Coherent multidimensional vibrational spectroscopy of biomolecules: concepts, simulations, and challenges

Unraveling dynamic protein structures by two-dimensional infrared spectra with a pretrained machine learning model

Dynamic protein structures are crucial for deciphering their diverse biological functions. Two-dimensional infrared (2DIR) spectroscopy stands as an ideal tool for tracing rapid conformational evolutions in proteins. However, linking spectral characteristics to dynamic structures poses a formidable challenge. Here, we present a pretrained machine learning model based on 2DIR spectra analysis. This model has learned signal features from approximately 204,300 spectra to establish a "spectrum-structure" correlation, thereby tracing the dynamic conformations of proteins. It excels in accurately predicting the dynamic content changes of various secondary structures and demonstrates universal transferability on real folding trajectories spanning timescales from microseconds to milliseconds. Beyond exceptional predictive performance, the model offers attention-based spectral explanations of dynamic conformational changes. Our 2DIR-based pretrained model is anticipated to provide unique insights into the dynamic structural information of proteins in their native environments.

A New Gramicidin S Analogue with Potent Antibacterial Activity and Negligible Hemolytic Toxicity

Antibiotic resistance is an urgent threat to global health, with the decreasing efficacy of conventional drugs underscoring the urgency for innovative therapeutic strategies. Antimicrobial peptides present as promising alternatives to conventional antibiotics. Gramicidin S is one such naturally occurring antimicrobial peptide that is effective against Staphylococcus aureus, with a minimum inhibitory concentration (MIC) of 4 μg/mL (3.6 μM). Despite this potent activity, its significant hemolytic toxicity restricts its clinical use to topical applications. Herein, we present rational modifications to the key β-strand and β-turn regions of gramicidin S to concurrently mitigate hemolytic effects, while maintaining potency. Critically, peptide 9 displayed negligible hemolytic toxicity, while possessing significant antibacterial potency against a panel of methicillin-sensitive and methicillin-resistant S. aureus clinical isolates (MIC of 8 μg/mL, 7.2 μM). Given the substantial antibacterial activity and near absence of cytotoxicity, 9 presents as a potential candidate for systemic administration in the treatment of S. aureus bacteremia/sepsis.

Beyond the Condon limit: Condensed phase optical spectra from atomistic simulations

While dark transitions made bright by molecular motions determine the optoelectronic properties of many materials, simulating such non-Condon effects in condensed phase spectroscopy remains a fundamental challenge. We derive a Gaussian theory to predict and analyze condensed phase optical spectra beyond the Condon limit. Our theory introduces novel quantities that encode how nuclear motions modulate the energy gap and transition dipole of electronic transitions in the form of spectral densities. By formulating the theory through a statistical framework of thermal averages and fluctuations, we circumvent the limitations of widely used microscopically harmonic theories, allowing us to tackle systems with generally anharmonic atomistic interactions and non-Condon fluctuations of arbitrary strength. We show how to calculate these spectral densities using first-principles simulations, capturing realistic molecular interactions and incorporating finite-temperature, disorder, and dynamical effects. Our theory accurately predicts the spectra of systems known to exhibit strong non-Condon effects (phenolate in various solvents) and reveals distinct mechanisms for electronic peak splitting: timescale separation of modes that tune non-Condon effects and spectral interference from correlated energy gap and transition dipole fluctuations. We further introduce analysis tools to identify how intramolecular vibrations, solute-solvent interactions, and environmental polarization effects impact dark transitions. Moreover, we prove an upper bound on the strength of cross correlated energy gap and transition dipole fluctuations, thereby elucidating a simple condition that a system must follow for our theory to accurately predict its spectrum.

