A comprehensive multidimensional-embedded, one-dimensional reaction coordinate for protein unfolding/folding

High Energy Channeling and Malleable Transition States: Molecular Dynamics Simulations and Free Energy Landscapes for the Thermal Unfolding of Protein U1A and 13 Mutants

The spliceosome protein U1A is a prototype case of the RNA recognition motif (RRM) ubiquitous in biological systems. The in vitro kinetics of the chemical denaturation of U1A indicate that the unfolding of U1A is a two-state process but takes place via high energy channeling and a malleable transition state, an interesting variation of typical two-state behavior. Molecular dynamics (MD) simulations have been applied extensively to the study of two-state unfolding and folding of proteins and provide an opportunity to obtain a theoretical account of the experimental results and a molecular model for the transition state ensemble. We describe herein all-atom MD studies including explicit solvent of up to 100 ns on the thermal unfolding (UF) of U1A and 13 mutants. Multiple MD UF trajectories are carried out to ensure accuracy and reproducibility. A vector representation of the MD unfolding process in RMSD space is obtained and used to calculate a free energy landscape for U1A unfolding. A corresponding MD simulation and free energy landscape for the protein CI2, well known to follow a simple two state folding/unfolding model, is provided as a control. The results indicate that the unfolding pathway on the MD calculated free energy landscape of U1A shows a markedly extended transition state compared with that of CI2. The MD results support the interpretation of the observed chevron plots for U1A in terms of a high energy, channel-like transition state. Analysis of the MDUF structures shows that the transition state ensemble involves microstates with most of the RRM secondary structure intact but expanded by ~14% with respect to the radius of gyration. Comparison with results on a prototype system indicates that the transition state involves an ensemble of molten globule structures and extends over the region of ~1-35 ns in the trajectories. Additional MDUF simulations were carried out for 13 U1A mutants, and the calculated φ-values show close accord with observed results and serve to validate our methodology.

Effect of Osmolytes on Conformational Behavior of Intrinsically Disordered Protein α-Synuclein

α-Synuclein is an intrinsically disordered protein whose function in a healthy brain is poorly understood. It is genetically and neuropathologically linked to Parkinson's disease (PD). PD is manifested after the accumulation of plaques of α-synuclein aggregates in the brain cells. Aggregates of α-synuclein are very toxic and lead to the disruption of cellular homeostasis and neuronal death. α-Synuclein can also contribute to disease propagation as it may exert noxious effects on neighboring cells. Understanding the mechanism of α-synuclein aggregation will facilitate the problem of dealing with neurodegenerative diseases in general and that of PD in particular. Here, we have used molecular dynamics simulations to investigate the behavior of α-synuclein at various temperatures and in different concentrations of urea and trimethyl amine oxide. The residue region from 61 to 95 of α-synuclein is experimentally known as amyloidogenic. In our study, we have identified some other regions, which also have the propensity to form an aggregate besides this known sequence. Urea being a denaturant interacts more with these regions of α-synuclein through hydrogen bond formation and inhibits the β-sheet formation, whereas trimethyl amine oxide itself does not interact much with the protein and stabilizes the protein by preferentially distributing water molecules on the surface of the protein.

Enhancing thermostability of Yarrowia lipolytica lipase 2 through engineering multiple disulfide bonds and mitigating reduced lipase production associated with disulfide bonds

The limited thermostability of Yarrowia lipolytica lipase 2 (Lip2) hampers its industrial application. To improve its thermostability, we combined single disulfide bonds which our group identified previously. In this study, combining different regional disulfide bonds had greater effect than combining same regional disulfide bonds. Furthermore, mutants with 4, 5, and 6 disulfide bonds exhibited dramatically enhanced thermostability. Compared with the wild-type, sextuple mutant 6s displayed a 22.53 and 31.23 ℃ increase in the melting temperature (T_m) and the half loss temperature at 15 min (T15 50), respectively, with greater pH stability and a wider reaction pH range. Molecular dynamics simulation revealed that multiple disulfide bonds resulted in more rigid structures of mutants 4s, 5s and 6s, and prolonged enzyme unfolding times. Moreover, secretions of mutants 5s and 6s were significantly increased by 60% and 80% by co-expressing with the chaperone protein disulfide isomerase (PDI), which mitigated the reduced production issue caused by multiple disulfide bonds. Results of this study indicated that enhanced heat endurance giving more potential for industrial application.

