ABSTRACT
What were the physico-chemical forces that drove the origins of life? We discuss four major prebiotic 'discoveries': persistent sampling of chemical reaction space; sequence-encodable foldable catalysts; assembly of functional pathways; and encapsulation and heritability. We describe how a 'proteins-first' world gives plausible mechanisms. We note the importance of hydrophobic and polar compositions of matter in these advances.
Subject(s)
Biocatalysis , Origin of Life , Evolution, Molecular , PolymerizationABSTRACT
Complex feedback systems are ubiquitous in biology. Modeling such systems with mass action laws or master equations requires information rarely measured directly. Thus rates and reaction topologies are often treated as adjustable parameters. Here we present a general stochastic modeling method for small chemical and biochemical systems with emphasis on feedback systems. The method, Maximum Caliber (MaxCal), is more parsimonious than others in constructing dynamical models requiring fewer model assumptions and parameters to capture the effects of feedback. MaxCal is the dynamical analogue of Maximum Entropy. It uses average rate quantities and correlations obtained from short experimental trajectories to construct dynamical models. We illustrate the method on the bistable genetic toggle switch. To test our method, we generate synthetic data from an underlying stochastic model. MaxCal reliably infers the statistics of the stochastic bistability and other full dynamical distributions of the simulated data, without having to invoke complex reaction schemes. The method should be broadly applicable to other systems.
Subject(s)
Models, Chemical , Models, Molecular , Algorithms , EntropyABSTRACT
We develop theory for the dynamics and fluctuations in some cyclic and linear biochemical reactions. We use the approach of maximum caliber, which computes the ensemble of paths taken by the system, given a few experimental observables. This approach may be useful for interpreting single-molecule or few-particle experiments on molecular motors, enzyme reactions, ion-channels, and phosphorylation-driven biological clocks. We consider cycles where all biochemical states are observable. Our method shows how: (1) the noise in cycles increases with cycle size and decreases with the driving force that spins the cycle and (2) provides a recipe for estimating small-number features, such as probability of backward spin in small cycles, from experimental data. The back-spin probability diminishes exponentially with the deviation from equilibrium. We believe this method may also be useful for other few-particle nonequilibrium biochemical reaction systems.
Subject(s)
Models, Biological , Diffusion , Entropy , Linear Models , Stochastic ProcessesABSTRACT
Ionenes are alkyl polymer chains in which different numbers of methylene groups separate quaternary ammonium groups. They are ideal molecules for studying the balance between hydrophobic and charge effects in water. Implicit-solvent models predict osmotic coefficients that are too high (too low water vapor pressures), compared to experiments. We present a molecular dynamics simulation, in explicit SPC/E water, of a solution of aliphatic 6,6 ionene oligocations with sodium co-ions and fluorine, chlorine, bromine, or iodine counterions. In the 6,6 ionene solution, the latter polyion has more hydrophobic groups than its 3,3 counterpart, the waters are displaced more from the oligoion surface. Also, we find that the large ions, such as iodine, act like hydrophobic groups insofar as they bind to ionene's methylene groups. The water-mediated attraction between fluorine ions is enhanced in presence of weakly charged 6,6 ionene molecules. This effect may additionally reduce the osmotic pressure in such systems. Our results can explain some experimental trends in ionene solutions and weakly charged polyelectrolytes in general.
