Measurement of energy landscape roughness of folded and unfolded proteins

Interpreting forces as deep learning gradients improves quality of predicted protein structures

Protein structure predictions from deep learning models like AlphaFold2, despite their remarkable accuracy, are likely insufficient for direct use in downstream tasks like molecular docking. The functionality of such models could be improved with a combination of increased accuracy and physical intuition. We propose a new method to train deep learning protein structure prediction models using molecular dynamics force fields to work toward these goals. Our custom PyTorch loss function, OpenMM-Loss, represents the potential energy of a predicted structure. OpenMM-Loss can be applied to any all-atom representation of a protein structure capable of mapping into our software package, SidechainNet. We demonstrate our method's efficacy by finetuning OpenFold. We show that subsequently predicted protein structures, both before and after a relaxation procedure, exhibit comparable accuracy while displaying lower potential energy and improved structural quality as assessed by MolProbity metrics.

Experimental Evidence for the Role of Dynamics in pH-Dependent Enzymatic Activity

Enzymatic activity is heavily influenced by pH, but the rationale for the dynamical mechanism of pH-dependent enzymatic activity has not been fully understood. In this work, combined neutron scattering techniques, including quasielastic neutron scattering (QENS) and small angle neutron scattering (SANS), are used to study the structural and dynamic changes of a model enzyme, xylanase, under different pH and temperature environments. The QENS results reveal that xylanase at optimal pH exhibits faster relaxational dynamics and a lower energy barrier between conformational substates. The SANS results demonstrate that pH affects both xylanase's stability and monodispersity. Our findings indicate that enzymes have optimized stability and function under their optimal pH conditions, with both structure and dynamics being affected. The current study offers valuable insights into enzymatic functionality mechanisms, allowing for broad industrial applications.

Main role of fractal-like nature of conformational space in subdiffusion in proteins

Protein dynamics involves a myriad of mechanical movements happening at different time and space scales, which make it highly complex. One of the less understood features of protein dynamics is subdiffusivity, defined as sublinear dependence between displacement and time. Here, we use all-atoms molecular dynamics (MD) simulations to directly interrogate an already well-established theory and demonstrate that subdiffusivity arises from the fractal nature of the network of metastable conformations over which the dynamics, thought of as a diffusion process, takes place.

Log-periodic oscillations as real-time signatures of hierarchical dynamics in proteins

The time-dependent relaxation of a dynamical system may exhibit a power-law behavior that is superimposed by log-periodic oscillations. D. Sornette [Phys. Rep. 297, 239 (1998)] showed that this behavior can be explained by a discrete scale invariance of the system, which is associated with discrete and equidistant timescales on a logarithmic scale. Examples include such diverse fields as financial crashes, random diffusion, and quantum topological materials. Recent time-resolved experiments and molecular dynamics simulations suggest that discrete scale invariance may also apply to hierarchical dynamics in proteins, where several fast local conformational changes are a prerequisite for a slow global transition to occur. Employing entropy-based timescale analysis and Markov state modeling to a simple one-dimensional hierarchical model and biomolecular simulation data, it is found that hierarchical systems quite generally give rise to logarithmically spaced discrete timescales. By introducing a one-dimensional reaction coordinate that collectively accounts for the hierarchically coupled degrees of freedom, the free energy landscape exhibits a characteristic staircase shape with two metastable end states, which causes the log-periodic time evolution of the system. The period of the log-oscillations reflects the effective roughness of the energy landscape and can, in simple cases, be interpreted in terms of the barriers of the staircase landscape.

Selective chiral dimerization and folding driven by arene-perfluoroarene force

Oligomerization and folding of chiral compounds afford diversified chiral molecular architectures with interesting chiroptical properties, but their rational and precise control remain poorly understood. In this work, we employed arene-perfluoroarene (AP) interaction to manipulate the folding and dimerization of alanine derivatives bearing pyrene and a perfluoronaphthalene derivative. Based on X-ray crystallography and nuclear magnetic resonance, the compound with a smaller tether and high skeleton rigidity self-assembled into double helical dimers by duplex hydrogen bonding and AP forces in a less polar solvent. Reversible disassociation occurred upon switching to a dipolar solvent or applying heating-cooling cycles. In comparison, the compound with increased skeleton flexibility folds into chiral molecular clamps in a less polar solvent, and is transformed into planar dimers upon switching to a polar solvent. The dynamic geometrical transformation between dimerization and folding was accompanied by chiroptical switching. Beyond the molecular and supramolecular level, we showed hierarchy control in the self-assembled nanoarchitectures and columnar and lamellar arrangements of their molecular packing. This work utilized AP forces to prepare and manipulate the chiral architectures at different hierarchical levels, enriching methodologies in precise chiral synthetic chemistry.

