Wookyung Yu

Benchmarking all-atom simulations using hydrogen exchange

Significance Molecular dynamics simulations have recently become capable of observing multiple protein unfolding and refolding events in a single-millisecond–long trajectory. This major advance produces atomic-level information with nanosecond resolution, a feat unmatched by experimental methods. Such simulations are being extensively analyzed to assess their description of protein folding, yet the results remain difficult to validate experimentally. We apply a combination of hydrogen exchange, NMR, and other techniques to test the simulations with a resolution of single H-bonds. Several significant discrepancies between the simulations and experimental data were uncovered for regions of the energy surface outside of the native basin. This comparison yields suggestions for improving the force fields and provides a general method for experimentally validating folding simulations. Long-time molecular dynamics (MD) simulations are now able to fold small proteins reversibly to their native structures [Lindorff-Larsen K, Piana S, Dror RO, Shaw DE (2011) Science 334(6055):517–520]. These results indicate that modern force fields can reproduce the energy surface near the native structure. To test how well the force fields recapitulate the other regions of the energy surface, MD trajectories for a variant of protein G are compared with data from site-resolved hydrogen exchange (HX) and other biophysical measurements. Because HX monitors the breaking of individual H-bonds, this experimental technique identifies the stability and H-bond content of excited states, thus enabling quantitative comparison with the simulations. Contrary to experimental findings of a cooperative, all-or-none unfolding process, the simulated denatured state ensemble, on average, is highly collapsed with some transient or persistent native 2° structure. The MD trajectories of this protein G variant and other small proteins exhibit excessive intramolecular H-bonding even for the most expanded conformations, suggesting that the force fields require improvements in describing H-bonding and backbone hydration. Moreover, these comparisons provide a general protocol for validating the ability of simulations to accurately capture rare structural fluctuations.

Functional Implications of an Intermeshing Cogwheel-Like Interaction between TolC and MacA in the Action of Macrolide-Specific Efflux Pump MacAB-TolC

Macrolide-specific efflux pump MacAB-TolC has been identified in diverse Gram-negative bacteria including Escherichia coli. The inner membrane transporter MacB requires the outer membrane factor TolC and the periplasmic adaptor protein MacA to form a functional tripartite complex. In this study, we used a chimeric protein containing the tip region of the TolC α-barrel to investigate the role of the TolC α-barrel tip region with regard to its interaction with MacA. The chimeric protein formed a stable complex with MacA, and the complex formation was abolished by substitution at the functionally essential residues located at the MacA α-helical tip region. Electron microscopic study delineated that this complex was made by tip-to-tip interaction between the tip regions of the α-barrels of TolC and MacA, which correlated well with the TolC and MacA complex calculated by molecular dynamics. Taken together, our results demonstrate that the MacA hexamer interacts with TolC in a tip-to-tip manner, and implies the manner by which MacA induces opening of the TolC channel.

Cooperative folding kinetics of BBL protein and peripheral subunit-binding domain homologues

Recent experiments claiming that Naf-BBL protein follows a global downhill folding raised an important controversy as to the folding mechanism of fast-folding proteins. Under the global downhill folding scenario, not only do proteins undergo a gradual folding, but folding events along the continuous folding pathway also could be mapped out from the equilibrium denaturation experiment. Based on the exact calculation using a free energy landscape, relaxation eigenmodes from a master equation, and Monte Carlo simulation of an extended Muñoz–Eaton model that incorporates multiscale-heterogeneous pairwise interactions between amino acids, here we show that the very nature of a two-state cooperative transition such as a bimodal distribution from an exact free energy landscape and biphasic relaxation kinetics manifest in the thermodynamics and folding–unfolding kinetics of BBL and peripheral subunit-binding domain homologues. Our results provide an unequivocal resolution to the fundamental controversy related to the global downhill folding scheme, whose applicability to other proteins should be critically reexamined.