Subject(s)
Ions/chemistry , Quaternary Ammonium Compounds/chemistry , Solutions/chemistry , Hydrophobic and Hydrophilic Interactions , Molecular Dynamics Simulation , Polymers/chemistry , Thermodynamics , Water/chemistryABSTRACT
Ionenes are alkyl polymer chains in which hydrophobic groups are separated by ionic charges. They are useful for studying the properties of water as a solvent because they demonstrate a sufficiently complex combination of hydrophobicity, charge interactions, and specific-ion effects that some properties cannot be predicted by implicit-solvation theories. On the other hand, they are simple enough that their molecular structures can be varied and controlled in systematic experiments. In particular, implicit-solvent models predict that all such solutes will have negative enthalpies of dilution, whereas experiments show that enthalpies of dilution are positive for the chaotropic counterions. Here, we study ionenes that are short chains (six monomer units) in solutions of different counterions, with sodium as the coion by molecular dynamics simulations in explicit water. We explore the pair distributions of various atoms within the system at three different temperatures: T=278, 298, and 318 K. We find (i) that the molecular dynamics simulations are consistent with the experimental trends for the osmotic coefficients and enthalpies of dilution, (ii) that the fluorine-nitrogen and fluorine-carbon correlations decrease with decreasing temperature, (iii) while the opposite behavior is found for iodine ions, and (iv) that in the counterion-Na(+) pair distributions, too, fluorine ions behave oppositely to iodine ions upon temperature increase.
Subject(s)
Bromides/chemistry , Sodium Chloride/chemistry , Sodium Compounds/chemistry , Sodium Fluoride/chemistry , Water/chemistry , Ions/chemistry , Models, Molecular , SolutionsABSTRACT
We present a theory for protein folding stability and cooperativity for helix bundle proteins. We treat the individual helices with a Schellman-Zimm-Bragg-like approach, using nucleation and propagation quantities, and we treat the hydrophobic and van der Waals contacts between the helices as a binding equilibrium. Predictions are in good agreement with experiments on both thermal and urea-induced transitions of (1) molecules that can undergo single helix-to-coil transitions for various chain lengths and (2) three-helix-bundle proteins A and alpha3C. The present model addresses a problem raised by Kaya and Chan that proteins fold more cooperatively than previous models predict. The present model correctly predicts the experimentally observed two-state cooperativities, DeltaH(van't Hoff)/DeltaH(cal) approximately 1, for helix-bundle proteins. The predicted folding cooperativity is greater than that of helix formation alone, or collapse alone, because of the nonlinear coupling between the tertiary interactions and the helical interactions.
Subject(s)
Protein Folding , Proteins/chemistry , Staphylococcal Protein A/chemistry , Models, Chemical , Models, Molecular , Protein Structure, Quaternary , Protein Structure, Secondary , ThermodynamicsABSTRACT
We recently developed an angle-dependent Wertheim integral equation theory (IET) of the Mercedes-Benz (MB) model of pure water [Silverstein et al., J. Am. Chem. Soc. 120, 3166 (1998)]. Our approach treats explicitly the coupled orientational constraints within water molecules. The analytical theory offers the advantage of being less computationally expensive than Monte Carlo simulations by two orders of magnitude. Here we apply the angle-dependent IET to studying the hydrophobic effect, the transfer of a nonpolar solute into MB water. We find that the theory reproduces the Monte Carlo results qualitatively for cold water and quantitatively for hot water.
Subject(s)
Chemistry, Physical/methods , Water/chemistry , Algorithms , Argon/chemistry , Hydrogen Bonding , Hydrophobic and Hydrophilic Interactions , Models, Molecular , Models, Statistical , Monte Carlo Method , Solutions , SolventsABSTRACT
We previously applied Wertheim's thermodynamic perturbation theory for associative fluids to the simple Mercedes-Benz model of water. We found that the theory reproduced well the physical properties of hot water, but was less successful in capturing the more structured hydrogen bonding that occurs in cold water. Here, we propose an improved version of the thermodynamic perturbation theory in which the effective density of the reference system is calculated self-consistently. The new theory is a significant improvement, giving good agreement with Monte Carlo simulations of the model, and predicting key anomalies of cold water, such as minima in the molar volume and large heat capacity, in addition to giving good agreement with the isothermal compressibility and thermal expansion coefficient.