On-Site Potential Creates Complexity in Systems with Disordered Coupling

We calculate the average number of critical points N[over ¯] of the energy landscape of a many-body system with disordered two-body interactions and a weak on-site potential. We find that introducing a weak nonlinear on-site potential dramatically increases N[over ¯] to exponential in system size and give a complete picture of the organization of critical points. Our results extend solvable spin-glass models to physically more realistic models and are of relevance to glassy systems, nonlinear oscillator networks, and many-body interacting systems.

Conformational landscapes of artificial peptides predicted by various force fields: are we ready to simulate β-amino acids?

With the introduction of artificial peptides as antimicrobial agents and organic catalysts, numerous efforts have been made to design foldamers with desirable structures and functions. Computational tools are a helpful proxy for revealing the dynamic structures at atomic resolution and understanding foldamer's complex structure-function relationships. However, the performance of conventional force fields in predicting the structures of artificial peptides has not been systematically evaluated. In this study, we critically assessed three popular force fields, AMBER ff14SB, CHARMM36m, and OPLS-AA/L, in predicting conformational propensities of a β-peptide foldamer at monomer and hexamer levels. Simulation results were compared to those obtained from quantum chemistry calculations and experimental data. We also utilised replica exchange molecular dynamics simulations to investigate the energy landscape of each force field and assess the similarities and differences between force fields. We compared different solvent systems in the AMBER ff14SB and CHARMM36m frameworks and confirmed the unanimous role of hydrogen bonds in shaping energy landscapes. We anticipate that our data will pave the way for further improvements to force fields and for understanding the role of solvents in peptide folding, crystallisation, and engineering.

Explicit analytical form for memory kernel in the generalized Langevin equation for end-to-end vector of Rouse chains

The generalized Langevin equation (GLE) provides an attractive theoretical framework for investigating the dynamics of conformational fluctuations of polymeric systems. While the memory kernel is a central function in the GLE, explicit analytical forms for this function have been challenging to obtain, even for the simple models of polymer dynamics. Here, we achieve an explicit analytical expression for the memory kernel in the GLE for the end-to-end vector of Rouse chains in the overdamped limit. Our derivation takes advantage of the finding that the dynamics of the end-to-end vector of Rouse chains with both free ends are equivalent to those of Rouse chains with one free end and the other fixed. For the latter model, we first show that the equations of motion of the Rouse modes as well as their statistical properties can be obtained under the boundary conditions where the free end is held fixed temporarily. We then analytically solve the terms associated with intrachain interactions in the GLE. By formally comparing these terms with the GLE based on the Rouse modes, we obtain an explicit expression for the memory kernel, along with analytical forms for the potential field and the random colored noise force. Our analytical memory kernel is confirmed by numerical calculations in the Laplace space and is shown to yield asymptotic behaviors that are consistent with previous studies. Finally, we utilize our analytical result to simulate the cyclization dynamics of Rouse chains and discuss the scaling of the cyclization time with chain length.

Monoclonal antibody stability can be usefully monitored using the excitation-energy-dependent fluorescence edge-shift

Among the major challenges in the development of biopharmaceuticals are structural heterogeneity and aggregation. The development of a successful therapeutic monoclonal antibody (mAb) requires both a highly active and also stable molecule. Whilst a range of experimental (biophysical) approaches exist to track changes in stability of proteins, routine prediction of stability remains challenging. The fluorescence red edge excitation shift (REES) phenomenon is sensitive to a range of changes in protein structure. Based on recent work, we have found that quantifying the REES effect is extremely sensitive to changes in protein conformational state and dynamics. Given the extreme sensitivity, potentially this tool could provide a ‘fingerprint’ of the structure and stability of a protein. Such a tool would be useful in the discovery and development of biopharamceuticals and so we have explored our hypothesis with a panel of therapeutic mAbs. We demonstrate that the quantified REES data show remarkable sensitivity, being able to discern between structurally identical antibodies and showing sensitivity to unfolding and aggregation. The approach works across a broad concentration range (µg–mg/ml) and is highly consistent. We show that the approach can be applied alongside traditional characterisation testing within the context of a forced degradation study (FDS). Most importantly, we demonstrate the approach is able to predict the stability of mAbs both in the short (hours), medium (days) and long-term (months). The quantified REES data will find immediate use in the biopharmaceutical industry in quality assurance, formulation and development. The approach benefits from low technical complexity, is rapid and uses instrumentation which exists in most biochemistry laboratories without modification.

