Dynamic complexity of chaotic transitions in high-dimensional classical dynamics:Leu-Enkephalin folding

Leu-Enkephalin in explicit water is simulated using classical molecular dynamics. A ß-turn transition is investigated by calculating the topological complexity (in the "computational mechanics" framework [J. P. Crutchfield and K. Young, Phys. Rev. Lett., 63, 105 (1989)]) of the dynamics of both the peptide and the neighbouring water molecules. The complexity of the atomic trajectories of the (relatively short) simulations used in this study reflect the degree of phase space mixing in the system. It is demonstrated that the dynamic complexity of the hydrogen atoms of the peptide and almost all of the hydrogens of the neighbouring waters exhibit a minimum precisely at the moment of the ß-turn transition. This indicates the appearance of simplified periodic patterns in the atomic motion, which could correspond to high-dimensional tori in the phase space. It is hypothesized that this behaviour is the manifestation of the effect described in the approach to molecular transitions by Komatsuzaki and Berry [T. Komatsuzaki and R.S. Berry, Adv. Chem. Phys., 123, 79 (2002)], where a "quasi-regular" dynamics at the transition is suggested. Therefore, for the first time, the less chaotic character of the folding transition in a realistic molecular system is demonstrated. © Springer-Verlag Berlin Heidelberg 2006.

Non-Markov state model of peptide dynamics

A hidden Markov state model has been applied to classical molecular dynamics simulated small peptide in explicit water. The methodology allows increasing the time resolution of the model and describe the dynamics with the precision of 0.3 ps (comparing to 6 ps for the standard methodology). It also permits the investigation of the mechanisms of transitions between the conformational states of the peptide. The detailed description of one of such transitions for the studied molecule is presented. © 2012 Elsevier B.V. All rights reserved.

Molecular mechanisms of salt effects on carbon nanotube dispersions in an organic solvent (N-methyl-2-pyrrolidone)

We consider the effects of salt (sodium iodide) on pristine carbon nanotube (CNT) dispersions in an organic solvent, N-methyl-2-pyrrolidone (NMP). We investigate the molecular-scale mechanisms of ion interactions with the nanotube surface and we show how the microscopic ion-surface interactions affect the stability of CNT dispersions in NMP. In our study we use a combination of fully atomistic Molecular Dynamics simulations of sodium and iodide ions at the CNT-NMP interface with direct experiments on the CNT dispersions. In the experiments we analyze the effects of salt on the stability of the dispersions by photoluminescence (PL) and optical absorption spectroscopy of the samples as well as by visual inspection. By fully atomistic Molecular Dynamics simulations we investigate the molecular-scale mechanisms of sodium and iodide ion interactions with the nanotube surface. Our simulations reveal that both ions are depleted from the CNT surface in the CNT-NMP dispersions mainly due to the two reasons: (1) there is a high energy penalty for the ion partial desolvation at the CNT surface; (2) NMP molecules form a dense solvation layer at the CNT surface that prevents ions to come close to the CNT surface. As a result, an increase of the salt concentration increases the "osmotic" stress in the CNT-NMP system and, thus, decreases the stability of the CNT dispersions in NMP. Direct experiments confirm the simulation results: addition of NaI salt into the NMP dispersions of pristine CNTs leads to precipitation of CNTs (bundle formation) even at very small salt concentration (∼10 -3 mol L -1). In line with the simulation predictions, the effect increases with the increase of the salt concentration. Overall, our results show that dissolved salt ions have strong effects on the stability of CNT dispersions. Therefore, it is possible to stimulate the bundle formation in the CNT-NMP dispersions and regulate the overall concentration of nanotubes in the dispersions by changing the NaI concentration in the solvent. © 2012 The Royal Society of Chemistry.

Molecular alignment relaxation in polymer optical fibers for sensing applications

A systematic study of annealing behavior of drawn PMMA fibers was performed. Annealing dynamics were investigated under different environmental conditions by fiber longitudinal shrinkage monitoring. The shrinkage process was found to follow a stretched exponential decay function revealing the heterogeneous nature of the underlying molecular dynamics. The complex dependence of the fiber shrinkage on initial degree of molecular alignment in the fiber, annealing time and temperature was investigated and interpreted. Moreover, humidity was shown to have a profound effect on the annealing process, which was not recognized previously. Annealing was also shown to have considerable effect on the fiber mechanical properties associated with the relaxation of molecular alignment in the fiber. The consequences of fiber annealing for the climatic stability of certain polymer optical fiber-based sensors are discussed, emphasizing the importance of fiber controlled pre-annealing with respect to the foreseeable operating conditions.

