A computational chemistry perspective on the current status and future direction of hepatitis B antiviral drug discovery.

PubMed

Morgnanesi, Dante; Heinrichs, Eric J; Mele, Anthony R; Wilkinson, Sean; Zhou, Suzanne; Kulp, John L

2015-11-01

Computational chemical biology, applied to research on hepatitis B virus (HBV), has two major branches: bioinformatics (statistical models) and first-principle methods (molecular physics). While bioinformatics focuses on statistical tools and biological databases, molecular physics uses mathematics and chemical theory to study the interactions of biomolecules. Three computational techniques most commonly used in HBV research are homology modeling, molecular docking, and molecular dynamics. Homology modeling is a computational simulation to predict protein structure and has been used to construct conformers of the viral polymerase (reverse transcriptase domain and RNase H domain) and the HBV X protein. Molecular docking is used to predict the most likely orientation of a ligand when it is bound to a protein, as well as determining an energy score of the docked conformation. Molecular dynamics is a simulation that analyzes biomolecule motions and determines conformation and stability patterns. All of these modeling techniques have aided in the understanding of resistance mutations on HBV non-nucleos(t)ide reverse-transcriptase inhibitor binding. Finally, bioinformatics can be used to study the DNA and RNA protein sequences of viruses to both analyze drug resistance and to genotype the viral genomes. Overall, with these techniques, and others, computational chemical biology is becoming more and more necessary in hepatitis B research. This article forms part of a symposium in Antiviral Research on "An unfinished story: from the discovery of the Australia antigen to the development of new curative therapies for hepatitis B." Copyright © 2015 Elsevier B.V. All rights reserved.

Prediction of solubility parameters and miscibility of pharmaceutical compounds by molecular dynamics simulations.

PubMed

Gupta, Jasmine; Nunes, Cletus; Vyas, Shyam; Jonnalagadda, Sriramakamal

2011-03-10

The objectives of this study were (i) to develop a computational model based on molecular dynamics technique to predict the miscibility of indomethacin in carriers (polyethylene oxide, glucose, and sucrose) and (ii) to experimentally verify the in silico predictions by characterizing the drug-carrier mixtures using thermoanalytical techniques. Molecular dynamics (MD) simulations were performed using the COMPASS force field, and the cohesive energy density and the solubility parameters were determined for the model compounds. The magnitude of difference in the solubility parameters of drug and carrier is indicative of their miscibility. The MD simulations predicted indomethacin to be miscible with polyethylene oxide and to be borderline miscible with sucrose and immiscible with glucose. The solubility parameter values obtained using the MD simulations values were in reasonable agreement with those calculated using group contribution methods. Differential scanning calorimetry showed melting point depression of polyethylene oxide with increasing levels of indomethacin accompanied by peak broadening, confirming miscibility. In contrast, thermal analysis of blends of indomethacin with sucrose and glucose verified general immiscibility. The findings demonstrate that molecular modeling is a powerful technique for determining the solubility parameters and predicting miscibility of pharmaceutical compounds. © 2011 American Chemical Society

Methods in Molecular Biology: Germline Stem Cells | Center for Cancer Research

Cancer.gov

The protocols in Germline Stem Cells are intended to present selected genetic, molecular, and cellular techniques used in germline stem cell research. The book is divided into two parts. Part I covers germline stem cell identification and regulation in model organisms. Part II covers current techniques used in in vitro culture and applications of germline stem cells.

Bio-functions and molecular carbohydrate structure association study in forage with different source origins revealed using non-destructive vibrational molecular spectroscopy techniques

NASA Astrophysics Data System (ADS)

Ji, Cuiying; Zhang, Xuewei; Yan, Xiaogang; Mostafizar Rahman, M.; Prates, Luciana L.; Yu, Peiqiang

2017-08-01

The objectives of this study were to: 1) investigate forage carbohydrate molecular structure profiles; 2) bio-functions in terms of CHO rumen degradation characteristics and hourly effective degradation ratio of N to OM (HEDN/OM), and 3) quantify interactive association between molecular structures, bio-functions and nutrient availability. The vibrational molecular spectroscopy was applied to investigate the structure feature on a molecular basis. Two sourced-origin alfalfa forages were used as modeled forages. The results showed that the carbohydrate molecular structure profiles were highly linked to the bio-functions in terms of rumen degradation characteristics and hourly effective degradation ratio. The molecular spectroscopic technique can be used to detect forage carbohydrate structure features on a molecular basis and can be used to study interactive association between forage molecular structure and bio-functions.

State of the Art Assessment of Simulation in Advanced Materials Development

NASA Technical Reports Server (NTRS)

Wise, Kristopher E.

2008-01-01

Advances in both the underlying theory and in the practical implementation of molecular modeling techniques have increased their value in the advanced materials development process. The objective is to accelerate the maturation of emerging materials by tightly integrating modeling with the other critical processes: synthesis, processing, and characterization. The aims of this report are to summarize the state of the art of existing modeling tools and to highlight a number of areas in which additional development is required. In an effort to maintain focus and limit length, this survey is restricted to classical simulation techniques including molecular dynamics and Monte Carlo simulations.

Simulation of aerosol flow interaction with a solid body on molecular level

NASA Astrophysics Data System (ADS)

Amelyushkin, Ivan A.; Stasenko, Albert L.

2018-05-01

Physico-mathematical models and numerical algorithm of two-phase flow interaction with a solid body are developed. Results of droplet motion and its impingement upon a rough surface in real gas boundary layer simulation on the molecular level obtained via molecular dynamics technique are presented.

Massively Parallel Simulations of Diffusion in Dense Polymeric Structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faulon, Jean-Loup, Wilcox, R.T.

1997-11-01

An original computational technique to generate close-to-equilibrium dense polymeric structures is proposed. Diffusion of small gases are studied on the equilibrated structures using massively parallel molecular dynamics simulations running on the Intel Teraflops (9216 Pentium Pro processors) and Intel Paragon(1840 processors). Compared to the current state-of-the-art equilibration methods this new technique appears to be faster by some orders of magnitude.The main advantage of the technique is that one can circumvent the bottlenecks in configuration space that inhibit relaxation in molecular dynamics simulations. The technique is based on the fact that tetravalent atoms (such as carbon and silicon) fit in themore » center of a regular tetrahedron and that regular tetrahedrons can be used to mesh the three-dimensional space. Thus, the problem of polymer equilibration described by continuous equations in molecular dynamics is reduced to a discrete problem where solutions are approximated by simple algorithms. Practical modeling applications include the constructing of butyl rubber and ethylene-propylene-dimer-monomer (EPDM) models for oxygen and water diffusion calculations. Butyl and EPDM are used in O-ring systems and serve as sealing joints in many manufactured objects. Diffusion coefficients of small gases have been measured experimentally on both polymeric systems, and in general the diffusion coefficients in EPDM are an order of magnitude larger than in butyl. In order to better understand the diffusion phenomena, 10, 000 atoms models were generated and equilibrated for butyl and EPDM. The models were submitted to a massively parallel molecular dynamics simulation to monitor the trajectories of the diffusing species.« less

Electronic excitations in molecular solids: bridging theory and experiment.

PubMed

Skelton, Jonathan M; da Silva, E Lora; Crespo-Otero, Rachel; Hatcher, Lauren E; Raithby, Paul R; Parker, Stephen C; Walsh, Aron

2015-01-01

As the spatial and temporal resolution accessible to experiment and theory converge, computational chemistry is an increasingly powerful tool for modelling and interpreting spectroscopic data. However, the study of molecular processes, in particular those related to electronic excitations (e.g. photochemistry), frequently pushes quantum-chemical techniques to their limit. The disparity in the level of theory accessible to periodic and molecular calculations presents a significant challenge when modelling molecular crystals, since accurate calculations require a high level of theory to describe the molecular species, but must also take into account the influence of the crystalline environment on their properties. In this article, we briefly review the different classes of quantum-chemical techniques, and present an overview of methods that account for environmental influences with varying levels of approximation. Using a combination of solid-state and molecular calculations, we quantitatively evaluate the performance of implicit-solvent models for the [Ni(Et4dien)(η2-O,ON)(η1-NO2)] linkage-isomer system as a test case. We focus particularly on the accurate reproduction of the energetics of the isomerisation, and on predicting spectroscopic properties to compare with experimental results. This work illustrates how the synergy between periodic and molecular calculations can be exploited for the study of molecular crystals, and forms a basis for the investigation of more challenging phenomena, such as excited-state dynamics, and for further methodological developments.

Macro and micro analysis of small molecule diffusion in amorphous polymers

NASA Astrophysics Data System (ADS)

Putta, Santosh Krishna

In this study, both macroscopic and microscopic numerical techniques have been explored, to model and understand the diffusion behavior of small molecules in amorphous polymers, which very often do not follow the classical Fickian law. It was attempted to understand the influence of various aspects of the molecular structure of a polymer on its macroscopic diffusion behavior. At the macroscopic level, a hybrid finite-element/finite-difference model is developed to implement the coupled diffusion and deformation constitutive equations. A viscoelasticity theory, combined with time-freevolume superposition is used to model the deformation processes. A freevolume-based model is used to model the diffusion processes. The freevolume in the polymer is used as a coupling factor between the deformation and the diffusion processes. The model is shown to qualitatively describe some of the typical non-Fickian diffusion behavior in polymers. However, it does not directly involve the microstructure of a polymer. Further, some of the input parameters to the model are difficult to obtain experimentally. A numerical microscopic approach is therefore adopted to study the molecular structure of polymers. A molecular mechanics and dynamics technique combined with a modified Rotational Isomeric State (RIS) approach, is followed to generate the molecular structure for two types of polycarbonates, and, two types of polyacrylates, starting only with their chemical structures. A new efficient 3-D algorithm for Delaunay Tessellation is developed, and, then applied to discretize the molecular structure into Delaunay Tetrahedra. By using the dicretized molecular structure, size, shape, and, connectivity of free-spaces for small molecule diffusion in the above mentioned polymers, are then studied in relation to their diffusion properties. The influence of polymer and side chain flexibility, and diffusant-diffusant and diffusant-polymer molecular interactions, is also discussed with respect to the diffusion properties.

Computer-aided molecular modeling techniques for predicting the stability of drug cyclodextrin inclusion complexes in aqueous solutions

NASA Astrophysics Data System (ADS)

Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola

2002-06-01

Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.

Applications of molecular modeling in coal research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlson, G.A.; Faulon, J.L.

Over the past several years, molecular modeling has been applied to study various characteristics of coal molecular structures. Powerful workstations coupled with molecular force-field-based software packages have been used to study coal and coal-related molecules. Early work involved determination of the minimum-energy three-dimensional conformations of various published coal structures (Given, Wiser, Solomon and Shinn), and the dominant role of van der Waals and hydrogen bonding forces in defining the energy-minimized structures. These studies have been extended to explore various physical properties of coal structures, including density, microporosity, surface area, and fractal dimension. Other studies have related structural characteristics to cross-linkmore » density and have explored small molecule interactions with coal. Finally, recent studies using a structural elucidation (molecular builder) technique have constructed statistically diverse coal structures based on quantitative and qualitative data on coal and its decomposition products. This technique is also being applied to study coalification processes based on postulated coalification chemistry.« less

Mathematical modeling of molecular diffusion through mucus

PubMed Central

Cu, Yen; Saltzman, W. Mark

2008-01-01

The rate of molecular transport through the mucus gel can be an important determinant of efficacy for therapeutic agents delivered by oral, intranasal, intravaginal/rectal, and intraocular routes. Transport through mucus can be described by mathematical models based on principles of physical chemistry and known characteristics of the mucus gel, its constituents, and of the drug itself. In this paper, we review mathematical models of molecular diffusion in mucus, as well as the techniques commonly used to measure diffusion of solutes in the mucus gel, mucus gel mimics, and mucosal epithelia. PMID:19135488

Application of computer-assisted molecular modeling (CAMM) for immunoassay of low molecular weight food contaminants: A review

USDA-ARS?s Scientific Manuscript database

Immunoassay for low molecular weight food contaminants, such as pesticides, veterinary drugs, and mycotoxins is now a well-established technique which meets the demands for a rapid, reliable, and cost-effective analytical method. However, due to limited understanding of the fundamental aspects of i...

Modeling of metal thin film growth: Linking angstrom-scale molecular dynamics results to micron-scale film topographies

NASA Astrophysics Data System (ADS)

Hansen, U.; Rodgers, S.; Jensen, K. F.

2000-07-01

A general method for modeling ionized physical vapor deposition is presented. As an example, the method is applied to growth of an aluminum film in the presence of an ionized argon flux. Molecular dynamics techniques are used to examine the surface adsorption, reflection, and sputter reactions taking place during ionized physical vapor deposition. We predict their relative probabilities and discuss their dependence on energy and incident angle. Subsequently, we combine the information obtained from molecular dynamics with a line of sight transport model in a two-dimensional feature, incorporating all effects of reemission and resputtering. This provides a complete growth rate model that allows inclusion of energy- and angular-dependent reaction rates. Finally, a level-set approach is used to describe the morphology of the growing film. We thus arrive at a computationally highly efficient and accurate scheme to model the growth of thin films. We demonstrate the capabilities of the model predicting the major differences on Al film topographies between conventional and ionized sputter deposition techniques studying thin film growth under ionized physical vapor deposition conditions with different Ar fluxes.

Experimental and molecular docking studies on DNA binding interaction of adefovir dipivoxil: Advances toward treatment of hepatitis B virus infections

NASA Astrophysics Data System (ADS)

Shahabadi, Nahid; Falsafi, Monireh

The toxic interaction of adefovir dipivoxil with calf thymus DNA (CT-DNA) was investigated in vitro under simulated physiological conditions by multi-spectroscopic techniques and molecular modeling study. The fluorescence spectroscopy and UV absorption spectroscopy indicated drug interacted with CT-DNA in a groove binding mode. The binding constant of UV-visible and the number of binding sites were 3.33 ± 0.2 × 104 L mol-1and 0.99, respectively. The fluorimetric studies showed that the reaction between the drug and CT-DNA is exothermic (ΔH = 34.4 kJ mol-1; ΔS = 184.32 J mol-1 K-1). Circular dichroism spectroscopy (CD) was employed to measure the conformational change of CT-DNA in the presence of adefovir dipivoxil, which verified the groove binding mode. Furthermore, the drug induces detectable changes in its viscosity. The molecular modeling results illustrated that adefovir strongly binds to groove of DNA by relative binding energy of docked structure -16.83 kJ mol-1. This combination of multiple spectroscopic techniques and molecular modeling methods can be widely used in the investigation on the toxic interaction of small molecular pollutants and drugs with bio macromolecules, which contributes to clarify the molecular mechanism of toxicity or side effect in vivo.

Shedding light on the puzzle of drug-membrane interactions: Experimental techniques and molecular dynamics simulations.

PubMed

Lopes, Daniela; Jakobtorweihen, Sven; Nunes, Cláudia; Sarmento, Bruno; Reis, Salette

2017-01-01

Lipid membranes work as barriers, which leads to inevitable drug-membrane interactions in vivo. These interactions affect the pharmacokinetic properties of drugs, such as their diffusion, transport, distribution, and accumulation inside the membrane. Furthermore, these interactions also affect their pharmacodynamic properties with respect to both therapeutic and toxic effects. Experimental membrane models have been used to perform in vitro assessment of the effects of drugs on the biophysical properties of membranes by employing different experimental techniques. In in silico studies, molecular dynamics simulations have been used to provide new insights at an atomistic level, which enables the study of properties that are difficult or even impossible to measure experimentally. Each model and technique has its advantages and disadvantages. Hence, combining different models and techniques is necessary for a more reliable study. In this review, the theoretical backgrounds of these (in vitro and in silico) approaches are presented, followed by a discussion of the pharmacokinetic and pharmacodynamic properties of drugs that are related to their interactions with membranes. All approaches are discussed in parallel to present for a better connection between experimental and simulation studies. Finally, an overview of the molecular dynamics simulation studies used for drug-membrane interactions is provided. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiscale geometric modeling of macromolecules II: Lagrangian representation

PubMed Central

Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei

2013-01-01

Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599

Application of Deep Learning in Automated Analysis of Molecular Images in Cancer: A Survey

PubMed Central

Xue, Yong; Chen, Shihui; Liu, Yong

2017-01-01

Molecular imaging enables the visualization and quantitative analysis of the alterations of biological procedures at molecular and/or cellular level, which is of great significance for early detection of cancer. In recent years, deep leaning has been widely used in medical imaging analysis, as it overcomes the limitations of visual assessment and traditional machine learning techniques by extracting hierarchical features with powerful representation capability. Research on cancer molecular images using deep learning techniques is also increasing dynamically. Hence, in this paper, we review the applications of deep learning in molecular imaging in terms of tumor lesion segmentation, tumor classification, and survival prediction. We also outline some future directions in which researchers may develop more powerful deep learning models for better performance in the applications in cancer molecular imaging. PMID:29114182

CELLULAR, BIOCHEMICAL, AND MOLECULAR TECHNIQUES IN DEVELOPMENTAL TOXICOLOGY

EPA Science Inventory

Cellular, molecular and biochemical approaches vastly expand the possibilities for revealing the underlying mechanisms of developmental toxicity. The increasing interest in embryonic development as a model system for the study of gene expression has resulted in a cornucopia of i...

Exploring Biomolecular Recognition by Modeling and Simulation

NASA Astrophysics Data System (ADS)

Wade, Rebecca

2007-12-01

Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.

Molecular dynamics computer simulation of permeation in solids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pohl, P.I.; Heffelfinger, G.S.; Fisler, D.K.

1997-12-31

In this work the authors simulate permeation of gases and cations in solid models using molecular mechanics and a dual control volume grand canonical molecular dynamics technique. The molecular sieving nature of microporous zeolites are discussed and compared with that for amorphous silica made by sol-gel methods. One mesoporous and one microporous membrane model are tested with Lennard-Jones gases corresponding to He, H{sub 2}, Ar and CH{sub 4}. The mesoporous membrane model clearly follows a Knudsen diffusion mechanism, while the microporous model having a hard-sphere cutoff pore diameter of {approximately}3.4 {angstrom} demonstrates molecular sieving of the methane ({sigma} = 3.8more » {angstrom}) but anomalous behavior for Ar ({sigma} = 3.4 {angstrom}). Preliminary results of Ca{sup +} diffusion in calcite and He/H{sub 2} diffusion in polyisobutylene are also presented.« less

Molecular rheology of branched polymers: decoding and exploring the role of architectural dispersity through a synergy of anionic synthesis, interaction chromatography, rheometry and modeling.

PubMed

van Ruymbeke, E; Lee, H; Chang, T; Nikopoulou, A; Hadjichristidis, N; Snijkers, F; Vlassopoulos, D

2014-07-21

An emerging challenge in polymer physics is the quantitative understanding of the influence of a macromolecular architecture (i.e., branching) on the rheological response of entangled complex polymers. Recent investigations of the rheology of well-defined architecturally complex polymers have determined the composition in the molecular structure and identified the role of side-products in the measured samples. The combination of different characterization techniques, experimental and/or theoretical, represents the current state-of-the-art. Here we review this interdisciplinary approach to molecular rheology of complex polymers, and show the importance of confronting these different tools for ensuring an accurate characterization of a given polymeric sample. We use statistical tools in order to relate the information available from the synthesis protocols of a sample and its experimental molar mass distribution (typically obtained from size exclusion chromatography), and hence obtain precise information about its structural composition, i.e. enhance the existing sensitivity limit. We critically discuss the use of linear rheology as a reliable quantitative characterization tool, along with the recently developed temperature gradient interaction chromatography. The latter, which has emerged as an indispensable characterization tool for branched architectures, offers unprecedented sensitivity in detecting the presence of different molecular structures in a sample. Combining these techniques is imperative in order to quantify the molecular composition of a polymer and its consequences on the macroscopic properties. We validate this approach by means of a new model asymmetric comb polymer which was synthesized anionically. It was thoroughly characterized and its rheology was carefully analyzed. The main result is that the rheological signal reveals fine molecular details, which must be taken into account to fully elucidate the viscoelastic response of entangled branched polymers. It is important to appreciate that, even optimal model systems, i.e., those synthesized with high-vacuum anionic methods, need thorough characterization via a combination of techniques. Besides helping to improve synthetic techniques, this methodology will be significant in fine-tuning mesoscopic tube-based models and addressing outstanding issues such as the quantitative description of the constraint release mechanism.

Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System

PubMed Central

Adelson, David; Brown, Fred; Chaudhri, Naeem

2017-01-01

The use of intelligent techniques in medicine has brought a ray of hope in terms of treating leukaemia patients. Personalized treatment uses patient's genetic profile to select a mode of treatment. This process makes use of molecular technology and machine learning, to determine the most suitable approach to treating a leukaemia patient. Until now, no reviews have been published from a computational perspective concerning the development of personalized medicine intelligent techniques for leukaemia patients using molecular data analysis. This review studies the published empirical research on personalized medicine in leukaemia and synthesizes findings across studies related to intelligence techniques in leukaemia, with specific attention to particular categories of these studies to help identify opportunities for further research into personalized medicine support systems in chronic myeloid leukaemia. A systematic search was carried out to identify studies using intelligence techniques in leukaemia and to categorize these studies based on leukaemia type and also the task, data source, and purpose of the studies. Most studies used molecular data analysis for personalized medicine, but future advancement for leukaemia patients requires molecular models that use advanced machine-learning methods to automate decision-making in treatment management to deliver supportive medical information to the patient in clinical practice. PMID:28812013

Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System.

PubMed

Banjar, Haneen; Adelson, David; Brown, Fred; Chaudhri, Naeem

2017-01-01

The use of intelligent techniques in medicine has brought a ray of hope in terms of treating leukaemia patients. Personalized treatment uses patient's genetic profile to select a mode of treatment. This process makes use of molecular technology and machine learning, to determine the most suitable approach to treating a leukaemia patient. Until now, no reviews have been published from a computational perspective concerning the development of personalized medicine intelligent techniques for leukaemia patients using molecular data analysis. This review studies the published empirical research on personalized medicine in leukaemia and synthesizes findings across studies related to intelligence techniques in leukaemia, with specific attention to particular categories of these studies to help identify opportunities for further research into personalized medicine support systems in chronic myeloid leukaemia. A systematic search was carried out to identify studies using intelligence techniques in leukaemia and to categorize these studies based on leukaemia type and also the task, data source, and purpose of the studies. Most studies used molecular data analysis for personalized medicine, but future advancement for leukaemia patients requires molecular models that use advanced machine-learning methods to automate decision-making in treatment management to deliver supportive medical information to the patient in clinical practice.

Treatment of atomic and molecular line blanketing by opacity sampling. [atmospheric optics - stellar atmospheres

NASA Technical Reports Server (NTRS)

Johnson, H. R.; Krupp, B. M.

1975-01-01

An opacity sampling (OS) technique for treating the radiative opacity of large numbers of atomic and molecular lines in cool stellar atmospheres is presented. Tests were conducted and results show that the structure of atmospheric models is accurately fixed by the use of 1000 frequency points, and 500 frequency points is often adequate. The effects of atomic and molecular lines are separately studied. A test model computed by using the OS method agrees very well with a model having identical atmospheric parameters computed by the giant line (opacity distribution function) method.

A new model for simulating 3-d crystal growth and its application to the study of antifreeze proteins.

PubMed

Wathen, Brent; Kuiper, Michael; Walker, Virginia; Jia, Zongchao

2003-01-22

A novel computational technique for modeling crystal formation has been developed that combines three-dimensional (3-D) molecular representation and detailed energetics calculations of molecular mechanics techniques with the less-sophisticated probabilistic approach used by statistical techniques to study systems containing millions of molecules undergoing billions of interactions. Because our model incorporates both the structure of and the interaction energies between participating molecules, it enables the 3-D shape and surface properties of these molecules to directly affect crystal formation. This increase in model complexity has been achieved while simultaneously increasing the number of molecules in simulations by several orders of magnitude over previous statistical models. We have applied this technique to study the inhibitory effects of antifreeze proteins (AFPs) on ice-crystal formation. Modeling involving both fish and insect AFPs has produced results consistent with experimental observations, including the replication of ice-etching patterns, ice-growth inhibition, and specific AFP-induced ice morphologies. Our work suggests that the degree of AFP activity results more from AFP ice-binding orientation than from AFP ice-binding strength. This technique could readily be adapted to study other crystal and crystal inhibitor systems, or to study other noncrystal systems that exhibit regularity in the structuring of their component molecules, such as those associated with the new nanotechnologies.

Materials-by-design: computation, synthesis, and characterization from atoms to structures

NASA Astrophysics Data System (ADS)

Yeo, Jingjie; Jung, Gang Seob; Martín-Martínez, Francisco J.; Ling, Shengjie; Gu, Grace X.; Qin, Zhao; Buehler, Markus J.

2018-05-01

In the 50 years that succeeded Richard Feynman’s exposition of the idea that there is ‘plenty of room at the bottom’ for manipulating individual atoms for the synthesis and manufacturing processing of materials, the materials-by-design paradigm is being developed gradually through synergistic integration of experimental material synthesis and characterization with predictive computational modeling and optimization. This paper reviews how this paradigm creates the possibility to develop materials according to specific, rational designs from the molecular to the macroscopic scale. We discuss promising techniques in experimental small-scale material synthesis and large-scale fabrication methods to manipulate atomistic or macroscale structures, which can be designed by computational modeling. These include recombinant protein technology to produce peptides and proteins with tailored sequences encoded by recombinant DNA, self-assembly processes induced by conformational transition of proteins, additive manufacturing for designing complex structures, and qualitative and quantitative characterization of materials at different length scales. We describe important material characterization techniques using numerous methods of spectroscopy and microscopy. We detail numerous multi-scale computational modeling techniques that complements these experimental techniques: DFT at the atomistic scale; fully atomistic and coarse-grain molecular dynamics at the molecular to mesoscale; continuum modeling at the macroscale. Additionally, we present case studies that utilize experimental and computational approaches in an integrated manner to broaden our understanding of the properties of two-dimensional materials and materials based on silk and silk-elastin-like proteins.

Characterization of Pathogenic Human MSH2 Missense Mutations Using Yeast as a Model System: A Laboratory Course in Molecular Biology

ERIC Educational Resources Information Center

Gammie, Alison E.; Erdeniz, Naz

2004-01-01

This work describes the project for an advanced undergraduate laboratory course in cell and molecular biology. One objective of the course is to teach students a variety of cellular and molecular techniques while conducting original research. A second objective is to provide instruction in science writing and data presentation by requiring…

Understanding valence-shell electron-pair repulsion (VSEPR) theory using origami molecular models

NASA Astrophysics Data System (ADS)

Endah Saraswati, Teguh; Saputro, Sulistyo; Ramli, Murni; Praseptiangga, Danar; Khasanah, Nurul; Marwati, Sri

2017-01-01

Valence-shell electron-pair repulsion (VSEPR) theory is conventionally used to predict molecular geometry. However, it is difficult to explore the full implications of this theory by simply drawing chemical structures. Here, we introduce origami modelling as a more accessible approach for exploration of the VSEPR theory. Our technique is simple, readily accessible and inexpensive compared with other sophisticated methods such as computer simulation or commercial three-dimensional modelling kits. This method can be implemented in chemistry education at both the high school and university levels. We discuss the example of a simple molecular structure prediction for ammonia (NH3). Using the origami model, both molecular shape and the scientific justification can be visualized easily. This ‘hands-on’ approach to building molecules will help promote understanding of VSEPR theory.

Molecular Imaging of Experimental Abdominal Aortic Aneurysms

PubMed Central

Ramaswamy, Aneesh K.; Hamilton, Mark; Joshi, Rucha V.; Kline, Benjamin P.; Li, Rui; Wang, Pu; Goergen, Craig J.

2013-01-01

Current laboratory research in the field of abdominal aortic aneurysm (AAA) disease often utilizes small animal experimental models induced by genetic manipulation or chemical application. This has led to the use and development of multiple high-resolution molecular imaging modalities capable of tracking disease progression, quantifying the role of inflammation, and evaluating the effects of potential therapeutics. In vivo imaging reduces the number of research animals used, provides molecular and cellular information, and allows for longitudinal studies, a necessity when tracking vessel expansion in a single animal. This review outlines developments of both established and emerging molecular imaging techniques used to study AAA disease. Beyond the typical modalities used for anatomical imaging, which include ultrasound (US) and computed tomography (CT), previous molecular imaging efforts have used magnetic resonance (MR), near-infrared fluorescence (NIRF), bioluminescence, single-photon emission computed tomography (SPECT), and positron emission tomography (PET). Mouse and rat AAA models will hopefully provide insight into potential disease mechanisms, and the development of advanced molecular imaging techniques, if clinically useful, may have translational potential. These efforts could help improve the management of aneurysms and better evaluate the therapeutic potential of new treatments for human AAA disease. PMID:23737735

Molecular modeling: An open invitation for applied mathematics

NASA Astrophysics Data System (ADS)

Mezey, Paul G.

2013-10-01

Molecular modeling methods provide a very wide range of challenges for innovative mathematical and computational techniques, where often high dimensionality, large sets of data, and complicated interrelations imply a multitude of iterative approximations. The physical and chemical basis of these methodologies involves quantum mechanics with several non-intuitive aspects, where classical interpretation and classical analogies are often misleading or outright wrong. Hence, instead of the everyday, common sense approaches which work so well in engineering, in molecular modeling one often needs to rely on rather abstract mathematical constraints and conditions, again emphasizing the high level of reliance on applied mathematics. Yet, the interdisciplinary aspects of the field of molecular modeling also generates some inertia and perhaps too conservative reliance on tried and tested methodologies, that is at least partially caused by the less than up-to-date involvement in the newest developments in applied mathematics. It is expected that as more applied mathematicians take up the challenge of employing the latest advances of their field in molecular modeling, important breakthroughs may follow. In this presentation some of the current challenges of molecular modeling are discussed.

Application of computer-assisted molecular modeling for immunoassay of low molecular weight food contaminants: A review.

PubMed

Xu, Zhen-Lin; Shen, Yu-Dong; Beier, Ross C; Yang, Jin-Yi; Lei, Hong-Tao; Wang, Hong; Sun, Yuan-Ming

2009-08-11

Immunoassay for low molecular weight food contaminants, such as pesticides, veterinary drugs, and mycotoxins is now a well-established technique which meets the demand for a rapid, reliable, and cost-effective analytical method. However, due to limited understanding of the molecular structure of antibody binding sites and antigenic epitopes, as well as the intermolecular binding forces that come into play, the traditional 'trial and error' method used to develop antibodies still remains the method of choice. Therefore, development of enhanced immunochemical techniques for specific- and generic-assays, requires new approaches for antibody design that will improve affinity and specificity of the antibody in a more rapid and economic manner. Computer-assisted molecular modeling (CAMM) has been demonstrated to be a useful tool to help the immunochemist develop immunoassays. CAMM methods can be used to help direct improvements to important antibody features, and can provide insights into the effects of molecular structure on biological activity that are difficult or impossible to obtain in any other way. In this review, we briefly summarize applications of CAMM in immunoassay development, including assisting in hapten design, explaining cross-reactivity, modeling antibody-antigen interactions, and providing insights into the effects of the mouse body temperature on the three-dimensional conformation of a hapten during antibody production. The fundamentals and theory, programs and software, limitations, and prospects of CAMM in immunoassay development were also discussed.

Experimental and molecular docking studies on DNA binding interaction of adefovir dipivoxil: advances toward treatment of hepatitis B virus infections.

PubMed

Shahabadi, Nahid; Falsafi, Monireh

2014-05-05

The toxic interaction of adefovir dipivoxil with calf thymus DNA (CT-DNA) was investigated in vitro under simulated physiological conditions by multi-spectroscopic techniques and molecular modeling study. The fluorescence spectroscopy and UV absorption spectroscopy indicated drug interacted with CT-DNA in a groove binding mode. The binding constant of UV-visible and the number of binding sites were 3.33±0.2×10(4) L mol(-1)and 0.99, respectively. The fluorimetric studies showed that the reaction between the drug and CT-DNA is exothermic (ΔH=34.4 kJ mol(-1); ΔS=184.32 J mol(-1) K(-1)). Circular dichroism spectroscopy (CD) was employed to measure the conformational change of CT-DNA in the presence of adefovir dipivoxil, which verified the groove binding mode. Furthermore, the drug induces detectable changes in its viscosity. The molecular modeling results illustrated that adefovir strongly binds to groove of DNA by relative binding energy of docked structure -16.83 kJ mol(-1). This combination of multiple spectroscopic techniques and molecular modeling methods can be widely used in the investigation on the toxic interaction of small molecular pollutants and drugs with bio macromolecules, which contributes to clarify the molecular mechanism of toxicity or side effect in vivo. Copyright © 2014 Elsevier B.V. All rights reserved.

Computer simulation of surface and film processes

NASA Technical Reports Server (NTRS)

Tiller, W. A.; Halicioglu, M. T.

1984-01-01

All the investigations which were performed employed in one way or another a computer simulation technique based on atomistic level considerations. In general, three types of simulation methods were used for modeling systems with discrete particles that interact via well defined potential functions: molecular dynamics (a general method for solving the classical equations of motion of a model system); Monte Carlo (the use of Markov chain ensemble averaging technique to model equilibrium properties of a system); and molecular statics (provides properties of a system at T = 0 K). The effects of three-body forces on the vibrational frequencies of triatomic cluster were investigated. The multilayer relaxation phenomena for low index planes of an fcc crystal was analyzed also as a function of the three-body interactions. Various surface properties for Si and SiC system were calculated. Results obtained from static simulation calculations for slip formation were presented. The more elaborate molecular dynamics calculations on the propagation of cracks in two-dimensional systems were outlined.

Computer aided drug design

NASA Astrophysics Data System (ADS)

Jain, A.

2017-08-01

Computer based method can help in discovery of leads and can potentially eliminate chemical synthesis and screening of many irrelevant compounds, and in this way, it save time as well as cost. Molecular modeling systems are powerful tools for building, visualizing, analyzing and storing models of complex molecular structure that can help to interpretate structure activity relationship. The use of various techniques of molecular mechanics and dynamics and software in Computer aided drug design along with statistics analysis is powerful tool for the medicinal chemistry to synthesis therapeutic and effective drugs with minimum side effect.

Design of Novel Chemotherapeutic Agents Targeting Checkpoint Kinase 1 Using 3D-QSAR Modeling and Molecular Docking Methods.

PubMed

Balupuri, Anand; Balasubramanian, Pavithra K; Cho, Seung J

2016-01-01

Checkpoint kinase 1 (Chk1) has emerged as a potential therapeutic target for design and development of novel anticancer drugs. Herein, we have performed three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses on a series of diazacarbazoles to design potent Chk1 inhibitors. 3D-QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Docking studies were performed using AutoDock. The best CoMFA and CoMSIA models exhibited cross-validated correlation coefficient (q2) values of 0.631 and 0.585, and non-cross-validated correlation coefficient (r2) values of 0.933 and 0.900, respectively. CoMFA and CoMSIA models showed reasonable external predictabilities (r2 pred) of 0.672 and 0.513, respectively. A satisfactory performance in the various internal and external validation techniques indicated the reliability and robustness of the best model. Docking studies were performed to explore the binding mode of inhibitors inside the active site of Chk1. Molecular docking revealed that hydrogen bond interactions with Lys38, Glu85 and Cys87 are essential for Chk1 inhibitory activity. The binding interaction patterns observed during docking studies were complementary to 3D-QSAR results. Information obtained from the contour map analysis was utilized to design novel potent Chk1 inhibitors. Their activities and binding affinities were predicted using the derived model and docking studies. Designed inhibitors were proposed as potential candidates for experimental synthesis.

Temperature dependent effective potential method for accurate free energy calculations of solids

NASA Astrophysics Data System (ADS)

Hellman, Olle; Steneteg, Peter; Abrikosov, I. A.; Simak, S. I.

2013-03-01

We have developed a thorough and accurate method of determining anharmonic free energies, the temperature dependent effective potential technique (TDEP). It is based on ab initio molecular dynamics followed by a mapping onto a model Hamiltonian that describes the lattice dynamics. The formalism and the numerical aspects of the technique are described in detail. A number of practical examples are given, and results are presented, which confirm the usefulness of TDEP within ab initio and classical molecular dynamics frameworks. In particular, we examine from first principles the behavior of force constants upon the dynamical stabilization of the body centered phase of Zr, and show that they become more localized. We also calculate the phase diagram for 4He modeled with the Aziz potential and obtain results which are in favorable agreement both with respect to experiment and established techniques.

Molecular environmental geochemistry

NASA Astrophysics Data System (ADS)

O'Day, Peggy A.

1999-05-01

The chemistry, mobility, and bioavailability of contaminant species in the natural environment are controlled by reactions that occur in and among solid, aqueous, and gas phases. These reactions are varied and complex, involving changes in chemical form and mass transfer among inorganic, organic, and biochemical species. The field of molecular environmental geochemistry seeks to apply spectroscopic and microscopic probes to the mechanistic understanding of environmentally relevant chemical processes, particularly those involving contaminants and Earth materials. In general, empirical geochemical models have been shown to lack uniqueness and adequate predictive capability, even in relatively simple systems. Molecular geochemical tools, when coupled with macroscopic measurements, can provide the level of chemical detail required for the credible extrapolation of contaminant reactivity and bioavailability over ranges of temperature, pressure, and composition. This review focuses on recent advances in the understanding of molecular chemistry and reaction mechanisms at mineral surfaces and mineral-fluid interfaces spurred by the application of new spectroscopies and microscopies. These methods, such as synchrotron X-ray absorption and scattering techniques, vibrational and resonance spectroscopies, and scanning probe microscopies, provide direct chemical information that can elucidate molecular mechanisms, including element speciation, ligand coordination and oxidation state, structural arrangement and crystallinity on different scales, and physical morphology and topography of surfaces. Nonvacuum techniques that allow examination of reactions in situ (i.e., with water or fluids present) and in real time provide direct links between molecular structure and reactivity and measurements of kinetic rates or thermodynamic properties. Applications of these diverse probes to laboratory model systems have provided fundamental insight into inorganic and organic reactions at mineral surfaces and mineral-water interfaces. A review of recent studies employing molecular characterizations of soils, sediments, and biological samples from contaminated sites exemplifies the utility and benefits, as well as the challenge, of applying molecular probes to complicated natural materials. New techniques, technological advances, and the crossover of methods from other disciplines such as biochemistry and materials science promise better examination of environmental chemical processes in real time and at higher resolution, and will further the integration of molecular information into field-scale chemical and hydrologic models.

Molecular Modeling of a Probe in 2D IR Spectroscopy

NASA Astrophysics Data System (ADS)

Cooper, Anthony; Larini, Luca

Proteins must adopt a precise three dimensional structure in the folding process in order to perform its designated function. Although much has been learned about folding, there are still many details in structural dynamics that are difficult to characterize by existing experimental techniques. In order to overcome these challenges, novel infrared and fluorescent spectroscopic techniques have recently been employed to probe the molecular structure at the atomistic scale. These techniques rely on the spectroscopic properties of the nitrile group attached to a phenylalanine. In this study, we model this probe and we compute its properties in different solvents. This is done by performing Molecular Dynamics simulations with a PheCN solvated in water, urea and TMAO. We measure the decay rate of the vibrational stretching of the CN group in order to characterize the effects of different solvents on the local structure of the molecule. This data can be used to identify non-trivial conformational changes of the protein in the folding process. Preliminary results show agreement with current experimental data on 2D IR spectroscopy.

Assessment of Molecular Acoustic Angiography for Combined Microvascular and Molecular Imaging in Preclinical Tumor Models

PubMed Central

Lindsey, Brooks D.; Shelton, Sarah E.; Foster, F. Stuart; Dayton, Paul A.

2017-01-01

Purpose To evaluate a new ultrasound molecular imaging approach in its ability to image a preclinical tumor model and to investigate the capacity to visualize and quantify co-registered microvascular and molecular imaging volumes. Procedures Molecular imaging using the new technique was compared with a conventional ultrasound molecular imaging technique (multi-pulse imaging) by varying the injected microbubble dose and scanning each animal using both techniques. Each of the 14 animals was randomly assigned one of three doses; bolus dose was varied, and the animals were imaged for three consecutive days so that each animal received every dose. A microvascular scan was also acquired for each animal by administering an infusion of non-targeted microbubbles. These scans were paired with co-registered molecular images (VEGFR2-targeted microbubbles), the vessels were segmented, and the spatial relationships between vessels and VEGFR2 targeting locations were analyzed. In 5 animals, an additional scan was performed in which the animal received a bolus of microbubbles targeted to E- and P-selectin. Vessel tortuosity as a function of distance from VEGF and selectin targeting was analyzed in these animals. Results Although resulting differences in image intensity due to varying microbubble dose were not significant between the two lowest doses, superharmonic imaging had significantly higher contrast-to-tissue ratio (CTR) than multi-pulse imaging (mean across all doses: 13.98 dB for molecular acoustic angiography vs. 0.53 dB for multi-pulse imaging; p = 4.9 × 10−10). Analysis of registered microvascular and molecular imaging volumes indicated that vessel tortuosity decreases with increasing distance from both VEGFR2 and selectin targeting sites. Conclusions Molecular acoustic angiography (superharmonic molecular imaging) exhibited a significant increase in CTR at all doses tested due to superior rejection of tissue artifact signals. Due to the high resolution of acoustic angiography molecular imaging, it is possible to analyze spatial relationships in aligned microvascular and molecular superharmonic imaging volumes. Future studies are required to separate the effects of biomarker expression and blood flow kinetics in comparing local tortuosity differences between different endothelial markers such as VEGFR2, E-selectin and P-selectin. PMID:27519522

Computational Neuroscience.

ERIC Educational Resources Information Center

Sejnowski, Terrence J.; And Others

1988-01-01

Describes the use of brain models to connect the microscopic level accessible by molecular and cellular techniques with the systems level accessible by the study of behavior. Discusses classes of brain models, and specific examples of such models. Evaluates the strengths and weaknesses of using brain modelling to understand human brain function.…

Computer-aided design of polymers and composites

NASA Technical Reports Server (NTRS)

Kaelble, D. H.

1985-01-01

This book on computer-aided design of polymers and composites introduces and discusses the subject from the viewpoint of atomic and molecular models. Thus, the origins of stiffness, strength, extensibility, and fracture toughness in composite materials can be analyzed directly in terms of chemical composition and molecular structure. Aspects of polymer composite reliability are considered along with characterization techniques for composite reliability, relations between atomic and molecular properties, computer aided design and manufacture, polymer CAD/CAM models, and composite CAD/CAM models. Attention is given to multiphase structural adhesives, fibrous composite reliability, metal joint reliability, polymer physical states and transitions, chemical quality assurance, processability testing, cure monitoring and management, nondestructive evaluation (NDE), surface NDE, elementary properties, ionic-covalent bonding, molecular analysis, acid-base interactions, the manufacturing science, and peel mechanics.

Dynamic NMR Study of Model CMP Slurry Containing Silica Particles as Abrasives

NASA Astrophysics Data System (ADS)

Odeh, F.; Al-Bawab, A.; Li, Y.

2018-02-01

Chemical mechanical planarization (CMP) should provide a good surface planarity with minimal surface defectivity. Since CMP slurries are multi-component systems, it is very important to understand the various processes and interactions taking place in such slurries. Several techniques have been employed for such task, however, most of them lack the molecular recognition to investigate molecular interactions without adding probes which in turn increase complexity and might alter the microenvironment of the slurry. Nuclear magnetic resonance (NMR) is a powerful technique that can be employed in such study. The longitudinal relaxation times (T1) of the different components of CMP slurries were measured using Spin Echo-NMR (SE-NMR) at a constant temperature. The fact that NMR is non-invasive and gives information on the molecular level gives more advantage to the technique. The model CMP slurry was prepared in D2O to enable monitoring of T1 for the various components' protons. SE-NMR provide a very powerful tool to study the various interactions and adsorption processes that take place in a model CMP silica based slurry which contains BTA and/or glycine and/or Cu+2 ions. It was found that BTA is very competitive towards complexation with Cu+2 ions and BTA-Cu complex adsorbs on silica surface.

Modeling the chemistry of complex petroleum mixtures.

PubMed Central

Quann, R J

1998-01-01

Determining the complete molecular composition of petroleum and its refined products is not feasible with current analytical techniques because of the astronomical number of molecular components. Modeling the composition and behavior of such complex mixtures in refinery processes has accordingly evolved along a simplifying concept called lumping. Lumping reduces the complexity of the problem to a manageable form by grouping the entire set of molecular components into a handful of lumps. This traditional approach does not have a molecular basis and therefore excludes important aspects of process chemistry and molecular property fundamentals from the model's formulation. A new approach called structure-oriented lumping has been developed to model the composition and chemistry of complex mixtures at a molecular level. The central concept is to represent an individual molecular or a set of closely related isomers as a mathematical construct of certain specific and repeating structural groups. A complex mixture such as petroleum can then be represented as thousands of distinct molecular components, each having a mathematical identity. This enables the automated construction of large complex reaction networks with tens of thousands of specific reactions for simulating the chemistry of complex mixtures. Further, the method provides a convenient framework for incorporating molecular physical property correlations, existing group contribution methods, molecular thermodynamic properties, and the structure--activity relationships of chemical kinetics in the development of models. PMID:9860903

Free molecular collision cross section calculation methods for nanoparticles and complex ions with energy accommodation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larriba, Carlos, E-mail: clarriba@umn.edu; Hogan, Christopher J.

2013-10-15

The structures of nanoparticles, macromolecules, and molecular clusters in gas phase environments are often studied via measurement of collision cross sections. To directly compare structure models to measurements, it is hence necessary to have computational techniques available to calculate the collision cross sections of structural models under conditions matching measurements. However, presently available collision cross section methods contain the underlying assumption that collision between gas molecules and structures are completely elastic (gas molecule translational energy conserving) and specular, while experimental evidence suggests that in the most commonly used background gases for measurements, air and molecular nitrogen, gas molecule reemission ismore » largely inelastic (with exchange of energy between vibrational, rotational, and translational modes) and should be treated as diffuse in computations with fixed structural models. In this work, we describe computational techniques to predict the free molecular collision cross sections for fixed structural models of gas phase entities where inelastic and non-specular gas molecule reemission rules can be invoked, and the long range ion-induced dipole (polarization) potential between gas molecules and a charged entity can be considered. Specifically, two calculation procedures are described detail: a diffuse hard sphere scattering (DHSS) method, in which structures are modeled as hard spheres and collision cross sections are calculated for rectilinear trajectories of gas molecules, and a diffuse trajectory method (DTM), in which the assumption of rectilinear trajectories is relaxed and the ion-induced dipole potential is considered. Collision cross section calculations using the DHSS and DTM methods are performed on spheres, models of quasifractal aggregates of varying fractal dimension, and fullerene like structures. Techniques to accelerate DTM calculations by assessing the contribution of grazing gas molecule collisions (gas molecules with altered trajectories by the potential interaction) without tracking grazing trajectories are further discussed. The presented calculation techniques should enable more accurate collision cross section predictions under experimentally relevant conditions than pre-existing approaches, and should enhance the ability of collision cross section measurement schemes to discern the structures of gas phase entities.« less

Modeling Stochastic Kinetics of Molecular Machines at Multiple Levels: From Molecules to Modules

PubMed Central

Chowdhury, Debashish

2013-01-01

A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here. PMID:23746505

The dance of molecules: new dynamical perspectives on highly excited molecular vibrations.

PubMed

Kellman, Michael E; Tyng, Vivian

2007-04-01

At low energies, molecular vibrational motion is described by the normal modes model. This model breaks down at higher energy, with strong coupling between normal modes and onset of chaotic dynamics. New anharmonic modes are born in bifurcations, or branchings of the normal modes. Knowledge of these new modes is obtained through the window of frequency-domain spectroscopy, using techniques of nonlinear classical dynamics. It may soon be possible to "watch" molecular rearrangement reactions spectroscopically. Connections are being made with reaction rate theories, condensed phase systems, and motions of electrons in quantum dots.

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Computational studies of novel chymase inhibitors against cardiovascular and allergic diseases: mechanism and inhibition.

PubMed

Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong K; Lee, Keun W

2012-12-01

To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure-activity relationships models. Two models (genetic function approximation model 1 r(2) = 0.812 and genetic function approximation model 2 r(2) = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure-activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors. © 2012 John Wiley & Sons A/S.

Binding of fluorescent acridine dyes acridine orange and 9-aminoacridine to hemoglobin: Elucidation of their molecular recognition by spectroscopy, calorimetry and molecular modeling techniques.

PubMed

Chatterjee, Sabyasachi; Kumar, Gopinatha Suresh

2016-06-01

The molecular interaction between hemoglobin (HHb), the major human heme protein, and the acridine dyes acridine orange (AO) and 9-aminoacridine (9AA) was studied by various spectroscopic, calorimetric and molecular modeling techniques. The dyes formed stable ground state complex with HHb as revealed from spectroscopic data. Temperature dependent fluorescence data showed the strength of the dye-protein complexation to be inversely proportional to temperature and the fluorescence quenching was static in nature. The binding-induced conformational change in the protein was investigated using circular dichroism, synchronous fluorescence, 3D fluorescence and FTIR spectroscopy results. Circular dichroism data also quantified the α-helicity change in hemoglobin due to the binding of acridine dyes. Calorimetric studies revealed the binding to be endothermic in nature for both AO and 9AA, though the latter had higher affinity, and this was also observed from spectroscopic data. The binding of both dyes was entropy driven. pH dependent fluorescence studies revealed the existence of electrostatic interaction between the protein and dye molecules. Molecular modeling studies specified the binding site and the non-covalent interactions involved in the association. Overall, the results revealed that a small change in the acridine chromophore leads to remarkable alteration in the structural and thermodynamic aspects of binding to HHb. Copyright © 2016 Elsevier B.V. All rights reserved.

Molecular Simulation of the Phase Diagram of Methane Hydrate: Free Energy Calculations, Direct Coexistence Method, and Hyperparallel Tempering.

PubMed

Jin, Dongliang; Coasne, Benoit

2017-10-24

Different molecular simulation strategies are used to assess the stability of methane hydrate under various temperature and pressure conditions. First, using two water molecular models, free energy calculations consisting of the Einstein molecule approach in combination with semigrand Monte Carlo simulations are used to determine the pressure-temperature phase diagram of methane hydrate. With these calculations, we also estimate the chemical potentials of water and methane and methane occupancy at coexistence. Second, we also consider two other advanced molecular simulation techniques that allow probing the phase diagram of methane hydrate: the direct coexistence method in the Grand Canonical ensemble and the hyperparallel tempering Monte Carlo method. These two direct techniques are found to provide stability conditions that are consistent with the pressure-temperature phase diagram obtained using rigorous free energy calculations. The phase diagram obtained in this work, which is found to be consistent with previous simulation studies, is close to its experimental counterpart provided the TIP4P/Ice model is used to describe the water molecule.

Molecular Cardiac Surgery with Recirculating Delivery (MCARD): Procedure and Vector Transfer.

PubMed

Katz, Michael G; Fargnoli, Anthony S; Kendle, Andrew P; Bridges, Charles R

2017-01-01

Despite progress in clinical treatment, cardiovascular diseases are still the leading cause of morbidity and mortality worldwide. Therefore, novel therapeutic approaches are needed, targeting the underlying molecular mechanisms of disease with improved outcomes for patients. Gene therapy is one of the most promising fields for the development of new treatments for the advanced stages of cardiovascular diseases. The establishment of clinically relevant methods of gene transfer remains one of the principal limitations on the effectiveness of gene therapy. Recently, there have been significant advances in direct and transvascular gene delivery methods. The ideal gene transfer method should be explored in clinically relevant large animal models of heart disease to evaluate the roles of specific molecular pathways in disease pathogenesis. Characteristics of the optimal technique for gene delivery include low morbidity, an increased myocardial transcapillary gradient, esxtended vector residence time in the myocytes, and the exclusion of residual vector from the systemic circulation after delivery to minimize collateral expression and immune response. Here we describe myocardial gene transfer techniques with molecular cardiac surgery with recirculating delivery in a large animal model of post ischemic heart failure.

LAMMPS integrated materials engine (LIME) for efficient automation of particle-based simulations: application to equation of state generation

NASA Astrophysics Data System (ADS)

Barnes, Brian C.; Leiter, Kenneth W.; Becker, Richard; Knap, Jaroslaw; Brennan, John K.

2017-07-01

We describe the development, accuracy, and efficiency of an automation package for molecular simulation, the large-scale atomic/molecular massively parallel simulator (LAMMPS) integrated materials engine (LIME). Heuristics and algorithms employed for equation of state (EOS) calculation using a particle-based model of a molecular crystal, hexahydro-1,3,5-trinitro-s-triazine (RDX), are described in detail. The simulation method for the particle-based model is energy-conserving dissipative particle dynamics, but the techniques used in LIME are generally applicable to molecular dynamics simulations with a variety of particle-based models. The newly created tool set is tested through use of its EOS data in plate impact and Taylor anvil impact continuum simulations of solid RDX. The coarse-grain model results from LIME provide an approach to bridge the scales from atomistic simulations to continuum simulations.

On the computation of molecular surface correlations for protein docking using fourier techniques.