Even with nonnative interactions, the updated folding transition states of the homologs Proteins G & L are extensive and similar

Significance An outstanding issue in protein science is identifying the relationship between sequence and folding, e.g., do sequences having similar structures have similar folding pathways? The homologs Proteins G & L have been cited as a primary example where sequence variations dramatically affect folding dynamics. However, our new results indicate that the homologs have similar folding behavior. At the highest point on the reaction surface, the pathways converge to similar ensembles. These findings are distinct from descriptions based on the widely used mutational ϕ analysis, partly due to nonnative behavior. Our study emphasizes that significant challenges remain both in characterizing and predicting transition state ensembles even for relatively simple proteins whose folding behavior is believed to be well understood. Experimental and computational folding studies of Proteins L & G and NuG2 typically find that sequence differences determine which of the two hairpins is formed in the transition state ensemble (TSE). However, our recent work on Protein L finds that its TSE contains both hairpins, compelling a reassessment of the influence of sequence on the folding behavior of the other two homologs. We characterize the TSEs for Protein G and NuG2b, a triple mutant of NuG2, using ψ analysis, a method for identifying contacts in the TSE. All three homologs are found to share a common and near-native TSE topology with interactions between all four strands. However, the helical content varies in the TSE, being largely absent in Proteins G & L but partially present in NuG2b. The variability likely arises from competing propensities for the formation of nonnative β turns in the naturally occurring proteins, as observed in our TerItFix folding algorithm. All-atom folding simulations of NuG2b recapitulate the observed TSEs with four strands for 5 of 27 transition paths [Lindorff-Larsen K, Piana S, Dror RO, Shaw DE (2011) Science 334(6055):517–520]. Our data support the view that homologous proteins have similar folding mechanisms, even when nonnative interactions are present in the transition state. These findings emphasize the ongoing challenge of accurately characterizing and predicting TSEs, even for relatively simple proteins.

Perplexing cooperative folding and stability of a low-sequence complexity, polyproline 2 protein lacking a hydrophobic core

Significance The basis of protein-folding cooperativity and stability elicits a variety of opinions, as does the existence and importance of possible residual structure in the denatured state. We examine these issues in a protein that is striking in its dearth of hydrophobic burial and its lack of canonical α and β structures, while having a low sequence complexity with 46% glycine. Unexpectedly, the protein’s folding behavior is similar to that observed for typical globular proteins. This enigma forces a reexamination of the possible combination of factors that can stabilize a protein. The burial of hydrophobic side chains in a protein core generally is thought to be the major ingredient for stable, cooperative folding. Here, we show that, for the snow flea antifreeze protein (sfAFP), stability and cooperativity can occur without a hydrophobic core, and without α-helices or β-sheets. sfAFP has low sequence complexity with 46% glycine and an interior filled only with backbone H-bonds between six polyproline 2 (PP2) helices. However, the protein folds in a kinetically two-state manner and is moderately stable at room temperature. We believe that a major part of the stability arises from the unusual match between residue-level PP2 dihedral angle bias in the unfolded state and PP2 helical structure in the native state. Additional stabilizing factors that compensate for the dearth of hydrophobic burial include shorter and stronger H-bonds, and increased entropy in the folded state. These results extend our understanding of the origins of cooperativity and stability in protein folding, including the balance between solvent and polypeptide chain entropies.

Cooperative folding near the downhill limit determined with amino acid resolution by hydrogen exchange

Significance Fast-folding proteins provide a testing ground for theories and simulations of folding at the extreme limit, in particular when it occurs on the timescale of chain diffusion and potentially in the elusive barrier-free limit. Whereas most fast-folding studies probe the reaction near the transition point with limited resolution, we apply hydrogen exchange methods to a microsecond folder, characterizing its energy landscape with amino acid precision under highly stabilizing conditions where barrier-free folding is most probable. Despite folding with τ = 5 μs, we find that the molecule folds and unfolds in a cooperative process matching the properties observed at elevated denaturant concentration, implying that much faster folding rate constants are required to reach the downhill limit. The relationship between folding cooperativity and downhill, or barrier-free, folding of proteins under highly stabilizing conditions remains an unresolved topic, especially for proteins such as λ-repressor that fold on the microsecond timescale. Under aqueous conditions where downhill folding is most likely to occur, we measure the stability of multiple H bonds, using hydrogen exchange (HX) in a λYA variant that is suggested to be an incipient downhill folder having an extrapolated folding rate constant of 2 × 105 s−1 and a stability of 7.4 kcal·mol−1 at 298 K. At least one H bond on each of the three largest helices (α1, α3, and α4) breaks during a common unfolding event that reflects global denaturation. The use of HX enables us to both examine folding under highly stabilizing, native-like conditions and probe the pretransition state region for stable species without the need to initiate the folding reaction. The equivalence of the stability determined at zero and high denaturant indicates that any residual denatured state structure minimally affects the stability even under native conditions. Using our ψ analysis method along with mutational ϕ analysis, we find that the three aforementioned helices are all present in the folding transition state. Hence, the free energy surface has a sufficiently high barrier separating the denatured and native states that folding appears cooperative even under extremely stable and fast folding conditions.