Modelagem molecular voltada para a construção de um nanobiossensor para detecção do herbicida Imazaquin

In this study, our goal was develop and describe a molecular model of the enzyme-inhibiting interaction which can be used for an optimized projection of a Microscope Force Atomic nanobiosensor to detect pesticides molecules, used in agriculture, to evaluate its accordance with limit levels stipulated in valid legislation for its use. The studied herbicide (imazaquin) is a typical member of imidazolinone family and is an inhibitor of the enzymatic activity of Acetohydroxiacid Synthase (AHAS) enzyme that is responsible for the first step of pathway for the synthesis of side-chains in amino acids. The analysis of this enzyme property in the presence of its cofactors was made to obtain structural information and charge distribution of the molecular surface to evaluate its capacity of became immobilized on the Microscopy Atomic Force tip. The computational simulation of the system, using Molecular Dynamics, was possible with the force-field parameters for the cofactor and the herbicides obtained by the online tool SwissParam and it was implemented in force-field CHARMM27, used by software GROMACS; then appropriated simulations were made to validate the new parameters. The molecular orientation of the AHAS was defined based on electrostatic map and the availability of the herbicide in the active site. Steered Molecular Dynamics (SMD) Simulations, followed by quantum mechanics calculations for more representative frames, according to the sequential QM/MM methodology, in a specific direction of extraction of the herbicide from the active site. Therefore, external harmonic forces were applied with similar force constants of AFM cantilever for to simulate herbicide detection experiments by the proposed nanobiosensor. Force value of 1391 pN and binding energy of -14048.52 kJ mol-1 were calculated.

Stable algorithm for event detection in event-driven particle dynamics : logical states

Acknowledgments The authors gratefully acknowledge the support of the German Research Foundation (DFG) through the Cluster of Excellence ‘Engineering of Advanced Materials’ at the University of Erlangen-Nuremberg and through Grant Po 472/25.

A disappearing act performed by magnesium: the nucleotide exchange mechanism of Ran GTPase by Quantum mechanics/Molecular mechanics studies

The Ran GTPase protein is a guanine nucleotide-binding protein (GNBP) with an acknowledged profile in cancer onset, progression and metastases. The complex mechanism adopted by GNBPs in exchanging GDP for GTP is an intriguing process and crucial for Ran viability. The successful completion of the process is a fundamental aspect of propagating downstream signalling events. QM/MM molecular dynamics simulations were employed in this study to provide a deeper mechanistic understanding of the initiation of nucleotide exchange in Ran. Results indicate significant disruption of the metal-binding site upon interaction with RCC1 (the Ran guanine nucleotide exchange factor), overall culminating in the prominent shift of the divalent magnesium ion. The observed ion drifting is reasoned to occur as a consequence of the complex formation between Ran and RCC1 and is postulated to be a critical factor in the exchange process adopted by Ran. This is the first report to observe and detail such intricate dynamics for a protein in Ras superfamily.

A study of electrochemical transport and diffuse charge dynamics using a Langevin equation

This thesis aims to develop new numerical and computational tools to study electrochemical transport and diffuse charge dynamics at small scales. Previous efforts at modeling electrokinetic phenomena at scales where the noncontinuum effects become significant have included continuum models based on the Poisson-Nernst-Planck equations and atomic simulations using molecular dynamics algorithms. Neither of them is easy to use or conducive to electrokinetic transport modeling in strong confinement or over long time scales. This work introduces a new approach based on a Langevin equation for diffuse charge dynamics in nanofluidic devices, which incorporates features from both continuum and atomistic methods. The model is then extended to include steric effects resulting from finite ion size, and applied to the phenomenon of double layer charging in a symmetric binary electrolyte between parallel-plate blocking electrodes, between which a voltage is applied. Finally, the results of this approach are compared to those of the continuum model based on the Poisson-Nernst-Planck equations.

A influência da incorporação de ácido α-eleosteárico, purificado e isolado do óleo de tungue, na dinâmica molecular de lipossomos

Este trabalho descreve o isolamento e purificação do ácido α-eleosteárico (α-ESA) a partir do óleo de tungue e sua caracterização por espectroscopia de infravermelho com transformada de Fourier (FTIR), cromatografia gasosa acoplada com espectrometria de massas (GC-MS) e espectroscopia de ressonância magnética nuclear (RMN) de 1H e 13C. O α-ESA apresenta atividades biológicas (antitumorais, anti-inflamatórias e antioxidantes), tornando-se importante compreender sua interação com membranas lipídicas. Assim, este trabalho também descreve resultados referentes ao efeito da incorporação de α-ESA na dinâmica molecular de lipossomos compostos por fosfatidilcolina. O sistema lipossomal puro e contendo α-ESA foi caracterizado através do uso de espectroscopia de UV-visível, FTIR, RMN e calorimetria de varredura diferencial (DSC). Como resultados da purificação do α-ESA, obtivemos uma pureza de 95,9% utilizando acetona como solvente de recristalização em detrimento dos 92,2% em solução etanólica. Na incorporação em lipossomos, observou-se uma maior interação do α-ESA com a parte polar, de interface e os primeiros metilenos da região apolar da fosfatidilcolina. Além disso, α-ESA apresentou um efeito de redução da fluidez de lipossomos. Os resultados contribuem para a geração de conhecimento para o desenvolvimento de novos sistemas farmacológicos.