Galván I, Alavi A, Aleotti F, Aquilante F, Autschbach J, Avagliano D, Baiardi A, Bao JJ, Battaglia S, Birnoschi L, Blanco-González A, Bokarev SI, Broer R, Cacciari R, Calio PB, Carlson RK, Carvalho Couto R, Cerdán L, Chibotaru LF, Chilton NF, Church JR, Conti I, Coriani S, Cuéllar-Zuquin J, Daoud RE, Dattani N, Decleva P, de Graaf C, Delcey M, De Vico L, Dobrautz W, Dong SS, Feng R, Ferré N, Filatov(Gulak) M, Gagliardi L, Garavelli M, González L, Guan Y, Guo M, Hennefarth MR, Hermes MR, Hoyer CE, Huix-Rotllant M, Jaiswal VK, Kaiser A, Kaliakin DS, Khamesian M, King DS, Kochetov V, Krośnicki M, Kumaar AA, Larsson ED, Lehtola S, Lepetit MB, Lischka H, López Ríos P, Lundberg M, Ma D, Mai S, Marquetand P, Merritt ICD, Montorsi F, Mörchen M, Nenov A, Nguyen VHA, Nishimoto Y, Oakley MS, Olivucci M, Oppel M, Padula D, Pandharkar R, Phung QM, Plasser F, Raggi G, Rebolini E, Reiher M, Rivalta I, Roca-Sanjuán D, Romig T, Safari AA, Sánchez-Mansilla A, Sand AM, Schapiro I, Scott TR, Segarra-Martí J, Segatta F, Sergentu DC, Sharma P, Shepard R, Shu Y, Staab JK, Straatsma TP, Sørensen LK, Tenorio BNC, Truhlar DG, Ungur L, Vacher M, Veryazov V, Voß TA, Weser O, Wu D, Yang X, Yarkony D, Zhou C, Zobel JP, Lindh R. The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry

The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments span a wide range of topics in computational chemistry and are presented in thematic sections: electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report offers an overview of the chemical phenomena and processes OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations.

Structural Dependence of Extended Amide III Vibrations in Two-Dimensional Infrared Spectra

Two-dimensional infrared (2D-IR) spectroscopy is a powerful experimental method for probing the structure and dynamics of proteins in aqueous solution. So far, most experimental studies have focused on the amide I vibrations, for which empirical vibrational exciton models provide a means of interpreting such experiments. However, such models are largely lacking for other regions of the vibrational spectrum. To close this gap, we employ an efficient quantum-chemical methodology for the calculation of 2D-IR spectra, which is based on anharmonic theoretical vibrational spectroscopy with localized modes. We apply this approach to explore the potential of 2D-IR spectroscopy in the extended amide III region. Using calculations for a dipeptide model as well as alanine polypeptides, we show that distinct 2D-IR cross-peaks in the extended amide III region can potentially be used to distinguish α-helix and β-strand structures. We propose that the extended amide III region could be a promising target for future 2D-IR experiments.

Parameter estimation in ultrafast spectroscopy using probability theory

Ultrafast spectroscopy is a powerful technique that utilizes short pulses on the femtosecond time scale to generate and probe coherent responses in molecular systems. While the specific ultrafast methodologies vary, the most common data analysis tools rely on discrete Fourier transformation for recovering coherences that report on electronic or vibrational states and multi-exponential fitting for probing population dynamics, such as excited-state relaxation. These analysis tools are widely used due to their perceived reliability in estimating frequencies and decay rates. Here, we demonstrate that such "black box" methods for parameter estimation often lead to inaccurate results even in the absence of noise. To address this issue, we propose an alternative approach based on Bayes probability theory that simultaneously accounts for both population and coherence contributions to the signal. This Bayesian inference method offers accurate parameter estimations across a broad range of experimental conditions, including scenarios with high noise and data truncation. In contrast to traditional methods, Bayesian inference incorporates prior information about the measured signal and noise, leading to improved accuracy. Moreover, it provides estimator error bounds, enabling a systematic statistical framework for interpreting confidence in the results. By employing Bayesian inference, all parameters of a realistic model system may be accurately recovered, even in extremely challenging scenarios where Fourier and multi-exponential fitting methods fail. This approach offers a more reliable and comprehensive analysis tool for time-resolved coherent spectroscopy, enhancing our understanding of molecular systems and enabling a better interpretation of experimental data.

Two-dimensional fluorescence excitation spectroscopy: A novel technique for monitoring excited-state photophysics of molecular species with high time and frequency resolution

We propose a novel UV/Vis femtosecond spectroscopic technique, two-dimensional fluorescence-excitation (2D-FLEX) spectroscopy, which combines spectral resolution during the excitation process with exclusive monitoring of the excited-state system dynamics at high time and frequency resolution. We discuss the experimental feasibility and realizability of 2D-FLEX, develop the necessary theoretical framework, and demonstrate the high information content of this technique by simulating the 2D-FLEX spectra of a model four-level system and the Fenna-Matthews-Olson antenna complex. We show that the evolution of 2D-FLEX spectra with population time directly monitors energy transfer dynamics and can thus yield direct qualitative insight into the investigated system. This makes 2D-FLEX a highly efficient instrument for real-time monitoring of photophysical processes in polyatomic molecules and molecular aggregates.