PubMed

Sakk, Eric

2007-08-01

The computation of surface correlations using a variety of molecular models has been applied to the unbound protein docking problem. Because of the computational complexity involved in examining all possible molecular orientations, the fast Fourier transform (FFT) (a fast numerical implementation of the discrete Fourier transform (DFT)) is generally applied to minimize the number of calculations. This approach is rooted in the convolution theorem which allows one to inverse transform the product of two DFTs in order to perform the correlation calculation. However, such a DFT calculation results in a cyclic or "circular" correlation which, in general, does not lead to the same result as the linear correlation desired for the docking problem. In this work, we provide computational bounds for constructing molecular models used in the molecular surface correlation problem. The derived bounds are then shown to be consistent with various intuitive guidelines previously reported in the protein docking literature. Finally, these bounds are applied to different molecular models in order to investigate their effect on the correlation calculation.

Fine- and hyperfine-structure effects in molecular photoionization. II. Resonance-enhanced multiphoton ionization and hyperfine-selective generation of molecular cations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Germann, Matthias; Willitsch, Stefan, E-mail: stefan.willitsch@unibas.ch

2016-07-28

Resonance-enhanced multiphoton ionization (REMPI) is a widely used technique for studying molecular photoionization and producing molecular cations for spectroscopy and dynamics studies. Here, we present a model for describing hyperfine-structure effects in the REMPI process and for predicting hyperfine populations in molecular ions produced by this method. This model is a generalization of our model for fine- and hyperfine-structure effects in one-photon ionization of molecules presented in Paper I [M. Germann and S. Willitsch, J. Chem. Phys. 145, 044314 (2016)]. This generalization is achieved by covering two main aspects: (1) treatment of the neutral bound-bound transition including the hyperfine structuremore » that makes up the first step of the REMPI process and (2) modification of our ionization model to account for anisotropic populations resulting from this first excitation step. Our findings may be used for analyzing results from experiments with molecular ions produced by REMPI and may serve as a theoretical background for hyperfine-selective ionization experiments.« less

A Comparative Study of YSO Classification Techniques using WISE Observations of the KR 120 Molecular Cloud

NASA Astrophysics Data System (ADS)

Kang, Sung-Ju; Kerton, C. R.

2014-01-01

KR 120 (Sh2-187) is a small Galactic HII region located at a distance of 1.4 kpc that shows evidence for triggered star formation in the surrounding molecular cloud. We present an analysis of the young stellar object (YSO) population of the molecular cloud as determined using a variety of classification techniques. YSO candidates are selected from the WISE all sky catalog and classified as Class I, Class II and Flat based on 1) spectral index, 2) color-color or color-magnitude plots, and 3) spectral energy distribution (SED) fits to radiative transfer models. We examine the discrepancies in YSO classification between the various techniques and explore how these discrepancies lead to uncertainty in such scientifically interesting quantities such as the ratio of Class I/Class II sources and the surface density of YSOs at various stages of evolution.

A multiscale simulation technique for molecular electronics: design of a directed self-assembled molecular n-bit shift register memory device.

PubMed

Lambropoulos, Nicholas A; Reimers, Jeffrey R; Crossley, Maxwell J; Hush, Noel S; Silverbrook, Kia

2013-12-20

A general method useful in molecular electronics design is developed that integrates modelling on the nano-scale (using quantum-chemical software) and on the micro-scale (using finite-element methods). It is applied to the design of an n-bit shift register memory that could conceivably be built using accessible technologies. To achieve this, the entire complex structure of the device would be built to atomic precision using feedback-controlled lithography to provide atomic-level control of silicon devices, controlled wet-chemical synthesis of molecular insulating pillars above the silicon, and controlled wet-chemical self-assembly of modular molecular devices to these pillars that connect to external metal electrodes (leads). The shift register consists of n connected cells that read data from an input electrode, pass it sequentially between the cells under the control of two external clock electrodes, and deliver it finally to an output device. The proposed cells are trimeric oligoporphyrin units whose internal states are manipulated to provide functionality, covalently connected to other cells via dipeptide linkages. Signals from the clock electrodes are conveyed by oligoporphyrin molecular wires, and μ-oxo porphyrin insulating columns are used as the supporting pillars. The developed multiscale modelling technique is applied to determine the characteristics of this molecular device, with in particular utilization of the inverted region for molecular electron-transfer processes shown to facilitate latching and control using exceptionally low energy costs per logic operation compared to standard CMOS shift register technology.

A multiscale simulation technique for molecular electronics: design of a directed self-assembled molecular n-bit shift register memory device

NASA Astrophysics Data System (ADS)

Lambropoulos, Nicholas A.; Reimers, Jeffrey R.; Crossley, Maxwell J.; Hush, Noel S.; Silverbrook, Kia

2013-12-01

A general method useful in molecular electronics design is developed that integrates modelling on the nano-scale (using quantum-chemical software) and on the micro-scale (using finite-element methods). It is applied to the design of an n-bit shift register memory that could conceivably be built using accessible technologies. To achieve this, the entire complex structure of the device would be built to atomic precision using feedback-controlled lithography to provide atomic-level control of silicon devices, controlled wet-chemical synthesis of molecular insulating pillars above the silicon, and controlled wet-chemical self-assembly of modular molecular devices to these pillars that connect to external metal electrodes (leads). The shift register consists of n connected cells that read data from an input electrode, pass it sequentially between the cells under the control of two external clock electrodes, and deliver it finally to an output device. The proposed cells are trimeric oligoporphyrin units whose internal states are manipulated to provide functionality, covalently connected to other cells via dipeptide linkages. Signals from the clock electrodes are conveyed by oligoporphyrin molecular wires, and μ-oxo porphyrin insulating columns are used as the supporting pillars. The developed multiscale modelling technique is applied to determine the characteristics of this molecular device, with in particular utilization of the inverted region for molecular electron-transfer processes shown to facilitate latching and control using exceptionally low energy costs per logic operation compared to standard CMOS shift register technology.

Molecular orientation in a dielectric liquid-vapor interphase

NASA Astrophysics Data System (ADS)

Chacón, E.; Mederos, L.; Navascués, G.; Tarazona, P.

1985-04-01

The density functional theory of Chacón et al. is used to study the molecular orientation in an interphase of a weak dipolar fluid. Explicit expressions are obtained using standard perturbation techniques. Molecular orientation, local susceptibility, and the Gibbsean surface susceptibility are evaluated for a Stockmayer model of dipolar fluid. The effect of the surface structure on the bulk ferroelectric transition is discussed in the light of the present theory and the numerical results.

Challenges and Advances for Genetic Engineering of Non-model Bacteria and Uses in Consolidated Bioprocessing

PubMed Central

Yan, Qiang; Fong, Stephen S.

2017-01-01

Metabolic diversity in microorganisms can provide the basis for creating novel biochemical products. However, most metabolic engineering projects utilize a handful of established model organisms and thus, a challenge for harnessing the potential of novel microbial functions is the ability to either heterologously express novel genes or directly utilize non-model organisms. Genetic manipulation of non-model microorganisms is still challenging due to organism-specific nuances that hinder universal molecular genetic tools and translatable knowledge of intracellular biochemical pathways and regulatory mechanisms. However, in the past several years, unprecedented progress has been made in synthetic biology, molecular genetics tools development, applications of omics data techniques, and computational tools that can aid in developing non-model hosts in a systematic manner. In this review, we focus on concerns and approaches related to working with non-model microorganisms including developing molecular genetics tools such as shuttle vectors, selectable markers, and expression systems. In addition, we will discuss: (1) current techniques in controlling gene expression (transcriptional/translational level), (2) advances in site-specific genome engineering tools [homologous recombination (HR) and clustered regularly interspaced short palindromic repeats (CRISPR)], and (3) advances in genome-scale metabolic models (GSMMs) in guiding design of non-model species. Application of these principles to metabolic engineering strategies for consolidated bioprocessing (CBP) will be discussed along with some brief comments on foreseeable future prospects. PMID:29123506

MULTI: a shared memory approach to cooperative molecular modeling.

PubMed

Darden, T; Johnson, P; Smith, H

1991-03-01

A general purpose molecular modeling system, MULTI, based on the UNIX shared memory and semaphore facilities for interprocess communication is described. In addition to the normal querying or monitoring of geometric data, MULTI also provides processes for manipulating conformations, and for displaying peptide or nucleic acid ribbons, Connolly surfaces, close nonbonded contacts, crystal-symmetry related images, least-squares superpositions, and so forth. This paper outlines the basic techniques used in MULTI to ensure cooperation among these specialized processes, and then describes how they can work together to provide a flexible modeling environment.

An Insilico Design of Nanoclay Based Nanocomposites and Scaffolds in Bone Tissue Engineering

NASA Astrophysics Data System (ADS)

Sharma, Anurag

A multiscale in silico approach to design polymer nanocomposites and scaffolds for bone tissue engineering applications is described in this study. This study focuses on the role of biomaterials design and selection, structural integrity and mechanical properties evolution during degradation and tissue regeneration in the successful design of polymer nanocomposite scaffolds. Polymer nanocomposite scaffolds are synthesized using aminoacid modified montmorillonite nanoclay with biomineralized hydroxyapatite and polycaprolactone (PCL/in situ HAPclay). Representative molecular models of polymer nanocomposite system are systematically developed using molecular dynamics (MD) technique and successfully validated using material characterization techniques. The constant force steered molecular dynamics (fSMD) simulation results indicate a two-phase nanomechanical behavior of the polymer nanocomposite. The MD and fSMD simulations results provide quantitative contributions of molecular interactions between different constituents of representative models and their effect on nanomechanical responses of nanoclay based polymer nanocomposite system. A finite element (FE) model of PCL/in situ HAPclay scaffold is built using micro-computed tomography images and bridging the nanomechanical properties obtained from fSMD simulations into the FE model. A new reduction factor, K is introduced into modeling results to consider the effect of wall porosity of the polymer scaffold. The effect of accelerated degradation under alkaline conditions and human osteoblast cells culture on the evolution of mechanical properties of scaffolds are studied and the damage mechanics based analytical models are developed. Finally, the novel multiscale models are developed that incorporate the complex molecular and microstructural properties, mechanical properties at nanoscale and structural levels and mechanical properties evolution during degradation and tissue formation in the polymer nanocomposite scaffold. Overall, this study provides a leap into methodologies for in silico design of biomaterials for bone tissue engineering applications. Furthermore, as a part of this work, a molecular dynamics study of rice DNA in the presence of single walled carbon nanotube is carried out to understand the role played by molecular interactions in the conformation changes of rice DNA. The simulations results showed wrapping of DNA onto SWCNT, breaking and forming of hydrogen bonds due to unzipping of Watson-Crick (WC) nucleobase pairs and forming of new non-WC nucleobase pairs in DNA.

Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools.

PubMed

Price, Jeffrey H; Goodacre, Angela; Hahn, Klaus; Hodgson, Louis; Hunter, Edward A; Krajewski, Stanislaw; Murphy, Robert F; Rabinovich, Andrew; Reed, John C; Heynen, Susanne

2002-01-01

Cellular behavior is complex. Successfully understanding systems at ever-increasing complexity is fundamental to advances in modern science and unraveling the functional details of cellular behavior is no exception. We present a collection of prospectives to provide a glimpse of the techniques that will aid in collecting, managing and utilizing information on complex cellular processes via molecular imaging tools. These include: 1) visualizing intracellular protein activity with fluorescent markers, 2) high throughput (and automated) imaging of multilabeled cells in statistically significant numbers, and 3) machine intelligence to analyze subcellular image localization and pattern. Although not addressed here, the importance of combining cell-image-based information with detailed molecular structure and ligand-receptor binding models cannot be overlooked. Advanced molecular imaging techniques have the potential to impact cellular diagnostics for cancer screening, clinical correlations of tissue molecular patterns for cancer biology, and cellular molecular interactions for accelerating drug discovery. The goal of finally understanding all cellular components and behaviors will be achieved by advances in both instrumentation engineering (software and hardware) and molecular biochemistry. Copyright 2002 Wiley-Liss, Inc.

Molecular dynamics-based model of VEGF-A and its heparin interactions.

PubMed

Uciechowska-Kaczmarzyk, Urszula; Babik, Sándor; Zsila, Ferenc; Bojarski, Krzysztof Kamil; Beke-Somfai, Tamás; Samsonov, Sergey A

2018-06-01

We present a computational model of the Vascular Endothelial Growth Factor (VEGF), an important regulator of blood vessels formation, which function is affected by its heparin interactions. Although structures of a receptor binding (RBD) and a heparin binding domain (HBD) of VEGF are known, there are structural data neither on the 12 amino acids interdomain linker nor on its complexes with heparin. We apply molecular docking and molecular dynamics techniques combined with circular dichroism spectroscopy to model the full structure of the dimeric VEGF and to propose putative molecular mechanisms underlying the function of VEGF/VEGF receptors/heparin system. We show that both the conformational flexibility of the linker and the formation of HBD-heparin-HBD sandwich-like structures regulate the mutual disposition of HBDs and so affect the VEGF-mediated signalling. Copyright © 2018 Elsevier Inc. All rights reserved.

Ordinary differential equations with applications in molecular biology.

PubMed

Ilea, M; Turnea, M; Rotariu, M

2012-01-01

Differential equations are of basic importance in molecular biology mathematics because many biological laws and relations appear mathematically in the form of a differential equation. In this article we presented some applications of mathematical models represented by ordinary differential equations in molecular biology. The vast majority of quantitative models in cell and molecular biology are formulated in terms of ordinary differential equations for the time evolution of concentrations of molecular species. Assuming that the diffusion in the cell is high enough to make the spatial distribution of molecules homogenous, these equations describe systems with many participating molecules of each kind. We propose an original mathematical model with small parameter for biological phospholipid pathway. All the equations system includes small parameter epsilon. The smallness of epsilon is relative to the size of the solution domain. If we reduce the size of the solution region the same small epsilon will result in a different condition number. It is clear that the solution for a smaller region is less difficult. We introduce the mathematical technique known as boundary function method for singular perturbation system. In this system, the small parameter is an asymptotic variable, different from the independent variable. In general, the solutions of such equations exhibit multiscale phenomena. Singularly perturbed problems form a special class of problems containing a small parameter which may tend to zero. Many molecular biology processes can be quantitatively characterized by ordinary differential equations. Mathematical cell biology is a very active and fast growing interdisciplinary area in which mathematical concepts, techniques, and models are applied to a variety of problems in developmental medicine and bioengineering. Among the different modeling approaches, ordinary differential equations (ODE) are particularly important and have led to significant advances. Ordinary differential equations are used to model biological processes on various levels ranging from DNA molecules or biosynthesis phospholipids on the cellular level.

Influence of macromolecular architecture on necking in polymer extrusion film casting process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pol, Harshawardhan; Banik, Sourya; Azad, Lal Busher

2015-05-22

Extrusion film casting (EFC) is an important polymer processing technique that is used to produce several thousand tons of polymer films/coatings on an industrial scale. In this research, we are interested in understanding quantitatively how macromolecular chain architecture (for example long chain branching (LCB) or molecular weight distribution (MWD or PDI)) influences the necking and thickness distribution of extrusion cast films. We have used different polymer resins of linear and branched molecular architecture to produce extrusion cast films under controlled experimental conditions. The necking profiles of the films were imaged and the velocity profiles during EFC were monitored using particlemore » tracking velocimetry (PTV) technique. Additionally, the temperature profiles were captured using an IR thermography and thickness profiles were calculated. The experimental results are compared with predictions of one-dimensional flow model of Silagy et al{sup 1} wherein the polymer resin rheology is modeled using molecular constitutive equations such as the Rolie-Poly (RP) and extended Pom Pom (XPP). We demonstrate that the 1-D flow model containing the molecular constitutive equations provides new insights into the role of macromolecular chain architecture on film necking.{sup 1}D. Silagy, Y. Demay, and J-F. Agassant, Polym. Eng. Sci., 36, 2614 (1996)« less

Visibility Equalizer Cutaway Visualization of Mesoscopic Biological Models.

PubMed

Le Muzic, M; Mindek, P; Sorger, J; Autin, L; Goodsell, D; Viola, I

2016-06-01

In scientific illustrations and visualization, cutaway views are often employed as an effective technique for occlusion management in densely packed scenes. We propose a novel method for authoring cutaway illustrations of mesoscopic biological models. In contrast to the existing cutaway algorithms, we take advantage of the specific nature of the biological models. These models consist of thousands of instances with a comparably smaller number of different types. Our method constitutes a two stage process. In the first step, clipping objects are placed in the scene, creating a cutaway visualization of the model. During this process, a hierarchical list of stacked bars inform the user about the instance visibility distribution of each individual molecular type in the scene. In the second step, the visibility of each molecular type is fine-tuned through these bars, which at this point act as interactive visibility equalizers. An evaluation of our technique with domain experts confirmed that our equalizer-based approach for visibility specification was valuable and effective for both, scientific and educational purposes.

Visibility Equalizer Cutaway Visualization of Mesoscopic Biological Models

PubMed Central

Le Muzic, M.; Mindek, P.; Sorger, J.; Autin, L.; Goodsell, D.; Viola, I.

2017-01-01

In scientific illustrations and visualization, cutaway views are often employed as an effective technique for occlusion management in densely packed scenes. We propose a novel method for authoring cutaway illustrations of mesoscopic biological models. In contrast to the existing cutaway algorithms, we take advantage of the specific nature of the biological models. These models consist of thousands of instances with a comparably smaller number of different types. Our method constitutes a two stage process. In the first step, clipping objects are placed in the scene, creating a cutaway visualization of the model. During this process, a hierarchical list of stacked bars inform the user about the instance visibility distribution of each individual molecular type in the scene. In the second step, the visibility of each molecular type is fine-tuned through these bars, which at this point act as interactive visibility equalizers. An evaluation of our technique with domain experts confirmed that our equalizer-based approach for visibility specification was valuable and effective for both, scientific and educational purposes. PMID:28344374

Modeling and Deorphanization of Orphan GPCRs.

PubMed

Diaz, Constantino; Angelloz-Nicoud, Patricia; Pihan, Emilie

2018-01-01

Despite tremendous efforts, approximately 120 GPCRs remain orphan. Their physiological functions and their potential roles in diseases are poorly understood. Orphan GPCRs are extremely important because they may provide novel therapeutic targets for unmet medical needs. As a complement to experimental approaches, molecular modeling and virtual screening are efficient techniques to discover synthetic surrogate ligands which can help to elucidate the role of oGPCRs. Constitutively activated mutants and recently published active structures of GPCRs provide stimulating opportunities for building active molecular models for oGPCRs and identifying activators using virtual screening of compound libraries. We describe the molecular modeling and virtual screening process we have applied in the discovery of surrogate ligands, and provide examples for CCKA, a simulated oGPCR, and for two oGPCRs, GPR52 and GPR34.

Special conference of the American Association for Cancer Research on molecular imaging in cancer: linking biology, function, and clinical applications in vivo.

PubMed

Luker, Gary D

2002-04-01

The AACR Special Conference on Molecular Imaging in Cancer: Linking Biology, Function, and Clinical Applications In Vivo, was held January 23-27, 2002, at the Contemporary Hotel, Walt Disney World, Orlando, FL. Co-Chairs David Piwnica-Worms, Patricia Price and Thomas Meade brought together researchers with diverse expertise in molecular biology, gene therapy, chemistry, engineering, pharmacology, and imaging to accelerate progress in developing and applying technologies for imaging specific cellular and molecular signals in living animals and humans. The format of the conference was the presentation of research that focused on basic and translational biology of cancer and current state-of-the-art techniques for molecular imaging in animal models and humans. This report summarizes the special conference on molecular imaging, highlighting the interfaces of molecular biology with animal models, instrumentation, chemistry, and pharmacology that are essential to convert the dreams and promise of molecular imaging into improved understanding, diagnosis, and management of cancer.

Phase computations and phase models for discrete molecular oscillators.

PubMed

Suvak, Onder; Demir, Alper

2012-06-11

Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations.

Phase computations and phase models for discrete molecular oscillators

PubMed Central

2012-01-01

Background Biochemical oscillators perform crucial functions in cells, e.g., they set up circadian clocks. The dynamical behavior of oscillators is best described and analyzed in terms of the scalar quantity, phase. A rigorous and useful definition for phase is based on the so-called isochrons of oscillators. Phase computation techniques for continuous oscillators that are based on isochrons have been used for characterizing the behavior of various types of oscillators under the influence of perturbations such as noise. Results In this article, we extend the applicability of these phase computation methods to biochemical oscillators as discrete molecular systems, upon the information obtained from a continuous-state approximation of such oscillators. In particular, we describe techniques for computing the instantaneous phase of discrete, molecular oscillators for stochastic simulation algorithm generated sample paths. We comment on the accuracies and derive certain measures for assessing the feasibilities of the proposed phase computation methods. Phase computation experiments on the sample paths of well-known biological oscillators validate our analyses. Conclusions The impact of noise that arises from the discrete and random nature of the mechanisms that make up molecular oscillators can be characterized based on the phase computation techniques proposed in this article. The concept of isochrons is the natural choice upon which the phase notion of oscillators can be founded. The isochron-theoretic phase computation methods that we propose can be applied to discrete molecular oscillators of any dimension, provided that the oscillatory behavior observed in discrete-state does not vanish in a continuous-state approximation. Analysis of the full versatility of phase noise phenomena in molecular oscillators will be possible if a proper phase model theory is developed, without resorting to such approximations. PMID:22687330

Photoacoustic and luminescence spectroscopy of benzil crystals

NASA Astrophysics Data System (ADS)

Bonno, B.; Laporte, J. L.; Rousset, Y.

1991-06-01

In the present work, both photoacoustic and luminescence techniques were employed to study molecular crystals. This paper presents an extension of the standard Rosencwaig-Gersho photoacoustic model to molecular crystals, which includes finite-deexcitation-time effects and excited-state populations. In the temperature range 100-300 K, the phosphorescence quantum yield and thermal diffusivity of benzil crystals were determined.

CAMD studies of coal structure and coal liquefaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faulon, J.L.; Carlson, G.A.

The macromolecular structure of coal is essential to understand the mechanisms occurring during coal liquefaction. Many attempts to model coal structure can be found in the literature. More specifically for high volatile bituminous coal, the subject of interest the most commonly quoted models are the models of Given, Wiser, Solomon, and Shinn. In past work, the authors`s have used computer-aided molecular design (CAMD) to develop three-dimensional representations for the above coal models. The three-dimensional structures were energy minimized using molecular mechanics and molecular dynamics. True density and micopore volume were evaluated for each model. With the exception of Given`s model,more » the computed density values were found to be in agreement with the corresponding experimental results. The above coal models were constructed by a trial and error technique consisting of a manual fitting of the-analytical data. It is obvious that for each model the amount of data is small compared to the actual complexity of coal, and for all of the models more than one structure can be built. Hence, the process by which one structure is chosen instead of another is not clear. In fact, all the authors agree that the structure they derived was only intended to represent an {open_quotes}average{close_quotes} coal model rather than a unique correct structure. The purpose of this program is further develop CAMD techniques to increase the understanding of coal structure and its relationship to coal liquefaction.« less

Modeling stochastic kinetics of molecular machines at multiple levels: from molecules to modules.

PubMed

Chowdhury, Debashish

2013-06-04

A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Collisional excitation of molecules in dense interstellar clouds

NASA Technical Reports Server (NTRS)

Green, S.

1985-01-01

State transitions which permit the identification of the molecular species in dense interstellar clouds are reviewed, along with the techniques used to calculate the transition energies, the database on known molecular transitions and the accuracy of the values. The transition energies cannot be measured directly and therefore must be modeled analytically. Scattering theory is used to determine the intermolecular forces on the basis of quantum mechanics. The nuclear motions can also be modeled with classical mechanics. Sample rate constants are provided for molecular systems known to inhabit dense interstellar clouds. The values serve as a database for interpreting microwave and RF astrophysical data on the transitions undergone by interstellar molecules.

Studies of the interaction between FNC and human hemoglobin: a spectroscopic analysis and molecular docking.

PubMed

Li, Huiyi; Dou, Huanjing; Zhang, Yuhai; Li, Zhigang; Wang, Ruiyong; Chang, Junbiao

2015-02-05

FNC (2'-deoxy-2'-bfluoro-4'-azidocytidine) is a novel nucleoside analogue with pharmacologic effects on several human diseases. In this work, the binding of FNC to human hemoglobin (HHb) have been investigated by absorption spectroscopy, fluorescence quenching technique, synchronous fluorescence, three-dimensional fluorescence and molecular modeling methods. Analysis of fluorescence data showed that the binding of FNC to HHb occurred via a static quenching mechanism. Thermodynamic analysis and molecular modeling suggest that hydrogen bond and van der Waals force are the mainly binding force in the binding of FNC to HHb. Copyright © 2014 Elsevier B.V. All rights reserved.

Structure and Dynamics of End-to-End Loop Formation of the Penta-Peptide Cys-Ala-Gly-Gln-Trp in Implicit Solvents

DTIC Science & Technology

2009-01-01

implicit solvents on peptide structure and dynamics , we performed extensive molecular dynamics simulations on the penta-peptide Cys-Ala-Gly-Gln-Trp. Two...end-to-end distances and dihedral angles obtained from molecular dynamics simulations with implicit solvent models were in a good agreement with those...to maintain the temperature of the systems. Introduction Molecular dynamics (MD) simulation techniques are widely used to study structure and

Vibrational cross-angles in condensed molecules: a structural tool.

PubMed

Chen, Hailong; Zhang, Yufan; Li, Jiebo; Liu, Hongjun; Jiang, De-En; Zheng, Junrong

2013-09-05

The fluctuations of three-dimensional molecular conformations of a molecule in different environments play critical roles in many important chemical and biological processes. X-ray diffraction (XRD) techniques and nuclear magnetic resonance (NMR) methods are routinely applied to monitor the molecular conformations in condensed phases. However, some special requirements of the methods have prevented them from exploring many molecular phenomena at the current stage. Here, we introduce another method to resolve molecular conformations based on an ultrafast MIR/T-Hz multiple-dimensional vibrational spectroscopic technique. The model molecule (4'-methyl-2'-nitroacetanilide, MNA) is prepared in two of its crystalline forms and liquid samples. Two polarized ultrafast infrared pulses are then used to determine the cross-angles of vibrational transition moment directions by exciting one vibrational band and detecting the induced response on another vibrational band of the molecule. The vibrational cross-angles are then converted into molecular conformations with the aid of calculations. The molecular conformations determined by the method are supported by X-ray diffraction and molecular dynamics simulation results. The experimental results suggest that thermodynamic interactions with solvent molecules are not altering the molecular conformations of MNA in the solutions to control their ultimate conformations in the crystals.

Constructing Cross-Linked Polymer Networks Using Monte Carlo Simulated Annealing Technique for Atomistic Molecular Simulations

DTIC Science & Technology

2014-10-01

the angles and dihedrals that are truly unique will be indicated by the user by editing NewAngleTypesDump and NewDihedralTypesDump. The program ...Atomistic Molecular Simulations 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Robert M Elder, Timothy W Sirk, and...Antechamber program in Assisted Model Building with Energy Refinement (AMBER) Tools to assign partial charges (using the Austin Model 1 [AM1]-bond charge

Uncertainties in Atomic Data and Their Propagation Through Spectral Models. I.

NASA Technical Reports Server (NTRS)

Bautista, M. A.; Fivet, V.; Quinet, P.; Dunn, J.; Gull, T. R.; Kallman, T. R.; Mendoza, C.

2013-01-01

We present a method for computing uncertainties in spectral models, i.e., level populations, line emissivities, and emission line ratios, based upon the propagation of uncertainties originating from atomic data.We provide analytic expressions, in the form of linear sets of algebraic equations, for the coupled uncertainties among all levels. These equations can be solved efficiently for any set of physical conditions and uncertainties in the atomic data. We illustrate our method applied to spectral models of Oiii and Fe ii and discuss the impact of the uncertainties on atomic systems under different physical conditions. As to intrinsic uncertainties in theoretical atomic data, we propose that these uncertainties can be estimated from the dispersion in the results from various independent calculations. This technique provides excellent results for the uncertainties in A-values of forbidden transitions in [Fe ii]. Key words: atomic data - atomic processes - line: formation - methods: data analysis - molecular data - molecular processes - techniques: spectroscopic

Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible?

PubMed

Knapp, B; Frantal, S; Cibena, M; Schreiner, W; Bauer, P

2011-08-01

Molecular dynamics is a commonly used technique in computational biology. One key issue of each molecular dynamics simulation is: When does this simulation reach equilibrium state? A widely used way to determine this is the visual and intuitive inspection of root mean square deviation (RMSD) plots of the simulation. Although this technique has been criticized several times, it is still often used. Therefore, we present a study proving that this method is not reliable at all. We conducted a survey with participants from the field in which we illustrated different RMSD plots to scientists in the field of molecular dynamics. These plots were randomized and repeated, using a statistical model and different variants of the plots. We show that there is no mutual consent about the point of equilibrium. The decisions are severely biased by different parameters. Therefore, we conclude that scientists should not discuss the equilibration of a molecular dynamics simulation on the basis of a RMSD plot.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henderson, Michael A.; Lyubinetsky, Igor

The field of heterogeneous photocatalysis has grown considerably in the decades since Fujishima and Honda's ground-breaking publications of photoelectrochemistry on TiO2. Numerous review articles continue to point to both progress made in the use of heterogeneous materials (such as TiO2) to perform photoconversion processes, and the many opportunities and challenges in heterogeneous photocatalysis research such as solar energy conversion and environmental remediation. The past decade has also seen an increase in the use of molecular-level approaches applied to model single crystal surfaces in an effort to obtain new insights into photocatalytic phenomena. In particular, scanning probe techniques (SPM) have enabledmore » researchers to take a ‘nanoscale’ approach to photocatalysis that includes interrogation of the reactivities of specific sites and adsorbates on a model photocatalyst surface. The rutile TiO2(110) surface has become the prototypical oxide single crystal surface for fundamental studies of many interfacial phenomena. In particular, TiO2(110) has become an excellent model surface for probing photochemical and photocatalytic reactions at the molecular level. A variety of experimental approaches have emerged as being ideally suited for studying photochemical reactions on TiO2(110), including desorption-oriented approaches and electronic spectroscopies, but perhaps the most promising techniques for evaluating site-specific properties are those of SPM. In this review, we highlight the growing use of SPM techniques in providing molecular-level insights into surface photochemistry on the model photocatalyst surface of rutile TiO2(110). Our objective is to both illustrate the unique knowledge that scanning probe techniques have already provided the field of photocatalysis, and also to motivate a new generation of effort into the use of such approaches to obtain new insights into the molecular level details of photochemical events occurring at interfaces. Discussion will start with an examination of how scanning probe techniques are being used to characterize the TiO2(110) surface in ways that are relevant to photocatalysis. We will then discuss specific classes of photochemical reaction on TiO2(110) for which SPM has proven indispensible in providing unique molecular-level insights, and conclude with discussion of future areas in which SPM studies may prove valuable to photocatalysis on TiO2. This work was supported by the US Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. I.L. was partially supported by a Pacific Northwest National Laboratory (PNNL) Chemical Imaging Initiative project. PNNL is a multiprogram national laboratory operated for DOE by Battelle.« less

Correction for intravascular activity in the oxygen-15 steady-state technique is independent of the regional hematocrit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lammertsma, A.A.; Baron, J.C.; Jones, T.

1987-06-01

The oxygen-15 steady-state technique to measure the regional cerebral metabolic rate for oxygen requires a correction for the nonextracted intravascular molecular oxygen-15. To perform this correction, an additional procedure is carried out using RBCs labeled with /sup 11/CO or C/sup 15/O. The previously reported correction method, however, required knowledge of the regional cerebral to large vessel hematocrit ratio. A closer examination of the underlying model eliminated this ratio. Both molecular oxygen and carbon monoxide are carried by RBCs and are therefore similarly affected by a change in hematocrit.

First principle chemical kinetics in zeolites: the methanol-to-olefin process as a case study.

PubMed

Van Speybroeck, Veronique; De Wispelaere, Kristof; Van der Mynsbrugge, Jeroen; Vandichel, Matthias; Hemelsoet, Karen; Waroquier, Michel

2014-11-07

To optimally design next generation catalysts a thorough understanding of the chemical phenomena at the molecular scale is a prerequisite. Apart from qualitative knowledge on the reaction mechanism, it is also essential to be able to predict accurate rate constants. Molecular modeling has become a ubiquitous tool within the field of heterogeneous catalysis. Herein, we review current computational procedures to determine chemical kinetics from first principles, thus by using no experimental input and by modeling the catalyst and reacting species at the molecular level. Therefore, we use the methanol-to-olefin (MTO) process as a case study to illustrate the various theoretical concepts. This process is a showcase example where rational design of the catalyst was for a long time performed on the basis of trial and error, due to insufficient knowledge of the mechanism. For theoreticians the MTO process is particularly challenging as the catalyst has an inherent supramolecular nature, for which not only the Brønsted acidic site is important but also organic species, trapped in the zeolite pores, must be essentially present during active catalyst operation. All these aspects give rise to specific challenges for theoretical modeling. It is shown that present computational techniques have matured to a level where accurate enthalpy barriers and rate constants can be predicted for reactions occurring at a single active site. The comparison with experimental data such as apparent kinetic data for well-defined elementary reactions has become feasible as current computational techniques also allow predicting adsorption enthalpies with reasonable accuracy. Real catalysts are truly heterogeneous in a space- and time-like manner. Future theory developments should focus on extending our view towards phenomena occurring at longer length and time scales and integrating information from various scales towards a unified understanding of the catalyst. Within this respect molecular dynamics methods complemented with additional techniques to simulate rare events are now gradually making their entrance within zeolite catalysis. Recent applications have already given a flavor of the benefit of such techniques to simulate chemical reactions in complex molecular environments.

Molecular-Based Optical Measurement Techniques for Transition and Turbulence in High-Speed Flow

NASA Technical Reports Server (NTRS)

Bathel, Brett F.; Danehy, Paul M.; Cutler, Andrew D.

2013-01-01

High-speed laminar-to-turbulent transition and turbulence affect the control of flight vehicles, the heat transfer rate to a flight vehicle's surface, the material selected to protect such vehicles from high heating loads, the ultimate weight of a flight vehicle due to the presence of thermal protection systems, the efficiency of fuel-air mixing processes in high-speed combustion applications, etc. Gaining a fundamental understanding of the physical mechanisms involved in the transition process will lead to the development of predictive capabilities that can identify transition location and its impact on parameters like surface heating. Currently, there is no general theory that can completely describe the transition-to-turbulence process. However, transition research has led to the identification of the predominant pathways by which this process occurs. For a truly physics-based model of transition to be developed, the individual stages in the paths leading to the onset of fully turbulent flow must be well understood. This requires that each pathway be computationally modeled and experimentally characterized and validated. This may also lead to the discovery of new physical pathways. This document is intended to describe molecular based measurement techniques that have been developed, addressing the needs of the high-speed transition-to-turbulence and high-speed turbulence research fields. In particular, we focus on techniques that have either been used to study high speed transition and turbulence or techniques that show promise for studying these flows. This review is not exhaustive. In addition to the probe-based techniques described in the previous paragraph, several other classes of measurement techniques that are, or could be, used to study high speed transition and turbulence are excluded from this manuscript. For example, surface measurement techniques such as pressure and temperature paint, phosphor thermography, skin friction measurements and photogrammetry (for model attitude and deformation measurement) are excluded to limit the scope of this report. Other physical probes such as heat flux gauges, total temperature probes are also excluded. We further exclude measurement techniques that require particle seeding though particle based methods may still be useful in many high speed flow applications. This manuscript details some of the more widely used molecular-based measurement techniques for studying transition and turbulence: laser-induced fluorescence (LIF), Rayleigh and Raman Scattering and coherent anti-Stokes Raman scattering (CARS). These techniques are emphasized, in part, because of the prior experience of the authors. Additional molecular based techniques are described, albeit in less detail. Where possible, an effort is made to compare the relative advantages and disadvantages of the various measurement techniques, although these comparisons can be subjective views of the authors. Finally, the manuscript concludes by evaluating the different measurement techniques in view of the precision requirements described in this chapter. Additional requirements and considerations are discussed to assist with choosing an optical measurement technique for a given application.

InterPred: A pipeline to identify and model protein-protein interactions.

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Recent developments in MrBUMP: better search-model preparation, graphical interaction with search models, and solution improvement and assessment.

PubMed

Keegan, Ronan M; McNicholas, Stuart J; Thomas, Jens M H; Simpkin, Adam J; Simkovic, Felix; Uski, Ville; Ballard, Charles C; Winn, Martyn D; Wilson, Keith S; Rigden, Daniel J

2018-03-01

Increasing sophistication in molecular-replacement (MR) software and the rapid expansion of the PDB in recent years have allowed the technique to become the dominant method for determining the phases of a target structure in macromolecular X-ray crystallography. In addition, improvements in bioinformatic techniques for finding suitable homologous structures for use as MR search models, combined with developments in refinement and model-building techniques, have pushed the applicability of MR to lower sequence identities and made weak MR solutions more amenable to refinement and improvement. MrBUMP is a CCP4 pipeline which automates all stages of the MR procedure. Its scope covers everything from the sourcing and preparation of suitable search models right through to rebuilding of the positioned search model. Recent improvements to the pipeline include the adoption of more sensitive bioinformatic tools for sourcing search models, enhanced model-preparation techniques including better ensembling of homologues, and the use of phase improvement and model building on the resulting solution. The pipeline has also been deployed as an online service through CCP4 online, which allows its users to exploit large bioinformatic databases and coarse-grained parallelism to speed up the determination of a possible solution. Finally, the molecular-graphics application CCP4mg has been combined with MrBUMP to provide an interactive visual aid to the user during the process of selecting and manipulating search models for use in MR. Here, these developments in MrBUMP are described with a case study to explore how some of the enhancements to the pipeline and to CCP4mg can help to solve a difficult case.

Recent developments in MrBUMP: better search-model preparation, graphical interaction with search models, and solution improvement and assessment

PubMed Central

Keegan, Ronan M.; McNicholas, Stuart J.; Thomas, Jens M. H.; Simpkin, Adam J.; Uski, Ville; Ballard, Charles C.

2018-01-01

Increasing sophistication in molecular-replacement (MR) software and the rapid expansion of the PDB in recent years have allowed the technique to become the dominant method for determining the phases of a target structure in macromolecular X-ray crystallography. In addition, improvements in bioinformatic techniques for finding suitable homologous structures for use as MR search models, combined with developments in refinement and model-building techniques, have pushed the applicability of MR to lower sequence identities and made weak MR solutions more amenable to refinement and improvement. MrBUMP is a CCP4 pipeline which automates all stages of the MR procedure. Its scope covers everything from the sourcing and preparation of suitable search models right through to rebuilding of the positioned search model. Recent improvements to the pipeline include the adoption of more sensitive bioinformatic tools for sourcing search models, enhanced model-preparation techniques including better ensembling of homologues, and the use of phase improvement and model building on the resulting solution. The pipeline has also been deployed as an online service through CCP4 online, which allows its users to exploit large bioinformatic databases and coarse-grained parallelism to speed up the determination of a possible solution. Finally, the molecular-graphics application CCP4mg has been combined with MrBUMP to provide an interactive visual aid to the user during the process of selecting and manipulating search models for use in MR. Here, these developments in MrBUMP are described with a case study to explore how some of the enhancements to the pipeline and to CCP4mg can help to solve a difficult case. PMID:29533225

Integrated Multiscale Modeling of Molecular Computing Devices. Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tim Schulze

2012-11-01

The general theme of this research has been to expand the capabilities of a simulation technique, Kinetic Monte Carlo (KMC) and apply it to study self-assembled nano-structures on epitaxial thin films. KMC simulates thin film growth and evolution by replacing the detailed dynamics of the system's evolution, which might otherwise be studied using molecular dynamics, with an appropriate stochastic process.

Live Imaging of Centriole Dynamics by Fluorescently Tagged Proteins in Starfish Oocyte Meiosis.

PubMed

Borrego-Pinto, Joana; Somogyi, Kálmán; Lénárt, Péter

2016-01-01

High throughput DNA sequencing, the decreasing costs of DNA synthesis, and universal techniques for genetic manipulation have made it much easier and quicker to establish molecular tools for any organism than it has been 5 years ago. This opens a great opportunity for reviving "nonconventional" model organisms, which are particularly suited to study a specific biological process and many of which have already been established before the era of molecular biology. By taking advantage of transcriptomics, in particular, these systems can now be easily turned into full fetched models for molecular cell biology.As an example, here we describe how we established molecular tools in the starfish Patiria miniata, which has been a popular model for cell and developmental biology due to the synchronous and rapid development, transparency, and easy handling of oocytes, eggs, and embryos. Here, we detail how we used a de novo assembled transcriptome to produce molecular markers and established conditions for live imaging to investigate the molecular mechanisms underlying centriole elimination-a poorly understood process essential for sexual reproduction of animal species.

Constraint Logic Programming approach to protein structure prediction.

PubMed

Dal Palù, Alessandro; Dovier, Agostino; Fogolari, Federico

2004-11-30

The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Igglessi-Markopoulou, Olga; Kollias, George

2010-05-01

A novel QSAR workflow is constructed that combines MLR with LS-SVM classification techniques for the identification of quinazolinone analogs as "active" or "non-active" CXCR3 antagonists. The accuracy of the LS-SVM classification technique for the training set and test was 100% and 90%, respectively. For the "active" analogs a validated MLR QSAR model estimates accurately their I-IP10 IC(50) inhibition values. The accuracy of the QSAR model (R (2) = 0.80) is illustrated using various evaluation techniques, such as leave-one-out procedure (R(LOO2)) = 0.67) and validation through an external test set (R(pred2) = 0.78). The key conclusion of this study is that the selected molecular descriptors, Highest Occupied Molecular Orbital energy (HOMO), Principal Moment of Inertia along X and Y axes PMIX and PMIZ, Polar Surface Area (PSA), Presence of triple bond (PTrplBnd), and Kier shape descriptor ((1) kappa), demonstrate discriminatory and pharmacophore abilities.

From molecules to mating: Rapid evolution and biochemical studies of reproductive proteins

PubMed Central

Wilburn, Damien B.; Swanson, Willie J.

2015-01-01

Sexual reproduction and the exchange of genetic information are essential biological processes for species across all branches of the tree of life. Over the last four decades, biochemists have continued to identify many of the factors that facilitate reproduction, but the molecular mechanisms that mediate this process continue to elude us. However, a recurring observation in this research has been the rapid evolution of reproductive proteins. In animals, the competing interests of males and females often result in arms race dynamics between pairs of interacting proteins. This phenomenon has been observed in all stages of reproduction, including pheromones, seminal fluid components, and gamete recognition proteins. In this article, we review how the integration of evolutionary theory with biochemical experiments can be used to study interacting reproductive proteins. Examples are included from both model and non-model organisms, and recent studies are highlighted for their use of state-of-the-art genomic and proteomic techniques. Significance Despite decades of research, our understanding of the molecular mechanisms that mediate fertilization remain poorly characterized. To date, molecular evolutionary studies on both model and non-model organisms have provided some of the best inferences to elucidating the molecular underpinnings of animal reproduction. This review article details how biochemical and evolutionary experiments have jointly enhanced the field for 40 years, and how recent work using high-throughput genomic and proteomic techniques have shed additional insights into this crucial biological process. PMID:26074353

Charge transport in molecular junctions: From tunneling to hopping with the probe technique

NASA Astrophysics Data System (ADS)

Kilgour, Michael; Segal, Dvira

2015-07-01

We demonstrate that a simple phenomenological approach can be used to simulate electronic conduction in molecular wires under thermal effects induced by the surrounding environment. This "Landauer-Büttiker's probe technique" can properly replicate different transport mechanisms, phase coherent nonresonant tunneling, ballistic behavior, and hopping conduction. Specifically, our simulations with the probe method recover the following central characteristics of charge transfer in molecular wires: (i) the electrical conductance of short wires falls off exponentially with molecular length, a manifestation of the tunneling (superexchange) mechanism. Hopping dynamics overtakes superexchange in long wires demonstrating an ohmic-like behavior. (ii) In off-resonance situations, weak dephasing effects facilitate charge transfer, but under large dephasing, the electrical conductance is suppressed. (iii) At high enough temperatures, kBT/ɛB > 1/25, with ɛB as the molecular-barrier height, the current is enhanced by a thermal activation (Arrhenius) factor. However, this enhancement takes place for both coherent and incoherent electrons and it does not readily indicate on the underlying mechanism. (iv) At finite-bias, dephasing effects may impede conduction in resonant situations. We further show that memory (non-Markovian) effects can be implemented within the Landauer-Büttiker's probe technique to model the interaction of electrons with a structured environment. Finally, we examine experimental results of electron transfer in conjugated molecular wires and show that our computational approach can reasonably reproduce reported values to provide mechanistic information.

Coupled two-dimensional edge plasma and neutral gas modeling of tokamak scrape-off-layers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maingi, Rajesh

1992-08-01

The objective of this study is to devise a detailed description of the tokamak scrape-off-layer (SOL), which includes the best available models of both the plasma and neutral species and the strong coupling between the two in many SOL regimes. A good estimate of both particle flux and heat flux profiles at the limiter/divertor target plates is desired. Peak heat flux is one of the limiting factors in determining the survival probability of plasma-facing-components at high power levels. Plate particle flux affects the neutral flux to the pump, which determines the particle exhaust rate. A technique which couples a two-dimensionalmore » (2-D) plasma and a 2-D neutral transport code has been developed (coupled code technique), but this procedure requires large amounts of computer time. Relevant physics has been added to an existing two-neutral-species model which takes the SOL plasma/neutral coupling into account in a simple manner (molecular physics model), and this model is compared with the coupled code technique mentioned above. The molecular physics model is benchmarked against experimental data from a divertor tokamak (DIII-D), and a similar model (single-species model) is benchmarked against data from a pump-limiter tokamak (Tore Supra). The models are then used to examine two key issues: free-streaming-limits (ion energy conduction and momentum flux) and the effects of the non-orthogonal geometry of magnetic flux surfaces and target plates on edge plasma parameter profiles.« less

Machine learning molecular dynamics for the simulation of infrared spectra.

PubMed

Gastegger, Michael; Behler, Jörg; Marquetand, Philipp

2017-10-01

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects - typically neglected by conventional quantum chemistry approaches - we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n -alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra.

Pressure calculation in hybrid particle-field simulations

NASA Astrophysics Data System (ADS)

Milano, Giuseppe; Kawakatsu, Toshihiro

2010-12-01

In the framework of a recently developed scheme for a hybrid particle-field simulation techniques where self-consistent field (SCF) theory and particle models (molecular dynamics) are combined [J. Chem. Phys. 130, 214106 (2009)], we developed a general formulation for the calculation of instantaneous pressure and stress tensor. The expressions have been derived from statistical mechanical definition of the pressure starting from the expression for the free energy functional in the SCF theory. An implementation of the derived formulation suitable for hybrid particle-field molecular dynamics-self-consistent field simulations is described. A series of test simulations on model systems are reported comparing the calculated pressure with those obtained from standard molecular dynamics simulations based on pair potentials.

State-space reduction and equivalence class sampling for a molecular self-assembly model.

PubMed

Packwood, Daniel M; Han, Patrick; Hitosugi, Taro

2016-07-01

Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models.

Molecular dynamics modeling of bonding two materials by atomic scale friction stir welding

NASA Astrophysics Data System (ADS)

Konovalenko S., Iv.; Konovalenko, Ig. S.; Psakhie, S. G.

2017-12-01

Molecular dynamics model of atomic scale friction stir welding has been developed. Formation of a butt joint between two crystallites was modeled by means of rotating rigid conical tool traveling along the butt joint line. The formed joint had an intermixed atomic structure composed of atoms initially belonged to the opposite mated piece of metal. Heat removal was modeled by adding the extra viscous force to peripheral atomic layers. This technique provides the temperature control in the tool-affected zone during welding. Auxiliary vibration action was added to the rotating tool. The model provides the variation of the tool's angular velocity, amplitude, frequency and direction of the auxiliary vibration action to provide modeling different welding modes.

Mechanical Properties of Nanostructured Materials Determined Through Molecular Modeling Techniques

NASA Technical Reports Server (NTRS)

Clancy, Thomas C.; Gates, Thomas S.

2005-01-01

The potential for gains in material properties over conventional materials has motivated an effort to develop novel nanostructured materials for aerospace applications. These novel materials typically consist of a polymer matrix reinforced with particles on the nanometer length scale. In this study, molecular modeling is used to construct fully atomistic models of a carbon nanotube embedded in an epoxy polymer matrix. Functionalization of the nanotube which consists of the introduction of direct chemical bonding between the polymer matrix and the nanotube, hence providing a load transfer mechanism, is systematically varied. The relative effectiveness of functionalization in a nanostructured material may depend on a variety of factors related to the details of the chemical bonding and the polymer structure at the nanotube-polymer interface. The objective of this modeling is to determine what influence the details of functionalization of the carbon nanotube with the polymer matrix has on the resulting mechanical properties. By considering a range of degree of functionalization, the structure-property relationships of these materials is examined and mechanical properties of these models are calculated using standard techniques.

A Trachylobane Diterpenoid from Xylopia aethiopica

PubMed

Ngouela; Nyassé; Tsamo; Brochier; Morin

1998-02-27

A new trachylobane derivative identified as 7alpha-hydroxytrachyloban-19beta-oic acid (1) has been isolated from the bark of Xylopia aethiopica and its structure elucidated by various NMR techniques and molecular modeling.

From laptop to benchtop to bedside: Structure-based Drug Design on Protein Targets

PubMed Central

Chen, Lu; Morrow, John K.; Tran, Hoang T.; Phatak, Sharangdhar S.; Du-Cuny, Lei; Zhang, Shuxing

2013-01-01

As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches. PMID:22316152

Synchrotron IR microspectroscopy for protein structure analysis: Potential and questions

DOE PAGES

Yu, Peiqiang

2006-01-01

Synchrotron radiation-based Fourier transform infrared microspectroscopy (S-FTIR) has been developed as a rapid, direct, non-destructive, bioanalytical technique. This technique takes advantage of synchrotron light brightness and small effective source size and is capable of exploring the molecular chemical make-up within microstructures of a biological tissue without destruction of inherent structures at ultra-spatial resolutions within cellular dimension. To date there has been very little application of this advanced technique to the study of pure protein inherent structure at a cellular level in biological tissues. In this review, a novel approach was introduced to show the potential of the newly developed, advancedmore » synchrotron-based analytical technology, which can be used to localize relatively “pure“ protein in the plant tissues and relatively reveal protein inherent structure and protein molecular chemical make-up within intact tissue at cellular and subcellular levels. Several complex protein IR spectra data analytical techniques (Gaussian and Lorentzian multi-component peak modeling, univariate and multivariate analysis, principal component analysis (PCA), and hierarchical cluster analysis (CLA) are employed to relatively reveal features of protein inherent structure and distinguish protein inherent structure differences between varieties/species and treatments in plant tissues. By using a multi-peak modeling procedure, RELATIVE estimates (but not EXACT determinations) for protein secondary structure analysis can be made for comparison purpose. The issues of pro- and anti-multi-peaking modeling/fitting procedure for relative estimation of protein structure were discussed. By using the PCA and CLA analyses, the plant molecular structure can be qualitatively separate one group from another, statistically, even though the spectral assignments are not known. The synchrotron-based technology provides a new approach for protein structure research in biological tissues at ultraspatial resolutions.« less

Animal models for the study of inflammatory bowel diseases: a meta-analysis on modalities for imaging inflammatory lesions.

PubMed

Auletta, Sveva; Bonfiglio, Rita; Wunder, Andreas; Varani, Michela; Galli, Filippo; Borri, Filippo; Scimeca, Manuel; Niessen, Heiko G; Schönberger, Tanja; Bonanno, Elena

2018-03-01

Inflammatory bowel diseases are lifelong disorders affecting the gastrointestinal tract characterized by intermittent disease flares and periods of remission with a progressive and destructive nature. Unfortunately, the exact etiology is still not completely known, therefore a causal therapy to cure the disease is not yet available. Current treatment options mainly encompass the use of non-specific anti-inflammatory agents and immunosuppressive drugs that cause significant side effects that often have a negative impact on patients' quality of life. As the majority of patients need a long-term follow-up it would be ideal to rely on a non-invasive technique with good compliance. Currently, the gold standard diagnostic tools for managing IBD are represented by invasive procedures such as colonoscopy and histopathology. Nevertheless, recent advances in imaging technology continue to improve the ability of imaging techniques to non-invasively monitor disease activity and treatment response in preclinical models of IBD. Novel and emerging imaging techniques not only allow direct visualization of intestinal inflammation, but also enable molecular imaging and targeting of specific alterations of the inflamed murine mucosa. Furthermore, molecular imaging advances allow us to increase our knowledge on the critical biological pathways involved in disease progression by characterizing in vivo processes at a cellular and molecular level and enabling significant improvements in the understanding of the etiology of IBD. This review presents a critical and updated overview on the imaging advances in animal models of IBD. Our aim is to highlight the potential beneficial impact and the range of applications that imaging techniques could offer for the improvement of the clinical monitoring and management of IBD patients: diagnosis, staging, determination of therapeutic targets, monitoring therapy and evaluation of the prognosis, personalized therapeutic approaches.

