Olga K. Dudko

Bio: Olga K. Dudko is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Force spectroscopy & Magnetization. The author has an hindex of 24, co-authored 50 publications receiving 3270 citations. Previous affiliations of Olga K. Dudko include University of Bath & Tel Aviv University.

Intrinsic rates and activation free energies from single-molecule pulling experiments.

Abstract: We present a unified framework for extracting kinetic information from single-molecule pulling experiments at constant force or constant pulling speed. Our procedure provides estimates of not only (i) the intrinsic rate coefficient and (ii) the location of the transition state but also (iii) the free energy of activation. By analyzing simulated data, we show that the resulting rates of force-induced rupture are significantly more reliable than those obtained by the widely used approach based on Bell's formula. We consider the uniqueness of the extracted kinetic information and suggest guidelines to avoid overinterpretation of experiments.

Theory, analysis, and interpretation of single-molecule force spectroscopy experiments

Abstract: Dynamic force spectroscopy probes the kinetic and thermodynamic properties of single molecules and molecular assemblies. Here, we propose a simple procedure to extract kinetic information from such experiments. The cornerstone of our method is a transformation of the rupture-force histograms obtained at different force-loading rates into the force-dependent lifetimes measurable in constant-force experiments. To interpret the force-dependent lifetimes, we derive a generalization of Bell's formula that is formally exact within the framework of Kramers theory. This result complements the analytical expression for the lifetime that we derived previously for a class of model potentials. We illustrate our procedure by analyzing the nanopore unzipping of DNA hairpins and the unfolding of a protein attached by flexible linkers to an atomic force microscope. Our procedure to transform rupture-force histograms into the force-dependent lifetimes remains valid even when the molecular extension is a poor reaction coordinate and higher-dimensional free-energy surfaces must be considered. In this case the microscopic interpretation of the lifetimes becomes more challenging because the lifetimes can reveal richer, and even nonmonotonic, dependence on the force.

Global analysis of X-chromosome dosage compensation

Abstract: Drosophila melanogaster females have two X chromosomes and two autosome sets (XX;AA), while males have a single X chromosome and two autosome sets (X;AA). Drosophila male somatic cells compensate for a single copy of the X chromosome by deploying male-specific-lethal (MSL) complexes that increase transcription from the X chromosome. Male germ cells lack MSL complexes, indicating that either germline X-chromosome dosage compensation is MSL-independent, or that germ cells do not carry out dosage compensation. To investigate whether dosage compensation occurs in germ cells, we directly assayed X-chromosome transcripts using DNA microarrays and show equivalent expression in XX;AA and X;AA germline tissues. In X;AA germ cells, expression from the single X chromosome is about twice that of a single autosome. This mechanism ensures balanced X-chromosome expression between the sexes and, more importantly, it ensures balanced expression between the single X chromosome and the autosome set. Oddly, the inactivation of an X chromosome in mammalian females reduces the effective X-chromosome dose and means that females face the same X-chromosome transcript deficiency as males. Contrary to most current dosage-compensation models, we also show increased X-chromosome expression in X;AA and XX;AA somatic cells of Caenorhabditis elegans and mice. Drosophila germ cells compensate for X-chromosome dose. This occurs by equilibrating X-chromosome and autosome expression in X;AA cells. Increased expression of the X chromosome in X;AA individuals appears to be phylogenetically conserved.

Beyond the conventional description of dynamic force spectroscopy of adhesion bonds

Abstract: Dynamic force spectroscopy of single molecules is described by a model that predicts a distribution of rupture forces, the corresponding mean rupture force, and variance, which are all amenable to experimental tests. The distribution has a pronounced asymmetry, which has recently been observed experimentally. The mean rupture force follows a (lnV)2/3 dependence on the pulling velocity, V, and differs from earlier predictions. Interestingly, at low pulling velocities, a rebinding process is obtained whose signature is an intermittent behavior of the spring force, which delays the rupture. An extension to include conformational changes of the adhesion complex is proposed, which leads to the possibility of bimodal distributions of rupture forces.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Molecular self-assembly and nanochemistry: A chemical strategy for the synthesis of nanostructures

