Metadynamics Simulation of Prion Protein: β-Structure Stability and the Early Stages of Misfolding

Probing Reactivity with External Forces: The Case of Nitroacetamides in Water

Many computational methods have been applied to interpret and predict changes in reactivity by slight modifications of a given molecular scaffold. We describe a novel and simple method based on approximate density-functional theory of valence electrons that can be applied within a large high-performance computational infrastructure to probe such changes using a statistical sample of molecular configurations, including the solvent. All the used computational tools are fully open-source. Following our previous application, we are able to explain the high acidity of C-H bond at α position in nitro compounds when the amide linkage an ammonium group is inserted into the α substituent.

Probing protein stability: towards a computational atomistic, reliable, affordable, and improvable model

We present an improved application of a recently proposed computational method designed to evaluate the change of free energy as a function of the average value of a suitably chosen collective variable in proteins. The method is based on a full atomistic description of the protein and its environment. The goal is to understand how the protein melting temperature changes upon single-point mutations, because the sign of the temperature variation will allow us to discriminate stabilizing vs. destabilizing mutations in protein sequences. In this refined application the method is based on altruistic well-tempered metadynamics, a variant of multiple-walkers metadynamics. The resulting metastatistics is then modulated by the maximal constrained entropy principle. The latter turns out to be especially helpful in free-energy calculations as it is able to alleviate the severe limitations of metadynamics in properly sampling folded and unfolded configurations. In this work we apply the computational strategy outlined above in the case of the bovine pancreatic trypsin inhibitor, a well-studied small protein, which is a reference for computer simulations since decades. We compute the variation of the melting temperature characterizing the folding-unfolding process between the wild-type protein and two of its single-point mutations that are seen to have opposite effect on the free energy changes. The same approach is used for free energy difference calculations between a truncated form of frataxin and a set of five of its variants. Simulation data are compared to in vitro experiments. In all cases the sign of the change of melting temperature is reproduced, under the further approximation of using an empirical effective mean-field to average out protein-solvent interactions.

Free-Energy Profiles for Membrane Permeation of Compounds Calculated Using Rare-Event Sampling Methods

The free-energy profile of a compound is an essential measurement in evaluating the membrane permeation process by means of theoretical methods. Computationally, molecular dynamics (MD) simulation allows the free-energy profile calculation. However, MD simulations frequently fail to sample membrane permeation because they are rare events induced in longer timescales than the accessible timescale of MD, leading to an insufficient conformational search to calculate an incorrect free-energy profile. To achieve a sufficient conformational search, several enhanced sampling methods have been developed and elucidated the membrane permeation process. In addition to these enhanced sampling methods, we proposed a simple yet powerful free-energy calculation of a compound for the membrane permeation process based on originally rare-event sampling methods developed by us. Our methods have a weak dependency on external biases and their optimizations to promote the membrane permeation process. Based on distributed computing, our methods only require the selection of initial structures and their conformational resampling, whereas the enhanced sampling methods may be required to adjust external biases. Furthermore, our methods efficiently search membrane permeation processes with simple scripts without modifying any MD program. As demonstrations, we calculated the free-energy profiles of seven linear compounds for their membrane permeation based on a hybrid conformational search using two rare-event sampling methods, that is, (1) parallel cascade selection MD (PaCS-MD) and (2) outlier flooding method (OFLOOD), combined with a Markov state model (MSM) construction. In the first step, PaCS-MD generated initial membrane permeation paths of a compound. In the second step, OFLOOD expanded the unsearched conformational area around the initial paths, allowing for a broad conformational search. Finally, the trajectories were employed to construct reliable MSMs, enabling correct free-energy profile calculations. Furthermore, we estimated the membrane permeability coefficients of all compounds by constructing the reliable MSMs for their membrane permeation. In conclusion, the calculated coefficients were qualitatively correlated with the experimental measurements (correlation coefficient (R²) = 0.8689), indicating that the hybrid conformational search successfully calculated the free-energy profiles and membrane permeability coefficients of the seven compounds.

Impact of Side-Chain Hydrophilicity on Packing, Swelling, and Ion Interactions in Oxy-Bithiophene Semiconductors

Exchanging hydrophobic alkyl-based side chains to hydrophilic glycol-based side chains is a widely adopted method for improving mixed-transport device performance, despite the impact on solid-state packing and polymer-electrolyte interactions being poorly understood. Presented here is a molecular dynamics (MD) force field for modeling alkoxylated and glycolated polythiophenes. The force field is validated against known packing motifs for their monomer crystals. MD simulations, coupled with X-ray diffraction (XRD), show that alkoxylated polythiophenes will pack with a "tilted stack" and straight interdigitating side chains, whilst their glycolated counterpart will pack with a "deflected stack" and an s-bend side-chain configuration. MD simulations reveal water penetration pathways into the alkoxylated and glycolated crystals-through the π-stack and through the lamellar stack respectively. Finally, the two distinct ways triethylene glycol polymers can bind to cations are revealed, showing the formation of a metastable single bound state, or an energetically deep double bound state, both with a strong side-chain length dependence. The minimum energy pathways for the formation of the chelates are identified, showing the physical process through which cations can bind to one or two side chains of a glycolated polythiophene, with consequences for ion transport in bithiophene semiconductors.

