arXiv subjects

Ruxandra I. Dima

Publications and source records attributed to Ruxandra I. Dima.

8 recordsLinked to original sources

arXiv2015

Structural transitions and energy landscape for Cowpea Chlorotic Mottle Virus capsid mechanics from nanomanipulation in vitro and in silico

Physical properties of capsids of plant and animal viruses are important factors in capsid self-assembly, survival of viruses in the extracellular environment, and their cell infectivity. Virus shells can have applications as nanocontainers and delivery vehicles in biotechnology and medicine. Combined AFM experiments and computational modeling on sub-second timescales of the indentation nanomechanics of Cowpea Chlorotic Mottle Virus (CCMV) capsid show that the capsid's physical properties are dynamic and local characteristics of the structure, which depend on the magnitude and geometry of mechanical input. Surprisingly, under large deformations the CCMV capsid transitions to the collapsed state without substantial local structural alterations. The enthalpy change in this deformation state dH = 11.5 - 12.8 MJ/mol is mostly due to large-amplitude out-of-plane excitations, which contribute to the capsid bending, and the entropy change TdS = 5.1 - 5.8 MJ/mol is mostly due to coherent in-plane rearrangements of protein chains, which result in the capsid stiffening. Dynamic coupling of these modes defines the extent of elasticity and reversibility of capsid mechanical deformation. This emerging picture illuminates how unique physico-chemical properties of protein nanoshells help define their structure and morphology, and determine their viruses' biological function.

physics.bio-ph↗

arXiv2015

Tubulin bond energies and microtubule biomechanics determined from nanoindentation in silico

Microtubules, the primary components of the chromosome segregation machinery, are stabilized by longitudinal and lateral non-covalent bonds between the tubulin subunits. However, the thermodynamics of these bonds and the microtubule physico-chemical properties are poorly understood. Here, we explore the biomechanics of microtubule polymers using multiscale computational modeling and nanoindentations in silico of a contiguous microtubule fragment. A close match between the simulated and experimental force-deformation spectra enabled us to correlate the microtubule biomechanics with dynamic structural transitions at the nanoscale. Our mechanical testing revealed that the compressed MT behaves as a system of rigid elements interconnected through a network of lateral and longitudinal elastic bonds. The initial regime of continuous elastic deformation of the microtubule is followed by the transition regime, during which the microtubule lattice undergoes discrete structural changes, which include first the reversible dissociation of lateral bonds followed by irreversible dissociation of the longitudinal bonds. We have determined the free energies of dissociation of the lateral (6.9+/-0.4 kcal/mol) and longitudinal (14.9+/-1.5 kcal/mol) tubulin-tubulin bonds. These values in conjunction with the large flexural rigidity of tubulin protofilaments obtained (18,000-26,000 pN*nm^2), support the idea that the disassembling microtubule is capable of generating a large mechanical force to move chromosomes during cell division. Our computational modeling offers a comprehensive quantitative platform to link molecular tubulin characteristics with the physiological behavior of microtubules. The developed in silico nanoindentation method provides a powerful tool for the exploration of biomechanical properties of other cytoskeletal and multiprotein assemblies

physics.bio-ph↗

arXiv2007

Allosteric communication in Dihydrofolate Reductase: Signaling network and pathways for closed to occluded transition and back

E. Coli. dihydrofolate reductase (DHFR) undergoes conformational transitions between the closed (CS) and occluded (OS) states which, respectively, describe whether the active site is closed or occluded by the Met20 loop. A sequence-based approach is used to identify a network of residues that represents the allostery wiring diagram. We also use a self-organized polymer model to monitor the kinetics of the CS->OS and the reverse transitions. a sliding motion of Met20 loop is observed. The residues that facilitate the Met20 loop motion are part of the network of residues that transmit allosteric signals during the CS->OS transition.

