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Experimental and theoretical studies of photodissociation and recombination of dihalide ions in gas-phase clusters and liquid solution are examined. A comprehensive physical picture of the interplay of charge flow and solvent dynamics on multiple, coupled electronic states is constructed by using a model inspired by the theory of electron-transfer reactions.

Product distributions from the photodissociation of I2-(OCS)n (n = 1-26) cluster ions at 790 and 395 nm are presented. Implications regarding the structure of these clusters are examined. There were near-infrared and near-ultraviolet photofragmentation of the I2-(OCS)n clusters. After the photoexcitation of I2- through the near-infrared absorption band, complete recombination of the chromophore was seen in clusters with n = 17.

Knopp et al. [J. Raman Spectrosc. 31, 51 (2000)] have recently used resonant femtosecond coherent anti-Stokes Raman spectroscopy (CARS) to prepare and probe highly excited vibrational wave packets on the ground electronic potential surface of molecular iodine. The experiment uses a sequence of three resonant femtosecond pulses with two independently variable time delays. The first two pulses act as a pump and dump sequence to create a predefined, highly excited wave packet on the ground electronic state, whose amplitude is optimized by selecting the proper pump–dump (Raman) frequency difference and varying the time delay. The third pulse promotes the pump–dump wave packet to an excited electronic state, resulting in subsequent coherent emission of light at the anti-Stokes frequency. This fully-resonant CARS signal, measured as a function of time delay between the second and third pulses, oscillates at a frequency characteristic of the pump–dump wave packet. Due to anharmonicity, this frequency is a sensitive measure of the amount of vibrational excitation. Knopp et al. observed that under certain conditions the signal exhibits pronounced beating between the pump–dump wave packet frequency and the frequency characteristic of the bottom of the ground state well. In this paper we show that these beats arise only when the final pump–dump–pump wave packet is above the excited state dissociation threshold of the molecule. We derive analytical expressions showing that under these conditions, where the polarization is short-lived, there may be strong interferences between the contributions from molecules originally in different vibrational states of the thermal ensemble. In contrast, the CARS polarization in the below threshold case is long-lived, and these interferences cancel. Numerical evaluation of the CARS signal through vibrational wave packet propagation confirms the predictions of the analytical theory and reproduc... [ABSTRACT FROM AUTHOR]

Examines the simulation of ultraviolet (UV) photodissociation of I[sub 2] embedded in clusters of 6 to 22 carbon dioxide molecules. Observation of an efficient electronic relaxation; Time scale and cluster size dependence of the spin-orbit quenching process; Derivation of a model from the theory of electron transfer.

Presents evidence that the peak in the pump-probe spectrum of iodide dissociated inside carbon dioxide clusters is due to transitions from the ground state to the spin-orbit excited states. Use of nonadiabatic molecular dynamics simulations; Occurrence of absorption at large internuclear distances.

Examines the photoelectron spectrum of iodine ion photodissociation in argon clusters. Use of the Hamiltonian model of electronic structure with a nonadiatic molecular dynamics simulation; Depiction of the simulation with several electronic potential surfaces; Importance for examining the excited states of charged species.

A method for calculating the vibrational eigenstates of van der Waals clusters is presented and applied to argon–benzene. The method employs the linear variational principle with a nonorthogonal basis set of Gaussian functions in both the stretching and bending coordinates. These localized functions allow greater flexibility than the standard spherical harmonics or Wigner D functions and should be more efficient when the motion is confined to specific regions of the potential energy surface. Calculations are performed on several potential surfaces including two recent fits to a previously published ab initio calculation. Accurate results with rapid convergence are obtained here for the states of zero total angular momentum (J=0). The results agree with calculations recently performed on the same potential surfaces by a different method [J. Chem. Phys. 98, 5327 (1993)] and suggest a reassignment of the experimentally observed bands. An extension of the basis set to nonzero J is presented in the Appendix. [ABSTRACT FROM AUTHOR]

