Numerical analysis of the relation between interactions and structure in a molecular fluid

Coarse graining is a popular technique used in physics to speed up the computer simulation of molecular fluids. An essential part of this technique is a method that solves the inverse problem of determining the interaction potential or its parameters from the given structural data. Due to discrepancies between model and reality, the potential is not unique, such that stability of such method and its convergence to a meaningful solution are issues.rnrnIn this work, we investigate empirically whether coarse graining can be improved by applying the theory of inverse problems from applied mathematics. In particular, we use the singular value analysis to reveal the weak interaction parameters, that have a negligible influence on the structure of the fluid and which cause non-uniqueness of the solution. Further, we apply a regularizing Levenberg-Marquardt method, which is stable against the mentioned discrepancies. Then, we compare it to the existing physical methods - the Iterative Boltzmann Inversion and the Inverse Monte Carlo method, which are fast and well adapted to the problem, but sometimes have convergence problems.rnrnFrom analysis of the Iterative Boltzmann Inversion, we elaborate a meaningful approximation of the structure and use it to derive a modification of the Levenberg-Marquardt method. We engage the latter for reconstruction of the interaction parameters from experimental data for liquid argon and nitrogen. We show that the modified method is stable, convergent and fast. Further, the singular value analysis of the structure and its approximation allows to determine the crucial interaction parameters, that is, to simplify the modeling of interactions. Therefore, our results build a rigorous bridge between the inverse problem from physics and the powerful solution tools from mathematics. rn

Pi release from myosin: a simulation analysis of possible pathways

The release of phosphate (Pi) is an important element in actomyosin function and has been shown to be accelerated by the binding of myosin to actin. To provide information about the structural elements important for Pi release, possible escape pathways from various isolated myosin II structures have been determined by molecular dynamics simulations designed for studying such slow processes. The residues forming the pathways were identified and their role was evaluated by mutant simulations. Pi release is slow in the pre-powerstroke structure, an important element in preventing the powerstroke prior to actin binding, and is much more rapid for Pi modeled into the post-rigor and rigor-like structures. The previously proposed backdoor route is dominant in the pre-powerstroke and post-rigor states, whereas a different path is most important in the rigor-like state. This finding suggests a mechanism for the actin-activated acceleration of Pi release.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Regulatory mechanism of the light-activable allosteric switch LOV-TAP for the control of DNA binding: a computer simulation study

The spatio-temporal control of gene expression is fundamental to elucidate cell proliferation and deregulation phenomena in living systems. Novel approaches based on light-sensitive multiprotein complexes have recently been devised, showing promising perspectives for the noninvasive and reversible modulation of the DNA-transcriptional activity in vivo. This has lately been demonstrated in a striking way through the generation of the artificial protein construct light-oxygen-voltage (LOV)-tryptophan-activated protein (TAP), in which the LOV-2-Jα photoswitch of phototropin1 from Avena sativa (AsLOV2-Jα) has been ligated to the tryptophan-repressor (TrpR) protein from Escherichia coli. Although tremendous progress has been achieved on the generation of such protein constructs, a detailed understanding of their functioning as opto-genetical tools is still in its infancy. Here, we elucidate the early stages of the light-induced regulatory mechanism of LOV-TAP at the molecular level, using the noninvasive molecular dynamics simulation technique. More specifically, we find that Cys450-FMN-adduct formation in the AsLOV2-Jα-binding pocket after photoexcitation induces the cleavage of the peripheral Jα-helix from the LOV core, causing a change of its polarity and electrostatic attraction of the photoswitch onto the DNA surface. This goes along with the flexibilization through unfolding of a hairpin-like helix-loop-helix region interlinking the AsLOV2-Jα- and TrpR-domains, ultimately enabling the condensation of LOV-TAP onto the DNA surface. By contrast, in the dark state the AsLOV2-Jα photoswitch remains inactive and exerts a repulsive electrostatic force on the DNA surface. This leads to a distortion of the hairpin region, which finally relieves its tension by causing the disruption of LOV-TAP from the DNA.

