Two-dimensional stimulated resonance Raman spectroscopy study of the Trp-cage peptide folding

Effect of Main and Side Chains on the Folding Mechanism of the Trp-Cage Miniprotein

Proteins that do not fold into their functional native state have been linked to diseases. In this study, the influence of the main and side chains of individual amino acids on the folding of the tryptophan cage (Trp-cage), a designed 20-residue miniprotein, was analyzed. For this purpose, we calculated the solvation free energy (SFE) contributions of individual atoms by using the 3D-reference interaction site model with the atomic decomposition method. The mechanism by which the Trp-cage is stabilized during the folding process was examined by calculating the total energy, which is the sum of the conformational energy and SFE. The folding process of the Trp-cage resulted in a stable native state, with a total energy that was 62.4 kcal/mol lower than that of the unfolded state. The solvation entropy, which is considered to be responsible for the hydrophobic effect, contributed 31.3 kcal/mol to structural stabilization. In other words, the contribution of the solvation entropy accounted for approximately half of the total contribution to Trp-cage folding. The hydrophobic core centered on Trp6 contributed 15.6 kcal/mol to the total energy, whereas the solvation entropy contribution was 6.3 kcal/mol. The salt bridge formed by the hydrophilic side chains of Asp9 and Arg16 contributed 10.9 and 5.0 kcal/mol, respectively. This indicates that not only the hydrophobic core but also the salt bridge of the hydrophilic side chains gain solvation entropy and contribute to stabilizing the native structure of the Trp-cage.

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.

Ultrafast stimulated resonance Raman signatures of lithium polysulfides for shuttling effect characterization: An ab initio study

The shuttling effect is a crucial obstacle to the practical deployment of lithium sulfur batteries (LSBs). This can be ascribed to the generation of lithium polysulfide (LiPS) redox intermediates that are soluble in the electrolyte. The detailed mechanism of the shuttling, including the chemical structures responsible for the loss of effective mass and the dynamics/kinetics of the redox reactions, are not clear so far. To obtain this microscopic information, characterization techniques with high spatial and temporal resolutions are required. Here, we propose that resonance Raman spectroscopy combined with ultrafast broadband pulses is a powerful tool to reveal the mechanism of the shuttling effect. By combining the chemical bond level spatial resolution of resonance Raman and the femtosecond scale temporal resolution of the ultrafast pulses, this novel technique holds the potential of capturing the spectroscopic fingerprints of the LiPS intermediates during the working stages of LSBs. Using ab initio simulations, we show that, in addition to the excitation energy selective enhancement, resonance Raman signals of different LiPS intermediates are also characteristic and distinguishable. These results will facilitate the real-time in situ monitoring of LiPS species and reveal the underlying mechanism of the shuttling effect.

CORE-MD II: A fast, adaptive, and accurate enhanced sampling method

In this paper, we present a fast and adaptive correlation guided enhanced sampling method (CORE-MD II). The CORE-MD II technique relies, in part, on partitioning of the entire pathway into short trajectories that we refer to as instances. The sampling within each instance is accelerated by adaptive path-dependent metadynamics simulations. The second part of this approach involves kinetic Monte Carlo (kMC) sampling between the different states that have been accessed during each instance. Through the combination of the partition of the total simulation into short non-equilibrium simulations and the kMC sampling, the CORE-MD II method is capable of sampling protein folding without any a priori definitions of reaction pathways and additional parameters. In the validation simulations, we applied the CORE-MD II on the dialanine peptide and the folding of two peptides: TrpCage and TrpZip2. In a comparison with long time equilibrium Molecular Dynamics (MD), 1 µs replica exchange MD (REMD), and CORE-MD I simulations, we find that the level of convergence of the CORE-MD II method is improved by a factor of 8.8, while the CORE-MD II method reaches acceleration factors of ∼120. In the CORE-MD II simulation of TrpZip2, we observe the formation of the native state in contrast to the REMD and the CORE-MD I simulations. The method is broadly applicable for MD simulations and is not restricted to simulations of protein folding or even biomolecules but also applicable to simulations of protein aggregation, protein signaling, or even materials science simulations.

