The use of site-directed fluorophore labeling and donor–donor energy migration to investigate solution structure and dynamics in proteins

The use of molecular genetics for introducing fluorescent molecules enables the use of donor–donor energy migration to determine intramolecular distances in a variety of proteins. This approach can be applied to examine the overall molecular dimensions of proteins and to investigate structural changes upon interactions with specific target molecules. In this report, the donor–donor energy migration method is demonstrated by experiments with the latent form of plasminogen activator inhibitor type 1. Based on the known x-ray structure of plasminogen activator inhibitor type 1, three positions forming the corners of a triangle were chosen. Double Cys substitution mutants (V106C-H185C, H185C-M266C, and M266C-V106C) and corresponding single substitution mutants (V106C, H185C, and M266C) were created and labeled with a sulfhydryl specific derivative of BODIPY (=the D molecule). The side lengths of this triangle were obtained from analyses of the experimental data. The analyses account for the local anisotropic order and rotational motions of the D molecules, as well as for the influence of a partial DD-labeling. The distances, as determined from x-ray diffraction, between the Cα-atoms of the positions V106C–H185C, H185C–M266C, and M266C–V106C were 60.9, 30.8, and 55.1 Å, respectively. These are in good agreement with the distances of 54 ± 4, 38 ± 3, and 55 ± 3 Å, as determined between the BODIPY groups attached via linkers to the same residues. Although the positions of the D-molecules and the Cα-atoms physically cannot coincide, there is a reasonable agreement between the methods.

Experimental evidence for a behavior-mediated trophic cascade in a terrestrial food chain

Predators of herbivorous animals can affect plant populations by altering herbivore density, behavior, or both. To test whether the indirect effect of predators on plants arises from density or behavioral responses in a herbivore population, we experimentally examined the dynamics of terrestrial food chains comprised of old field plants, leaf-chewing grasshoppers, and spider predators in Northeast Connecticut. To separate the effects of predators on herbivore density from the effects on herbivore behavior, we created two classes of spiders: (i) risk spiders that had their feeding mouth parts glued to render them incapable of killing prey and (ii) predator spiders that remained unmanipulated. We found that the effect of predators on plants resulted from predator-induced changes in herbivore behavior (shifts in activity time and diet selection) rather than from predator-induced changes in grasshopper density. Neither predator nor risk spiders had a significant effect on grasshopper density relative to a control. This demonstrates that the behavioral response of prey to predators can have a strong impact on the dynamics of terrestrial food chains. The results make a compelling case to examine behavioral as well as density effects in theoretical and empirical research on food chain dynamics.

Molecular dynamics of MHC genesis unraveled by sequence analysis of the 1,796,938-bp HLA class I region

The intensely studied MHC has become the paradigm for understanding the architectural evolution of vertebrate multigene families. The 4-Mb human MHC (also known as the HLA complex) encodes genes critically involved in the immune response, graft rejection, and disease susceptibility. Here we report the continuous 1,796,938-bp genomic sequence of the HLA class I region, linking genes between MICB and HLA-F. A total of 127 genes or potentially coding sequences were recognized within the analyzed sequence, establishing a high gene density of one per every 14.1 kb. The identification of 758 microsatellite provides tools for high-resolution mapping of HLA class I-associated disease genes. Most importantly, we establish that the repeated duplication and subsequent diversification of a minimal building block, MIC-HCGIX-3.8–1-P5-HCGIV-HLA class I-HCGII, engendered the present-day MHC. That the currently nonessential HLA-F and MICE genes have acted as progenitors to today’s immune-competent HLA-ABC and MICA/B genes provides experimental evidence for evolution by “birth and death,” which has general relevance to our understanding of the evolutionary forces driving vertebrate multigene families.

Vibrational population relaxation of carbon monoxide in the heme pocket of photolyzed carbonmonoxy myoglobin: Comparison of time-resolved mid-IR absorbance experiments and molecular dynamics simulations

The vibrational energy relaxation of carbon monoxide in the heme pocket of sperm whale myoglobin was studied by using molecular dynamics simulation and normal mode analysis methods. Molecular dynamics trajectories of solvated myoglobin were run at 300 K for both the δ- and ɛ-tautomers of the distal His-64. Vibrational population relaxation times of 335 ± 115 ps for the δ-tautomer and 640 ± 185 ps for the ɛ-tautomer were estimated by using the Landau–Teller model. Normal mode analysis was used to identify those protein residues that act as the primary “doorway” modes in the vibrational relaxation of the oscillator. Although the CO relaxation rates in both the ɛ- and δ-tautomers are similar in magnitude, the simulations predict that the vibrational relaxation of the CO is faster in the δ-tautomer with the distal His playing an important role in the energy relaxation mechanism. Time-resolved mid-IR absorbance measurements were performed on photolyzed carbonmonoxy hemoglobin (Hb13CO). From these measurements, a T1 time of 600 ± 150 ps was determined. The simulation and experimental estimates are compared and discussed.