Subject(s)
Water/chemistry , Chemistry, Physical/methods , Computer Simulation , Hydrogen Bonding , Models, Statistical , Molecular Conformation , Monte Carlo Method , Solutions , Temperature , ThermodynamicsABSTRACT
We study water that is confined within small geometric spaces. We use the Mercedes-Benz (MB) model of water, in NVT and muVT Monte Carlo computer simulations. For MB water molecules between two planes separated by a distance d, we explore the structures, hydrogen bond networks, and thermodynamics as a function of d, temperature T, and water chemical potential mu. We find that squeezing the planes close enough together leads to a vaporization of waters out of the cavity. This vaporization transition has a corresponding peak in the heat capacity of the water. We also find that, in small pores, hydrogen bonding is not isotropic but, rather, it preferentially forms chains along the axis of the cavity. This may be relevant for fast proton transport in pores. Our simulations show oscillations in the forces between the inert plates, due to water structure, even for plate separations of 5-10 water diameters, consistent with experiments by Israelachvili et al. [Nature 1983, 306, 249]. Finally, we find that confinement affects water's heat capacity, consistent with recent experiments of Tombari et al. on Vycor nanopores [J. Chem. Phys. 2005, 122, 104712].
Subject(s)
Models, Chemical , Water/chemistry , Computer Simulation , Fourier Analysis , Hydrogen Bonding , Monte Carlo Method , Temperature , ThermodynamicsABSTRACT
We show that CombiMatrix's VLSI arrays of individually addressable electrodes, using conventional CMOS integrated circuitry, can be used in detecting various analytes via immunoassay protocols. These microarrays provide over 1000 electrodes per square centimeter. The chips are coated with a porous material on which specific affinity tags are synthesized proximate to selected electrode sites. CombiMatrix microarrays are used to develop spatially multiplexed assay formats for biological entities over a wide range of sizes, from small molecules to cells. Antibodies are tagged with coded affinity labels and then allowed to self-assemble on the appropriate electrode assay sites. Each analyte-specific antibody is chaperoned to individual, predetermined locations by the self-assembly process. The resulting chip can perform numerous different analyte-specific immunoassays, simultaneously. We present new detection technologies based upon the use of the active individually addressable microelectrodes on the chip: redox enzyme amplified electrochemical detection. The results for human alpha1 acid glycoprotein, ricin, M13 phage, Bacillus globigii spores, and fluorescein indicate that this method is one of the most sensitive available, with limits of detection in the attomole range. The detection range is 4-5 logs of analyte concentration, with an assay volume of 50 microl or less. The system provides for a host of multiplexed immunoassays because of the large number of electrodes available. We show how the assays can be optimized for maximum performance on the CombiMatrix microarray platform.
Subject(s)
Biosensing Techniques/instrumentation , Electrochemistry/instrumentation , Immunoassay/instrumentation , Microelectrodes , Biosensing Techniques/methods , Electrochemistry/methods , Equipment Design , Equipment Failure Analysis , Immunoassay/methods , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
We present theory showing that confining a protein to a small inert space (a "cage") should stabilize the protein against reversible unfolding. Examples of such spaces might include the pores within chromatography columns, the Anfinsen cage in chaperonins, the interiors of ribosomes, or regions of steric occlusion inside cells. Confinement eliminates some expanded configurations of the unfolded chain, shifting the equilibrium from the unfolded state toward the native state. The partition coefficient for a protein in a confined space is predicted to decrease significantly when the solvent is changed from native to denaturing conditions. Small cages are predicted to increase the stability of the native state by as much as 15 kcal/mol. Confinement may also increase the rates of protein or RNA folding.
Subject(s)
Protein Conformation , Proteins/chemistry , Chaperonins/chemistry , Drug Stability , Models, Molecular , Models, Theoretical , Peptides/chemistry , Protein Folding , RNA/chemistry , Ribosomes/ultrastructure , ThermodynamicsABSTRACT
What is the mechanism of two-state protein folding? The rate-limiting step is typically explored through a Phi-value, which is the mutation-induced change in the transition state free energy divided by the change in the equilibrium free energy of folding. Phi-values ranging from 0 to 1 have been interpreted as meaning the transition state is denatured-like (0), native-like (1) or in-between. But there is no classical interpretation for the experimental Phi-values that are negative or >1. Using a rigorous method to identity transition states via an exact lattice model, we find that nonclassical Phi-values can arise from parallel microscopic flow processes, such as those in funnel-shaped energy landscapes. Phi < 0 results when a mutation destabilizes a slow flow channel, causing a backflow into a faster flow channel. Phi > 1 implies the reverse: a backflow from a fast channel into a slow one. Using a 'landscape mapping' method, we find that Phi correlates with the acceleration/deceleration of folding induced by mutations, rather than with the degree of nativeness of the transition state.
