1,721,013 research outputs found
Protein dynamics: complex by itself
No full textBiological functions are intimately rooted in biopolymer dynamics. It is commonly accepted that proteins can be considered as complex systems, but the origin of such complexity is still not fully understood. Moreover, it is still not really clear if proteins are true complex systems or complicated ones. Here, molecular dynamics simulations on a two helix bundle protein have been performed, and protein trajectories have been analyzed by using correlation functions in the frequency domain. We show that even a simple protein exhibits the hallmarks of complex systems. Moreover, the molecular bases of this complex behavior are possessed completely by the protein itself, because such complexity emerges without considering the solvent explicitly
Cytochrome c oxidase structures suggest a four-state stochastic pump mechanism
No full textCytochrome c oxidase catalyses the terminal step of cellular respiration in eukaryotes and in many prokaryotes. This enzyme reduces molecular oxygen by means of a process coupled with proton pumping. Models for proton pumping activity in cytochrome c oxidase can be divided into two groups, which are still strongly debated to date: one in which haem a is the key player, and another where this role is covered by the oxygen reduction site. Current models share the fact of requesting, more or less explicitly, an ordered sequence of events. Here, we show that all the available subunit I structures of this enzyme can be clustered in four groups. Starting from these structural observations, and considering the large corpus of available experimental data and theoretical considerations, a simple four-state (stochastic) pump model is proposed. This model implies a series of characteristics that reflect the behavior of the real enzyme in a natural way, where strictly sequential models require ad hoc assumptions (e.g. slipping mechanisms). Our results suggest that the stochastic conformational coupling could be a mechanism for energy transduction used by the protein machines
Random Matrix Theory in molecular dynamics analysis
No full textIt is well known that, in some situations, principal component analysis (PCA) carried out on molecular dynamics data results in the appearance of cosine-shaped low index projections. Because this is reminiscent of the results obtained by performing PCA on a multidimensional Brownian dynamics, it has been suggested that short-time protein dynamics is essentially nothing more than a noisy signal. Here we use Random Matrix Theory to analyze a series of short-time molecular dynamics experiments which are specifically designed to be simulations with high cosine content. We use as a model system the protein apoCox17, a mitochondrial copper chaperone. Spectral analysis on correlation matrices allows to easily differentiate random correlations, simply deriving from the finite length of the process, from non-random signals reflecting the intrinsic system properties. Our results clearly show that protein dynamics is not really Brownian also in presence of the cosine-shaped low index projections on principal axes
Amyloid beta(1–42) in aqueous environments: Effects of ionic strength and E22Q (Dutch) mutation
No full textDevelopment of extracellular plaques characteristic of Alzheimer’s disease is related to aggregation of amyloid peptides. The Aβ-42 peptide is the most aggregation prone species, and some missense mutant forms increase this aggregation ability. Due to its poor solubility as monomer in aqueous solutions, Aβ-42 conformational transitions in water have been largely investigated by molecular dynamics. Here we report an all-atom molecular dynamics analysis of the Aβ-42 peptide in aqueous environment using as starting conformation a structure obtained in an isotropic, low-polarity medium, representing a plausible model for the membrane-bound species. While previous studies commonly show that Aβ-42 is largely unstructured in aqueous solution, here we report that this peptide can adopt partially folded structures. Importance of ionic strength has been also investigated, showing that at physiological ionic strength condition a loop stabilizing electrostatic interaction involving Lys28 builds-up. In addition, beside stable α-helix structures, we observe the appearance of 310 helix, similar to what reported experimentally for the Aβ-40 species. The effect of E22Q (Dutch) mutation in high ionic strength condition has been explored. We show that this mutation has a dramatic impact on the Aβ-42 structure. Instead of a partially folded, but extended, conformation obtained with the wild type, the E22Q assumes a two-helix collapsed one due to the clustering of hydrophobic residues
The human extended mitochondrial metabolic network: New hubs from lipids
No full textEven if systems thinking is not new in biology, rationalizing the explosively growing amount of knowledge
has been the compelling reason for the sudden rise and spreading of systems biology. Based on ‘omics’
data, several genome-scale metabolic networks have been reconstructed and validated. One of the most
striking aspects of complex metabolic networks is the pervasive power-law appearance of metabolite
connectivity. However, the combinatorial diversity of some classes of compounds, such as lipids, has been
scarcely considered so far. In this work, a lipid-extended human mitochondrial metabolic network has
been built and analyzed. It is shown that, considering combinatorial diversity of lipids and multipurpose
enzymes, an intimate connection between membrane lipids and oxidative phosphorilation appears. This
