approaches to data pre-processing, standardization of 2D-IR data collection, and signal quantification. Ultimately, we visualize a direction of travel toward the creation of 2D-IR spectral libraries that can be linked to advanced computational methods for use in high-throughput protein screening and disease diagnosis.

Computational spectroscopy of complex systems

Numerous linear and non-linear spectroscopic techniques have been developed to elucidate structural and functional information of complex systems ranging from natural systems, such as proteins and light-harvesting systems, to synthetic systems, such as solar cell materials and light-emitting diodes. The obtained experimental data can be challenging to interpret due to the complexity and potential overlapping spectral signatures. Therefore, computational spectroscopy plays a crucial role in the interpretation and understanding of spectral observables of complex systems. Computational modeling of various spectroscopic techniques has seen significant developments in the past decade, when it comes to the systems that can be addressed, the size and complexity of the sample types, the accuracy of the methods, and the spectroscopic techniques that can be addressed. In this Perspective, I will review the computational spectroscopy methods that have been developed and applied for infrared and visible spectroscopies in the condensed phase. I will discuss some of the questions that this has allowed answering. Finally, I will discuss current and future challenges and how these may be addressed.

A computational insight into the relationship between side chain IR line shapes and local environment in fibril-like structures

Infrared spectroscopy is a widely used technique to characterize protein structures and protein mediated processes. While the amide I band provides information on proteins' secondary structure, amino acid side chains are used as infrared probes for the investigation of protein reactions and local properties. In this paper, we use a hybrid quantum mechanical/classical molecular dynamical approach based on the perturbed matrix method to compute the infrared band due to the C=O stretching mode of amide-containing side chains. We calculate, at first, the infrared band of zwitterionic glutamine in water and obtain results in very good agreement with the experimental data. Then, we compute the signal arising from glutamine side chains in a microcrystal of the yeast prion Sup35-derived peptide, GNNQQNY, with a fibrillar structure. The infrared bands obtained by selective isotopic labeling of the two glutamine residues, Q4 and Q5, of each peptide were experimentally used to investigate the local hydration in the fibrillar microcrystal. The experimental spectra of the two glutamine residues, which experience different hydration environments, feature different spectral signals that are well reproduced by the corresponding calculated spectra. In addition, the analysis of the simulated spectra clarifies the molecular origin of the experimentally observed spectroscopic differences that arise from the different local electric field experienced by the two glutamine residues, which is, in turn, determined by a different hydrogen bonding pattern.

Searching for a Better Match between Protein Secondary Structure Definitions and Protein FTIR Spectra

Obtaining protein secondary structure content from high-resolution structures requires definitions and thresholds for the various parameters involved, typically hydrogen bond energy or length/angle and backbone φ/ψ angles. Several definitions are currently used and can have a profound impact on secondary structure content. Fourier transform infrared (FTIR) spectroscopy has its own sensitivity to molecular geometry. It is, therefore, important to select a set of definitions that matches this sensitivity. Here, we used a new protein set consisting of 92 proteins designed for the calibration of spectroscopic methods. Spectra have been obtained from protein microarrays in a high throughput process. The potential for improving secondary structure predictions from FTIR spectra has been tested using 71 structures determined according to different definitions. The paper demonstrates that different secondary structure definitions result in large variations in secondary structure content that are not equivalent in view of the protein FTIR spectra. The prediction quality factor ζ can be improved by ca. 20-50% by selecting an adequate definition set. The results also indicate that the dictionary of secondary structure of proteins (DSSP) algorithm, which is currently widely used to evaluate protein secondary structure content, is a good choice when dealing with FTIR spectra.

A Machine Learning Protocol for Predicting Protein Infrared Spectra

Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary structure determination from IR spectra is tedious since its theoretical interpretation requires repeated expensive quantum-mechanical calculations in a fluctuating environment. Herein we present a novel machine learning protocol that uses a few key structural descriptors to rapidly predict amide I IR spectra of various proteins and agrees well with experiment. Its transferability enabled us to distinguish protein secondary structures, probe atomic structure variations with temperature, and monitor protein folding. This approach offers a cost-effective tool to model the relationship between protein spectra and their biological/chemical properties.