Subject(s)
Models, Molecular , Protein Folding , Proteins/chemistry , Proteins/metabolism , Kinetics , Mutation , Protein Conformation , Proteins/genetics , ThermodynamicsABSTRACT
The average packing density inside proteins is as high as in crystalline solids. Does this mean proteins are well-packed? We go beyond average densities, and look at the full distribution functions of free volumes inside proteins. Using a new and rigorous Delaunay triangulation method for parsing space into empty and filled regions, we introduce formal definitions of interior and surface packing densities. Although proteins look like organic crystals by the criterion of average density, they look more like liquids and glasses by the criterion of their free volume distributions. The distributions are broad, and the scalings of volume-to-surface, volume-to-cluster-radius, and numbers of void versus volume show that the interiors of proteins are more like randomly packed spheres near their percolation threshold than like jigsaw puzzles. We find that larger proteins are packed more loosely than smaller proteins. And we find that the enthalpies of folding (per amino acid) are independent of the packing density of a protein, indicating that van der Waals interactions are not a dominant component of the folding forces.
Subject(s)
Proteins/chemistry , Computer Simulation , Crystallography , Models, Molecular , Protein Conformation , Protein Denaturation , Protein Folding , Proteins/metabolism , Thermodynamics , Water/metabolismABSTRACT
We describe the successful application of a modified gene-trap approach, the secretory trap, to systematically analyze the functions in vivo of large numbers of genes encoding secreted and membrane proteins. Secretory-trap insertions in embryonic stem cells can be transmitted to the germ line of mice with high efficiency and effectively mutate the target gene. Of 60 insertions analyzed in mice, one-third cause recessive lethal phenotypes affecting various stages of embryonic and postnatal development. Thus, secretory-trap mutagenesis can be used for a genome-wide functional analysis of cell signaling pathways that are critical for normal mammalian development and physiology.
Subject(s)
Membrane Proteins/genetics , Mice/genetics , Molecular Biology/methods , Proteins/metabolism , Animals , Blastocyst/cytology , Breeding , Genes, Lethal , Genetic Vectors , Genotype , Mutagenesis, Insertional , Phenotype , Polymerase Chain Reaction , Selection, Genetic , Sequence Tagged Sites , Stem Cells/cytologyABSTRACT
A challenge in computational protein folding is to assemble secondary structure elements-helices and strands-into well-packed tertiary structures. Particularly difficult is the formation of beta-sheets from strands, because they involve large conformational searches at the same time as precise packing and hydrogen bonding. Here we describe a method, called Geocore-2, that (1) grows chains one monomer or secondary structure at a time, then (2) disconnects the loops and performs a fast rigid-body docking step to achieve canonical packings, then (3) in the case of intrasheet strand packing, adjusts the side-chain rotamers; and finally (4) reattaches loops. Computational efficiency is enhanced by using a branch-and-bound search in which pruning rules aim to achieve a hydrophobic core and satisfactory hydrogen bonding patterns. We show that the pruning rules reduce computational time by 10(3)- to 10(5)-fold, and that this strategy is computationally practical at least for molecules up to about 100 amino acids long.