Met/Val129 polymorphism of the full-length human prion protein dictates distinct pathways of amyloid formation

Methionine/valine polymorphism at position 129 of the human prion protein, huPrP, is tightly associated with the pathogenic phenotype, disease progress, and age of onset of neurodegenerative diseases such as Creutzfeldt–Jakob disease or Fatal Familial Insomnia. This raises the question of whether and how the amino acid type at position 129 influences the structural properties of huPrP, affecting its folding, stability, and amyloid formation behavior. Here, our detailed biophysical characterization of the 129M and 129V variants of recombinant full-length huPrP(23–230) by amyloid formation kinetics, CD spectroscopy, molecular dynamics simulations, and sedimentation velocity analysis reveals differences in their aggregation propensity and oligomer content, leading to deviating pathways for the conversion into amyloid at acidic pH. We determined that the 129M variant exhibits less secondary structure content before amyloid formation and higher resistance to thermal denaturation compared to the 129V variant, whereas the amyloid conformation of both variants shows similar thermal stability. Additionally, our molecular dynamics simulations and rigidity analyses at the atomistic level identify intramolecular interactions responsible for the enhanced monomer stability of the 129M variant, involving more frequent minimum distances between E196 and R156, forming a salt bridge. Removal of the N-terminal half of the 129M full-length variant diminishes its differences compared to the 129V full-length variant and highlights the relevance of the flexible N terminus in huPrP. Taken together, our findings provide insight into structural properties of huPrP and the effects of the amino acid identity at position 129 on amyloid formation behavior.

Antibody binding modulates the dynamics of the membrane-bound prion protein

Misfolding of the cellular prion protein (PrP^C) is associated with lethal neurodegeneration. PrP^C consists of a flexible tail (residues 23-123) and a globular domain (residues 124-231) whose C-terminal end is anchored to the cell membrane. The neurotoxic antibody POM1 and the innocuous antibody POM6 recognize the globular domain. Experimental evidence indicates that POM1 binding to PrP^C emulates the influence on PrP^C of the misfolded prion protein (PrP^Sc) while the binding of POM6 has the opposite biological response. Little is known about the potential interactions between flexible tail, globular domain, and the membrane. Here, we used atomistic simulations to investigate how these interactions are modulated by the binding of the Fab fragments of POM1 and POM6 to PrP^C and by interstitial sequence truncations to the flexible tail. The simulations show that the binding of the antibodies restricts the range of orientations of the globular domain with respect to the membrane and decreases the distance between tail and membrane. Five of the six sequence truncations influence only marginally this distance and the contact patterns between tail and globular domain. The only exception is a truncation coupled to a charge inversion mutation of four N-terminal residues, which increases the distance of the flexible tail from the membrane. The interactions of the flexible tail and globular domain are modulated differently by the two antibodies.

Metal Ion Binding in Wild-Type and Mutated Frataxin: A Stability Study

This work studies the stability of wild-type frataxin and some of its variants found in cancer tissues upon Co2+ binding. Although the physiologically involved metal ion in the frataxin enzymatic activity is Fe2+, as it is customarily done, Co2+ is most often used in experiments because Fe2+ is extremely unstable owing to the fast oxidation reaction Fe2+ → Fe3+. Protein stability is monitored following the conformational changes induced by Co2+ binding as measured by circular dichroism, fluorescence spectroscopy, and melting temperature measurements. The stability ranking among the wild-type frataxin and its variants obtained in this way is confirmed by a detailed comparative analysis of the XAS spectra of the metal-protein complex at the Co K-edge. In particular, a fit to the EXAFS region of the spectrum allows positively identifying the frataxin acidic ridge as the most likely location of the metal-binding sites. Furthermore, we can explain the surprising feature emerging from a detailed analysis of the XANES region of the spectrum, showing that the longer 81-210 frataxin fragment has a smaller propensity for Co2+ binding than the shorter 90-210 one. This fact is explained by the peculiar role of the N-terminal disordered tail in modulating the protein ability to interact with the metal.

Modelling Protein Plasticity: The Example of Frataxin and Its Variants

Frataxin (FXN) is a protein involved in storage and delivery of iron in the mitochondria. Single-point mutations in the FXN gene lead to reduced production of functional frataxin, with the consequent dyshomeostasis of iron. FXN variants are at the basis of neurological impairment (the Friedreich's ataxia) and several types of cancer. By using altruistic metadynamics in conjunction with the maximal constrained entropy principle, we estimate the change of free energy in the protein unfolding of frataxin and of some of its pathological mutants. The sampled configurations highlight differences between the wild-type and mutated sequences in the stability of the folded state. In partial agreement with thermodynamic experiments, where most of the analyzed variants are characterized by lower thermal stability compared to wild type, the D104G variant is found with a stability comparable to the wild-type sequence and a lower water-accessible surface area. These observations, obtained with the new approach we propose in our work, point to a functional switch, affected by single-point mutations, of frataxin from iron storage to iron release. The method is suitable to investigate wide structural changes in proteins in general, after a proper tuning of the chosen collective variable used to perform the transition.