Vibrational Spectroscopic Map, Vibrational Spectroscopy, and Intermolecular Interaction

Vibrational spectroscopy is an essential tool in chemical analyses, biological assays, and studies of functional materials. Over the past decade, various coherent nonlinear vibrational spectroscopic techniques have been developed and enabled researchers to study time-correlations of the fluctuating frequencies that are directly related to solute-solvent dynamics, dynamical changes in molecular conformations and local electrostatic environments, chemical and biochemical reactions, protein structural dynamics and functions, characteristic processes of functional materials, and so on. In order to gain incisive and quantitative information on the local electrostatic environment, molecular conformation, protein structure and interprotein contacts, ligand binding kinetics, and electric and optical properties of functional materials, a variety of vibrational probes have been developed and site-specifically incorporated into molecular, biological, and material systems for time-resolved vibrational spectroscopic investigation. However, still, an all-encompassing theory that describes the vibrational solvatochromism, electrochromism, and dynamic fluctuation of vibrational frequencies has not been completely established mainly due to the intrinsic complexity of intermolecular interactions in condensed phases. In particular, the amount of data obtained from the linear and nonlinear vibrational spectroscopic experiments has been rapidly increasing, but the lack of a quantitative method to interpret these measurements has been one major obstacle in broadening the applications of these methods. Among various theoretical models, one of the most successful approaches is a semiempirical model generally referred to as the vibrational spectroscopic map that is based on a rigorous theory of intermolecular interactions. Recently, genetic algorithm, neural network, and machine learning approaches have been applied to the development of vibrational solvatochromism theory. In this review, we provide comprehensive descriptions of the theoretical foundation and various examples showing its extraordinary successes in the interpretations of experimental observations. In addition, a brief introduction to a newly created repository Web site (http://frequencymap.org) for vibrational spectroscopic maps is presented. We anticipate that a combination of the vibrational frequency map approach and state-of-the-art multidimensional vibrational spectroscopy will be one of the most fruitful ways to study the structure and dynamics of chemical, biological, and functional molecular systems in the future.

On the Secondary Structure of Silk Fibroin Nanoparticles Obtained Using Ionic Liquids: An Infrared Spectroscopy Study

Silk fibroin from Bombyx mori caterpillar is an outstanding biocompatible polymer for the production of biomaterials. Its impressive combination of strength, flexibility, and degradability are related to the protein’s secondary structure, which may be altered during the manufacture of the biomaterial. The present study looks at the silk fibroin secondary structure during nanoparticle production using ionic liquids and high-power ultrasound using novel infrared spectroscopic approaches. The infrared spectrum of silk fibroin fibers shows that they are composed of 58% β-sheet, 9% turns, and 33% irregular and/or turn-like structures. When fibroin was dissolved in ionic liquids, its amide I band resembled that of soluble silk and no β-sheet absorption was detected. Silk fibroin nanoparticles regenerated from the ionic liquid solution exhibited an amide I band that resembled that of the silk fibers but had a reduced β-sheet content and a corresponding higher content of turns, suggesting an incomplete turn-to-sheet transition during the regeneration process. Both the analysis of the experimental infrared spectrum and spectrum calculations suggest a particular type of β-sheet structure that was involved in this deficiency, whereas the two other types of β-sheet structure found in silk fibroin fibers were readily formed.