Subject(s)
Protein Conformation , Protein Structure, Secondary , Protein Structure, Tertiary , Proteins/chemistry , Algorithms , Computer Graphics , Models, Molecular , Models, Theoretical , Protein Folding , SoftwareABSTRACT
Models in computational biology, such as those used in binding, docking, and folding, are often empirical and have adjustable parameters. Because few of these models are yet fully predictive, the problem may be nonoptimal choices of parameters. We describe an algorithm called ENPOP (energy function parameter optimization) that improves-and sometimes optimizes-the parameters for any given model and for any given search strategy that identifies the stable state of that model. ENPOP iteratively adjusts the parameters simultaneously to move the model global minimum energy conformation for each of m different molecules as close as possible to the true native conformations, based on some appropriate measure of structural error. A proof of principle is given for two very different test problems. The first involves three different two-dimensional model protein molecules having 12 to 37 monomers and four parameters in common. The parameters converge to the values used to design the model native structures. The second problem involves nine bumpy landscapes, each having between 4 and 12 degrees of freedom. For the three adjustable parameters, the globally optimal values are known in advance. ENPOP converges quickly to the correct parameter set.
Subject(s)
Algorithms , Computational Biology/methods , Models, Biological , Models, Theoretical , Energy Metabolism , Protein Folding , Proteins/chemistryABSTRACT
We performed a retrospective analysis of 384 consecutive stereotactic breast biopsies (SBBs) from March 1995 through January 1999 and compared it with our historical breast biopsy experience. Two hundred forty-four patients underwent biopsies for microcalcifications and 135 patients for abnormal mammographic densities. Pathology diagnoses included 302 patients with benign disease, 35 patients with atypical ductal hyperplasia, 4 patients with lobular carcinoma in situ, 29 patients with ductal carcinoma in situ, and 9 patients with invasive breast cancer. These diagnostic rates were compared with our prior needle-localized pathology findings. For the study period, the number of mammograms, open biopsies, and needle-localized biopsies remained stable. The number of SBBs, however, increased progressively in every year. Medicare reimbursement for SBB was $921.19, and for breast biopsy after needle localization, $1566.22. Our study strongly suggests that the availability of SBB has significantly lowered the threshold for recommending biopsy of abnormal mammograms. The increased utilization of SBB almost certainly indicates an increase in the overall cost of breast care. This cost must be balanced against substantial potential benefits of this minimally invasive technique: possible earlier diagnosis of atypical and precancerous lesions, patient reassurance in cases of uncertain mammographic interpretation, and a reduced need for follow-up of indeterminate mammograms.
Subject(s)
Breast Diseases/pathology , Breast Neoplasms/pathology , Adult , Aged , Aged, 80 and over , Biopsy/statistics & numerical data , Breast Diseases/diagnostic imaging , Breast Neoplasms/diagnostic imaging , Hospitals, Community , Hospitals, Teaching , Humans , Mammography , Middle Aged , Retrospective StudiesABSTRACT
Two studies examined violent video game effects on aggression-related variables. Study 1 found that real-life violent video game play was positively related to aggressive behavior and delinquency. The relation was stronger for individuals who are characteristically aggressive and for men. Academic achievement was negatively related to overall amount of time spent playing video games. In Study 2, laboratory exposure to a graphically violent video game increased aggressive thoughts and behavior. In both studies, men had a more hostile view of the world than did women. The results from both studies are consistent with the General Affective Aggression Model, which predicts that exposure to violent video games will increase aggressive behavior in both the short term (e.g., laboratory aggression) and the long term (e.g., delinquency).
Subject(s)
Aggression , Personality , Social Behavior Disorders/etiology , Video Games/adverse effects , Violence/psychology , Adult , Female , Humans , Male , Models, Psychological , Sex Factors , Social Behavior Disorders/psychologyABSTRACT
Using a statistical mechanical treatment, we study RNA folding energy landscapes. We first validate the theory by showing that, for the RNA molecules we tested having only secondary structures, this treatment (i) predicts about the same native structures as the Zuker method, and (ii) qualitatively predicts the melting curve peaks and shoulders seen in experiments. We then predict thermodynamic folding intermediates. For one hairpin sequence, unfolding is a simple unzipping process. But for another sequence, unfolding is more complex. It involves multiple stable intermediates and a rezipping into a completely non-native conformation before unfolding. The principle that emerges, for which there is growing experimental support, is that although protein folding tends to involve highly cooperative two-state thermodynamic transitions, without detectable intermediates, the folding of RNA secondary structures may involve rugged landscapes, often with more complex intermediate states.