Methods in Molecular Biology Mouse Genetics: Methods and Protocols | Center for Cancer Research

Cancer.gov

Mouse Genetics: Methods and Protocols provides selected mouse genetic techniques and their application in modeling varieties of human diseases. The chapters are mainly focused on the generation of different transgenic mice to accomplish the manipulation of genes of interest, tracing cell lineages, and modeling human diseases.

Landscaping plant epigenetics.

PubMed

McKeown, Peter C; Spillane, Charles

2014-01-01

The understanding of epigenetic mechanisms is necessary for assessing the potential impacts of epigenetics on plant growth, development and reproduction, and ultimately for the response of these factors to evolutionary pressures and crop breeding programs. This volume highlights the latest in laboratory and bioinformatic techniques used for the investigation of epigenetic phenomena in plants. Such techniques now allow genome-wide analyses of epigenetic regulation and help to advance our understanding of how epigenetic regulatory mechanisms affect cellular and genome function. To set the scene, we begin with a short background of how the field of epigenetics has evolved, with a particular focus on plant epigenetics. We consider what has historically been understood by the term "epigenetics" before turning to the advances in biochemistry, molecular biology, and genetics which have led to current-day definitions of the term. Following this, we pay attention to key discoveries in the field of epigenetics that have emerged from the study of unusual and enigmatic phenomena in plants. Many of these phenomena have involved cases of non-Mendelian inheritance and have often been dismissed as mere curiosities prior to the elucidation of their molecular mechanisms. In the penultimate section, consideration is given to how advances in molecular techniques are opening the doors to a more comprehensive understanding of epigenetic phenomena in plants. We conclude by assessing some opportunities, challenges, and techniques for epigenetic research in both model and non-model plants, in particular for advancing understanding of the regulation of genome function by epigenetic mechanisms.

Recommender engine for continuous-time quantum Monte Carlo methods

NASA Astrophysics Data System (ADS)

Huang, Li; Yang, Yi-feng; Wang, Lei

2017-03-01

Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.

Solving the problem of building models of crosslinked polymers: an example focussing on validation of the properties of crosslinked epoxy resins.

PubMed

Hall, Stephen A; Howlin, Brendan J; Hamerton, Ian; Baidak, Alex; Billaud, Claude; Ward, Steven

2012-01-01

The construction of molecular models of crosslinked polymers is an area of some difficulty and considerable interest. We report here a new method of constructing these models and validate the method by modelling three epoxy systems based on the epoxy monomers bisphenol F diglycidyl ether (BFDGE) and triglycidyl-p-amino phenol (TGAP) with the curing agent diamino diphenyl sulphone (DDS). The main emphasis of the work concerns the improvement of the techniques for the molecular simulation of these epoxies and specific attention is paid towards model construction techniques, including automated model building and prediction of glass transition temperatures (T(g)). Typical models comprise some 4200-4600 atoms (ca. 120-130 monomers). In a parallel empirical study, these systems have been cast, cured and analysed by dynamic mechanical thermal analysis (DMTA) to measure T(g). Results for the three epoxy systems yield good agreement with experimental T(g) ranges of 200-220°C, 270-285°C and 285-290°C with corresponding simulated ranges of 210-230°C, 250-300°C, and 250-300°C respectively.

Solving the Problem of Building Models of Crosslinked Polymers: An Example Focussing on Validation of the Properties of Crosslinked Epoxy Resins

PubMed Central

Hall, Stephen A.; Howlin, Brendan J; Hamerton, Ian; Baidak, Alex; Billaud, Claude; Ward, Steven

2012-01-01

The construction of molecular models of crosslinked polymers is an area of some difficulty and considerable interest. We report here a new method of constructing these models and validate the method by modelling three epoxy systems based on the epoxy monomers bisphenol F diglycidyl ether (BFDGE) and triglycidyl-p-amino phenol (TGAP) with the curing agent diamino diphenyl sulphone (DDS). The main emphasis of the work concerns the improvement of the techniques for the molecular simulation of these epoxies and specific attention is paid towards model construction techniques, including automated model building and prediction of glass transition temperatures (Tg). Typical models comprise some 4200–4600 atoms (ca. 120–130 monomers). In a parallel empirical study, these systems have been cast, cured and analysed by dynamic mechanical thermal analysis (DMTA) to measure Tg. Results for the three epoxy systems yield good agreement with experimental Tg ranges of 200–220°C, 270–285°C and 285–290°C with corresponding simulated ranges of 210–230°C, 250–300°C, and 250–300°C respectively. PMID:22916182

Discovery of an Unexplored Protein Structural Scaffold of Serine Protease from Big Blue Octopus (Octopus cyanea): A New Prospective Lead Molecule.

PubMed

Panda, Subhamay; Kumari, Leena

2017-01-01

Serine proteases are a group of enzymes that hydrolyses the peptide bonds in proteins. In mammals, these enzymes help in the regulation of several major physiological functions such as digestion, blood clotting, responses of immune system, reproductive functions and the complement system. Serine proteases obtained from the venom of Octopodidae family is a relatively unexplored area of research. In the present work, we tried to effectively utilize comparative composite molecular modeling technique. Our key aim was to propose the first molecular model structure of unexplored serine protease 5 derived from big blue octopus. The other objective of this study was to analyze the distribution of negatively and positively charged amino acid over molecular modeled structure, distribution of secondary structural elements, hydrophobicity molecular surface analysis and electrostatic potential analysis with the aid of different bioinformatic tools. In the present study, molecular model has been generated with the help of I-TASSER suite. Afterwards the refined structural model was validated with standard methods. For functional annotation of protein molecule we used Protein Information Resource (PIR) database. Serine protease 5 of big blue octopus was analyzed with different bioinformatical algorithms for the distribution of negatively and positively charged amino acid over molecular modeled structure, distribution of secondary structural elements, hydrophobicity molecular surface analysis and electrostatic potential analysis. The functionally critical amino acids and ligand- binding site (LBS) of the proteins (modeled) were determined using the COACH program. The molecular model data in cooperation to other pertinent post model analysis data put forward molecular insight to proteolytic activity of serine protease 5, which helps in the clear understanding of procoagulant and anticoagulant characteristics of this natural lead molecule. Our approach was to investigate the octopus venom protein as a whole or a part of their structure that may result in the development of new lead molecule. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Clustering molecular dynamics trajectories for optimizing docking experiments.

PubMed

De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

Experimental Study and Numerical Modeling of Gas Flow in Microchannels and Micronozzles

DTIC Science & Technology

2005-12-01

built and used to study gas flows in microscale. Gas velocity measurements in microscale were conducted using both Laser Induced Fluorescence...velocity measurements in microscale were conducted using both Laser Induced Fluorescence technique (LIF) in conjunction with Image Correlation...micronozzles, several velocity measurement techniques have been used, such as laser doppler anemometry (LDA), particle image velocimetry (PIV), molecular

Technical Status Review Appraisal of the Suitability of Turbulence Models in Flow Calculations (Revue Technique - L’Evaluation de l’Applicabilite des Modeles de Turbulence dans de Calcul des Ecoulements)

DTIC Science & Technology

1991-07-01

wall compared with a smooth wall. layer is due to the molecular diffusivity and to the increase in heat flux is less than the in- the transport by...models in use an Reyon-stmss- is now much , and cosiderable acityw recenly equit (R!) mdek also know ma lela 1 di1w1sed towass tesa; ad dewioplag low...flow relation is used to take into account the dependence of variables are hypothesized for the different zones. the molecular viscosity coefficient

Equation-free and variable free modeling for complex/multiscale systems. Coarse-grained computation in science and engineering using fine-grained models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kevrekidis, Ioannis G.

The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.

A molecular model for ice nucleation and growth, attachment 1

NASA Technical Reports Server (NTRS)

Plummer, P. L. M.

1981-01-01

The quantum mechanical technique is used to study ionic, configurational, and impurity defects in the ice surface. In addition to static calculations of the energetics of the water monomer-ice surface interactions, molecular dynamics studies were initiated. The calculations of the monomer-ice surface interaction, molecular dynamics studies were initiated. The calculations of monomer-ice surface interactions indicate that many adsorption sites exist on the ice surfaces and that the barriers between bonding sites are relatively low. Bonding on the prism face of ice is preferentially above lattice sites.

Self-assembly of a triangle-shaped, hexaplatinum-incorporated, supramolecular amphiphile in solution and at interfaces.

PubMed

Maran, Umamageswaran; Britt, David; Fox, Christopher B; Harris, Joel M; Orendt, Anita M; Conley, Hiram; Davis, Robert; Hlady, Vladamir; Stang, Peter J

2009-08-24

The self-assembly and characterization of a novel supramolecular amphiphile built from a new 60 degree amphiphilic precursor that incorporates hydrophilic platinum(II) metals and hydrophobic dioctadecyloxy chains is reported. The amphiphilic macrocycle and its precursor compound have been characterized by multinuclear NMR spectroscopy, ESI-MS, and other standard techniques. The coacervate morphology of the amphiphile at the liquid-liquid interface has been studied by using confocal optical microscopy and in situ Raman spectroscopy. The self-assembly of the amphiphilic macrocycle at the air-water interface has been investigated through Langmuir-trough techniques. The study indicates the possible formation of surface micelle-like aggregates. The disparity between the experimental molecular areas and those derived from molecular models support the idea of aggregation. AFM images of the surface aggregates show the formation of a flat topology with arbitrary ridgelike patterns. Reasonable molecular-packing arrangements are proposed to explain the molecular organization within the observed structures.

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

Empirical simulations of materials

NASA Astrophysics Data System (ADS)

Jogireddy, Vasantha

2011-12-01

Molecular dynamics is a specialized discipline of molecular modelling and computer techniques. In this work, first we presented simulation results from a study carried out on silicon nanowires. In the second part of the work, we presented an electrostatic screened coulomb potential developed for studying metal alloys and metal oxides. In particular, we have studied aluminum-copper alloys, aluminum oxides and copper oxides. Parameter optimization for the potential is done using multiobjective optimization algorithms.

Structure-activity relationships for serotonin transporter and dopamine receptor selectivity.

PubMed

Agatonovic-Kustrin, Snezana; Davies, Paul; Turner, Joseph V

2009-05-01

Antipsychotic medications have a diverse pharmacology with affinity for serotonergic, dopaminergic, adrenergic, histaminergic and cholinergic receptors. Their clinical use now also includes the treatment of mood disorders, thought to be mediated by serotonergic receptor activity. The aim of our study was to characterise the molecular properties of antipsychotic agents, and to develop a model that would indicate molecular specificity for the dopamine (D(2)) receptor and the serotonin (5-HT) transporter. Back-propagation artificial neural networks (ANNs) were trained on a dataset of 47 ligands categorically assigned antidepressant or antipsychotic utility. The structure of each compound was encoded with 63 calculated molecular descriptors. ANN parameters including hidden neurons and input descriptors were optimised based on sensitivity analyses, with optimum models containing between four and 14 descriptors. Predicted binding preferences were in excellent agreement with clinical antipsychotic or antidepressant utility. Validated models were further tested by use of an external prediction set of five drugs with unknown mechanism of action. The SAR models developed revealed the importance of simple molecular characteristics for differential binding to the D(2) receptor and the 5-HT transporter. These included molecular size and shape, solubility parameters, hydrogen donating potential, electrostatic parameters, stereochemistry and presence of nitrogen. The developed models and techniques employed are expected to be useful in the rational design of future therapeutic agents.

Macromolecular powder diffraction : structure solution via molecular.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doebbler, J.; Von Dreele, R.; X-Ray Science Division

Macromolecular powder diffraction is a burgeoning technique for protein structure solution - ideally suited for cases where no suitable single crystals are available. Over the past seven years, pioneering work by Von Dreele et al. [1,2] and Margiolaki et al. [3,4] has demonstrated the viability of this approach for several protein structures. Among these initial powder studies, molecular replacement solutions of insulin and turkey lysozyme into alternate space groups were accomplished. Pressing the technique further, Margiolaki et al. [5] executed the first molecular replacement of an unknown protein structure: the SH3 domain of ponsin, using data from a multianalyzer diffractometer.more » To demonstrate that cross-species molecular replacement using image plate data is also possible, we present the solution of hen egg white lysozyme using the 60% identical human lysozyme (PDB code: 1LZ1) as the search model. Due to the high incidence of overlaps in powder patterns, especially in more complex structures, we have used extracted intensities from five data sets taken at different salt concentrations in a multi-pattern Pawley refinement. The use of image plates severely increases the overlap problem due to lower detector resolution, but radiation damage effects are minimized with shorter exposure times and the fact that the entire pattern is obtained in a single exposure. This image plate solution establishes the robustness of powder molecular replacement resulting from different data collection techniques.« less

Synthesis, spectroscopic, thermal and molecular modeling studies of Zn2+, Cd2+ and UO22+ complexes of Schiff bases containing triazole moiety. Antimicrobial, anticancer, antioxidant and DNA binding studies.

PubMed

Gaber, Mohamed; El-Ghamry, Hoda A; Fathalla, Shaimaa K; Mansour, Mohammed A

2018-02-01

A novel series of Zn 2+ , Cd 2+ and UO 2 2+ complexes of ligands namely 1-[(5-mercapto-1H-1,2,4-triazole-3-ylimino) methyl]naphthalene-2-ol (HL 1 ) and [(1H-1,2,4-triazole-3-ylimino) methyl] naphthalene-2-ol (HL 2 ) have been prepared and characterized by different analytical and spectral techniques. The stoichiometry, stereochemistry, conductivity measurements and mode of bonding of the complexes have been elucidated. Accurate comparison of the IR spectra of the ligands with their metal chelates proved the involvement of nitrogen atoms of the azomethine group and/or triazole ring in chelation in addition to the deprotonated hydroxyl oxygen. The UV-Vis and molar conductance data supported the octahedral geometry for the metal complexes. TGA technique has been used to study the thermal decomposition way of the metal complexes and the thermo kinetic parameters were estimated. Valuable information is obtained from calculations of molecular parameters using the molecular modeling techniques. The interaction between the metal complexes and CT-DNA has been studied from which the binding constants (k b ) were calculated. The Schiff bases and their metal chelates have shown potent antimicrobial, antioxidant and antitumor activities. The antitumor activities of the compounds have been tested in vitro against HEPG2 cell line and in silico by the molecular docking analysis with the VEGFR-2 receptor responsible for angiogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular modeling of polymer composite interactions with analytes in electronic nose sensors for environmental monitoring in International Space Station

NASA Technical Reports Server (NTRS)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Zhou, H.; Manatt, K.

2002-01-01

We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL Electronic Nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings (with no hydrogens). The Dreiding 2.21 force field is used for the polymer and solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4- vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic (ammonia) and organic (methanol, toluene, hydrazine) compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites.

Molecular modeling of polymer composite-analyte interactions in electronic nose sensors

NASA Technical Reports Server (NTRS)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Zhou, H.; Manatt, K. S.

2003-01-01

We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL electronic nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereoisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings with no hydrogens. The Dreiding 2.21 force field is used for the polymer, solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4-vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic and organic compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites. c2003 Elsevier Science B.V. All rights reserved.

Coarse-grained models of key self-assembly processes in HIV-1

NASA Astrophysics Data System (ADS)

Grime, John

Computational molecular simulations can elucidate microscopic information that is inaccessible to conventional experimental techniques. However, many processes occur over time and length scales that are beyond the current capabilities of atomic-resolution molecular dynamics (MD). One such process is the self-assembly of the HIV-1 viral capsid, a biological structure that is crucial to viral infectivity. The nucleation and growth of capsid structures requires the interaction of large numbers of capsid proteins within a complicated molecular environment. Coarse-grained (CG) models, where degrees of freedom are removed to produce more computationally efficient models, can in principle access large-scale phenomena such as the nucleation and growth of HIV-1 capsid lattice. We report here studies of the self-assembly behaviors of a CG model of HIV-1 capsid protein, including the influence of the local molecular environment on nucleation and growth processes. Our results suggest a multi-stage process, involving several characteristic structures, eventually producing metastable capsid lattice morphologies that are amenable to subsequent capsid dissociation in order to transmit the viral infection.

Hairy Root as a Model System for Undergraduate Laboratory Curriculum and Research

ERIC Educational Resources Information Center

Keyes, Carol A.; Subramanian, Senthil; Yu, Oliver

2009-01-01

Hairy root transformation has been widely adapted in plant laboratories to rapidly generate transgenic roots for biochemical and molecular analysis. We present hairy root transformations as a versatile and adaptable model system for a wide variety of undergraduate laboratory courses and research. This technique is easy, efficient, and fast making…

3D-QSAR and molecular docking studies on HIV protease inhibitors

NASA Astrophysics Data System (ADS)

Tong, Jianbo; Wu, Yingji; Bai, Min; Zhan, Pei

2017-02-01

In order to well understand the chemical-biological interactions governing their activities toward HIV protease activity, QSAR models of 34 cyclic-urea derivatives with inhibitory HIV were developed. The quantitative structure activity relationship (QSAR) model was built by using comparative molecular similarity indices analysis (CoMSIA) technique. And the best CoMSIA model has rcv2, rncv2 values of 0.586 and 0.931 for cross-validated and non-cross-validated. The predictive ability of CoMSIA model was further validated by a test set of 7 compounds, giving rpred2 value of 0.973. Docking studies were used to find the actual conformations of chemicals in active site of HIV protease, as well as the binding mode pattern to the binding site in protease enzyme. The information provided by 3D-QSAR model and molecular docking may lead to a better understanding of the structural requirements of 34 cyclic-urea derivatives and help to design potential anti-HIV protease molecules.

SketchBio: a scientist's 3D interface for molecular modeling and animation.

PubMed

Waldon, Shawn M; Thompson, Peter M; Hahn, Patrick J; Taylor, Russell M

2014-10-30

Because of the difficulties involved in learning and using 3D modeling and rendering software, many scientists hire programmers or animators to create models and animations. This both slows the discovery process and provides opportunities for miscommunication. Working with multiple collaborators, a tool was developed (based on a set of design goals) to enable them to directly construct models and animations. SketchBio is presented, a tool that incorporates state-of-the-art bimanual interaction and drop shadows to enable rapid construction of molecular structures and animations. It includes three novel features: crystal-by-example, pose-mode physics, and spring-based layout that accelerate operations common in the formation of molecular models. Design decisions and their consequences are presented, including cases where iterative design was required to produce effective approaches. The design decisions, novel features, and inclusion of state-of-the-art techniques enabled SketchBio to meet all of its design goals. These features and decisions can be incorporated into existing and new tools to improve their effectiveness.

Partial molar enthalpies and reaction enthalpies from equilibrium molecular dynamics simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schnell, Sondre K.; Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720; Department of Chemistry, Faculty of Natural Science and Technology, Norwegian University of Science and Technology, 4791 Trondheim

2014-10-14

We present a new molecular simulation technique for determining partial molar enthalpies in mixtures of gases and liquids from single simulations, without relying on particle insertions, deletions, or identity changes. The method can also be applied to systems with chemical reactions. We demonstrate our method for binary mixtures of Weeks-Chandler-Anderson particles by comparing with conventional simulation techniques, as well as for a simple model that mimics a chemical reaction. The method considers small subsystems inside a large reservoir (i.e., the simulation box), and uses the construction of Hill to compute properties in the thermodynamic limit from small-scale fluctuations. Results obtainedmore » with the new method are in excellent agreement with those from previous methods. Especially for modeling chemical reactions, our method can be a valuable tool for determining reaction enthalpies directly from a single MD simulation.« less

ATOMIC RESOLUTION CRYO ELECTRON MICROSCOPY OF MACROMOLECULAR COMPLEXES

PubMed Central

ZHOU, Z. HONG

2013-01-01

Single-particle cryo electron microscopy (cryoEM) is a technique for determining three-dimensional (3D) structures from projection images of molecular complexes preserved in their “native,” noncrystalline state. Recently, atomic or near-atomic resolution structures of several viruses and protein assemblies have been determined by single-particle cryoEM, allowing ab initio atomic model building by following the amino acid side chains or nucleic acid bases identifiable in their cryoEM density maps. In particular, these cryoEM structures have revealed extended arms contributing to molecular interactions that are otherwise not resolved by the conventional structural method of X-ray crystallography at similar resolutions. High-resolution cryoEM requires careful consideration of a number of factors, including proper sample preparation to ensure structural homogeneity, optimal configuration of electron imaging conditions to record high-resolution cryoEM images, accurate determination of image parameters to correct image distortions, efficient refinement and computation to reconstruct a 3D density map, and finally appropriate choice of modeling tools to construct atomic models for functional interpretation. This progress illustrates the power of cryoEM and ushers it into the arsenal of structural biology, alongside conventional techniques of X-ray crystallography and NMR, as a major tool (and sometimes the preferred one) for the studies of molecular interactions in supramolecular assemblies or machines. PMID:21501817

Raman spectroscopy for cancer detection and characterization in metastasis models

NASA Astrophysics Data System (ADS)

Koga, Shigehiro; Oshima, Yusuke; Sato, Mitsunori; Ishimaru, Kei; Yoshida, Motohira; Yamamoto, Yuji; Matsuno, Yusuke; Watanabe, Yuji

2017-02-01

Raman spectroscopy provides a wealth of diagnostic information to the surgeon with in situ cancer detection and label-free histopathology in clinical practice. Raman spectroscopy is a developing optical technique which can analyze biological tissues with light scattering. The difference in frequencies between the incident light and the scattering light are called Raman shifts, which correspond to the vibrational energy of the molecular bonds. Raman spectrum gives information about the molecular structure and composition in biological specimens. We had been previously reported that Raman spectroscopy could distinguish various histological types of human lung cancer cells from normal cells in vitro. However, to identify and detect cancer diagnostic biomarkers in vivo on Raman spectroscopy is still challenging, because malignancy can be characterized not only by the cancer cells but also by the environmental factors including immune cells, stroma cells, secretion vesicles and extracellular matrix. Here we investigate morphological and molecular dynamics in both cancer cells and their environment in xenograft models and spontaneous metastasis models using Raman spectroscopy combined with fluorescence microscopy and photoluminescence imaging. We are also constructing a custom-designed Raman spectral imaging system for both in vitro and in vivo assay of tumor tissues to reveal the metastasis process and to evaluate therapeutic effects of anti-cancer drugs and their drug delivery toward the clinical application of the technique.

Non-invasive molecular imaging for preclinical cancer therapeutic development

PubMed Central

O'Farrell, AC; Shnyder, SD; Marston, G; Coletta, PL; Gill, JH

2013-01-01

Molecular and non-invasive imaging are rapidly emerging fields in preclinical cancer drug discovery. This is driven by the need to develop more efficacious and safer treatments, the advent of molecular-targeted therapeutics, and the requirements to reduce and refine current preclinical in vivo models. Such bioimaging strategies include MRI, PET, single positron emission computed tomography, ultrasound, and optical approaches such as bioluminescence and fluorescence imaging. These molecular imaging modalities have several advantages over traditional screening methods, not least the ability to quantitatively monitor pharmacodynamic changes at the cellular and molecular level in living animals non-invasively in real time. This review aims to provide an overview of non-invasive molecular imaging techniques, highlighting the strengths, limitations and versatility of these approaches in preclinical cancer drug discovery and development. PMID:23488622

Preclinical Magnetic Resonance Imaging and Spectroscopy Studies of Memory, Aging, and Cognitive Decline

PubMed Central

Febo, Marcelo; Foster, Thomas C.

2016-01-01

Neuroimaging provides for non-invasive evaluation of brain structure and activity and has been employed to suggest possible mechanisms for cognitive aging in humans. However, these imaging procedures have limits in terms of defining cellular and molecular mechanisms. In contrast, investigations of cognitive aging in animal models have mostly utilized techniques that have offered insight on synaptic, cellular, genetic, and epigenetic mechanisms affecting memory. Studies employing magnetic resonance imaging and spectroscopy (MRI and MRS, respectively) in animal models have emerged as an integrative set of techniques bridging localized cellular/molecular phenomenon and broader in vivo neural network alterations. MRI methods are remarkably suited to longitudinal tracking of cognitive function over extended periods permitting examination of the trajectory of structural or activity related changes. Combined with molecular and electrophysiological tools to selectively drive activity within specific brain regions, recent studies have begun to unlock the meaning of fMRI signals in terms of the role of neural plasticity and types of neural activity that generate the signals. The techniques provide a unique opportunity to causally determine how memory-relevant synaptic activity is processed and how memories may be distributed or reconsolidated over time. The present review summarizes research employing animal MRI and MRS in the study of brain function, structure, and biochemistry, with a particular focus on age-related cognitive decline. PMID:27468264

Mid-IR enhanced laser ablation molecular isotopic spectrometry

NASA Astrophysics Data System (ADS)

Brown, Staci; Ford, Alan; Akpovo, Codjo A.; Johnson, Lewis

2016-08-01

A double-pulsed laser-induced breakdown spectroscopy (DP-LIBS) technique utilizing wavelengths in the mid-infrared (MIR) for the second pulse, referred to as double-pulse LAMIS (DP-LAMIS), was examined for its effect on detection limits compared to single-pulse laser ablation molecular isotopic spectrometry (LAMIS). A MIR carbon dioxide (CO2) laser pulse at 10.6 μm was employed to enhance spectral emissions from nanosecond-laser-induced plasma via mid-IR reheating and in turn, improve the determination of the relative abundance of isotopes in a sample. This technique was demonstrated on a collection of 10BO and 11BO molecular spectra created from enriched boric acid (H3BO3) isotopologues in varying concentrations. Effects on the overall ability of both LAMIS and DP-LAMIS to detect the relative abundance of boron isotopes in a starting sample were considered. Least-squares fitting to theoretical models was used to deduce plasma parameters and understand reproducibility of results. Furthermore, some optimization for conditions of the enhanced emission was achieved, along with a comparison of the overall emission intensity, plasma density, and plasma temperature generated by the two techniques.

Noninvasive Assessment of Cell Fate and Biology in Transplanted Mesenchymal Stem Cells.

PubMed

Franchi, Federico; Rodriguez-Porcel, Martin

2017-01-01

Recently, molecular imaging has become a conditio sine qua non for cell-based regenerative medicine. Developments in molecular imaging techniques, such as reporter gene technology, have increasingly enabled the noninvasive assessment of the fate and biology of cells after cardiovascular applications. In this context, bioluminescence imaging is the most commonly used imaging modality in small animal models of preclinical studies. Here, we present a detailed protocol of a reporter gene imaging approach for monitoring the viability and biology of Mesenchymal Stem Cells transplanted in a mouse model of myocardial ischemia reperfusion injury.

Multi-scale modeling in cell biology

PubMed Central

Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

2009-01-01

Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808

Towards better modelling of drug-loading in solid lipid nanoparticles: Molecular dynamics, docking experiments and Gaussian Processes machine learning.

PubMed

Hathout, Rania M; Metwally, Abdelkader A

2016-11-01

This study represents one of the series applying computer-oriented processes and tools in digging for information, analysing data and finally extracting correlations and meaningful outcomes. In this context, binding energies could be used to model and predict the mass of loaded drugs in solid lipid nanoparticles after molecular docking of literature-gathered drugs using MOE® software package on molecularly simulated tripalmitin matrices using GROMACS®. Consequently, Gaussian processes as a supervised machine learning artificial intelligence technique were used to correlate the drugs' descriptors (e.g. M.W., xLogP, TPSA and fragment complexity) with their molecular docking binding energies. Lower percentage bias was obtained compared to previous studies which allows the accurate estimation of the loaded mass of any drug in the investigated solid lipid nanoparticles by just projecting its chemical structure to its main features (descriptors). Copyright © 2016 Elsevier B.V. All rights reserved.

Molecular biology of mycoplasmas: from the minimum cell concept to the artificial cell.

PubMed

Cordova, Caio M M; Hoeltgebaum, Daniela L; Machado, Laís D P N; Santos, Larissa Dos

2016-01-01

Mycoplasmas are a large group of bacteria, sorted into different genera in the Mollicutes class, whose main characteristic in common, besides the small genome, is the absence of cell wall. They are considered cellular and molecular biology study models. We present an updated review of the molecular biology of these model microorganisms and the development of replicative vectors for the transformation of mycoplasmas. Synthetic biology studies inspired by these pioneering works became possible and won the attention of the mainstream media. For the first time, an artificial genome was synthesized (a minimal genome produced from consensus sequences obtained from mycoplasmas). For the first time, a functional artificial cell has been constructed by introducing a genome completely synthesized within a cell envelope of a mycoplasma obtained by transformation techniques. Therefore, this article offers an updated insight to the state of the art of these peculiar organisms' molecular biology.

Growth and modelling of spherical crystalline morphologies of molecular materials

NASA Astrophysics Data System (ADS)

Shalev, O.; Biswas, S.; Yang, Y.; Eddir, T.; Lu, W.; Clarke, R.; Shtein, M.

2014-10-01

Crystalline, yet smooth, sphere-like morphologies of small molecular compounds are desirable in a wide range of applications but are very challenging to obtain using common growth techniques, where either amorphous films or faceted crystallites are the norm. Here we show solvent-free, guard flow-assisted organic vapour jet printing of non-faceted, crystalline microspheroids of archetypal small molecular materials used in organic electronic applications. We demonstrate how process parameters control the size distribution of the spheroids and propose an analytical model and a phase diagram predicting the surface morphology evolution of different molecules based on processing conditions, coupled with the thermophysical and mechanical properties of the molecules. This experimental approach opens a path for exciting applications of small molecular organic compounds in optical coatings, textured surfaces with controlled wettability, pharmaceutical and food substance printing and others, where thick organic films and particles with high surface area are needed.

Optical/MRI Multimodality Molecular Imaging

NASA Astrophysics Data System (ADS)

Ma, Lixin; Smith, Charles; Yu, Ping

2007-03-01

Multimodality molecular imaging that combines anatomical and functional information has shown promise in development of tumor-targeted pharmaceuticals for cancer detection or therapy. We present a new multimodality imaging technique that combines fluorescence molecular tomography (FMT) and magnetic resonance imaging (MRI) for in vivo molecular imaging of preclinical tumor models. Unlike other optical/MRI systems, the new molecular imaging system uses parallel phase acquisition based on heterodyne principle. The system has a higher accuracy of phase measurements, reduced noise bandwidth, and an efficient modulation of the fluorescence diffuse density waves. Fluorescent Bombesin probes were developed for targeting breast cancer cells and prostate cancer cells. Tissue phantom and small animal experiments were performed for calibration of the imaging system and validation of the targeting probes.

A novel approach for the removal of radiocesium from aqueous solution by ZSM-5 molecular sieve.

PubMed

Gao, Xiaoqing; Zhang, Peng; Yang, Junqiang; Sun, Xuejie; Fu, Yi; Shi, Keliang; Chai, Zhifang; Wu, Wangsuo

2018-05-21

Finding an approach for pretreatment of radionuclides from contaminated water are interesting topics of research. In present work, the ZSM-5 molecular sieve was characterized with different techniques such as zeta potential, SEM, FT-IR and XRD to clarify the surface properties of sample and applied as a sorbent to concentrate and recover Cs(I) from aqueous solution. The effect of environmental conditions such as contact time, ionic strength, content of sorbent and solution pH on Cs(I) uptake were optimized using batch techniques. Different kinetic and isotherm models were utilized to evaluate the experimental data and the correlation parameters were obtained. Based on the sorption/desorption experiment, it can be deduced that the ZSM-5 molecular sieve has potential application for the rapid and quantitative recovery of radiocesium from wastewater. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fine refinement of solid state structure of racemic form of phospho-tyrosine employing NMR Crystallography approach.

PubMed

Paluch, Piotr; Pawlak, Tomasz; Oszajca, Marcin; Lasocha, Wieslaw; Potrzebowski, Marek J

2015-02-01

We present step by step facets important in NMR Crystallography strategy employing O-phospho-dl-tyrosine as model sample. The significance of three major techniques being components of this approach: solid state NMR (SS NMR), X-ray diffraction of powdered sample (PXRD) and theoretical calculations (Gauge Invariant Projector Augmented Wave; GIPAW) is discussed. Each experimental technique provides different set of structural constraints. From the PXRD measurement the size of the unit cell, space group and roughly refined molecular structure are established. SS NMR provides information about content of crystallographic asymmetric unit, local geometry, molecular motion in the crystal lattice and hydrogen bonding pattern. GIPAW calculations are employed for validation of quality of elucidation and fine refinement of structure. Crystal and molecular structure of O-phospho-dl-tyrosine solved by NMR Crystallography is deposited at Cambridge Crystallographic Data Center under number CCDC 1005924. Copyright © 2014 Elsevier Inc. All rights reserved.

Whole-Brain Microscopy Meets In Vivo Neuroimaging: Techniques, Benefits, and Limitations.

PubMed

Aswendt, Markus; Schwarz, Martin; Abdelmoula, Walid M; Dijkstra, Jouke; Dedeurwaerdere, Stefanie

2017-02-01

Magnetic resonance imaging, positron emission tomography, and optical imaging have emerged as key tools to understand brain function and neurological disorders in preclinical mouse models. They offer the unique advantage of monitoring individual structural and functional changes over time. What remained unsolved until recently was to generate whole-brain microscopy data which can be correlated to the 3D in vivo neuroimaging data. Conventional histological sections are inappropriate especially for neuronal tracing or the unbiased screening for molecular targets through the whole brain. As part of the European Society for Molecular Imaging (ESMI) meeting 2016 in Utrecht, the Netherlands, we addressed this issue in the Molecular Neuroimaging study group meeting. Presentations covered new brain clearing methods, light sheet microscopes for large samples, and automatic registration of microscopy to in vivo imaging data. In this article, we summarize the discussion; give an overview of the novel techniques; and discuss the practical needs, benefits, and limitations.

Simulations of a molecular plasma in collisional-radiative nonequilibrium

NASA Technical Reports Server (NTRS)

Cambier, Jean-Luc; Moreau, Stephane

1993-01-01

A code for the simulation of nonequilibrium plasmas is being developed, with the capability to couple the plasma fluid-dynamics for a single fluid with a collisional-radiative model, where electronic states are treated as separate species. The model allows for non-Boltzmann distribution of the electronic states. Deviations from the Boltzmann distributions are expected to occur in the rapidly ionizing regime behind a strong shock or in the recombining regime during a fast expansion. This additional step in modeling complexity is expected to yield more accurate predictions of the nonequilibrium state and the radiation spectrum and intensity. An attempt at extending the code to molecular plasma flows is presented. The numerical techniques used, the thermochemical model, and the results of some numerical tests are described.

Animal models for rotator cuff repair.

PubMed

Lebaschi, Amir; Deng, Xiang-Hua; Zong, Jianchun; Cong, Guang-Ting; Carballo, Camila B; Album, Zoe M; Camp, Christopher; Rodeo, Scott A

2016-11-01

Rotator cuff (RC) injuries represent a significant source of pain, functional impairment, and morbidity. The large disease burden of RC pathologies necessitates rapid development of research methodologies to treat these conditions. Given their ability to model anatomic, biomechanical, cellular, and molecular aspects of the human RC, animal models have played an indispensable role in reducing injury burden and advancing this field of research for many years. The development of animal models in the musculoskeletal (MSK) research arena is uniquely different from that in other fields in that the similarity of macrostructures and functions is as critical to replicate as cellular and molecular functions. Traditionally, larger animals have been used because of their anatomic similarity to humans and the ease of carrying out realistic surgical procedures. However, refinement of current molecular methods, introduction of novel research tools, and advancements in microsurgical techniques have increased the applicability of small animal models in MSK research. In this paper, we review RC animal models and emphasize a murine model that may serve as a valuable instrument for future RC tendon repair investigations. © 2016 New York Academy of Sciences.

Learning Kinetic Monte Carlo Models of Condensed Phase High Temperature Chemistry from Molecular Dynamics

NASA Astrophysics Data System (ADS)

Yang, Qian; Sing-Long, Carlos; Chen, Enze; Reed, Evan

2017-06-01

Complex chemical processes, such as the decomposition of energetic materials and the chemistry of planetary interiors, are typically studied using large-scale molecular dynamics simulations that run for weeks on high performance parallel machines. These computations may involve thousands of atoms forming hundreds of molecular species and undergoing thousands of reactions. It is natural to wonder whether this wealth of data can be utilized to build more efficient, interpretable, and predictive models. In this talk, we will use techniques from statistical learning to develop a framework for constructing Kinetic Monte Carlo (KMC) models from molecular dynamics data. We will show that our KMC models can not only extrapolate the behavior of the chemical system by as much as an order of magnitude in time, but can also be used to study the dynamics of entirely different chemical trajectories with a high degree of fidelity. Then, we will discuss three different methods for reducing our learned KMC models, including a new and efficient data-driven algorithm using L1-regularization. We demonstrate our framework throughout on a system of high-temperature high-pressure liquid methane, thought to be a major component of gas giant planetary interiors.

On The Development of Biophysical Models for Space Radiation Risk Assessment

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Dicello, J. F.

1999-01-01

Experimental techniques in molecular biology are being applied to study biological risks from space radiation. The use of molecular assays presents a challenge to biophysical models which in the past have relied on descriptions of energy deposition and phenomenological treatments of repair. We describe a biochemical kinetics model of cell cycle control and DNA damage response proteins in order to model cellular responses to radiation exposures. Using models of cyclin-cdk, pRB, E2F's, p53, and GI inhibitors we show that simulations of cell cycle populations and GI arrest can be described by our biochemical approach. We consider radiation damaged DNA as a substrate for signal transduction processes and consider a dose and dose-rate reduction effectiveness factor (DDREF) for protein expression.

Self-consistent continuum solvation for optical absorption of complex molecular systems in solution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timrov, Iurii; Biancardi, Alessandro; Andreussi, Oliviero

2015-01-21

We introduce a new method to compute the optical absorption spectra of complex molecular systems in solution, based on the Liouville approach to time-dependent density-functional perturbation theory and the revised self-consistent continuum solvation model. The former allows one to obtain the absorption spectrum over a whole wide frequency range, using a recently proposed Lanczos-based technique, or selected excitation energies, using the Casida equation, without having to ever compute any unoccupied molecular orbitals. The latter is conceptually similar to the polarizable continuum model and offers the further advantages of allowing an easy computation of atomic forces via the Hellmann-Feynman theorem andmore » a ready implementation in periodic-boundary conditions. The new method has been implemented using pseudopotentials and plane-wave basis sets, benchmarked against polarizable continuum model calculations on 4-aminophthalimide, alizarin, and cyanin and made available through the QUANTUM ESPRESSO distribution of open-source codes.« less

Exploring the mechanism of interaction between 5-(ethoxycarbonyl)-6-methyl-4-(4-methoxyphenyl)-3,4-dihydropyrimidin-2(1H)-one and human serum albumin: Spectroscopic, calorimetric and molecular modeling studies.

PubMed

Wang, Gongke; Li, Xiang; Ding, Xuelian; Wang, Dongchao; Yan, Changling; Lu, Yan

2011-07-15

In this paper, binding interaction of 5-(ethoxycarbonyl)-6-methyl-4-(4-methoxyphenyl)-3,4-dihydropyrimidin-2(1H)-one (EMMD) with human serum albumin (HSA) under physiological conditions was investigated by using spectroscopy, isothermal titration calorimetry (ITC) and molecular modeling techniques. The results of spectroscopic studies suggested that EMMD have a strong ability to quench the intrinsic fluorescence of HSA through static quenching procedure. ITC investigations indicated that drug-protein complex was stabilized by hydrophobic forces and hydrogen bonds, which was consistent with the results of molecular modeling studies. Competitive experiments indicated the displacement of warfarin by EMMD, which revealed that the binding site of EMMD to HSA was located at subdomain IIA. Copyright © 2011 Elsevier B.V. All rights reserved.

Molecular Rotation Signals: Molecule Chemistry and Particle Physics

NASA Astrophysics Data System (ADS)

Grabow, Jens-Uwe

2015-06-01

Molecules - large or small - are attractive academic resources, with numerous questions on their chemical behaviour as well as problems in fundamental physics now (or still) waiting to be answered: Targeted by high-resolution spectroscopy, a rotating molecular top can turn into a laboratory for molecule chemistry or a laboratory for particle physics. Once successfully entrained (many species - depending on size and chemical composition - have insufficient vapour pressures or are of transient nature, such that specifically designed pulsed-jet sources are required for their transfer into the gas phase or in-situ generation) into the collision-free environment of a supersonic-jet expansion, each molecular top comes with its own set of challenges, theoretically and experimentally: Multiple internal interactions are causing complicated energy level schemes and the resulting spectra will be rather difficult to predict theoretically. Experimentally, these spectra are difficult to assess and assign. With today's broad-banded chirp microwave techniques, finding and identifying such spectral features have lost their major drawback of being very time consuming for many molecules. For other molecules, the unrivalled resolution and sensitivity of the narrow-banded impulse microwave techniques provide a window to tackle - at the highest precision available to date - fundamental questions in physics, even particle physics - potentially beyond the standard model. Molecular charge distribution, properties of the chemical bond, details on internal dynamics and intermolecular interaction, the (stereo-chemical) molecular structure (including the possibility of their spatial separation) as well as potential evidence for tiny yet significant interactions encode their signature in pure molecular rotation subjected to time-domain microwave spectroscopic techniques. Ongoing exciting technical developments promise rapid progress. We present recent examples from Hannover, new directions, and an outlook at the future of molecular rotation spectroscopy.

Validating clustering of molecular dynamics simulations using polymer models.

PubMed

Phillips, Joshua L; Colvin, Michael E; Newsam, Shawn

2011-11-14

Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.

Validating clustering of molecular dynamics simulations using polymer models

PubMed Central

2011-01-01

Background Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers. PMID:22082218

Advances in visual representation of molecular potentials.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen

2010-06-01

The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.

Molecular alignment and orientation with a hybrid Raman scattering technique

NASA Astrophysics Data System (ADS)

Bustard, Philip J.; Lausten, R.; Sussman, Benjamin J.

2012-11-01

We demonstrate a scheme for the preparation of molecular alignment and angular momentum orientation using a hybrid combination of two limits of Raman scattering. First a weak, impulsive pump pulse initializes the system via the nonresonant dynamic Stark effect. Then, having overcome the influence of the vacuum fluctuations, an amplification pulse selectively enhances the initial coherences by transient stimulated Raman scattering, generating alignment and angular momentum orientation of molecular hydrogen. The amplitude and phase of the resulting coherent dynamics are experimentally probed, indicating an amplification factor of 4.5. An analytic theory is developed to model the dynamics.

Understanding the kinetics of ligand binding to globins with molecular dynamics simulations: the necessity of multiple state models.

PubMed

Estarellas Martin, Carolina; Seira Castan, Constantí; Luque Garriga, F Javier; Bidon-Chanal Badia, Axel

2015-10-01

Residue conformational changes and internal cavity migration processes play a key role in regulating the kinetics of ligand migration and binding events in globins. Molecular dynamics simulations have demonstrated their value in the study of these processes in different haemoglobins, but derivation of kinetic data demands the use of more complex techniques like enhanced sampling molecular dynamics methods. This review discusses the different methodologies that are currently applied to study the ligand migration process in globins and highlight those specially developed to derive kinetic data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

NASA Astrophysics Data System (ADS)

Chung, K. K.; Do, D. Q.

2010-09-01

In order to model relationships between chemical structures and biological effects in quantitative structure-activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data.

Study on the interaction of the drug mesalamine with calf thymus DNA using molecular docking and spectroscopic techniques.

PubMed

Shahabadi, Nahid; Fili, Soraya Moradi; Kheirdoosh, Fahimeh

2013-11-05

The interaction of CT-DNA with the drug mesalamine (5-ASA) at physiological pH has been investigated by absorption, emission, circular dichroism (CD), cyclic voltammetry (CV), viscosity studies and molecular modeling. Thermodynamic parameters (ΔH>0 and ΔS<0) indicated that hydrogen bond and van der Waals play main roles in the binding of 5-ASA to CT-DNA. Ethidium bromide (EB) displacement studies revealed that 5-ASA did not have any effect on ethidium bromide (EB) bound DNA which is indicative of groove binding. The results obtained from experimental and molecular modeling showed that 5-ASA is a minor groove binder of DNA and preferentially binds to GC rich regions. Copyright © 2013 Elsevier B.V. All rights reserved.

Elucidation of chemosensitization effect of acridones in cancer cell lines: Combined pharmacophore modeling, 3D QSAR, and molecular dynamics studies.

PubMed

Gade, Deepak Reddy; Makkapati, Amareswararao; Yarlagadda, Rajesh Babu; Peters, Godefridus J; Sastry, B S; Rajendra Prasad, V V S

2018-06-01

Overexpression of P-glycoprotein (P-gp) leads to the emergence of multidrug resistance (MDR) in cancer treatment. Acridones have the potential to reverse MDR and sensitize cells. In the present study, we aimed to elucidate the chemosensitization potential of acridones by employing various molecular modelling techniques. Pharmacophore modeling was performed for the dataset of chemosensitizing acridones earlier proved for cytotoxic activity against MCF7 breast cancer cell line. Gaussian-based QSAR studies also performed to predict the favored and disfavored region of the acridone molecules. Molecular dynamics simulations were performed for compound 10 and human P-glycoprotein (obtained from Homology modeling). An efficient pharmacophore containing 2 hydrogen bond acceptors and 3 aromatic rings (AARRR.14) was identified. NCI 2012 chemical database was screened against AARRR.14 CPH and identified 25 best-fit molecules. Potential regions of the compound were identified through Field (Gaussian) based QSAR. Regression analysis of atom-based QSAR resulted in r 2 of 0.95 and q 2 of 0.72, whereas, regression analysis of field-based QSAR resulted in r 2 of 0.92 and q 2 of 0.87 along with r 2 cv as 0.71. The fate of the acridone molecule (compound 10) in the P-glycoprotein environment is analyzed through analyzing the conformational changes occurring during the molecular dynamics simulations. Combined data of different in silico techniques provided basis for deeper understanding of structural and mechanistic insights of interaction phenomenon of acridones with P-glycoprotein and also as strategic basis for designing more potent molecules for anti-cancer and multidrug resistance reversal activities. Copyright © 2018 Elsevier Ltd. All rights reserved.

First-Principles Molecular Dynamics Studies of Organometallic Complexes and Homogeneous Catalytic Processes.

PubMed

Vidossich, Pietro; Lledós, Agustí; Ujaque, Gregori

2016-06-21

Computational chemistry is a valuable aid to complement experimental studies of organometallic systems and their reactivity. It allows probing mechanistic hypotheses and investigating molecular structures, shedding light on the behavior and properties of molecular assemblies at the atomic scale. When approaching a chemical problem, the computational chemist has to decide on the theoretical approach needed to describe electron/nuclear interactions and the composition of the model used to approximate the actual system. Both factors determine the reliability of the modeling study. The community dedicated much effort to developing and improving the performance and accuracy of theoretical approaches for electronic structure calculations, on which the description of (inter)atomic interactions rely. Here, the importance of the model system used in computational studies is highlighted through examples from our recent research focused on organometallic systems and homogeneous catalytic processes. We show how the inclusion of explicit solvent allows the characterization of molecular events that would otherwise not be accessible in reduced model systems (clusters). These include the stabilization of nascent charged fragments via microscopic solvation (notably, hydrogen bonding), transfer of charge (protons) between distant fragments mediated by solvent molecules, and solvent coordination to unsaturated metal centers. Furthermore, when weak interactions are involved, we show how conformational and solvation properties of organometallic complexes are also affected by the explicit inclusion of solvent molecules. Such extended model systems may be treated under periodic boundary conditions, thus removing the cluster/continuum (or vacuum) boundary, and require a statistical mechanics simulation technique to sample the accessible configurational space. First-principles molecular dynamics, in which atomic forces are computed from electronic structure calculations (namely, density functional theory), is certainly the technique of choice to investigate chemical events in solution. This methodology is well established and thanks to advances in both algorithms and computational resources simulation times required for the modeling of chemical events are nowadays accessible, though the computational requirements use to be high. Specific applications reviewed here include mechanistic studies of the Shilov and Wacker processes, speciation in Pd chemistry, hydrogen bonding to metal centers, and the dynamics of agostic interactions.

Molecular imaging of inflammation and intraplaque vasa vasorum: A step forward to identification of vulnerable plaques?

PubMed Central

ten Kate, Gerrit L.; Sijbrands, Eric J. G.; Valkema, Roelf; ten Cate, Folkert J.; Feinstein, Steven B.; van der Steen, Antonius F. W.; Daemen, Mat J. A. P.

2010-01-01

Current developments in cardiovascular biology and imaging enable the noninvasive molecular evaluation of atherosclerotic vascular disease. Intraplaque neovascularization sprouting from the adventitial vasa vasorum has been identified as an independent predictor of intraplaque hemorrhage and plaque rupture. These intraplaque vasa vasorum result from angiogenesis, most likely under influence of hypoxic and inflammatory stimuli. Several molecular imaging techniques are currently available. Most experience has been obtained with molecular imaging using positron emission tomography and single photon emission computed tomography. Recently, the development of targeted contrast agents has allowed molecular imaging with magnetic resonance imaging, ultrasound and computed tomography. The present review discusses the use of these molecular imaging techniques to identify inflammation and intraplaque vasa vasorum to identify vulnerable atherosclerotic plaques at risk of rupture and thrombosis. The available literature on molecular imaging techniques and molecular targets associated with inflammation and angiogenesis is discussed, and the clinical applications of molecular cardiovascular imaging and the use of molecular techniques for local drug delivery are addressed. PMID:20552308

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

PubMed Central

De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944

Use of radionuclides in cancer research and treatment.

PubMed

Macías, M T

2009-03-01

Cancer occurs as a result of misregulation of cell growth, which appears to be a consequence of alteration in the function of oncogenes and tumour suppressor genes. Ionising radiation has been used, since the discovery of X-rays in 1896 by Roentgen, both in cancer research and treatment of the disease. The main purpose of cancer research is to understand the molecular alterations involved in the development and progression of the disease in order to improve diagnosis and develop personalised therapies, by focusing on the features of the tumoral cell and the biological events associated to carcinogenesis. Radioisotopic techniques have been used routinely for in vitro research in the molecular and cellular biology of cancer for more than 20 years and are in the process of being substituted by alternative non-radioactive techniques. However in vivo techniques such as irradiation of cells in culture and/or experimental animal models and radioactive labelling are in development, due in part to advances in molecular imaging technologies. The objective of this review is to analyse in an integrative way the applications of ionising radiation in cancer research and therapy. It had been divided into two parts. The first one will approach the techniques applied to cancer research and the second will summarise how ionising radiation is applied to the treatment of neoplastic disease.

Molecular Characterization of Growth Hormone-producing Tumors in the GC Rat Model of Acromegaly.

PubMed

Martín-Rodríguez, Juan F; Muñoz-Bravo, Jose L; Ibañez-Costa, Alejandro; Fernandez-Maza, Laura; Balcerzyk, Marcin; Leal-Campanario, Rocío; Luque, Raúl M; Castaño, Justo P; Venegas-Moreno, Eva; Soto-Moreno, Alfonso; Leal-Cerro, Alfonso; Cano, David A

2015-11-09

Acromegaly is a disorder resulting from excessive production of growth hormone (GH) and consequent increase of insulin-like growth factor 1 (IGF-I), most frequently caused by pituitary adenomas. Elevated GH and IGF-I levels results in wide range of somatic, cardiovascular, endocrine, metabolic, and gastrointestinal morbidities. Subcutaneous implantation of the GH-secreting GC cell line in rats leads to the formation of tumors. GC tumor-bearing rats develop characteristics that resemble human acromegaly including gigantism and visceromegaly. However, GC tumors remain poorly characterized at a molecular level. In the present work, we report a detailed histological and molecular characterization of GC tumors using immunohistochemistry, molecular biology and imaging techniques. GC tumors display histopathological and molecular features of human GH-producing tumors, including hormone production, cell architecture, senescence activation and alterations in cell cycle gene expression. Furthermore, GC tumors cells displayed sensitivity to somatostatin analogues, drugs that are currently used in the treatment of human GH-producing adenomas, thus supporting the GC tumor model as a translational tool to evaluate therapeutic agents. The information obtained would help to maximize the usefulness of the GC rat model for research and preclinical studies in GH-secreting tumors.

Molecular Characterization of Growth Hormone-producing Tumors in the GC Rat Model of Acromegaly

PubMed Central

Martín-Rodríguez, Juan F.; Muñoz-Bravo, Jose L.; Ibañez-Costa, Alejandro; Fernandez-Maza, Laura; Balcerzyk, Marcin; Leal-Campanario, Rocío; Luque, Raúl M.; Castaño, Justo P.; Venegas-Moreno, Eva; Soto-Moreno, Alfonso; Leal-Cerro, Alfonso; Cano, David A.