Origin of subdiffusions in proteins: Insight from peptide systems

Subdiffusive kinetics are popular in proteins and peptides as observed in experiments and simulations. For protein systems with diverse interactions, are there multiple mechanisms to produce the common subdiffusion behavior? To approach this problem, long trajectories of two model peptides are simulated to study the mechanism of subdiffusion and the relations with their interactions. The free-energy profiles and the subdiffusive kinetics are observed for these two peptides. A hierarchical plateau analysis is employed to extract the features of the landscape from the mean square of displacement. The mechanism of subdiffusions can be postulated by comparing the exponents by simulations with those based on various models. The results indicate that the mechanisms of these two peptides are different and are related to the characteristics of their energy landscapes. The subdiffusion of the flexible peptide is mainly caused by depth distribution of traps on the energy landscape, while the subdiffusion of the helical peptide is attributed to the fractal topology of local minima on the landscape. The emergence of these different mechanisms reflects different kinetic scenarios in peptide systems though the peptides behave in a similar way of diffusion. To confirm these ideas, the transition networks between various conformations of these peptides are generated. Based on the network description, the controlled kinetics based only on the topology of the networks are calculated and compared with the results based on simulations. For the flexible peptide, the feature of controlled diffusion is distinct from that of simulation, and for the helical peptide, two kinds of kinetics have a similar exponent of subdiffusion. These results further exemplify the importance of the landscape topology in the kinetics of structural proteins and the effect of depth distribution of traps for the subdiffusion of disordered peptides.

Quantifying residue-specific conformational dynamics of a highly reactive 29-mer peptide

Understanding structural transitions within macromolecules remains an important challenge in biochemistry, with important implications for drug development and medicine. Insight into molecular behavior often requires residue-specific dynamics measurement at micromolar concentrations. We studied MP01-Gen4, a library peptide selected to rapidly undergo bioconjugation, by using electron paramagnetic resonance (EPR) to measure conformational dynamics. We mapped the dynamics of MP01-Gen4 with residue-specificity and identified the regions involved in a structural transformation related to the conjugation reaction. Upon reaction, the conformational dynamics of residues near the termini slow significantly more than central residues, indicating that the reaction induces a structural transition far from the reaction site. Arrhenius analysis demonstrates a nearly threefold decrease in the activation energy of conformational diffusion upon reaction (8.0 kBT to 3.4 kBT), which occurs across the entire peptide, independently of residue position. This novel approach to EPR spectral analysis provides insight into the positional extent of disorder and the nature of the energy landscape of a highly reactive, intrinsically disordered library peptide before and after conjugation.

Intraresidual Correlated Motions in Peptide Chains

We investigate the interresidual and intraresidual correlations between dihedral displacements of adjacent residues within model polyalanine peptides by analyzing extensive molecular dynamics trajectories. Correlations are evaluated individually at different residue conformations covering the whole (ϕ_i,ψ_i)-space. From these, we draw maps that unveil an unprecedented strong intramolecular correlation displaying opposite (correlated/anticorrelated) behaviors at different conformations. Both interresidual and intraresidual correlations arise from the propensity of the peptide to minimize the overall atomic displacements.

Cyclization and Relaxation Dynamics of Finite-Length Collapsed Self-Avoiding Polymers

We study the cyclization and relaxation dynamics of ideal as well as interacting polymers as a function of chain length N. For the cyclization time τ_{cyc} of ideal chains we recover the known scaling τ_{cyc}∼N^{2} for different backbone models, for a self-avoiding slightly collapsed chain we obtain from Langevin simulations and scaling theory a modified scaling τ_{cyc}∼N^{5/3}. The cyclization and relaxation dynamics of a finite-length collapsed chain scale differently; this unexpected dynamic multiscale behavior is rationalized by the crossover between swollen and collapsed chain behavior.