The photoisomerization of retinal in bacteriorhodopsin: Experimental evidence for a three-state model

The primary events in the all-trans to 13-cis photoisomerization of retinal in bacteriorhodopsin have been investigated with femtosecond time-resolved absorbance spectroscopy. Spectra measured over a broad range extending from 7000 to 22,400 cm−1 reveal features whose dynamics are inconsistent with a model proposed earlier to account for the highly efficient photoisomerization process. Emerging from this work is a new three-state model. Photoexcitation of retinal with visible light accesses a shallow well on the excited state potential energy surface. This well is bounded by a small barrier, arising from an avoided crossing that separates the Franck–Condon region from the nearby reactive region of the photoisomerization coordinate. At ambient temperatures, the reactive region is accessed with a time constant of ≈500 fs, whereupon the retinal rapidly twists and encounters a second avoided crossing region. The protein mediates the passage into the second avoided crossing region and thereby exerts control over the quantum yield for forming 13-cis retinal. The driving force for photoisomerization resides in the retinal, not in the surrounding protein. This view contrasts with an earlier model where photoexcitation was thought to access directly a reactive region of the excited-state potential and thereby drive the retinal to a twisted conformation within 100–200 fs.

Modeling the dynamics of human hair cycles by a follicular automaton

The hair follicle cycle successively goes through the anagen, catagen, telogen, and latency phases, which correspond, respectively, to hair growth, arrest, shedding, and absence before a new anagen phase is initiated. Experimental observations collected over a period of 14 years in a group of 10 male volunteers, alopecic and nonalopecic, allowed us to determine the characteristics of scalp hair follicle cycles. On the basis of these observations, we propose a follicular automaton model to simulate the dynamics of human hair cycles. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states anagen, telogen, and latency, and the subsequent return to anagen. The transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a variance. The follicular automaton model accounts both for the dynamical transitions observed in a single follicle and for the behavior of an ensemble of independently cycling follicles. Thus, the model successfully reproduces the evolution of the fractions of follicle populations in each of the three phases, which fluctuate around steady-state or slowly drifting values. We apply the follicular automaton model to the study of spatial patterns of follicular growth that result from a spatially heterogeneous distribution of parameters such as the mean duration of anagen phase. When considering that follicles die or miniaturize after going through a critical number of successive cycles, the model can reproduce the evolution to hair patterns similar to well known types of diffuse or androgenetic alopecia.

Ultrafast detection and control of molecular dynamics

Many elementary chemical and physical processes such as the breaking of a chemical bond or the vibrational motion of atoms within a molecule take place on a femtosecond (fs = 10−15 s) or picosecond (ps = 10−12 s) time scale. It is now possible to monitor these events as a function of time with temporal resolution well below 100 fs. This capability is based on the pump-probe technique where one optical pulse triggers a reaction and a second delayed optical pulse probes the changes that ensue. To illustrate this capability, the dynamics of ligand motion within a protein are presented. Moving beyond casual observation of a reaction to active control of its outcome requires additional experimental and theoretical effort. To illustrate the concept of control, the effect of optical pulse duration on the vibrational dynamics of a tri-atomic molecule are discussed. The experimental and theoretical resources currently available are poised to make the dream of reaction control a reality for certain molecular systems.

Memory from the dynamics of intrinsic membrane currents

Almost all theoretical and experimental studies of the mechanisms underlying learning and memory focus on synaptic efficacy and make the implicit assumption that changes in synaptic efficacy are both necessary and sufficient to account for learning and memory. However, network dynamics depends on the complex interaction between intrinsic membrane properties and synaptic strengths and time courses. Furthermore, neuronal activity itself modifies not only synaptic efficacy but also the intrinsic membrane properties of neurons. This paper presents examples demonstrating that neurons with complex temporal dynamics can provide short-term “memory” mechanisms that rely solely on intrinsic neuronal properties. Additionally, we discuss the potential role that activity may play in long-term modification of intrinsic neuronal properties. While not replacing synaptic plasticity as a powerful learning mechanism, these examples suggest that memory in networks results from an ongoing interplay between changes in synaptic efficacy and intrinsic membrane properties.