2015-01-01

Acromegaly is a disorder resulting from excessive production of growth hormone (GH) and consequent increase of insulin-like growth factor 1 (IGF-I), most frequently caused by pituitary adenomas. Elevated GH and IGF-I levels results in wide range of somatic, cardiovascular, endocrine, metabolic, and gastrointestinal morbidities. Subcutaneous implantation of the GH-secreting GC cell line in rats leads to the formation of tumors. GC tumor-bearing rats develop characteristics that resemble human acromegaly including gigantism and visceromegaly. However, GC tumors remain poorly characterized at a molecular level. In the present work, we report a detailed histological and molecular characterization of GC tumors using immunohistochemistry, molecular biology and imaging techniques. GC tumors display histopathological and molecular features of human GH-producing tumors, including hormone production, cell architecture, senescence activation and alterations in cell cycle gene expression. Furthermore, GC tumors cells displayed sensitivity to somatostatin analogues, drugs that are currently used in the treatment of human GH-producing adenomas, thus supporting the GC tumor model as a translational tool to evaluate therapeutic agents. The information obtained would help to maximize the usefulness of the GC rat model for research and preclinical studies in GH-secreting tumors. PMID:26549306

Synchrotron based mass spectrometry to investigate the molecular properties of mineral-organic associations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Suet Yi; Kleber, Markus; Takahashi, Lynelle K.

2013-04-01

Soil organic matter (OM) is important because its decay drives life processes in the biosphere. Analysis of organic compounds in geological systems is difficult because of their intimate association with mineral surfaces. To date there is no procedure capable of quantitatively separating organic from mineral phases without creating artifacts or mass loss. Therefore, analytical techniques that can (a) generate information about both organic and mineral phases simultaneously and (b) allow the examination of predetermined high-interest regions of the sample as opposed to conventional bulk analytical techniques are valuable. Laser Desorption Synchrotron Postionization (synchrotron-LDPI) mass spectrometry is introduced as a novelmore » analytical tool to characterize the molecular properties of organic compounds in mineral-organic samples from terrestrial systems, and it is demonstrated that when combined with Secondary Ion Mass Spectrometry (SIMS), can provide complementary information on mineral composition. Mass spectrometry along a decomposition gradient in density fractions, verifies the consistency of our results with bulk analytical techniques. We further demonstrate that by changing laser and photoionization energies, variations in molecular stability of organic compounds associated with mineral surfaces can be determined. The combination of synchrotron-LDPI and SIMS shows that the energetic conditions involved in desorption and ionization of organic matter may be a greater determinant of mass spectral signatures than the inherent molecular structure of the organic compounds investigated. The latter has implications for molecular models of natural organic matter that are based on mass spectrometric information.« less

Quantitative spectral and orientational analysis in surface sum frequency generation vibrational spectroscopy (SFG-VS)

NASA Astrophysics Data System (ADS)

Wang, Hong-Fei; Gan, Wei; Lu, Rong; Rao, Yi; Wu, Bao-Hua

Sum frequency generation vibrational spectroscopy (SFG-VS) has been proven to be a uniquely effective spectroscopic technique in the investigation of molecular structure and conformations, as well as the dynamics of molecular interfaces. However, the ability to apply SFG-VS to complex molecular interfaces has been limited by the ability to abstract quantitative information from SFG-VS experiments. In this review, we try to make assessments of the limitations, issues and techniques as well as methodologies in quantitative orientational and spectral analysis with SFG-VS. Based on these assessments, we also try to summarize recent developments in methodologies on quantitative orientational and spectral analysis in SFG-VS, and their applications to detailed analysis of SFG-VS data of various vapour/neat liquid interfaces. A rigorous formulation of the polarization null angle (PNA) method is given for accurate determination of the orientational parameter D = /, and comparison between the PNA method with the commonly used polarization intensity ratio (PIR) method is discussed. The polarization and incident angle dependencies of the SFG-VS intensity are also reviewed, in the light of how experimental arrangements can be optimized to effectively abstract crucial information from the SFG-VS experiments. The values and models of the local field factors in the molecular layers are discussed. In order to examine the validity and limitations of the bond polarizability derivative model, the general expressions for molecular hyperpolarizability tensors and their expression with the bond polarizability derivative model for C3v, C2v and C∞v molecular groups are given in the two appendixes. We show that the bond polarizability derivative model can quantitatively describe many aspects of the intensities observed in the SFG-VS spectrum of the vapour/neat liquid interfaces in different polarizations. Using the polarization analysis in SFG-VS, polarization selection rules or guidelines are developed for assignment of the SFG-VS spectrum. Using the selection rules, SFG-VS spectra of vapour/diol, and vapour/n-normal alcohol (n˜ 1-8) interfaces are assigned, and some of the ambiguity and confusion, as well as their implications in previous IR and Raman assignment, are duly discussed. The ability to assign a SFG-VS spectrum using the polarization selection rules makes SFG-VS not only an effective and useful vibrational spectroscopy technique for interface studies, but also a complementary vibrational spectroscopy method in general condensed phase studies. These developments will put quantitative orientational and spectral analysis in SFG-VS on a more solid foundation. The formulations, concepts and issues discussed in this review are expected to find broad applications for investigations on molecular interfaces in the future.

Development of quantitative structure-activity relationships and its application in rational drug design.

PubMed

Yang, Guang-Fu; Huang, Xiaoqin

2006-01-01

Over forty years have elapsed since Hansch and Fujita published their pioneering work of quantitative structure-activity relationships (QSAR). Following the introduction of Comparative Molecular Field Analysis (CoMFA) by Cramer in 1998, other three-dimensional QSAR methods have been developed. Currently, combination of classical QSAR and other computational techniques at three-dimensional level is of greatest interest and generally used in the process of modern drug discovery and design. During the last several decades, a number of different mythologies incorporating a range of molecular descriptors and different statistical regression ways have been proposed and successfully applied in developing of new drugs, thus QSAR method has been proven to be indispensable in not only the reliable prediction of specific properties of new compounds, but also the help to elucidate the possible molecular mechanism of the receptor-ligand interactions. Here, we review the recent developments in QSAR and their applications in rational drug design, focusing on the reasonable selection of novel molecular descriptors and the construction of predictive QSAR models by the help of advanced computational techniques.

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

PubMed

Caetano, Fabiana A; Dirk, Brennan S; Tam, Joshua H K; Cavanagh, P Craig; Goiko, Maria; Ferguson, Stephen S G; Pasternak, Stephen H; Dikeakos, Jimmy D; de Bruyn, John R; Heit, Bryan

2015-12-01

Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

CHARMM: The Biomolecular Simulation Program

PubMed Central

Brooks, B.R.; Brooks, C.L.; MacKerell, A.D.; Nilsson, L.; Petrella, R.J.; Roux, B.; Won, Y.; Archontis, G.; Bartels, C.; Boresch, S.; Caflisch, A.; Caves, L.; Cui, Q.; Dinner, A.R.; Feig, M.; Fischer, S.; Gao, J.; Hodoscek, M.; Im, W.; Kuczera, K.; Lazaridis, T.; Ma, J.; Ovchinnikov, V.; Paci, E.; Pastor, R.W.; Post, C.B.; Pu, J.Z.; Schaefer, M.; Tidor, B.; Venable, R. M.; Woodcock, H. L.; Wu, X.; Yang, W.; York, D.M.; Karplus, M.

2009-01-01

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. In addition, the CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This paper provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM paper in 1983. PMID:19444816

Kinetic Analysis of a Molecular Model of the Budding Yeast Cell Cycle

PubMed Central

Chen, Katherine C.; Csikasz-Nagy, Attila; Gyorffy, Bela; Val, John; Novak, Bela; Tyson, John J.

2000-01-01

The molecular machinery of cell cycle control is known in more detail for budding yeast, Saccharomyces cerevisiae, than for any other eukaryotic organism. In recent years, many elegant experiments on budding yeast have dissected the roles of cyclin molecules (Cln1–3 and Clb1–6) in coordinating the events of DNA synthesis, bud emergence, spindle formation, nuclear division, and cell separation. These experimental clues suggest a mechanism for the principal molecular interactions controlling cyclin synthesis and degradation. Using standard techniques of biochemical kinetics, we convert the mechanism into a set of differential equations, which describe the time courses of three major classes of cyclin-dependent kinase activities. Model in hand, we examine the molecular events controlling “Start” (the commitment step to a new round of chromosome replication, bud formation, and mitosis) and “Finish” (the transition from metaphase to anaphase, when sister chromatids are pulled apart and the bud separates from the mother cell) in wild-type cells and 50 mutants. The model accounts for many details of the physiology, biochemistry, and genetics of cell cycle control in budding yeast. PMID:10637314

Studying molecular changes during gravity perception and response in a single cell.

PubMed

Cannon, Ashley E; Salmi, Mari L; Bushart, Thomas J; Roux, Stanley J

2015-01-01

Early studies revealed a highly predictable pattern of gravity-directed growth and development in Ceratopteris richardii spores. This makes the spores a valuable model system for the study of how a single cell senses and responds to the force of gravity. Gravity regulates both the direction and magnitude of a trans-cell calcium current in germinating spores, and the orientation of this current predicts the polarization of spore development. Molecular techniques have been developed to evaluate the transcriptomic and proteomic profiles of spores before and after gravity establishes the polarity of their development. Here we describe these techniques, along with protocols for sterilizing the spores, sowing them in a solid or liquid growth media, and evaluating germination.

Imaging molecular dynamics in vivo--from cell biology to animal models.

PubMed

Timpson, Paul; McGhee, Ewan J; Anderson, Kurt I

2011-09-01

Advances in fluorescence microscopy have enabled the study of membrane diffusion, cell adhesion and signal transduction at the molecular level in living cells grown in culture. By contrast, imaging in living organisms has primarily been restricted to the localization and dynamics of cells in tissues. Now, imaging of molecular dynamics is on the cusp of progressing from cell culture to living tissue. This transition has been driven by the understanding that the microenvironment critically determines many developmental and pathological processes. Here, we review recent progress in fluorescent protein imaging in vivo by drawing primarily on cancer-related studies in mice. We emphasize the need for techniques that can be easily combined with genetic models and complement fluorescent protein imaging by providing contextual information about the cellular environment. In this Commentary we will consider differences between in vitro and in vivo experimental design and argue for an approach to in vivo imaging that is built upon the use of intermediate systems, such as 3-D and explant culture models, which offer flexibility and control that is not always available in vivo. Collectively, these methods present a paradigm shift towards the molecular-level investigation of disease and therapy in animal models of disease.

3D-Pharmacophore Identification for κ-Opioid Agonists Using Ligand-Based Drug-Design Techniques

NASA Astrophysics Data System (ADS)

Yamaotsu, Noriyuki; Hirono, Shuichi

A selective κ-opioid receptor (KOR) agonist might act as a powerful analgesic without the side effects of μ-opioid receptor-selective drugs such as morphine. The eight classes of known KOR agonists have different chemical structures, making it difficult to construct a pharmacophore model that takes them all into account. Here, we summarize previous efforts to identify the pharmacophore for κ-opioid agonists and propose a new three-dimensional pharmacophore model that encompasses the κ-activities of all classes. This utilizes conformational sampling of agonists by high-temperature molecular dynamics and pharmacophore extraction through a series of molecular superpositions.

Guidance on individual monitoring programmes for radioisotopic techniques in molecular and cellular biology.

PubMed

Macías, M T; Navarro, T; Lavara, A; Robredo, L M; Sierra, I; Lopez, M A

2003-01-01

The radioisotope techniques used in molecular and cellular biology involve external and internal irradiation risk. The personal dosemeter may be a reasonable indicator for external irradiation. However, it is necessary to control the possible internal contamination associated with the development of these techniques. The aim of this project is to analyse the most usual techniques and to establish programmes of internal monitoring for specific radionuclides (32P, 35S, 14C, 3H, 125I and 131I). To elaborate these programmes it was necessary to analyse the radioisotope techniques. Two models have been applied (NRPB and IAEA) to the more significant techniques, according to the physical and chemical nature of the radionuclides, their potential importance in occupational exposure and the possible injury to the genetic material of the cell. The results allowed the identification of the techniques with possible risk of internal contamination. It was necessary to identify groups of workers that require individual monitoring. The risk groups have been established among the professionals exposed, according to different parameters: the general characteristics of receptor, the radionuclides used (the same user can work with one, two or three radionuclides at the same time) and the results of the models applied. Also a control group was established. The study of possible intakes in these groups has been made by urinalysis and whole-body counter. The theoretical results are coherent with the experimental results. They have allowed guidance to individual monitoring to be proposed. Basically, the document shows: (1) the analysis of the radiosotopic techniques, taking into account the special containment equipment; (2) the establishment of the need of individual monitoring; and (3) the required frequency of measurements in a routine programme.

Structural characterisation of medically relevant protein assemblies by integrating mass spectrometry with computational modelling.

PubMed

Politis, Argyris; Schmidt, Carla

2018-03-20

Structural mass spectrometry with its various techniques is a powerful tool for the structural elucidation of medically relevant protein assemblies. It delivers information on the composition, stoichiometries, interactions and topologies of these assemblies. Most importantly it can deal with heterogeneous mixtures and assemblies which makes it universal among the conventional structural techniques. In this review we summarise recent advances and challenges in structural mass spectrometric techniques. We describe how the combination of the different mass spectrometry-based methods with computational strategies enable structural models at molecular levels of resolution. These models hold significant potential for helping us in characterizing the function of protein assemblies related to human health and disease. In this review we summarise the techniques of structural mass spectrometry often applied when studying protein-ligand complexes. We exemplify these techniques through recent examples from literature that helped in the understanding of medically relevant protein assemblies. We further provide a detailed introduction into various computational approaches that can be integrated with these mass spectrometric techniques. Last but not least we discuss case studies that integrated mass spectrometry and computational modelling approaches and yielded models of medically important protein assembly states such as fibrils and amyloids. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Ab Initio Studies of Shock-Induced Chemical Reactions of Inter-Metallics

NASA Astrophysics Data System (ADS)

Zaharieva, Roussislava; Hanagud, Sathya

2009-06-01

Shock-induced and shock assisted chemical reactions of intermetallic mixtures are studied by many researchers, using both experimental and theoretical techniques. The theoretical studies are primarily at continuum scales. The model frameworks include mixture theories and meso-scale models of grains of porous mixtures. The reaction models vary from equilibrium thermodynamic model to several non-equilibrium thermodynamic models. The shock-effects are primarily studied using appropriate conservation equations and numerical techniques to integrate the equations. All these models require material constants from experiments and estimates of transition states. Thus, the objective of this paper is to present studies based on ab initio techniques. The ab inito studies, to date, use ab inito molecular dynamics. This paper presents a study that uses shock pressures, and associated temperatures as starting variables. Then intermetallic mixtures are modeled as slabs. The required shock stresses are created by straining the lattice. Then, ab initio binding energy calculations are used to examine the stability of the reactions. Binding energies are obtained for different strain components super imposed on uniform compression and finite temperatures. Then, vibrational frequencies and nudge elastic band techniques are used to study reactivity and transition states. Examples include Ni and Al.

Diagnostic imaging advances in murine models of colitis.

PubMed

Brückner, Markus; Lenz, Philipp; Mücke, Marcus M; Gohar, Faekah; Willeke, Peter; Domagk, Dirk; Bettenworth, Dominik

2016-01-21

Inflammatory bowel diseases (IBD) such as Crohn's disease and ulcerative colitis are chronic-remittent inflammatory disorders of the gastrointestinal tract still evoking challenging clinical diagnostic and therapeutic situations. Murine models of experimental colitis are a vital component of research into human IBD concerning questions of its complex pathogenesis or the evaluation of potential new drugs. To monitor the course of colitis, to the present day, classical parameters like histological tissue alterations or analysis of mucosal cytokine/chemokine expression often require euthanasia of animals. Recent advances mean revolutionary non-invasive imaging techniques for in vivo murine colitis diagnostics are increasingly available. These novel and emerging imaging techniques not only allow direct visualization of intestinal inflammation, but also enable molecular imaging and targeting of specific alterations of the inflamed murine mucosa. For the first time, in vivo imaging techniques allow for longitudinal examinations and evaluation of intra-individual therapeutic response. This review discusses the latest developments in the different fields of ultrasound, molecularly targeted contrast agent ultrasound, fluorescence endoscopy, confocal laser endomicroscopy as well as tomographic imaging with magnetic resonance imaging, computed tomography and fluorescence-mediated tomography, discussing their individual limitations and potential future diagnostic applications in the management of human patients with IBD.

[The use of molecular biology techniques in the articles published in Revista Médica de Chile].

PubMed

Herskovic, V; Jacard, M; Reyes, H

2000-04-01

Molecular biology is a new branch of biological sciences, with novel laboratory techniques that are being progressively applied into biomedical and clinical research and, furthermore, into medical practice. To evaluate the use of molecular biology techniques in Chilean biomedical and clinical research and its evolution in the recent decade. All papers published as research articles, clinical experiences or case reports, in Revista Médica de Chile, during two time periods: 1987-1989 and 1997-1999, were reviewed to find out whether molecular biology techniques had been used or not. This journal publishes roughly 40% of papers generated in Chile, in biomedical or clinical topics, while another 15% appears in foreign journals. Among 341 papers published in 1987-1989, 57 (16.7%) had used one or more molecular biology techniques; in contrast, among 318 papers published in 1997-1999, 91 (28.8%) had used them (p < 0.001). Most papers using molecular biology techniques were research articles. Immunology, genetics, endocrinology, hematology, hepatology and rheumatology were the specialties providing a greater number and proportion of papers using molecular biology techniques. Chilean universities were the main institutions sponsoring these articles and FONDECYT (the Chilean Government Research Granting Office) was the main source of funding. The University of Chile (State-owned) provided most centers where these publications had been generated, followed by the Pontifical Catholic University of Chile. Molecular biology techniques have been rapidly and progressively incorporated as research tools in biomedicine and clinical medicine, in Chile. At the present time, these techniques are predominantly used in research conducted in University settings and funded by Governmental research grants.

3D-liquid chromatography as a complex mixture characterization tool for knowledge-based downstream process development.

PubMed

Hanke, Alexander T; Tsintavi, Eleni; Ramirez Vazquez, Maria Del Pilar; van der Wielen, Luuk A M; Verhaert, Peter D E M; Eppink, Michel H M; van de Sandt, Emile J A X; Ottens, Marcel

2016-09-01

Knowledge-based development of chromatographic separation processes requires efficient techniques to determine the physicochemical properties of the product and the impurities to be removed. These characterization techniques are usually divided into approaches that determine molecular properties, such as charge, hydrophobicity and size, or molecular interactions with auxiliary materials, commonly in the form of adsorption isotherms. In this study we demonstrate the application of a three-dimensional liquid chromatography approach to a clarified cell homogenate containing a therapeutic enzyme. Each separation dimension determines a molecular property relevant to the chromatographic behavior of each component. Matching of the peaks across the different separation dimensions and against a high-resolution reference chromatogram allows to assign the determined parameters to pseudo-components, allowing to determine the most promising technique for the removal of each impurity. More detailed process design using mechanistic models requires isotherm parameters. For this purpose, the second dimension consists of multiple linear gradient separations on columns in a high-throughput screening compatible format, that allow regression of isotherm parameters with an average standard error of 8%. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1283-1291, 2016. © 2016 American Institute of Chemical Engineers.

Graphene symmetry-breaking with molecular adsorbates: modeling and experiment

NASA Astrophysics Data System (ADS)

Groce, M. A.; Hawkins, M. K.; Wang, Y. L.; Cullen, W. G.; Einstein, T. L.

2012-02-01

Graphene's structure and electronic properties provide a framework for understanding molecule-substrate interactions and developing techniques for band gap engineering. Controlled deposition of molecular adsorbates can create superlattices which break the degeneracy of graphene's two-atom unit cell, opening a band gap. We simulate scanning tunneling microscopy and spectroscopy measurements for a variety of organic molecule/graphene systems, including pyridine, trimesic acid, and isonicotinic acid, based on density functional theory calculations using VASP. We also compare our simulations to ultra-high vacuum STM and STS results.

Modeling Amorphous Microporous Polymers for CO2 Capture and Separations.

PubMed

Kupgan, Grit; Abbott, Lauren J; Hart, Kyle E; Colina, Coray M

2018-06-13

This review concentrates on the advances of atomistic molecular simulations to design and evaluate amorphous microporous polymeric materials for CO 2 capture and separations. A description of atomistic molecular simulations is provided, including simulation techniques, structural generation approaches, relaxation and equilibration methodologies, and considerations needed for validation of simulated samples. The review provides general guidelines and a comprehensive update of the recent literature (since 2007) to promote the acceleration of the discovery and screening of amorphous microporous polymers for CO 2 capture and separation processes.

New Researches and Application Progress of Commonly Used Optical Molecular Imaging Technology

PubMed Central

Chen, Zhi-Yi; Yang, Feng; Lin, Yan; Zhou, Qiu-Lan; Liao, Yang-Ying

2014-01-01

Optical molecular imaging, a new medical imaging technique, is developed based on genomics, proteomics and modern optical imaging technique, characterized by non-invasiveness, non-radiativity, high cost-effectiveness, high resolution, high sensitivity and simple operation in comparison with conventional imaging modalities. Currently, it has become one of the most widely used molecular imaging techniques and has been applied in gene expression regulation and activity detection, biological development and cytological detection, drug research and development, pathogenesis research, pharmaceutical effect evaluation and therapeutic effect evaluation, and so forth, This paper will review the latest researches and application progresses of commonly used optical molecular imaging techniques such as bioluminescence imaging and fluorescence molecular imaging. PMID:24696850

Manipulation of individual hyperfine states in cold trapped molecular ions and application to HD+ frequency metrology.

PubMed

Bressel, U; Borodin, A; Shen, J; Hansen, M; Ernsting, I; Schiller, S

2012-05-04

Advanced techniques for manipulation of internal states, standard in atomic physics, are demonstrated for a charged molecular species for the first time. We address individual hyperfine states of rovibrational levels of a diatomic ion by optical excitation of individual hyperfine transitions, and achieve controlled transfer of population into a selected hyperfine state. We use molecular hydrogen ions (HD+) as a model system and employ a novel frequency-comb-based, continuous-wave 5  μm laser spectrometer. The achieved spectral resolution is the highest obtained so far in the optical domain on a molecular ion species. As a consequence, we are also able to perform the most precise test yet of the ab initio theory of a molecule.

Molecular composition of recycled organic wastes, as determined by solid-state 13C NMR and elemental analyses.

PubMed

Eldridge, S M; Chen, C R; Xu, Z H; Nelson, P N; Boyd, S E; Meszaros, I; Chan, K Y

2013-11-01

Using solid state (13)C NMR data and elemental composition in a molecular mixing model, we estimated the molecular components of the organic matter in 16 recycled organic (RO) wastes representative of the major materials generated in the Sydney basin area. Close correspondence was found between the measured NMR signal intensities and those predicted by the model for all RO wastes except for poultry manure char. Molecular nature of the organic matter differed widely between the RO wastes. As a proportion of organic C, carbohydrate C ranged from 0.07 to 0.63, protein C from <0.01 to 0.66, lignin C from <0.01 to 0.31, aliphatic C from 0.09 to 0.73, carbonyl C from 0.02 to 0.23, and char C from 0 to 0.45. This method is considered preferable to techniques involving imprecise extraction methods for RO wastes. Molecular composition data has great potential as a predictor of RO waste soil carbon and nutrient outcomes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Molecular Phenotyping Combines Molecular Information, Biological Relevance, and Patient Data to Improve Productivity of Early Drug Discovery.

PubMed

Drawnel, Faye Marie; Zhang, Jitao David; Küng, Erich; Aoyama, Natsuyo; Benmansour, Fethallah; Araujo Del Rosario, Andrea; Jensen Zoffmann, Sannah; Delobel, Frédéric; Prummer, Michael; Weibel, Franziska; Carlson, Coby; Anson, Blake; Iacone, Roberto; Certa, Ulrich; Singer, Thomas; Ebeling, Martin; Prunotto, Marco

2017-05-18

Today, novel therapeutics are identified in an environment which is intrinsically different from the clinical context in which they are ultimately evaluated. Using molecular phenotyping and an in vitro model of diabetic cardiomyopathy, we show that by quantifying pathway reporter gene expression, molecular phenotyping can cluster compounds based on pathway profiles and dissect associations between pathway activities and disease phenotypes simultaneously. Molecular phenotyping was applicable to compounds with a range of binding specificities and triaged false positives derived from high-content screening assays. The technique identified a class of calcium-signaling modulators that can reverse disease-regulated pathways and phenotypes, which was validated by structurally distinct compounds of relevant classes. Our results advocate for application of molecular phenotyping in early drug discovery, promoting biological relevance as a key selection criterion early in the drug development cascade. Copyright © 2017 Elsevier Ltd. All rights reserved.

Pyrogallol-imprinted polymers with methyl methacrylate via precipitation polymerization

NASA Astrophysics Data System (ADS)

Mehamod, Faizatul Shimal; Othman, Nor Amira; Bulat, Ku Halim Ku; Suah, Faiz Bukhari Mohd

2018-06-01

Molecular simulation techniques are important to study the understanding of chemical and physical properties of any material. Computational modeling is considered as time reducer in finding the best recipes for Molecularly-Imprinted Polymers (MIPs). In this study, Pyrogallol-imprinted polymers (PIP) and non-imprinted polymers (NIPs) were synthesized via precipitation polymerization using Pyrogallol (Py), methyl methacrylate (MMA), divinylbenzene (DVB) as template, functional monomer and cross-linker, respectively. The recipe was according to the results from computational techniques. The synthesized PIP and NIPs were characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) and UV-visible spectroscopy (UV-vis). Studies on adsorption isotherm showed that PIP and NIPs follow Scatchard isotherm models. Sorption kinetic study found that PIP and NIPs follow pseudo-second order which indicates the rate-limiting step is the surface adsorption. The imprinting factor of PIP was determined by selectivity study and showed the value of k >1, which proved that PIP was selective toward Pyrogallol compared to NIP.

Accelerating Monte Carlo molecular simulations by reweighting and reconstructing Markov chains: Extrapolation of canonical ensemble averages and second derivatives to different temperature and density conditions

NASA Astrophysics Data System (ADS)

Kadoura, Ahmad; Sun, Shuyu; Salama, Amgad

2014-08-01

Accurate determination of thermodynamic properties of petroleum reservoir fluids is of great interest to many applications, especially in petroleum engineering and chemical engineering. Molecular simulation has many appealing features, especially its requirement of fewer tuned parameters but yet better predicting capability; however it is well known that molecular simulation is very CPU expensive, as compared to equation of state approaches. We have recently introduced an efficient thermodynamically consistent technique to regenerate rapidly Monte Carlo Markov Chains (MCMCs) at different thermodynamic conditions from the existing data points that have been pre-computed with expensive classical simulation. This technique can speed up the simulation more than a million times, making the regenerated molecular simulation almost as fast as equation of state approaches. In this paper, this technique is first briefly reviewed and then numerically investigated in its capability of predicting ensemble averages of primary quantities at different neighboring thermodynamic conditions to the original simulated MCMCs. Moreover, this extrapolation technique is extended to predict second derivative properties (e.g. heat capacity and fluid compressibility). The method works by reweighting and reconstructing generated MCMCs in canonical ensemble for Lennard-Jones particles. In this paper, system's potential energy, pressure, isochoric heat capacity and isothermal compressibility along isochors, isotherms and paths of changing temperature and density from the original simulated points were extrapolated. Finally, an optimized set of Lennard-Jones parameters (ε, σ) for single site models were proposed for methane, nitrogen and carbon monoxide.

Molecular pathology of adamantinomatous craniopharyngioma: review and opportunities for practice.

PubMed

Apps, John Richard; Martinez-Barbera, Juan Pedro

2016-12-01

Since the first identification of CTNNB1 mutations in adamantinomatous craniopharyngioma (ACP), much has been learned about the molecular pathways and processes that are disrupted in ACP pathogenesis. To date this understanding has not translated into tangible patient benefit. The recent development of novel techniques and a range of preclinical models now provides an opportunity to begin to support treatment decisions and develop new therapeutics based on molecular pathology. In this review the authors summarize many of the key findings and pathways implicated in ACP pathogenesis and discuss the challenges that need to be tackled to translate these basic science findings for the benefit of patients.

Gas-phase reactions in extraterrestrial environments: laboratory investigations by crossed molecular beams.

PubMed

Balucani, Nadia; Casavecchia, Piergiorgio

2006-12-01

We have investigated gas-phase reactions of N((2)D) with the most abundant hydrocarbons in the atmosphere of Titan by the crossed molecular beam technique. In all cases, molecular products containing a novel CN bond are formed, thus suggesting possible routes of formation of gas-phase nitriles in the atmosphere of Titan and primordial Earth. The same approach has been recently extended to the study of radical-radical reactions, such as the reaction of atomic oxygen with the CH(3) and C(3)H(5) radicals. Products other than those already considered in the modeling of planetary atmospheres and interstellar medium have been identified.

Future Technology-Driven Revolutions in Military Operations. Results of a Workshop

DTIC Science & Technology

1994-01-01

sensor missions. "• Biomolecular Electronics - The use of techniques from molecular biology and biotechnology to develop new molecular electronic materials...34* Biomolecular electronics - The use of techniques from molecular biology and biotechnology to develop new molecular electronic materials, components, and...occurring in molecular biology . 42 Biotechnology Molecular Biologists Arm Develoni "Magical" Caoabilitles "• To mynthsieh genm (frm satch) with conboi

Generalized Green's function molecular dynamics for canonical ensemble simulations

NASA Astrophysics Data System (ADS)

Coluci, V. R.; Dantas, S. O.; Tewary, V. K.

2018-05-01

The need of small integration time steps (˜1 fs) in conventional molecular dynamics simulations is an important issue that inhibits the study of physical, chemical, and biological systems in real timescales. Additionally, to simulate those systems in contact with a thermal bath, thermostating techniques are usually applied. In this work, we generalize the Green's function molecular dynamics technique to allow simulations within the canonical ensemble. By applying this technique to one-dimensional systems, we were able to correctly describe important thermodynamic properties such as the temperature fluctuations, the temperature distribution, and the velocity autocorrelation function. We show that the proposed technique also allows the use of time steps one order of magnitude larger than those typically used in conventional molecular dynamics simulations. We expect that this technique can be used in long-timescale molecular dynamics simulations.

Course-based undergraduate research experiences in molecular biosciences-patterns, trends, and faculty support.

PubMed

Wang, Jack T H

2017-08-15

Inquiry-driven learning, research internships and course-based undergraduate research experiences all represent mechanisms through which educators can engage undergraduate students in scientific research. In life sciences education, the benefits of undergraduate research have been thoroughly evaluated, but limitations in infrastructure and training can prevent widespread uptake of these practices. It is not clear how faculty members can integrate complex laboratory techniques and equipment into their unique context, while finding the time and resources to implement undergraduate research according to best practice guidelines. This review will go through the trends and patterns in inquiry-based undergraduate life science projects with particular emphasis on molecular biosciences-the research-aligned disciplines of biochemistry, molecular cell biology, microbiology, and genomics and bioinformatics. This will provide instructors with an overview of the model organisms, laboratory techniques and research questions that are adaptable for semester-long projects, and serve as starting guidelines for course-based undergraduate research. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Supramolecular Systems and Chemical Reactions in Single-Molecule Break Junctions.

PubMed

Li, Xiaohui; Hu, Duan; Tan, Zhibing; Bai, Jie; Xiao, Zongyuan; Yang, Yang; Shi, Jia; Hong, Wenjing

2017-04-01

The major challenges of molecular electronics are the understanding and manipulation of the electron transport through the single-molecule junction. With the single-molecule break junction techniques, including scanning tunneling microscope break junction technique and mechanically controllable break junction technique, the charge transport through various single-molecule and supramolecular junctions has been studied during the dynamic fabrication and continuous characterization of molecular junctions. This review starts from the charge transport characterization of supramolecular junctions through a variety of noncovalent interactions, such as hydrogen bond, π-π interaction, and electrostatic force. We further review the recent progress in constructing highly conductive molecular junctions via chemical reactions, the response of molecular junctions to external stimuli, as well as the application of break junction techniques in controlling and monitoring chemical reactions in situ. We suggest that beyond the measurement of single molecular conductance, the single-molecule break junction techniques provide a promising access to study molecular assembly and chemical reactions at the single-molecule scale.

Implications of recent research on microstructure modifications, through heat-related processing and trait alteration to bio-functions, molecular thermal stability and mobility, metabolic characteristics and nutrition in cool-climate cereal grains and other types of seeds with advanced molecular techniques.

PubMed

Ying, Yuguang; Zhang, Huihua; Yu, Peiqiang

2018-02-16

The cutting-edge synchrotron radiation based and globar-sourced vibrational infrared microspectroscopy have recently been developed. These novel techniques are able to reveal structure features at cellular and molecular levels with the tested tissues being intact. However, to date, the advanced techniques are unfamiliar or unknown to food and feed scientists and have not been used to study the molecular structure changes in cool-climate cereal grain seeds and other types of bio-oil and bioenergy seeds. This article aims to provide some recent research in cool-climate cereal grains and other types of seeds on molecular structures and metabolic characteristics of carbohydrate and protein, and implication of microstructure modification through heat-related processing and trait alteration to bio-functions, molecular thermal stability and mobility, and nutrition with advanced molecular techniques- synchrotron radiation based and globar-sourced vibrational infrared microspectroscopy in the areas of (1) Inherent microstructure of cereal grain seeds; (2) The nutritional values of cereal grains; (3) Impact and modification of heat-related processing to cereal grain; (4) Conventional nutrition evaluation methodology; (5) Synchrotron radiation-based and globar-sourced vibrational (micro)-spectroscopy for molecular structure study and molecular thermal stability and mobility, and (6) Recent molecular spectroscopic technique applications in research on raw, traits altered and processed cool-climate cereal grains and other types of seeds. The information described in this article gives better insights of research progress and update in cool-climate cereal grains and other seeds with advanced molecular techniques.

Modeling techniques and fluorescence imaging investigation of the interactions of an anthraquinone derivative with HSA and ctDNA

NASA Astrophysics Data System (ADS)

Fu, Zheng; Cui, Yanrui; Cui, Fengling; Zhang, Guisheng

2016-01-01

A new anthraquinone derivative (AORha) was synthesized. Its interactions with human serum albumin (HSA) and calf thymus DNA (ctDNA) were investigated by fluorescence spectroscopy, UV-visible absorption spectroscopy and molecular modeling. Cell viability assay and cell imaging experiment were performed using cervical cancer cells (HepG2 cells). The fluorescence results revealed that the quenching mechanism was static quenching. At different temperatures (290, 300, 310 K), the binding constants (K) and the number of binding sites (n) were determined, respectively. The positive ΔH and ΔS values showed that the binding of AORha with HSA was hydrophobic force, which was identical with the molecular docking result. Studying the fluorescence spectra, UV spectra and molecular modeling also verified that the binding mode of AORha and ctDNA might be intercalative. When HepG2 cells were treated with AORha, the fluorescence became brighter and turned green, which could be used for bioimaging.

Modeling techniques and fluorescence imaging investigation of the interactions of an anthraquinone derivative with HSA and ctDNA.

PubMed

Fu, Zheng; Cui, Yanrui; Cui, Fengling; Zhang, Guisheng

2016-01-15

A new anthraquinone derivative (AORha) was synthesized. Its interactions with human serum albumin (HSA) and calf thymus DNA (ctDNA) were investigated by fluorescence spectroscopy, UV-visible absorption spectroscopy and molecular modeling. Cell viability assay and cell imaging experiment were performed using cervical cancer cells (HepG2 cells). The fluorescence results revealed that the quenching mechanism was static quenching. At different temperatures (290, 300, 310 K), the binding constants (K) and the number of binding sites (n) were determined, respectively. The positive ΔH and ΔS values showed that the binding of AORha with HSA was hydrophobic force, which was identical with the molecular docking result. Studying the fluorescence spectra, UV spectra and molecular modeling also verified that the binding mode of AORha and ctDNA might be intercalative. When HepG2 cells were treated with AORha, the fluorescence became brighter and turned green, which could be used for bioimaging. Copyright © 2015 Elsevier B.V. All rights reserved.

Modeling of substrate and inhibitor binding to phospholipase A2.

PubMed

Sessions, R B; Dauber-Osguthorpe, P; Campbell, M M; Osguthorpe, D J

1992-09-01

Molecular graphics and molecular mechanics techniques have been used to study the mode of ligand binding and mechanism of action of the enzyme phospholipase A2. A substrate-enzyme complex was constructed based on the crystal structure of the apoenzyme. The complex was minimized to relieve initial strain, and the structural and energetic features of the resultant complex analyzed in detail, at the molecular and residue level. The minimized complex was then used as a basis for examining the action of the enzyme on modified substrates, binding of inhibitors to the enzyme, and possible reaction intermediate complexes. The model is compatible with the suggested mechanism of hydrolysis and with experimental data about stereoselectivity, efficiency of hydrolysis of modified substrates, and inhibitor potency. In conclusion, the model can be used as a tool in evaluating new ligands as possible substrates and in the rational design of inhibitors, for the therapeutic treatment of diseases such as rheumatoid arthritis, atherosclerosis, and asthma.

New mathematic model for predicting chiral separation using molecular docking: mechanism of chiral recognition of triadimenol analogues.

PubMed

Zhang, Guoqing; Sun, Qingyan; Hou, Ying; Hong, Zhanying; Zhang, Jun; Zhao, Liang; Zhang, Hai; Chai, Yifeng

2009-07-01

The purpose of this paper was to study the enantioseparation mechanism of triadimenol compounds by carboxymethylated (CM)-beta-CD mediated CE. All the enantiomers were separated under the same experimental conditions to study the chiral recognition mechanism using a 30 mM sodium dihydrogen phosphate buffer at pH 2.2 adjusted by phosphoric acid. The inclusion courses between CM-beta-CD and enantiomers were investigated by the means of molecular docking technique. It was found that there were at least three points (one hydrophobic bond and two hydrogen bonds) involved in the interaction of each enantiomer with the chiral selectors. A new mathematic model has been built up based on the results of molecular mechanics calculations, which could analyze the relationship between the resolution of enantioseparation and the interaction energy in the docking area. Comparing the results of the separation by CE, the established mathematic model demonstrated good capability to predict chiral separation of triadimenol enantiomers using CM-beta-CD mediated CE.

Atomistic characterization of the active-site solvation dynamics of a model photocatalyst

DOE PAGES

van Driel, Tim B.; Kjær, Kasper S.; Hartsock, Robert W.; ...

2016-11-28

The interactions between the reactive excited state of molecular photocatalysts and surrounding solvent dictate reaction mechanisms and pathways, but are not readily accessible to conventional optical spectroscopic techniques. Here we report an investigation of the structural and solvation dynamics following excitation of a model photocatalytic molecular system [Ir 2(dimen) 4] 2+, where dimen is para-diisocyanomenthane. The time-dependent structural changes in this model photocatalyst, as well as the changes in the solvation shell structure, have been measured with ultrafast diffuse X-ray scattering and simulated with Born-Oppenheimer Molecular Dynamics. Both methods provide direct access to the solute–solvent pair distribution function, enabling themore » solvation dynamics around the catalytically active iridium sites to be robustly characterized. Our results provide evidence for the coordination of the iridium atoms by the acetonitrile solvent and demonstrate the viability of using diffuse X-ray scattering at free-electron laser sources for studying the dynamics of photocatalysis.« less

Incorporation of genomic information into genetic evaluation: U. S. beef industry as a model

USDA-ARS?s Scientific Manuscript database

In his presentation, Dr. Kuehn described approaches for using information garnered through developments in genomics to improve the accuracy of genetic evaluation. He considered the history of these molecular-based techniques, including their strengths and potential weaknesses, and his experiences wi...

Developing sensor activity relationships for the JPL electronic nose sensors using molecular modeling and QSAR techniques

NASA Technical Reports Server (NTRS)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Jewell, A. D.; Zhou, H.; Manatt, K.; Kisor, A. K.

2005-01-01

We report a Quantitative Structure-Activity Relationships (QSAR) study using Genetic Function Approximations (GFA) to describe the polymer-carbon composite sensor activities in the JPL Electronic Nose, when exposed to chemical vapors at parts-per-million concentration levels.

A Laboratory Practical Illustrating the Use of the ChIP-qPCR Method in a Robust Model: Estrogen Receptor Alpha Immunoprecipitation Using MCF-7 Culture Cells

ERIC Educational Resources Information Center

Lacazette, Eric

2017-01-01

Chromatin immunoprecipitation followed by qPCR analysis (ChIP-qPCR) is a widely used technique to study gene expression. A large number of students in molecular biology and more generally in life sciences will be confronted with the use of this technique, which is quite difficult to set up and can lead to misinterpretation if not carefully…

Coarse-Grained Models Reveal Functional Dynamics – II. Molecular Dynamics Simulation at the Coarse-Grained Level – Theories and Biological Applications

PubMed Central

Chng, Choon-Peng; Yang, Lee-Wei

2008-01-01

Molecular dynamics (MD) simulation has remained the most indispensable tool in studying equilibrium/non-equilibrium conformational dynamics since its advent 30 years ago. With advances in spectroscopy accompanying solved biocomplexes in growing sizes, sampling their dynamics that occur at biologically interesting spatial/temporal scales becomes computationally intractable; this motivated the use of coarse-grained (CG) approaches. CG-MD models are used to study folding and conformational transitions in reduced resolution and can employ enlarged time steps due to the absence of some of the fastest motions in the system. The Boltzmann-Inversion technique, heavily used in parameterizing these models, provides a smoothed-out effective potential on which molecular conformation evolves at a faster pace thus stretching simulations into tens of microseconds. As a result, a complete catalytic cycle of HIV-1 protease or the assembly of lipid-protein mixtures could be investigated by CG-MD to gain biological insights. In this review, we survey the theories developed in recent years, which are categorized into Folding-based and Molecular-Mechanics-based. In addition, physical bases in the selection of CG beads/time-step, the choice of effective potentials, representation of solvent, and restoration of molecular representations back to their atomic details are systematically discussed. PMID:19812774

Notes on quantitative structure-properties relationships (QSPR) (1): A discussion on a QSPR dimensionality paradox (QSPR DP) and its quantum resolution.

PubMed

Carbó-Dorca, Ramon; Gallegos, Ana; Sánchez, Angel J

2009-05-01

Classical quantitative structure-properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations. From there, effective models for the computation of unknown properties of known molecular structures are obtained. However, the reduced descriptor dimension causes linear dependence within the set of discrete vector molecular representations, leading to positive semi-definite Gram matrices in molecular spaces. To resolve this QSPR dimensionality paradox (QSPR DP) here is proposed to adopt as starting point the quantum QSPR (QQSPR) computational framework perspective, where density functions act as infinite dimensional descriptors. The fundamental QQSPR equation, deduced from employing quantum expectation value numerical evaluation, can be approximately solved in order to obtain models exempt of the QSPR DP. The substitution of the quantum similarity matrix by an empirical Gram matrix in molecular spaces, build up with the original non manipulated discrete molecular descriptor vectors, permits to obtain classical QSPR models with the same characteristics as in QQSPR, that is: possessing a certain degree of causality and explicitly independent of the descriptor dimension. 2008 Wiley Periodicals, Inc.

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

Simplified molecular input line entry system-based: QSAR modelling for MAP kinase-interacting protein kinase (MNK1).

PubMed

Begum, S; Achary, P Ganga Raju

2015-01-01

Quantitative structure-activity relationship (QSAR) models were built for the prediction of inhibition (pIC50, i.e. negative logarithm of the 50% effective concentration) of MAP kinase-interacting protein kinase (MNK1) by 43 potent inhibitors. The pIC50 values were modelled with five random splits, with the representations of the molecular structures by simplified molecular input line entry system (SMILES). QSAR model building was performed by the Monte Carlo optimisation using three methods: classic scheme; balance of correlations; and balance correlation with ideal slopes. The robustness of these models were checked by parameters as rm(2), r(*)m(2), [Formula: see text] and randomisation technique. The best QSAR model based on single optimal descriptors was applied to study in vitro structure-activity relationships of 6-(4-(2-(piperidin-1-yl) ethoxy) phenyl)-3-(pyridin-4-yl) pyrazolo [1,5-a] pyrimidine derivatives as a screening tool for the development of novel potent MNK1 inhibitors. The effects of alkyl group, -OH, -NO2, F, Cl, Br, I, etc. on the IC50 values towards the inhibition of MNK1 were also reported.

Obstructive renal injury: from fluid mechanics to molecular cell biology.

PubMed

Ucero, Alvaro C; Gonçalves, Sara; Benito-Martin, Alberto; Santamaría, Beatriz; Ramos, Adrian M; Berzal, Sergio; Ruiz-Ortega, Marta; Egido, Jesus; Ortiz, Alberto

2010-04-22

Urinary tract obstruction is a frequent cause of renal impairment. The physiopathology of obstructive nephropathy has long been viewed as a mere mechanical problem. However, recent advances in cell and systems biology have disclosed a complex physiopathology involving a high number of molecular mediators of injury that lead to cellular processes of apoptotic cell death, cell injury leading to inflammation and resultant fibrosis. Functional studies in animal models of ureteral obstruction using a variety of techniques that include genetically modified animals have disclosed an important role for the renin-angiotensin system, transforming growth factor-β1 (TGF-β1) and other mediators of inflammation in this process. In addition, high throughput techniques such as proteomics and transcriptomics have identified potential biomarkers that may guide clinical decision-making.

Molecular detection of pathogens in water--the pros and cons of molecular techniques.

PubMed

Girones, Rosina; Ferrús, Maria Antonia; Alonso, José Luis; Rodriguez-Manzano, Jesus; Calgua, Byron; Corrêa, Adriana de Abreu; Hundesa, Ayalkibet; Carratala, Anna; Bofill-Mas, Sílvia

2010-08-01

Pollution of water by sewage and run-off from farms produces a serious public health problem in many countries. Viruses, along with bacteria and protozoa in the intestine or in urine are shed and transported through the sewer system. Even in highly industrialized countries, pathogens, including viruses, are prevalent throughout the environment. Molecular methods are used to monitor viral, bacterial, and protozoan pathogens, and to track pathogen- and source-specific markers in the environment. Molecular techniques, specifically polymerase chain reaction-based methods, provide sensitive, rapid, and quantitative analytical tools with which to study such pathogens, including new or emerging strains. These techniques are used to evaluate the microbiological quality of food and water, and to assess the efficiency of virus removal in drinking and wastewater treatment plants. The range of methods available for the application of molecular techniques has increased, and the costs involved have fallen. These developments have allowed the potential standardization and automation of certain techniques. In some cases they facilitate the identification, genotyping, enumeration, viability assessment, and source-tracking of human and animal contamination. Additionally, recent improvements in detection technologies have allowed the simultaneous detection of multiple targets in a single assay. However, the molecular techniques available today and those under development require further refinement in order to be standardized and applicable to a diversity of matrices. Water disinfection treatments may have an effect on the viability of pathogens and the numbers obtained by molecular techniques may overestimate the quantification of infectious microorganisms. The pros and cons of molecular techniques for the detection and quantification of pathogens in water are discussed. (c) 2010 Elsevier Ltd. All rights reserved.

Raman spectroscopic analysis for gastric and colorectal cancer in surgical treatment toward molecular-guided surgery

NASA Astrophysics Data System (ADS)

Koga, Shigehiro; Watanabe, Yuji; Oshima, Yusuke

2018-02-01

Raman spectroscopy provides a wealth of diagnostic information to the surgeon with in situ cancer detection and label-free histopathology in intraoperative conditions. Raman spectroscopy is a promising optical technique which can analyze biological tissues with light scattering. The difference in frequencies between the incident light and the scattering light are called Raman shifts, which correspond to the vibrational energy of the molecular bonds. Raman spectrum gives information about the molecular structure and composition in biological specimens. We had been previously reported that Raman spectroscopy could distinguish various histological types of human lung cancer cells from normal cells in vitro, and also confirmed that Raman spectra obtained from cancer cells and their environment including other cells and extracellular matrix in xenograft models and spontaneous metastasis models were distinguishable using Raman spectroscopy combined with fluorescence microscopy and photoluminescence imaging. Malignancy can be characterized not only by the cancer cells but also by the environmental factors including immune cells, stroma cells, secretion vesicles and extracellular matrix, but to identify and detect cancer diagnostic biomarkers in vivo on Raman spectroscopy is still challenging. Here we investigate morphological and molecular dynamics in advanced cancer specimens obtained from patients. We are also constructing a customdesigned Raman spectral imaging system for both in vitro and in vivo assay of tumor tissues to reveal the metastasis process and to evaluate therapeutic effects of anti-cancer drugs and their drug delivery toward the clinical application of the technique.

Characterization and Higher-Order Structure Assessment of an Interchain Cysteine-Based ADC: Impact of Drug Loading and Distribution on the Mechanism of Aggregation.

PubMed

Guo, Jianxin; Kumar, Sandeep; Chipley, Mark; Marcq, Olivier; Gupta, Devansh; Jin, Zhaowei; Tomar, Dheeraj S; Swabowski, Cecily; Smith, Jacquelynn; Starkey, Jason A; Singh, Satish K

2016-03-16

The impact of drug loading and distribution on higher order structure and physical stability of an interchain cysteine-based antibody drug conjugate (ADC) has been studied. An IgG1 mAb was conjugated with a cytotoxic auristatin payload following the reduction of interchain disulfides. The 2-D LC-MS analysis shows that there is a preference for certain isomers within the various drug to antibody ratios (DARs). The physical stability of the unconjugated monoclonal antibody, the ADC, and isolated conjugated species with specific DAR, were compared using calorimetric, thermal, chemical denaturation and molecular modeling techniques, as well as techniques to assess hydrophobicity. The DAR was determined to have a significant impact on the biophysical properties and stability of the ADC. The CH2 domain was significantly perturbed in the DAR6 species, which was attributable to quaternary structural changes as assessed by molecular modeling. At accelerated storage temperatures, the DAR6 rapidly forms higher molecular mass species, whereas the DAR2 and the unconjugated mAb were largely stable. Chemical denaturation study indicates that DAR6 may form multimers while DAR2 and DAR4 primarily exist in monomeric forms in solution at ambient conditions. The physical state differences were correlated with a dramatic increase in the hydrophobicity and a reduction in the surface tension of the DAR6 compared to lower DAR species. Molecular modeling of the various DAR species and their conformers demonstrates that the auristatin-based linker payload directly contributes to the hydrophobicity of the ADC molecule. Higher order structural characterization provides insight into the impact of conjugation on the conformational and colloidal factors that determine the physical stability of cysteine-based ADCs, with implications for process and formulation development.

Noninvasive Detection and Imaging of Molecular Markers in Live Cardiomyocytes Derived from Human Embryonic Stem Cells

PubMed Central

Pascut, Flavius C.; Goh, Huey T.; Welch, Nathan; Buttery, Lee D.; Denning, Chris; Notingher, Ioan

2011-01-01

Raman microspectroscopy (RMS) was used to detect and image molecular markers specific to cardiomyocytes (CMs) derived from human embryonic stem cells (hESCs). This technique is noninvasive and thus can be used to discriminate individual live CMs within highly heterogeneous cell populations. Principal component analysis (PCA) of the Raman spectra was used to build a classification model for identification of individual CMs. Retrospective immunostaining imaging was used as the gold standard for phenotypic identification of each cell. We were able to discriminate CMs from other phenotypes with >97% specificity and >96% sensitivity, as calculated with the use of cross-validation algorithms (target 100% specificity). A comparison between Raman spectral images corresponding to selected Raman bands identified by the PCA model and immunostaining of the same cells allowed assignment of the Raman spectral markers. We conclude that glycogen is responsible for the discrimination of CMs, whereas myofibril proteins have a lesser contribution. This study demonstrates the potential of RMS for allowing the noninvasive phenotypic identification of hESC progeny. With further development, such label-free optical techniques may enable the separation of high-purity cell populations with mature phenotypes, and provide repeated measurements to monitor time-dependent molecular changes in live hESCs during differentiation in vitro. PMID:21190678

Modeling of lipase catalyzed ring-opening polymerization of epsilon-caprolactone.

PubMed

Sivalingam, G; Madras, Giridhar

2004-01-01

Enzymatic ring-opening polymerization of epsilon-caprolactone by various lipases was investigated in toluene at various temperatures. The determination of molecular weight and structural identification was carried out with gel permeation chromatography and proton NMR, respectively. Among the various lipases employed, an immobilized lipase from Candida antartica B (Novozym 435) showed the highest catalytic activity. The polymerization of epsilon-caprolactone by Novozym 435 showed an optimal temperature of 65 degrees C and an optimum toluene content of 50/50 v/v of toluene and epsilon-caprolactone. As lipases can degrade polyesters, a maximum in the molecular weight with time was obtained due to the competition of ring opening polymerization and degradation by specific chain end scission. The optimum temperature, toluene content, and the variation of molecular weight with time are consistent with earlier observations. A comprehensive model based on continuous distribution kinetics was developed to model these phenomena. The model accounts for simultaneous polymerization, degradation and enzyme deactivation and provides a technique to determine the rate coefficients for these processes. The dependence of these rate coefficients with temperature and monomer concentration is also discussed.

Modeling Natural Anti-Inflammatory Compounds by Molecular Topology

PubMed Central

Galvez-Llompart, María; Zanni, Riccardo; García-Domenech, Ramón

2011-01-01

One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with the remaining compounds (those not used in building up the model), has been carried out. Finally, a virtual screening on natural products was performed and 74 compounds showed actual anti-inflammatory activity. From them, 54 had been previously described as anti-inflammatory in the literature. This can be seen as a plus in the model validation and as a reinforcement of the role of Molecular Topology as an efficient tool for the discovery of new anti-inflammatory natural compounds. PMID:22272145

Harnessing Integrative Omics to Facilitate Molecular Imaging of the Human Epidermal Growth Factor Receptor Family for Precision Medicine.