The interaction potentials between the six lowest electronic states of I-2 and an arbitrary discrete charge distribution are calculated approximately using a one-electron model. The model potentials are much easier to calculate than ab initio potentials, with the cost of a single energy point scaling linearly with the number of solvent molecules, enabling relatively large systems to be studied. Application of the model to simulation of electronically excited I-2 in liquids and CO2 clusters is discussed. In a preliminary application, solvent effects are approximated by a uniform electric field. If electronically excited (2Πg,1/2) I-2 undergoes dissociation in the presence of a strong electric field, the negative charge localizes so as to minimize the total potential energy. However, in a weak field the negative charge localizes in the opposite direction, maximizing the potential energy. Based on a study of the field-dependent potential surfaces, a solvent-transfer mechanism is proposed for the electronic relaxation of 2Πg,1/2I-2, in contrast to the conventional view of relaxation via electron transfer. [ABSTRACT FROM AUTHOR]

Examines the resolution spectrum of the ground vibration state of the molecular complex ArHCN. Properties of the excited vibrational states of ArHCN; information on the resonances observed in the experiment; Description of the quadruple hyperfine structure associated with the transition.

The properties of a simple molecular model for the interior of an aqueous reverse micelle have been analyzed. Water creates distinct molecular layers at the interface that are bound to the surface ions and characterized by reduced mobility and hydrogen bonding.

Many receptor systems initiate cell signalling through ligand-induced receptor aggregation. For bivalent ligands binding to mono- or bivalent receptors, a plot of the equilibrium concentration of receptors in aggregates against the log of the free ligand concentration, the cross-linking curve, is symmetric and bell shaped. However, steady state cellular responses initiated through receptor cross-linking may have a different dependence on ligand concentration than the aggregated receptors that initiate and maintain these responses. The authors illustrate by considering the activation of the protein kinase Syk that rapidly occurs after high affinity receptors for IgE, FcεRI, are aggregated on the surface of mast cells and basophils. Using a mathematical model of Syk activation the authors investigate two effects, one straightforward and one less so, that result in Syk activation not qualitatively following the cross-linking curve. Model predictions show that if the mechanism by which Syk is fully activated involves the transphosphorylation of Syk by Syk, then Syk activation curves can be either bell shaped or double humped, depending on the cellular concentrations of Syk and FcεRI. The model also predicts that the Syk activation curve can be non-symmetric with respect to the ligand concentration. The cell can exhibit differential Syk activation at two different ligand concentrations that produce identical distributions of receptor aggregates that form and dissociate at the same rates. The authors discuss how, even though it is only receptor aggregates that trigger responses, differences in total ligand concentration can lead to subtle kinetic effects that yield qualitative differences in the levels of Syk activation. [ABSTRACT FROM AUTHOR]

The design of efficient combination therapies is a difficult key challenge in the treatment of complex diseases such as cancers. The large heterogeneity of cancers and the large number of available drugs renders exhaustive in vivo or even in vitro investigation of possible treatments impractical. In recent years, sophisticated mechanistic, ordinary differential equation-based pathways models that can predict treatment responses at a molecular level have been developed. However, surprisingly little effort has been put into leveraging these models to find novel therapies. In this paper we use for the first time, to our knowledge, a large-scale state-of-the-art pan-cancer signaling pathway model to identify candidates for novel combination therapies to treat individual cancer cell lines from various tissues (e.g., minimizing proliferation while keeping dosage low to avoid adverse side effects) and populations of heterogeneous cancer cell lines (e.g., minimizing the maximum or average proliferation across the cell lines while keeping dosage low). We also show how our method can be used to optimize the drug combinations used in sequential treatment plans-that is, optimized sequences of potentially different drug combinations-providing additional benefits. In order to solve the treatment optimization problems, we combine the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm with a significantly more scalable sampling scheme for truncated Gaussian distributions, based on a Hamiltonian Monte-Carlo method. These optimization techniques are independent of the signaling pathway model, and can thus be adapted to find treatment candidates for other complex diseases than cancers as well, as long as a suitable predictive model is available., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: TS is Founder, President, and CEO of Sandholm Enterprises, Ltd., Strategic Machine, Inc., Strategy Robot, Inc., and Optimized Markets, Inc.; these affiliations did not affect the conclusions of this paper.

Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through "wildcards" representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the "type" concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes a medium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications.