The Amide I Spectrum of Proteins-Optimization of Transition Dipole Coupling Parameters Using Density Functional Theory Calculations

The amide I region of the infrared spectrum is related to the protein backbone conformation and can provide important structural information. However, the interpretation of the experimental results is hampered because the theoretical description of the amide I spectrum is still under development. Quantum mechanical calculations, for example, using density functional theory (DFT), can be used to study the amide I spectrum of small systems, but the high computational cost makes them inapplicable to proteins. Other approaches that solve the eigenvalues of the coupled amide I oscillator system are used instead. An important interaction to be considered is transition dipole coupling (TDC). Its calculation depends on the parameters of the transition dipole moment. This work aims to find the optimal parameters for TDC in three major secondary structures: α-helices, antiparallel β-sheets, and parallel β-sheets. The parameters were suggested through a comparison between DFT and TDC calculations. The comparison showed a good agreement for the spectral shape and for the wavenumbers of the normal modes for all secondary structures. The matching between the two methods improved when hydrogen bonding to the amide oxygen was considered. Optimal parameters for individual secondary structures were also suggested.

Modeling amino-acid side chain infrared spectra: the case of carboxylic residues

Infrared (IR) spectroscopy is commonly utilized for the investigation of protein structures and protein-mediated processes.

Mapping the amide-I vibrations of model dipeptides with secondary structure sensitivity and amino acid residue specificity, and its application to amyloid β-peptide in aqueous solution

Vibrational spectroscopy has been known as particularly well-suited for deciphering the polypeptide's structure. To decode structural information encoded in IR spectra, we developed amide-I frequency maps on the basis of model dipeptides to correlate the amide-I frequency of interest to the combination of the calculated secondary structure dependent amide-I frequency by using DFT method and the electrostatic potentials that projected onto the amide unit from the micro-environment within molecular mechanics force field. The constructed maps were applied to model dipeptides and amyloid β-peptide fragment (Aβ_25-35). The dipeptide specified map (DS map) and the hybrid map (HYB map) predicted amide-I bands of Aβ_25-35 in solution satisfactorily reproduce experimental observation, and indicate the preference of forming β-sheet and random coil structure for Aβ_25-35 in D₂O just as the results of cluster analysis suggested. These maps with secondary structural sensitivity and amino acid residue specificity open up a way for the interpretation of amide-I vibrations and show their potentials in the understanding of molecular structure of polypeptides in solution.

Insight into the internal structure of amyloid-β oligomers by isotope-edited Fourier transform infrared spectroscopy

Isotope-edited infrared spectroscopy reveals the structural unit of amyloid-β oligomers.

Computing infrared spectra of proteins using the exciton model

The ability to compute from first principles the infrared spectrum of a protein in solution phase representing a biological system would provide a useful connection to atomistic models of protein structure and dynamics. Indeed, such calculations are a vital complement to 2DIR experimental measurements, allowing the observed signals to be interpreted in terms of detailed structural and dynamical information. In this article, we have studied nine structurally and spectroscopically well-characterized proteins, representing a range of structural types. We have simulated the equilibrium conformational dynamics in an explicit point charge water model. Using the resulting trajectories based on MD simulations, we have computed the one and two dimensional infrared spectra in the Amide I region, using an exciton approach, in which a local mode basis of carbonyl stretches is considered. The role of solvent in shifting the Amide I band (by 30 to 50 cm-1 ) is clearly evident. Similarly, the conformational dynamics contribute to the broadening of peaks in the spectrum. The inhomogeneous broadening in both the 1D and 2D spectra reflects the significant conformational diversity observed in the simulations. Through the computed 2D cross-peak spectra, we show how different pulse schemes can provide additional information on the coupled vibrations. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Assessing Spectral Simulation Protocols for the Amide I Band of Proteins

We present a benchmark study of spectral simulation protocols for the amide I band of proteins. The amide I band is widely used in infrared spectroscopy of proteins due to the large signal intensity, high sensitivity to hydrogen bonding, and secondary structural motifs. This band has, thus, proven valuable in many studies of protein structure-function relationships. We benchmark spectral simulation protocols using two common force fields in combination with several electrostatic mappings and coupling models. The results are validated against experimental linear absorption and two-dimensional infrared spectroscopy for three well-studied proteins. We find two-dimensional infrared spectroscopy to be much more sensitive to the simulation protocol than linear absorption and report on the best simulation protocols. The findings demonstrate that there is still room for ideas to improve the existing models for the amide I band of proteins.