Ab initio simulation of peak evolutions and beating maps for electronic two-dimensional signals of a polyatomic chromophore

By employing the doorway-window (DW) on-the-fly simulation protocol, we performed ab initio simulations of peak evolutions and beating maps of electronic two-dimensional (2D) spectra of a polyatomic molecule in the gas phase. As the system under study, we chose pyrazine, which is a paradigmatic example of photodynamics dominated by conical intersections (CIs). From the technical perspective, we demonstrate that the DW protocol is a numerically efficient methodology suitable for simulations of 2D spectra for a wide range of excitation/detection frequencies and population times. From the information content perspective, we show that peak evolutions and beating maps not only reveal timescales of transitions through CIs but also pinpoint the most relevant coupling and tuning modes active at these CIs.

Equation-of-Motion Methods for the Calculation of Femtosecond Time-Resolved 4-Wave-Mixing and N-Wave-Mixing Signals

Femtosecond nonlinear spectroscopy is the main tool for the time-resolved detection of photophysical and photochemical processes. Since most systems of chemical interest are rather complex, theoretical support is indispensable for the extraction of the intrinsic system dynamics from the detected spectroscopic responses. There exist two alternative theoretical formalisms for the calculation of spectroscopic signals, the nonlinear response-function (NRF) approach and the spectroscopic equation-of-motion (EOM) approach. In the NRF formalism, the system-field interaction is assumed to be sufficiently weak and is treated in lowest-order perturbation theory for each laser pulse interacting with the sample. The conceptual alternative to the NRF method is the extraction of the spectroscopic signals from the solutions of quantum mechanical, semiclassical, or quasiclassical EOMs which govern the time evolution of the material system interacting with the radiation field of the laser pulses. The NRF formalism and its applications to a broad range of material systems and spectroscopic signals have been comprehensively reviewed in the literature. This article provides a detailed review of the suite of EOM methods, including applications to 4-wave-mixing and N-wave-mixing signals detected with weak or strong fields. Under certain circumstances, the spectroscopic EOM methods may be more efficient than the NRF method for the computation of various nonlinear spectroscopic signals.

Quantum-chemical calculation of two-dimensional infrared spectra using localized-mode VSCF/VCI

Computational protocols for the simulation of two-dimensional infrared (2D IR) spectroscopy usually rely on vibrational exciton models which require an empirical parameterization. Here, we present an efficient quantum-chemical protocol for predicting static 2D IR spectra that does not require any empirical parameters. For the calculation of anharmonic vibrational energy levels and transition dipole moments, we employ the localized-mode vibrational self-consistent field (L-VSCF)/vibrational configuration interaction (L-VCI) approach previously established for (linear) anharmonic theoretical vibrational spectroscopy [P. T. Panek and C. R. Jacob, ChemPhysChem 15, 3365-3377 (2014)]. We demonstrate that with an efficient expansion of the potential energy surface using anharmonic one-mode potentials and harmonic two-mode potentials, 2D IR spectra of metal carbonyl complexes and dipeptides can be predicted reliably. We further show how the close connection between L-VCI and vibrational exciton models can be exploited to extract the parameters of such models from those calculations. This provides a novel route to the fully quantum-chemical parameterization of vibrational exciton models for predicting 2D IR spectra.

Measuring Protein Conformation at Aqueous Interfaces with 2D Infrared Spectroscopy of Emulsions

Determining the secondary and tertiary structures of proteins at aqueous interfaces is crucial for understanding their function, but measuring these structures selectively at the interface is challenging. Here we demonstrate that two-dimensional infrared (2D-IR) spectroscopy of protein stabilized emulsions offers a new route to measuring interfacial protein structure with high levels of detail. We prepared hexadecane/water oil-in-water emulsions stabilized by model LK peptides that are known to fold into either α-helix or β-sheet conformations at hydrophobic interfaces and measured 2D-IR spectra in a transmission geometry. We saw clear spectral signatures of the peptides folding at the interface, with no detectable residue from remaining bulk peptides. Using 2D spectroscopy gives us access to correlation and dynamics data, which enables structural assignment in cases where linear spectroscopy fails. Using the emulsions allows one to study interfacial spectra with standard transmission geometry spectrometers, bringing the richness of 2D-IR to the interface with no additional optical complexity.