A Hybrid Hamiltonian for the Accelerated Sampling along Experimental Restraints

In this article, we present an enhanced sampling method based on a hybrid Hamiltonian which combines experimental distance restraints with a bias dependent from multiple path-dependent variables. This simulation method determines the bias-coordinates on the fly and does not require a priori knowledge about reaction coordinates. The hybrid Hamiltonian accelerates the sampling of proteins, and, combined with experimental distance information, the technique considers the restraints adaptively and in dependency of the system's intrinsic dynamics. We validate the methodology on the dipole relaxation of two water models and the conformational landscape of dialanine. Using experimental NMR-restraint data, we explore the folding landscape of the TrpCage mini-protein and in a second example apply distance restraints from chemical crosslinking/mass spectrometry experiments for the sampling of the conformation space of the Killer Cell Lectin-like Receptor Subfamily B Member 1A (NKR-P1A). The new methodology has the potential to adaptively introduce experimental restraints without affecting the conformational space of the system along an ergodic trajectory. Since only a limited number of input- and no-order parameters are required for the setup of the simulation, the method is broadly applicable and has the potential to be combined with coarse-graining methods.

Enriched Conformational Sampling of DNA and Proteins with a Hybrid Hamiltonian Derived from the Protein Data Bank

In this article, we present a method for the enhanced molecular dynamics simulation of protein and DNA systems called potential of mean force (PMF)-enriched sampling. The method uses partitions derived from the potentials of mean force, which we determined from DNA and protein structures in the Protein Data Bank (PDB). We define a partition function from a set of PDB-derived PMFs, which efficiently compensates for the error introduced by the assumption of a homogeneous partition function from the PDB datasets. The bias based on the PDB-derived partitions is added in the form of a hybrid Hamiltonian using a renormalization method, which adds the PMF-enriched gradient to the system depending on a linear weighting factor and the underlying force field. We validated the method using simulations of dialanine, the folding of TrpCage, and the conformational sampling of the Dickerson⁻Drew DNA dodecamer. Our results show the potential for the PMF-enriched simulation technique to enrich the conformational space of biomolecules along their order parameters, while we also observe a considerable speed increase in the sampling by factors ranging from 13.1 to 82. The novel method can effectively be combined with enhanced sampling or coarse-graining methods to enrich conformational sampling with a partition derived from the PDB.

An adaptive bias - hybrid MD/kMC algorithm for protein folding and aggregation

In this paper, we present a novel hybrid Molecular Dynamics/kinetic Monte Carlo (MD/kMC) algorithm and apply it to protein folding and aggregation in explicit solvent. The new algorithm uses a dynamical definition of biases throughout the MD component of the simulation, normalized in relation to the unbiased forces. The algorithm guarantees sampling of the underlying ensemble in dependency of one average linear coupling factor 〈α〉_τ. We test the validity of the kinetics in simulations of dialanine and compare dihedral transition kinetics with long-time MD-simulations. We find that for low 〈α〉_τ values, kinetics are in good quantitative agreement. In folding simulations of TrpCage and TrpZip4 in explicit solvent, we also find good quantitative agreement with experimental results and prior MD/kMC simulations. Finally, we apply our algorithm to study growth of the Alzheimer Amyloid Aβ 16-22 fibril by monomer addition. We observe two possible binding modes, one at the extremity of the fibril (elongation) and one on the surface of the fibril (lateral growth), on timescales ranging from ns to 8 μs.

Identifying Cu(ii)-amyloid peptide binding intermediates in the early stages of aggregation by resonance Raman spectroscopy: a simulation study

The aggregation of amyloid beta (Aβ) peptides plays a crucial role in the pathology and etiology of Alzheimer's disease. Experimental evidence shows that copper ion is an aggregation-prone species with the ability to coordinately bind to Aβ and further induce the formation of neurotoxic Aβ oligomers. However, the detailed structures of Cu(ii)-Aβ complexes have not been illustrated, and the kinetics and dynamics of the Cu(ii) binding are not well understood. Two Cu(ii)-Aβ complexes have been proposed to exist under physiological conditions, and another two might exist at higher pH values. By using ab initio simulations for the spontaneous resonance Raman and time domain stimulated resonance Raman spectroscopy signals, we obtained the characteristic Raman vibronic features of each complex. These signals contain rich structural information with high temporal resolution, enabling the characterization of transient states during the fast Cu-Aβ binding and interconversion processes.