Sibe: a computation tool to apply protein sequence statistics to folding and design

Statistical analysis plays a significant role in both protein sequences and structures, expanding in recent years from the studies of co-evolution guided single-site mutations to protein folding in silico. Here we describe a computational tool, termed Sibe, with a particular focus on protein sequence analysis, folding and design. Since Sibe has various easy-interface modules, expressive architecture and extensible codes, it is powerful in statistically analyzing sequence data and building energetic potentials in boosting both protein folding and design. In this study, Sibe is used to capture positional conserved couplings between pairwise amino acids and help rational protein design, in which the pairwise couplings are filtered according to the relative entropy computed from the positional conservations and grouped into several ‘sectors’. A human β2-adrenergic receptor (β2AR) was used to demonstrated that those ‘sectors’ could contribute rational design at functional residues. In addition, Sibe provides protein folding modules based on both the positionally conserved couplings and well-established statistical potentials. Accordingly, these modules in Sibe can help rationally design proteins and study corresponding folding problems.

De novo protein structure prediction using ultra-fast molecular dynamics simulation

Modern genomics sequencing techniques have provided a massive amount of protein sequences, but experimental endeavor in determining protein structures is largely lagging far behind the vast and unexplored sequences. Apparently, computational biology is playing a more important role in protein structure prediction than ever. Here, we present a system of de novo predictor, termed NiDelta, building on a deep convolutional neural network and statistical potential enabling molecular dynamics simulation for modeling protein tertiary structure. Combining with evolutionary-based residue-contacts, the presented predictor can predict the tertiary structures of a number of target proteins with remarkable accuracy. The proposed approach is demonstrated by calculations on a set of eighteen large proteins from different fold classes. The results show that the ultra-fast molecular dynamics simulation could dramatically reduce the gap between the sequence and its structure at atom level, and it could also present high efficiency in protein structure determination if sparse experimental data is available.

Exploring the Ligand Efficacy of Cannabinoid Receptor 1 (CB1) using Molecular Dynamics Simulations

Cannabinoid receptor 1 (CB1) is a promising therapeutic target for a variety of disorders. Distinct efficacy profiles showed different therapeutic effects on CB1 dependent on three classes of ligands: agonists, antagonists, and inverse agonists. To discriminate the distinct efficacy profiles of the ligands, we carried out molecular dynamics (MD) simulations to identify the dynamic behaviors of inactive and active conformations of CB1 structures with the ligands. In addition, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method was applied to analyze the binding free energy decompositions of the CB1-ligand complexes. With these two methods, we found the possibility that the three classes of ligands can be discriminated. Our findings shed light on the understanding of different efficacy profiles of ligands by analyzing the structural behaviors of intact CB1 structures and the binding energies of ligands, thereby yielding insights that are useful for the design of new potent CB1 drugs.

pH-Dependent Free Energy Landscape, Conformational Selection, and Thermodynamics of Protein Folding

Protein conformation change depending not only on the values of temperature, denaturant concentration but also on the values of solvent pH. The difference of the pH-denaturation from the thermal or urea denaturation is that hydrogen atoms (un)bind exclusively to R, K, Y, C, H, D, E amino acids. Thus the pH effect on the protein conformation is selective so that the physico-chemical machinery for the biological function of a protein frequently has its origin due to the solvent pH. Although several previous approaches were suggested to elucidate the (un)protonation behavior of a protein conformation, those were mainly oriented on evaluating pKa values of titratable residues in a given static protein conformation. The theoretical and calculation framework for describing the effect of solvent pH to the thermodynamic and kinetic properties of proteins under the equilibrium fluctuation is indispensable for the fundamental understanding of important biological phenomena of proteins.Here we present a development of the pH-dependent free energy function of proteins incorporating its equilibrium fluctuations based on the concept of statistical physics. The validity of our approach is justified by reproducing the experimental pKa values of titratable residues in several proteins. We also present the analytical and calculation framework for describing the pH-dependent thermodynamics and folding kinetics of proteins by the exact calculation. The effects of pH not only on the free energy landscape but also on the folding characters of several proteins are discussed.