finding leads to some biomedical considerations on diseases involving mitochondrial enzymes. Moreover,
the lipid-extended network still shows power-law features. Power-law distributions are intrinsic
to metabolic network organization and evolution. Hubs in the lipid-extended mitochondrial network
strongly suggest that the “RNA world” and the “lipid world” hypothesis are both correct
Correlation Analysis of Trp-Cage Dynamics in Folded and Unfolded States
No full textA fundamental and still debated problem is how folded structures of proteins are related to their unfolded state. Besides the classical view, in which a large number of conformations characterize the unfolded state while the folded one is dominated by a single structure, recently a reassessment of the denatured state has been suggested. A growing amount of evidence indicates that not only the folded but also the unfolded state is at least partially organized. Here, we try to answer the question of how different protein dynamics is in folded and unfolded states by performing all-atom molecular dynamics simulations on the model protein Trp-cage. Random matrix theory inspired analysis of the correlation matrices has been carried out. The spectra of these correlation matrices show that the low rank modes of Trp-cage dynamics are outside of the limit expected for a random system both in folded and in unfolded conditions. These findings shed light on the nature of the unfolded state of the proteins, suggesting that it is much less random than previously thought
A random version of principal component analysis in data clustering
Full text linkPrincipal component analysis (PCA) is a widespread technique for data analysis that relies on the covariance/correlation matrix of the analyzed data. However, to properly work with high-dimensional data sets, PCA poses severe mathematical constraints on the minimum number of different replicates, or samples, that must be included in the analysis. Generally, improper sampling is due to a small number of data respect to the number of the degrees of freedom that characterize the ensemble. In the field of life sciences it is often important to have an algorithm that can accept poorly dimensioned data sets, including degenerated ones. Here a new random projection algorithm is proposed, in which a random symmetric matrix surrogates the covariance/correlation matrix of PCA, while maintaining the data clustering capacity. We demonstrate that what is important for clustering efficiency of PCA is not the exact form of the covariance/correlation matrix, but simply its symmetry
Analysis of the conformations of the HIV-1 protease from a large crystallographic data set
Full text linkThe HIV-1 protease performs essential roles in viral maturation by processing specific cleavage sites in the Gag and Gag-Pol precursor polyproteins to release their mature forms. Here the analysis of a large HIV-1 protease data set (containing 552 dimer structures) are reported. These data are related to article entitled âConformations of the HIV-1 protease: a crystal structure data set analysisâ (Palese, 2017) [1]
Conformations of the HIV-1 protease: A crystal structure data set analysis
No full textThe HIV protease is an important drug target for HIV/AIDS therapy, and its structure and function have been extensively investigated. This enzyme performs an essential role in viral maturation by processing specific cleavage sites in the Gag and Gag-Pol precursor polyproteins so as to release their mature forms. This 99 amino acid aspartic protease works as a homodimer, with the active site localized in a central cavity capped by two flexible flap regions. The dimer presents closed or open conformations, which are involved in the substrate binding and release. Here the results of the analysis of a HIV-1 protease data set containing 552 dimer structures are reported. Different dimensionality reduction methods have been used in order to get information from this multidimensional database. Most of the structures in the data set belong to two conformational clusters. An interesting observation that comes from the analysis of these data is that some protease sequences are localized preferentially in specific areas of the conformational landscape of this protein
Protein States as Symmetry Transitions in the Correlation Matrices
No full textOver the last few years, there has been significant progress in the knowledge on protein folding. However, some aspects of protein folding still need further attention. One of these is the exact relationship between the folded and unfolded states and the differences between them. Whereas the folded state is well known, at least from a structural point of view (just think of the thousands of structures in online databases), the unfolded state is more elusive. Also, these are dynamic states of matter, and this aspect cannot be overlooked. Molecular dynamics-derived correlation matrices are an invaluable source of information on the protein dynamics. Here, bulk eigenvalue spectra of the correlation matrices obtained from the Trp-cage dynamics in the folded and unfolded states have been analyzed. The associated modes represent localized vibrations and are significantly affected by the fine details of the structure and interactions. Therefore, these bulk modes can be used as probes of the protein local dynamics in different states. The results of these analyses show that the correlation matrices describing the folded and unfolded dynamics belong to different symmetry classes. This finding provides new support to the phase-transition models of protein folding
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