Ligand Binding Path Sampling Based on Parallel Cascade Selection Molecular Dynamics: LB-PaCS-MD

Parallel cascade selection molecular dynamics (PaCS-MD) is a rare-event sampling method that generates transition pathways between a reactant and product. To sample the transition pathways, PaCS-MD repeats short-time MD simulations from important configurations as conformational resampling cycles. In this study, PaCS-MD was extended to sample ligand binding pathways toward a target protein, which is referred to as LB-PaCS-MD. In a ligand-concentrated environment, where multiple ligand copies are randomly arranged around the target protein, LB-PaCS-MD allows for the frequent sampling of ligand binding pathways. To select the important configurations, we specified the center of mass (COM) distance between each ligand and the relevant binding site of the target protein, where snapshots generated by the short-time MD simulations were ranked by their COM distance values. From each cycle, snapshots with smaller COM distance values were selected as the important configurations to be resampled using the short-time MD simulations. By repeating conformational resampling cycles, the COM distance values gradually decreased and converged to constants, meaning that a set of ligand binding pathways toward the target protein was sampled by LB-PaCS-MD. To demonstrate relative efficiency, LB-PaCS-MD was applied to several proteins, and their ligand binding pathways were sampled more frequently than conventional MD simulations.

Independent Nontargeted Parallel Cascade Selection Molecular Dynamics (Ino-PaCS-MD) to Enhance the Conformational Sampling of Proteins

Biological functions are related to long-time protein dynamics (rare events) that are induced over microseconds. Such protein dynamics can be investigated using molecular dynamics (MD) simulations. However, the detection of rare events remains challenging using conventional MD (cMD) since the accessible timescales of cMD are shorter than those of the biological functions. Recently, the parallel cascade selection MD (PaCS-MD) has been proposed to detect such rare events, wherein transition paths are generated between a given reactant and product. As an extension, the nontargeted PaCS-MD (nt-PaCS-MD) has been proposed to predict the transition paths without requiring reference to any product. Thus, as a further extension, we herein propose independent nt-PaCS-MD, namely, Ino-PaCS-MD, wherein multiple walkers are launched from a set of different starting configurations. Each walker repeats a cycle of restarting short-time MD simulations from configurations with high potentials for making transitions to neighboring metastable states. To further enhance the sampling ability, Ino-PaCS-MD temporarily stops the conformational search and periodically resets the starting configurations so that they are uniformly distributed in a conformational subspace, thereby preventing a given protein from being trapped in one of the metastable states. As a demonstration, Ino-PaCS-MD successfully detects rare events of a maltose-binding protein as open-close transitions with a nanosecond-order simulation time, although a microsecond-order cMD simulation failed to detect these rare events, showing the high sampling efficiency of Ino-PaCS-MD.

Mutation-Dependent Refolding of Prion Protein Unveils Amyloidogenic-Related Structural Ramifications: Insights from Molecular Dynamics Simulations

The main focus of prion structural biology studies is to understand the molecular basis of prion diseases caused by misfolding, and aggregation of the cellular prion protein PrP^C remains elusive. Several genetic mutations are linked with human prion diseases and driven by the conformational conversion of PrP^C to the toxic PrP^Sc. The main goal of this study is to gain a better insight into the molecular effect of disease-associated V210I mutation on this process by molecular dynamics simulations. This inherited mutation elicited copious structural changes in the β1-α1-β2 subdomain, including an unfolding of a helix α1 and the elongation of the β-sheet. These unusual structural changes likely appeared to detach the β1-α1-β2 subdomain from the α2-α3 core, an early misfolding event necessary for the conformational conversion of PrP^C to PrP^Sc. Ultimately, the unfolded α1 and its prior β1-α1 loop further engaged with unrestrained conformational dynamics and were widely considered as amyloidogenic-inducing traits. Furthermore, the resulting folding intermediate possesses a highly unstable β1-α1-β2 subdomain, thereby enhancing the aggregation of misfolded PrP^C through intermolecular interactions between frequently refolding regions. Briefly, these remarkable changes as seen in the mutant β1-α1-β2 subdomain are consistent with previous experimental results and thus provide a molecular basis of PrP^C misfolding associated with the conformational conversion of PrP^C to PrP^Sc.

Volatile Anesthetic Sevoflurane Precursor 1,1,1,3,3,3-Hexafluoro-2-Propanol (HFIP) Exerts an Anti-Prion Activity in Prion-Infected Culture Cells

Prion disease is a neurodegenerative disorder with progressive neurologic symptoms and accelerated cognitive decline. The causative protein of prion disease is the prion protein (PrP), and structural transition of PrP from the normal helix rich form (PrP^C) to the abnormal β-sheet rich form (PrP^Sc) occurs in prion disease. While so far numerous therapeutic agents for prion diseases have been developed, none of them are still useful. A fluorinated alcohol, hexafluoro isopropanol (HFIP), is a precursor to the inhalational anesthetic sevoflurane and its metabolites. HFIP is also known as a robust α-helix inducer and is widely used as a solvent for highly aggregated peptides. Here we show that the α-helix-inducing activity of HFIP caused the conformational transformation of the fibrous structure of PrP into amorphous aggregates in vitro. HFIP added to the ScN2a cell medium, which continuously expresses PrP^Sc, reduced PrP^Sc protease resistance after 24-h incubation. It was also clarified that ScN2a cells are more susceptible to HFIP than any of the cells being compared. Based on these findings, HFIP is expected to develop as a therapeutic agent for prion disease.

Protein aggregation: in silico algorithms and applications

Protein aggregation is a topic of immense interest to the scientific community due to its role in several neurodegenerative diseases/disorders and industrial importance. Several in silico techniques, tools, and algorithms have been developed to predict aggregation in proteins and understand the aggregation mechanisms. This review attempts to provide an essence of the vast developments in in silico approaches, resources available, and future perspectives. It reviews aggregation-related databases, mechanistic models (aggregation-prone region and aggregation propensity prediction), kinetic models (aggregation rate prediction), and molecular dynamics studies related to aggregation. With a multitude of prediction models related to aggregation already available to the scientific community, the field of protein aggregation is rapidly maturing to tackle new applications.