TFE-induced local unfolding and fibrillation of SOD1: bridging the experiment and simulation studies

Misfolding and aggregation of Cu, Zn Superoxide dismutase (SOD1) is involved in the neurodegenerative disease, amyotrophic lateral sclerosis. Many studies have shown that metal-depleted, monomeric form of SOD1 displays substantial local unfolding dynamics and is the precursor for aggregation. Here, we have studied the structure and dynamics of different apo monomeric SOD1 variants associated with unfolding and aggregation in aqueous trifluoroethanol (TFE) through experiments and simulation. TFE induces partially unfolded β-sheet-rich extended conformations in these SOD1 variants, which subsequently develops aggregates with fibril-like characteristics. Fibrillation was achieved more easily in disulfide-reduced monomeric SOD1 when compared with wild-type and mutant monomeric SOD1. At higher concentrations of TFE, a native-like structure with the increase in α-helical content was observed. The molecular dynamics simulation results illustrate distinct structural dynamics for different regions of SOD1 variants and show uniform local unfolding of β-strands. The strands protected by the zinc-binding and electrostatic loops were found to unfold first in 20% (v/v) TFE, leading to a partial unfolding of β-strands 4, 5, and 6 which are prone to aggregation. Our results thus shed light on the role of local unfolding and conformational dynamics in SOD1 misfolding and aggregation.

Identification of putative unfolding intermediates of the mutant His-107-tyr of human carbonic anhydrase II in a multidimensional property space

In this article, we develop an extensive search procedure of the multi-dimensional folding energy landscape of a protein. Our aim is to identify different classes of structures that have different aggregation propensities and catalytic activity. Following earlier studies by Daggett et al. [Jong, D. D.; Riley, R.: Alonso, D.O.: Dagett, V. J. Mol. Biol. 2002, 319, 229], a series of high temperature all-atom classical molecular simulation studies has been carried out to derive a multi-dimensional property space. Dynamical changes in these properties are then monitored by projecting them along a one-dimensional reaction coordinate, dmean . We have focused on the application of this method to partition a wide array of conformations of wild type human carbonic anhydrase II (HCA II) and its unstable mutant His-107-Tyr along dmean by sampling a 35-dimensional property space. The resultant partitioning not only reveals the distribution of conformations corresponding to stable structures of HCA II and its mutant, but also allows the monitoring of several partially unfolded and less stable conformations of the mutant. We have investigated the population of these conformations at different stages of unfolding and collected separate sets of structures that are widely separated in the property space. The dynamical diversity of these sets are examined in terms of the loading of their respective first principal component. The partially unfolded structures thus collected are qualitatively mapped on to the experimentally postulated light molten globule (MGL) and molten globule (MG) intermediates with distinct aggregation propensities and catalytic activities. Proteins 2016; 84:726-743. © 2016 Wiley Periodicals, Inc.

Revisiting the conundrum of trehalose stabilization

Protein aggregation and loss of protein's biological functionality are manifestations of protein instability. Cosolvents, in particular trehalose, are widely accepted antidotes against such destabilization. Although numerous theories have been promulgated in the literature with regard to its mechanism of stabilization, the present scenario is still elusive in view of the discrepancies existing in them. To this end, we have revisited the conundrum and attempted to rationalize the mechanism by conducting thorough investigation of the effect of trehalose on the native, partially unfolded and denatured states of protein "Lysozyme" by means of molecular dynamic (MD) simulations under different temperature and concentration regimes. Two-dimensional contour plots along with principal component analysis suggest that trehalose molecules offer on-pathway stabilization unaltering the principal direction of protein's motion, although it slows down protein dynamics so that the protein gets trapped in the homogeneous ensemble of conformations closer to the native state. Free energy landscape reveals higher population of native compared to intermediate and denatured states. Delphi results and calculation of the preferential interaction parameter demonstrate that this relative stabilization of the native state can be ascribed to be the consequence of favourable interactions of trehalose with side chains of certain loci on the protein surface encompassing polar flexible residues. Stability of protein results from the observed difference in binding affinity of trehalose for native and denatured states of protein. Our findings are at variance with the common conception of relative destabilization of the denatured state. Rather, we provide evidence for relative stabilization of the native state. This stabilization is due to interplay of protein-trehalose, water-trehalose, water-water, protein-water and trehalose-trehalose interactions.