Host-guest system of 4-nerolidylcatechol in 2-hydroxypropyl-beta-cyclodextrin: preparation, characterization and molecular modeling

The interaction of 4-nerolidylcatechol (4-NRC), a potent antioxidant agent, and 2-hydroxypropyl-beta-cyclodextrin (HP-beta-CD) was investigated by the solubility method using Fourier transform infrared (FTIR) methods in addition to UV-Vis, (1)H-nuclear magnetic resonance (NMR) spectroscopy and molecular modeling. The inclusion complexes were prepared using grinding, kneading and freeze-drying methods. According to phase solubility studies in water a B(S)-type diagram was found, displaying a stoichiometry complexation of 2:1 (drug:host) and stability constant of 6494 +/- A 837 M(-1). Stoichiometry was established by the UV spectrophotometer using Job's plot method and, also confirmed by molecular modeling. Data from (1)H-NMR, and FTIR, experiments also provided formation evidence of an inclusion complex between 4-NRC and HP-beta-CD. 4-NRC complexation indeed led to higher drug solubility and stability which could probably be useful to improve its biological properties and make it available to oral administration and topical formulations.

Path-integral and Coarse-graining Strategies for Complex Molecular Phenomena

Molecular simulation provides a powerful tool for connecting molecular-level processes to physical observables. However, the facility to make those connections relies upon the application and development of theoretical methods that permit appropriate descriptions of the systems or processes to be studied. In this thesis, we utilize molecular simulation to study and predict two phenomena with very different theoretical challenges, beginning with (1) lithium-ion transport behavior in polymers and following with (2) equilibrium isotope effects with relevance to position-specific and clumped isotope studies. In the case of ion transport in polymers, there is motivation to use molecular simulation to provide guidance in polymer electrolyte design, but the length and timescales relevant for ion diffusion in polymers preclude the use of direct molecular dynamics simulation to compute ion diffusivities in more than a handful of candidate systems. In the case of equilibrium isotope effects, the thermodynamic driving forces for isotopic fractionation are often fundamentally quantum mechanical in nature, and the high precision of experimental instruments demands correspondingly accurate theoretical approaches. Herein, we describe respectively coarse-graining and path-integral strategies to address outstanding questions in these two subject areas.

MOLECULAR MODELING OF EPON 862-DETDA / CARBON COMPOSITES

The thermoset epoxy resin EPON 862, coupled with the DETDA hardening agent, are utilized as the polymer matrix component in many graphite (carbon fiber) composites. Because it is difficult to experimentally characterize the interfacial region, computational molecular modeling is a necessary tool for understanding the influence of the interfacial molecular structure on bulk-level material properties. The purpose of this research is to investigate the many possible variables that may influence the interfacial structure and the effect they will have on the mechanical behavior of the bulk level composite. Molecular models are established for EPON 862-DETDA polymer in the presence of a graphite surface. Material characteristics such as polymer mass-density, residual stresses, and molecular potential energy are investigated near the polymer/fiber interface. Because the exact degree of crosslinking in these thermoset systems is not known, many different crosslink densities (degrees of curing) are investigated. It is determined that a region exists near the carbon fiber surface in which the polymer mass density is different than that of the bulk mass density. These surface effects extend ~10 Å into the polymer from the center of the outermost graphite layer. Early simulations predict polymer residual stress levels to be higher near the graphite surface. It is also seen that the molecular potential energy in polymer atoms decreases with increasing crosslink density. New models are then established in order to investigate the interface between EPON 862-DETDA polymer and graphene nanoplatelets (GNPs) of various atomic thicknesses. Mechanical properties are extracted from the models using Molecular Dynamics techniques. These properties are then implemented into micromechanics software that utilizes the generalized method of cells to create representations of macro-scale composites. Micromechanics models are created representing GNP doped epoxy with varying number of graphene layers and interfacial polymer crosslink densities. The initial micromechanics results for the GNP doped epoxy are then taken to represent the matrix component and are re-run through the micromechanics software with the addition of a carbon fiber to simulate a GNP doped epoxy/carbon fiber composite. Micromechanics results agree well with experimental data, and indicate GNPs of 1 to 2 atomic layers to be highly favorable. The effect of oxygen bonded to the surface of the GNPs is lastly investigated. Molecular Models are created for systems with varying graphene atomic thickness, along with different amounts of oxygen species attached to them. Models are created for graphene containing hydroxyl groups only, epoxide groups only, and a combination of epoxide and hydroxyl groups. Results show models of oxidized graphene to decrease in both tensile and shear modulus. Attaching only epoxide groups gives the best results for mechanical properties, though pristine graphene is still favored.