Machine learning recognition of protein secondary structures based on two-dimensional spectroscopic descriptors

Protein secondary structure discrimination is crucial for understanding their biological function. It is not generally possible to invert spectroscopic data to yield the structure. We present a machine learning protocol which uses two-dimensional UV (2DUV) spectra as pattern recognition descriptors, aiming at automated protein secondary structure determination from spectroscopic features. Accurate secondary structure recognition is obtained for homologous (97%) and nonhomologous (91%) protein segments, randomly selected from simulated model datasets. The advantage of 2DUV descriptors over one-dimensional linear absorption and circular dichroism spectra lies in the cross-peak information that reflects interactions between local regions of the protein. Thanks to their ultrafast (∼200 fs) nature, 2DUV measurements can be used in the future to probe conformational variations in the course of protein dynamics.

Progress in infrared spectroscopy as an efficient tool for predicting protein secondary structure

Infrared (IR) spectroscopy is a highly sensitive technique that provides complete information on chemical compositions. The IR spectra of proteins or peptides give rise to nine characteristic IR absorption bands. The amide I bands are the most prominent and sensitive vibrational bands and widely used to predict protein secondary structures. The interference of H₂O absorbance is the greatest challenge for IR protein secondary structure prediction. Much effort has been made to reduce/eliminate the interference of H₂O, simplify operation steps, and increase prediction accuracy. Progress in sampling and equipment has rendered the Fourier transform infrared (FTIR) technique suitable for determining the protein secondary structure in broader concentration ranges, greatly simplifying the operating steps. This review highlights the recent progress in sample preparation, data analysis, and equipment development of FTIR in A/T mode, with a focus on recent applications of FTIR spectroscopy in the prediction of protein secondary structure. This review also provides a brief introduction of the progress in ATR-FTIR for predicting protein secondary structure and discusses some combined IR methods, such as AFM-based IR spectroscopy, that are used to analyze protein structural dynamics and protein aggregation.

iSPECTRON: A simulation interface for linear and nonlinear spectra with ab-initio quantum chemistry software

We introduce iSPECTRON, a program that parses data from common quantum chemistry software (NWChem, OpenMolcas, Gaussian, Cobramm, etc.), produces the input files for the simulation of linear and nonlinear spectroscopy of molecules with the Spectron code, and analyzes the spectra with a broad range of tools. Vibronic spectra are expressed in term of the electronic eigenstates, obtained from quantum chemistry computations, and vibrational/bath effects are incorporated in the framework of the displaced harmonic oscillator model, where all required quantities are computed at the Franck-Condon point. The program capabilities are illustrated by simulating linear absorption, transient absorption and two dimensional electronic spectra of the pyrene molecule. Calculations at two levels of electronic structure theory, time-dependent density functional theory (with NWChem) and RASSCF/RASPT2 (with OpenMolcas) are presented and compared where possible. The iSPECTRON program is available online at https://github.com/ispectrongit/iSPECTRON/ and distributed open source under the terms of the Educational Community License version 2.0 (ECL 2.0).

Rationally designed peptide-based inhibitor of Aβ42 fibril formation and toxicity: a potential therapeutic strategy for Alzheimer's disease

Amyloid beta peptide (Aβ42) aggregation in the brain is thought to be responsible for the onset of Alzheimer's disease, an insidious condition without an effective treatment or cure. Hence, a strategy to prevent aggregation and subsequent toxicity is crucial. Bio-inspired peptide-based molecules are ideal candidates for the inhibition of Aβ42 aggregation, and are currently deemed to be a promising option for drug design. In this study, a hexapeptide containing a self-recognition component unique to Aβ42 was designed to mimic the β-strand hydrophobic core region of the Aβ peptide. The peptide is comprised exclusively of D-amino acids to enhance specificity towards Aβ42, in conjunction with a C-terminal disruption element to block the recruitment of Aβ42 monomers on to fibrils. The peptide was rationally designed to exploit the synergy between the recognition and disruption components, and incorporates features such as hydrophobicity, β-sheet propensity, and charge, that all play a critical role in the aggregation process. Fluorescence assays, native ion-mobility mass spectrometry (IM-MS) and cell viability assays were used to demonstrate that the peptide interacts with Aβ42 monomers and oligomers with high specificity, leading to almost complete inhibition of fibril formation, with essentially no cytotoxic effects. These data define the peptide-based inhibitor as a potentially potent anti-amyloid drug candidate for this hitherto incurable disease.