Intrinsic compressibility and volume compression in solvated proteins by molecular dynamics simulation at high pressure.

Constant pressure and temperature molecular dynamics techniques have been employed to investigate the changes in structure and volumes of two globular proteins, superoxide dismutase and lysozyme, under pressure. Compression (the relative changes in the proteins' volumes), computed with the Voronoi technique, is closely related with the so-called protein intrinsic compressibility, estimated by sound velocity measurements. In particular, compression computed with Voronoi volumes predicts, in agreement with experimental estimates, a negative bound water contribution to the apparent protein compression. While the use of van der Waals and molecular volumes underestimates the intrinsic compressibilities of proteins, Voronoi volumes produce results closer to experimental estimates. Remarkably, for two globular proteins of very different secondary structures, we compute identical (within statistical error) protein intrinsic compressions, as predicted by recent experimental studies. Changes in the protein interatomic distances under compression are also investigated. It is found that, on average, short distances compress less than longer ones. This nonuniform contraction underlines the peculiar nature of the structural changes due to pressure in contrast with temperature effects, which instead produce spatially uniform changes in proteins. The structural effects observed in the simulations at high pressure can explain protein compressibility measurements carried out by fluorimetric and hole burning techniques. Finally, the calculation of the proteins static structure factor shows significant shifts in the peaks at short wavenumber as pressure changes. These effects might provide an alternative way to obtain information concerning compressibilities of selected protein regions.

Glass transition in DNA from molecular dynamics simulations.

Molecular dynamics simulations of the oligonucleotide duplex d(CGCGCG)2 in aqueous solution are used to investigate the glass transition phenomenon. The simulations were performed at temperatures in the 20 K to 340 K range. The mean square atomic fluctuations showed that the behavior of the oligonucleotide duplex was harmonic at low temperatures. A glass transition temperature at 223 K to 234 K was inferred for the oligonucleotide duplex, which is in agreement with experimental observations. The largest number of hydrogen bounds between the polar atoms of the oligonucleotide duplex and the water molecules was obtained at the glass transition temperature. With increasing temperature we observed a decrease in the average lifetime of the hydrogen bonds to water molecules.

Antigenic variation and the within-host dynamics of parasites.

Many parasites exhibit antigenic variation within their hosts. We use mathematical models to investigate the dynamical interaction between an antigenically varying parasite and the host's immune system. The models incorporate antigenic variation in the parasite population and the generation of immune responses directed against (i) antigens specific to individual parasite variants and (ii) antigens common to all the parasite variants. Analysis of the models allows us to evaluate the relative importance of variant-specific and cross-reactive immune responses in controlling the parasite. Early in the course of infection within the host, when parasite diversity is below a defined threshold value (the value is determined by the biological properties of the parasite and of the host's immune response), the variant-specific immune responses are predominant. Later, when the parasite diversity is high, the cross-reactive immune response is largely responsible for controlling the parasitemia. It is argued that increasing antigenic diversity leads to a switch from variant-specific to cross-reactive immune responses. These simple models mimic various features of observed infections recorded in the experimental literature, including an initial peak in parasitemia, a long and variable duration of infection with fluctuating parasitemia that ends with either the clearance of the parasite or persistent infection.

Thermodynamic parameters for the helix-coil transition of oligopeptides: molecular dynamics simulation with the peptide growth method.

The helix-coil transition equilibrium of polypeptides in aqueous solution was studied by molecular dynamics simulation. The peptide growth simulation method was introduced to generate dynamic models of polypeptide chains in a statistical (random) coil or an alpha-helical conformation. The key element of this method is to build up a polypeptide chain during the course of a molecular transformation simulation, successively adding whole amino acid residues to the chain in a predefined conformation state (e.g., alpha-helical or statistical coil). Thus, oligopeptides of the same length and composition, but having different conformations, can be incrementally grown from a common precursor, and their relative conformational free energies can be calculated as the difference between the free energies for growing the individual peptides. This affords a straightforward calculation of the Zimm-Bragg sigma and s parameters for helix initiation and helix growth. The calculated sigma and s parameters for the polyalanine alpha-helix are in reasonable agreement with the experimental measurements. The peptide growth simulation method is an effective way to study quantitatively the thermodynamics of local protein folding.