Dynameomics: a consensus view of the protein unfolding/folding transition state ensemble across a diverse set of protein folds

Tumorigenic p53 mutants undergo common structural disruptions including conversion to α-sheet structure

The p53 protein is a commonly studied cancer target because of its role in tumor suppression. Unfortunately, it is susceptible to mutation-associated loss of function; approximately 50% of cancers are associated with mutations to p53, the majority of which are located in the central DNA-binding domain. Here, we report molecular dynamics simulations of wild-type (WT) p53 and 20 different mutants, including a stabilized pseudo-WT mutant. Our findings indicate that p53 mutants tend to exacerbate latent structural-disruption tendencies, or vulnerabilities, already present in the WT protein, suggesting that it may be possible to develop cancer therapies by targeting a relatively small set of structural-disruption motifs rather than a multitude of effects specific to each mutant. In addition, α-sheet secondary structure formed in almost all of the proteins. α-Sheet has been hypothesized and recently demonstrated to play a role in amyloidogenesis, and its presence in the reported p53 simulations coincides with the recent re-consideration of cancer as an amyloid disease.

Discrete analyses of protein dynamics

Protein structures are highly dynamic macromolecules. This dynamics is often analysed through experimental and/or computational methods only for an isolated or a limited number of proteins. Here, we explore large-scale protein dynamics simulation to observe dynamics of local protein conformations using different perspectives. We analysed molecular dynamics to investigate protein flexibility locally, using classical approaches such as RMSf, solvent accessibility, but also innovative approaches such as local entropy. First, we focussed on classical secondary structures and analysed specifically how β-strand, β-turns, and bends evolve during molecular simulations. We underlined interesting specific bias between β-turns and bends, which are considered as the same category, while their dynamics show differences. Second, we used a structural alphabet that is able to approximate every part of the protein structures conformations, namely protein blocks (PBs) to analyse (i) how each initial local protein conformations evolve during dynamics and (ii) if some exchange can exist among these PBs. Interestingly, the results are largely complex than simple regular/rigid and coil/flexible exchange. AbbreviationsN_eqnumber of equivalentPBProtein BlocksPDBProtein DataBankRMSfroot mean square fluctuationsCommunicated by Ramaswamy H. Sarma.

Influence of glycerol on the cooling effect of pair hydrophobicity in water: relevance to proteins’ stabilization at low temperature

Glycerol reduces the cooling effect of pair hydrophobicity (reduction of hydrophobicity with decreasing temperature) in water.

Molecular dynamics-derived rotamer libraries for d-amino acids within homochiral and heterochiral polypeptides

Computational resources have contributed to the design and engineering of novel proteins by integrating genomic, structural and dynamic aspects of proteins. Non-canonical amino acids, such as d-amino acids, expand the available sequence space for designing and engineering proteins; however, the rotamer libraries for d-amino acids are usually constructed as the mirror images of l-amino acid rotamer libraries, an assumption that has not been tested. To this end, we have performed molecular dynamics (MD) simulations of model host-guest peptide systems containing d-amino acids. Our simulations systematically address the applicability of the mirror image convention as well as the effects of neighboring residue chirality. Rotamer libraries derived from these systems provide realistic rotamer distributions suitable for use in both rational and computational design workflows. Our simulations also address the impact of chirality on the intrinsic conformational preferences of amino acids, providing fundamental insights into the relationship between chirality and biomolecular dynamics. While d-amino acids are rare in naturally occurring proteins, they are used in designed proteins to stabilize a desired conformation, increase bioavailability or confer favorable biochemical and physical attributes. Here, we present d-amino acid rotamer libraries derived from MD simulations of alanine-based host-guest pentapeptides and show how certain residues can deviate from mirror image symmetry. Our simulations directly model d-amino acids as guest residues within the chiral l-Ala and d-Ala pentapeptide series to explicitly incorporate any contributions resulting from the chiralities of neighboring residues.

Comparative thermal unfolding study of psychrophilic and mesophilic subtilisin-like serine proteases by molecular dynamics simulations

Molecular dynamics (MD) simulations of a subtilisin-like serine protease VPR from the psychrophilic marine bacterium Vibrio sp. PA-44 and its mesophilic homologue, proteinase K (PRK), have been performed for 20 ns at four different temperatures (300, 373, 473, and 573 K). The comparative analyses of MD trajectories reveal that at almost all temperatures, VPR exhibits greater structural fluctuations/deviations, more unstable regular secondary structural elements, and higher global flexibility than PRK. Although these two proteases follow similar unfolding pathways at high temperatures, VPR initiates unfolding at a lower temperature and unfolds faster at the same high temperatures than PRK. These observations collectively indicate that VPR is less stable and more heat-labile than PRK. Analyses of the structural/geometrical properties reveal that, when compared to PRK, VPR has larger radius of gyration (Rg), less intramolecular contacts and hydrogen bonds (HBs), more protein-solvent HBs, and smaller burial of nonpolar area and larger exposure of polar area. These suggest that the increased flexibility of VPR would be most likely caused by its reduced intramolecular interactions and more favourable protein-solvent interactions arising from the larger exposure of the polar area, whereas the enhanced stability of PRK could be ascribed to its increased intramolecular interactions arising from the better optimized hydrophobicity. The factors responsible for the significant differences in local flexibility between these two proteases were also analyzed and ascertained. This study provides insights into molecular basis of thermostability of homologous serine proteases adapted to different temperatures.