Abstract: Molecular self-assembly is the spontaneous association of molecules under equilibrium conditions into stable, structurally well-defined aggregates joined by noncovalent bonds. Molecular self-assembly is ubiquitous in biological systems and underlies the formation of a wide variety of complex biological structures. Understanding self-assembly and the associated noncovalent interactions that connect complementary interacting molecular surfaces in biological aggregates is a central concern in structural biochemistry. Self-assembly is also emerging as a new strategy in chemical synthesis, with the potential of generating nonbiological structures with dimensions of 1 to 10(2) nanometers (with molecular weights of 10(4) to 10(10) daltons). Structures in the upper part of this range of sizes are presently inaccessible through chemical synthesis, and the ability to prepare them would open a route to structures comparable in size (and perhaps complementary in function) to those that can be prepared by microlithography and other techniques of microfabrication.

Anomalous diffusion models and their properties: non-stationarity, non-ergodicity, and ageing at the centenary of single particle tracking.

Abstract: Modern microscopic techniques following the stochastic motion of labelled tracer particles have uncovered significant deviations from the laws of Brownian motion in a variety of animate and inanimate systems. Such anomalous diffusion can have different physical origins, which can be identified from careful data analysis. In particular, single particle tracking provides the entire trajectory of the traced particle, which allows one to evaluate different observables to quantify the dynamics of the system under observation. We here provide an extensive overview over different popular anomalous diffusion models and their properties. We pay special attention to their ergodic properties, highlighting the fact that in several of these models the long time averaged mean squared displacement shows a distinct disparity to the regular, ensemble averaged mean squared displacement. In these cases, data obtained from time averages cannot be interpreted by the standard theoretical results for the ensemble averages. Here we therefore provide a comparison of the main properties of the time averaged mean squared displacement and its statistical behaviour in terms of the scatter of the amplitudes between the time averages obtained from different trajectories. We especially demonstrate how anomalous dynamics may be identified for systems, which, on first sight, appear to be Brownian. Moreover, we discuss the ergodicity breaking parameters for the different anomalous stochastic processes and showcase the physical origins for the various behaviours. This Perspective is intended as a guidebook for both experimentalists and theorists working on systems, which exhibit anomalous diffusion.

Mechanically-induced chemical changes in polymeric materials

Abstract: Engineering applications of synthetic polymers are widespread due to their availability, processability, low density, and diversity of mechanical properties (Figure 1a). Despite their ubiquitous nature, modern polymers are evolving into multifunctional systems with highly sophisticated behavior. These emergent functions are commonly described as “smart” characteristics whereby “intelligence” is rooted in a specific response elicited from a particular stimulus. Materials that exhibit stimuli-responsive functions thus achieve a desired output (O, the response) upon being subjected to a specific input (I, the stimulus). Given that mechanical loading is inevitable, coupled with the wide range of mechanical properties for synthetic polymers, it is not surprising that mechanoresponsive polymers are an especially attractive class of smart materials. To design materials with stimuli-responsive functions, it is helpful to consider the I-O relationship as an energy transduction process. Achieving the desired I-O linkage thus becomes a problem in finding how to transform energy from the stimulus into energy that executes the desired response. The underlying mechanism that forms this I-O coupling need not be a direct, one-step transduction event; rather, the overall process may proceed through a sequence of energy transduction steps. In this regard, the network of energy transduction pathways is a useful roadmap for designing stimuli-responsive materials (Figure 1b). It is the purpose of this review to broadly survey the mechanical to chemical * To whom correspondence should be addressed. Phone: 217-244-4024. Fax: 217-244-8024. E-mail: jsmoore@illinois.edu. † Department of Chemistry and Beckman Institute. ‡ Department of Materials Science and Engineering and Beckman Institute. § Department of Aerospace Engineering and Beckman Institute. Chem. Rev. XXXX, xxx, 000–000 A

Nanopore analytics: sensing of single molecules

Abstract: In nanopore analytics, individual molecules pass through a single nanopore giving rise to detectable temporary blockades in ionic pore current. Reflecting its simplicity, nanopore analytics has gained popularity and can be conducted with natural protein as well as man-made polymeric and inorganic pores. The spectrum of detectable analytes ranges from nucleic acids, peptides, proteins, and biomolecular complexes to organic polymers and small molecules. Apart from being an analytical tool, nanopores have developed into a general platform technology to investigate the biophysics, physicochemistry, and chemistry of individual molecules (critical review, 310 references).