Theoretical and computational advances in protein misfolding

Misfolded proteins escape the cellular quality control mechanism and fail to fold properly or remain correctly folded leading to a loss in their functional specificity. Thus misfolding of proteins cause a large number of very different diseases ranging from errors in metabolism to various types of complex neurodegenerative diseases. A theoretical and computational perspective of protein misfolding is presented with a special emphasis on its salient features, mechanism and consequences. These insights quantitatively analyze different determinants of misfolding, that may be applied to design disease specific molecular targets.

Combining molecular dynamics simulations and experimental analyses in protein misfolding

The fold of a protein determines its function and its misfolding can result in loss-of-function defects. In addition, for certain proteins their misfolding can lead to gain-of-function toxicities resulting in protein misfolding diseases such as Alzheimer's, Parkinson's, or the prion diseases. In all of these diseases one or more proteins misfold and aggregate into disease-specific assemblies, often in the form of fibrillar amyloid deposits. Most, if not all, protein misfolding diseases share a fundamental molecular mechanism that governs the misfolding and subsequent aggregation. A wide variety of experimental methods have contributed to our knowledge about misfolded protein aggregates, some of which are briefly described in this review. The misfolding mechanism itself is difficult to investigate, as the necessary timescale and resolution of the misfolding events often lie outside of the observable parameter space. Molecular dynamics simulations fill this gap by virtue of their intrinsic, molecular perspective and the step-by-step iterative process that forms the basis of the simulations. This review focuses on molecular dynamics simulations and how they combine with experimental analyses to provide detailed insights into protein misfolding and the ensuing diseases.

Ok Google, how could I design therapeutics against prion diseases?

A number of previous successful attempts in the search for therapeutics for a variety of human pathologies highlight the importance of computational technologies in the drug discovery pipeline. This approach, often referred to as computer-aided drug design, is unfortunately inapplicable when the precise information regarding the three-dimensional structure of disease-associated proteins or the mechanism by which they are altered to generate misfolded isoforms are missing. A typical example is represented by prion diseases, fatal pathologies of the nervous system characterized by the conformational conversion of a physiological protein called PrP^C into a misfolded and infectious isoform referred to as PrP^Sc. Missing information regarding the atomic structure of PrP^Sc as well as the mechanism of templated conversion of PrP^C has severely halted the discovery of effective therapies for prion diseases. In this manuscript, we review emerging opportunities to apply computer-aided techniques to target PrP^C, PrP^Sc or to design inhibitors of prion replication, and discuss how these fast-evolving technologies could lay the groundwork for the application of entirely novel rational drug design schemes for these devastating pathologies.

Understanding the Exceptional Properties of Nitroacetamides in Water: A Computational Model Including the Solvent

Proton transfer in water involving C–H bonds is a challenge and nitro compounds have been studied for many years as good examples. The effect of substituents on acidity of protons geminal to the nitro group is exploited here with new pKa measurements and electronic structure models, the latter including explicit water environment. Substituents with the amide moiety display an exceptional combination of acidity and solubility in water. In order to find a rationale for the unexpected pKa changes in the (ZZ′)NCO- substituents, we measured and modeled the pKa with Z=Z′=H and Z=Z′=methyl. The dominant contribution to the observed pKa can be understood with advanced computational experiments, where the geminal proton is smoothly moved to the solvent bath. These models, mostly based on density-functional theory (DFT), include the explicit solvent (water) and statistical thermal fluctuations. As a first approximation, the change of pKa can be correlated with the average energy difference between the two tautomeric forms (aci and nitro, respectively). The contribution of the solvent molecules interacting with the solute to the proton transfer mechanism is made evident.

A Multiscale Simulation Approach to Modeling Drug-Protein Binding Kinetics

Drug-target binding kinetics has recently emerged as a sometimes critical determinant of in vivo efficacy and toxicity. Its rational optimization to improve potency or reduce side effects of drugs is, however, extremely difficult. Molecular simulations can play a crucial role in identifying features and properties of small ligands and their protein targets affecting the binding kinetics, but significant challenges include the long time scales involved in (un)binding events and the limited accuracy of empirical atomistic force fields (lacking, e.g., changes in electronic polarization). In an effort to overcome these hurdles, we propose a method that combines state-of-the-art enhanced sampling simulations and quantum mechanics/molecular mechanics (QM/MM) calculations at the BLYP/VDZ level to compute association free energy profiles and characterize the binding kinetics in terms of structure and dynamics of the transition state ensemble. We test our combined approach on the binding of the anticancer drug Imatinib to Src kinase, a well-characterized target for cancer therapy with a complex binding mechanism involving significant conformational changes. The results indicate significant changes in polarization along the binding pathways, which affect the predicted binding kinetics. This is likely to be of widespread importance in binding of ligands to protein targets.