Inflammation is a complex, non-linear process central to many of the diseases that affect both developed and emerging nations. A systems-based understanding of inflammation, coupled to translational applications, is therefore necessary for efficient development of drugs and devices, for streamlining analyses at the level of populations, and for the implementation of personalized medicine. We have carried out an iterative and ongoing program of literature analysis, generation of prospective data, data analysis, and computational modeling in various experimental and clinical inflammatory disease settings. These simulations have been used to gain basic insights into the inflammatory response under baseline, gene-knockout, and drug-treated experimental animals for in silico studies associated with the clinical settings of sepsis, trauma, acute liver failure, and wound healing to create patient-specific simulations in polytrauma, traumatic brain injury, and vocal fold inflammation; and to gain insight into host-pathogen interactions in malaria, necrotizing enterocolitis, and sepsis. These simulations have converged with other systems biology approaches (e.g., functional genomics) to aid in the design of new drugs or devices geared towards modulating inflammation. Since they include both circulating and tissue-level inflammatory mediators, these simulations transcend typical cytokine networks by associating inflammatory processes with tissue/organ impacts via tissue damage/dysfunction. This framework has now allowed us to suggest how to modulate acute inflammation in a rational, individually optimized fashion. This plethora of computational and intertwined experimental/engineering approaches is the cornerstone of Translational Systems Biology approaches for inflammatory diseases.

The coupling of membrane-bound receptors to transcriptional regulators and other effector functions is mediated by multi-domain proteins that form complex assemblies. The modularity of protein interactions lends itself to a rule-based description, in which species and reactions are generated by rules that encode the necessary context for an interaction to occur, but also can produce a combinatorial explosion in the number of chemical species that make up the signalling network. The authors have shown previously that exact network reduction can be achieved using hierarchical control relationships between sites/domains on proteins to dissect multi-domain proteins into sets of non-interacting sites, allowing the replacement of each 'full' (progenitor) protein with a set of derived auxiliary (offspring) proteins. The description of a network in terms of auxiliary proteins that have fewer sites than progenitor proteins often greatly reduces network size. The authors describe here a method for automating domain-oriented model reduction and its implementation as a module in the BioNetGen modelling package. It takes as input a standard BioNetGen model and automatically performs the following steps: 1) detecting the hierarchical control relationships between sites; 2) building up the auxiliary proteins; 3) generating a raw reduced model and 4) cleaning up the raw model to provide the correct mass balance for each chemical species in the reduced network. The authors tested the performance of this module on models representing portions of growth factor receptor and immunoreceptor-mediated signalling networks and confirmed its ability to reduce the model size and simulation cost by at least one or two orders of magnitude. Limitations of the current algorithm include the inability to reduce models based on implicit site dependencies or heterodimerisation and loss of accuracy when dynamics are computed stochastically.

We present molecular dynamics simulation results for solvation dynamics in the water pool of anionic-surfactant reverse micelles (RMs) of varying water content, w(0). The model RMs are designed to represent water/aerosol-OT/oil systems, where aerosol-OT is the common name for sodium bis(2-ethylhexyl)sulfosuccinate. To determine the effects of chromophore-headgroup interactions on solvation dynamics, we compare the results for charge localization in model ionic diatomic chromophores that differ only in charge sign. Electronic excitation in both cases is modeled as charge localization on one of the solute sites. We find dramatic differences in the solvation responses for anionic and cationic chromophores. Solvation dynamics for the cationic chromophore are considerably slower and more strongly w(0)-dependent than those for the anionic chromophore. Further analysis indicates that the difference in the responses can be ascribed in part to the different initial locations of the two chromophores relative to the surfactant interface. In addition, slow motion of the cationic chromophore relative to the interface is the main contributor to the longer-time decay of the solvation response to charge localization in this case.

The activities and interactions of proteins that govern the cellular response to a signal generate a multitude of protein phosphorylation states and heterogeneous protein complexes. Here, using a computational model that accounts for 307 molecular species implied by specified interactions of four proteins involved in signalling by the immunoreceptor FcepsilonRI, we determine the relative importance of molecular species that can be generated during signalling, chemical transitions among these species, and reaction paths that lead to activation of the protein tyrosine kinase (PTK) Syk. By all of these measures and over two- and ten-fold ranges of model parameters--rate constants and initial concentrations--only a small portion of the biochemical network is active. The spectrum of active complexes, however, can be shifted dramatically, even by a change in the concentration of a single protein, which suggests that the network can produce qualitatively different responses under different cellular conditions and in response to different inputs. Reduced models that reproduce predictions of the full model for a particular set of parameters lose their predictive capacity when parameters are varied over two-fold ranges.