Digging for Buried Amino Acids Unearths New Protein Quality Control Treasure

Proteins rely on three-dimensional structure for function, yet many proteins are marginally stable and prone to misfolding. In this issue of Structure, Brock et al. (2015) present a novel computational modeling method to gain insights into protein stability and misfolding.

Structural and dynamic evolution of the amphipathic N-terminus diversifies enzyme thermostability in the glycoside hydrolase family 12

The N-terminus diversifies enzyme thermostability in the GH12 family, which was investigated by MD simulations, and provides potential applications in protein engineering.

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.

Take home lessons from studies of related proteins

The 'Fold Approach' involves a detailed analysis of the folding of several topologically, structurally and/or evolutionarily related proteins. Such studies can reveal determinants of the folding mechanism beyond the gross topology, and can dissect the residues required for folding from those required for stability or function. While this approach has not yet matured to the point where we can predict the native conformation of any polypeptide chain in silico, it has been able to highlight, amongst others, the specific residues that are responsible for nucleation, pathway malleability, kinetic intermediates, chain knotting, internal friction and Paracelsus switches. Some of the most interesting discoveries have resulted from the attempt to explain differences between homologues.

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.

Effects of thermal denaturation on the solid-state structure and molecular mobility of glycinin

The effects of moisture and thermal denaturation on the solid-state structure and molecular mobility of soy glycinin powder were investigated using multiple techniques that probe over a range of length and time scales. In native glycinin, increased moisture resulted in a decrease in both the glass transition temperature and the denaturation temperature. The sensitivity of the glass transition temperature to moisture is shown to follow the Gordon-Taylor equation, while the sensitivity of the denaturation temperature to moisture is modeled using Flory's melting point depression theory. While denaturation resulted in a loss of long-range order, the principal conformational structures as detected by infrared are maintained. The temperature range over which the glass to rubber transition occurred was extended on the high temperature side, leading to an increase in the midpoint glass transition temperature and suggesting that the amorphous regions of the newly disordered protein are less mobile. (13)C NMR results supported this hypothesis.

Protein structure along the order-disorder continuum

Thermal fluctuations cause proteins to adopt an ensemble of conformations wherein the relative stability of the different ensemble members is determined by the topography of the underlying energy landscape. “Folded” proteins have relatively homogeneous ensembles, while “unfolded” proteins have heterogeneous ensembles. Hence, the labels “folded” and “unfolded” represent attempts to provide a qualitative characterization of the extent of structural heterogeneity within the underlying ensemble. In this work, we introduce an information-theoretic order parameter to quantify this conformational heterogeneity. We demonstrate that this order parameter can be estimated in a straightforward manner from an ensemble and is applicable to both unfolded and folded proteins. In addition, a simple formula for approximating the order parameter directly from crystallographic B factors is presented. By applying these metrics to a large sample of proteins, we show that proteins span the full range of the order–disorder axis.

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.

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.

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

The goal of the Dynameomics project is to perform, store, and analyze molecular dynamics simulations of representative proteins, of all known globular folds, in their native state and along their unfolding pathways. To analyze unfolding simulations, the location of the protein along the unfolding reaction coordinate (RXN) must be determined. Properties such as the fraction of native contacts and radius of gyration are often used; however, there is an issue regarding degeneracy with these properties, as native and nonnative species can overlap. Here, we used 15 physical properties of the protein to construct a multidimensional-embedded, one-dimensional RXN coordinate that faithfully captures the complex nature of unfolding. The unfolding RXN coordinates for 188 proteins (1534 simulations and 22.9 mus in explicit water) were calculated. Native, transition, intermediate, and denatured states were readily identified with the use of this RXN coordinate. A global native ensemble based on the native-state properties of the 188 proteins was created. This ensemble was shown to be effective for calculating RXN coordinates for folds outside the initial 188 targets. These RXN coordinates enable, high-throughput assignment of conformational states, which represents an important step in comparing protein properties across fold space as well as characterizing the unfolding of individual proteins.

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.

Fine grained sampling of residue characteristics using molecular dynamics simulation

In a fine-grained computational analysis of protein structure, we investigated the relationships between a residue's backbone conformations and its side-chain packing as well as conformations. To produce continuous distributions in high resolution, we ran molecular dynamics simulations over a set of protein folds (dynameome). In effect, the dynameome dataset samples not only the states well represented in the PDB but also the known states that are not well represented in the structural database. In our analysis, we characterized the mutual influence among the backbone phi,psi angles with the first side-chain torsion angles (chi(1)) and the volumes occupied by the side-chains. The dependencies of these relationships on side-chain environment and amino acids are further explored. We found that residue volumes exhibit dependency on backbone 2 degrees structure conformation: side-chains pack more densely in extended beta-sheet than in alpha-helical structures. As expected, residue volumes on the protein surface were larger than those in the interior. The first side-chain torsion angles are found to be dependent on the backbone conformations in agreement with previous studies, but the dynameome dataset provides higher resolution of rotamer preferences based on the backbone conformation. All three gauche(-), gauche(+), and trans rotamers show different patterns of phi,psi dependency, and variations in chi(1) value are skewed from their canonical values to relieve the steric strains. By demonstrating the utility of dynameomic modeling on the native state ensemble, this study reveals details of the interplay among backbone conformations, residue volumes and side-chain conformations.