Structural basis for the complete resistance of the human prion protein mutant G127V to prion disease

Prion diseases are caused by the propagation of misfolded cellular prion proteins (PrPs). A completely prion disease-resistant genotype, V127M129, has been identified in Papua New Guinea and verified in transgenic mice. To disclose the structural basis of the disease-resistant effect of the G127V mutant, we determined and compared the structural and dynamic features of the G127V-mutated human PrP (residues 91-231) and the wild-type PrP in solution. HuPrP(G127V) contains α1, α2 and α3 helices and a stretch-strand (SS) pattern comprising residues Tyr128-Gly131 (SS1) and Val161-Arg164 (SS2), with extending atomic distances between the SS1 and SS2 strands, and a structural rearrangement of the Tyr128 side chain due to steric hindrance of the larger hydrophobic side chain of Val127. The extended α1 helix gets closer to the α2 and α3 helices. NMR dynamics analysis revealed that Tyr128, Gly131 and Tyr163 underwent significant conformational exchanges. Molecular dynamics simulations suggest that HuPrP(G127V) prevents the formation of stable β-sheets and dimers. Unique structural and dynamic features potentially inhibit the conformational conversion of the G127V mutant. This work is beneficial for understanding the molecular mechanisms underlying the complete resistance of the G127V mutant to prion disease and for developing new therapeutics for prion disease.

Emergent Properties of Antiagglomerant Films Control Methane Transport: Implications for Hydrate Management

The relationship between collective properties and performance of antiagglomerants (AAs) used in hydrate management is handled using molecular dynamics simulations and enhanced sampling techniques. A thin film of AAs adsorbed at the interface between one flat sII methane hydrate substrate and a fluid hydrocarbon mixture containing methane and n-dodecane is studied. The AA considered is a surface-active compound with a complex hydrophilic head that contains both amide and tertiary ammonium cation groups and hydrophobic tails. At a sufficiently high AA density, the interplay between the surfactant layer and the liquid hydrocarbon excludes methane from the interfacial region. In this scenario, we combine metadynamics and umbrella sampling frameworks to study accurately the free-energy landscape and the equilibrium rates associated with the transport of one methane molecule across the AA film. We observe that the local configurational changes of the liquid hydrocarbon packed within the AA film are associated with high free-energy barriers for methane transport. The time scales estimated for the transport of methane across the AA film can be, in some cases, comparable to those reported in the literature for the growth of hydrates, suggesting that one possible mechanism by which AAs delay the formation of hydrate plugs could be providing a barrier to methane transport. Considering the interplay between the structural design and collective properties of AAs might be of relevance to improve their performance in flow assurance.

Copper Binding Induces Polymorphism in Amyloid-β Peptide: Results of Computational Models

Amyloid-β (Aβ) peptides are intrinsically disordered peptides, and their aggregation is the hallmark of Alzheimer's disease development. The propensity of the Aβ peptide to intermolecular interactions, the latter favoring different types of oligomers and aggregated forms, has been the object of a huge number of studies. Several facts are now established: the presence of large amount of d-block (M) ions (Zn, Cu, and Fe) in the aggregated forms; the 1:1 M/Aβ ratio favors the formation of amorphous aggregates, with an aggregation rate lower than that in the absence of such ions. In particular, statistical models describing the interactions between copper and amyloid peptides are mandatory to explain the relationship between neurodegeneration, copper dyshomeostasis, and overproduction of reactive oxygen species, the latter event occurring with aging. In this work, we show, by replica-exchange molecular dynamics simulations, that a copper ion (Cu²⁺) bound as in the experimentally observed prevailing coordination enhances the probability of closed structures that hinder the formation of extended intermolecular hydrogen bonds that stabilize fibrillar ordered aggregated forms. On the other hand, this effect enhances the catalytic role of the complex during the lifetime of soluble forms.

Effects of pH and aggregation in the human prion conversion into scrapie form: a study using molecular dynamics with excited normal modes

There are two different prion conformations: (1) the cellular natural (PrP^C) and (2) the scrapie (PrP^Sc), an infectious form that tends to aggregate under specific conditions. PrP^C and PrP^Sc are widely different regarding secondary and tertiary structures. PrP^Sc contains more and longer β-strands compared to PrP^C. The lack of solved PrP^Sc structures precludes a proper understanding of the mechanisms related to the transition between cellular and scrapie forms, as well as the aggregation process. In order to investigate the conformational transition between PrP^C and PrP^Sc, we applied MDeNM (molecular dynamics with excited normal modes), an enhanced sampling simulation technique that has been recently developed to probe large structural changes. These simulations yielded new structural rearrangements of the cellular prion that would have been difficult to obtain with standard MD simulations. We observed an increase in β-sheet formation under low pH (≤ 4) and upon oligomerization, whose relevance was discussed on the basis of the energy landscape theory for protein folding. The characterization of intermediate structures corresponding to transition states allowed us to propose a conversion model from the cellular to the scrapie prion, which possibly ignites the fibril formation. This model can assist the design of new drugs to prevent neurological disorders related to the prion aggregation mechanism.

Self-Avoiding Conformational Sampling Based on Histories of Past Conformational Searches

Self-avoiding conformational sampling (SACS) is proposed as an enhanced conformational sampling method for proteins. In SACS, the following conformational resampling is repeated for a given protein: (1) identification of newly visited states in a subspace and (2) conformational resampling by restarting short-time molecular dynamics (MD) simulations from the newly visited states. To identify the newly visited states, a set of history-dependent histograms projected onto the subspace is used. One is constructed from the trajectories sampled at the current (ith) cycle, and the other is constructed from all of the trajectories accumulated up through the previous ((i - 1)th) cycle. By reference to the history-dependent histograms, the newly visited states appearing at the current (ith) cycle are defined as a difference set between them. By repeating the cycle of conformational resampling, SACS prevents the system from revisiting states that have already been visited for previous cycles, promoting structural transitions via resampling from the newly visited states. To verify the conformational sampling efficiency of SACS, the present method was applied to reveal underlying mechanisms of biologically important domain motions of maltodextrin binding protein in explicit water and successfully reproduced the open-closed transition with a reasonable (nanosecond-order) computational cost.