Three-dimensional attosecond resonant stimulated X-ray Raman spectroscopy of electronic excitations in core-ionized glycine

We investigate computationally the valence electronic excitations of the amino acid glycine prepared by a sudden nitrogen core ionization induced by an attosecond X-ray pump pulse. The created superposition of cationic excited states is probed by two-dimensional transient X-ray absorption and by three dimensional attosecond stimulated X-ray Raman signals. The latter, generated by applying a second broadband X-ray pulse combined with a narrowband pulse tuned to the carbon K-edge, reveal the complex coupling between valence and core-excited manifolds of the cation.

Finite element analysis of minimal invasive transforaminal lumbar interbody fusion

The purpose of our study is to develop and validate three-dimensional finite element models of transforaminal lumbar interbody fusion, and explore the most appropriate method of fixation and fusion by comparing biomechanical characteristics of different fixation method. We developed four fusion models: bilateral pedicle screws fixation with a single cage insertion model (A), bilateral pedicle screws fixation with two cages insertion model (B), unilateral pedicle screws fixation with a single cage insertion model (C), and unilateral pedicle screws fixation with two cages insertion model (D); the models were subjected to different forces including anterior bending, posterior extension, left bending, right bending, rotation, and axial compressive. The von Mises stress of the fusion segments on the pedicle screw and cages was recorded. Angular variation and stress of pedicle screw and cage were compared. There were differences of Von Mises peak stress among four models, but were within the range of maximum force. The angular variation in A, B, C, and D decreased significantly compared with normal. There was no significant difference of angular variation between A and B, and C and D. Bilateral pedicle screws fixation had more superior biomechanics than unilateral pedicle screws fixation. In conclusion, the lumbar interbody fusion models were established using varying fixation methods, and the results verified that unilateral pedicle screws fixation with a single cage could meet the stability demand in minimal invasive transforaminal interbody fusion.

Signatures of the Protein Folding Pathway in Two-Dimensional Ultraviolet Spectroscopy

The function of protein relies on their folding to assume the proper structure. Probing the structural variations during the folding process is crucial for understanding the underlying mechanism. We present a combined quantum mechanics/molecular dynamics simulation study that demonstrates how coherent resonant nonlinear ultraviolet spectra can be used to follow the fast folding dynamics of a mini-protein, Trp-cage. Two dimensional ultraviolet signals of the backbone transitions carry rich information of both local (secondary) and global (tertiary) structures. The complexity of signals decreases as the conformational entropy decreases in the course of the folding process. We show that the approximate entropy of the signals provides a quantitative marker of protein folding status, accessible by both theoretical calculations and experiments.

A hybrid MD-kMC algorithm for folding proteins in explicit solvent

We present a novel hybrid MD-kMC algorithm that is capable of efficiently folding proteins in explicit solvent. We apply this algorithm to the folding of a small protein, Trp-Cage. Different kMC move sets that capture different possible rate limiting steps are implemented. The first uses secondary structure formation as a relevant rate event (a combination of dihedral rotations and hydrogen-bonding formation and breakage). The second uses tertiary structure formation events through formation of contacts via translational moves. Both methods fold the protein, but via different mechanisms and with different folding kinetics. The first method leads to folding via a structured helical state, with kinetics fit by a single exponential. The second method leads to folding via a collapsed loop, with kinetics poorly fit by single or double exponentials. In both cases, folding times are faster than experimentally reported values, The secondary and tertiary move sets are integrated in a third MD-kMC implementation, which now leads to folding of the protein via both pathways, with single and double-exponential fits to the rates, and to folding rates in good agreement with experimental values. The competition between secondary and tertiary structure leads to a longer search for the helix-rich intermediate in the case of the first pathway, and to the emergence of a kinetically trapped long-lived molten-globule collapsed state in the case of the second pathway. The algorithm presented not only captures experimentally observed folding intermediates and kinetics, but yields insights into the relative roles of local and global interactions in determining folding mechanisms and rates.