Universality and Specificity in Protein Fluctuation Dynamics

We investigate the universal scaling of protein fluctuation dynamics with a site-specific diffusive model of protein motion, which predicts an initial subdiffusive regime in the configurational relaxation. The long-time dynamics of proteins is controlled by an activated regime. We argue that the hierarchical free energy barriers set the time scales of biological processes and establish an upper limit to the size of single protein domains. We find it compelling that the scaling behavior for the protein dynamics is in close agreement with the Kardar-Parisi-Zhang scaling exponents.

Meandering Down the Energy Landscape of Protein Folding: Are We There Yet?

As judged by a single publication metric, the activity in the protein folding field has been declining over the past 5 years, after enjoying a decade-long growth. Does this development indicate that the field is sunsetting or is this decline only temporary? Upon surveying a small territory of its landscape, we find that the protein folding field is still quite active and many important findings have emerged from recent experimental studies. However, it is also clear that only continued development of new techniques and methods, especially those enabling dissection of the fine details and features of the protein folding energy landscape, will fuel this old field to move forward.

Coexisting origins of subdiffusion in internal dynamics of proteins

Subdiffusion in conformational dynamics of proteins is observed both experimentally and in simulations. Although its origin has been attributed to multiple mechanisms, including trapping on a rugged energy landscape, fractional Brownian noise, or a fractal topology of the energy landscape, it is unclear which of these, if any, is most relevant. To obtain insights into the actual mechanism, we introduce an analytically tractable hierarchical trapping model and apply it to molecular dynamics simulation trajectories of three proteins in solution. The analysis of the simulations introduces a subdiffusive exponent that varies with time and associates plateaus in the mean-squared displacement with traps on the energy landscape. This analysis permits us to separate the component of subdiffusion due to a trapping mechanism from that due to an underlying fluctuating process, such as fractional Brownian motion. The present results thus provide insights concerning the physical origin of subdiffusion in the dynamics of proteins.

Thermal activation of 'allosteric-like' large-scale motions in a eukaryotic Lactate Dehydrogenase

Conformational changes occurring during the enzymatic turnover are essential for the regulation of protein functionality. Individuating the protein regions involved in these changes and the associated mechanical modes is still a challenge at both experimental and theoretical levels. We present here a detailed investigation of the thermal activation of the functional modes and conformational changes in a eukaryotic Lactate Dehydrogenase enzyme (LDH). Neutron Spin Echo spectroscopy and Molecular Dynamics simulations were used to uncover the characteristic length- and timescales of the LDH nanoscale motions in the apo state. The modes involving the catalytic loop and the mobile region around the binding site are activated at room temperature, and match the allosteric reorganisation of bacterial LDHs. In a temperature window of about 15 degrees, these modes render the protein flexible enough and capable of reorganising the active site toward reactive configurations. On the other hand an excess of thermal excitation leads to the distortion of the protein matrix with a possible anti-catalytic effect. Thus, the temperature activates eukaryotic LDHs via the same conformational changes observed in the allosteric bacterial LDHs. Our investigation provides an extended molecular picture of eukaryotic LDH's conformational landscape that enriches the static view based on crystallographic studies alone.

A Rough Energy Landscape to Describe Surface-Linked Antibody and Antigen Bond Formation

Antibodies and B cell receptors often bind their antigen at cell-cell interface while both molecular species are surface-bound, which impacts bond kinetics and function. Despite the description of complex energy landscapes for dissociation kinetics which may also result in significantly different association kinetics, surface-bound molecule (2D) association kinetics usually remain described by an on-rate due to crossing of a single free energy barrier, and few experimental works have measured association kinetics under conditions implying force and two-dimensional relative ligand-receptor motion. We use a new laminar flow chamber to measure 2D bond formation with systematic variation of the distribution of encounter durations between antigen and antibody, in a range from 0.1 to 10 ms. Under physiologically relevant forces, 2D association is 100-fold slower than 3D association as studied by surface plasmon resonance assays. Supported by brownian dynamics simulations, our results show that a minimal encounter duration is required for 2D association; an energy landscape featuring a rough initial part might be a reasonable way of accounting for this. By systematically varying the temperature of our experiments, we evaluate roughness at 2k_BT, in the range of previously proposed rough parts of landscapes models during dissociation.