Quantifying the Sources of Kinetic Frustration in Folding Simulations of Small Proteins

Experiments and atomistic simulations of polypeptides have revealed structural intermediates that promote or inhibit conformational transitions to the native state during folding. We invoke a concept of “kinetic frustration” to quantify the prevalence and impact of these behaviors on folding rates within a large set of atomistic simulation data for 10 fast-folding proteins, where each protein’s conformational space is represented as a Markov state model of conformational transitions. Our graph theoretic approach addresses what conformational features correlate with folding inhibition and therefore permits comparison among features within a single protein network and also more generally between proteins. Nonnative contacts and nonnative secondary structure formation can thus be quantitatively implicated in inhibiting folding for several of the tested peptides.

Glucose oxidase from Penicillium amagasakiense: characterization of the transition state of its denaturation from molecular dynamics simulations

Glucose oxidase (GOx) is a flavoenzyme having applications in food and medical industries. However, GOx, as many other enzymes when extracted from the cells, has relatively short operational lifetimes. Several recent studies (both experimental and theoretical), carried out on small proteins (or small fractions of large proteins), show that a detailed knowledge of how the breakdown process starts and proceeds on molecular level could be of significant help to artificially improve the stability of fragile proteins. We have performed extended molecular dynamics (MD) simulations to study the denaturation of GOx (a protein dimer containing nearly 1200 amino acids) to identify weak points in its structure and in this way gather information to later make it more stable, for example, by mutations. A denaturation of a protein can be simulated by increasing the temperature far above physiological temperature. We have performed a series of MD simulations at different temperatures (300, 400, 500, and 600 K). The exit from the protein's native state has been successfully identified with the clustering method and supported by other methods used to analyze the simulation data. A common set of amino acids is regularly found to initiate the denaturation, suggesting a moiety where the enzyme could be strengthened by a suitable amino acid based modification.

Coarse-grained model for colloidal protein interactions, B(22), and protein cluster formation

Reversible protein cluster formation is an important initial step in the processes of native and non-native protein aggregation, but involves relatively long time and length scales for detailed atomistic simulations and extensive mapping of free energy landscapes. A coarse-grained (CG) model is presented to semiquantitatively characterize the thermodynamics and key configurations involved in the landscape for protein oligomerization, as well as experimental measures of interactions such as the osmotic second virial coefficient (B22). Based on earlier work (Grüenberger et al., J. Phys. Chem. B 2013, 117, 763), this CG model treats proteins as rigid bodies composed of one bead per amino acid, with each amino acid having specific parameters for its size, hydrophobicity, and charge. The net interactions are a combination of steric repulsions, short-range attractions, and screened long-range charge-charge interactions. Model parametrization was done by fitting simulation results against experimental value of B22 as a function of solution ionic strength for α-chymotrypsinogen A and γD-Crystallin (gD-Crys). The CG model is applied to characterize the pairwise interactions and dimerization of gD-Crys and the dependence on temperature, protein concentration, and ionic strength. The results illustrate that at experimentally relevant conditions where stable dimers do not form, the entropic contributions are predominant in the free-energy of protein cluster formation and colloidal protein interactions, arguing against interpretations that treat B22 primarily from energetic considerations alone. Additionally, the results suggest that electrostatic interactions help to modulate the population of the different stable configurations for protein nearest-neighbor pairs, while short-range attractions determine the relative orientations of proteins within these configurations. Finally, simulation results are combined with Principal Component Analysis to identify those amino-acids/surface patches that form interprotein contacts at conditions that favor dimerization of gD-Crys. The resulting regions agree with previously found aggregation-prone sites, as well as suggesting new ones that may be important.