A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.

Modeling of human P450 oxidoreductase structure by in silico mutagenesis and MD simulation

P450 oxidoreductase (POR) is the obligate electron donor for microsomal cytochrome P450s and mutations in POR cause several metabolic disorders. We have modeled the structure of human P450 oxidoreductase by in silico amino acid replacements in the rat POR crystal structure. The rat POR has 94% homology with human POR and 38 amino acids were replaced to make its sequence identical to human POR. Several rounds of molecular dynamic simulations refined the model and removed structural clashes from side chain alterations of replaced amino acids. This approach has the advantage of keeping the cofactor contacts and structural features of the core enzyme intact which could not be achieved by homology based approaches. The final model from our approach was of high quality and compared well with experimentally determined structures of other PORs. This model will be used for analyzing the structural implications of mutations and polymorphisms in human POR.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Bifurcation and singularity analysis of a molecular network for the induction of long-term memory.

Withdrawal reflexes of the mollusk Aplysia exhibit sensitization, a simple form of long-term memory (LTM). Sensitization is due, in part, to long-term facilitation (LTF) of sensorimotor neuron synapses. LTF is induced by the modulatory actions of serotonin (5-HT). Pettigrew et al. developed a computational model of the nonlinear intracellular signaling and gene network that underlies the induction of 5-HT-induced LTF. The model simulated empirical observations that repeated applications of 5-HT induce persistent activation of protein kinase A (PKA) and that this persistent activation requires a suprathreshold exposure of 5-HT. This study extends the analysis of the Pettigrew model by applying bifurcation analysis, singularity theory, and numerical simulation. Using singularity theory, classification diagrams of parameter space were constructed, identifying regions with qualitatively different steady-state behaviors. The graphical representation of these regions illustrates the robustness of these regions to changes in model parameters. Because persistent protein kinase A (PKA) activity correlates with Aplysia LTM, the analysis focuses on a positive feedback loop in the model that tends to maintain PKA activity. In this loop, PKA phosphorylates a transcription factor (TF-1), thereby increasing the expression of an ubiquitin hydrolase (Ap-Uch). Ap-Uch then acts to increase PKA activity, closing the loop. This positive feedback loop manifests multiple, coexisting steady states, or multiplicity, which provides a mechanism for a bistable switch in PKA activity. After the removal of 5-HT, the PKA activity either returns to its basal level (reversible switch) or remains at a high level (irreversible switch). Such an irreversible switch might be a mechanism that contributes to the persistence of LTM. The classification diagrams also identify parameters and processes that might be manipulated, perhaps pharmacologically, to enhance the induction of memory. Rational drug design, to affect complex processes such as memory formation, can benefit from this type of analysis.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects

Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

Impact of Taylor-Aris diffusivity on analyte and system zone dispersion in CZE assessed by computer simulation and experimental validation.

Application of pressure-driven laminar flow has an impact on zone and boundary dispersion in open tubular CE. The GENTRANS dynamic simulator for electrophoresis was extended with Taylor-Aris diffusivity which accounts for dispersion due to the parabolic flow profile associated with pressure-driven flow. Effective diffusivity of analyte and system zones as functions of the capillary diameter and the amount of flow in comparison to molecular diffusion alone were studied for configurations with concomitant action of imposed hydrodynamic flow and electroosmosis. For selected examples under realistic experimental conditions, simulation data are compared with those monitored experimentally using modular CE setups featuring both capacitively coupled contactless conductivity and UV absorbance detection along a 50 μm id fused-silica capillary of 90 cm total length. The data presented indicate that inclusion of flow profile based Taylor-Aris diffusivity provides realistic simulation data for analyte and system peaks, particularly those monitored in CE with conductivity detection.

