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Molecular dynamics simulations of liquid ethanol at four thermodynamic states ranging from T ) 173 K to T ) 348 K were carried out using the transferable OPLS potential model of Jorgensen (J. Phys. Chem. 1986Chem. , 90, 1276. Both static and dynamic properties are analyzed. The resulting properties show an overall agreement with available experimental data. Special attention is paid to the hydrogen bonds and to their influence on the molecular behavior. Results for liquid ethanol are compared with those for methanol in earlier computer simulation studies.

The formation of DNA loops by the binding of proteins and protein complexes at distal DNA sites plays a central role in many cellular processes, such as transcription, recombination and replication. Important thermodynamic concepts underlie the assembly of macromolecular complexes on looped DNA. The effects that this process has on the properties of gene regulation extend beyond the traditional view of DNA looping as a mechanism to increase the affinity of regulatory molecules for their cognate sites. Recent developments indicate that DNA looping can also lead to the suppression of cell-to-cell variability, the control of transcriptional noise, and the activation of cooperative interactions on demand.

The structure of a fully hydrated mixed (saturated/polyunsaturated) chain lipid bilayer in the biologically relevant liquid crystalline phase has been examined by performing a molecular dynamics study. The model membrane, a 1-stearoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine (SDPC, 18:0/22:6 PC) lipid bilayer, was investigated at constant (room) temperature and (ambient) pressure, and the results obtained in the nanosecond time scale reproduced quite well the available experimental data. Polyunsaturated fatty acids are found in high concentrations in neuronal and retinal tissues and are essential for the development of human brain function. The docosahexaenoic fatty acid, in particular, is fundamental for the proper function of the visual receptor rhodopsin. The lipid bilayer order has been investigated through the orientational order parameters. The water-lipid interface has been explored thoroughly in terms of its dimensions and the organization of the different components. Several types of interactions occurring in the system have been analyzed, specifically, the water-hydrocarbon chain, lipid-lipid and lipid-water interactions. The distribution of dihedral angles along the chains and the molecular conformations of the polyunsaturated chain of the lipids have also been studied. Special attention has been focused on the microscopic (molecular) origin of the effects of polyunsaturations on the different physical properties of membranes.

This Account is focused on computer simulation studies of model biological membrane systems with potential applications in biomedical research. In the past decade, classical molecular dynamics has provided novel insights into the properties of model biomembrane systems, including the nature of the DNA-lipid interactions, the effect of pore-forming transmembrane peptides on the lipid environment, and the partitioning of volatile anesthetic molecules. Such simulations, employing full atomic detail, are typically restricted to systems of dimensions less than approximately 10 nm. Simplified models of the coarse-grain type have been intended to bridge the gap between full atomistic detail and the mesoscopic (micron) regime. The use of such models is illustrated with the example of anesthetics in a phospholipid bilayer.

Aptamers consist of short oligonucleotides that bind specific targets. They provide advantages over antibodies, including robustness, low cost, and reusability. Their chemical structure allows the insertion of reporter molecules and surface-binding agents in specific locations, which have been recently exploited for the development of aptamer-based biosensors and direct detection strategies. Mainstream use of these devices, however, still requires significant improvements in optimization for consistency and reproducibility. DNA aptamers are more stable than their RNA counterparts for biomedical applications but have the disadvantage of lacking the wide array of computational tools for RNA structural prediction. Here, we present the first approach to predict from sequence the three-dimensional structures of single stranded (ss) DNA required for aptamer applications, focusing explicitly on ssDNA hairpins. The approach consists of a pipeline that integrates sequentially building ssDNA secondary structure from sequence, constructing equivalent 3D ssRNA models, transforming the 3D ssRNA models into ssDNA 3D structures, and refining the resulting ssDNA 3D structures. Through this pipeline, our approach faithfully predicts the representative structures available in the Nucleic Acid Database and Protein Data Bank databases. Our results, thus, open up a much-needed avenue for integrating DNA in the computational analysis and design of aptamer-based biosensors.

The free energy of looping DNA by proteins and protein complexes determines to what extent distal DNA sites can affect each other. We inferred its in vivo value through a combined computationalexperimental approach for different lengths of the loop and found that, in addition to the intrinsic periodicity of the DNA double helix, the free energy has an oscillatory component of about half the helical period. Moreover, the oscillations have such an amplitude that the effects of regulatory molecules become strongly dependent on their precise DNA positioning and yet easily tunable by their cooperative interactions. These unexpected results can confer to the physical properties of DNA a more prominent role at shaping the properties of gene regulation than previously thought.computational modeling ͉ DNA looping ͉ gene expression ͉ lac operon ͉ regulation T he cell is a densely packed dynamic structure made of thousands of different molecular species that orchestrate their interactions to form a functional unit. Such complexity poses a strong barrier for experimentally characterizing the cellular components: not only the properties of the components can change when studied in vitro outside the cell, but also the in vivo probing of the cell can perturb the process under study (1). Here we use computational modeling to obtain the properties of the in vivo unperturbed components at the molecular level from physiological measurements at the cellular level. Explicitly, we infer the in vivo free energies of DNA looping from enzyme production in the lac operon (2).The formation of DNA loops by the binding of proteins at distal DNA sites plays a fundamental role in many cellular processes, such as transcription, recombination, and replication (3-5). In gene regulation, proteins bound far away from the genes they regulate can be brought to the initiation of transcription region by looping the intervening DNA. The free energy cost of this process determines how easily DNA can loop and therefore the extent to which distal DNA sites can affect each other (5).In the lac operon, there is a repressor molecule that regulates transcription by binding specifically to DNA sites known as operators and preventing the RNA polymerase from transcribing the genes. DNA looping allows the repressor to bind to two operators simultaneously, leading to an increase in repression of transcription. This increase, characterized by the repression level, can be connected to the free energy of looping DNA by a recent model for transcription regulation by the lac repressor (6). The distance between operators determines the length of the DNA loop and affects the repression level through the changes in the free energy of looping. For interoperator distances from 57.5 to 98.5 bp, Muller et al. (7) systematically varied the distance between two operators in increments of 1 bp and measured the in vivo repression levels under conditions similar to wild type. These physiological measurements of enzyme production in Escherichia coli cell populations allowed us to ...

The formation and regulation of macromolecular complexes provides the backbone of most cellular processes, including gene regulation and signal transduction. The inherent complexity of assembling macromolecular structures makes current computational methods strongly limited for understanding how the physical interactions between cellular components give rise to systemic properties of cells. Here, we present a stochastic approach to study the dynamics of networks formed by macromolecular complexes in terms of the molecular interactions of their components. Exploiting key thermodynamic concepts, this approach makes it possible to both estimate reaction rates and incorporate the resulting assembly dynamics into the stochastic kinetics of cellular networks. As prototype systems, we consider the lac operon and phage k induction switches, which rely on the formation of DNA loops by proteins and on the integration of these protein-DNA complexes into intracellular networks. This cross-scale approach offers an effective starting point to move forward from network diagrams, such as those of protein-protein and DNA-protein interaction networks, to the actual dynamics of cellular processes. Molecular Systems Biology 16 May 2006; doi:10.1038/msb4100061Subject Categories: metabolic and regulatory networks; computational methods