Pump-Probe Spectroscopy Using the Hadamard Transform

A new method of performing pump-probe experiments is proposed and experimentally demonstrated by a proof of concept on the millisecond scale. The idea behind this method is to measure the total probe intensity arising from several time points as a group, instead of measuring each time separately. These measurements are multiplexes that are then transformed into the true signal via multiplication with a binary Hadamard S matrix. Each group of probe pulses is determined by using the pattern of a row of the Hadamard S matrix and the experiment is completed by rotating this pattern by one step for each sample excitation until the original pattern is again produced. Thus to measure n time points, n excitation events are needed and n probe patterns each taken from the n × n S matrix. The time resolution is determined by the shortest time between the probe pulses. In principle, this method could be used over all timescales, instead of the conventional pump-probe method which uses delay lines for picosecond and faster time resolution, or fast detectors and oscilloscopes on longer timescales. This new method is particularly suitable for situations where the probe intensity is weak and/or the detector is noisy. When the detector is noisy, there is in principle a signal to noise advantage over conventional pump-probe methods.

Enhancing pairwise state-transition weights: A new weighting scheme in simulated tempering that can minimize transition time between a pair of conformational states

Simulated tempering (ST) is a widely used enhancing sampling method for Molecular Dynamics simulations. As one expanded ensemble method, ST is a combination of canonical ensembles at different temperatures and the acceptance probability of cross-temperature transitions is determined by both the temperature difference and the weights of each temperature. One popular way to obtain the weights is to adopt the free energy of each canonical ensemble, which achieves uniform sampling among temperature space. However, this uniform distribution in temperature space may not be optimal since high temperatures do not always speed up the conformational transitions of interest, as anti-Arrhenius kinetics are prevalent in protein and RNA folding. Here, we propose a new method: Enhancing Pairwise State-transition Weights (EPSW), to obtain the optimal weights by minimizing the round-trip time for transitions among different metastable states at the temperature of interest in ST. The novelty of the EPSW algorithm lies in explicitly considering the kinetics of conformation transitions when optimizing the weights of different temperatures. We further demonstrate the power of EPSW in three different systems: a simple two-temperature model, a two-dimensional model for protein folding with anti-Arrhenius kinetics, and the alanine dipeptide. The results from these three systems showed that the new algorithm can substantially accelerate the transitions between conformational states of interest in the ST expanded ensemble and further facilitate the convergence of thermodynamics compared to the widely used free energy weights. We anticipate that this algorithm is particularly useful for studying functional conformational changes of biological systems where the initial and final states are often known from structural biology experiments.

Direct measurement of the tryptophan-mediated photocleavage kinetics of a protein disulfide bond

Disulfide cleavage is one of the major causes underlying ultraviolet (UV) light-induced protein damage. While previous studies have provided strong evidence to support the notion that this process is mediated by photo-induced electron transfer from the excited state of an aromatic residue (e.g., tryptophan) to the disulfide bond, many mechanistic details are still lacking. For example, we do not know how quickly this process occurs in a protein environment. Herein, we design an experiment, which uses the unfolding kinetics of a protein as an observable, to directly assess the kinetics and mechanism of photo-induced disulfide cleavage. Our results show that this disulfide bond cleavage event takes place in ∼2 μs via a mechanism involving electron transfer from the triplet state of a tryptophan (Trp) residue to the disulfide bond. Furthermore, we find that one of the photoproducts of this reaction, a Trp-SR adduct, is formed locally, thus preventing the protein from re-cross-linking. Taken together, these findings suggest that a Trp-disulfide pair could be used as a photo-trigger to initiate protein folding dynamics and control the biological activities of disulfide-containing peptides.