Cerebellar mechanisms for motor learning: Testing predictions from a large-scale computer simulation

The cerebellum is the major brain structure that contributes to our ability to improve movements through learning and experience. We have combined computer simulations with behavioral and lesion studies to investigate how modification of synaptic strength at two different sites within the cerebellum contributes to a simple form of motor learning—Pavlovian conditioning of the eyelid response. These studies are based on the wealth of knowledge about the intrinsic circuitry and physiology of the cerebellum and the straightforward manner in which this circuitry is engaged during eyelid conditioning. Thus, our simulations are constrained by the well-characterized synaptic organization of the cerebellum and further, the activity of cerebellar inputs during simulated eyelid conditioning is based on existing recording data. These simulations have allowed us to make two important predictions regarding the mechanisms underlying cerebellar function, which we have tested and confirmed with behavioral studies. The first prediction describes the mechanisms by which one of the sites of synaptic modification, the granule to Purkinje cell synapses (gr → Pkj) of the cerebellar cortex, could generate two time-dependent properties of eyelid conditioning—response timing and the ISI function. An empirical test of this prediction using small, electrolytic lesions of the cerebellar cortex revealed the pattern of results predicted by the simulations. The second prediction made by the simulations is that modification of synaptic strength at the other site of plasticity, the mossy fiber to deep nuclei synapses (mf → nuc), is under the control of Purkinje cell activity. The analysis predicts that this property should confer mf → nuc synapses with resistance to extinction. Thus, while extinction processes erase plasticity at the first site, residual plasticity at mf → nuc synapses remains. The residual plasticity at the mf → nuc site confers the cerebellum with the capability for rapid relearning long after the learned behavior has been extinguished. We confirmed this prediction using a lesion technique that reversibly disconnected the cerebellar cortex at various stages during extinction and reacquisition of eyelid responses. The results of these studies represent significant progress toward a complete understanding of how the cerebellum contributes to motor learning. ^

Molecular Mechanics of Water Monomer

Simulation of the classical molecular dynamics of a water molecule can be useful in explaining normal modes of motion, Fourier Transforms, and fundamental frequencies of vibration, as illustrated herein.

Simulación atomística de metales líquidos y aleaciones para reactores de fusión nuclear = Atomistic simulation of liquid metals and alloys for nuclear fusion reactors