PubMed

Pool, Martin; de Boer, H Rudolf; Hooge, Marjolijn N Lub-de; van Vugt, Marcel A T M; de Vries, Elisabeth G E

2017-01-01

Cancer is a growing problem worldwide. The cause of death in cancer patients is often due to treatment-resistant metastatic disease. Many molecularly targeted anticancer drugs have been developed against 'oncogenic driver' pathways. However, these treatments are usually only effective in properly selected patients. Resistance to molecularly targeted drugs through selective pressure on acquired mutations or molecular rewiring can hinder their effectiveness. This review summarizes how molecular imaging techniques can potentially facilitate the optimal implementation of targeted agents. Using the human epidermal growth factor receptor (HER) family as a model in (pre)clinical studies, we illustrate how molecular imaging may be employed to characterize whole body target expression as well as monitor drug effectiveness and the emergence of tumor resistance. We further discuss how an integrative omics discovery platform could guide the selection of 'effect sensors' - new molecular imaging targets - which are dynamic markers that indicate treatment effectiveness or resistance.

Unraveling the benzocaine-receptor interaction at molecular level using mass-resolved spectroscopy.

PubMed

Aguado, Edurne; León, Iker; Millán, Judith; Cocinero, Emilio J; Jaeqx, Sander; Rijs, Anouk M; Lesarri, Alberto; Fernández, José A

2013-10-31

The benzocaine-toluene cluster has been used as a model system to mimic the interaction between the local anesthetic benzocaine and the phenylalanine residue in Na(+) channels. The cluster was generated in a supersonic expansion of benzocaine and toluene in helium. Using a combination of mass-resolved laser-based experimental techniques and computational methods, the complex was fully characterized, finding four conformational isomers in which the molecules are bound through N-H···π and π···π weak hydrogen bonds. The structures of the detected isomers closely resemble those predicted for benzocaine in the inner pore of the ion channels, giving experimental support to previously reported molecular chemistry models.

Genetics and child psychiatry: I Advances in quantitative and molecular genetics.

PubMed

Rutter, M; Silberg, J; O'Connor, T; Simonoff, E

1999-01-01

Advances in quantitative psychiatric genetics as a whole are reviewed with respect to conceptual and methodological issues in relation to statistical model fitting, new genetic designs, twin and adoptee studies, definition of the phenotype, pervasiveness of genetic influences, pervasiveness of environmental influences, shared and nonshared environmental effects, and nature-nurture interplay. Advances in molecular genetics are discussed in relation to the shifts in research strategies to investigate multifactorial disorders (affected relative linkage designs, association strategies, and quantitative trait loci studies); new techniques and identified genetic mechanisms (expansion of trinucleotide repeats, genomic imprinting, mitochondrial DNA, fluorescent in-situ hybridisation, behavioural phenotypes, and animal models); and the successful localisation of genes.

A model for including thermal conduction in molecular dynamics simulations

NASA Technical Reports Server (NTRS)

Wu, Yue; Friauf, Robert J.

1989-01-01

A technique is introduced for including thermal conduction in molecular dynamics simulations for solids. A model is developed to allow energy flow between the computational cell and the bulk of the solid when periodic boundary conditions cannot be used. Thermal conduction is achieved by scaling the velocities of atoms in a transitional boundary layer. The scaling factor is obtained from the thermal diffusivity, and the results show good agreement with the solution for a continuous medium at long times. The effects of different temperature and size of the system, and of variations in strength parameter, atomic mass, and thermal diffusivity were investigated. In all cases, no significant change in simulation results has been found.

Phase solubility, 1H NMR and molecular modelling studies of bupivacaine hydrochloride complexation with different cyclodextrin derivates

NASA Astrophysics Data System (ADS)

Jug, Mario; Mennini, Natascia; Melani, Fabrizio; Maestrelli, Francesca; Mura, Paola

2010-11-01

A novel method, which simultaneously exploits experimental (NMR) and theoretically calculated data obtained by a molecular modelling technique, was proposed, to obtain deeper insight into inclusion geometry and possible stereoselective binding of bupivacaine hydrochloride with selected cyclodextrin derivatives. Sulphobuthylether-β-cyclodextrin and water soluble polymeric β-cyclodextrin demonstrated to be the best complexing agents for the drug, resulting in formation of the most stable inclusion complexes with the highest increase in aqueous drug solubility. The drug-carrier binding modes with these cyclodextrins and phenomena which may be directly related to the higher stability and better aqueous solubility of complexes formed were discussed in details.

Development of a Polarizable Force Field For Proteins via Ab Initio Quantum Chemistry: First Generation Model and Gas Phase Tests

PubMed Central

KAMINSKI, GEORGE A.; STERN, HARRY A.; BERNE, B. J.; FRIESNER, RICHARD A.; CAO, YIXIANG X.; MURPHY, ROBERT B.; ZHOU, RUHONG; HALGREN, THOMAS A.

2014-01-01

We present results of developing a methodology suitable for producing molecular mechanics force fields with explicit treatment of electrostatic polarization for proteins and other molecular system of biological interest. The technique allows simulation of realistic-size systems. Employing high-level ab initio data as a target for fitting allows us to avoid the problem of the lack of detailed experimental data. Using the fast and reliable quantum mechanical methods supplies robust fitting data for the resulting parameter sets. As a result, gas-phase many-body effects for dipeptides are captured within the average RMSD of 0.22 kcal/mol from their ab initio values, and conformational energies for the di- and tetrapeptides are reproduced within the average RMSD of 0.43 kcal/mol from their quantum mechanical counterparts. The latter is achieved in part because of application of a novel torsional fitting technique recently developed in our group, which has already been used to greatly improve accuracy of the peptide conformational equilibrium prediction with the OPLS-AA force field.1 Finally, we have employed the newly developed first-generation model in computing gas-phase conformations of real proteins, as well as in molecular dynamics studies of the systems. The results show that, although the overall accuracy is no better than what can be achieved with a fixed-charges model, the methodology produces robust results, permits reasonably low computational cost, and avoids other computational problems typical for polarizable force fields. It can be considered as a solid basis for building a more accurate and complete second-generation model. PMID:12395421

A Molecular Dynamic Modeling of Hemoglobin-Hemoglobin Interactions

NASA Astrophysics Data System (ADS)

Wu, Tao; Yang, Ye; Sheldon Wang, X.; Cohen, Barry; Ge, Hongya

2010-05-01

In this paper, we present a study of hemoglobin-hemoglobin interaction with model reduction methods. We begin with a simple spring-mass system with given parameters (mass and stiffness). With this known system, we compare the mode superposition method with Singular Value Decomposition (SVD) based Principal Component Analysis (PCA). Through PCA we are able to recover the principal direction of this system, namely the model direction. This model direction will be matched with the eigenvector derived from mode superposition analysis. The same technique will be implemented in a much more complicated hemoglobin-hemoglobin molecule interaction model, in which thousands of atoms in hemoglobin molecules are coupled with tens of thousands of T3 water molecule models. In this model, complex inter-atomic and inter-molecular potentials are replaced by nonlinear springs. We employ the same method to get the most significant modes and their frequencies of this complex dynamical system. More complex physical phenomena can then be further studied by these coarse grained models.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

New Methods in Tissue Engineering: Improved Models for Viral Infection.

PubMed

Ramanan, Vyas; Scull, Margaret A; Sheahan, Timothy P; Rice, Charles M; Bhatia, Sangeeta N

2014-11-01

New insights in the study of virus and host biology in the context of viral infection are made possible by the development of model systems that faithfully recapitulate the in vivo viral life cycle. Standard tissue culture models lack critical emergent properties driven by cellular organization and in vivo-like function, whereas animal models suffer from limited susceptibility to relevant human viruses and make it difficult to perform detailed molecular manipulation and analysis. Tissue engineering techniques may enable virologists to create infection models that combine the facile manipulation and readouts of tissue culture with the virus-relevant complexity of animal models. Here, we review the state of the art in tissue engineering and describe how tissue engineering techniques may alleviate some common shortcomings of existing models of viral infection, with a particular emphasis on hepatotropic viruses. We then discuss possible future applications of tissue engineering to virology, including current challenges and potential solutions.

Agent based simulations in disease modeling Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by Martine Ben Amar and Carlo Bianca

NASA Astrophysics Data System (ADS)

Pappalardo, Francesco; Pennisi, Marzio

2016-07-01

Fibrosis represents a process where an excessive tissue formation in an organ follows the failure of a physiological reparative or reactive process. Mathematical and computational techniques may be used to improve the understanding of the mechanisms that lead to the disease and to test potential new treatments that may directly or indirectly have positive effects against fibrosis [1]. In this scenario, Ben Amar and Bianca [2] give us a broad picture of the existing mathematical and computational tools that have been used to model fibrotic processes at the molecular, cellular, and tissue levels. Among such techniques, agent based models (ABM) can give a valuable contribution in the understanding and better management of fibrotic diseases.

Numerical study of the magnetized friction force

NASA Astrophysics Data System (ADS)

Fedotov, A. V.; Bruhwiler, D. L.; Sidorin, A. O.; Abell, D. T.; Ben-Zvi, I.; Busby, R.; Cary, J. R.; Litvinenko, V. N.

2006-07-01

Fundamental advances in experimental nuclear physics will require ion beams with orders of magnitude luminosity increase and temperature reduction. One of the most promising particle accelerator techniques for achieving these goals is electron cooling, where the ion beam repeatedly transfers thermal energy to a copropagating electron beam. The dynamical friction force on a fully ionized gold ion moving through magnetized and unmagnetized electron distributions has been simulated, using molecular dynamics techniques that resolve close binary collisions. We present a comprehensive examination of theoretical models in use by the electron cooling community. Differences in these models are clarified, enabling the accurate design of future electron cooling systems for relativistic ion accelerators.

Synthesis, in vitro and in vivo studies, and molecular modeling of N-alkylated dextromethorphan derivatives as non-competitive inhibitors of α3β4 nicotinic acetylcholine receptor.

PubMed

Jozwiak, Krzysztof; Targowska-Duda, Katarzyna M; Kaczor, Agnieszka A; Kozak, Joanna; Ligeza, Agnieszka; Szacon, Elzbieta; Wrobel, Tomasz M; Budzynska, Barbara; Biala, Grazyna; Fornal, Emilia; Poso, Antti; Wainer, Irving W; Matosiuk, Dariusz

2014-12-15

9 N-alkylated derivatives of dextromethorphan are synthesized and studied as non-competitive inhibitors of α3β4 nicotinic acetylcholine receptors (nAChRs). In vitro activity towards α3β4 nicotinic acetylcholine receptor is determined using a patch-clamp technique and is in the micromolar range. Homology modeling, molecular docking and molecular dynamics of ligand-receptor complexes in POPC membrane are used to find the mode of interactions of N-alkylated dextromethorphan derivatives with α3β4 nAChR. The compounds, similarly as dextromethorphan, interact with the middle portion of α3β4 nAChR ion channel. Finally, behavioral tests confirmed potential application of the studied compounds for the treatment of addiction. Copyright © 2014 Elsevier Ltd. All rights reserved.

Carbohydrates.

PubMed

Cocinero, Emilio J; Çarçabal, Pierre

2015-01-01

Although carbohydrates represent one of the most important families of biomolecules, they remain under-studied in comparison to the other biomolecular families (peptides, nucleobases). Beyond their best-known function of energy source in living systems, they act as mediator of molecular recognition processes, carrying molecular information in the so-called "sugar code," just to name one of their countless functions. Owing to their high conformational flexibility, they encode extremely rich information conveyed via the non-covalent hydrogen bonds within the carbohydrate and with other biomolecular assemblies, such as peptide subunits of proteins. Over the last decade there has been tremendous progress in the study of the conformational preferences of neutral oligosaccharides, and of the interactions between carbohydrates and various molecular partners (water, aromatic models, and peptide models), using vibrational spectroscopy as a sensitive probe. In parallel, other spectroscopic techniques have recently become available to the study of carbohydrates in the gas phase (microwave spectroscopy, IRMPD on charged species).

CURVATURE-DRIVEN MOLECULAR FLOW ON MEMBRANE SURFACE*

PubMed Central

MIKUCKI, MICHAEL; ZHOU, Y. C.

2017-01-01

This work presents a mathematical model for the localization of multiple species of diffusion molecules on membrane surfaces. Morphological change of bilayer membrane in vivo is generally modulated by proteins. Most of these modulations are associated with the localization of related proteins in the crowded lipid environments. We start with the energetic description of the distributions of molecules on curved membrane surface, and define the spontaneous curvature of bilayer membrane as a function of the molecule concentrations on membrane surfaces. A drift-diffusion equation governs the gradient flow of the surface molecule concentrations. We recast the energetic formulation and the related governing equations by using an Eulerian phase field description to define membrane morphology. Computational simulations with the proposed mathematical model and related numerical techniques predict (i) the molecular localization on static membrane surfaces at locations with preferred mean curvatures, and (ii) the generation of preferred mean curvature which in turn drives the molecular localization. PMID:29056778

Identification of control targets in Boolean molecular network models via computational algebra.

PubMed

Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

2016-09-23

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

Comparison of gravimetric and a double-indicator dilution technique for assessment of extra-vascular lung water in endotoxaemia.

PubMed

Rossi, P; Oldner, A; Wanecek, M; Leksell, L G; Rudehill, A; Konrad, D; Weitzberg, E

2003-03-01

To compare a molecular double-indicator dilution technique with the gravimetrical reference method for measurement of extra-vascular lung water in porcine endotoxin shock. Open comparative experimental study. Animal research laboratory. In fourteen anaesthetised, mechanically ventilated landrace pigs, central and pulmonary haemodynamics as well as pulmonary gas exchange were measured. Extra-vascular lung water was quantitated gravimetrically as well as with a molecular double indicator dilution technique. Eight of these animals were subjected to endotoxaemia, the rest serving as sham controls. No difference in extra-vascular lung water was observed between the two methods in sham animals. Furthermore, extra-vascular lung water assessed with the molecular double-indicator dilution technique at the initiation of endotoxin infusion did not differ significantly from the corresponding values for sham animals. Endotoxaemia induced a hypodynamic shock with concurrent pulmonary hypertension and a pronounced deterioration in gas exchange. No increase in extra-vascular lung water was detected with the molecular double-indicator dilution technique in response to endotoxin, whereas this parameter was significantly higher when assessed with the gravimetric method. The molecular double-indicator dilution technique showed similar results as the gravimetrical method for assessment of extra-vascular lung water in non-endotoxaemic conditions. However, during endotoxin-induced lung injury the molecular double indicator dilution technique failed to detect the significant increase in extra-vascular lung water as measured by the gravimetric method. These data suggest that the molecular double indicator dilution technique may be of limited value during sepsis-induced lung injury.

Toward the identification of a reliable 3D-QSAR model for the protein tyrosine phosphatase 1B inhibitors

NASA Astrophysics Data System (ADS)

Wang, Fangfang; Zhou, Bo

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) is an intracellular non-receptor phosphatase that is implicated in signal transduction of insulin and leptin pathways, thus PTP1B is considered as potential target for treating type II diabetes and obesity. The present article is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling of a series of compounds possessing PTP1B inhibitory activities using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The optimum template ligand-based models are statistically significant with great CoMFA (R2cv = 0.600, R2pred = 0.6760) and CoMSIA (R2cv = 0.624, R2pred = 0.8068) values. Molecular docking was employed to elucidate the inhibitory mechanisms of this series of compounds against PTP1B. In addition, the CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of PTP1B active site. The knowledge of structure-activity relationship and ligand-receptor interactions from 3D-QSAR model and molecular docking will be useful for better understanding the mechanism of ligand-receptor interaction and facilitating development of novel compounds as potent PTP1B inhibitors.

Research on golden-winged warblers: recent progress and current needs

Treesearch

Henry M. Streby; Ronald W. Rohrbaugh; David A. Buehler; David E. Andersen; Rachel Vallender; David I. King; Tom Will

2016-01-01

Considerable advances have been made in knowledge about Golden-winged Warblers (Vermivora chrysoptera) in the past decade. Recent employment of molecular analysis, stable-isotope analysis, telemetry-based monitoring of survival and behavior, and spatially explicit modeling techniques have added to, and revised, an already broad base of published...

Molecular Sieve Bench Testing and Computer Modeling

NASA Technical Reports Server (NTRS)

Mohamadinejad, Habib; DaLee, Robert C.; Blackmon, James B.

1995-01-01

The design of an efficient four-bed molecular sieve (4BMS) CO2 removal system for the International Space Station depends on many mission parameters, such as duration, crew size, cost of power, volume, fluid interface properties, etc. A need for space vehicle CO2 removal system models capable of accurately performing extrapolated hardware predictions is inevitable due to the change of the parameters which influences the CO2 removal system capacity. The purpose is to investigate the mathematical techniques required for a model capable of accurate extrapolated performance predictions and to obtain test data required to estimate mass transfer coefficients and verify the computer model. Models have been developed to demonstrate that the finite difference technique can be successfully applied to sorbents and conditions used in spacecraft CO2 removal systems. The nonisothermal, axially dispersed, plug flow model with linear driving force for 5X sorbent and pore diffusion for silica gel are then applied to test data. A more complex model, a non-darcian model (two dimensional), has also been developed for simulation of the test data. This model takes into account the channeling effect on column breakthrough. Four FORTRAN computer programs are presented: a two-dimensional model of flow adsorption/desorption in a packed bed; a one-dimensional model of flow adsorption/desorption in a packed bed; a model of thermal vacuum desorption; and a model of a tri-sectional packed bed with two different sorbent materials. The programs are capable of simulating up to four gas constituents for each process, which can be increased with a few minor changes.

Imaging the molecular dimensions and oligomerization of protein molecules at the solid-liquid interface by surface oriented molecular sizing (SOMS) microscopy

NASA Astrophysics Data System (ADS)

Waner, Mark Joseph

The structure and behavior of proteins at the solid/liquid interface is of great scientific interest. It has application both to fundamental biochemical understanding, as well as to biotechnological purposes. Interfaces play a critical role in many physiological processes. The mechanism of protein adsorption to surfaces is not very well understood. The current model put forth in much of the literature assumes a two step model. In the first step of this model the protein collides with the surface and adsorbs if its energy is sufficient to overcome the free energy of desorption of surface adsorbed solvent. The second step is often assumed to involve significant conformational change of the secondary and tertiary structure of the protein or enzyme, akin to denaturation. This unfolding of the protein would tend to indicate that loss of function would occur concomitantly, but studies have found very little loss in activity upon adsorption for a number of different protein systems. The recent development of the atomic force microscope (AFM) offers another tool for the examination of protein structure at liquid/solid interfaces. For atomically flat crystals the AFM has been used to determine atomic positions to <1 A resolution. In the case of samples with topographic features larger than atoms, the probe tip of the AFM 'convolutes' with the size and shape of surface features. This has hindered the use of AFM for molecular level structural determination of proteins at the liquid/solid interface. The work presented in this dissertation covers the development of the surface oriented molecular sizing (SOMS) technique which makes use of the angstrom height resolution of the AFM and a physically based mathematical framework for the analysis of the height distribution of adsorbed protein molecules. The surface adsorption and orientation (SAO) model is developed using statistical thermodynamics to model the expected height distributions for molecules adsorbed on a surface. The SOMS technique will be shown to be viable through studies of ferritin and concanavalin A (Con A) at the water/mica interface. Using this technique we are able to determine both the three-dimensional size and the oligomerization state of the adsorbed molecules. This technique will then be utilized for the examination of denaturation of Con A at the interface, by a number of mechanisms. Further, the structural and orientational changes in Con A as a function of pH will also be presented. The final chapter of this dissertation will present an extension of these studies to the deposition and structure of Con A thin films on mica.

Molecular modeling of the microstructure evolution during carbon fiber processing

NASA Astrophysics Data System (ADS)

Desai, Saaketh; Li, Chunyu; Shen, Tongtong; Strachan, Alejandro

2017-12-01

The rational design of carbon fibers with desired properties requires quantitative relationships between the processing conditions, microstructure, and resulting properties. We developed a molecular model that combines kinetic Monte Carlo and molecular dynamics techniques to predict the microstructure evolution during the processes of carbonization and graphitization of polyacrylonitrile (PAN)-based carbon fibers. The model accurately predicts the cross-sectional microstructure of the fibers with the molecular structure of the stabilized PAN fibers and physics-based chemical reaction rates as the only inputs. The resulting structures exhibit key features observed in electron microcopy studies such as curved graphitic sheets and hairpin structures. In addition, computed X-ray diffraction patterns are in good agreement with experiments. We predict the transverse moduli of the resulting fibers between 1 GPa and 5 GPa, in good agreement with experimental results for high modulus fibers and slightly lower than those of high-strength fibers. The transverse modulus is governed by sliding between graphitic sheets, and the relatively low value for the predicted microstructures can be attributed to their perfect longitudinal texture. Finally, the simulations provide insight into the relationships between chemical kinetics and the final microstructure; we observe that high reaction rates result in porous structures with lower moduli.

Computer modeling of the neurotoxin binding site of acetylcholine receptor spanning residues 185 through 196

NASA Technical Reports Server (NTRS)

Garduno-Juarez, R.; Shibata, M.; Zielinski, T. J.; Rein, R.

1987-01-01

A model of the complex between the acetylcholine receptor and the snake neurotoxin, cobratoxin, was built by molecular model building and energy optimization techniques. The experimentally identified functionally important residues of cobratoxin and the dodecapeptide corresponding to the residues 185-196 of acetylcholine receptor alpha subunit were used to build the model. Both cis and trans conformers of cyclic L-cystine portion of the dodecapeptide were examined. Binding residues independently identified on cobratoxin are shown to interact with the dodecapeptide AChR model.

Cleaning up with genomics: applying molecular biology to bioremediation.

PubMed

Lovley, Derek R

2003-10-01

Bioremediation has the potential to restore contaminated environments inexpensively yet effectively, but a lack of information about the factors controlling the growth and metabolism of microorganisms in polluted environments often limits its implementation. However, rapid advances in the understanding of bioremediation are on the horizon. Researchers now have the ability to culture microorganisms that are important in bioremediation and can evaluate their physiology using a combination of genome-enabled experimental and modelling techniques. In addition, new environmental genomic techniques offer the possibility for similar studies on as-yet-uncultured organisms. Combining models that can predict the activity of microorganisms that are involved in bioremediation with existing geochemical and hydrological models should transform bioremediation from a largely empirical practice into a science.

Molecular modeling of calmodulin: a comparison with crystallographic data

NASA Technical Reports Server (NTRS)

McDonald, J. J.; Rein, R.

1989-01-01

Two methods of side-chain placement on a modeled protein have been examined. Two molecular models of calmodulin were constructed that differ in the treatment of side chains prior to optimization of the molecule. A virtual bond analysis program developed by Purisima and Scheraga was used to determine the backbone conformation based on 2.2 angstroms resolution C alpha coordinates for the molecules. In the first model, side chains were initially constructed in an extended conformation. In the second model, a conformational grid search technique was employed. Calcium ions were treated explicitly during energy optimization using CHARMM. The models are compared to a recently published refined crystal structure of calmodulin. The results indicate that the initial choices for side-chains, but also significant effects on the main-chain conformation and supersecondary structure. The conformational differences are discussed. Analysis of these and other methods makes possible the formulation of a methodology for more appropriate side-chain placement in modeled proteins.

QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa

PubMed Central

Podunavac-Kuzmanović, Sanja O.; Cvetković, Dragoljub D.; Barna, Dijana J.

2009-01-01

A set of benzimidazole derivatives were tested for their inhibitory activities against the Gram-negative bacterium Pseudomonas aeruginosa and minimum inhibitory concentrations were determined for all the compounds. Quantitative structure activity relationship (QSAR) analysis was applied to fourteen of the abovementioned derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the antibacterial activity of the benzimidazole derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. To confirm the predictive power of the models, an external set of molecules was used. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. PMID:19468332

Conversion of laser energy to gas kinetic energy

NASA Technical Reports Server (NTRS)

Caledonia, G. E.

1975-01-01

Techniques for the gas phase absorption of laser radiation for conversion to gas kinetic energy are discussed. Absorption by inverse Bremsstrahlung, in which laser energy is converted at a gas kinetic rate in a spectrally continuous process, is briefly described, and absorption by molecular vibrational rotation bands is discussed at length. High pressure absorption is proposed as a means of minimizing gas bleaching and dissociation, the major disadvantages of the molecular absorption process. A band model is presented for predicting the molecular absorption spectra in the high pressure absorption region and is applied to the CO molecule. Use of a rare gas seeded with Fe(CO)5 for converting vibrational modes to translation modes is described.

Molecular Spintronics: Theory of Spin-Dependent Electron Transport in Fe/BDT/Fe Molecular Wire Systems

NASA Astrophysics Data System (ADS)

Dalgleish, Hugh; Kirczenow, George

2004-03-01

Metal/Molecule/Metal junction systems forming molecular wires are currently the focus of intense study. Recently, spin-dependent electron transport in molecular wires with magnetic Ni electrodes has been studied theoretically, and spin-valve effects have been predicted.* Here we explore theoretically another magnetic molecular wire system, namely, ferromagnetic Fe nano-contacts bridged with 1,4-benzene-dithiolate (BDT). We estimate the essential structural and electronic parameters for this system based on ab initio density functional calculations (DFT) for some simple model systems involving thiol groups and Fe clusters as well as semi-empirical considerations and the known electronic structure of bulk Fe. We then use Lippmann-Schwinger and Green's function techniques together with the Landauer formalism to study spin-dependent transport. *E. G. Emberly and G. Kirczenow, Chem. Phys. 281, 311 (2002); R. Pati, L. Senapati, P.M. Ajayan and S.K. Nayak, Phys. Rev. B68, 100407 (2003).

Activity coefficients from molecular simulations using the OPAS method

NASA Astrophysics Data System (ADS)

Kohns, Maximilian; Horsch, Martin; Hasse, Hans

2017-10-01

A method for determining activity coefficients by molecular dynamics simulations is presented. It is an extension of the OPAS (osmotic pressure for the activity of the solvent) method in previous work for studying the solvent activity in electrolyte solutions. That method is extended here to study activities of all components in mixtures of molecular species. As an example, activity coefficients in liquid mixtures of water and methanol are calculated for 298.15 K and 323.15 K at 1 bar using molecular models from the literature. These dense and strongly interacting mixtures pose a significant challenge to existing methods for determining activity coefficients by molecular simulation. It is shown that the new method yields accurate results for the activity coefficients which are in agreement with results obtained with a thermodynamic integration technique. As the partial molar volumes are needed in the proposed method, the molar excess volume of the system water + methanol is also investigated.

Ambiguities in the identification of giant molecular cloud complexes from longitude-velocity diagrams

NASA Technical Reports Server (NTRS)

Adler, David S.; Roberts, William W., Jr.

1992-01-01

Techniques which use longitude-velocity diagrams to identify molecular cloud complexes in the disk of the Galaxy are investigated by means of model Galactic disks generated from N-body cloud-particle simulations. A procedure similar to the method used to reduce the low-level emission in Galactic l-v diagrams is employed to isolate complexes of emission in the model l-v diagram (LVCs) from the 'background'clouds. The LVCs produced in this manner yield a size-line-width relationship with a slope of 0.58 and a mass spectrum with a slope of 1.55, consistent with Galactic observations. It is demonstrated that associations identified as LVCs are often chance superpositions of clouds spread out along the line of sight in the disk of the model system. This indicates that the l-v diagram cannot be used to unambiguously determine the location of molecular cloud complexes in the model Galactic disk. The modeling results also indicate that the existence of a size-line-width relationship is not a reliable indicator of the physical nature of cloud complexes, in particular, whether the complexes are gravitationally bound objects.

New Methods in Tissue Engineering

PubMed Central

Sheahan, Timothy P.; Rice, Charles M.; Bhatia, Sangeeta N.

2015-01-01

New insights in the study of virus and host biology in the context of viral infection are made possible by the development of model systems that faithfully recapitulate the in vivo viral life cycle. Standard tissue culture models lack critical emergent properties driven by cellular organization and in vivo–like function, whereas animal models suffer from limited susceptibility to relevant human viruses and make it difficult to perform detailed molecular manipulation and analysis. Tissue engineering techniques may enable virologists to create infection models that combine the facile manipulation and readouts of tissue culture with the virus-relevant complexity of animal models. Here, we review the state of the art in tissue engineering and describe how tissue engineering techniques may alleviate some common shortcomings of existing models of viral infection, with a particular emphasis on hepatotropic viruses. We then discuss possible future applications of tissue engineering to virology, including current challenges and potential solutions. PMID:25893203

Scaling analysis of [Fe(pyrazole)4]2[Nb(CN)8] molecular magnet

NASA Astrophysics Data System (ADS)

Konieczny, P.; Pełka, R.; Zieliński, P. M.; Pratt, F. L.; Pinkowicz, D.; Sieklucka, B.; Wasiutyński, T.

2013-10-01

The critical behaviour of the three dimensional (3D) molecular magnet {[FeII(pirazol)4]2[NbIV(CN)8]·4H2O}n has been studied with the use of experimental techniques such as ac magnetometry and zero field μSR spectroscopy. The sample orders magnetically below Tc=7.8 K. The measurements allowed to determine static exponents β, γ, and the dynamic exponent w. The resulting exponent values indicate that the studied system belongs to the universality class of the 3D Heisenberg model.

Molecular dynamics simulations of dense plasmas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, L.A.; Kress, J.D.; Kwon, I.

1993-12-31

We have performed quantum molecular dynamics simulations of hot, dense plasmas of hydrogen over a range of temperatures(0.1-5eV) and densities(0.0625-5g/cc). We determine the forces quantum mechanically from density functional, extended Huckel, and tight binding techniques and move the nuclei according to the classical equations of motion. We determine pair-correlation functions, diffusion coefficients, and electrical conductivities. We find that many-body effects predominate in this regime. We begin to obtain agreement with the OCP and Thomas-Fermi models only at the higher temperatures and densities.

Porting LAMMPS to GPUs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, William Michael; Plimpton, Steven James; Wang, Peng

2010-03-01

LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. LAMMPS has potentials for soft materials (biomolecules, polymers) and solid-state materials (metals, semiconductors) and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale. LAMMPS runs on single processors or in parallel using message-passing techniques and a spatial-decomposition of the simulation domain. The code is designed to be easy to modify or extend with new functionality.

Integrating Nanostructured Artificial Receptors with Whispering Gallery Mode Optical Microresonators via Inorganic Molecular Imprinting Techniques

PubMed Central

Hammond, G. Denise; Vojta, Adam L.; Grant, Sheila A.; Hunt, Heather K.

2016-01-01

The creation of label-free biosensors capable of accurately detecting trace contaminants, particularly small organic molecules, is of significant interest for applications in environmental monitoring. This is achieved by pairing a high-sensitivity signal transducer with a biorecognition element that imparts selectivity towards the compound of interest. However, many environmental pollutants do not have corresponding biorecognition elements. Fortunately, biomimetic chemistries, such as molecular imprinting, allow for the design of artificial receptors with very high selectivity for the target. Here, we perform a proof-of-concept study to show how artificial receptors may be created from inorganic silanes using the molecular imprinting technique and paired with high-sensitivity transducers without loss of device performance. Silica microsphere Whispering Gallery Mode optical microresonators are coated with a silica thin film templated by a small fluorescent dye, fluorescein isothiocyanate, which serves as our model target. Oxygen plasma degradation and solvent extraction of the template are compared. Extracted optical devices are interacted with the template molecule to confirm successful sorption of the template. Surface characterization is accomplished via fluorescence and optical microscopy, ellipsometry, optical profilometry, and contact angle measurements. The quality factors of the devices are measured to evaluate the impact of the coating on device sensitivity. The resulting devices show uniform surface coating with no microstructural damage with Q factors above 106. This is the first report demonstrating the integration of these devices with molecular imprinting techniques, and could lead to new routes to biosensor creation for environmental monitoring. PMID:27314397

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things

PubMed Central

Akan, Ozgur B.

2018-01-01

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication technology (ICT), as they enable an optimisation framework to develop advanced communication techniques, such as optimum detection methods and reliable transmission schemes. In this direction, we develop an analytical model to approximate the expected time course of bound receptor concentration, i.e., the received signal used to decode the transmitted messages. The model obviates the need for computationally expensive numerical methods by capturing the nonlinearities caused by laminar flow resulting in parabolic velocity profile, and finite number of ligand receptors leading to receiver saturation. The model also captures the effects of reactive surface depletion layer resulting from the mass transport limitations and moving reaction boundary originated from the passage of finite-duration molecular concentration pulse over the receiver surface. Based on the proposed model, we derive closed form analytical expressions that approximate the received pulse width, pulse delay and pulse amplitude, which can be used to optimize the system from an ICT perspective. We evaluate the accuracy of the proposed model by comparing model-based analytical results to the numerical results obtained by solving the exact system model with COMSOL Multiphysics. PMID:29415019

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things.

PubMed

Kuscu, Murat; Akan, Ozgur B

2018-01-01

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g., finite element analysis (FEA). However, analytical models are key for the information and communication technology (ICT), as they enable an optimisation framework to develop advanced communication techniques, such as optimum detection methods and reliable transmission schemes. In this direction, we develop an analytical model to approximate the expected time course of bound receptor concentration, i.e., the received signal used to decode the transmitted messages. The model obviates the need for computationally expensive numerical methods by capturing the nonlinearities caused by laminar flow resulting in parabolic velocity profile, and finite number of ligand receptors leading to receiver saturation. The model also captures the effects of reactive surface depletion layer resulting from the mass transport limitations and moving reaction boundary originated from the passage of finite-duration molecular concentration pulse over the receiver surface. Based on the proposed model, we derive closed form analytical expressions that approximate the received pulse width, pulse delay and pulse amplitude, which can be used to optimize the system from an ICT perspective. We evaluate the accuracy of the proposed model by comparing model-based analytical results to the numerical results obtained by solving the exact system model with COMSOL Multiphysics.

Screening the Molecular Framework Underlying Local Dendritic mRNA Translation

PubMed Central

Namjoshi, Sanjeev V.; Raab-Graham, Kimberly F.

2017-01-01

In the last decade, bioinformatic analyses of high-throughput proteomics and transcriptomics data have enabled researchers to gain insight into the molecular networks that may underlie lasting changes in synaptic efficacy. Development and utilization of these techniques have advanced the field of learning and memory significantly. It is now possible to move from the study of activity-dependent changes of a single protein to modeling entire network changes that require local protein synthesis. This data revolution has necessitated the development of alternative computational and statistical techniques to analyze and understand the patterns contained within. Thus, the focus of this review is to provide a synopsis of the journey and evolution toward big data techniques to address still unanswered questions regarding how synapses are modified to strengthen neuronal circuits. We first review the seminal studies that demonstrated the pivotal role played by local mRNA translation as the mechanism underlying the enhancement of enduring synaptic activity. In the interest of those who are new to the field, we provide a brief overview of molecular biology and biochemical techniques utilized for sample preparation to identify locally translated proteins using RNA sequencing and proteomics, as well as the computational approaches used to analyze these data. While many mRNAs have been identified, few have been shown to be locally synthesized. To this end, we review techniques currently being utilized to visualize new protein synthesis, a task that has proven to be the most difficult aspect of the field. Finally, we provide examples of future applications to test the physiological relevance of locally synthesized proteins identified by big data approaches. PMID:28286470

Prediction of blood-brain partitioning: a model based on molecular electronegativity distance vector descriptors.

PubMed

Zhang, Yong-Hong; Xia, Zhi-Ning; Qin, Li-Tang; Liu, Shu-Shen

2010-09-01

The objective of this paper is to build a reliable model based on the molecular electronegativity distance vector (MEDV) descriptors for predicting the blood-brain barrier (BBB) permeability and to reveal the effects of the molecular structural segments on the BBB permeability. Using 70 structurally diverse compounds, the partial least squares regression (PLSR) models between the BBB permeability and the MEDV descriptors were developed and validated by the variable selection and modeling based on prediction (VSMP) technique. The estimation ability, stability, and predictive power of a model are evaluated by the estimated correlation coefficient (r), leave-one-out (LOO) cross-validation correlation coefficient (q), and predictive correlation coefficient (R(p)). It has been found that PLSR model has good quality, r=0.9202, q=0.7956, and R(p)=0.6649 for M1 model based on the training set of 57 samples. To search the most important structural factors affecting the BBB permeability of compounds, we performed the values of the variable importance in projection (VIP) analysis for MEDV descriptors. It was found that some structural fragments in compounds, such as -CH(3), -CH(2)-, =CH-, =C, triple bond C-, -CH<, =C<, =N-, -NH-, =O, and -OH, are the most important factors affecting the BBB permeability. (c) 2010. Published by Elsevier Inc.

Knowledge discovery and system biology in molecular medicine: an application on neurodegenerative diseases.

PubMed

Fattore, Matteo; Arrigo, Patrizio

2005-01-01

The possibility to study an organism in terms of system theory has been proposed in the past, but only the advancement of molecular biology techniques allow us to investigate the dynamical properties of a biological system in a more quantitative and rational way than before . These new techniques can gave only the basic level view of an organisms functionality. The comprehension of its dynamical behaviour depends on the possibility to perform a multiple level analysis. Functional genomics has stimulated the interest in the investigation the dynamical behaviour of an organism as a whole. These activities are commonly known as System Biology, and its interests ranges from molecules to organs. One of the more promising applications is the 'disease modeling'. The use of experimental models is a common procedure in pharmacological and clinical researches; today this approach is supported by 'in silico' predictive methods. This investigation can be improved by a combination of experimental and computational tools. The Machine Learning (ML) tools are able to process different heterogeneous data sources, taking into account this peculiarity, they could be fruitfully applied to support a multilevel data processing (molecular, cellular and morphological) that is the prerequisite for the formal model design; these techniques can allow us to extract the knowledge for mathematical model development. The aim of our work is the development and implementation of a system that combines ML and dynamical models simulations. The program is addressed to the virtual analysis of the pathways involved in neurodegenerative diseases. These pathologies are multifactorial diseases and the relevance of the different factors has not yet been well elucidated. This is a very complex task; in order to test the integrative approach our program has been limited to the analysis of the effects of a specific protein, the Cyclin dependent kinase 5 (CDK5) which relies on the induction of neuronal apoptosis. The system has a modular structure centred on a textual knowledge discovery approach. The text mining is the only way to enhance the capability to extract ,from multiple data sources, the information required for the dynamical simulator. The user may access the publically available modules through the following site: http://biocomp.ge.ismac.cnr.it.

Contributions to advances in blend pellet products (BPP) research on molecular structure and molecular nutrition interaction by advanced synchrotron and globar molecular (Micro)spectroscopy.

PubMed

Guevara-Oquendo, Víctor H; Zhang, Huihua; Yu, Peiqiang

2018-04-13

To date, advanced synchrotron-based and globar-sourced techniques are almost unknown to food and feed scientists. There has been little application of these advanced techniques to study blend pellet products at a molecular level. This article aims to provide recent research on advanced synchrotron and globar vibrational molecular spectroscopy contributions to advances in blend pellet products research on molecular structure and molecular nutrition interaction. How processing induced molecular structure changes in relation to nutrient availability and utilization of the blend pellet products. The study reviews Utilization of co-product components for blend pellet product in North America; Utilization and benefits of inclusion of pulse screenings; Utilization of additives in blend pellet products; Application of pellet processing in blend pellet products; Conventional evaluation techniques and methods for blend pellet products. The study focus on recent applications of cutting-edge vibrational molecular spectroscopy for molecular structure and molecular structure association with nutrient utilization in blend pellet products. The information described in this article gives better insight on how advanced molecular (micro)spectroscopy contributions to advances in blend pellet products research on molecular structure and molecular nutrition interaction.

Modeling the hyperpolarizability dispersion with the Thomas-Kuhn sum rules

NASA Astrophysics Data System (ADS)

De Mey, Kurt; Perez-Moreno, Javier; Clays, Koen

2011-10-01

The continued interest in molecules that possess large quadratic nonlinear optical (NLO) properties has motivated considerable interplay between molecular synthesis and theory. The screening of viable candidates for NLO applications has been a tedious work, much helped by the advent of the hyper-Rayleigh scattering (HRS) technique. The downside of this technique is the low efficiency, which usually means that measurements have to be performed at wavelengths that are close to the molecular resonances, in the visible area. This means generally that one has to extrapolate the results from HRS characterization to the longer wavelengths that are useful for applications. Such extrapolation is far from trivial and the classic 2-level model can only be used for the most straightforward single charge-transfer chromophores. An alternative is the TKSSOS technique, which uses a few input-hyperpolarizabilities and UV-Vis absorption data to calculate the entire hyperpolarizability spectrum. We have applied this TKS-SOS technique on a set of porphyrines to calculate the hyperpolarizability dispersion. We have also built a tunable HRS set up, capable of determining hyperpolarizabilities in the near infrared (up to 1600 nm). This has allowed us to directly confirm the results predicted in the application region. Due to the very sharp transitions in the hyperpolarizability dispersion, the calculation is subjected to a very precise calibration with respect to the input-hyperpolarizabilities, resulting in very accurate predictions for long wavelength hyperpolarizabilities. Our results not only underscribe the aforementioned technique, but also confirm the use of porphyrines as powerful moieties in NLO applications.

Marine molecular biology: an emerging field of biological sciences.

PubMed

Thakur, Narsinh L; Jain, Roopesh; Natalio, Filipe; Hamer, Bojan; Thakur, Archana N; Müller, Werner E G

2008-01-01

An appreciation of the potential applications of molecular biology is of growing importance in many areas of life sciences, including marine biology. During the past two decades, the development of sophisticated molecular technologies and instruments for biomedical research has resulted in significant advances in the biological sciences. However, the value of molecular techniques for addressing problems in marine biology has only recently begun to be cherished. It has been proven that the exploitation of molecular biological techniques will allow difficult research questions about marine organisms and ocean processes to be addressed. Marine molecular biology is a discipline, which strives to define and solve the problems regarding the sustainable exploration of marine life for human health and welfare, through the cooperation between scientists working in marine biology, molecular biology, microbiology and chemistry disciplines. Several success stories of the applications of molecular techniques in the field of marine biology are guiding further research in this area. In this review different molecular techniques are discussed, which have application in marine microbiology, marine invertebrate biology, marine ecology, marine natural products, material sciences, fisheries, conservation and bio-invasion etc. In summary, if marine biologists and molecular biologists continue to work towards strong partnership during the next decade and recognize intellectual and technological advantages and benefits of such partnership, an exciting new frontier of marine molecular biology will emerge in the future.

Protein Modelling: What Happened to the “Protein Structure Gap”?

PubMed Central

Schwede, Torsten

2013-01-01

Computational modeling and prediction of three-dimensional macromolecular structures and complexes from their sequence has been a long standing vision in structural biology as it holds the promise to bypass part of the laborious process of experimental structure solution. Over the last two decades, a paradigm shift has occurred: starting from a situation where the “structure knowledge gap” between the huge number of protein sequences and small number of known structures has hampered the widespread use of structure-based approaches in life science research, today some form of structural information – either experimental or computational – is available for the majority of amino acids encoded by common model organism genomes. Template based homology modeling techniques have matured to a point where they are now routinely used to complement experimental techniques. With the scientific focus of interest moving towards larger macromolecular complexes and dynamic networks of interactions, the integration of computational modeling methods with low-resolution experimental techniques allows studying large and complex molecular machines. Computational modeling and prediction techniques are still facing a number of challenges which hamper the more widespread use by the non-expert scientist. For example, it is often difficult to convey the underlying assumptions of a computational technique, as well as the expected accuracy and structural variability of a specific model. However, these aspects are crucial to understand the limitations of a model, and to decide which interpretations and conclusions can be supported. PMID:24010712

Complex Equilibrium Calculations of Nonideal Multiphase Systems (CEC- NMS) and Applications to Liquid Metal Fuel Combustion

DTIC Science & Technology

1989-03-15

3. F 2(g) -Li(L) 4. SF 6(g)-Li(L ) - vii - Several different modeling techniques are used to accurately estimate the activity coefficients of the...electrolytes with molecular species. The gas phase of the electrolytic solution is modeled using a pressure-explicit second order virial equation. The pure...calculated using the van Laar model . - viii - ACKNOWLEDGMENT This research was sponsored by the Office of Naval Research, Contract No. N00014-85--k

A research project-based and self-determined teaching system of molecular biology techniques for undergraduates.

PubMed

Zhang, Shuping

2008-05-01

Molecular biology techniques play a very important role in understanding the biological activity. Students who major in biology should know not only how to perform experiments, but also the reasons for performing them. Having the concept of conducting research by integrating various techniques is especially important. This paper introduces a research project-based and self-determined teaching system of molecular biology techniques for undergraduates. Its aim is to create an environment mimicking real research programs and to help students build up confidence in their research skills. The students are allowed to explore a set of commonly used molecular biology techniques to solve some fundamental problems about genes on their own. They find a gene of interest, write a mini-proposal, and give an oral presentation. This course provides students a foundation before entering the research laboratory and allows them to adapt easily to real research programs. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

Electrochemical impedimetric sensor based on molecularly imprinted polymers/sol-gel chemistry for methidathion organophosphorous insecticide recognition.

PubMed

Bakas, Idriss; Hayat, Akhtar; Piletsky, Sergey; Piletska, Elena; Chehimi, Mohamed M; Noguer, Thierry; Rouillon, Régis

2014-12-01

We report here a novel method to detect methidathion organophosphorous insecticides. The sensing platform was architected by the combination of molecularly imprinted polymers and sol-gel technique on inexpensive, portable and disposable screen printed carbon electrodes. Electrochemical impedimetric detection technique was employed to perform the label free detection of the target analyte on the designed MIP/sol-gel integrated platform. The selection of the target specific monomer by electrochemical impedimetric methods was consistent with the results obtained by the computational modelling method. The prepared electrochemical MIP/sol-gel based sensor exhibited a high recognition capability toward methidathion, as well as a broad linear range and a low detection limit under the optimized conditions. Satisfactory results were also obtained for the methidathion determination in waste water samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Addressing Loss of Efficiency Due to Misclassification Error in Enriched Clinical Trials for the Evaluation of Targeted Therapies Based on the Cox Proportional Hazards Model.

PubMed

Tsai, Chen-An; Lee, Kuan-Ting; Liu, Jen-Pei

2016-01-01

A key feature of precision medicine is that it takes individual variability at the genetic or molecular level into account in determining the best treatment for patients diagnosed with diseases detected by recently developed novel biotechnologies. The enrichment design is an efficient design that enrolls only the patients testing positive for specific molecular targets and randomly assigns them for the targeted treatment or the concurrent control. However there is no diagnostic device with perfect accuracy and precision for detecting molecular targets. In particular, the positive predictive value (PPV) can be quite low for rare diseases with low prevalence. Under the enrichment design, some patients testing positive for specific molecular targets may not have the molecular targets. The efficacy of the targeted therapy may be underestimated in the patients that actually do have the molecular targets. To address the loss of efficiency due to misclassification error, we apply the discrete mixture modeling for time-to-event data proposed by Eng and Hanlon [8] to develop an inferential procedure, based on the Cox proportional hazard model, for treatment effects of the targeted treatment effect for the true-positive patients with the molecular targets. Our proposed procedure incorporates both inaccuracy of diagnostic devices and uncertainty of estimated accuracy measures. We employed the expectation-maximization algorithm in conjunction with the bootstrap technique for estimation of the hazard ratio and its estimated variance. We report the results of simulation studies which empirically investigated the performance of the proposed method. Our proposed method is illustrated by a numerical example.

Imaging Neuroinflammation – from Bench to Bedside

PubMed Central

Pulli, Benjamin; Chen, John W

2014-01-01

Neuroinflammation plays a central role in a variety of neurological diseases, including stroke, multiple sclerosis, Alzheimer’s disease, and malignant CNS neoplasms, among many other. Different cell types and molecular mediators participate in a cascade of events in the brain that is ultimately aimed at control, regeneration and repair, but leads to damage of brain tissue under pathological conditions. Non-invasive molecular imaging of key players in the inflammation cascade holds promise for identification and quantification of the disease process before it is too late for effective therapeutic intervention. In this review, we focus on molecular imaging techniques that target inflammatory cells and molecules that are of interest in neuroinflammation, especially those with high translational potential. Over the past decade, a plethora of molecular imaging agents have been developed and tested in animal models of (neuro)inflammation, and a few have been translated from bench to bedside. The most promising imaging techniques to visualize neuroinflammation include MRI, positron emission tomography (PET), single photon emission computed tomography (SPECT), and optical imaging methods. These techniques enable us to image adhesion molecules to visualize endothelial cell activation, assess leukocyte functions such as oxidative stress, granule release, and phagocytosis, and label a variety of inflammatory cells for cell tracking experiments. In addition, several cell types and their activation can be specifically targeted in vivo, and consequences of neuroinflammation such as neuronal death and demyelination can be quantified. As we continue to make progress in utilizing molecular imaging technology to study and understand neuroinflammation, increasing efforts and investment should be made to bring more of these novel imaging agents from the “bench to bedside.” PMID:25525560

Applications of molecular physics 'biotechnology' to the rational design of an improved phenytoin analogue.

PubMed

Weaver, D F

1992-12-01

This study exploits molecular physics, in conjunction with a large scale computing environment, as a tool for understanding the clinical phenomenology of phenytoin (PHT) toxicology at a molecular level and for employing this understanding in an attempt to design improved drugs. The application of molecular physics techniques, such as quantum mechanics and molecular force field calculations, to the process of rational anticonvulsant drug design remains virtually unexplored. A 3-step strategy for applying these techniques to the design of an improved PHT molecule is presented. Step 1 employs quantitative structure-activity relationship calculations on 80 PHT analogues to ascertain the portion of the PHT molecule necessary for bioactivity (i.e. the 'bioactive face' of PHT); the N3-C4(O)-C5-R fragment of PHT was identified as the bioactive face. Step 2 employs molecular modelling studies to determine the portion of the PHT molecule necessary for the teratogenic, mutagenic and connective tissue toxicities of PHT (i.e. the 'biotoxic face'); the C2(O)-N3 fragment of PHT was identified as the biotoxic face. Step 3 experiments design an 'improved' PHT analogue, which maintains the bioactive face while eliminating the integrity of the biotoxic face; 2-deoxy-5,5-diphenylhydantoin was designed and synthesized as the improved PHT analogue. This compound had biological activity equivalent to PHT, but was unable to bind to nucleic acids or to chelate metals involved in connective tissue metabolism.

Hybrid optimal descriptors as a tool to predict skin sensitization in accordance to OECD principles.

PubMed

Toropova, Alla P; Toropov, Andrey A

2017-06-05

Skin sensitization (allergic contact dermatitis) is a widespread problem arising from the contact of chemicals with the skin. The detection of molecular features with undesired effect for skin is complex task owing to unclear biochemical mechanisms and unclearness of conditions of action of chemicals to skin. The development of computational methods for estimation of this endpoint in order to reduce animal testing is recommended (Cosmetics Directive EC regulation 1907/2006; EU Regulation, Regulation, 1223/2009). The CORAL software (http://www.insilico.eu/coral) gives good predictive models for the skin sensitization. Simplified molecular input-line entry system (SMILES) together with molecular graph are used to represent the molecular structure for these models. So-called hybrid optimal descriptors are used to establish quantitative structure-activity relationships (QSARs). The aim of this study is the estimation of the predictive potential of the hybrid descriptors. Three different distributions into the training (≈70%), calibration (≈15%), and validation (≈15%) sets are studied. QSAR for these three distributions are built up with using the Monte Carlo technique. The statistical characteristics of these models for external validation set are used as a measure of predictive potential of these models. The best model, according to the above criterion, is characterized by n validation =29, r 2 validation =0.8596, RMSE validation =0.489. Mechanistic interpretation and domain of applicability for these models are defined. Copyright © 2017 Elsevier B.V. All rights reserved.

Solid-State Solvation and Enhanced Exciton Diffusion in Doped Organic Thin Films under Mechanical Pressure.

PubMed

Chang, Wendi; Akselrod, Gleb M; Bulović, Vladimir

2015-04-28

Direct modification of exciton energy has been previously used to optimize the operation of organic optoelectronic devices. One demonstrated method for exciton energy modification is through the use of the solvent dielectric effects in doped molecular films. To gain a deeper appreciation of the underlying physical mechanisms, in this work we test the solid-state solvation effect in molecular thin films under applied external pressure. We observe that external mechanical pressure increases dipole-dipole interactions, leading to shifts in the Frenkel exciton energy and enhancement of the time-resolved spectral red shift associated with the energy-transfer-mediated exciton diffusion. Measurements are performed on host:dopant molecular thin films, which show bathochromic shifts in photoluminescence (PL) under increasing pressure. This is in agreement with a simple solvation theory model of exciton energetics with a fitting parameter based on the mechanical properties of the host matrix material. We measure no significant change in exciton lifetime with increasing pressure, consistent with unchanged aggregation in molecular films under compression. However, we do observe an increase in exciton spectral thermalization rate for compressed molecular films, indicating enhanced exciton diffusion for increased dipole-dipole interactions under pressure. The results highlight the contrast between molecular energy landscapes obtained when dipole-dipole interactions are increased by the pressure technique versus the conventional dopant concentration variation methods, which can lead to extraneous effects such as aggregation at higher doping concentrations. The present work demonstrates the use of pressure-probing techniques in studying energy disorder and exciton dynamics in amorphous molecular thin films.