Computing the structural and vibrational properties of polymorphic organic molecular crystals through van der Waals corrected density functional theory and the electronic properties of organic thin films through microelectrostatic calculations.

The present Thesis reports on the various research projects to which I have contributed during my PhD period, working with several research groups, and whose results have been communicated in a number of scientific publications. The main focus of my research activity was to learn, test, exploit and extend the recently developed vdW-DFT (van der Waals corrected Density Functional Theory) methods for computing the structural, vibrational and electronic properties of ordered molecular crystals from first principles. A secondary, and more recent, research activity has been the analysis with microelectrostatic methods of Molecular Dynamics (MD) simulations of disordered molecular systems. While only very unreliable methods based on empirical models were practically usable until a few years ago, accurate calculations of the crystal energy are now possible, thanks to very fast modern computers and to the excellent performance of the best vdW-DFT methods. Accurate energies are particularly important for describing organic molecular solids, since they often exhibit several alternative crystal structures (polymorphs), with very different packing arrangements but very small energy differences. Standard DFT methods do not describe the long-range electron correlations which give rise to the vdW interactions. Although weak, these interactions are extremely sensitive to the packing arrangement, and neglecting them used to be a problem. The calculations of reliable crystal structures and vibrational frequencies has been made possible only recently, thanks to development of some good representations of the vdW contribution to the energy (known as “vdW corrections”).

Molecular modelling of organic functional materials

The investigation of the mechanisms lying behind the (photo-)chemical processes is fundamental to address and improve the design of new organic functional materials. In many cases, dynamics simulations represent the only tool to capture the system properties emerging from complex interactions between many molecules. Despite the outstanding progresses in calculation power, the only way to carry out such computational studies is to introduce several approximations with respect to a fully quantum mechanical (QM) description. This thesis presents an approach that combines QM calculations with a classical Molecular Dynamics (MD) approach by means of accurate QM-derived force fields. It is based on a careful selection of the most relevant molecular degrees of freedom, whose potential energy surface is calculated at QM level and reproduced by the analytic functions of the force field, as well as by an accurate tuning of the approximations introduced in the model of the process to be simulated. This is made possible by some tools developed purposely, that allow to obtain and test the FF parameters through comparison with the QM frequencies and normal modes. These tools were applied in the modelling of three processes: the npi* photoisomerisation of azobenzene, where the FF description was extended to the excited state too and the non-adiabatic events were treated stochastically with Tully fewest switching algorithm; the charge separation in donors-acceptors bulk heterojunction organic solar cells, where a tight-binding Hamiltonian was carefully parametrised and solved by means of a code, also written specifically; the effect of the protonation state on the photoisomerisation quantum yield of the aryl-azoimidazolium unit of the axle molecule of a rotaxane molecular shuttle. In each case, the QM-based MD models that were specifically developed gave noteworthy information about the investigated phenomena, proving to be a fundamental key for a deeper comprehension of several experimental evidences.

A multidisciplinary approach to the study of protein dynamics and signal transmission

Allostery is a phenomenon of fundamental importance in biology, allowing regulation of function and dynamic adaptability of enzymes and proteins. Despite the allosteric effect was first observed more than a century ago allostery remains a biophysical enigma, defined as the “second secret of life”. The challenge is mainly associated to the rather complex nature of the allosteric mechanisms, which manifests itself as the alteration of the biological function of a protein/enzyme (e.g. ligand/substrate binding at the active site) by binding of “other object” (“allos stereos” in Greek) at a site distant (> 1 nanometer) from the active site, namely the effector site. Thus, at the heart of allostery there is signal propagation from the effector to the active site through a dense protein matrix, with a fundamental challenge being represented by the elucidation of the physico-chemical interactions between amino acid residues allowing communicatio n between the two binding sites, i.e. the “allosteric pathways”. Here, we propose a multidisciplinary approach based on a combination of computational chemistry, involving molecular dynamics simulations of protein motions, (bio)physical analysis of allosteric systems, including multiple sequence alignments of known allosteric systems, and mathematical tools based on graph theory and machine learning that can greatly help understanding the complexity of dynamical interactions involved in the different allosteric systems. The project aims at developing robust and fast tools to identify unknown allosteric pathways. The characterization and predictions of such allosteric spots could elucidate and fully exploit the power of allosteric modulation in enzymes and DNA-protein complexes, with great potential applications in enzyme engineering and drug discovery.