Comparing the energy landscapes for native folding and aggregation of PrP

Protein sequences are evolved to encode generally one folded structure, out of a nearly infinite array of possible folds. Underlying this code is a funneled free energy landscape that guides folding to the native conformation. Protein misfolding and aggregation are also a manifestation of free-energy landscapes. The detailed mechanisms of these processes are poorly understood, but often involve rare, transient species and a variety of different pathways. The inherent complexity of misfolding has hampered efforts to measure aggregation pathways and the underlying energy landscape, especially using traditional methods where ensemble averaging obscures important rare and transient events. We recently studied the misfolding and aggregation of prion protein by examining 2 monomers tethered in close proximity as a dimer, showing how the steps leading to the formation of a stable aggregated state can be resolved in the single-molecule limit and the underlying energy landscape thereby reconstructed. This approach allows a more quantitative comparison of native folding versus misfolding, including fundamental differences in the dynamics for misfolding. By identifying key steps and interactions leading to misfolding, it should help to identify potential drug targets. Here we describe the importance of characterizing free-energy landscapes for aggregation and the challenges involved in doing so, and we discuss how single-molecule studies can help test proposed structural models for PrP aggregates.

Polymorphism at 129 dictates metastable conformations of the human prion protein N-terminal β-sheet

We study the thermodynamic stability of the native state of the human prion protein using a new free-energy method, replica-exchange on-the-fly parameterization. This method is designed to overcome hidden-variable sampling limitations to yield nearly error-free free-energy profiles along a conformational coordinate. We confirm that all four (M129V, D178N) polymorphs have a ground-state conformation with three intact β-sheet hydrogen bonds. Additionally, they are observed to have distinct metastabilities determined by the side-chain at position 129. We rationalize these findings with reference to the prion "strain" hypothesis, which links the variety of transmissible spongiform encephalopathy phenotypes to conformationally distinct infectious prion forms and classifies distinct phenotypes of sporadic Creutzfeldt-Jakob disease based solely on the 129 polymorphism. Because such metastable structures are not easily observed in structural experiments, our approach could potentially provide new insights into the conformational origins of prion diseases and other pathologies arising from protein misfolding and aggregation.

Mechanism of Unfolding of Human Prion Protein

Misfolding and aggregation of prion proteins are associated with several neurodegenerative diseases. Therefore, understanding the mechanism of the misfolding process is of enormous interest in the scientific community. It has been speculated and widely discussed that the native cellular prion protein (PrP^C) form needs to undergo substantial unfolding to a more stable PrP^C* state, which may further oligomerize into the toxic scrapie (PrP^Sc) form. Here, we have studied the mechanism of the unfolding of the human prion protein (huPrP) using a set of extensive well-tempered metadynamics simulations. Through multiple microsecond-long metadynamics simulations, we find several possible unfolding pathways. We show that each pathway leads to an unfolded state of lower free energy than the native state. Thus, our study may point to the signature of a PrP^C* form that corresponds to a global minimum on the conformational free-energy landscape. Moreover, we find that these global minima states do not involve an increased β-sheet content, as was assumed to be a signature of PrP^Sc formation in previous simulation studies. We have further analyzed the origin of metastability of the PrP^C form through free-energy surfaces of the chopped helical segments to show that the helices, particularly H2 and H3 of the prion protein, have the tendency to form either a random coil or a β-structure. Therefore, the secondary structural elements of the prion protein are only weakly stabilized by tertiary contacts and solvation forces so that relatively weak perturbations induced by temperature, pressure, pH, and so forth can lead to substantial unfolding with characteristics of intrinsically disordered proteins.

Exploring Flexibility of Progesterone Receptor Ligand Binding Domain Using Molecular Dynamics

Progesterone receptor (PR), a member of nuclear receptor (NR) superfamily, plays a vital role for female reproductive tissue development, differentiation and maintenance. PR ligand, such as progesterone, induces conformation changes in PR ligand binding domain (LBD), thus mediates subsequent gene regulation cascades. PR LBD may adopt different conformations upon an agonist or an antagonist binding. These different conformations would trigger distinct transcription events. Therefore, the dynamics of PR LBD would be of general interest to biologists for a deep understanding of its structure-function relationship. However, no apo-form (non-ligand bound) of PR LBD model has been proposed either by experiments or computational methods so far. In this study, we explored the structural dynamics of PR LBD using molecular dynamics simulations and advanced sampling tools in both ligand-bound and the apo-forms. Resolved by the simulation study, helix 11, helix 12 and loop 895–908 (the loop between these two helices) are quite flexible in antagonistic conformation. Several residues, such as Arg899 and Glu723, could form salt-bridging interaction between helix 11 and helix 3, and are important for the PR LBD dynamics. And we also propose that helix 12 in apo-form PR LBD, not like other NR LBDs, such as human estrogen receptor α (ERα) LBD, may not adopt a totally extended conformation. With the aid of umbrella sampling and metadynamics simulations, several stable conformations of apo-form PR LBD have been sampled, which may work as critical structural models for further large scale virtual screening study to discover novel PR ligands for therapeutic application.