q-bio.BM↗

arXiv2006

Size, shape, and flexibility of RNA structures

Determination of sizes and flexibilities of RNA molecules is important in understanding the nature of packing in folded structures and in elucidating interactions between RNA and DNA or proteins. Using the coordinates of the structures of RNA in the Protein Data Bank we find that the size of the folded RNA structures, measured using the radius of gyration, $R_G$, follows the Flory scaling law, namely, $R_G =5.5 N^{1/3}$ Åwhere N is the number of nucleotides. The shape of RNA molecules is characterized by the asphericity $Δ$ and the shape $S$ parameters that are computed using the eigenvalues of the moment of inertia tensor. From the distribution of $Δ$, we find that a large fraction of folded RNA structures are aspherical and the distribution of $S$ values shows that RNA molecules are prolate ($S>0$). The flexibility of folded structures is characterized by the persistence length $l_p$. By fitting the distance distribution function $P(r)$ to the worm-like chain model we extracted the persistence length $l_p$. We find that $l_p\approx 1.5 N^{0.33}$ Å. The dependence of $l_p$ on $N$ implies the average length of helices should increases as the size of RNA grows. We also analyze packing in the structures of ribosomes (30S, 50S, and 70S) in terms of $R_G$, $Δ$, $S$, and $l_p$. The 70S and the 50S subunits are more spherical compared to most RNA molecules. The globularity in 50S is due to the presence of an unusually large number (compared to 30S subunit) of small helices that are stitched together by bulges and loops. Comparison of the shapes of the intact 70S ribosome and the constituent particles suggests that folding of the individual molecules might occur prior to assembly.

q-bio.BM↗

arXiv2006

Scenarios for protein aggregation: Molecular Dynamics simulations and Bioinformatic Analysis

The need to understand the assembly kinetics of fibril formation has become urgent because of the realization that soluble oligomers of amyloidogenic peptides may be even more neurotoxic than the end product, namely, the amyloid fibrils. In order to fully understand the routes to fibril formation one has to characterize the major species in the assembly pathways. The characterization of the energetics and dynamics of oligomers (dimers, trimers etc) is difficult using experiments alone because they undergo large conformational fluctuations. In this context, carefully planned molecular dynamics simulation studies, computations using coarse-grained models, and bioinformatic analysis have given considerable insights into the early events in the route to fibril formation. Here, we describe progress along this direction using examples taken largely from our own work. In this chapter, we focus on aspects of protein aggregation using Abeta-peptides and prion proteins as examples.

q-bio.BM↗

arXiv2004

Proteins associated with diseases show enhanced sequence correlation between charged residues

Function of proteins or a network of interacting proteins often involves communication between residues that are well separated in sequence. The classic example is the participation of distant residues in allosteric regulation. Bioinformatic and structural analysis methods have been introduced to infer residues that are correlated. Recently, increasing attention has been paid to obtain the sequence properties that determine the tendency of disease related proteins (Abeta peptides, prion proteins, transthyretin etc.) to aggregate and form fibrils. Motivated in part by the need to identify sequence characteristics that indicate a tendency to aggregate, we introduce a general method that probes covariations in charged residues along the sequence in a given protein family. The method, which involves computing the Sequence Correlation Entropy (SCE) using the quenched probability Psk(i,j) of finding a residue pair at a given sequence separation sk, allows us to classify protein families in terms of their SCE. Our general approach may be a useful way in obtaining evolutionary covariations of amino acid residues on a genome wide level.

q-bio.BM↗

arXiv2003

Asymmetry in the shapes of folded and denatured states of proteins

The asymmetry in the shapes of folded and unfolded states are probed using two parameters, one being a measure of the sphericity and the other that describes the shape. For the folded states, whose interiors are densely packed, the radii of gyration (Rg) and these two parameters are calculated using the coordinates of the experimentally determined structures. Although Rg scales as expected for maximally compact structures, the distributions of the shape parameters show that there is considerable asymmetry in the shapes of folded structures. The degree of asymmetry is greater for proteins that form oligomers. Analysis of the two- and three-body contacts in the native structures shows that the presence of near equal number of contacts between backbone and side-chains and between side-chains gives rise to dense packing. We suggest that proteins with relatively large values of shape parameters can tolerate volume mutations without greatly affecting the network of contacts or their stability. To probe shape characteristics of denatured states we have developed a model of a WW-like domain. The shape parameters, which are calculated using Langevin simulations, change dramatically in the course of coil to globule transition. Comparison of the values of shape parameters between the globular state and the folded state of WW domain shows that both energetic (especially dispersion in the hydrophobic interactions) and steric effects are important in determining packing in proteins.

q-bio.BM↗

arXiv2001

Protein threading by learning

Using techniques borrowed from statistical physics and neural networks, we determine the parameters, associated with a scoring function, that are chosen optimally to ensure complete success in threading tests in a training set of proteins. These parameters provide a quantitative measure of the propensities of amino acids to be buried or exposed and to be in a given secondary structure and are a good starting point for solving both the threading and design problems.

cond-mat.soft↗