Application of two-dimensional infrared spectroscopy to benchmark models for the amide I band of proteins

In this paper, we present a novel benchmarking method for validating the modelling of vibrational spectra for the amide I region of proteins. We use the linear absorption spectra and two-dimensional infrared spectra of four experimentally well-studied proteins as a reference and test nine combinations of molecular dynamics force fields, vibrational frequency mappings, and coupling models. We find that two-dimensional infrared spectra provide a much stronger test of the models than linear absorption does. The best modelling approach in the present study still leaves significant room for future improvement. The presented benchmarking scheme, thus, provides a way of validating future protocols for modelling the amide I band in proteins.

Isotope-enriched protein standards for computational amide I spectroscopy

We present a systematic isotope labeling study of the protein G mutant NuG2b as a step toward the production of reliable, structurally stable, experimental standards for amide I infrared spectroscopic simulations. By introducing isotope enriched amino acids into a minimal growth medium during bacterial expression, we induce uniform labeling of the amide bonds following specific amino acids, avoiding the need for chemical peptide synthesis. We use experimental data to test several common amide I frequency maps and explore the influence of various factors on map performance. Comparison of the predicted absorption frequencies for the four maps tested with empirical assignments to our experimental spectra yields a root-mean-square error of 6-12 cm(-1), with outliers of at least 12 cm(-1) in all models. This means that the predictions may be useful for predicting general trends such as changes in hydrogen bonding configuration; however, for finer structural constraints or absolute frequency assignments, the models are unreliable. The results indicate the need for careful testing of existing literature maps and shed light on possible next steps for the development of quantitative spectral maps.

General Applicable Frequency Map for the Amide-I Mode in β-Peptides

In this work, a general applicable amide-I vibrational frequency map (GA map) for β-peptides in a number of common solvents was constructed, based on a peptide derivative, N-ethylpropionamide (NEPA). The map utilizes force fields at the ab initio computational level to accurately describe molecular structure and solute-solvent interactions, and also force fields at the molecular mechanics level to take into account long-range solute-solvent interactions. The results indicate that the GA map works reasonably for mapping the vibrational frequencies of the amide-I local-modes for β-peptides, holding promises for understanding the complicated infrared spectra of the amide-I mode in β-polypeptides.

Solvent induced conformational fluctuation of alanine dipeptide studied by using vibrational probes

The solvation effect on the three dimensional structure and the vibrational feature of alanine dipeptide (ALAD) was evaluated by applying the implicit solvents from polarizable continuum solvent model (PCM) through ab initio calculations, by using molecular dynamic (MD) simulations with explicit solvents, and by combining these two approaches. The implicit solvent induced potential energy fluctuations of ALAD in CHCl3, DMSO and H2O are revealed by means of ab initio calculations, and a global view of conformational and solvation environmental dependence of amide I frequencies is achieved. The results from MD simulations with explicit solvents show that ALAD trends to form PPII, αL, αR, and C5 in water, PPII and C5 in DMSO, and C5 in CHCl3, ordered by population, and the demonstration of the solvated structure, the solute-solvent interaction and hydrogen bonding is therefore enhanced. Representative ALAD-solvent clusters were sampled from MD trajectories and undergone ab initio calculations. The explicit solvents reveal the hydrogen bonding between ALAD and solvents, and the correlation between amide I frequencies and the CO bond length is built. The implicit solvents applied to the ALAD-solvent clusters further compensate the solvation effect from the bulk, and thus enlarge the degree of structural distortion and the amide I frequency red shift. The combination of explicit solvent in the first hydration shell and implicit solvent in the bulk is helpful for our understanding about the conformational fluctuation of solvated polypeptides through vibrational probes.