Multimolecule test-tube simulations of protein unfolding and aggregation

Molecular dynamics simulations of protein folding or unfolding, unlike most in vitro experimental methods, are performed on a single molecule. The effects of neighboring molecules on the unfolding/folding pathway are largely ignored experimentally and simply not modeled computationally. Here, we present two all-atom, explicit solvent molecular dynamics simulations of 32 copies of the Engrailed homeodomain (EnHD), an ultrafast-folding and -unfolding protein for which the folding/unfolding pathway is well-characterized. These multimolecule simulations, in comparison with single-molecule simulations and experimental data, show that intermolecular interactions have little effect on the folding/unfolding pathway. EnHD unfolded by the same mechanism whether it was simulated in only water or also in the presence of other EnHD molecules. It populated the same native state, transition state, and folding intermediate in both simulation systems, and was in good agreement with experimental data available for each of the three states. Unfolding was slowed slightly by interactions with neighboring proteins, which were mostly hydrophobic in nature and ultimately caused the proteins to aggregate. Protein-water hydrogen bonds were also replaced with protein-protein hydrogen bonds, additionally contributing to aggregation. Despite the increase in protein-protein interactions, the protein aggregates formed in simulation did not do so at the total exclusion of water. These simulations support the use of single-molecule techniques to study protein unfolding and also provide insight into the types of interactions that occur as proteins aggregate at high temperature at an atomic level.

Thermal unfolding pathway of PHD2 catalytic domain in three different PHD2 species: computational approaches

Prolyl hydroxylase domain 2 containing protein (PHD2) is a key protein in regulation of angiogenesis and metastasis. In normoxic condition, PHD2 triggers the degradation of hypoxia-inducible factor 1 (HIF-1α) that induces the expression of hypoxia response genes. Therefore the correct function of PHD2 would inhibit angiogenesis and consequent metastasis of tumor cells in normoxic condition. PHD2 mutations were reported in some common cancers. However, high levels of HIF-1α protein were observed even in normoxic metastatic tumors with normal expression of wild type PHD2. PHD2 malfunctions due to protein misfolding may be the underlying reason of metastasis and invasion in such cases. In this study, we scrutinize the unfolding pathways of the PHD2 catalytic domain’s possible species and demonstrate the properties of their unfolding states by computational approaches. Our study introduces the possibility of aggregation disaster for the prominent species of PHD2 during its partial unfolding. This may justify PHD2 inability to regulate HIF-1α level in some normoxic tumor types.

Exploring protein dynamics space: the dynasome as the missing link between protein structure and function

Proteins are usually described and classified according to amino acid sequence, structure or function. Here, we develop a minimally biased scheme to compare and classify proteins according to their internal mobility patterns. This approach is based on the notion that proteins not only fold into recurring structural motifs but might also be carrying out only a limited set of recurring mobility motifs. The complete set of these patterns, which we tentatively call the dynasome, spans a multi-dimensional space with axes, the dynasome descriptors, characterizing different aspects of protein dynamics. The unique dynamic fingerprint of each protein is represented as a vector in the dynasome space. The difference between any two vectors, consequently, gives a reliable measure of the difference between the corresponding protein dynamics. We characterize the properties of the dynasome by comparing the dynamics fingerprints obtained from molecular dynamics simulations of 112 proteins but our approach is, in principle, not restricted to any specific source of data of protein dynamics. We conclude that: 1. the dynasome consists of a continuum of proteins, rather than well separated classes. 2. For the majority of proteins we observe strong correlations between structure and dynamics. 3. Proteins with similar function carry out similar dynamics, which suggests a new method to improve protein function annotation based on protein dynamics.

GB1 is not a two-state folder: identification and characterization of an on-pathway intermediate

The folding pathway of the small α/β protein GB1 has been extensively studied during the past two decades using both theoretical and experimental approaches. These studies provided a consensus view that the protein folds in a two-state manner. Here, we reassessed the folding of GB1, both by experiments and simulations, and detected the presence of an on-pathway intermediate. This intermediate has eluded earlier experimental characterization and is distinct from the collapsed state previously identified using ultrarapid mixing. Failure to identify the presence of an intermediate affects some of the conclusions that have been drawn for GB1, a popular model for protein folding studies.

Chemodiversity and molecular plasticity: recognition processes as explored by property spaces

In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure--activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences.

Computational model for protein unfolding simulation

The protein folding problem is one of the fundamental and important questions in molecular biology. However, the all-atom molecular dynamics studies of protein folding and unfolding are still computationally expensive and severely limited by the time scale of simulation. In this paper, a simple and fast protein unfolding method is proposed based on the conformational stability analyses and structure modeling. In this method, two structure-based conditions are considered to identify the unstable regions of proteins during the unfolding processes. The protein unfolding trajectories are mimicked through iterative structure modeling according to conformational stability analyses. Two proteins, chymotrypsin inhibitor 2 (CI2) and α -spectrin SH3 domain (SH3) were simulated by this method. Their unfolding pathways are consistent with the previous molecular dynamics simulations. Furthermore, the transition states of the two proteins were identified in unfolding processes and the theoretical Φ values of these transition states showed significant correlations with the experimental data (the correlation coefficients are >0.8). The results indicate that this method is effective in studying protein unfolding. Moreover, we analyzed and discussed the influence of parameters on the unfolding simulation. This simple coarse-grained model may provide a general and fast approach for the mechanism studies of protein folding.