La presente tesis comprende un estudio de metales líquidos, Li, Pb y eutéctico Li17Pb en el ámbito de la tecnología de fusión nuclear. Uno de los problemas fundamentales en futuros reactores de fusión es la producción y extracción de tritio en la denominada envoltura regeneradora (blanket en inglés). Dicho blanket tendrá dos propósitos, la extracción del calor generado por las reacciones de fusión para su posterior conversión en energía eléctrica así como la producción de tritio para realimentar el proceso. Dicha producción se realizará mediante el “splitting” del Li con los neutrones provenientes de la fusión. Esta reacción produce tritio y helio por lo que la interacción del T y el He con el metal líquido, con los materiales estructurales así como con el He es un problema fundamental aun no bien entendido y de gran importancia para futuros diseños. Los capítulos 1 2 y 3 presentan una introducción a dichos problemas. El capítulo 1 introduce al lector en la tecnología de fusión nuclear. El segundo capítulo explica en mayor detalle el uso de metales líquidos en reactores de fusión, no solo en blankets sino también como primera pared, divertor etc, lo que se denomina en general “plasma facing materials”. Por último se ofrece una breve introducción a las técnicas de dinámica molecular clásica (CMD) y un breve resumen de los potenciales más usados. El estudio se ha llevado a cabo utilizando simulación atomística mediante potenciales semi-empíricos del tipo átomo embebido (EAM). La Tesis consta de 4 partes bien definidas. En primer lugar se verificó la idoneidad de los potenciales tipo EAM para simular las propiedades de los metales Li y Pb en fase líquida. Dicho estudio se detalla en el Capítulo 4 y en su extensión, el Apéndice 1, en el que se estudia los límites de validez de esta aproximación. Los resultados de dicho estudio han sido publicados y presentados en diversos congresos internacionales. Un resumen de la metodología seguida fue publicado como capítulo de libro en Technofusión 2011. Los resultados se presentaron en diversos congresos internacionales, entre ellos ICENES 2011, (Artículo en ICENES Proceedings) ICOPS-SOFE 2011, en una presentación oral etc. El trabajo ha sido aceptado recientemente en Journal of Nuclear Materiales (Fraile et al 2012). La segunda parte y más importante comprende el desarrollo de un potencial para el estudio de la mezcla de ambos metales. Éste es el trabajo más novedoso e importante dado que no existía en la literatura un potencial semejante. Se estudiaron dos aproximaciones distintas al problema, un potencial tipo EAM/cd y un potencial EAM/alloy. Ambos potenciales dan resultados satisfactorios para la simulación del eutéctico (y concentraciones de Li menores que el 17%). Sin embargo el sistema LiPb en todas las concentraciones es un sistema que se aparta enormemente de una solución ideal y dicho potencial no daba buenos resultados para mezclas PbLi con concentraciones de Li grandes. Este problema fue solventado mediante el desarrollo de un segundo potencial, esta vez tipo EAM/alloy (segunda parte del Capítulo 5). Dicho trabajo será enviado a Physical Review Letters o a Phys. Rev. B, y una extensión junto con un estudio detallado de las propiedades del eutéctico de acuerdo con nuestras simulaciones se enviará a continuación a Phys. Rev. B. En tercer lugar se estudió el problema de la difusividad del H en metales líquidos aprovechando distintos potenciales existentes en la literatura. El problema del H en metales líquidos es importante en metalurgia. En dicho capítulo se estudió la difusividad del H en Pd, Ni y Al con potenciales tipo EAM, y también con un potencial más sofisticado que tiene en cuenta la dependencia angular de las interacciones (ADP por sus siglas en inglés). De este modo disponemos de un estudio detallado del problema con diferentes modelos y diferentes metales. La conclusión apunta a que si se compara con los resultados experimentales (muy escasos) los resultados obtenidos mediante CMD dan valores bajos de la difusividad del H. Las razones de dicho desacuerdo entre simulación y experimentos se detallan en el Capítulo 6. Este trabajo ha sido presentado en una presentación oral en el reciente congreso internacional “Trends on Nanothecnology” TNT 2012 celebrado en Madrid. El trabajo será publicado en un futuro próximo. Por último, como se dijo anteriormente, el estudio del He, la formación de burbujas en metales líquidos, su difusión nucleación y cavitación es otro problema deseable de ser estudiado mediante técnicas atomísticas. Para ello es necesario el desarrollo de diversos potenciales, He-Li, He-Pb y un potencial ternario Pb-Li-He. Para ello se han realizado simulación ab initio de los sistemas Pb+He y Li+He. Dicho estudio pretende calcular las fuerzas entre los átomos del metal (Pb o Li) con intersticiales de He. De este modo aplicaremos el “force matching method” (FMM) para el desarrollo de dichos potenciales. En el Capítulo 7 se detallan los resultados obtenidos referidos a las posiciones más favorables de las impurezas de He dentro de redes cristalinas de Pb y Li así como el efecto de tener en cuenta el acoplo spin-orbita (SOC en inglés). El análisis de los resultados en términos de transferencia de carga y análisis de las densidades electrónicas, así como la creación de los potenciales mencionados está en progreso. En conjunto la tesis presenta un estudio de los diversos problemas relacionados con el uso de metales líquidos en reactores de fusión y representa un primer paso en la determinación de parámetros de gran importancia para el diseño de blankets y sistemas de primera pared. Con la simulación MD de dichos problemas mediante, importante, potenciales realistas, valores de difusión, solubilidad etc de especies ligeras, H (o sus isotopos) y He en metales líquidos podrá ser calculada complementando así la base de datos que presenta enormes incertidumbres.