Solid-State Solvation and Enhanced Exciton Diffusion in Doped Organic Thin Films under Mechanical Pressure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Wendi; Akselrod, Gleb M.; Bulović, Vladimir

2015-04-28

Direct modification of exciton energy has been previously used to optimize the operation of organic optoelectronic devices. One demonstrated method for exciton energy modification is through the use of the solvent dielectric effects in doped molecular films. To gain a deeper appreciation of the underlying physical mechanisms, in this work we test the solid-state solvation effect in molecular thin films under applied external pressure. We observe that external mechanical pressure increases dipole–dipole interactions, leading to shifts in the Frenkel exciton energy and enhancement of the time-resolved spectral red shift associated with the energy-transfer-mediated exciton diffusion. Measurements are performed on host:dopantmore » molecular thin films, which show bathochromic shifts in photoluminescence (PL) under increasing pressure. This is in agreement with a simple solvation theory model of exciton energetics with a fitting parameter based on the mechanical properties of the host matrix material. We measure no significant change in exciton lifetime with increasing pressure, consistent with unchanged aggregation in molecular films under compression. However, we do observe an increase in exciton spectral thermalization rate for compressed molecular films, indicating enhanced exciton diffusion for increased dipole–dipole interactions under pressure. The results highlight the contrast between molecular energy landscapes obtained when dipole–dipole interactions are increased by the pressure technique versus the conventional dopant concentration variation methods, which can lead to extraneous effects such as aggregation at higher doping concentrations. The present work demonstrates the use of pressure-probing techniques in studying energy disorder and exciton dynamics in amorphous molecular thin films.« less

Final Report: Biological and Synthetic Nanostructures Controlled at the Atomistic Level

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williamson, A; van Buuren, T

2007-02-21

Nanotechnology holds great promise for many application fields, ranging from the semiconductor industry to medical research and national security. Novel, nanostructured materials are the fundamental building blocks upon which all these future nanotechnologies will be based. In this Strategic Initiative (SI) we conducted a combined theoretical and experimental investigation of the modeling, synthesis, characterization, and design techniques which are required to fabricate semiconducting and metallic nanostructures with enhanced properties. We focused on developing capabilities that have broad applicability to a wide range of materials and can be applied both to nanomaterials that are currently being developed for nanotechnology applications andmore » also to new, yet to be discovered, nanomaterials. During this 3 year SI project we have made excellent scientific progress in each of the components of this project. We have developed first-principles techniques for modeling the structural, electronic, optical, and transport properties of materials at the nanoscale. For the first time, we have simulated nanomaterials both in vacuum and in aqueous solution. These simulation capabilities harness the worldleading computational resources available at LLNL to model, at the quantum mechanical level, systems containing hundreds of atoms and thousands of electrons. Significant advances in the density functional and quantum Monte Carlo techniques employed in this project were developed to enable these techniques to scale up to simulating realistic size nanostructured materials. We have developed the first successful techniques for chemically synthesizing crystalline silicon and germanium nanoparticles and nanowires. We grew the first macroscopic, faceted superlattice crystals from these nanoparticles. We have also advanced our capabilities to synthesize semiconductor nanoparticles using physical vapor deposition techniques so that we are now able to control of the size, shape and surface structure of these nanoparticles. We have made advances in characterizing the surface of nanoparticles using x-ray absorption experiments. Throughout this SI a number of long-term, strategic external collaborations have been established. These collaborations have resulted in 30 joint publications, strategic hires of postdocs and graduate students from these groups into groups at LLNL and the submission of joint research grants. We have developed collaborations on the theory and modeling of nanomaterials with the groups of Profs. Ceder and Marzari (MIT), Crespi (Penn State), Freeman (Northwestern), Grossman and Lester (UC Berkeley), Mitas (North Carolina State), and Needs (Cambridge). We are collaborating with Dr. Alivisatos's group in the Molecular Foundry at Lawrence Berkeley Laboratory on the fabrication, characterization and modeling of inorganic nanomaterials. We are working with Prof. Majumdar's group at UC Berkeley on the characterization of nanomaterials. We are working with the molecular diamond group at Chevron-Texaco who has developed a process for extracting mono-disperse samples of nano-scale diamonds from crude oil. We are collaborating with Dr. Chen at UCSF to develop CdSe nanoparticle-biolabels. As a result of the outstanding scientific achievements and the long-term collaborations developed during this strategic initiative we have been extremely successful in obtaining external funding to continue and grow this research activity at the LLNL. We have received two DARPA grants to support the further development of our computational modeling techniques and to develop carbon nanotube based molecular separation devices. We have received two new Office of Science BES grants to support our nanomaterials modeling and synthesis projects. We have received funding from the NA22 office of DOE to develop the materials modeling capabilities begun in this SI for modeling detector materials. We have received funding from Intel Corporation to apply the modeling techniques developed in this initiative to examine silicon nanowires fabricated on computer chips. We are also pursuing several additional sources of funding from BES, the DHS, and NIH to support the continuation of the research programs developed in this SI. The remainder of this report and the attached publications describe the background to this SI research project and the details of the scientific achievements that have been made.« less

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

PubMed Central

Sung, Myong-Hee

2013-01-01

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

ECUT: Energy Conversion and Utilization Technologies program - Biocatalysis research activity

NASA Technical Reports Server (NTRS)

Wilcox, R.

1984-01-01

The activities of the Biocatalysis Research Activity are organized into the Biocatalysis and Molecular Modeling work elements and a supporting planning and analysis function. In the Biocatalysis work element, progress is made in developing a method for stabilizing genetically engineered traits in microorganisms, refining a technique for monitoring cells that are genetically engineered, and identifying strains of fungi for highly efficient preprocessing of biomass for optimizing the efficiency of bioreactors. In the Molecular Modeling work element, a preliminary model of the behavior of enzymes is developed. A preliminary investigation of the potential for synthesizing enzymes for use in electrochemical processes is completed. Contact with industry and universities is made to define key biocatalysis technical issues and to broaden the range of potential participants in the activity. Analyses are conducted to identify and evaluate potential concepts for future research funding.

Charting molecular free-energy landscapes with an atlas of collective variables

NASA Astrophysics Data System (ADS)

Hashemian, Behrooz; Millán, Daniel; Arroyo, Marino

2016-11-01

Collective variables (CVs) are a fundamental tool to understand molecular flexibility, to compute free energy landscapes, and to enhance sampling in molecular dynamics simulations. However, identifying suitable CVs is challenging, and is increasingly addressed with systematic data-driven manifold learning techniques. Here, we provide a flexible framework to model molecular systems in terms of a collection of locally valid and partially overlapping CVs: an atlas of CVs. The specific motivation for such a framework is to enhance the applicability and robustness of CVs based on manifold learning methods, which fail in the presence of periodicities in the underlying conformational manifold. More generally, using an atlas of CVs rather than a single chart may help us better describe different regions of conformational space. We develop the statistical mechanics foundation for our multi-chart description and propose an algorithmic implementation. The resulting atlas of data-based CVs are then used to enhance sampling and compute free energy surfaces in two model systems, alanine dipeptide and β-D-glucopyranose, whose conformational manifolds have toroidal and spherical topologies.

Computational studies of Ras and PI3K

NASA Technical Reports Server (NTRS)

Ren, Lei; Cucinotta, Francis A.

2004-01-01

Until recently, experimental techniques in molecular cell biology have been the primary means to investigate biological risk upon space radiation. However, computational modeling provides an alternative theoretical approach, which utilizes various computational tools to simulate proteins, nucleotides, and their interactions. In this study, we are focused on using molecular mechanics (MM) and molecular dynamics (MD) to study the mechanism of protein-protein binding and to estimate the binding free energy between proteins. Ras is a key element in a variety of cell processes, and its activation of phosphoinositide 3-kinase (PI3K) is important for survival of transformed cells. Different computational approaches for this particular study are presented to calculate the solvation energies and binding free energies of H-Ras and PI3K. The goal of this study is to establish computational methods to investigate the roles of different proteins played in the cellular responses to space radiation, including modification of protein function through gene mutation, and to support the studies in molecular cell biology and theoretical kinetics models for our risk assessment project.

EVALUATION OF ENDOGENOUS HORMONES AND A XENOBIOTIC PESTICIDE ON SHEEPSHEAD MINNOW GROWTH USING MOLECULAR BIOLOGICAL TECHNIQUES

EPA Science Inventory

Presented at the 131st Annual Meeting of the American Fisheries Society, "2001: A Fisheries Odyssey: The Journey of Science and Education Continues," 19-23 August 2001, Phoenix, AZ. 1 p.

We have developed a teleost model to screen physiological effects of endocrine disrup...

USE OF MOLECULAR BIOLOGICAL TECHNIQUES TO EVALUATE EFFECT OF ENDOGENOUS HORMONES AND A XENOBIOTIC PESTICIDE ON GROWTH OF SHEEPSHEAD MINNOW

EPA Science Inventory

We have developed a teleost model to screen physiological effects of endocrine disrupting chemicals (EDCs) on somatic growth. Growth is largely controlled by the endocrine system via the growth-hormone releasing hormone (GRF) - growth hormone (GH) - insulin-like growth factor (IG...

A Self-Instructional Approach To the Teaching of Enzymology Involving Computer-Based Sequence Analysis and Molecular Modelling.

ERIC Educational Resources Information Center

Attwood, Paul V.

1997-01-01

Describes a self-instructional assignment approach to the teaching of advanced enzymology. Presents an assignment that offers a means of teaching enzymology to students that exposes them to modern computer-based techniques of analyzing protein structure and relates structure to enzyme function. (JRH)

Combining a Standard Fischer Esterification Experiment with Stereochemical and Molecular-Modeling Concepts

ERIC Educational Resources Information Center

Clausen, Thomas P.

2011-01-01

The Fisher esterification reaction is ideally suited for the undergraduate organic laboratory because it is easy to carry out and often involves a suitable introduction to basic laboratory techniques including extraction, distillation, and simple spectroscopic (IR and NMR) analyses. Here, a Fisher esterification reaction is described in which the…

Computation of Dielectric Response in Molecular Solids for High Capacitance Organic Dielectrics.

PubMed

Heitzer, Henry M; Marks, Tobin J; Ratner, Mark A

2016-09-20

The dielectric response of a material is central to numerous processes spanning the fields of chemistry, materials science, biology, and physics. Despite this broad importance across these disciplines, describing the dielectric environment of a molecular system at the level of first-principles theory and computation remains a great challenge and is of importance to understand the behavior of existing systems as well as to guide the design and synthetic realization of new ones. Furthermore, with recent advances in molecular electronics, nanotechnology, and molecular biology, it has become necessary to predict the dielectric properties of molecular systems that are often difficult or impossible to measure experimentally. In these scenarios, it is would be highly desirable to be able to determine dielectric response through efficient, accurate, and chemically informative calculations. A good example of where theoretical modeling of dielectric response would be valuable is in the development of high-capacitance organic gate dielectrics for unconventional electronics such as those that could be fabricated by high-throughput printing techniques. Gate dielectrics are fundamental components of all transistor-based logic circuitry, and the combination high dielectric constant and nanoscopic thickness (i.e., high capacitance) is essential to achieving high switching speeds and low power consumption. Molecule-based dielectrics offer the promise of cheap, flexible, and mass producible electronics when used in conjunction with unconventional organic or inorganic semiconducting materials to fabricate organic field effect transistors (OFETs). The molecular dielectrics developed to date typically have limited dielectric response, which results in low capacitances, translating into poor performance of the resulting OFETs. Furthermore, the development of better performing dielectric materials has been hindered by the current highly empirical and labor-intensive pace of synthetic progress. An accurate and efficient theoretical computational approach could drastically decrease this time by screening potential dielectric materials and providing reliable design rules for future molecular dielectrics. Until recently, accurate calculation of dielectric responses in molecular materials was difficult and highly approximate. Most previous modeling efforts relied on classical formalisms to relate molecular polarizability to macroscopic dielectric properties. These efforts often vastly overestimated polarizability in the subject materials and ignored crucial material properties that can affect dielectric response. Recent advances in first-principles calculations via density functional theory (DFT) with periodic boundary conditions have allowed accurate computation of dielectric properties in molecular materials. In this Account, we outline the methodology used to calculate dielectric properties of molecular materials. We demonstrate the validity of this approach on model systems, capturing the frequency dependence of the dielectric response and achieving quantitative accuracy compared with experiment. This method is then used as a guide to new high-capacitance molecular dielectrics by determining what materials and chemical properties are important in maximizing dielectric response in self-assembled monolayers (SAMs). It will be seen that this technique is a powerful tool for understanding and designing new molecular dielectric systems, the properties of which are fundamental to many scientific areas.

Force-field parameters from the SAFT-γ equation of state for use in coarse-grained molecular simulations.

PubMed

Müller, Erich A; Jackson, George

2014-01-01

A description of fluid systems with molecular-based algebraic equations of state (EoSs) and by direct molecular simulation is common practice in chemical engineering and the physical sciences, but the two approaches are rarely closely coupled. The key for an integrated representation is through a well-defined force field and Hamiltonian at the molecular level. In developing coarse-grained intermolecular potential functions for the fluid state, one typically starts with a detailed, bottom-up quantum-mechanical or atomic-level description and then integrates out the unwanted degrees of freedom using a variety of techniques; an iterative heuristic simulation procedure is then used to refine the parameters of the model. By contrast, with a top-down technique, one can use an accurate EoS to link the macroscopic properties of the fluid and the force-field parameters. We discuss the latest developments in a top-down representation of fluids, with a particular focus on a group-contribution formulation of the statistical associating fluid theory (SAFT-γ). The accurate SAFT-γ EoS is used to estimate the parameters of the Mie force field, which can then be used with confidence in direct molecular simulations to obtain thermodynamic, structural, interfacial, and dynamical properties that are otherwise inaccessible from the EoS. This is exemplified for several prototypical fluids and mixtures, including carbon dioxide, hydrocarbons, perfluorohydrocarbons, and aqueous surfactants.

Polymer physics experiments with single DNA molecules

NASA Astrophysics Data System (ADS)

Smith, Douglas E.

1999-11-01

Bacteriophage DNA molecules were taken as a model flexible polymer chain for the experimental study of polymer dynamics at the single molecule level. Video fluorescence microscopy was used to directly observe the conformational dynamics of fluorescently labeled molecules, optical tweezers were used to manipulate individual molecules, and micro-fabricated flow cells were used to apply controlled hydrodynamic strain to molecules. These techniques constitute a powerful new experimental approach in the study of basic polymer physics questions. I have used these techniques to study the diffusion and relaxation of isolated and entangled polymer molecules and the hydrodynamic deformation of polymers in elongational and shear flows. These studies revealed a rich, and previously unobserved, ``molecular individualism'' in the dynamical behavior of single molecules. Individual measurements on ensembles of identical molecules allowed the average conformation to be determined as well as the underlying probability distributions for molecular conformation. Scaling laws, that predict the dependence of properties on chain length and concentration, were also tested. The basic assumptions of the reptation model were directly confirmed by visualizing the dynamics of entangled chains.

In vitro assessment of phthalate acid esters-trypsin complex formation.

PubMed

Chi, Zhenxing; Zhao, Jing; Li, Weiguo; Araghi, Arash; Tan, Songwen

2017-10-01

In this work, interactions of three phthalate acid esters (PAEs), including dimethyl phthalate (DMP), diethyl phthalate (DEP) and dibutyl phthalate (DBP), with trypsin have been studied in vitro, under simulated physiological conditions using multi-spectroscopic techniques and molecular modeling. The results show that these PAEs can bind to the trypsin, forming trypsin-PAEs complexes, mainly via hydrophobic interactions, with the affinity order of DMP > DEP > DBP. Binding to the PAEs is found to result in molecular deformation of trypsin. The modeling results suggest that only DBP can bind with the amino acid residues of the catalytic triad and S1 binding pocket of trypsin, leading to potential competitive enzyme inhibition. Copyright © 2017 Elsevier Ltd. All rights reserved.

Molecular-level removal of proteinaceous contamination from model surfaces and biomedical device materials by air plasma treatment.

PubMed

Banerjee, K K; Kumar, S; Bremmell, K E; Griesser, H J

2010-11-01

Established methods for cleaning and sterilising biomedical devices may achieve removal of bioburden only at the macroscopic level while leaving behind molecular levels of contamination (mainly proteinaceous). This is of particular concern if the residue might contain prions. We investigated at the molecular level the removal of model and real-life proteinaceous contamination from model and practical surfaces by air plasma (ionised air) treatment. The surface-sensitive technique of X-ray photoelectron spectroscopy (XPS) was used to assess the removal of proteinaceous contamination, with the nitrogen (N1s) photoelectron signal as its marker. Model proteinaceous contamination (bovine serum albumin) adsorbed on to a model surface (silicon wafer) and the residual proteinaceous contamination resulting from incubating surgical stainless steel (a practical biomaterial) in whole human blood exhibited strong N1s signals [16.8 and 18.5 atomic percent (at.%), respectively] after thorough washing. After 5min air plasma treatment, XPS detected no nitrogen on the sample surfaces, indicating complete removal of proteinaceous contamination, down to the estimated XPS detection limit 10ng/cm(2). Applying the same plasma treatment, the 7.7at.% nitrogen observed on a clinically cleaned dental bur was reduced to a level reflective of new, as-received burs. Contact angle measurements and atomic force microscopy also indicated complete molecular-level removal of the proteinaceous contamination upon air plasma treatment. This study demonstrates the effectiveness of air plasma treatment for removing proteinaceous contamination from both model and practical surfaces and offers a method for ensuring that no molecular residual contamination such as prions is transferred upon re-use of surgical and dental instruments. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Comparative molecular field analysis to derive pharmacophore maps for induction doses of intravenous anaesthetic agents.

PubMed

Sear, J W

2011-03-01

The present study examines the molecular basis of induction of anaesthesia by i.v. hypnotic agents using comparative molecular field analysis (CoMFA). ED(50) induction doses for 14 i.v. anaesthetics in human subjects (expressed as molar dose per kilogram body weight) were obtained from the literature. Immobilizing potency data for the same 14 agents (expressed as the EC(50) plasma free drug concentrations that abolish movement in response to a noxious stimulus in 50% patients) were taken from our previous publication. These data were used to form CoMFA models for the two aspects of anaesthetic activity. Molecular alignment was achieved by field-fit minimization techniques. The lead structure for both models was eltanolone. The final CoMFA model for the ED(50) induction dose was based on two latent variables, and explained 99.3% of the variance in observed activities. It showed good intrinsic predictability (cross-validated q(2)=0.849). The equivalent model for immobilizing activity was also based on two latent variables, with r(2)=0.988 and q(2)=0.852. Although there was a correlation between -log ED(50) and -log EC(50) (r(2)=0.779), comparison of the pharmacophore maps showed poor correlation for both electrostatic and steric regions when isocontours were constructed by linking lattice grid points, making the greatest 40% contributions; the relative contributions of electrostatic and steric interactions differing between the models (induction dose: 2.5:1; immobilizing activity 1.8:1). Comparison of two CoMFA activity models shows only small elements of commonality, suggesting that different molecular features may be responsible for these two properties of i.v. anaesthetics.

Computational strategies to address chromatin structure problems

NASA Astrophysics Data System (ADS)

Perišić, Ognjen; Schlick, Tamar

2016-06-01

While the genetic information is contained in double helical DNA, gene expression is a complex multilevel process that involves various functional units, from nucleosomes to fully formed chromatin fibers accompanied by a host of various chromatin binding enzymes. The chromatin fiber is a polymer composed of histone protein complexes upon which DNA wraps, like yarn upon many spools. The nature of chromatin structure has been an open question since the beginning of modern molecular biology. Many experiments have shown that the chromatin fiber is a highly dynamic entity with pronounced structural diversity that includes properties of idealized zig-zag and solenoid models, as well as other motifs. This diversity can produce a high packing ratio and thus inhibit access to a majority of the wound DNA. Despite much research, chromatin’s dynamic structure has not yet been fully described. Long stretches of chromatin fibers exhibit puzzling dynamic behavior that requires interpretation in the light of gene expression patterns in various tissue and organisms. The properties of chromatin fiber can be investigated with experimental techniques, like in vitro biochemistry, in vivo imagining, and high-throughput chromosome capture technology. Those techniques provide useful insights into the fiber’s structure and dynamics, but they are limited in resolution and scope, especially regarding compact fibers and chromosomes in the cellular milieu. Complementary but specialized modeling techniques are needed to handle large floppy polymers such as the chromatin fiber. In this review, we discuss current approaches in the chromatin structure field with an emphasis on modeling, such as molecular dynamics and coarse-grained computational approaches. Combinations of these computational techniques complement experiments and address many relevant biological problems, as we will illustrate with special focus on epigenetic modulation of chromatin structure.

Illuminating necrosis: From mechanistic exploration to preclinical application using fluorescence molecular imaging with indocyanine green

PubMed Central

Fang, Cheng; Wang, Kun; Zeng, Chaoting; Chi, Chongwei; Shang, Wenting; Ye, Jinzuo; Mao, Yamin; Fan, Yingfang; Yang, Jian; Xiang, Nan; Zeng, Ning; Zhu, Wen; Fang, Chihua; Tian, Jie

2016-01-01

Tissue necrosis commonly accompanies the development of a wide range of serious diseases. Therefore, highly sensitive detection and precise boundary delineation of necrotic tissue via effective imaging techniques are crucial for clinical treatments; however, no imaging modalities have achieved satisfactory results to date. Although fluorescence molecular imaging (FMI) shows potential in this regard, no effective necrosis-avid fluorescent probe has been developed for clinical applications. Here, we demonstrate that indocyanine green (ICG) can achieve high avidity of necrotic tissue owing to its interaction with lipoprotein (LP) and phospholipids. The mechanism was explored at the cellular and molecular levels through a series of in vitro studies. Detection of necrotic tissue and real-time image-guided surgery were successfully achieved in different organs of different animal models with the help of FMI using in house-designed imaging devices. The results indicated that necrotic tissue with a 0.6 mm diameter could be effectively detected with precise boundary definition. We believe that the new discovery and the associated imaging techniques will improve personalized and precise surgery in the near future. PMID:26864116

ExoMol molecular line lists - XXVII: spectra of C2H4

NASA Astrophysics Data System (ADS)

Mant, Barry P.; Yachmenev, Andrey; Yurchenko, Jonathan Tennyson Sergei N.

2018-05-01

A new line list for ethylene, 12C21H4 is presented. The line list is based on high level ab initiopotential energy and dipole moment surfaces. The potential energy surface is refined by fitting to experimental energies. The line list covers the range up to 7000 cm-1(1.43 μm) with all ro-vibrational transitions (50 billion) with the lower state below 5000 cm-1included and thus should be applicable for temperatures up to 700 K. A technique for computing molecular opacities from vibrational band intensities is proposed and used to provide temperature dependent cross sections of ethylene for shorter wavelength and higher temperatures. When combined with realistic band profiles (such as the proposed three-band model), the vibrational intensity technique offers a cheap but reasonably accurate alternative to the full ro-vibrational calculations at high temperatures and should be reliable for representing molecular opacities. The C2H4 line list, which is called MaYTY, is rmade available in electronic form from the CDS (http://cdsarc.u-strasbg.fr) and ExoMol (www.exomol.com) databases.

From classical to quantum and back: Hamiltonian adaptive resolution path integral, ring polymer, and centroid molecular dynamics

NASA Astrophysics Data System (ADS)

Kreis, Karsten; Kremer, Kurt; Potestio, Raffaello; Tuckerman, Mark E.

2017-12-01

Path integral-based methodologies play a crucial role for the investigation of nuclear quantum effects by means of computer simulations. However, these techniques are significantly more demanding than corresponding classical simulations. To reduce this numerical effort, we recently proposed a method, based on a rigorous Hamiltonian formulation, which restricts the quantum modeling to a small but relevant spatial region within a larger reservoir where particles are treated classically. In this work, we extend this idea and show how it can be implemented along with state-of-the-art path integral simulation techniques, including path-integral molecular dynamics, which allows for the calculation of quantum statistical properties, and ring-polymer and centroid molecular dynamics, which allow the calculation of approximate quantum dynamical properties. To this end, we derive a new integration algorithm that also makes use of multiple time-stepping. The scheme is validated via adaptive classical-path-integral simulations of liquid water. Potential applications of the proposed multiresolution method are diverse and include efficient quantum simulations of interfaces as well as complex biomolecular systems such as membranes and proteins.

Molecular-Scale Investigation of Heavy Metal Ions at a Charged Langmuir Monolayer

NASA Astrophysics Data System (ADS)

Rock, William; Qiao, Baofu; Uysal, Ahmet; Bu, Wei; Lin, Binhua

Solvent extraction - the surfactant-aided preferential transfer of a species from an aqueous to an organic phase - is an important technique used in heavy and precious metal refining and reprocessing. Solvent extraction requires transfer through an oil/water interface, and interfacial interactions are expected to control transfer kinetics and phase stability, yet these key interactions are poorly understood. Langmuir monolayers with charged headgroups atop concentrated salt solutions containing heavy metal ions act as a model of solvent extraction interfaces; studies of ions at a charged surface are also fundamentally important to many other phenomena including protein solvation, mineral surface chemistry, and electrochemistry. We probe these charged interfaces using a variety of surface-sensitive techniques - vibrational sum frequency generation (VSFG) spectroscopy, x-ray reflectivity (XRR), x-ray fluorescence near total reflection (XFNTR), and grazing incidence diffraction (GID). We integrate experiments with Molecular Dynamics (MD) simulations to uncover the molecular-level interfacial structure. This work is supported by the U.S. DOE, BES, Contract DE-AC02-06CH11357. ChemMatCARS is supported by NSF/CHE-1346572.

Inelastic effects in molecular transport junctions: The probe technique at high bias

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kilgour, Michael; Segal, Dvira, E-mail: dsegal@chem.utoronto.ca

2016-03-28

We extend the Landauer-Büttiker probe formalism for conductances to the high bias regime and study the effects of environmentally induced elastic and inelastic scattering on charge current in single molecule junctions, focusing on high-bias effects. The probe technique phenomenologically incorporates incoherent elastic and inelastic effects to the fully coherent case, mimicking a rich physical environment at trivial cost. We further identify environmentally induced mechanisms which generate an asymmetry in the current, manifested as a weak diode behavior. This rectifying behavior, found in two types of molecular junction models, is absent in the coherent-elastic limit and is only active in themore » case with incoherent-inelastic scattering. Our work illustrates that in the low bias-linear response regime, the commonly used “dephasing probe” (mimicking only elastic decoherence effects) operates nearly indistinguishably from a “voltage probe” (admitting inelastic-dissipative effects). However, these probes realize fundamentally distinct I-V characteristics at high biases, reflecting the central roles of dissipation and inelastic scattering processes on molecular electronic transport far-from-equilibrium.« less

An accurate computational method for an order parameter with a Markov state model constructed using a manifold-learning technique

NASA Astrophysics Data System (ADS)

Ito, Reika; Yoshidome, Takashi

2018-01-01

Markov state models (MSMs) are a powerful approach for analyzing the long-time behaviors of protein motion using molecular dynamics simulation data. However, their quantitative performance with respect to the physical quantities is poor. We believe that this poor performance is caused by the failure to appropriately classify protein conformations into states when constructing MSMs. Herein, we show that the quantitative performance of an order parameter is improved when a manifold-learning technique is employed for the classification in the MSM. The MSM construction using the K-center method, which has been previously used for classification, has a poor quantitative performance.

A window on disease pathogenesis and potential therapeutic strategies: molecular imaging for arthritis

PubMed Central

2011-01-01

Novel molecular imaging techniques are at the forefront of both preclinical and clinical imaging strategies. They have significant potential to offer visualisation and quantification of molecular and cellular changes in health and disease. This will help to shed light on pathobiology and underlying disease processes and provide further information about the mechanisms of action of novel therapeutic strategies. This review explores currently available molecular imaging techniques that are available for preclinical studies with a focus on optical imaging techniques and discusses how current and future advances will enable translation into the clinic for patients with arthritis. PMID:21345267

Molecular Imprinting Techniques Used for the Preparation of Biosensors

PubMed Central

Ertürk, Gizem; Mattiasson, Bo

2017-01-01

Molecular imprinting is the technology of creating artificial recognition sites in polymeric matrices which are complementary to the template in their size, shape and spatial arrangement of the functional groups. Molecularly imprinted polymers (MIPs) and their incorporation with various transducer platforms are among the most promising approaches for detection of several analytes. There are a variety of molecular imprinting techniques used for the preparation of biomimetic sensors including bulk imprinting, surface imprinting (soft lithography, template immobilization, grafting, emulsion polymerization) and epitope imprinting. This chapter presents an overview of all of these techniques with examples from particular publications. PMID:28165419

Assessment of Knowledge of Participants on Basic Molecular Biology Techniques after 5-Day Intensive Molecular Biology Training Workshops in Nigeria

ERIC Educational Resources Information Center

Yisau, J. I.; Adagbada, A. O.; Bamidele, T.; Fowora, M.; Brai, B. I. C.; Adebesin, O.; Bamidele, M.; Fesobi, T.; Nwaokorie, F. O.; Ajayi, A.; Smith, S. I.

2017-01-01

The deployment of molecular biology techniques for diagnosis and research in Nigeria is faced with a number of challenges, including the cost of equipment and reagents coupled with the dearth of personnel skilled in the procedures and handling of equipment. Short molecular biology training workshops were conducted at the Nigerian Institute of…

Perspective: Reaches of chemical physics in biology.

PubMed

Gruebele, Martin; Thirumalai, D

2013-09-28

Chemical physics as a discipline contributes many experimental tools, algorithms, and fundamental theoretical models that can be applied to biological problems. This is especially true now as the molecular level and the systems level descriptions begin to connect, and multi-scale approaches are being developed to solve cutting edge problems in biology. In some cases, the concepts and tools got their start in non-biological fields, and migrated over, such as the idea of glassy landscapes, fluorescence spectroscopy, or master equation approaches. In other cases, the tools were specifically developed with biological physics applications in mind, such as modeling of single molecule trajectories or super-resolution laser techniques. In this introduction to the special topic section on chemical physics of biological systems, we consider a wide range of contributions, all the way from the molecular level, to molecular assemblies, chemical physics of the cell, and finally systems-level approaches, based on the contributions to this special issue. Chemical physicists can look forward to an exciting future where computational tools, analytical models, and new instrumentation will push the boundaries of biological inquiry.

3D Pharmacophore-Based Virtual Screening and Docking Approaches toward the Discovery of Novel HPPD Inhibitors.

PubMed

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2017-06-09

p -Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking-based virtual screening were performed to identify novel potential HPPD inhibitors. The complex-based pharmacophore model (CBP) with 0.721 of ROC used for screening compounds showed remarkable ability to retrieve known active ligands from among decoy molecules. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5 (DS 2.5) to discern interactions with key residues at the active site of HPPD. Four compounds with top rankings in the HipHop model and well-known binding model were finally chosen as lead compounds with potential inhibitory effects on the active site of target. The results provided powerful insight into the development of novel HPPD inhibitors herbicides using computational techniques.

Perspective: Reaches of chemical physics in biology

PubMed Central

Gruebele, Martin; Thirumalai, D.

2013-01-01

Chemical physics as a discipline contributes many experimental tools, algorithms, and fundamental theoretical models that can be applied to biological problems. This is especially true now as the molecular level and the systems level descriptions begin to connect, and multi-scale approaches are being developed to solve cutting edge problems in biology. In some cases, the concepts and tools got their start in non-biological fields, and migrated over, such as the idea of glassy landscapes, fluorescence spectroscopy, or master equation approaches. In other cases, the tools were specifically developed with biological physics applications in mind, such as modeling of single molecule trajectories or super-resolution laser techniques. In this introduction to the special topic section on chemical physics of biological systems, we consider a wide range of contributions, all the way from the molecular level, to molecular assemblies, chemical physics of the cell, and finally systems-level approaches, based on the contributions to this special issue. Chemical physicists can look forward to an exciting future where computational tools, analytical models, and new instrumentation will push the boundaries of biological inquiry. PMID:24089712

Using "Pseudomonas Putida xylE" Gene to Teach Molecular Cloning Techniques for Undergraduates

ERIC Educational Resources Information Center

Dong, Xu; Xin, Yi; Ye, Li; Ma, Yufang

2009-01-01

We have developed and implemented a serial experiment in molecular cloning laboratory course for undergraduate students majored in biotechnology. "Pseudomonas putida xylE" gene, encoding catechol 2, 3-dioxygenase, was manipulated to learn molecular biology techniques. The integration of cloning, expression, and enzyme assay gave students…

Predicting Biological Information Flow in a Model Oxygen Minimum Zone

NASA Astrophysics Data System (ADS)

Louca, S.; Hawley, A. K.; Katsev, S.; Beltran, M. T.; Bhatia, M. P.; Michiels, C.; Capelle, D.; Lavik, G.; Doebeli, M.; Crowe, S.; Hallam, S. J.

2016-02-01

Microbial activity drives marine biochemical fluxes and nutrient cycling at global scales. Geochemical measurements as well as molecular techniques such as metagenomics, metatranscriptomics and metaproteomics provide great insight into microbial activity. However, an integration of molecular and geochemical data into mechanistic biogeochemical models is still lacking. Recent work suggests that microbial metabolic pathways are, at the ecosystem level, strongly shaped by stoichiometric and energetic constraints. Hence, models rooted in fluxes of matter and energy may yield a holistic understanding of biogeochemistry. Furthermore, such pathway-centric models would allow a direct consolidation with meta'omic data. Here we present a pathway-centric biogeochemical model for the seasonal oxygen minimum zone in Saanich Inlet, a fjord off the coast of Vancouver Island. The model considers key dissimilatory nitrogen and sulfur fluxes, as well as the population dynamics of the genes that mediate them. By assuming a direct translation of biocatalyzed energy fluxes to biosynthesis rates, we make predictions about the distribution and activity of the corresponding genes. A comparison of the model to molecular measurements indicates that the model explains observed DNA, RNA, protein and cell depth profiles. This suggests that microbial activity in marine ecosystems such as oxygen minimum zones is well described by DNA abundance, which, in conjunction with geochemical constraints, determines pathway expression and process rates. Our work further demonstrates how meta'omic data can be mechanistically linked to environmental redox conditions and biogeochemical processes.

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents.

PubMed

Balakumar, Chandrasekaran; Ramesh, Muthusamy; Tham, Chuin Lean; Khathi, Samukelisiwe Pretty; Kozielski, Frank; Srinivasulu, Cherukupalli; Hampannavar, Girish A; Sayyad, Nisar; Soliman, Mahmoud E; Karpoormath, Rajshekhar

2017-11-29

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.

Structure–Function Analysis of the Non-Muscle Myosin Light Chain Kinase (nmMLCK) Isoform by NMR Spectroscopy and Molecular Modeling: Influence of MYLK Variants

PubMed Central

Shen, Kui; Ramirez, Benjamin; Mapes, Brandon; Shen, Grace R.; Gokhale, Vijay; Brown, Mary E.; Santarsiero, Bernard; Ishii, Yoshitaka; Dudek, Steven M.; Wang, Ting; Garcia, Joe G. N.

2015-01-01

The MYLK gene encodes the multifunctional enzyme, myosin light chain kinase (MLCK), involved in isoform-specific non-muscle and smooth muscle contraction and regulation of vascular permeability during inflammation. Three MYLK SNPs (P21H, S147P, V261A) alter the N-terminal amino acid sequence of the non-muscle isoform of MLCK (nmMLCK) and are highly associated with susceptibility to acute lung injury (ALI) and asthma, especially in individuals of African descent. To understand the functional effects of SNP associations, we examined the N-terminal segments of nmMLCK by 1H-15N heteronuclear single quantum correlation (HSQC) spectroscopy, a 2-D NMR technique, and by in silico molecular modeling. Both NMR analysis and molecular modeling indicated SNP localization to loops that connect the immunoglobulin-like domains of nmMLCK, consistent with minimal structural changes evoked by these SNPs. Molecular modeling analysis identified protein-protein interaction motifs adversely affected by these MYLK SNPs including binding by the scaffold protein 14-3-3, results confirmed by immunoprecipitation and western blot studies. These structure-function studies suggest novel mechanisms for nmMLCK regulation, which may confirm MYLK as a candidate gene in inflammatory lung disease and advance knowledge of the genetic underpinning of lung-related health disparities. PMID:26111161

Modeling and Prediction of Drug Dispersability in Polyvinylpyrrolidone-Vinyl Acetate Copolymer Using a Molecular Descriptor.

PubMed

DeBoyace, Kevin; Buckner, Ira S; Gong, Yuchuan; Ju, Tzu-Chi Rob; Wildfong, Peter L D

2018-01-01

The expansion of a novel in silico model for the prediction of the dispersability of 18 model compounds with polyvinylpyrrolidone-vinyl acetate copolymer is described. The molecular descriptor R3m (atomic mass weighted 3rd-order autocorrelation index) is shown to be predictive of the formation of amorphous solid dispersions at 2 drug loadings (15% and 75% w/w) using 2 preparation methods (melt quenching and solvent evaporation using a rotary evaporator). Cosolidified samples were characterized using a suite of analytical techniques, which included differential scanning calorimetry, powder X-ray diffraction, pair distribution function analysis, polarized light microscopy, and hot stage microscopy. Logistic regression was applied, where appropriate, to model the success and failure of compound dispersability in polyvinylpyrrolidone-vinyl acetate copolymer. R3m had combined prediction accuracy greater than 90% for tested samples. The usefulness of this descriptor appears to be associated with the presence of heavy atoms in the molecular structure of the active pharmaceutical ingredient, and their location with respect to the geometric center of the molecule. Given the higher electronegativity and atomic volume of these types of atoms, it is hypothesized that they may impact the molecular mobility of the active pharmaceutical ingredient, or increase the likelihood of forming nonbonding interactions with the carrier polymer. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Prognostic factors, predictive markers and cancer biology: the triad for successful oral cancer chemoprevention.

PubMed

Monteiro de Oliveira Novaes, Jose Augusto; William, William N

2016-10-01

Oral squamous cell carcinomas represent a significant cancer burden worldwide. Unfortunately, chemoprevention strategies investigated to date have failed to produce an agent considered standard of care to prevent oral cancers. Nonetheless, recent advances in clinical trial design may streamline drug development in this setting. In this manuscript, we review some of these improvements, including risk prediction tools based on molecular markers that help select patients most suitable for chemoprevention. We also discuss the opportunities that novel preclinical models and modern molecular profiling techniques will bring to the prevention field in the near future, and propose a clinical trials framework that incorporates molecular prognostic factors, predictive markers and cancer biology as a roadmap to improve chemoprevention strategies for oral cancers.

Molecular gas excitation in Kleinmann-Low nebula

NASA Astrophysics Data System (ADS)

Callejo, Gonzague; Lemaire, Jean-Louis; Le Petit, F.; Pineau Des Forets, Guillaume; Field, David

2004-12-01

The Orion molecular cloud OMC-1 is the perfect object for the study of the dense interstellar medium accounting for active star formation; the intrinsic complexity of this region serves as a stallion, both for observing techniques and for interstellar medium modelling. A detailed dynamic and spectroscopic study has been performed using VLT and CFHT observations of the infrared Kleinmann-Low nebula; yielding a complete small-scale structure in velocity and most importantly powerful diagnosis tools in order to put a new light into the gas behaviour. These results allow to build up a consistent model of the gas excitation, and a clear dynamical view of the region. The crucial action of the shock waves is confirmed, and the discrepancies between the observations and the standard models are discussed. The consequences of this modelling will be discussed in terms of extinction, magnetic field, and other quantities related to induced star formation. The goodness of the models used for the interpretations will be also discussed and some future directions of investigation enhanced.

Integration of a zebrafish research project into a molecular biology course to support critical thinking and course content goals.

PubMed

Felzien, Lisa K

2016-11-12

Engaging undergraduates in research is essential for teaching them to think like scientists, and it has become a desired component of classroom and laboratory instruction. Research projects that span an entire semester expose students to a variety of concepts and techniques and allow students to use experiments to learn scientific principles, understand why specific techniques are applicable, critically analyze varied data, and examine how experimentation leads to acquiring knowledge. To provide an experience with these features, a semester long research project was integrated into a combined lecture and laboratory course, Molecular Biology. The project utilized the zebrafish model to examine gene expression during embryonic development and required students to develop and test hypotheses about the timing of expression of previously uncharacterized genes. The main goals for the project were to provide opportunities for students to develop critical thinking skills required for conducting research and to support the content goals of the course. To determine whether these goals were met, student performance on the steps of the project and related pre-test and post-test questions was examined. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(6):565-573, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

A Bone-Implant Interaction Mouse Model for Evaluating Molecular Mechanism of Biomaterials/Bone Interaction.

PubMed

Liu, Wenlong; Dan, Xiuli; Wang, Ting; Lu, William W; Pan, Haobo

2016-11-01

The development of an optimal animal model that could provide fast assessments of the interaction between bone and orthopedic implants is essential for both preclinical and theoretical researches in the design of novel biomaterials. Compared with other animal models, mice have superiority in accessing the well-developed transgenic modification techniques (e.g., cell tracing, knockoff, knockin, and so on), which serve as powerful tools in studying molecular mechanisms. In this study, we introduced the establishment of a mouse model, which was specifically tailored for the assessment of bone-implant interaction in a load-bearing bone marrow microenvironment and could potentially allow the molecular mechanism study of biomaterials by using transgenic technologies. The detailed microsurgery procedures for developing a bone defect (Φ = 0.8 mm) at the metaphysis region of the mouse femur were recorded. According to our results, the osteoconductive and osseointegrative properties of a well-studied 45S5 bioactive glass were confirmed by utilizing our mouse model, verifying the reliability of this model. The feasibility and reliability of the present model were further checked by using other materials as objects of study. Furthermore, our results indicated that this animal model provided a more homogeneous tissue-implant interacting surface than the rat at the early stage of implantation and this is quite meaningful for conducting quantitative analysis. The availability of transgenic techniques to mechanism study of biomaterials was further testified by establishing our model on Nestin-GFP transgenic mice. Intriguingly, the distribution of Nestin + cells was demonstrated to be recruited to the surface of 45S5 glass as early as 3 days postsurgery, indicating that Nestin + lineage stem cells may participate in the subsequent regeneration process. In summary, the bone-implant interaction mouse model could serve as a potential candidate to evaluate the early stage tissue response near the implant surface in a bone marrow microenvironment, and it also shows great potential in making transgenic animal resource applicable to biomaterial studies, so that the design of novel biomaterials could be better guided.

Significance and integration of molecular diagnostics in the framework of veterinary practice.

PubMed

Aranaz, Alicia

2015-01-01

The field of molecular diagnostics in veterinary practice is rapidly evolving. An array of molecular techniques of different complexity is available to facilitate the fast and specific diagnosis of animal diseases. The choice for the adequate technique is dependent on the mission and attributions of the laboratory and requires both a knowledge of the molecular biology basis and of its limitations. The ability to quickly detect pathogens and their characteristics would allow for precise decision-making and target measures such as prophylaxis, appropriate therapy, and biosafety plans to control disease outbreaks. In practice, taking benefit of the huge amount of data that can be obtained using molecular techniques highlights the need of collaboration between veterinarians in the laboratory and practitioners.

Quantitative molecular characterization of bovine vitreous and lens with non-invasive dynamic light scattering

NASA Technical Reports Server (NTRS)

Ansari, R. R.; Suh, K. I.; Dunker, S.; Kitaya, N.; Sebag, J.

2001-01-01

The non-invasive technique of dynamic light scattering (DLS) was used to quantitatively characterize vitreous and lens structure on a molecular level by measuring the sizes of the predominant particles and mapping the three-dimensional topographic distribution of these structural macromolecules in three spatial dimensions. The results of DLS measurements in five fresh adult bovine eyes were compared to DLS measurements in model solutions of hyaluronan (HA) and collagen (Coll). In the bovine eyes DLS measurements were obtained from excised samples of gel and liquid vitreous and compared to the model solutions. Measurements in whole vitreous were obtained at multiple points posterior to the lens to generate a three-dimensional 'map' of molecular structure. The macromolecule distribution in bovine lens was similarly characterized.In each bovine vitreous (Bo Vit) specimen, DLS predominantly detected two distinct particles, which differed in diffusion properties and hence size. Comparisons with model vitreous solutions demonstrated that these most likely corresponded to the Coll and HA components of vitreous. Three-dimensional mapping of Bo Vit found heterogeneity throughout the vitreous body, with different particle size distributions for Coll and HA at different loci. In contrast, the three-dimensional distribution of lens macromolecules was more homogeneous. Thus, the non-invasive DLS technique can quantitate the average sizes of vitreous and lens macromolecules and map their three-dimensional distribution. This method to assess quantitatively the macromolecular structure of vitreous and lens should be useful for clinical as well as experimental applications in health and disease. Copyright 2001 Academic Press.

Novel methodology developments in modern molecular simulations

NASA Astrophysics Data System (ADS)

Minary, Peter

The present thesis aims to summarize novel methodological developments and their uses in the rapidly expanding field of molecular simulations. A new formalism designed to treat long range interactions on surfaces/wires, systems which are infinitely replicated in two/one spatial directions but have finite extent in the remaining dimensions, is developed in the first part of this thesis. The method is tested on both model and realistic problems and is found to be accurate, efficient and a marked improvement over existing formulations in speed, accuracy and utility. In the second part of this thesis, a novel ab initio molecular dynamics technique capable of treating metallic systems and highly exothermic chemical reactions is presented. The combination of the aforementioned methods are applied in the next part to study functionalization reactions at the Si(100)-2x1 semiconductor interface. Here, a set of forty finite temperature ab initio molecular dynamics trajectories is employed to investigate the microscopic mechanism of the addition of 1,3-butadiene to the Si(100)-2x1 surface. The detailed study of the trajectories indicate a common non-concerted stepwise mechanism that proceeds via an intermediate carbocation. In the remaining parts of the thesis, a novel set of methods is introduced to significantly enhance conformational sampling in molecular dynamics simulations of biomolecular systems. First, a new set of equations of motion and a reversible, resonance free, integrator are developed which permits step sizes on the order of 100 fs to be used. The new technique provides sufficient sampling to impact studies of the 200--300 residue proteins of greatest interest. Second, it is shown that combining molecular dynamics with novel variable transformations designed to warp configuration space so as to reduce barrier regions and enhance attractive basins lead to substantial gains in conformational sampling efficiency. Here, new transformations designed to overcome barriers induced by intermolecular interactions are introduced. The method is shown to substantially enhance conformational sampling in long alkane chains and in a model protein over standard molecular dynamics as well as parallel tempering.

Development of an in Silico Model of DPPH• Free Radical Scavenging Capacity: Prediction of Antioxidant Activity of Coumarin Type Compounds.

PubMed

Goya Jorge, Elizabeth; Rayar, Anita Maria; Barigye, Stephen J; Jorge Rodríguez, María Elisa; Sylla-Iyarreta Veitía, Maité

2016-06-07

A quantitative structure-activity relationship (QSAR) study of the 2,2-diphenyl-l-picrylhydrazyl (DPPH•) radical scavenging ability of 1373 chemical compounds, using DRAGON molecular descriptors (MD) and the neural network technique, a technique based on the multilayer multilayer perceptron (MLP), was developed. The built model demonstrated a satisfactory performance for the training ( R 2 = 0.713 ) and test set ( Q ext 2 = 0.654 ) , respectively. To gain greater insight on the relevance of the MD contained in the MLP model, sensitivity and principal component analyses were performed. Moreover, structural and mechanistic interpretation was carried out to comprehend the relationship of the variables in the model with the modeled property. The constructed MLP model was employed to predict the radical scavenging ability for a group of coumarin-type compounds. Finally, in order to validate the model's predictions, an in vitro assay for one of the compounds (4-hydroxycoumarin) was performed, showing a satisfactory proximity between the experimental and predicted pIC50 values.

Early years of Computational Statistical Mechanics

NASA Astrophysics Data System (ADS)

Mareschal, Michel

2018-05-01

Evidence that a model of hard spheres exhibits a first-order solid-fluid phase transition was provided in the late fifties by two new numerical techniques known as Monte Carlo and Molecular Dynamics. This result can be considered as the starting point of computational statistical mechanics: at the time, it was a confirmation of a counter-intuitive (and controversial) theoretical prediction by J. Kirkwood. It necessitated an intensive collaboration between the Los Alamos team, with Bill Wood developing the Monte Carlo approach, and the Livermore group, where Berni Alder was inventing Molecular Dynamics. This article tells how it happened.

Mechanisms of X Chromosome Dosage Compensation

PubMed Central

Ercan, Sevinç

2015-01-01

In many animals, males have one X and females have two X chromosomes. The difference in X chromosome dosage between the two sexes is compensated by mechanisms that regulate X chromosome transcription. Recent advances in genomic techniques have provided new insights into the molecular mechanisms of X chromosome dosage compensation. In this review, I summarize our current understanding of dosage imbalance in general, and then review the molecular mechanisms of X chromosome dosage compensation with an emphasis on the parallels and differences between the three well-studied model systems, M. musculus, D. melanogaster and C. elegans. PMID:25628761

Molecular beam epitaxy growth method for vertical-cavity surface-emitting laser resonators based on substrate thermal emission

NASA Astrophysics Data System (ADS)

Talghader, J. J.; Hadley, M. A.; Smith, J. S.

1995-12-01

A molecular beam epitaxy growth monitoring method is developed for distributed Bragg reflectors and vertical-cavity surface-emitting laser (VCSEL) resonators. The wavelength of the substrate thermal emission that corresponds to the optical cavity resonant wavelength is selected by a monochromator and monitored during growth. This method allows VCSEL cavities of arbitrary design wavelength to be grown with a single control program. This letter also presents a theoretical model for the technique which is based on transmission matrices and simple thermal emission properties. Demonstrated reproducibility of the method is well within 0.1%.

Scaffold-based novel SHP2 allosteric inhibitors design using Receptor-Ligand pharmacophore model, virtual screening and molecular dynamics.

PubMed

Jin, Wen-Yan; Ma, Ying; Li, Wei-Ya; Li, Hong-Lian; Wang, Run-Ling

2018-04-01

SHP2 is a potential target for the development of novel therapies for SHP2-dependent cancers. In our research, with the aid of the 'Receptor-Ligand Pharmacophore' technique, a 3D-QSAR method was carried out to explore structure activity relationship of SHP2 allosteric inhibitors. Structure-based drug design was employed to optimize SHP099, an efficacious, potent, and selective SHP2 allosteric inhibitor. A novel class of selective SHP2 allosteric inhibitors was discovered by using the powerful 'SBP', 'ADMET' and 'CDOCKER' techniques. By means of molecular dynamics simulations, it was observed that these novel inhibitors not only had the same function as SHP099 did in inhibiting SHP2, but also had more favorable conformation for binding to the receptor. Thus, this report may provide a new method in discovering novel and selective SHP2 allosteric inhibitors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

The Neuro-Oncology Branch (NOB), Center for Cancer Research (CCR), National Cancer Institute (NCI) of the National Institutes of Health (NIH) is seeking outstanding postdoctoral candidates interested in studying the metabolic changes in brain tumors such as glioblastoma multiforme (GBMs).  NOB’s Metabolomics program is interested in revealing the metabolic alterations of isocitrate dehydrogenase (IDH1)-mutated GBMs and in exploiting these deregulations for therapeutic applications.  A combination of methods such as molecular biology, animal models, as well as in vitro and in vivo metabolomics using Raman Imaging Microscopy, Nuclear Magnetic Resonance spectroscopy (NMR), Mass Spectrometry (MS) and Magnetic Resonance Imaging (MRI) techniques are employed.  The position will specifically focus on molecular biology and Raman Imaging Microscopy, which includes work in Western Blotting, mammalian cell culture and other common biomedical techniques used in cancer bio  logy labs such as handling tissue samples, preparing tissue slides, staining, and extracting proteins from brain tissue.

Pyrite: A blender plugin for visualizing molecular dynamics simulations using industry-standard rendering techniques.