Malleability of folding intermediates in the homeodomain superfamily

Members of the homeodomain superfamily are three-helix bundle proteins whose second and third helices form a helix-turn-helix motif (HTH). Their folding mechanism slides from the ultrafast, three-state framework mechanism for the engrailed homeodomain (EnHD), in which the HTH motif is independently stable, to an apparent two-state nucleation-condensation model for family members with an unstable HTH motif. The folding intermediate of EnHD has nearly native HTH structure, but it is not docked with helix1. The determinant of whether two- or three-state folding was hypothesized to be the stability of the HTH substructure. Here, we describe a detailed Φ-value analysis of the folding of the Pit1 homeodomain, which has similar ultrafast kinetics to that of EnHD. Formation of helix1 was strongly coupled with formation of HTH, which was initially surprising because they are uncoupled in the EnHD folding intermediate. However, we found a key difference between Pit1 and EnHD: The isolated peptide corresponding to the HTH motif in Pit1 was not folded in the absence of H1. Independent molecular dynamics simulations of Pit1 unfolding found an intermediate with H1 misfolded onto the HTH motif. The Pit1 folding pathway is the connection between that of EnHD and the slower folding homeodomains and provides a link in the transition of mechanisms from two- to three-state folding in this superfamily. The malleability of folding intermediates can lead to unstable substructures being stabilized by a variety of nonnative interactions, adding to the continuum of folding mechanisms.

Protein folds and protein folding

The classification of protein folds is necessarily based on the structural elements that distinguish domains. Classification of protein domains consists of two problems: the partition of structures into domains and the classification of domains into sets of similar structures (or folds). Although similar topologies may arise by convergent evolution, the similarity of their respective folding pathways is unknown. The discovery and the characterization of the majority of protein folds will be followed by a similar enumeration of available protein folding pathways. Consequently, understanding the intricacies of structural domains is necessary to understanding their collective folding pathways. We review the current state of the art in the field of protein domain classification and discuss methods for the systematic and comprehensive study of protein folding across protein fold space via atomistic molecular dynamics simulation. Finally, we discuss our large-scale Dynameomics project, which includes simulations of representatives of all autonomous protein folds.

Refolding the engrailed homeodomain: structural basis for the accumulation of a folding intermediate

The ultrafast folding pathway of the engrailed homeodomain has been exceptionally well characterized by experiment and simulation. Helices II and III of the three-helix bundle protein form the native helix-turn-helix motif as an on-pathway intermediate within a few microseconds. The slow step is then the proper docking of the helices in approximately 15 mus. However, there is still the unexplained puzzle of why helix docking is relatively slow, which is part of the more general question as to why rearrangements of intermediates occur slowly. To address this problem, we performed 46 all-atom molecular dynamics refolding simulations in explicit water, for a total of 15 micros of simulation time. The simulations started from an intermediate state structure that was generated in an unfolding simulation at 498 K and was then quenched to folding-permissive temperatures. The protein refolded successfully in only one of the 46 simulations, and in that case the refolding pathway mirrored the unfolding pathway at high temperature. In the 45 simulations in which the protein did not fully fold, nonnative salt bridges trapped the protein, which explains why the protein folds relatively slowly from the intermediate state.

Dynameomics: a comprehensive database of protein dynamics

The dynamic behavior of proteins is important for an understanding of their function and folding. We have performed molecular dynamics simulations of the native state and unfolding pathways of over 2000 protein/peptide systems (approximately 11,000 independent simulations) representing the majority of folds in globular proteins. These data are stored and organized using an innovative database approach, which can be mined to obtain both general and specific information about the dynamics and folding/unfolding of proteins, relevant subsets thereof, and individual proteins. Here we describe the project in general terms and the type of information contained in the database. Then we provide examples of mining the database for information relevant to protein folding, structure building, the effect of single-nucleotide polymorphisms, and drug design. The native state simulation data and corresponding analyses for the 100 most populated metafolds, together with related resources, are publicly accessible through http://www.dynameomics.org.