Speed of conformational change: comparing explicit and implicit solvent molecular dynamics simulations

Adequate sampling of conformation space remains challenging in atomistic simulations, especially if the solvent is treated explicitly. Implicit-solvent simulations can speed up conformational sampling significantly. We compare the speed of conformational sampling between two commonly used methods of each class: the explicit-solvent particle mesh Ewald (PME) with TIP3P water model and a popular generalized Born (GB) implicit-solvent model, as implemented in the AMBER package. We systematically investigate small (dihedral angle flips in a protein), large (nucleosome tail collapse and DNA unwrapping), and mixed (folding of a miniprotein) conformational changes, with nominal simulation times ranging from nanoseconds to microseconds depending on system size. The speedups in conformational sampling for GB relative to PME simulations, are highly system- and problem-dependent. Where the simulation temperatures for PME and GB are the same, the corresponding speedups are approximately onefold (small conformational changes), between ∼1- and ∼100-fold (large changes), and approximately sevenfold (mixed case). The effects of temperature on speedup and free-energy landscapes, which may differ substantially between the solvent models, are discussed in detail for the case of miniprotein folding. In addition to speeding up conformational sampling, due to algorithmic differences, the implicit solvent model can be computationally faster for small systems or slower for large systems, depending on the number of solute and solvent atoms. For the conformational changes considered here, the combined speedups are approximately twofold, ∼1- to 60-fold, and ∼50-fold, respectively, in the low solvent viscosity regime afforded by the implicit solvent. For all the systems studied, 1) conformational sampling speedup increases as Langevin collision frequency (effective viscosity) decreases; and 2) conformational sampling speedup is mainly due to reduction in solvent viscosity rather than possible differences in free-energy landscapes between the solvent models.

A biomimetic molecular switch at work: coupling photoisomerization dynamics to peptide structural rearrangement

A combined experimental and computational study of a peptide-linked retinal-like molecular switch shows the effects on photoreactivity and the α-helix structure.

Effects of pressure on the dynamics of an oligomeric protein from deep-sea hyperthermophile

Inorganic pyrophosphatase (IPPase) from Thermococcus thioreducens is a large oligomeric protein derived from a hyperthermophilic microorganism that is found near hydrothermal vents deep under the sea, where the pressure is up to 100 MPa (1 kbar). It has attracted great interest in biophysical research because of its high activity under extreme conditions in the seabed. In this study, we use the quasielastic neutron scattering (QENS) technique to investigate the effects of pressure on the conformational flexibility and relaxation dynamics of IPPase over a wide temperature range. The β-relaxation dynamics of proteins was studied in the time ranges from 2 to 25 ps, and from 100 ps to 2 ns, using two spectrometers. Our results indicate that, under a pressure of 100 MPa, close to that of the native environment deep under the sea, IPPase displays much faster relaxation dynamics than a mesophilic model protein, hen egg white lysozyme (HEWL), at all measured temperatures, opposite to what we observed previously under ambient pressure. This contradictory observation provides evidence that the protein energy landscape is distorted by high pressure, which is significantly different for hyperthermophilic (IPPase) and mesophilic (HEWL) proteins. We further derive from our observations a schematic denaturation phase diagram together with energy landscapes for the two very different proteins, which can be used as a general picture to understand the dynamical properties of thermophilic proteins under pressure.

Microsecond protein dynamics observed at the single-molecule level

How polypeptide chains acquire specific conformations to realize unique biological functions is a central problem of protein science. Single-molecule spectroscopy, combined with fluorescence resonance energy transfer, is utilized to study the conformational heterogeneity and the state-to-state transition dynamics of proteins on the submillisecond to second timescales. However, observation of the dynamics on the microsecond timescale is still very challenging. This timescale is important because the elementary processes of protein dynamics take place and direct comparison between experiment and simulation is possible. Here we report a new single-molecule technique to reveal the microsecond structural dynamics of proteins through correlation of the fluorescence lifetime. This method, two-dimensional fluorescence lifetime correlation spectroscopy, is applied to clarify the conformational dynamics of cytochrome c. Three conformational ensembles and the microsecond transitions in each ensemble are indicated from the correlation signal, demonstrating the importance of quantifying microsecond dynamics of proteins on the folding free energy landscape.

Single molecule spectroscopy can visualise dynamic changes in protein conformation on the submillisecond timescale. Here, Otosu et al. apply two-dimensional fluorescence lifetime correlation spectroscopy to visualise dynamics between seven conformers of cytochrome c on the microsecond timescale.