Binding of cloned Cel enzymes on clay minerals related to the pI of the enzymes and database survey of cellulases of soil bacteria for pI

The Cel genes from Bacillus licheniformis MSB03 were cloned and expressed to investigate binding ability on clay minerals and sea sand at pH ranging 3 to 9. FTIR analysis has been done to characterize bound enzymes on clay minerals. Subsequent, surveying of NCBI database for extracellular enzymes of soil bacteria was carried out. Among the five cloned Cel enzymes assayed for binding to clay minerals, only Cel5H enzyme had the binding ability. Enzyme Cel5H exhibited highest binding to montmorillonite followed by kaolinite and sea sand. Interestingly, Cel5H had higher pI value of 9.24 than other proteins (5.2-5.7). Cel5H binding to montmorillonite was shown to be negatively affected below pH 3 and above pH 9. Infrared absorption spectra of the Cel5H-montmorillonite complexes showed distinct peaks for clay minerals and bound proteins. Furthermore, database survey of soil bacterial extracellular enzymes revealed that Bacillus species enzymes had higher pI than other soil bacterial enzymes.

Optical spectra in the condensed phase: Capturing anharmonic and vibronic features using dynamic and static approaches

Simulating optical spectra in the condensed phase remains a challenge for theory due to the need to capture spectral signatures arising from anharmonicity and dynamical effects, such as vibronic progressions and asymmetry. As such, numerous simulation methods have been developed that invoke different approximations and vary in their ability to capture different physical regimes. Here, we use several models of chromophores in the condensed phase and ab initio molecular dynamics simulations to rigorously assess the applicability of methods to simulate optical absorption spectra. Specifically, we focus on the ensemble scheme, which can address anharmonic potential energy surfaces but relies on the applicability of extreme nuclear-electronic time scale separation; the Franck-Condon method, which includes dynamical effects but generally only at the harmonic level; and the recently introduced ensemble zero-temperature Franck-Condon approach, which straddles these limits. We also devote particular attention to the performance of methods derived from a cumulant expansion of the energy gap fluctuations and test the ability to approximate the requisite time correlation functions using classical dynamics with quantum correction factors. These results provide insights as to when these methods are applicable and able to capture the features of condensed phase spectra qualitatively and, in some cases, quantitatively across a range of regimes.

A neural network protocol for electronic excitations of N-methylacetamide

UV absorption is widely used for characterizing proteins structures. The mapping of UV spectra to atomic structure of proteins relies on expensive theoretical simulations, circumventing the heavy computational cost which involves repeated quantum-mechanical simulations of excited-state properties of many fluctuating protein geometries, which has been a long-time challenge. Here we show that a neural network machine-learning technique can predict electronic absorption spectra of N-methylacetamide (NMA), which is a widely used model system for the peptide bond. Using ground-state geometric parameters and charge information as descriptors, we employed a neural network to predict transition energies, ground-state, and transition dipole moments of many molecular-dynamics conformations at different temperatures, in agreement with time-dependent density-functional theory calculations. The neural network simulations are nearly 3,000× faster than comparable quantum calculations. Machine learning should provide a cost-effective tool for simulating optical properties of proteins.

Differentiation between Enamines and Tautomerizable Imines Oxidation Reaction Mechanism using Electron-Vibration-Vibration Two Dimensional Infrared Spectroscopy

Intermediates lie at the center of chemical reaction mechanisms. However, detecting intermediates in an organic reaction and understanding its role in reaction mechanisms remains a big challenge. In this paper, we used the theoretical calculations to explore the potential of the electron-vibration-vibration two-dimensional infrared (EVV-2DIR) spectroscopy in detecting the intermediates in the oxidation reactions of enamines and tautomerizable imines with 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO). We show that while it is difficult to identify the intermediates from their infrared and Raman signals, the simulated EVV-2DIR spectra of these intermediates have well resolved spectral features, which are absent in the signals of reactants and products. These characteristic spectral signatures can, therefore, be used to reveal the reaction mechanism as well as monitor the reaction progress. Our work suggests the potential strength of EVV-2DIR technique in studying the molecular mechanism of organic reactions in general.