PubMed

Rajendiran, Nivedita; Durrant, Jacob D

2018-05-05

Molecular dynamics (MD) simulations provide critical insights into many biological mechanisms. Programs such as VMD, Chimera, and PyMOL can produce impressive simulation visualizations, but they lack many advanced rendering algorithms common in the film and video-game industries. In contrast, the modeling program Blender includes such algorithms but cannot import MD-simulation data. MD trajectories often require many gigabytes of memory/disk space, complicating Blender import. We present Pyrite, a Blender plugin that overcomes these limitations. Pyrite allows researchers to visualize MD simulations within Blender, with full access to Blender's cutting-edge rendering techniques. We expect Pyrite-generated images to appeal to students and non-specialists alike. A copy of the plugin is available at http://durrantlab.com/pyrite/, released under the terms of the GNU General Public License Version 3. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Multiscale Modeling of Mesoscale and Interfacial Phenomena

NASA Astrophysics Data System (ADS)

Petsev, Nikolai Dimitrov

With rapidly emerging technologies that feature interfaces modified at the nanoscale, traditional macroscopic models are pushed to their limits to explain phenomena where molecular processes can play a key role. Often, such problems appear to defy explanation when treated with coarse-grained continuum models alone, yet remain prohibitively expensive from a molecular simulation perspective. A prominent example is surface nanobubbles: nanoscopic gaseous domains typically found on hydrophobic surfaces that have puzzled researchers for over two decades due to their unusually long lifetimes. We show how an entirely macroscopic, non-equilibrium model explains many of their anomalous properties, including their stability and abnormally small gas-side contact angles. From this purely transport perspective, we investigate how factors such as temperature and saturation affect nanobubbles, providing numerous experimentally testable predictions. However, recent work also emphasizes the relevance of molecular-scale phenomena that cannot be described in terms of bulk phases or pristine interfaces. This is true for nanobubbles as well, whose nanoscale heights may require molecular detail to capture the relevant physics, in particular near the bubble three-phase contact line. Therefore, there is a clear need for general ways to link molecular granularity and behavior with large-scale continuum models in the treatment of many interfacial problems. In light of this, we have developed a general set of simulation strategies that couple mesoscale particle-based continuum models to molecular regions simulated through conventional molecular dynamics (MD). In addition, we derived a transport model for binary mixtures that opens the possibility for a wide range of applications in biological and drug delivery problems, and is readily reconciled with our hybrid MD-continuum techniques. Approaches that couple multiple length scales for fluid mixtures are largely absent in the literature, and we provide a novel and general framework for multiscale modeling of systems featuring one or more dissolved species. This makes it possible to retain molecular detail for parts of the problem that require it while using a simple, continuum description for parts where high detail is unnecessary, reducing the number of degrees of freedom (i.e. number of particles) dramatically. This opens the possibility for modeling ion transport in biological processes and biomolecule assembly in ionic solution, as well as electrokinetic phenomena at interfaces such as corrosion. The number of particles in the system is further reduced through an integrated boundary approach, which we apply to colloidal suspensions. In this thesis, we describe this general framework for multiscale modeling single- and multicomponent systems, provide several simple equilibrium and non-equilibrium case studies, and discuss future applications.

Teaching Molecular Biological Techniques in a Research Content

ERIC Educational Resources Information Center

Stiller, John W.; Coggins, T. Chad

2006-01-01

Molecular biological methods, such as the polymerase chain reaction (PCR) and gel electrophoresis, are now commonly taught to students in introductory biology courses at the college and even high school levels. This often includes hands-on experience with one or more molecular techniques as part of a general biology laboratory. To assure that most…

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

NASA Astrophysics Data System (ADS)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-09-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G., E-mail: yannis@princeton.edu, E-mail: gerhard.hummer@biophys.mpg.de

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlapmore » with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.« less

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

PubMed Central

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-01-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space. PMID:25240340

Omics approaches to individual variation: modeling networks and the virtual patient.

PubMed

Lehrach, Hans

2016-09-01

Every human is unique. We differ in our genomes, environment, behavior, disease history, and past and current medical treatment-a complex catalog of differences that often leads to variations in the way each of us responds to a particular therapy. We argue here that true personalization of drug therapies will rely on "virtual patient" models based on a detailed characterization of the individual patient by molecular, imaging, and sensor techniques. The models will be based, wherever possible, on the molecular mechanisms of disease processes and drug action but can also expand to hybrid models including statistics/machine learning/artificial intelligence-based elements trained on available data to address therapeutic areas or therapies for which insufficient information on mechanisms is available. Depending on the disease, its mechanisms, and the therapy, virtual patient models can be implemented at a fairly high level of abstraction, with molecular models representing cells, cell types, or organs relevant to the clinical question, interacting not only with each other but also the environment. In the future, "virtual patient/in-silico self" models may not only become a central element of our health care system, reducing otherwise unavoidable mistakes and unnecessary costs, but also act as "guardian angels" accompanying us through life to protect us against dangers and to help us to deal intelligently with our own health and wellness.

Omics approaches to individual variation: modeling networks and the virtual patient

PubMed Central

Lehrach, Hans

2016-01-01

Every human is unique. We differ in our genomes, environment, behavior, disease history, and past and current medical treatment—a complex catalog of differences that often leads to variations in the way each of us responds to a particular therapy. We argue here that true personalization of drug therapies will rely on “virtual patient” models based on a detailed characterization of the individual patient by molecular, imaging, and sensor techniques. The models will be based, wherever possible, on the molecular mechanisms of disease processes and drug action but can also expand to hybrid models including statistics/machine learning/artificial intelligence-based elements trained on available data to address therapeutic areas or therapies for which insufficient information on mechanisms is available. Depending on the disease, its mechanisms, and the therapy, virtual patient models can be implemented at a fairly high level of abstraction, with molecular models representing cells, cell types, or organs relevant to the clinical question, interacting not only with each other but also the environment. In the future, “virtual patient/in-silico self” models may not only become a central element of our health care system, reducing otherwise unavoidable mistakes and unnecessary costs, but also act as “guardian angels” accompanying us through life to protect us against dangers and to help us to deal intelligently with our own health and wellness. PMID:27757060

Quantum Mechanics/Molecular Mechanics Modeling of Enzymatic Processes: Caveats and Breakthroughs.

PubMed

Quesne, Matthew G; Borowski, Tomasz; de Visser, Sam P

2016-02-18

Nature has developed large groups of enzymatic catalysts with the aim to transfer substrates into useful products, which enables biosystems to perform all their natural functions. As such, all biochemical processes in our body (we drink, we eat, we breath, we sleep, etc.) are governed by enzymes. One of the problems associated with research on biocatalysts is that they react so fast that details of their reaction mechanisms cannot be obtained with experimental work. In recent years, major advances in computational hardware and software have been made and now large (bio)chemical systems can be studied using accurate computational techniques. One such technique is the quantum mechanics/molecular mechanics (QM/MM) technique, which has gained major momentum in recent years. Unfortunately, it is not a black-box method that is easily applied, but requires careful set-up procedures. In this work we give an overview on the technical difficulties and caveats of QM/MM and discuss work-protocols developed in our groups for running successful QM/MM calculations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

2012 Gordon Research Conference on Vibrational Spectroscopy - Formal Schedule and Speaker/Poster Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geiger, Franz

2012-08-10

The Vibrational Spectroscopy conference brings together experimentalists and theoreticians working at the frontiers of modern vibrational spectroscopy, with a special emphasis on spectroscopies that probe the structure and dynamics of molecules in gases, liquids, and at interfaces. The conference explores the wide range of state-of-the-art techniques based on vibrational motion. These techniques span the fields of time-domain, high-resolution frequency-domain, spatially-resolved, nonlinear, and multidimensional spectroscopies. The conference highlights both the application of these techniques in chemistry, materials, biology, the environment, and medicine as well as the development of theoretical models that enable one to connect spectroscopic signatures to underlying molecular motionsmore » including chemical reaction dynamics. The conference goal is to advance the field of vibrational spectroscopy by bringing together a collection of researchers who share common interests and who will gain from discussing work at the forefront of several connected areas. The intent is to emphasize the insights and understanding that studies of vibrations provide about a variety of molecular systems ranging from small polyatomic molecules to large biomolecules, nanomaterials, and environmental systems.« less

Evaluation of molecular dynamics simulation methods for ionic liquid electric double layers.

PubMed

Haskins, Justin B; Lawson, John W

2016-05-14

We investigate how systematically increasing the accuracy of various molecular dynamics modeling techniques influences the structure and capacitance of ionic liquid electric double layers (EDLs). The techniques probed concern long-range electrostatic interactions, electrode charging (constant charge versus constant potential conditions), and electrolyte polarizability. Our simulations are performed on a quasi-two-dimensional, or slab-like, model capacitor, which is composed of a polarizable ionic liquid electrolyte, [EMIM][BF4], interfaced between two graphite electrodes. To ensure an accurate representation of EDL differential capacitance, we derive new fluctuation formulas that resolve the differential capacitance as a function of electrode charge or electrode potential. The magnitude of differential capacitance shows sensitivity to different long-range electrostatic summation techniques, while the shape of differential capacitance is affected by charging technique and the polarizability of the electrolyte. For long-range summation techniques, errors in magnitude can be mitigated by employing two-dimensional or corrected three dimensional electrostatic summations, which led to electric fields that conform to those of a classical electrostatic parallel plate capacitor. With respect to charging, the changes in shape are a result of ions in the Stern layer (i.e., ions at the electrode surface) having a higher electrostatic affinity to constant potential electrodes than to constant charge electrodes. For electrolyte polarizability, shape changes originate from induced dipoles that soften the interaction of Stern layer ions with the electrode. The softening is traced to ion correlations vertical to the electrode surface that induce dipoles that oppose double layer formation. In general, our analysis indicates an accuracy dependent differential capacitance profile that transitions from the characteristic camel shape with coarser representations to a more diffuse profile with finer representations.

Evaluation of bending modulus of lipid bilayers using undulation and orientation analysis

NASA Astrophysics Data System (ADS)

Chaurasia, Adarsh K.; Rukangu, Andrew M.; Philen, Michael K.; Seidel, Gary D.; Freeman, Eric C.

2018-03-01

In the current paper, phospholipid bilayers are modeled using coarse-grained molecular dynamics simulations with the MARTINI force field. The extracted molecular trajectories are analyzed using Fourier analysis of the undulations and orientation vectors to establish the differences between the two approaches for evaluating the bending modulus. The current work evaluates and extends the implementation of the Fourier analysis for molecular trajectories using a weighted horizon-based averaging approach. The effect of numerical parameters in the analysis of these trajectories is explored by conducting parametric studies. Computational modeling results are validated against experimentally characterized bending modulus of lipid membranes using a shape fluctuation analysis. The computational framework is then used to estimate the bending moduli for different types of lipids (phosphocholine, phosphoethanolamine, and phosphoglycerol). This work provides greater insight into the numerical aspects of evaluating the bilayer bending modulus, provides validation for the orientation analysis technique, and explores differences in bending moduli based on differences in the lipid nanostructures.

Adaptation of Laser Microdissection Technique for the Study of a Spontaneous Metastatic Mammary Carcinoma Mouse Model by NanoString Technologies

PubMed Central

Saylor, Karen L.; Anver, Miriam R.; Salomon, David S.; Golubeva, Yelena G.

2016-01-01

Laser capture microdissection (LCM) of tissue is an established tool in medical research for collection of distinguished cell populations under direct microscopic visualization for molecular analysis. LCM samples have been successfully analyzed in a number of genomic and proteomic downstream molecular applications. However, LCM sample collection and preparation procedure has to be adapted to each downstream analysis platform. In this present manuscript we describe in detail the adaptation of LCM methodology for the collection and preparation of fresh frozen samples for NanoString analysis based on a study of a model of mouse mammary gland carcinoma and its lung metastasis. Our adaptation of LCM sample preparation and workflow to the requirements of the NanoString platform allowed acquiring samples with high RNA quality. The NanoString analysis of such samples provided sensitive detection of genes of interest and their associated molecular pathways. NanoString is a reliable gene expression analysis platform that can be effectively coupled with LCM. PMID:27077656

Molecular modeling studies of structural properties of polyvinyl alcohol: a comparative study using INTERFACE force field.

PubMed

Radosinski, Lukasz; Labus, Karolina

2017-10-05

Polyvinyl alcohol (PVA) is a material with a variety of applications in separation, biotechnology, and biomedicine. Using combined Monte Carlo and molecular dynamics techniques, we present an extensive comparative study of second- and third-generation force fields Universal, COMPASS, COMPASS II, PCFF, and the newly developed INTERFACE, as applied to this system. In particular, we show that an INTERFACE force field provides a possibility of composing a reliable atomistic model to reproduce density change of PVA matrix in a narrow temperature range (298-348 K) and calculate a thermal expansion coefficient with reasonable accuracy. Thus, the INTERFACE force field may be used to predict mechanical properties of the PVA system, being a scaffold for hydrogels, with much greater accuracy than latter approaches. Graphical abstract Molecular Dynamics and Monte Carlo studies indicate that it is possible to predict properties of the PVA in narrow temperature range by using the INTERFACE force field.

Semi-Empirical Validation of the Cross-Band Relative Absorption Technique for the Measurement of Molecular Mixing Ratios

NASA Technical Reports Server (NTRS)

Pliutau, Denis; Prasad, Narasimha S

2013-01-01

Studies were performed to carry out semi-empirical validation of a new measurement approach we propose for molecular mixing ratios determination. The approach is based on relative measurements in bands of O2 and other molecules and as such may be best described as cross band relative absorption (CoBRA). . The current validation studies rely upon well verified and established theoretical and experimental databases, satellite data assimilations and modeling codes such as HITRAN, line-by-line radiative transfer model (LBLRTM), and the modern-era retrospective analysis for research and applications (MERRA). The approach holds promise for atmospheric mixing ratio measurements of CO2 and a variety of other molecules currently under investigation for several future satellite lidar missions. One of the advantages of the method is a significant reduction of the temperature sensitivity uncertainties which is illustrated with application to the ASCENDS mission for the measurement of CO2 mixing ratios (XCO2). Additional advantages of the method include the possibility to closely match cross-band weighting function combinations which is harder to achieve using conventional differential absorption techniques and the potential for additional corrections for water vapor and other interferences without using the data from numerical weather prediction (NWP) models.

Structural Analysis Of CD59 Of Chinese Tree Shrew: A New Reference Molecule For Human Immune System Specific CD59 Drug Discovery.

PubMed

Panda, Subhamay; Kumari, Leena; Panda, Santamay

2017-11-17

Chinese tree shrews (Tupaia belangeri chinensis) bear several characteristics that are considered to be very crucial for utilizing in animal experimental models in biomedical research. Subsequent to the identification of key aspects and signaling pathways in nervous and immune systems, it is revealed that tree shrews acquires shared common as well as unique characteristics, and hence offers a genetic basis for employing this animal as a prospective model for biomedical research. CD59 glycoprotein, commonly referred to as MAC-inhibitory protein (MAC-IP), membrane inhibitor of reactive lysis (MIRL), or protectin, is encoded by the CD59 gene in human beings. It is the member of the LY6/uPAR/alpha-neurotoxin protein family. With this initial point the objective of this study was to determine a comparative composite based structure of CD59 of Chinese tree shrew. The additional objective of this study was to examine the distribution of negatively and positively charged amino acid over molecular modeled structure, distribution of secondary structural elements, hydrophobicity molecular surface analysis and electrostatic potential analysis with the assistance of several bioinformatical analytical tools. CD59 Amino acid sequence of Chinese tree shrew collected from the online database system of National Centre for Biotechnology Information. SignalP 4.0 online server was employed for detection of signal peptide instance within the protein sequence of CD59. Molecular model structure of CD59 protein was generated by the Iterative Threading ASSEmbly Refinement (I-TASSER) suite. The confirmation for three-dimensional structural model was evaluated by structure validation tools. Location of negatively and positively charged amino acid over molecular modeled structure, distribution of secondary structural elements, and hydrophobicity molecular surface analysis was performed with the help of Chimera tool. Electrostatic potential analysis was carried out with the adaptive Poisson-Boltzmann solver package. Subsequently validated model was used for the functionally critical amino acids and active site prediction. The functionally critical amino acids and ligand- binding site (LBS) of the proteins (modeled) was determined using the COACH program. Analysis of Ramachandran plot for Chinese tree shrew depicted that overall, 100% of the residues in homology model were observed in allowed and favored regions, sequentially leading to the validation of the standard of generated protein structural model. In case of CD59 of Chinese tree shrew, the total score of G-factor was found to be -0.66 that was generally larger than the acceptable value. This approach suggests the significance and acceptability of the modeled structure of CD59 of Chinese tree shrew. The molecular model data in cooperation to other relevant post model analysis data put forward molecular insight to protecting activity of CD59 protein molecule of Chinese tree shrew. In the present study, we have proposed the first molecular model structure of uncharted CD59 of Chinese tree shrew by significantly utilizing the comparative composite modeling approach. Therefore, the development of a structural model of the CD59 protein was carried out and analyzed further for deducing molecular enrichment technique. The collaborative effort of molecular model and other relevant data of post model analysis carry forward molecular understanding to protecting activity of CD59 functions towards better insight of features of this natural lead compound. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The atomic scale structure of CXV carbon: wide-angle x-ray scattering and modeling studies.

PubMed

Hawelek, L; Brodka, A; Dore, J C; Honkimaki, V; Burian, A

2013-11-13

The disordered structure of commercially available CXV activated carbon produced from finely powdered wood-based carbon has been studied using the wide-angle x-ray scattering technique, molecular dynamics and density functional theory simulations. The x-ray scattering data has been converted to the real space representation in the form of the pair correlation function via the Fourier transform. Geometry optimizations using classical molecular dynamics based on the reactive empirical bond order potential and density functional theory at the B3LYP/6-31g* level have been performed to generate nanoscale models of CXV carbon consistent with the experimental data. The final model of the structure comprises four chain-like and buckled graphitic layers containing a small percentage of four-fold coordinated atoms (sp(3) defects) in each layer. The presence of non-hexagonal rings in the atomic arrangement has been also considered.

GARN: Sampling RNA 3D Structure Space with Game Theory and Knowledge-Based Scoring Strategies.

PubMed

Boudard, Mélanie; Bernauer, Julie; Barth, Dominique; Cohen, Johanne; Denise, Alain

2015-01-01

Cellular processes involve large numbers of RNA molecules. The functions of these RNA molecules and their binding to molecular machines are highly dependent on their 3D structures. One of the key challenges in RNA structure prediction and modeling is predicting the spatial arrangement of the various structural elements of RNA. As RNA folding is generally hierarchical, methods involving coarse-grained models hold great promise for this purpose. We present here a novel coarse-grained method for sampling, based on game theory and knowledge-based potentials. This strategy, GARN (Game Algorithm for RNa sampling), is often much faster than previously described techniques and generates large sets of solutions closely resembling the native structure. GARN is thus a suitable starting point for the molecular modeling of large RNAs, particularly those with experimental constraints. GARN is available from: http://garn.lri.fr/.

Leveraging Modeling Approaches: Reaction Networks and Rules

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349

Leveraging modeling approaches: reaction networks and rules.

PubMed

Blinov, Michael L; Moraru, Ion I

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

Alignment-independent technique for 3D QSAR analysis

NASA Astrophysics Data System (ADS)

Wilkes, Jon G.; Stoyanova-Slavova, Iva B.; Buzatu, Dan A.

2016-04-01

Molecular biochemistry is controlled by 3D phenomena but structure-activity models based on 3D descriptors are infrequently used for large data sets because of the computational overhead for determining molecular conformations. A diverse dataset of 146 androgen receptor binders was used to investigate how different methods for defining molecular conformations affect the performance of 3D-quantitative spectral data activity relationship models. Molecular conformations tested: (1) global minimum of molecules' potential energy surface; (2) alignment-to-templates using equal electronic and steric force field contributions; (3) alignment using contributions "Best-for-Each" template; (4) non-energy optimized, non-aligned (2D > 3D). Aggregate predictions from models were compared. Highest average coefficients of determination ranged from R Test 2 = 0.56 to 0.61. The best model using 2D > 3D (imported directly from ChemSpider) produced R Test 2 = 0.61. It was superior to energy-minimized and conformation-aligned models and was achieved in only 3-7 % of the time required using the other conformation strategies. Predictions averaged from models built on different conformations achieved a consensus R Test 2 = 0.65. The best 2D > 3D model was analyzed for underlying structure-activity relationships. For the compound strongest binding to the androgen receptor, 10 substructural features contributing to binding were flagged. Utility of 2D > 3D was compared for two other activity endpoints, each modeling a medium sized data set. Results suggested that large scale, accurate predictions using 2D > 3D SDAR descriptors may be produced for interactions involving endocrine system nuclear receptors and other data sets in which strongest activities are produced by fairly inflexible substrates.

Combining configurational energies and forces for molecular force field optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vlcek, Lukas; Sun, Weiwei; Kent, Paul R. C.

While quantum chemical simulations have been increasingly used as an invaluable source of information for atomistic model development, the high computational expenses typically associated with these techniques often limit thorough sampling of the systems of interest. It is therefore of great practical importance to use all available information as efficiently as possible, and in a way that allows for consistent addition of constraints that may be provided by macroscopic experiments. We propose a simple approach that combines information from configurational energies and forces generated in a molecular dynamics simulation to increase the effective number of samples. Subsequently, this information ismore » used to optimize a molecular force field by minimizing the statistical distance similarity metric. We also illustrate the methodology on an example of a trajectory of configurations generated in equilibrium molecular dynamics simulations of argon and water and compare the results with those based on the force matching method.« less

Combining configurational energies and forces for molecular force field optimization

DOE PAGES

Vlcek, Lukas; Sun, Weiwei; Kent, Paul R. C.

2017-07-21

While quantum chemical simulations have been increasingly used as an invaluable source of information for atomistic model development, the high computational expenses typically associated with these techniques often limit thorough sampling of the systems of interest. It is therefore of great practical importance to use all available information as efficiently as possible, and in a way that allows for consistent addition of constraints that may be provided by macroscopic experiments. We propose a simple approach that combines information from configurational energies and forces generated in a molecular dynamics simulation to increase the effective number of samples. Subsequently, this information ismore » used to optimize a molecular force field by minimizing the statistical distance similarity metric. We also illustrate the methodology on an example of a trajectory of configurations generated in equilibrium molecular dynamics simulations of argon and water and compare the results with those based on the force matching method.« less

LAD Dissertation Prize Talk: Molecular Collisional Excitation in Astrophysical Environments

NASA Astrophysics Data System (ADS)

Walker, Kyle M.

2017-06-01

While molecular excitation calculations are vital in determining particle velocity distributions, internal state distributions, abundances, and ionization balance in gaseous environments, both theoretical calculations and experimental data for these processes are lacking. Reliable molecular collisional data with the most abundant species - H2, H, He, and electrons - are needed to probe material in astrophysical environments such as nebulae, molecular clouds, comets, and planetary atmospheres. However, excitation calculations with the main collider, H2, are computationally expensive and therefore various approximations are used to obtain unknown rate coefficients. The widely-accepted collider-mass scaling approach is flawed, and alternate scaling techniques based on physical and mathematical principles are presented here. The most up-to-date excitation data are used to model the chemical evolution of primordial species in the Recombination Era and produce accurate non-thermal spectra of the molecules H2+, HD, and H2 in a primordial cloud as it collapses into a first generation star.

Ab initio genotype–phenotype association reveals intrinsic modularity in genetic networks

PubMed Central

Slonim, Noam; Elemento, Olivier; Tavazoie, Saeed

2006-01-01

Microbial species express an astonishing diversity of phenotypic traits, behaviors, and metabolic capacities. However, our molecular understanding of these phenotypes is based almost entirely on studies in a handful of model organisms that together represent only a small fraction of this phenotypic diversity. Furthermore, many microbial species are not amenable to traditional laboratory analysis because of their exotic lifestyles and/or lack of suitable molecular genetic techniques. As an adjunct to experimental analysis, we have developed a computational information-theoretic framework that produces high-confidence gene–phenotype predictions using cross-species distributions of genes and phenotypes across 202 fully sequenced archaea and eubacteria. In addition to identifying the genetic basis of complex traits, our approach reveals the organization of these genes into generic preferentially co-inherited modules, many of which correspond directly to known enzymatic pathways, molecular complexes, signaling pathways, and molecular machines. PMID:16732191

deltaGseg: macrostate estimation via molecular dynamics simulations and multiscale time series analysis.

PubMed

Low, Diana H P; Motakis, Efthymios

2013-10-01

Binding free energy calculations obtained through molecular dynamics simulations reflect intermolecular interaction states through a series of independent snapshots. Typically, the free energies of multiple simulated series (each with slightly different starting conditions) need to be estimated. Previous approaches carry out this task by moving averages at certain decorrelation times, assuming that the system comes from a single conformation description of binding events. Here, we discuss a more general approach that uses statistical modeling, wavelets denoising and hierarchical clustering to estimate the significance of multiple statistically distinct subpopulations, reflecting potential macrostates of the system. We present the deltaGseg R package that performs macrostate estimation from multiple replicated series and allows molecular biologists/chemists to gain physical insight into the molecular details that are not easily accessible by experimental techniques. deltaGseg is a Bioconductor R package available at http://bioconductor.org/packages/release/bioc/html/deltaGseg.html.

Introducing basic molecular biology to Turkish rural and urban primary school children via hands-on PCR and gel electrophoresis activities.

PubMed

Selli, Cigdem; Yıldırım, Gokce; Kaymak, Aysegul; Karacicek, Bilge; Ogut, Deniz; Gungor, Turkan; Erem, Erdem; Ege, Mehmet; Bümen, Nilay; Tosun, Metiner

2014-01-01

This study includes the results of a 2-day education project titled "Molecular Biology Laboratory Summer School, MoBiLYO." The project was held at a University Research Center by scientists from Department of Pharmacology and graduate students. The project was composed of introductory lectures, model construction, DNA isolation, polymerase chain reaction (PCR), and gel electrophoresis. The participants were 13-year-old eighth-graders attending primary schools affiliated with Ministry of National Education in urban and rural areas of Izmir, Turkey. The purpose of this study was to introduce basic molecular biology concepts through individually performed experiments such as PCR and gel electrophoresis integrated with creative drama. The students were assessed at the beginning and the end of each project day via mini-tests, experimental and presentation skills evaluation forms. Data showed that students' knowledge about DNA structure and basic molecular biology techniques significantly increased. On the basis of experimental and presentational skills, there was no significant difference between kids from urban and rural schools or between public and boarding public schools, whereas the average score of girls was significantly higher than that of boys. In conclusion, individually performed experiments integrated with creative drama significantly increased students' perception of complex experimental procedures on basic molecular biology concepts. Data suggests that integration of these concepts into the science and technology curriculum of Turkish primary education may support the recruitment of future scientists who can handle rapidly developing genomic techniques that will affect our everyday life. © 2014 by The International Union of Biochemistry and Molecular Biology.

Combined 3D-QSAR and molecular docking study on 7,8-dialkyl-1,3-diaminopyrrolo-[3,2-f] Quinazoline series compounds to understand the binding mechanism of DHFR inhibitors

NASA Astrophysics Data System (ADS)

Aouidate, Adnane; Ghaleb, Adib; Ghamali, Mounir; Chtita, Samir; Choukrad, M'barek; Sbai, Abdelouahid; Bouachrine, Mohammed; Lakhlifi, Tahar

2017-07-01

A series of nineteen DHFR inhibitors was studied based on the combination of two computational techniques namely, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking. The comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were developed using 19 molecules having pIC50 ranging from 9.244 to 5.839. The best CoMFA and CoMSIA models show conventional determination coefficients R2 of 0.96 and 0.93 as well as the Leave One Out cross-validation determination coefficients Q2 of 0.64 and 0.72, respectively. The predictive ability of those models was evaluated by the external validation using a test set of five compounds with predicted determination coefficients R2test of 0.92 and 0.94, respectively. The binding mode between this kind of compounds and the DHFR enzyme in addition to the key amino acid residues were explored by molecular docking simulation. Contour maps and molecular docking identified that the R1 and R2 natures at the pyrazole moiety are the important features for the optimization of the binding affinity to the DHFR receptor. According to the good concordance between the CoMFA/CoMSIA contour maps and docking results, the obtained information was explored to design novel molecules.

QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells.

PubMed

Toropov, Andrey A; Toropova, Alla P; Puzyn, Tomasz; Benfenati, Emilio; Gini, Giuseppina; Leszczynska, Danuta; Leszczynski, Jerzy

2013-06-01

Quantitative structure-property/activity relationships (QSPRs/QSARs) are a tool to predict various endpoints for various substances. The "classic" QSPR/QSAR analysis is based on the representation of the molecular structure by the molecular graph. However, simplified molecular input-line entry system (SMILES) gradually becomes most popular representation of the molecular structure in the databases available on the Internet. Under such circumstances, the development of molecular descriptors calculated directly from SMILES becomes attractive alternative to "classic" descriptors. The CORAL software (http://www.insilico.eu/coral) is provider of SMILES-based optimal molecular descriptors which are aimed to correlate with various endpoints. We analyzed data set on nanoparticles uptake in PaCa2 pancreatic cancer cells. The data set includes 109 nanoparticles with the same core but different surface modifiers (small organic molecules). The concept of a QSAR as a random event is suggested in opposition to "classic" QSARs which are based on the only one distribution of available data into the training and the validation sets. In other words, five random splits into the "visible" training set and the "invisible" validation set were examined. The SMILES-based optimal descriptors (obtained by the Monte Carlo technique) for these splits are calculated with the CORAL software. The statistical quality of all these models is good. Copyright © 2013 Elsevier Ltd. All rights reserved.

Method for fabrication and verification of conjugated nanoparticle-antibody tuning elements for multiplexed electrochemical biosensors.

PubMed

La Belle, Jeffrey T; Fairchild, Aaron; Demirok, Ugur K; Verma, Aman

2013-05-15

There is a critical need for more accurate, highly sensitive and specific assay for disease diagnosis and management. A novel, multiplexed, single sensor using rapid and label free electrochemical impedance spectroscopy tuning method has been developed. The key challenges while monitoring multiple targets is frequency overlap. Here we describe the methods to circumvent the overlap, tune by use of nanoparticle (NP) and discuss the various fabrication and characterization methods to develop this technique. First sensors were fabricated using printed circuit board (PCB) technology and nickel and gold layers were electrodeposited onto the PCB sensors. An off-chip conjugation of gold NP's to molecular recognition elements (with verification technique) is described as well. A standard covalent immobilization of the molecular recognition elements is also discussed with quality control techniques. Finally use and verification of sensitivity and specificity is also presented. By use of gold NP's of various sizes, we have demonstrated the possibility and shown little loss of sensitivity and specificity in the molecular recognition of inflammatory markers as "model" targets for our tuning system. By selection of other sized NP's or NP's of various materials, the tuning effect can be further exploited. The novel platform technology developed could be utilized in critical care, clinical management and at home health and disease management. Copyright © 2013 Elsevier Inc. All rights reserved.

New Technique for Speciation of Uranium in Sediments Following Acetate-Stimulated Bioremediation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2011-06-22

Acetate-stimulated bioremediation is a promising new technique for sequestering toxic uranium contamination from groundwater. The speciation of uranium in sediments after such bioremediation attempts remains unknown as a result of low uranium concentration, and is important to analyzing the stability of sequestered uranium. A new technique was developed for investigating the oxidation state and local molecular structure of uranium from field site sediments using X-Ray Absorption Spectroscopy (XAS), and was implemented at the site of a former uranium mill in Rifle, CO. Glass columns filled with bioactive Rifle sediments were deployed in wells in the contaminated Rifle aquifer and amendedmore » with a hexavalent uranium (U(VI)) stock solution to increase uranium concentration while maintaining field conditions. This sediment was harvested and XAS was utilized to analyze the oxidation state and local molecular structure of the uranium in sediment samples. Extended X-Ray Absorption Fine Structure (EXAFS) data was collected and compared to known uranium spectra to determine the local molecular structure of the uranium in the sediment. Fitting was used to determine that the field site sediments did not contain uraninite (UO{sub 2}), indicating that models based on bioreduction using pure bacterial cultures are not accurate for bioremediation in the field. Stability tests on the monomeric tetravalent uranium (U(IV)) produced by bioremediation are needed in order to assess the efficacy of acetate-stimulation bioremediation.« less

Molecular gearing systems

DOE PAGES

Gakh, Andrei A.; Sachleben, Richard A.; Bryan, Jeff C.

1997-11-01

The race to create smaller devices is fueling much of the research in electronics. The competition has intensified with the advent of microelectromechanical systems (MEMS), in which miniaturization is already reaching the dimensional limits imposed by physics of current lithographic techniques. Also, in the realm of biochemistry, evidence is accumulating that certain enzyme complexes are capable of very sophisticated modes of motion. Complex synergistic biochemical complexes driven by sophisticated biomechanical processes are quite common. Their biochemical functions are based on the interplay of mechanical and chemical processes, including allosteric effects. In addition, the complexity of this interplay far exceeds thatmore » of typical chemical reactions. Understanding the behavior of artificial molecular devices as well as complex natural molecular biomechanical systems is difficult. Fortunately, the problem can be successfully resolved by direct molecular engineering of simple molecular systems that can mimic desired mechanical or electronic devices. These molecular systems are called technomimetics (the name is derived, by analogy, from biomimetics). Several classes of molecular systems that can mimic mechanical, electronic, or other features of macroscopic devices have been successfully synthesized by conventional chemical methods during the past two decades. In this article we discuss only one class of such model devices: molecular gearing systems.« less

Effect of PEO molecular weight on the miscibility and dynamics in epoxy/PEO blends.

PubMed

Lu, Shoudong; Zhang, Rongchun; Wang, Xiaoliang; Sun, Pingchuan; Lv, Weifeng; Liu, Qingjie; Jia, Ninghong

2015-11-01

In this work, the effect of poly(ethylene oxide) (PEO) molecular weight in blends of epoxy (ER) and PEO on the miscibility, inter-chain weak interactions and local dynamics were systematically investigated by multi-frequency temperature modulation DSC and solid-state NMR techniques. We found that the molecular weight (M(w)) of PEO was a crucial factor in controlling the miscibility, chain dynamics and hydrogen bonding interactions between PEO and ER. A critical PEO molecular weight (M(crit)) around 4.5k was found. PEO was well miscible with ER when the molecular weight was below M(crit), where the chain motion of PEO was restricted due to strong inter-chain hydrogen bonding interactions. However, for the blends with high molecular weight PEO (M(w) > M(crit)), the miscibility between PEO and ER was poor, and most of PEO chains were considerably mobile. Finally, polarization inversion spin exchange at magic angle (PISEMA) solid-state NMR experiment further revealed the different mobility of the PEO in ER/PEO blends with different molecular weight of PEO at molecular level. Based on the DSC and NMR results, a tentative model was proposed to illustrate the miscibility in ER/PEO blends.

A novel numerical model to predict the morphological behavior of magnetic liquid marbles using coarse grained molecular dynamics concepts

NASA Astrophysics Data System (ADS)

Polwaththe-Gallage, Hasitha-Nayanajith; Sauret, Emilie; Nguyen, Nam-Trung; Saha, Suvash C.; Gu, YuanTong

2018-01-01

Liquid marbles are liquid droplets coated with superhydrophobic powders whose morphology is governed by the gravitational and surface tension forces. Small liquid marbles take spherical shapes, while larger liquid marbles exhibit puddle shapes due to the dominance of gravitational forces. Liquid marbles coated with hydrophobic magnetic powders respond to an external magnetic field. This unique feature of magnetic liquid marbles is very attractive for digital microfluidics and drug delivery systems. Several experimental studies have reported the behavior of the liquid marbles. However, the complete behavior of liquid marbles under various environmental conditions is yet to be understood. Modeling techniques can be used to predict the properties and the behavior of the liquid marbles effectively and efficiently. A robust liquid marble model will inspire new experiments and provide new insights. This paper presents a novel numerical modeling technique to predict the morphology of magnetic liquid marbles based on coarse grained molecular dynamics concepts. The proposed model is employed to predict the changes in height of a magnetic liquid marble against its width and compared with the experimental data. The model predictions agree well with the experimental findings. Subsequently, the relationship between the morphology of a liquid marble with the properties of the liquid is investigated. Furthermore, the developed model is capable of simulating the reversible process of opening and closing of the magnetic liquid marble under the action of a magnetic force. The scaling analysis shows that the model predictions are consistent with the scaling laws. Finally, the proposed model is used to assess the compressibility of the liquid marbles. The proposed modeling approach has the potential to be a powerful tool to predict the behavior of magnetic liquid marbles serving as bioreactors.

Web-Based Computational Chemistry Education with CHARMMing II: Coarse-Grained Protein Folding

PubMed Central

Schalk, Vinushka; Lerner, Michael G.; Woodcock, H. Lee; Brooks, Bernard R.

2014-01-01

A lesson utilizing a coarse-grained (CG) G-like model has been implemented into the CHARMM INterface and Graphics (CHARMMing) web portal (www.charmming.org) to the Chemistry at HARvard Macromolecular Mechanics (CHARMM) molecular simulation package. While widely used to model various biophysical processes, such as protein folding and aggregation, CG models can also serve as an educational tool because they can provide qualitative descriptions of complex biophysical phenomena for a relatively cheap computational cost. As a proof of concept, this lesson demonstrates the construction of a CG model of a small globular protein, its simulation via Langevin dynamics, and the analysis of the resulting data. This lesson makes connections between modern molecular simulation techniques and topics commonly presented in an advanced undergraduate lecture on physical chemistry. It culminates in a straightforward analysis of a short dynamics trajectory of a small fast folding globular protein; we briefly describe the thermodynamic properties that can be calculated from this analysis. The assumptions inherent in the model and the data analysis are laid out in a clear, concise manner, and the techniques used are consistent with those employed by specialists in the field of CG modeling. One of the major tasks in building the G-like model is determining the relative strength of the nonbonded interactions between coarse-grained sites. New functionality has been added to CHARMMing to facilitate this process. The implementation of these features into CHARMMing helps automate many of the tedious aspects of constructing a CG G model. The CG model builder and its accompanying lesson should be a valuable tool to chemistry students, teachers, and modelers in the field. PMID:25058338

Web-based computational chemistry education with CHARMMing II: Coarse-grained protein folding.

PubMed

Pickard, Frank C; Miller, Benjamin T; Schalk, Vinushka; Lerner, Michael G; Woodcock, H Lee; Brooks, Bernard R

2014-07-01

A lesson utilizing a coarse-grained (CG) Gō-like model has been implemented into the CHARMM INterface and Graphics (CHARMMing) web portal (www.charmming.org) to the Chemistry at HARvard Macromolecular Mechanics (CHARMM) molecular simulation package. While widely used to model various biophysical processes, such as protein folding and aggregation, CG models can also serve as an educational tool because they can provide qualitative descriptions of complex biophysical phenomena for a relatively cheap computational cost. As a proof of concept, this lesson demonstrates the construction of a CG model of a small globular protein, its simulation via Langevin dynamics, and the analysis of the resulting data. This lesson makes connections between modern molecular simulation techniques and topics commonly presented in an advanced undergraduate lecture on physical chemistry. It culminates in a straightforward analysis of a short dynamics trajectory of a small fast folding globular protein; we briefly describe the thermodynamic properties that can be calculated from this analysis. The assumptions inherent in the model and the data analysis are laid out in a clear, concise manner, and the techniques used are consistent with those employed by specialists in the field of CG modeling. One of the major tasks in building the Gō-like model is determining the relative strength of the nonbonded interactions between coarse-grained sites. New functionality has been added to CHARMMing to facilitate this process. The implementation of these features into CHARMMing helps automate many of the tedious aspects of constructing a CG Gō model. The CG model builder and its accompanying lesson should be a valuable tool to chemistry students, teachers, and modelers in the field.

Proteomic Profiling of Skin Fibroblasts as a Model of Schizophrenia.

PubMed

Wang, Lan; Rahmoune, Hassan; Guest, Paul C

2017-01-01

Since many aspects of schizophrenia are also manifested at the peripheral level in proliferating cell types, this chapter describes the analysis of skin fibroblasts biopsied from living patients. The method focuses on cell culture and sample preparation for characterization of the model. The resulting cell extracts can be analysed by any number of proteomic techniques for identification of biomarker candidates. This approach could help to elucidate the molecular mechanisms associated with the pathophysiology of schizophrenia and provide a useful model for a new target and drug discovery.

Depth-resolved analytical model and correction algorithm for photothermal optical coherence tomography

PubMed Central

Lapierre-Landry, Maryse; Tucker-Schwartz, Jason M.; Skala, Melissa C.

2016-01-01

Photothermal OCT (PT-OCT) is an emerging molecular imaging technique that occupies a spatial imaging regime between microscopy and whole body imaging. PT-OCT would benefit from a theoretical model to optimize imaging parameters and test image processing algorithms. We propose the first analytical PT-OCT model to replicate an experimental A-scan in homogeneous and layered samples. We also propose the PT-CLEAN algorithm to reduce phase-accumulation and shadowing, two artifacts found in PT-OCT images, and demonstrate it on phantoms and in vivo mouse tumors. PMID:27446693

ASSESSMENT OF VENOUS THROMBOSIS IN ANIMAL MODELS

PubMed Central

SP, Grover; CE, Evans; AS, Patel; B, Modarai; P, Saha; A, Smith

2016-01-01

Deep vein thrombosis and common complications, including pulmonary embolism and post thrombotic syndrome, represent a major source of morbidity and mortality worldwide. Experimental models of venous thrombosis have provided considerable insight into the cellular and molecular mechanisms that regulate thrombus formation and subsequent resolution. Here we critically appraise the ex vivo and in vivo techniques used to assess venous thrombosis in these models. Particular attention is paid to imaging modalities, including magnetic resonance imaging, micro computed tomography and high frequency ultrasound that facilitate longitudinal assessment of thrombus size and composition. PMID:26681755

Assessment of Venous Thrombosis in Animal Models.

PubMed

Grover, Steven P; Evans, Colin E; Patel, Ashish S; Modarai, Bijan; Saha, Prakash; Smith, Alberto

2016-02-01

Deep vein thrombosis and common complications, including pulmonary embolism and post-thrombotic syndrome, represent a major source of morbidity and mortality worldwide. Experimental models of venous thrombosis have provided considerable insight into the cellular and molecular mechanisms that regulate thrombus formation and subsequent resolution. Here, we critically appraise the ex vivo and in vivo techniques used to assess venous thrombosis in these models. Particular attention is paid to imaging modalities, including magnetic resonance imaging, micro-computed tomography, and high-frequency ultrasound that facilitate longitudinal assessment of thrombus size and composition. © 2015 American Heart Association, Inc.

Nowcasting recreational water quality

USGS Publications Warehouse

Boehm, Alexandria B.; Whitman, Richard L.; Nevers, Meredith; Hou, Deyi; Weisberg, Stephen B.

2007-01-01

Advances in molecular techniques may soon provide new opportunities to provide more timely information on whether recreational beaches are free from fecal contamination. However, an alternative approach is the use of predictive models. This chapter presents a summary of these developing efforts. First, we describe documented physical, chemical, and biological factors that have been demonstrated by researchers to affect bacterial concentrations at beaches and thus represent logical parameters for inclusion in a model. Then, we illustrate how various types of models can be applied to predict water quality at freshwater and marine beaches.

Theoretical and Experimental Study of Inclusion Complexes of β-Cyclodextrins with Chalcone and 2',4'-Dihydroxychalcone.

PubMed

Sancho, Matias I; Andujar, Sebastian; Porasso, Rodolfo D; Enriz, Ricardo D

2016-03-31

The inclusion complexes formed by chalcone and 2',4'-dihydroxychalcone with β-cyclodextrin have been studied combining experimental (phase solubility diagrams, Fourier transform infrared spectroscopy) and molecular modeling (molecular dynamics, quantum mechanics/molecular mechanics calculations) techniques. The formation constants of the complexes were determined at different temperatures, and the thermodynamic parameters of the process were obtained. The inclusion of chalcone in β-cyclodextrin is an exothermic process, while the inclusion of 2',4'-dihydroxychalcone is endothermic. Free energy profiles, derived from umbrella sampling using molecular dynamics simulations, were constructed to analyze the binding affinity and the complexation reaction at a molecular level. Hybrid QM/MM calculations were also employed to obtain a better description of the energetic and structural aspects of the complexes. The intermolecular interactions that stabilize both inclusion complexes were characterized by means of quantum atoms in molecules theory and reduce density gradient method. The calculated interactions were experimentally observed using FTIR.

Solution NMR structure of a designed metalloprotein and complementary molecular dynamics refinement.

PubMed

Calhoun, Jennifer R; Liu, Weixia; Spiegel, Katrin; Dal Peraro, Matteo; Klein, Michael L; Valentine, Kathleen G; Wand, A Joshua; DeGrado, William F

2008-02-01

We report the solution NMR structure of a designed dimetal-binding protein, di-Zn(II) DFsc, along with a secondary refinement step employing molecular dynamics techniques. Calculation of the initial NMR structural ensemble by standard methods led to distortions in the metal-ligand geometries at the active site. Unrestrained molecular dynamics using a nonbonded force field for the metal shell, followed by quantum mechanical/molecular mechanical dynamics of DFsc, were used to relax local frustrations at the dimetal site that were apparent in the initial NMR structure and provide a more realistic description of the structure. The MD model is consistent with NMR restraints, and in good agreement with the structural and functional properties expected for DF proteins. This work demonstrates that NMR structures of metalloproteins can be further refined using classical and first-principles molecular dynamics methods in the presence of explicit solvent to provide otherwise unavailable insight into the geometry of the metal center.

Recent progress and future directions in protein-protein docking.

PubMed

Ritchie, David W

2008-02-01

This article gives an overview of recent progress in protein-protein docking and it identifies several directions for future research. Recent results from the CAPRI blind docking experiments show that docking algorithms are steadily improving in both reliability and accuracy. Current docking algorithms employ a range of efficient search and scoring strategies, including e.g. fast Fourier transform correlations, geometric hashing, and Monte Carlo techniques. These approaches can often produce a relatively small list of up to a few thousand orientations, amongst which a near-native binding mode is often observed. However, despite the use of improved scoring functions which typically include models of desolvation, hydrophobicity, and electrostatics, current algorithms still have difficulty in identifying the correct solution from the list of false positives, or decoys. Nonetheless, significant progress is being made through better use of bioinformatics, biochemical, and biophysical information such as e.g. sequence conservation analysis, protein interaction databases, alanine scanning, and NMR residual dipolar coupling restraints to help identify key binding residues. Promising new approaches to incorporate models of protein flexibility during docking are being developed, including the use of molecular dynamics snapshots, rotameric and off-rotamer searches, internal coordinate mechanics, and principal component analysis based techniques. Some investigators now use explicit solvent models in their docking protocols. Many of these approaches can be computationally intensive, although new silicon chip technologies such as programmable graphics processor units are beginning to offer competitive alternatives to conventional high performance computer systems. As cryo-EM techniques improve apace, docking NMR and X-ray protein structures into low resolution EM density maps is helping to bridge the resolution gap between these complementary techniques. The use of symmetry and fragment assembly constraints are also helping to make possible docking-based predictions of large multimeric protein complexes. In the near future, the closer integration of docking algorithms with protein interface prediction software, structural databases, and sequence analysis techniques should help produce better predictions of protein interaction networks and more accurate structural models of the fundamental molecular interactions within the cell.

Microscopic aspects of the effect of friction reducers at the lubrication limit. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Mansot, J. L.

1984-01-01

An attempt is made to analytically model the physicochemical properties of lubricants and their capacity to reduce friction. A technique of frozen fracturing of the lubricants was employed to study the dispersion of additives throughout a lubricant. Adsorption was observed at the liquid-solid interface, which was the region where the solid and lubricant met, and the molecular dispersion of the additive enhanced the effectiveness of the lubricant. The electrically conductive characteristics of the lubricant at the friction interface indicated the presence of tunneling effects. The Bethe model was used to examine the relationship between the coefficient of friction and the variation of interface thickness. The electron transport permitted an inelastic tunnel electron spectroscopic investigation of the molecular transformations undergone by the additive during friction episodes.

Structure of N-(5-ethyl-[1,3,4]-thiadiazole-2-yl)toluenesulfonamide by combined X-ray powder diffraction, 13C solid-state NMR and molecular modelling.

PubMed

Hangan, Adriana; Borodi, Gheorghe; Filip, Xenia; Tripon, Carmen; Morari, Cristian; Oprean, Luminita; Filip, Claudiu

2010-12-01

The crystal structure solution of the title compound is determined from microcrystalline powder using a multi-technique approach that combines X-ray powder diffraction (XRPD) data analysis based on direct-space methods with information from (13)C solid-state NMR (SSNMR), and molecular modelling using the GIPAW (gauge including projector augmented-wave) method. The space group is Pbca with one molecule in the asymmetric unit. The proposed methodology proves very useful for unambiguously characterizing the supramolecular arrangement adopted by the N-(5-ethyl-[1,3,4]-thiadiazole-2-yl)toluenesulfonamide molecules in the crystal, which consists of extended double strands held together by C-H···π non-covalent interactions.

Scientific Communication and the Unified Laboratory Sequence1

NASA Astrophysics Data System (ADS)

Silverstein, Todd P.; Hudak, Norman J.; Chapple, Frances H.; Goodney, David E.; Brink, Christina P.; Whitehead, Joyce P.

1997-02-01

The "Temperature Dependent Relaxation Kinetics" lab was first implemented in 1987; it uses stopped-flow pH jump techniques to determine rate constants and activation parameters (H, S, G) for a reaction mechanism. Two new experiments (Monoamine Oxidase, and Molecular Modeling) will be implemented in the fall of 1997. The "Monoamine Oxidase" project uses chromatography and spectrophotometry to purify and characterize the enzyme. Subsequent photometric assays explore the enzyme's substrate specificity, activation energy, and denaturation. Finally, in the "Molecular Modeling"project, students characterize enzyme - substrate and drug - receptor interactions. Energy minimization protocols are used to make predictions about protein structure and ligand binding, and to explore pharmacological and biomedical implications. With these additions, the twelve Unified Laboratory projects introduce our chemistry majors to nearly all of the instrumental methods commonly encountered in modern chemistry.

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids.

PubMed

Dahlberg, Jerry; Tkacik, Peter T; Mullany, Brigid; Fleischhauer, Eric; Shahinian, Hossein; Azimi, Farzad; Navare, Jayesh; Owen, Spencer; Bisel, Tucker; Martin, Tony; Sholar, Jodie; Keanini, Russell G

2017-12-04

An analog, macroscopic method for studying molecular-scale hydrodynamic processes in dense gases and liquids is described. The technique applies a standard fluid dynamic diagnostic, particle image velocimetry (PIV), to measure: i) velocities of individual particles (grains), extant on short, grain-collision time-scales, ii) velocities of systems of particles, on both short collision-time- and long, continuum-flow-time-scales, iii) collective hydrodynamic modes known to exist in dense molecular fluids, and iv) short- and long-time-scale velocity autocorrelation functions, central to understanding particle-scale dynamics in strongly interacting, dense fluid systems. The basic system is composed of an imaging system, light source, vibrational sensors, vibrational system with a known media, and PIV and analysis software. Required experimental measurements and an outline of the theoretical tools needed when using the analog technique to study molecular-scale hydrodynamic processes are highlighted. The proposed technique provides a relatively straightforward alternative to photonic and neutron beam scattering methods traditionally used in molecular hydrodynamic studies.

An Update on in Vivo Imaging of Extracellular Vesicles as Drug Delivery Vehicles

PubMed Central

Gangadaran, Prakash; Hong, Chae Moon; Ahn, Byeong-Cheol

2018-01-01

Extracellular vesicles (EVs) are currently being considered as promising drug delivery vehicles. EVs are naturally occurring vesicles that exhibit many characteristics favorable to serve as drug delivery vehicles. In addition, EVs have inherent properties for treatment of cancers and other diseases. For research and clinical translation of use of EVs as drug delivery vehicles, in vivo tracking of EVs is essential. The latest molecular imaging techniques enable the tracking of EVs in living animals. However, each molecular imaging technique has its certain advantages and limitations for the in vivo imaging of EVs; therefore, understanding the molecular imaging techniques is essential to select the most appropriate imaging technology to achieve the desired imaging goal. In this review, we summarize the characteristics of EVs as drug delivery vehicles and the molecular imaging techniques used in visualizing and monitoring EVs in in vivo environments. Furthermore, we provide a perceptual vision of EVs as drug delivery vehicles and in vivo monitoring of EVs using molecular imaging technologies. PMID:29541030

Accurate Solution of Multi-Region Continuum Biomolecule Electrostatic Problems Using the Linearized Poisson-Boltzmann Equation with Curved Boundary Elements

PubMed Central

Altman, Michael D.; Bardhan, Jaydeep P.; White, Jacob K.; Tidor, Bruce

2009-01-01

We present a boundary-element method (BEM) implementation for accurately solving problems in biomolecular electrostatics using the linearized Poisson–Boltzmann equation. Motivating this implementation is the desire to create a solver capable of precisely describing the geometries and topologies prevalent in continuum models of biological molecules. This implementation is enabled by the synthesis of four technologies developed or implemented specifically for this work. First, molecular and accessible surfaces used to describe dielectric and ion-exclusion boundaries were discretized with curved boundary elements that faithfully reproduce molecular geometries. Second, we avoided explicitly forming the dense BEM matrices and instead solved the linear systems with a preconditioned iterative method (GMRES), using a matrix compression algorithm (FFTSVD) to accelerate matrix-vector multiplication. Third, robust numerical integration methods were employed to accurately evaluate singular and near-singular integrals over the curved boundary elements. Finally, we present a general boundary-integral approach capable of modeling an arbitrary number of embedded homogeneous dielectric regions with differing dielectric constants, possible salt treatment, and point charges. A comparison of the presented BEM implementation and standard finite-difference techniques demonstrates that for certain classes of electrostatic calculations, such as determining absolute electrostatic solvation and rigid-binding free energies, the improved convergence properties of the BEM approach can have a significant impact on computed energetics. We also demonstrate that the improved accuracy offered by the curved-element BEM is important when more sophisticated techniques, such as non-rigid-binding models, are used to compute the relative electrostatic effects of molecular modifications. In addition, we show that electrostatic calculations requiring multiple solves using the same molecular geometry, such as charge optimization or component analysis, can be computed to high accuracy using the presented BEM approach, in compute times comparable to traditional finite-difference methods. PMID:18567005

In silico platform for xenobiotics ADME-T pharmacological properties modeling and prediction. Part II: The body in a Hilbertian space.