Protective V127 prion variant prevents prion disease by interrupting the formation of dimer and fibril from molecular dynamics simulations

Recent studies uncovered a novel protective prion protein variant: V127 variant, which was reported intrinsically resistant to prion conversion and propagation. However, the structural basis of its protective effect is still unknown. To uncover the origin of the protective role of V127 variant, molecular dynamics simulations were performed to explore the influence of G127V mutation on two key processes of prion propagation: dimerization and fibril formation. The simulation results indicate V127 variant is unfavorable to form dimer by reducing the main-chain H-bond interactions. The simulations of formed fibrils consisting of β1 strand prove V127 variant will make the formed fibril become unstable and disorder. The weaker interaction energies between layers and reduced H-bonds number for V127 variant reveal this mutation is unfavorable to the formation of stable fibril. Consequently, we find V127 variant is not only unfavorable to the formation of dimer but also unfavorable to the formation of stable core and fibril, which can explain the mechanism on the protective role of V127 variant from the molecular level. Our findings can deepen the understanding of prion disease and may guide the design of peptide mimetics or small molecule to mimic the protective effect of V127 variant.

Free energy and hidden barriers of the β-sheet structure of prion protein

On-the-fly free-energy parametrization is a new collective variable biasing approach akin to metadynamics with one important distinction: rather than acquiring an accelerated distribution via a history-dependent bias potential, sampling on this distribution is achieved from the beginning of the simulation using temperature-accelerated molecular dynamics. In the present work, we compare the performance of both approaches to compute the free-energy profile along a scalar collective variable measuring the H-bond registry of the β-sheet structure of the mouse Prion protein. Both methods agree on the location of the free-energy minimum, but free-energy profiles from well-tempered metadynamics are subject to a much higher degree of statistical noise due to hidden barriers. The sensitivity of metadynamics to hidden barriers is shown to be a consequence of the history dependence of the bias potential, and we detail the nature of these barriers for the prion β-sheet. In contrast, on-the-fly parametrization is much less sensitive to these barriers and thus displays improved convergence behavior relative to that of metadynamics. While hidden barriers are a frequent and central issue in free-energy methods, on-the-fly free-energy parametrization appears to be a robust and preferable method to confront this issue.

Basis function sampling: a new paradigm for material property computation

Wang-Landau sampling, and the associated class of flat histogram simulation methods have been remarkably helpful for calculations of the free energy in a wide variety of physical systems. Practically, convergence of these calculations to a target free energy surface is hampered by reliance on parameters which are unknown a priori. Here, we derive and implement a method built upon orthogonal functions which is fast, parameter-free, and (importantly) geometrically robust. The method is shown to be highly effective in achieving convergence. An important feature of this method is its ability to attain arbitrary levels of description for the free energy. It is thus ideally suited to in silico measurement of elastic moduli and other material properties related to free energy perturbations. We demonstrate the utility of such applications by applying our method to calculate the Frank elastic constants of the Lebwohl-Lasher model of liquid crystals.

Combined EPR and molecular modeling study of PPI dendrimers interacting with copper ions: effect of generation and maltose decoration

Understanding the early onset of neurodegeneration is crucial to deploy specific treatments for patients before the process becomes irreversible. Copper has been proposed as a biomarker for many neurodegenerative disorders, being the ion released by pathologically unfolded proteins involved in many biochemical pathways. Dendrimers are macromolecules that bind metal ions with a large ion/ligand ratio, thus, allowing a massive collection of copper. This work provides structural information, obtained via molecular modeling and EPR, for the binding sites of copper in polypropyleneimine (PPI) dendrimers, especially in the maltose decorated form that has potential applications in diagnosis and therapies for various types of neurodegenerations. The analysis of the EPR spectra showed that, at the lowest Cu concentrations, the results are well supported by the calculations. Moreover, EPR analysis at increasing Cu(II) concentration allowed us to follow the saturation behavior of the interacting sites identified by the modeling study.

Structural determinants in prion protein folding and stability

Prions are responsible for a heterogeneous group of fatal neurodegenerative diseases, involving post-translational modifications of the cellular prion protein. Epidemiological studies on Creutzfeldt-Jakob disease, a prototype prion disorder, show a majority of cases being sporadic, while the remaining occurrences are either genetic or iatrogenic. The molecular mechanisms by which PrP(C) is converted into its pathological isoform have not yet been established. While point mutations and seeds trigger the protein to cross the energy barriers, thus causing genetic and infectious transmissible spongiform encephalopathies, respectively, the mechanism responsible for sporadic forms remains unclear. Since prion diseases are protein-misfolding disorders, we investigated prion protein folding and stability as functions of different milieus. Using spectroscopic techniques and atomistic simulations, we dissected the contribution of major structural determinants, also defining the energy landscape of prion protein. In particular, we elucidated (i) the essential role of the octapeptide region in prion protein folding and stability, (ii) the presence of a very enthalpically stable intermediate in prion-susceptible species, and (iii) the role of the disulfide bridge in prion protein folding.

