Conformations of Isolated Macromolecules in Solution and on the Surface

This dissertation studies different aspects of conformational properties of polymers. Two specific topics include (i) the deviations of single macromolecule conformations in the q-solution from the classical description, and (ii) conformations, order and flow of molecular brushes on solid surfaces. In solution we studied the deviations of single macromolecule conformations at the q-conditions from the predictions of classical theories. The previously unknown long range correlations in the conformations of linear polymers in a q-solvent were found using analytical calculations and molecular dynamics simulations. Long range power law decay of the bond vector correlation function hcosfi ¡« s.3/2 dominate the standard exponential decay hcosfi = e.s/lp , where f is the angle between the two bonds, s is their separation along the chain contour and lp is the persistence length. These long-range correlations lead to significant deviations of polymer size from ideal with mean square end-to-end distance hR2i.b2N ¡« ¡ÌN, where N is the number of Kuhn segments of size b. These findings are explained by a fine interplay of polymer connectivity and the non-zero range of monomer interactions. Moreover, this effect is not specific for dilute q-solutions and exists in semidilute solutions and melts of polymers. Our theory is in good agreement with the experimental data on Flory characteristic ratio, as well as with results of computer simulations. On surfaces, brush-like macromolecules were visualized by the atomic force microscopy (AFM). In order to quantitatively analyze conformations of visualized molecules we developed the corresponding algorithms and software. This software enables detection of the molecular contour, measurement of molecule size, area, orientational and nematic order parameters, etc. In addition, the automated procedure of molecular detection reduced the time and improved the quality of analysis of image series. Using our method we have studied the molecular weight and polydispersity of linear and multi-arm molecular brushes, the spontaneous curvature of grafted molecules, which is caused by competition of conformational entropy of side chains and elasticity of backbone, behavior of brushes in a matrix of linear polymer, the effect of structure of multi-armed brushes on their 2d orientational order, the dynamics and conformational transitions of individual molecules in the precursor layer of spreading droplet, the spontaneous scission of grafted molecules with long side-chains

Discrete Molecular Dynamics: An Efficient And Versatile Simulation Method For Fine Protein Characterization

Until now it has been impractical to observe protein folding in silico for proteins larger than 50 residues. Limitations of both force field accuracy and computational efficiency make the folding problem very challenging. Here we employ discrete molecular dynamics (DMD) simulations with an all-atom force field to fold fast-folding proteins. We extend the DMD force field by introducing long-range electrostatic interactions to model salt-bridges and a sequence-dependent semi-empirical potential accounting for natural tendencies of certain amino acid sequences to form specific secondary structures. We enhance the computational performance by parallelizing the DMD algorithm. Using a small number of commodity computers, we achieve sampling quality and folding accuracy comparable to the explicit-solvent simulations performed on high-end hardware. We demonstrate that DMD can be used to observe equilibrium folding of villin headpiece and WW domain, study two-state folding kinetics and sample near-native states in ab initio folding of proteins of ~100 residues

Hybrid Dynamics Simulation Engine for Metalloproteins

Quality computational description of metalloproteins is a great challenge due to the vast span of time- and lengthscales characteristic of their existence. We present an efficient new method that allows for robust characterization of metalloproteins. It combines quantum mechanical (QM) description of the metal-containing active site, and extensive dynamics of the protein captured by discrete molecular dynamics (DMD) (QM/DMD). DMD samples the entire protein, including the backbone, and most of the active site, except for the immediate coordination region of the metal. QM operates on the part of the protein of electronic and chemical significance, which may include tens to hundreds of atoms. The breathing quantum-classical boundary provides a continuous mutual feedback between the two machineries. We test QM/DMD using the Fe-containing electron transporter protein, rubredoxin, and its three mutants as a model. QM/DMD can provide a reliable balanced description of metalloproteins’ structure, dynamics, and electronic structure in a reasonable amount of time. As an illustration of QM/DMD capabilities, we then predict the structure of the Ca2+ form of the enzyme catechol O-methyl transferase, which, unlike the native Mg2+ form, is catalytically inactive. The Mg2+ site is ochtahedral, but the Ca2+ is 7-coordinate and features the misalignment of the reacting parts of the system. The change is facilitated by the backbone adjustment. QM/DMD is ideal and fast for providing this level of structural insight

Structure of the atypical bacteriocin pectocin M2 implies a novel mechanism of protein uptake