pH-jump induced leucine zipper folding beyond the diffusion limit

The folding of a pH-sensitive leucine zipper, that is, a GCN4 mutant containing eight glutamic acid residues, has been investigated. A pH-jump induced by a caged proton (o-nitrobenzaldehyde, oNBA) is employed to initiate the process, and time-resolved IR spectroscopy of the amide I band is used to probe it. The experiment has been carefully designed to minimize the buffer capacity of the sample solution so that a large pH jump can be achieved, leading to a transition from a completely unfolded to a completely folded state with a single laser shot. In order to eliminate the otherwise rate-limiting diffusion-controlled step of the association of two peptides, they have been covalently linked. The results for the folding kinetics of the cross-linked peptide are compared with those of an unlinked peptide, which reveals a detailed picture of the folding mechanism. That is, folding occurs in two steps, one on an ∼1-2 μs time scale leading to a partially folded α-helix even in the monomeric case and a second one leading to the final coiled-coil structure on distinctively different time scales of ∼30 μs for the cross-linked peptide and ∼200 μs for the unlinked peptide. By varying the initial pH, it is found that the folding mechanism is consistent with a thermodynamic two-state model, despite the fact that a transient intermediate is observed in the kinetic experiment.

The roughness of the protein energy landscape results in anomalous diffusion of the polypeptide backbone

Recombination of photolysed protein disulfide bonds confirms subdiffusional backbone motion and measures the roughness of the protein's energy landscape.

Recent applications of boxed molecular dynamics: a simple multiscale technique for atomistic simulations

In this paper, we briefly review the boxed molecular dynamics (BXD) method which allows analysis of thermodynamics and kinetics in complicated molecular systems. BXD is a multiscale technique, in which thermodynamics and long-time dynamics are recovered from a set of short-time simulations. In this paper, we review previous applications of BXD to peptide cyclization, solution phase organic reaction dynamics and desorption of ions from self-assembled monolayers (SAMs). We also report preliminary results of simulations of diamond etching mechanisms and protein unfolding in atomic force microscopy experiments. The latter demonstrate a correlation between the protein's structural motifs and its potential of mean force. Simulations of these processes by standard molecular dynamics (MD) is typically not possible, because the experimental time scales are very long. However, BXD yields well-converged and physically meaningful results. Compared with other methods of accelerated MD, our BXD approach is very simple; it is easy to implement, and it provides an integrated approach for simultaneously obtaining both thermodynamics and kinetics. It also provides a strategy for obtaining statistically meaningful dynamical results in regions of configuration space that standard MD approaches would visit only very rarely.

N-terminal domain of prion protein directs its oligomeric association

The self-association of prion protein (PrP) is a critical step in the pathology of prion diseases. It is increasingly recognized that small non-fibrillar β-sheet-rich oligomers of PrP may be of crucial importance in the prion disease process. Here, we characterize the structure of a well defined β-sheet-rich oligomer, containing ∼12 PrP molecules, and often enclosing a central cavity, formed using full-length recombinant PrP. The N-terminal region of prion protein (residues 23-90) is required for the formation of this distinct oligomer; a truncated form comprising residues 91-231 forms a broad distribution of aggregated species. No infectivity or toxicity was found using cell and animal model systems. This study demonstrates that examination of the full repertoire of conformers and assembly states that can be accessed by PrP under specific experimental conditions should ideally be done using the full-length protein.

The design and synthesis of alanine-rich α-helical peptides constrained by an S,S-tetrazine photochemical trigger: a fragment union approach

The design and synthesis of alanine-rich α-helical peptides constrained in a partially unfolded state by incorporation of the S,S-tetrazine phototrigger has been achieved, permitting, upon photochemical release, observation by 2D-IR spectroscopy of the subnanosecond conformational dynamics that govern the early steps associated with α-helix formation. Solid-phase peptide synthesis was employed to elaborate the requisite fragments, with full peptide construction via solution-phase fragment condensation. The fragment union tactic was also employed to construct (13)C═(18)O isotopically edited amides to permit direct observation of conformational motion at or near specific peptide bonds.

Kinetic response of a photoperturbed allosteric protein

By covalently linking an azobenzene photoswitch across the binding groove of a PDZ domain, a conformational transition, similar to the one occurring upon ligand binding to the unmodified domain, can be initiated on a picosecond timescale by a laser pulse. The protein structures have been characterized in the two photoswitch states through NMR spectroscopy and the transition between them through ultrafast IR spectroscopy and molecular dynamics simulations. The binding groove opens on a 100-ns timescale in a highly nonexponential manner, and the molecular dynamics simulations suggest that the process is governed by the rearrangement of the water network on the protein surface. We propose this rearrangement of the water network to be another possible mechanism of allostery.