In silico studies and fluorescence binding assays of potential anti-prion compounds reveal an important binding site for prion inhibition from PrP(C) to PrP(Sc)

To understand the pharmacophore properties of 2-aminothiazoles and design novel inhibitors against the prion protein, a highly predictive 3D quantitative structure-activity relationship (QSAR) has been developed by performing comparative molecular field analysis (CoMFA) and comparative similarity analysis (CoMSIA). Both CoMFA and CoMSIA maps reveal the presence of the oxymethyl groups in meta and para positions on the phenyl ring of compound 17 (N-[4-(3,4-dimethoxyphenyl)-1,3-thiazol-2-yl]quinolin-2-amine), is necessary for activity while electro-negative nitrogen of quinoline is highly favorable to enhance activity. The blind docking results for these compounds show that the compound with quinoline binds with higher affinity than isoquinoline and naphthalene groups. Out of 150 novel compounds retrieved using finger print analysis by pharmacophoric model predicted based on five test sets of compounds, five compounds with diverse scaffolds were selected for biological evaluation as possible PrP inhibitors. Molecular docking combined with fluorescence quenching studies show that these compounds bind to pocket-D of SHaPrP near Trp145. The new antiprion compounds 3 and 6, which bind with the interaction energies of -12.1 and -13.2 kcal/mol, respectively, show fluorescence quenching with binding constant (Kd) values of 15.5 and 44.14 μM, respectively. Further fluorescence binding assays with compound 5, which is similar to 2-aminothiazole as a positive control, also show that the molecule binds to the pocket-D with the binding constant (Kd) value of 84.7 μM. Finally, both molecular docking and a fluorescence binding assay of noscapine as a negative control reveals the same binding site on the surface of pocket-A near a rigid loop between β2 and α2 interacting with Arg164. This high level of correlation between molecular docking and fluorescence quenching studies confirm that these five compounds are likely to act as inhibitors for prion propagation while noscapine might act as a prion accelerator from PrP(C) to PrP(Sc).

Molecular Recognition of Platinated DNA from Chromosomal HMGB1

Cisplatin cures testicular and ovarian cancers with unprecedented potency. It induces its beneficial activity by covalently binding to DNA. Repair enzymes, which remove the platinated lesions from DNA, cause drug resistance. Chromosomal High Mobility Group Box proteins (HMGB) may interfere with this process by binding to platinated DNA. Using 8 μs multiple-walker well-tempered metadynamics simulations, here, we investigated the structural and the energetic determinants of one of the HMGB proteins (HMGB1A) in complex with the platinated oligonucleotide [Pt(NH3)2](2+)-d(CCUCTCTG*G*ACCTTCC)-d(GGAGAGACCTGGAAGG) (*G are platinated guanines), for which experimental structural information is available. The calculated affinity is in good agreement with experiment. The process is predicted to be enthalpy-driven, as found for other protein/DNA complexes. The Lys7 residue, whose side-chain was not resolved in the X-ray structure, is found to interact with the C4 5'-phosphate and this interaction emerges as a key facet for the molecular recognition process. In addition, our calculations provide a molecular basis for the experimentally measured decreased affinity of HMGB1A for platinated DNA, as a consequence of Cys22-Cys44 S-S bridge formation (such an oxidation cannot take place in some members of this protein family present in the testis, where the drug is particularly effective). This decrease is likely to be caused by a small yet significant rearrangement of helices H1 and H2 with consequent alteration of the Phe37 juxtaposition.

A theoretical view of protein dynamics

Proteins are fascinating supramolecular structures, which are able to recognize ligands transforming binding information into chemical signals. They can transfer information across the cell, can catalyse complex chemical reactions, and are able to transform energy into work with much more efficiency than any human engine. The unique abilities of proteins are tightly coupled with their dynamic properties, which are coded in a complex way in the sequence and carefully refined by evolution. Despite its importance, our experimental knowledge of protein dynamics is still rather limited, and mostly derived from theoretical calculations. I will review here, in a systematic way, the current state-of-the-art theoretical approaches to the study of protein dynamics, emphasizing the most recent advances, examples of use and the expected lines of development in the near future.

The Parkinson disease-linked LRRK2 protein mutation I2020T stabilizes an active state conformation leading to increased kinase activity

The effect of leucine-rich repeat kinase 2 (LRRK2) mutation I2020T on its kinase activity has been controversial, with both increased and decreased effects being reported. We conducted steady-state and pre-steady-state kinetic studies on LRRKtide and its analog LRRKtide(S). Their phosphorylation differs by the rate-limiting steps: product release is rate-limiting for LRRKtide and phosphoryl transfer is rate-limiting for LRRKtide(S). As a result, we observed that the I2020T mutant is more active than wild type (WT) LRRK2 for LRRKtide(S) phosphorylation, whereas it is less active than WT for LRRKtide phosphorylation. Our pre-steady-state kinetic data suggest that (i) the I2020T mutant accelerates the rates of phosphoryl transfer of both reactions by 3-7-fold; (ii) this increase is masked by a rate-limiting product release step for LRRKtide phosphorylation; and (iii) the observed lower activity of the mutant for LRRKtide phosphorylation is a consequence of its instability: the concentration of the active form of the mutant is 3-fold lower than WT. The I2020T mutant has a dramatically low KATP and therefore leads to resistance to ATP competitive inhibitors. Two well known DFG-out or type II inhibitors are also weaker toward the mutant because they inhibit the mutant in an unexpected ATP competitive mechanism. The I2020 residue lies next to the DYG motif of the activation loop of the LRRK2 kinase domain. Our modeling and metadynamic simulations suggest that the I2020T mutant stabilizes the DYG-in active conformation and creates an unusual allosteric pocket that can bind type II inhibitors but in an ATP competitive fashion.