Multispectral multidimensional spectrometer spanning the ultraviolet to the mid-infrared

Multidimensional spectroscopy is the optical analog to nuclear magnetic resonance, probing dynamical processes with ultrafast time resolution. At optical frequencies, the technical challenges of multidimensional spectroscopy have hindered its progress until recently, where advances in laser sources and pulse-shaping have removed many obstacles to its implementation. Multidimensional spectroscopy in the visible and infrared (IR) regimes has already enabled respective advances in our understanding of photosynthesis and the structural rearrangements of liquid water. A frontier of ultrafast spectroscopy is to extend and combine multidimensional techniques and frequency ranges, which have been largely restricted to operating in the distinct visible or IR regimes. By employing two independent amplifiers seeded by a single oscillator, it is straightforward to span a wide range of time scales (femtoseconds to seconds), all of which are often relevant to the most important energy conversion and catalysis problems in chemistry, physics, and materials science. Complex condensed phase systems have optical transitions spanning the ultraviolet (UV) to the IR and exhibit dynamics relevant to function on time scales of femtoseconds to seconds and beyond. We describe the development of the Multispectral Multidimensional Nonlinear Spectrometer (MMDS) to enable studies of dynamical processes in atomic, molecular, and material systems spanning femtoseconds to seconds, from the UV to the IR regimes. The MMDS employs pulse-shaping methods to provide an easy-to-use instrument with an unprecedented spectral range that enables unique combination spectroscopies. We demonstrate the multispectral capabilities of the MMDS on several model systems.

Signatures of vibronic coupling in two-dimensional electronic-vibrational and vibrational-electronic spectroscopies

Two-Dimensional Electronic-Vibrational (2D EV) spectroscopy and Two-Dimensional Vibrational-Electronic (2D VE) spectroscopy are new coherent four-wave mixing spectroscopies that utilize both electronically resonant and vibrationally resonant field-matter interactions to elucidate couplings between electronic and vibrational degrees of freedom. A system Hamiltonian is developed here to lay a foundation for interpreting the 2D EV and 2D VE signals that arise from a vibronically coupled molecular system in the condensed phase. A molecular system consisting of one anharmonic vibration and two electronic states is modeled. Equilibrium displacement of the vibrational coordinate and vibrational frequency shifts upon excitation to the first electronic excited state are included in our Hamiltonian through linear and quadratic vibronic coupling terms. We explicitly consider the nuclear dependence of the electronic transition dipole moment and demonstrate that these spectroscopies are sensitive to non-Condon effects. A series of simulations of 2D EV and 2D VE spectra obtained by varying parameters of the system, system-bath, and interaction Hamiltonians demonstrate that one of the following conditions must be met to observe signals: (1) non-zero linear and/or quadratic vibronic coupling in the electronic excited state, (2) vibrational-coordinate dependence of the electronic transition dipole moment, or (3) electronic-state-dependent vibrational dephasing dynamics. We explore how these vibronic interactions are manifested in the positions, amplitudes, and line shapes of the peaks in 2D EV and 2D VE spectroscopies.

Peptides as Bio-inspired Molecular Electronic Materials

Understanding the electronic properties of single peptides is not only of fundamental importance to biology, but it is also pivotal to the realization of bio-inspired molecular electronic materials. Natural proteins have evolved to promote electron transfer in many crucial biological processes. However, their complex conformational nature inhibits a thorough investigation, so in order to study electron transfer in proteins, simple peptide models containing redox active moieties present as ideal candidates. Here we highlight the importance of secondary structure characteristic to proteins/peptides, and its relevance to electron transfer. The proposed mechanisms responsible for such transfer are discussed, as are details of the electrochemical techniques used to investigate their electronic properties. Several factors that have been shown to influence electron transfer in peptides are also considered. Finally, a comprehensive experimental and theoretical study demonstrates that the electron transfer kinetics of peptides can be successfully fine tuned through manipulation of chemical composition and backbone rigidity. The methods used to characterize the conformation of all peptides synthesized throughout the study are outlined, along with the various approaches used to further constrain the peptides into their geometric conformations. The aforementioned sheds light on the potential of peptides to one day play an important role in the fledgling field of molecular electronics.