The colicin-like bacteriocins are potent protein antibiotics that have evolved to efficiently cross the outer membrane of Gram-negative bacteria by parasitizing nutrient uptake systems. We have structurally characterized the colicin M-like bacteriocin, pectocin M2, which is active against strains of Pectobacterium spp. This unusual bacteriocin lacks the intrinsically unstructured translocation domain that usually mediates translocation of these bacteriocins across the outer membrane, containing only a single globular ferredoxin domain connected to its cytotoxic domain by a flexible α-helix, which allows it to adopt two distinct conformations in solution. The ferredoxin domain of pectocin M2 is homologous to plant ferredoxins and allows pectocin M2 to parasitize a system utilized by Pectobacterium to obtain iron during infection of plants. Furthermore, we identify a novel ferredoxin-containing bacteriocin pectocin P, which possesses a cytotoxic domain homologous to lysozyme, illustrating that the ferredoxin domain acts as a generic delivery module for cytotoxic domains in Pectobacterium

Distance dependence of angular correlations in dense polymer solutions

Angular correlations in dense solutions and melts of flexible polymer chains are investigated with respect to the distance $r$ between the bonds by comparing quantitative predictions of perturbation calculations with numerical data obtained by Monte Carlo simulation of the bond-fluctuation model. We consider both monodisperse systems and grand-canonical (Flory-distributed) equilibrium polymers. Density effects are discussed as well as finite chain length corrections. The intrachain bond-bond correlation function $P(r)$ is shown to decay as $P(r) \sim 1/r^3$ for \xi \ll r \ll \r^* with $\xi$ being the screening length of the density fluctuations and $r^* \sim N^{1/3}$ a novel length scale increasing slowly with (mean) chain length $N$.Comment: 17 pages, 5 figures, accepted for publication at Macromolecule

Light Regulation of Protein Dimerization and Kinase Activity in Living Cells Using Photocaged Rapamycin and Engineered FKBP

We developed a new system for light-induced protein dimerization in living cells using a novel photocaged analog of rapamycin (pRap) together with an engineered rapamycin binding domain (iFKBP). Using focal adhesion kinase as a target, we demonstrated successful light-mediated regulation of protein interaction and localization in living cells. Modification of this approach enabled light-triggered activation of a protein kinase and initiation of kinase-induced phenotypic changes in vivo

Computational approaches to understanding protein aggregation in neurodegeneration

The generation of toxic non-native protein conformers has emerged as a unifying thread among disorders such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Atomic-level detail regarding dynamical changes that facilitate protein aggregation, as well as the structural features of large-scale ordered aggregates and soluble non-native oligomers, would contribute significantly to current understanding of these complex phenomena and offer potential strategies for inhibiting formation of cytotoxic species. However, experimental limitations often preclude the acquisition of high-resolution structural and mechanistic information for aggregating systems. Computational methods, particularly those combine both all-atom and coarse-grained simulations to cover a wide range of time and length scales, have thus emerged as crucial tools for investigating protein aggregation. Here we review the current state of computational methodology for the study of protein self-assembly, with a focus on the application of these methods toward understanding of protein aggregates in human neurodegenerative disorders

Rational design of a ligand-controlled protein conformational switch

Design of a regulatable multistate protein is a challenge for protein engineering. Here we design a protein with a unique topology, called uniRapR, whose conformation is controlled by the binding of a small molecule. We confirm switching and control ability of uniRapR in silico, in vitro, and in vivo. As a proof of concept, uniRapR is used as an artificial regulatory domain to control activity of kinases. By activating Src kinase using uniRapR in single cells and whole organism, we observe two unique phenotypes consistent with its role in metastasis. Activation of Src kinase leads to rapid induction of protrusion with polarized spreading in HeLa cells, and morphological changes with loss of cell–cell contacts in the epidermal tissue of zebrafish. The rational creation of uniRapR exemplifies the strength of computational protein design, and offers a powerful means for targeted activation of many pathways to study signaling in living organisms

Scale-free static and dynamical correlations in melts of monodisperse and Flory-distributed homopolymers: A review of recent bond-fluctuation model studies

It has been assumed until very recently that all long-range correlations are screened in three-dimensional melts of linear homopolymers on distances beyond the correlation length $\xi$ characterizing the decay of the density fluctuations. Summarizing simulation results obtained by means of a variant of the bond-fluctuation model with finite monomer excluded volume interactions and topology violating local and global Monte Carlo moves, we show that due to an interplay of the chain connectivity and the incompressibility constraint, both static and dynamical correlations arise on distances $r \gg \xi$. These correlations are scale-free and, surprisingly, do not depend explicitly on the compressibility of the solution. Both monodisperse and (essentially) Flory-distributed equilibrium polymers are considered.Comment: 60 pages, 49 figure

Discrete molecular dynamics can predict helical prestructured motifs in disordered proteins.

Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating alpha-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts alpha-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect alpha-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available