Empirical maps for the calculation of amide I vibrational spectra of proteins from classical molecular dynamics simulations

New sets of parameters (maps) for calculating amide I vibrational spectra for proteins through a vibrational exciton model are proposed. The maps are calculated as a function of electric field and van der Waals forces on the atoms of peptide bonds, taking into account the full interaction between peptide bonds and the surrounding environment. The maps are designed to be employed using data obtained from standard all-atom molecular simulations without any additional constraints on the system. Six proteins representing a wide range of sizes and secondary structure complexity were chosen as a test set. Spectra calculated for these proteins reproduce experimental data both qualitatively and quantitatively. The proposed maps lead to spectra that capture the weak second peak observed in proteins containing β-sheets, allowing for clear distinction between α-helical and β-sheet proteins. While the parametrization is specific to the CHARMM force field, the methodology presented can be readily applied to any empirical force field.

Vibrational solvatochromism: towards systematic approach to modeling solvation phenomena

Vibrational solvatochromic frequency shift of IR probe is an effect of interaction between local electric field and IR probe in condensed phases. Despite prolonged efforts to develop empirical maps for vibrational frequency shifts and transition dipoles of IR probes, a systematic approach to ab initio calculation of vibrational solvatochromic charges and multipoles has not been developed. Here, we report on density functional theory (DFT) calculations of N-methylacetamide (NMA) frequency shifts using implicit and coarse-grained models. The solvatochromic infrared spectral shifts are estimated based on the distributed multipole analysis of electronic densities calculated for gas-phase equilibrium structure of NMA. Thus obtained distributed solvatochromic multipole parameters are used to calculate the amide I vibrational frequency shifts of NMA in water clusters that mimic the instantaneous configurations of the liquid water. Our results indicate that the spectral shifts are primarily electrostatic in nature and can be quantitatively reproduced using the proposed model with semi-quantitative accuracy when compared to the corresponding DFT results.

Molecular mechanics force field-based general map for the solvation effect on amide I probe of peptide in different micro-environments

A general electrostatic potential map based on molecular mechanics force field for modeling the amide I frequency is presented. This map is applied to N-methylacetamide (NMA) and designed to be transferable in different micro-environments. The electrostatic potentials from solvent and peptide side chain are projected on the amide unit of NMA to induce the frequency shift of amide I mode. It is shown that the predicted amide I frequency reproduces the experimental data satisfactorily, especially when NMA in polar solvents. The amide I frequency shift is largely determined by the solvents in aqueous solution while it is dominated by the local structure of peptide in other solvent environments. The map parameters are further applied on NMA-MeOH system and the obtained IR spectra show doublet peak profile with negligible deviation from the experimental data, suggesting the usefulness of this general map for providing information about vibrational parameters of amide motions of peptide in different environments.

Electrostatic frequency shifts in amide I vibrational spectra: direct parameterization against experiment

The interpretation of protein amide I infrared spectra has been greatly assisted by the observation that the vibrational frequency of a peptide unit reports on its local electrostatic environment. However, the interpretation of spectra remains largely qualitative due to a lack of direct quantitative connections between computational models and experimental data. Here, we present an empirical parameterization of an electrostatic amide I frequency map derived from the infrared absorption spectra of 28 dipeptides. The observed frequency shifts are analyzed in terms of the local electrostatic potential, field, and field gradient, evaluated at sites near the amide bond in molecular dynamics simulations. We find that the frequency shifts observed in experiment correlate very well with the electric field in the direction of the C=O bond evaluated at the position of the amide oxygen atom. A linear best-fit mapping between observed frequencies and electric field yield sample standard deviations of 2.8 and 3.7 cm(-1) for the CHARMM27 and OPLS-AA force fields, respectively, and maximum deviations (within our data set) of 9 cm(-1). These results are discussed in the broader context of amide I vibrational models and the effort to produce quantitative agreement between simulated and experimental absorption spectra.