Multi-heterodyne two dimensional coherent spectroscopy using frequency combs

Optical multi-dimensional coherent spectroscopy is a powerful technique for studying the structure, properties and ultrafast dynamics of atoms, molecules, semiconductor materials and complex systems. Current implementations of multi-dimensional coherent spectroscopy have long acquisition times and/or limited spectral resolution. In addition, most of the techniques utilize complex geometries or phase cycling schemes to isolate non-linear signals. We demonstrate a novel approach of using frequency combs to perform rapid, high resolution and background free multi-dimensional coherent spectroscopy of semiconductor materials. Our approach is inspired by dual-comb spectroscopy, which has been proven to be a versatile tool for obtaining one dimensional absorption spectra with high resolution in a short acquisition time. We demonstrate the method using a GaAs multi-quantum well sample.

On the Simulation of Two-dimensional Electronic Spectroscopy of Indole-containing Peptides

A benchmark study of low-cost multiconfigurational CASSCF/CASPT2 schemes for computing the electronic structure of indole is presented. This facilitates the simulation of near-ultraviolet (UV) pump visible (VIS) probe (i.e. two-color) two-dimensional electronic spectra (2DES) of homo- and hetero-aggregates as well as for processing of multiple snapshots from molecular dynamics simulations. Fingerprint excited-state absorption signatures of indole are identified in a broad spectral window between 10 and 25 k cm^-1 . The 18-24 k cm^-1 spectral window which has no absorption of the monomer and noninteracting aggregates is ideally suited to embed charge-transfer signatures in stacked aggregates. The small peptide Trp-cage, containing a tryptophan and a tyrosine amino acids, having indole and phenol as side chains, respectively, serves to prove the concept. Clear charge-transfer signatures are found in the proposed spectral window for an interchromophore distance of 5 Å making near-UV pump VIS probe 2DES a suitable technique for resolving closely packed aggregates. We demonstrate that 2DES utilizing ultra-short pulses has the potential to resolve the nature of the spectroscopically resolved electronic states and that the line shapes of the excited-state absorption signals can be correlated to the polarity of the relevant states.

A weight averaged approach for predicting amide vibrational bands of a sphingomyelin bilayer

Infrared (IR) and Raman spectra of a sphingomyelin (SM) bilayer have been calculated for the amide I, II and A modes and the double-bonded CC stretching mode by a weight averaged approach, based on an all-atom molecular dynamics (MD) simulation and a vibrational structure calculation. Representative structures and statistical weights of SM clusters connected by hydrogen bonds (HBs) are observed in MD trajectories. After constructing smaller fragments from the SM clusters, the vibrational spectra of the target modes were calculated by normal mode analysis with a correction for anharmonicity, using density functional theory. The final IR and Raman spectra of a SM bilayer were obtained as the weight averages over all SM clusters. The calculated Raman spectrum is in excellent agreement with a recent measurement, providing a clear assignment of the peak in question observed at 1643 cm(-1) to the amide I modes of a SM bilayer. The analysis of the IR spectrum has also revealed that the amide bands are sensitive to the water content inside the membrane, since their band positions are strongly modulated by the HB between SM and water molecules. The present study suggests that the amide I band serves as a marker to identify the formation of SM clusters, and opens a new way to detect lipid rafts in the biological membrane.

From Ultrafast Structure Determination to Steering Reactions: Mixed IR/Non-IR Multidimensional Vibrational Spectroscopies

Ultrafast multidimensional infrared spectroscopy is a powerful method for resolving features of molecular structure and dynamics that are difficult or impossible to address with linear spectroscopy. Augmenting the IR pulse sequences by resonant or nonresonant UV, Vis, or NIR pulses considerably extends the range of application and creates techniques with possibilities far beyond a pure multidimensional IR experiment. These include surface-specific 2D-IR spectroscopy with sub-monolayer sensitivity, ultrafast structure determination in non-equilibrium systems, triggered exchange spectroscopy to correlate reactant and product bands, exploring the interplay of electronic and nuclear degrees of freedom, investigation of interactions between Raman- and IR-active modes, imaging with chemical contrast, sub-ensemble-selective photochemistry, and even steering a reaction by selective IR excitation. We give an overview of useful mixed IR/non-IR pulse sequences, discuss their differences, and illustrate their application potential.

Modeling the high-energy electronic state manifold of adenine: Calibration for nonlinear electronic spectroscopy

Pump-probe electronic spectroscopy using femtosecond laser pulses has evolved into a standard tool for tracking ultrafast excited state dynamics. Its two-dimensional (2D) counterpart is becoming an increasingly available and promising technique for resolving many of the limitations of pump-probe caused by spectral congestion. The ability to simulate pump-probe and 2D spectra from ab initio computations would allow one to link mechanistic observables like molecular motions and the making/breaking of chemical bonds to experimental observables like excited state lifetimes and quantum yields. From a theoretical standpoint, the characterization of the electronic transitions in the visible (Vis)/ultraviolet (UV), which are excited via the interaction of a molecular system with the incoming pump/probe pulses, translates into the determination of a computationally challenging number of excited states (going over 100) even for small/medium sized systems. A protocol is therefore required to evaluate the fluctuations of spectral properties like transition energies and dipole moments as a function of the computational parameters and to estimate the effect of these fluctuations on the transient spectral appearance. In the present contribution such a protocol is presented within the framework of complete and restricted active space self-consistent field theory and its second-order perturbation theory extensions. The electronic excited states of adenine have been carefully characterized through a previously presented computational recipe [Nenov et al., Comput. Theor. Chem. 1040-1041, 295-303 (2014)]. A wise reduction of the level of theory has then been performed in order to obtain a computationally less demanding approach that is still able to reproduce the characteristic features of the reference data. Foreseeing the potentiality of 2D electronic spectroscopy to track polynucleotide ground and excited state dynamics, and in particular its expected ability to provide conformational dependent fingerprints in dimeric systems, the performances of the selected reduced level of calculations have been tested in the construction of 2D electronic spectra for the in vacuo adenine monomer and the unstacked adenine homodimer, thereby exciting the Lb/La transitions with the pump pulse pair and probing in the Vis to near ultraviolet spectral window.

Two-Dimensional Vibrational Spectroscopy of a Dissipative System with the Optimized Mean-Trajectory Approximation

The optimized mean-trajectory (OMT) approximation is a semiclassical method for computing vibrational response functions from action-quantized classical trajectories connected by discrete transitions representing radiation-matter interactions. Here we apply this method to an anharmonic chromophore coupled to a harmonic bath. A forward-backward trajectory implementation of the OMT method is described that addresses the numerical challenges of applying the OMT to large systems with disparate frequency scales. The OMT is shown to well reproduce line shapes and waiting time dynamics in the pure dephasing limit of weak coupling to an off-resonant bath. The OMT is also shown to describe a case where energy transfer is the predominant source of line broadening.

Vibrational coherence and energy transfer in two-dimensional spectra with the optimized mean-trajectory approximation

The optimized mean-trajectory (OMT) approximation is a semiclassical method for computing vibrational response functions from action-quantized classical trajectories connected by discrete transitions that represent radiation-matter interactions. Here, we extend the OMT to include additional vibrational coherence and energy transfer processes. This generalized approximation is applied to a pair of anharmonic chromophores coupled to a bath. The resulting 2D spectra are shown to reflect coherence transfer between normal modes.

Vibrational ladder climbing in carboxy-hemoglobin: effects of the protein environment

We present simulations on vibrational ladder climbing in carboxy-hemoglobin. Motivated by recent experiments, we study the influence of different realistic pump probe parameters. To allow for a direct comparison with experimental results, transient absorption spectra obtained by a weak probe pulse following the strong, shaped pump pulse are calculated. The influence of the protein fluctuations is taken into account using a recently developed microscopic model. This model consists of a quantum Hamiltonian describing the CO vibration in carboxy-hemoglobin, together with a fluctuating potential, which is obtained by electronic structure calculation based on a large number of protein configurations. Using realistic pulse parameters, vibrational excitations to very high-lying states are possible, in qualitative agreement with experimental observations.

Vibrational energy transport in molecules studied by relaxation-assisted two-dimensional infrared spectroscopy

This review presents an overview of the relaxation-assisted two-dimensional infrared (RA 2DIR) spectroscopy method for measuring structures and energy transport dynamics in molecules. The method strongly enhances the range of accessible distances compared to traditional 2DIR and offers new structural reporters, such as the energy transport time, cross-peak amplification factors, and connectivity patterns. The use of the method for assigning vibrational modes with various levels of delocalization is illustrated. RA 2DIR relies on vibrational energy transport in molecules; as such, the transport mechanism can be conveniently studied by the method. Applications to identify diffusive and ballistic energy transport are demonstrated.

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.