PubMed

Jacob, Alexandre; Pratuangdejkul, Jaturong; Buffet, Sébastien; Launay, Jean-Marie; Manivet, Philippe

2009-04-01

We have broken old surviving dogmas and concepts used in computational chemistry and created an efficient in silico ADME-T pharmacological properties modeling and prediction toolbox for any xenobiotic. With the help of an innovative and pragmatic approach combining various in silico techniques, like molecular modeling, quantum chemistry and in-house developed algorithms, the interactions between drugs and those enzymes, transporters and receptors involved in their biotransformation can be studied. ADME-T pharmacological parameters can then be predicted after in vitro and in vivo validations of in silico models.

Bayesian molecular design with a chemical language model

NASA Astrophysics Data System (ADS)

Ikebata, Hisaki; Hongo, Kenta; Isomura, Tetsu; Maezono, Ryo; Yoshida, Ryo

2017-04-01

The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techniques. The method involves two different types of prediction; the forward and backward predictions. The objective of the forward prediction is to create a set of machine learning models on various properties of a given molecule. Inverting the trained forward models through Bayes' law, we derive a posterior distribution for the backward prediction, which is conditioned by a desired property requirement. Exploring high-probability regions of the posterior with a sequential Monte Carlo technique, molecules that exhibit the desired properties can computationally be created. One major difficulty in the computational creation of molecules is the exclusion of the occurrence of chemically unfavorable structures. To circumvent this issue, we derive a chemical language model that acquires commonly occurring patterns of chemical fragments through natural language processing of ASCII strings of existing compounds, which follow the SMILES chemical language notation. In the backward prediction, the trained language model is used to refine chemical strings such that the properties of the resulting structures fall within the desired property region while chemically unfavorable structures are successfully removed. The present method is demonstrated through the design of small organic molecules with the property requirements on HOMO-LUMO gap and internal energy. The R package iqspr is available at the CRAN repository.

Bayesian molecular design with a chemical language model.

PubMed

Ikebata, Hisaki; Hongo, Kenta; Isomura, Tetsu; Maezono, Ryo; Yoshida, Ryo

2017-04-01

The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techniques. The method involves two different types of prediction; the forward and backward predictions. The objective of the forward prediction is to create a set of machine learning models on various properties of a given molecule. Inverting the trained forward models through Bayes' law, we derive a posterior distribution for the backward prediction, which is conditioned by a desired property requirement. Exploring high-probability regions of the posterior with a sequential Monte Carlo technique, molecules that exhibit the desired properties can computationally be created. One major difficulty in the computational creation of molecules is the exclusion of the occurrence of chemically unfavorable structures. To circumvent this issue, we derive a chemical language model that acquires commonly occurring patterns of chemical fragments through natural language processing of ASCII strings of existing compounds, which follow the SMILES chemical language notation. In the backward prediction, the trained language model is used to refine chemical strings such that the properties of the resulting structures fall within the desired property region while chemically unfavorable structures are successfully removed. The present method is demonstrated through the design of small organic molecules with the property requirements on HOMO-LUMO gap and internal energy. The R package iqspr is available at the CRAN repository.

Molecular biology of myopia.

PubMed

Schaeffel, Frank; Simon, Perikles; Feldkaemper, Marita; Ohngemach, Sibylle; Williams, Robert W

2003-09-01

Experiments in animal models of myopia have emphasised the importance of visual input in emmetropisation but it is also evident that the development of human myopia is influenced to some degree by genetic factors. Molecular genetic approaches can help to identify both the genes involved in the control of ocular development and the potential targets for pharmacological intervention. This review covers a variety of techniques that are being used to study the molecular biology of myopia. In the first part, we describe techniques used to analyse visually induced changes in gene expression: Northern Blot, polymerase chain reaction (PCR) and real-time PCR to obtain semi-quantitative and quantitative measures of changes in transcription level of a known gene, differential display reverse transcription PCR (DD-RT-PCR) to search for new genes that are controlled by visual input, rapid amplification of 5' cDNA (5'-RACE) to extend the 5' end of sequences that are regulated by visual input, in situ hybridisation to localise the expression of a given gene in a tissue and oligonucleotide microarray assays to simultaneously test visually induced changes in thousands of transcripts in single experiments. In the second part, we describe techniques that are used to localise regions in the genome that contain genes that are involved in the control of eye growth and refractive errors in mice and humans. These include quantitative trait loci (QTL) mapping, exploiting experimental test crosses of mice and transmission disequilibrium tests (TDT) in humans to find chromosomal intervals that harbour genes involved in myopia development. We review several successful applications of this battery of techniques in myopia research.

Tumour and normal tissue radiobiology in mouse models: how close are mice to mini-humans?

PubMed

Koontz, Bridget F; Verhaegen, Frank; De Ruysscher, Dirk

2017-01-01

Animal modelling is essential to the study of radiobiology and the advancement of clinical radiation oncology by providing preclinical data. Mouse models in particular have been highly utilized in the study of both tumour and normal tissue radiobiology because of their cost effectiveness and versatility. Technology has significantly advanced in preclinical radiation techniques to allow highly conformal image-guided irradiation of small animals in an effort to mimic human treatment capabilities. However, the biological and physical limitations of animal modelling should be recognized and considered when interpreting preclinical radiotherapy (RT) studies. Murine tumour and normal tissue radioresponse has been shown to vary from human cellular and molecular pathways. Small animal irradiation techniques utilize different anatomical boundaries and may have different physical properties than human RT. This review addresses the difference between the human condition and mouse models and discusses possible strategies for future refinement of murine models of cancer and radiation for the benefit of both basic radiobiology and clinical translation.

Tumour and normal tissue radiobiology in mouse models: how close are mice to mini-humans?

PubMed Central

Verhaegen, Frank; De Ruysscher, Dirk

2017-01-01

Animal modelling is essential to the study of radiobiology and the advancement of clinical radiation oncology by providing preclinical data. Mouse models in particular have been highly utilized in the study of both tumour and normal tissue radiobiology because of their cost effectiveness and versatility. Technology has significantly advanced in preclinical radiation techniques to allow highly conformal image-guided irradiation of small animals in an effort to mimic human treatment capabilities. However, the biological and physical limitations of animal modelling should be recognized and considered when interpreting preclinical radiotherapy (RT) studies. Murine tumour and normal tissue radioresponse has been shown to vary from human cellular and molecular pathways. Small animal irradiation techniques utilize different anatomical boundaries and may have different physical properties than human RT. This review addresses the difference between the human condition and mouse models and discusses possible strategies for future refinement of murine models of cancer and radiation for the benefit of both basic radiobiology and clinical translation. PMID:27612010

High-resolution and high sensitivity mesoscopic fluorescence tomography based on de-scanning EMCCD: System design and thick tissue imaging applications

NASA Astrophysics Data System (ADS)

Ozturk, Mehmet Saadeddin

Optical microscopy has been one of the essential tools for biological studies for decades, however, its application areas was limited to superficial investigation due to strong scattering in live tissues. Even though advanced techniques such as confocal or multiphoton methods have been recently developed to penetrate beyond a few hundreds of microns deep in tissues, they still cannot perform in the mesoscopic regime (millimeter scale) without using destructive sample preparation protocols such as clearing techniques. They provide rich cellular information; however, they cannot be readily employed to investigate the biological processes at larger scales. Herein, we will present our effort to establish a novel imaging approach that can quantify molecular expression in intact tissues, well beyond the current microscopy depth limits. Mesoscopic Fluorescence Molecular Tomography (MFMT) is an emerging imaging modality that offers unique potential for the non-invasive molecular assessment of thick in-vitro and in-vivo live tissues. This novel imaging modality is based on an optical inverse problem that allows for retrieval of the quantitative spatial distribution of fluorescent tagged bio-markers at millimeter depth. MFMT is well-suited for in-vivo subsurface tissue imaging and thick bio-printed specimens due to its high sensitivity and fast acquisition times, as well as relatively large fields of view. Herein, we will first demonstrate the potential of this technique using our first generation MFMT system applied to multiplexed reporter gene imaging (in-vitro) and determination of Photodynamic Therapy (PDT) agent bio-distribution in a mouse model (in-vivo). Second, we will present the design rationale, in silico benchmarking, and experimental validation of a second generation MFMT (2GMFMT) system. We will demonstrate the gain in resolution and sensitivity achieved due to the de-scanned dense detector configuration implemented. The potential of this novel platform will be showcased by applying it to the longitudinal assessment of Ink-Jet Bio-Printed tumor models. This preliminary investigation focuses on monitoring four patient-derived glioblastoma multiforme (GBM) spheroids within their bioreactor for up to 70 days and following their volume change prior to and after exposure to a cytotoxic drug. Overall, our studies indicate that 2GMFMT is a powerful technique for in-vitro and in-vivo thick tissue molecular imaging applications due to its high resolution, fast tomographic imaging capability, and high sensitivity.

Cloning Yeast Actin cDNA Leads to an Investigative Approach for the Molecular Biology Laboratory

ERIC Educational Resources Information Center

Black, Michael W.; Tuan, Alice; Jonasson, Erin

2008-01-01

The emergence of molecular tools in multiple disciplines has elevated the importance of undergraduate laboratory courses that train students in molecular biology techniques. Although it would also be desirable to provide students with opportunities to apply these techniques in an investigative manner, this is generally not possible in the…

Self assembled monolayers on silicon for molecular electronics.

PubMed

Aswal, D K; Lenfant, S; Guerin, D; Yakhmi, J V; Vuillaume, D

2006-05-24

We present an overview of various aspects of the self-assembly of organic monolayers on silicon substrates for molecular electronics applications. Different chemical strategies employed for grafting the self-assembled monolayers (SAMs) of alkanes having different chain lengths on native oxide of Si or on bare Si have been reviewed. The utility of different characterization techniques in determination of the thickness, molecular ordering and orientation, surface coverage, growth kinetics and chemical composition of the SAMs has been discussed by choosing appropriate examples. The metal counterelectrodes are an integral part of SAMs for measuring their electrical properties as well as using them for molecular electronic devices. A brief discussion on the variety of options available for the deposition of metal counterelectrodes, that is, soft metal contacts, vapor deposition and soft lithography, has been presented. Various theoretical models, namely, tunneling (direct and Fowler-Nordheim), thermionic emission, Poole-Frenkel emission and hopping conduction, used for explaining the electronic transport in dielectric SAMs have been outlined and, some experimental data on alkane SAMs have been analyzed using these models. It has been found that short alkyl chains show excellent agreement with tunneling models; while more experimental data on long alkyl chains are required to understand their transport mechanism(s). Finally, the concepts and realization of various molecular electronic components, that is, diodes, resonant tunnel diodes, memories and transistors, based on appropriate architecture of SAMs comprising of alkyl chains (sigma- molecule) and conjugated molecules (pi-molecule) have been presented.

Machine learning in computational docking.

PubMed

Khamis, Mohamed A; Gomaa, Walid; Ahmed, Walaa F

2015-03-01

The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has gained much popularity and interest over the last few years. Central to this methodology is the notion of computational docking which is the process of predicting the best pose (orientation + conformation) of a small molecule (drug candidate) when bound to a target larger receptor molecule (protein) in order to form a stable complex molecule. In computational docking, a large number of binding poses are evaluated and ranked using a scoring function. The scoring function is a mathematical predictive model that produces a score that represents the binding free energy, and hence the stability, of the resulting complex molecule. Generally, such a function should produce a set of plausible ligands ranked according to their binding stability along with their binding poses. In more practical terms, an effective scoring function should produce promising drug candidates which can then be synthesized and physically screened using high throughput screening process. Therefore, the key to computer-aided drug design is the design of an efficient highly accurate scoring function (using ML techniques). The methods presented in this paper are specifically based on ML techniques. Despite many traditional techniques have been proposed, the performance was generally poor. Only in the last few years started the application of the ML technology in the design of scoring functions; and the results have been very promising. The ML-based techniques are based on various molecular features extracted from the abundance of protein-ligand information in the public molecular databases, e.g., protein data bank bind (PDBbind). In this paper, we present this paradigm shift elaborating on the main constituent elements of the ML approach to molecular docking along with the state-of-the-art research in this area. For instance, the best random forest (RF)-based scoring function on PDBbind v2007 achieves a Pearson correlation coefficient between the predicted and experimentally determined binding affinities of 0.803 while the best conventional scoring function achieves 0.644. The best RF-based ranking power ranks the ligands correctly based on their experimentally determined binding affinities with accuracy 62.5% and identifies the top binding ligand with accuracy 78.1%. We conclude with open questions and potential future research directions that can be pursued in smart computational docking; using molecular features of different nature (geometrical, energy terms, pharmacophore), advanced ML techniques (e.g., deep learning), combining more than one ML models. Copyright © 2015 Elsevier B.V. All rights reserved.

Lidar Measurements of Tropospheric Wind Profiles with the Double Edge Technique

NASA Technical Reports Server (NTRS)

Gentry, Bruce M.; Li, Steven X.; Korb, C. Laurence; Mathur, Savyasachee; Chen, Huailin

1998-01-01

Research has established the importance of global tropospheric wind measurements for large scale improvements in numerical weather prediction. In addition, global wind measurements provide data that are fundamental to the understanding and prediction of global climate change. These tasks are closely linked with the goals of the NASA Earth Science Enterprise and Global Climate Change programs. NASA Goddard has been actively involved in the development of direct detection Doppler lidar methods and technologies to meet the wind observing needs of the atmospheric science community. A variety of direct detection Doppler wind lidar measurements have recently been reported indicating the growing interest in this area. Our program at Goddard has concentrated on the development of the edge technique for lidar wind measurements. Implementations of the edge technique using either the aerosol or molecular backscatter for the Doppler wind measurement have been described. The basic principles have been verified in lab and atmospheric lidar wind experiments. The lidar measurements were obtained with an aerosol edge technique lidar operating at 1064 nm. These measurements demonstrated high spatial resolution (22 m) and high velocity sensitivity (rms variances of 0.1 m/s) in the planetary boundary layer (PBL). The aerosol backscatter is typically high in the PBL and the effects of the molecular backscatter can often be neglected. However, as was discussed in the original edge technique paper, the molecular contribution to the signal is significant above the boundary layer and a correction for the effects of molecular backscatter is required to make wind measurements. In addition, the molecular signal is a dominant source of noise in regions where the molecular to aerosol ratio is large since the energy monitor channel used in the single edge technique measures the sum of the aerosol and molecular signals. To extend the operation of the edge technique into the free troposphere we have developed a variation of the edge technique called the double edge technique. In this paper a ground based aerosol double edge lidar is described and the first measurements of wind profiles in the free troposphere obtained with this lidar will be presented.

Atomic and molecular hydrogen gas temperatures in a low-pressure helicon plasma

NASA Astrophysics Data System (ADS)

Samuell, Cameron M.; Corr, Cormac S.

2015-08-01

Neutral gas temperatures in hydrogen plasmas are important for experimental and modelling efforts in fusion technology, plasma processing, and surface modification applications. To provide values relevant to these application areas, neutral gas temperatures were measured in a low pressure (< 10 mTorr) radiofrequency helicon discharge using spectroscopic techniques. The atomic and molecular species were not found to be in thermal equilibrium with the atomic temperature being mostly larger then the molecular temperature. In low power operation (< 1 kW), the molecular hydrogen temperature was observed to be linearly proportional to the pressure while the atomic hydrogen temperature was inversely proportional. Both temperatures were observed to rise linearly with input power. For high power operation (5-20 kW), the molecular temperature was found to rise with both power and pressure up to a maximum of approximately 1200 K. Spatially resolved measurements near a graphite target demonstrated localised cooling near the sample surface. The temporal evolution of the molecular gas temperature during a high power 1.1 ms plasma pulse was also investigated and found to vary considerably as a function of pressure.

In silico quantitative structure-toxicity relationship study of aromatic nitro compounds.

PubMed

Pasha, Farhan Ahmad; Neaz, Mohammad Morshed; Cho, Seung Joo; Ansari, Mohiuddin; Mishra, Sunil Kumar; Tiwari, Sharvan

2009-05-01

Small molecules often have toxicities that are a function of molecular structural features. Minor variations in structural features can make large difference in such toxicity. Consequently, in silico techniques may be used to correlate such molecular toxicities with their structural features. Relative to nine different sets of aromatic nitro compounds having known observed toxicities against different targets, we developed ligand-based 2D quantitative structure-toxicity relationship models using 20 selected topological descriptors. The topological descriptors have several advantages such as conformational independency, facile and less time-consuming computation to yield good results. Multiple linear regression analysis was used to correlate variations of toxicity with molecular properties. The information index on molecular size, lopping centric index and Kier flexibility index were identified as fundamental descriptors for different kinds of toxicity, and further showed that molecular size, branching and molecular flexibility might be particularly important factors in quantitative structure-toxicity relationship analysis. This study revealed that topological descriptor-guided quantitative structure-toxicity relationship provided a very useful, cost and time-efficient, in silico tool for describing small-molecule toxicities.

Molecular profiling--a tool for addressing emerging gaps in the comparative risk assessment of GMOs.

PubMed

Heinemann, Jack A; Kurenbach, Brigitta; Quist, David

2011-10-01

Assessing the risks of genetically modified organisms (GMOs) is required by both international agreement and domestic legislation. Many view the use of the "omics" tools for profiling classes of molecules as useful in risk assessment, but no consensus has formed on the need or value of these techniques for assessing the risks of all GMOs. In this and many other cases, experts support case-by-case use of molecular profiling techniques for risk assessment. We review the latest research on the applicability and usefulness of molecular profiling techniques for GMO risk assessment. As more and more kinds of GMOs and traits are developed, broader use of molecular profiling in a risk assessment may be required to supplement the comparative approach to risk assessment. The literature-based discussions on the use of profiling appear to have settled on two findings: 1. profiling techniques are reliable and relevant, at least no less so than other techniques used in risk assessment; and 2. although not required routinely, regulators should be aware of when they are needed. The dismissal of routine molecular profiling may be confusing to regulators who then lack guidance on when molecular profiling might be worthwhile. Molecular profiling is an important way to increase confidence in risk assessments if the profiles are properly designed to address relevant risks and are applied at the correct stage of the assessment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Molecular Modeling on the PC (by Matthew F. Schlecht)

NASA Astrophysics Data System (ADS)

Rioux, Reviewed Frank

2000-06-01

"Computeraided molecular modeling doesn't exist for its own sake, but to contribute to scientific endeavor, and enable the scientist to work smarter." This is the last sentence of Schlecht's preface and it says something very important about contemporary scientific research in the academic and industrial venues. Owing to the accelerating improvement in computer technology (hardware and software) and its widespread availability, molecular modeling has become a reliable and important tool in chemical research. Consequently, experimentalists have incorporated molecular modeling techniques in their research, and partnerships with computational chemists have become common. This is a wellorganized and thorough monograph that devotes its attention to one type of molecular modeling, molecular mechanics, and one molecular modeling software package, PCMODEL. Schlecht targets two reader-user groups, the novice and the journeyman modeler, and articulates three goals. He wants to provide the novice with an introduction to molecular mechanics, and after that with some practical examples of the use of empirical force field calculations. His third goal is to provide the journeyman modeler with a reference work that will aid "further study and practice". These are potentially conflicting goals, but Schlecht is, in my opinion, successful because of the way his book is organized. A comprehensive treatment such as this one is not meant to be read from cover to cover, because it is both an exposition of basic principles and a user's manual. Therefore, the novice and the experienced modeler will undoubtedly use this book in different ways. For example, a novice modeler might be advised to read the Preface and Chapter 1, which together provide a broad introduction to the historical development and goals of molecular mechanics. From there the novice could go to Chapter 5 and read section 5.1 on the components of the molecular mechanics force field, which is presented in 22 pages with plenty of graphical support. The reader is now ready to move to Chapter 6 on applications and work through the 32 exercises (Chapters 3 and 4 have an additional 11 exercises) designed to illustrate the current uses of molecular modeling in academic and industrial research. Chapter 3 (Input and Output), Chapter 4 (File Formats), and the balance of Chapter 5 can be consulted as needed. For example, Chapter 5 contains 160 pages on the evolution of the various empirical force fields in use today and important information in each case on parameterization and implementation. Besides finding a clearly written, wellorganized, thorough presentation, the reader will appreciate a number of other important features. There are numerous references (993) to the primary literature covering the field of molecular mechanics from its beginnings to mid1997, when the book went to press. There is a complete glossary of PCMODEL commands, and a comprehensive and valuable glossary (77 pages) of frequently used computer terms. There are 392 figures (many of them screen captures) providing illustrations of the PCMODEL interface in use and examples of input and output files. To aid the reader/user in obtaining expertise as a modeler, a diskette containing all the structure files for all the exercises accompanies the text. In addition, the author provides, on the same diskette, a browserreadable HTML file that contains links to a large number of pertinent resources on the World Wide Web. In summary, Molecular Modeling on the PC, by Matthew Schlecht, is a very impressive contribution to the molecular modeling literature. Schlecht's book should be in every college and university library and in the personal libraries of those who want to learn more about molecular mechanics or who anticipate its use in their teaching or research.

Functional characterisation of metal(loid) processes in planta through the integration of synchrotron techniques and plant molecular biology

PubMed Central

Donner, Erica; Punshon, Tracy; Guerinot, Mary Lou; Lombi, Enzo

2013-01-01

Functional characterisation of the genes regulating metal(loid) homeostasis in plants is a major focus of crop biofortification, phytoremediation, and food security research. This paper focuses on the potential for advancing plant metal(loid) research by combining molecular biology and synchrotron-based techniques. Recent advances in x-ray focussing optics and fluorescence detection have greatly improved the potential of synchrotron techniques for plant science research, allowing metal(loids) to be imaged in vivo in hydrated plant tissues at sub-micron resolution. Laterally resolved metal(loid) speciation can also be determined. By using molecular techniques to probe the location of gene expression and protein localisation and combining it with this synchrotron-derived data, functional information can be effectively and efficiently assigned to specific genes. This paper provides a review of the state of the art in this field, and provides examples as to how synchrotron-based methods can be combined with molecular techniques to facilitate functional characterisation of genes in planta. PMID:22200921

Computer-assisted determination of minimum energy conformations. 7: A pharmacophore model of the active region of the alpha2-adrenoceptor

NASA Astrophysics Data System (ADS)

Ashman, William P.; Mickiewicz, A. P.; Nelson, Todd M.

1992-09-01

Molecular modeling and computational chemistry techniques are used to analyze compounds in developing pharmacophores of biological receptors to use as templates in structure activity relationship studies and to design new chemicals having physiological activity of interest. In this study, the results of x-ray crystal analyses and PM3 semi-empirical molecular orbital conformational analyses are used to determine the three-dimensional representations of selected adrenergic compounds known to be agonists with the alpha2-adrenoceptor in achieving optimized geometries and electrostatic parameters. The alpha2-adrenergic agonists interact with the adrenergic system receptors to produce various increases or decreases in hemodynamic responses (i.e., hypertension, hypotension, and bradycardia) and sedation. A pharmacophore model of the active region of the alpha2-adrenoceptor is described based on the superimposition of common structural, electrostatic, and physicochemical features of the compounds. Using the model to predict compound adrenergic activity and to design alpha2-adrenergic compounds is discussed.

Multiscale Analysis of a Collapsible Respiratory Airway

NASA Astrophysics Data System (ADS)

Ghadiali, Samir; Bell, E. David; Swarts, J. Douglas

2006-11-01

The Eustachian tube (ET) is a collapsible respiratory airway that connects the nasopharynx with the middle ear (ME). The ET normally exists in a collapsed state and must be periodically opened to maintain a healthy and sterile ME. Although the inability to open the ET (i.e. ET dysfunction) is the primary etiology responsible for several common ME diseases (i.e. Otitis Media), the mechanisms responsible for ET dysfunction are not well established. To investigate these mechanisms, we developed a multi-scale model of airflow in the ET and correlated model results with experimental data obtained in healthy and diseased subjects. The computational models utilized finite-element methods to simulate fluid-structure interactions and molecular dynamics techniques to quantify the adhesive properties of mucus glycoproteins. Results indicate that airflow in the ET is highly sensitive to both the dynamics of muscle contraction and molecular adhesion forces within the ET lumen. In addition, correlation of model results with experimental data obtained in diseased subjects was used to identify the biomechanical mechanisms responsible for ET dysfunction.

Structural and Molecular Modeling Features of P2X Receptors

PubMed Central

Alves, Luiz Anastacio; da Silva, João Herminio Martins; Ferreira, Dinarte Neto Moreira; Fidalgo-Neto, Antonio Augusto; Teixeira, Pedro Celso Nogueira; de Souza, Cristina Alves Magalhães; Caffarena, Ernesto Raúl; de Freitas, Mônica Santos

2014-01-01

Currently, adenosine 5′-triphosphate (ATP) is recognized as the extracellular messenger that acts through P2 receptors. P2 receptors are divided into two subtypes: P2Y metabotropic receptors and P2X ionotropic receptors, both of which are found in virtually all mammalian cell types studied. Due to the difficulty in studying membrane protein structures by X-ray crystallography or NMR techniques, there is little information about these structures available in the literature. Two structures of the P2X4 receptor in truncated form have been solved by crystallography. Molecular modeling has proven to be an excellent tool for studying ionotropic receptors. Recently, modeling studies carried out on P2X receptors have advanced our knowledge of the P2X receptor structure-function relationships. This review presents a brief history of ion channel structural studies and shows how modeling approaches can be used to address relevant questions about P2X receptors. PMID:24637936

Challenges in modelling homogeneous catalysis: new answers from ab initio molecular dynamics to the controversy over the Wacker process.

PubMed

Stirling, András; Nair, Nisanth N; Lledós, Agustí; Ujaque, Gregori

2014-07-21

We present here a review of the mechanistic studies of the Wacker process stressing the long controversy about the key reaction steps. We give an overview of the previous experimental and theoretical studies on the topic. Then we describe the importance of the most recent Ab Initio Molecular Dynamics (AIMD) calculations in modelling organometallic reactivity in water. As a prototypical example of homogeneous catalytic reactions, the Wacker process poses serious challenges to modelling. The adequate description of the multiple role of the water solvent is very difficult by using static quantum chemical approaches including cluster and continuum solvent models. In contrast, such reaction systems are suitable for AIMD, and by combining with rare event sampling techniques, the method provides reaction mechanisms and the corresponding free energy profiles. The review also highlights how AIMD has helped to obtain a novel understanding of the mechanism and kinetics of the Wacker process.

From 3D to 2D: A Review of the Molecular Imprinting of Proteins

PubMed Central

Turner, Nicholas W.; Jeans, Christopher W.; Brain, Keith R.; Allender, Christopher J.; Hlady, Vladimir; Britt, David W.

2008-01-01

Molecular imprinting is a generic technology that allows for the introduction of sites of specific molecular affinity into otherwise homogeneous polymeric matrices. Commonly this technique has been shown to be effective when targeting small molecules of molecular weight <1500, while extending the technique to larger molecules such as proteins has proven difficult. A number of key inherent problems in protein imprinting have been identified, including permanent entrapment, poor mass transfer, denaturation, and heterogeneity in binding pocket affinity, which have been addressed using a variety of approaches. This review focuses on protein imprinting in its various forms, ranging from conventional bulk techniques to novel thin film and monolayer surface imprinting approaches. PMID:17137293

From 3D to 2D: a review of the molecular imprinting of proteins.

PubMed

Turner, Nicholas W; Jeans, Christopher W; Brain, Keith R; Allender, Christopher J; Hlady, Vladimir; Britt, David W

2006-01-01

Molecular imprinting is a generic technology that allows for the introduction of sites of specific molecular affinity into otherwise homogeneous polymeric matrices. Commonly this technique has been shown to be effective when targeting small molecules of molecular weight <1500, while extending the technique to larger molecules such as proteins has proven difficult. A number of key inherent problems in protein imprinting have been identified, including permanent entrapment, poor mass transfer, denaturation, and heterogeneity in binding pocket affinity, which have been addressed using a variety of approaches. This review focuses on protein imprinting in its various forms, ranging from conventional bulk techniques to novel thin film and monolayer surface imprinting approaches.

[Molecular techniques in mycology].

PubMed

Rodríguez-Tudela, Juan Luis; Cuesta, Isabel; Gómez-López, Alicia; Alastruey-Izquierdo, Ana; Bernal-Martínez, Leticia; Cuenca-Estrella, Manuel

2008-11-01

An increasing number of molecular techniques for the diagnosis of fungal infections have been developed in the last few years, due to the growing prevalence of mycoses and the length of time required for diagnosis when classical microbiological methods are used. These methods are designed to resolve the following aspects of mycological diagnosis: a) Identification of fungi to species level by means of sequencing relevant taxonomic targets; b) early clinical diagnosis of invasive fungal infections; c) detection of molecular mechanisms of resistance to antifungal agents; and d) molecular typing of fungi. Currently, these methods are restricted to highly developed laboratories. However, some of these techniques will probably be available in daily clinical practice in the near future.

Opacity probability distribution functions for electronic systems of CN and C2 molecules including their stellar isotopic forms.

NASA Technical Reports Server (NTRS)

Querci, F.; Kunde, V. G.; Querci, M.

1971-01-01

The basis and techniques are presented for generating opacity probability distribution functions for the CN molecule (red and violet systems) and the C2 molecule (Swan, Phillips, Ballik-Ramsay systems), two of the more important diatomic molecules in the spectra of carbon stars, with a view to including these distribution functions in equilibrium model atmosphere calculations. Comparisons to the CO molecule are also shown. T he computation of the monochromatic absorption coefficient uses the most recent molecular data with revision of the oscillator strengths for some of the band systems. The total molecular stellar mass absorption coefficient is established through fifteen equations of molecular dissociation equilibrium to relate the distribution functions to each other on a per gram of stellar material basis.

Next generation patient-derived prostate cancer xenograft models

PubMed Central

Lin, Dong; Xue, Hui; Wang, Yuwei; Wu, Rebecca; Watahiki, Akira; Dong, Xin; Cheng, Hongwei; Wyatt, Alexander W; Collins, Colin C; Gout, Peter W; Wang, Yuzhuo

2014-01-01

There is a critical need for more effective therapeutic approaches for prostate cancer. Research in this area, however, has been seriously hampered by a lack of clinically relevant, experimental in vivo models of the disease. This review particularly focuses on the development of prostate cancer xenograft models based on subrenal capsule grafting of patients’ tumor tissue into nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice. This technique allows successful development of transplantable, patient-derived cancer tissue xenograft lines not only from aggressive metastatic, but also from localized prostate cancer tissues. The xenografts have been found to retain key biological properties of the original malignancies, including histopathological and molecular characteristics, tumor heterogeneity, response to androgen ablation and metastatic ability. As such, they are highly clinically relevant and provide valuable tools for studies of prostate cancer progression at cellular and molecular levels, drug screening for personalized cancer therapy and preclinical drug efficacy testing; especially when a panel of models is used to cover a broader spectrum of the disease. These xenograft models could therefore be viewed as next-generation models of prostate cancer. PMID:24589467

Density functional theory molecular modeling and antimicrobial behaviour of selected 1,2,3,4,5,6,7,8-octahydroacridine-N(10)-oxides

NASA Astrophysics Data System (ADS)

Marinescu, Maria; Cinteza, Ludmila Otilia; Marton, George Iuliu; Marutescu, Luminita Gabriela; Chifiriuc, Mariana-Carmen; Constantinescu, Catalin

2017-09-01

A series of 9-substituted 1,2,3,4,5,6,7,8-octahydroacridine-N(10)-oxides is evaluated against 12 bacterial and fungal strains, for their microbicidal and anti-pathogenic features. The largest spectrum of the antibacterial activity is evidenced for the nitro- (2b) and hydroxy- (5b) N-oxides, followed by the amino-N-oxide (3b). Density functional theory (DFT) modeling of the molecular structure and frontier molecular orbitals, i.e. highest occupied/lowest unoccupied molecular orbital (HOMO/LUMO), is accomplished by using the GAMESS 2012 software at M11/ktzvp level of theory in order to find their structural and electronic parameters. We show that the planarity of the molecules and the presence of the electron withdrawing group are advantages for its antimicrobial activity. Finally, we briefly present and discuss results on the processing of such compounds into thin films and hybrid structures by laser-assisted techniques, i.e. matrix-assisted pulsed laser evaporation (MAPLE) or laser-induced forward transfer (LIFT), to provide simple and environmental friendly, state-of-the-art solutions for antimicrobial/medical coatings and devices.

Molecular-orbital models for the catalytic activity and selectivity of coordinatively unsaturated platinum surfaces and complexes

NASA Astrophysics Data System (ADS)

Balazs, A. C.; Johnson, K. H.

1982-01-01

Electronic structures have been calculated for 5-, 6-, and 10-atom Pt clusters, as well as for a Pt(PH 3) 4 coordination complex, using the self-consistent-field X-alpha scattered-wave (SCF-Xα-SW) molecular-orbital technique. The 10-atom cluster models the local geometry of a flat, unreconstructed Pt(100) surface, while the 5- and 6-atom clusters show features of a stepped Pt surface. Pt(PH 3) 4 resembles the chemically similar homogeneous catalyst Pt(PPh 3) 4. Common to all these coordinatively unsaturated complexes are orbitals lying near or coinciding with the highest occupied molecular orbital ("Fermi level") which show pronounced d lobes pointing directly into the vacuum. Under the hypothesis that these molecular orbitals are mainly responsible for the chemical activities of the above species, one can account for the relative similarities and differences in catalytic activity and selectivity displayed by unreconstructed Pt(100) surfaces, stepped Pt surfaces or particles, and isolated Pt(PPh 3) 4 coordination complexes. The relevance of these findings to catalyst-support interactions is also discussed. Finally, relativistic corrections to the electronic structures are calculated and their implications on catalytic properties discussed.

Homology modeling, molecular docking and molecular dynamics studies of the catalytic domain of chitin deacetylase from Cryptococcus laurentii strain RY1.

PubMed

Sarkar, Soumyadev; Gupta, Suchetana; Chakraborty, Writachit; Senapati, Sanjib; Gachhui, Ratan

2017-11-01

This study provides structural insights into chitin deacetylase, over-expressing under nitrogen limiting condition in Cryptococcus laurentii strain RY1. The enzyme converts chitin, the second most abundant natural biopolymer, to chitosan, which offers tremendous applications in diverse fields. To elucidate the structure-function relationship of this biologically and industrially important enzyme, a homology model of the catalytic domain was constructed. The stability of the structure was assessed by molecular dynamics simulation studies. Tryptophan 151 of the domain was identified to form hydrogen bond and stacking interaction with chitin upon docking. In Silico substitution of Tryptophan (W) to Alanine (A), Phenylalanine (F) and Aspartate (D) corroborated the importance of the Tryptophan residue in interaction with the substrate. This is the first report of unravelling the structural characteristics of chitin deacetylase from Cryptococcus and understanding the approach of the enzyme towards its substrate. Our results would be helpful to perform experimental validations and apply quantum mechanics/molecular mechanics techniques to determine the detailed catalytic mechanism and enhance the industrial potency of the enzyme. Copyright © 2017 Elsevier B.V. All rights reserved.

Testing the limits of sensitivity in a solid-state structural investigation by combined X-ray powder diffraction, solid-state NMR, and molecular modelling.

PubMed

Filip, Xenia; Borodi, Gheorghe; Filip, Claudiu

2011-10-28

A solid state structural investigation of ethoxzolamide is performed on microcrystalline powder by using a multi-technique approach that combines X-ray powder diffraction (XRPD) data analysis based on direct space methods with information from (13)C((15)N) solid-state Nuclear Magnetic Resonance (SS-NMR) and molecular modeling. Quantum chemical computations of the crystal were employed for geometry optimization and chemical shift calculations based on the Gauge Including Projector Augmented-Wave (GIPAW) method, whereas a systematic search in the conformational space was performed on the isolated molecule using a molecular mechanics (MM) approach. The applied methodology proved useful for: (i) removing ambiguities in the XRPD crystal structure determination process and further refining the derived structure solutions, and (ii) getting important insights into the relationship between the complex network of non-covalent interactions and the induced supra-molecular architectures/crystal packing patterns. It was found that ethoxzolamide provides an ideal case study for testing the accuracy with which this methodology allows to distinguish between various structural features emerging from the analysis of the powder diffraction data. This journal is © the Owner Societies 2011

Mannich bases of 1,2,4-triazole-3-thione containing adamantane moiety: Synthesis, preliminary anticancer evaluation, and molecular modeling studies.

PubMed

Milošev, Milorad Z; Jakovljević, Katarina; Joksović, Milan D; Stanojković, Tatjana; Matić, Ivana Z; Perović, Milka; Tešić, Vesna; Kanazir, Selma; Mladenović, Milan; Rodić, Marko V; Leovac, Vukadin M; Trifunović, Snežana; Marković, Violeta

2017-06-01

A series of 18 novel N-Mannich bases derived from 5-adamantyl-1,2,4-triazole-3-thione was synthesized and characterized using NMR spectroscopy and X-ray diffraction technique. All derivatives were evaluated for their anticancer potential against four human cancer cell lines. Several tested compounds exerted good cytotoxic activities on K562 and HL-60 cell lines, along with pronounced selectivity, showing lower cytotoxicity against normal fibroblasts MRC-5 compared to cancer cells. The effects of compounds 5b, 5e, and 5j on the cell cycle were investigated by flow cytometric analysis. It was found that these compounds cause the accumulation of cells in the subG1 and G1 phases of the cell cycle and induce caspase-dependent apoptosis, while the anti-angiogenic effects of 5b, 5e, and 5j have been confirmed in EA.hy926 cells using a tube formation assay. Further, the interaction of Bax protein with compound 5b was investigated by means of molecular modeling, applying the combined molecular docking/molecular dynamics approach. © 2016 John Wiley & Sons A/S.

Surface similarity-based molecular query-retrieval

PubMed Central

Singh, Rahul

2007-01-01

Background Discerning the similarity between molecules is a challenging problem in drug discovery as well as in molecular biology. The importance of this problem is due to the fact that the biochemical characteristics of a molecule are closely related to its structure. Therefore molecular similarity is a key notion in investigations targeting exploration of molecular structural space, query-retrieval in molecular databases, and structure-activity modelling. Determining molecular similarity is related to the choice of molecular representation. Currently, representations with high descriptive power and physical relevance like 3D surface-based descriptors are available. Information from such representations is both surface-based and volumetric. However, most techniques for determining molecular similarity tend to focus on idealized 2D graph-based descriptors due to the complexity that accompanies reasoning with more elaborate representations. Results This paper addresses the problem of determining similarity when molecules are described using complex surface-based representations. It proposes an intrinsic, spherical representation that systematically maps points on a molecular surface to points on a standard coordinate system (a sphere). Molecular surface properties such as shape, field strengths, and effects due to field super-positioningcan then be captured as distributions on the surface of the sphere. Surface-based molecular similarity is subsequently determined by computing the similarity of the surface-property distributions using a novel formulation of histogram-intersection. The similarity formulation is not only sensitive to the 3D distribution of the surface properties, but is also highly efficient to compute. Conclusion The proposed method obviates the computationally expensive step of molecular pose-optimisation, can incorporate conformational variations, and facilitates highly efficient determination of similarity by directly comparing molecular surfaces and surface-based properties. Retrieval performance, applications in structure-activity modeling of complex biological properties, and comparisons with existing research and commercial methods demonstrate the validity and effectiveness of the approach. PMID:17634096

The Role of Molecular Motors in the Mechanics of Active Gels and the Effects of Inertia, Hydrodynamic Interaction and Compressibility in Passive Microrheology

DTIC Science & Technology

2014-07-01

to use the two-point microrheology technique 88 to measure the complex compressibility of biopolymers and cell components such as F-actin and...loads [23, 115]. Several works have used a continuum-mechanics level of description to model self- organization [64, 2] and rheology [79, 12, 33] of...morphogenesis [94]. Several works have used a continuum-mechanics level of description to model self- organization [64, 2] and rheology [79, 12, 33] of

Electronic structure studies of La2CuO4

NASA Astrophysics Data System (ADS)

Wachs, A. L.; Turchi, P. E. A.; Jean, Y. C.; Wetzler, K. H.; Howell, R. H.; Fluss, M. J.; Harshman, D. R.; Remeika, J. P.; Cooper, A. S.; Fleming, R. M.

1988-07-01

We report results of positron-electron momentum-distribution measurements of single-crystal La2CuO4 using two-dimensional angular correlation of positron-annihilation-radiation techniques. The data contain two components: a large (~85%), isotropic corelike electron contribution and a remaining, anisotropic valence-electron contribution modeled using a linear combination of atomic orbitals-molecular orbital method and a localized ion scheme, within the independent-particle model approximation. This work suggests a ligand-field Hamiltonian to be justified for describing the electronic properties of perovskite materials.

Comparison of selected analytical techniques for protein sizing, quantitation and molecular weight determination.

PubMed

Goetz, H; Kuschel, M; Wulff, T; Sauber, C; Miller, C; Fisher, S; Woodward, C

2004-09-30

Protein analysis techniques are developing fast due to the growing number of proteins obtained by recombinant DNA techniques. In the present paper we compare selected techniques, which are used for protein sizing, quantitation and molecular weight determination: sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE), lab-on-a-chip or microfluidics technology (LoaC), size exclusion chromatography (SEC) and mass spectrometry (MS). We compare advantages and limitations of each technique in respect to different application areas, analysis time, protein sizing and quantitation performance.

Molecular modelling of protein-protein/protein-solvent interactions

NASA Astrophysics Data System (ADS)

Luchko, Tyler

The inner workings of individual cells are based on intricate networks of protein-protein interactions. However, each of these individual protein interactions requires a complex physical interaction between proteins and their aqueous environment at the atomic scale. In this thesis, molecular dynamics simulations are used in three theoretical studies to gain insight at the atomic scale about protein hydration, protein structure and tubulin-tubulin (protein-protein) interactions, as found in microtubules. Also presented, in a fourth project, is a molecular model of solvation coupled with the Amber molecular modelling package, to facilitate further studies without the need of explicitly modelled water. Basic properties of a minimally solvated protein were calculated through an extended study of myoglobin hydration with explicit solvent, directly investigating water and protein polarization. Results indicate a close correlation between polarization of both water and protein and the onset of protein function. The methodology of explicit solvent molecular dynamics was further used to study tubulin and microtubules. Extensive conformational sampling of the carboxy-terminal tails of 8-tubulin was performed via replica exchange molecular dynamics, allowing the characterisation of the flexibility, secondary structure and binding domains of the C-terminal tails through statistical analysis methods. Mechanical properties of tubulin and microtubules were calculated with adaptive biasing force molecular dynamics. The function of the M-loop in microtubule stability was demonstrated in these simulations. The flexibility of this loop allowed constant contacts between the protofilaments to be maintained during simulations while the smooth deformation provided a spring-like restoring force. Additionally, calculating the free energy profile between the straight and bent tubulin configurations was used to test the proposed conformational change in tubulin, thought to cause microtubule destabilization. No conformational change was observed but a nucleotide dependent 'softening' of the interaction was found instead, suggesting that an entropic force in a microtubule configuration could be the mechanism of microtubule collapse. Finally, to overcome much of the computational costs associated with explicit soIvent calculations, a new combination of molecular dynamics with the 3D-reference interaction site model (3D-RISM) of solvation was integrated into the Amber molecular dynamics package. Our implementation of 3D-RISM shows excellent agreement with explicit solvent free energy calculations. Several optimisation techniques, including a new multiple time step method, provide a nearly 100 fold performance increase, giving similar computational performance to explicit solvent.

Evaluation of Molecular and Immunohistochemical Adjunct Modalities in the Diagnosis of Soft Tissue Neoplasms.

PubMed

Mourtzoukou, Despoina; Fisher, Cyril; Thway, Khin

2015-12-01

The accurate diagnosis of soft tissue neoplasms has crucial therapeutic and prognostic importance. There is frequent morphologic overlap between entities, and ancillary modalities are used in the vast majority of diagnoses. Immunohistochemistry is rapid and inexpensive, and in addition to the older markers that mainly detected cytoplasmic proteins, antibodies can indirectly detect tumor-specific genetic and molecular abnormalities. The use of molecular diagnostic techniques is now widespread, with molecular services often integrated into routine histopathology laboratories; as their cost and turnaround times begin to parallel those for immunohistochemistry, we compared the usefulness of ancillary immunohistochemistry, molecular genetic, and molecular cytogenetic techniques in the diagnosis of soft tissue lesions. We evaluated the number and contribution of immunohistochemical tests and panels and of ancillary molecular techniques in the primary histopathologic diagnosis of 150 soft tissue lesions. Ninety of 150 cases required either only one immunohistochemical panel or minimal immunohistochemistry for diagnosis, while 39/150 required 2 to 4 panels. In 5/150, ancillary molecular tests alone (without immunohistochemistry) were diagnostically sufficient. The majority of cases required one immunohistochemical panel for diagnosis, with a smaller proportion requiring a second, and a minority requiring a third or fourth (which mainly comprised neoplasms for which the final diagnosis was uncertain). Certain neoplasms required both extensive immunohistochemistry and ancillary molecular testing, despite which the final diagnosis was inconclusive. Ancillary molecular techniques now make a significant contribution to soft tissue tumor diagnosis, being required in over one third (52/150) of cases, and were useful in confirming or excluding tumors that were not possible to conclusively diagnose with histology and immunohistochemistry. Only a small proportion of soft tissue neoplasms (16/150; all benign) did not require immunohistochemistry or ancillary molecular methods, with morphology alone being sufficient for diagnosis. © The Author(s) 2015.

The temperature of large dust grains in molecular clouds

NASA Technical Reports Server (NTRS)

Clark, F. O.; Laureijs, R. J.; Prusti, T.

1991-01-01

The temperature of the large dust grains is calculated from three molecular clouds ranging in visual extinction from 2.5 to 8 mag, by comparing maps of either extinction derived from star counts or gas column density derived from molecular observations to I(100). Both techniques show the dust temperature declining into clouds. The two techniques do not agree in absolute scale.

Isobutylene Dimerization: A Discovery-Based Exploration of Mechanism and Regioselectivity by NMR Spectroscopy and Molecular Modeling

ERIC Educational Resources Information Center

Schuster, Mariah L.; Peterson, Karl P.; Stoffregen, Stacey A.

2018-01-01

This two-period undergraduate laboratory experiment involves the synthesis of a mixture of isomeric unknowns, isolation of the mixture by means of distillation, and characterization of the two products primarily by NMR spectroscopy (1D and 2D) supported with IR spectroscopy and GC-MS techniques. Subsequent calculation and examination of the…

Undergraduate Virology Exercises Demonstrate Conventional and Real-Time PCR Using Commercially Available HIV Primers and Noninfectious Target

ERIC Educational Resources Information Center

Sulzinski, Michael A.; Wasilewski, Melissa A.; Farrell, James C.; Glick, David L.

2009-01-01

It is an extraordinary challenge to offer an undergraduate laboratory course in virology that teaches hands-on, relevant molecular biology techniques using nonpathogenic models of human virus detection. To our knowledge, there exists no inexpensive kits or reagent sets that are appropriate for demonstrating real-time PCR (RT-PCR) in an…

Lunar and Planetary Science XXXVI, Part 9

NASA Technical Reports Server (NTRS)

2005-01-01

The following topics were discussed: Monitoring floods with NASA's ST6 autonomous spacecraft experiment; Dynamical cloud models constrained by high resolution spectroscopy of zodiacal light; The oxygen isotopic composition of the sun and implications for oxygen processing in molecular clouds; A nochian/hisperian hiatus and erosive reactivation of martian valley networks; Hard x-ray spectro-microscopy techniques; Thermoluminescence studies of carbonaceous chondrites, etc.

Interaction between holo transferrin and HSA-PPIX complex in the presence of lomefloxacin: An evaluation of PPIX aggregation in protein-protein interactions

NASA Astrophysics Data System (ADS)

Sattar, Zohreh; Iranfar, Hediye; Asoodeh, Ahmad; Saberi, Mohammad Reza; Mazhari, Mahboobeh; Chamani, Jamshidkhan

2012-11-01

Human serum albumin (HSA) and holo transferrin (TF) are two serum carrier proteins that are able to interact with each other, thereby altering their binding behavior toward their ligands. During the course of this study, the interaction between HSA-PPIX and TF, in the presence and absence of lomefloxacin (LMF), was for the first time investigated using different spectroscopic and molecular modeling techniques. Fluorescence spectroscopy experiments were performed in order to study conformational changes of proteins. The RLS technique was utilized to investigate the effect of LMF on J-aggregation of PPIX, which is the first report of its kind. Our findings present clear-cut evidence for the alteration of interactions between HSA and TF in the presence of PPIX and changes in drug-binding to HSA and HSA-PPIX complex upon interaction with TF. Moreover, molecular modeling studies suggested that the binding site for LMF became switched in the presence of PPIX, and that LMF bound to the site IIA of HSA. The obtained results should give new insight into research in this field and may cast some light on the dynamics of drugs in biological systems.

Teaching light scattering spectroscopy: the dimension and shape of tobacco mosaic virus.

PubMed Central

Santos, N C; Castanho, M A

1996-01-01

The tobacco mosaic virus is used as a model molecular assembly to illustrate the basic potentialities of light scattering techniques (both static and dynamic) to undergraduates. The work has two objectives: a pedagogic one (introducing light scattering to undergraduate students) and a scientific one (stabilization of the virus molecular assembly structure by the nucleic acid). Students are first challenged to confirm the stabilization of the cylindrical shape of the virus by the nucleic acid, at pH and ionic strength conditions where the coat proteins alone do not self-assemble. The experimental intramolecular scattering factor is compared with the theoretical ones for several model geometries. The data clearly suggest that the geometry is, in fact, a rod. Comparing the experimental values of gyration radius and hydrodynamic radius with the theoretical expectations further confirms this conclusion. Moreover, the rod structure is maintained over a wider range of pH and ionic strength than that valid for the coat proteins alone. The experimental values of the diffusion coefficient and radius of gyration are compared with the theoretical expectations assuming the dimensions detected by electron microscopy techniques. In fact, both values are in agreement (length approximately 300 nm, radius approximately 20 nm). PMID:8874039

Scalable Evaluation of Polarization Energy and Associated Forces in Polarizable Molecular Dynamics: II.Towards Massively Parallel Computations using Smooth Particle Mesh Ewald.

PubMed

Lagardère, Louis; Lipparini, Filippo; Polack, Étienne; Stamm, Benjamin; Cancès, Éric; Schnieders, Michael; Ren, Pengyu; Maday, Yvon; Piquemal, Jean-Philip

2014-02-28

In this paper, we present a scalable and efficient implementation of point dipole-based polarizable force fields for molecular dynamics (MD) simulations with periodic boundary conditions (PBC). The Smooth Particle-Mesh Ewald technique is combined with two optimal iterative strategies, namely, a preconditioned conjugate gradient solver and a Jacobi solver in conjunction with the Direct Inversion in the Iterative Subspace for convergence acceleration, to solve the polarization equations. We show that both solvers exhibit very good parallel performances and overall very competitive timings in an energy-force computation needed to perform a MD step. Various tests on large systems are provided in the context of the polarizable AMOEBA force field as implemented in the newly developed Tinker-HP package which is the first implementation for a polarizable model making large scale experiments for massively parallel PBC point dipole models possible. We show that using a large number of cores offers a significant acceleration of the overall process involving the iterative methods within the context of spme and a noticeable improvement of the memory management giving access to very large systems (hundreds of thousands of atoms) as the algorithm naturally distributes the data on different cores. Coupled with advanced MD techniques, gains ranging from 2 to 3 orders of magnitude in time are now possible compared to non-optimized, sequential implementations giving new directions for polarizable molecular dynamics in periodic boundary conditions using massively parallel implementations.

Scalable Evaluation of Polarization Energy and Associated Forces in Polarizable Molecular Dynamics: II.Towards Massively Parallel Computations using Smooth Particle Mesh Ewald

PubMed Central

Lagardère, Louis; Lipparini, Filippo; Polack, Étienne; Stamm, Benjamin; Cancès, Éric; Schnieders, Michael; Ren, Pengyu; Maday, Yvon; Piquemal, Jean-Philip

2015-01-01

In this paper, we present a scalable and efficient implementation of point dipole-based polarizable force fields for molecular dynamics (MD) simulations with periodic boundary conditions (PBC). The Smooth Particle-Mesh Ewald technique is combined with two optimal iterative strategies, namely, a preconditioned conjugate gradient solver and a Jacobi solver in conjunction with the Direct Inversion in the Iterative Subspace for convergence acceleration, to solve the polarization equations. We show that both solvers exhibit very good parallel performances and overall very competitive timings in an energy-force computation needed to perform a MD step. Various tests on large systems are provided in the context of the polarizable AMOEBA force field as implemented in the newly developed Tinker-HP package which is the first implementation for a polarizable model making large scale experiments for massively parallel PBC point dipole models possible. We show that using a large number of cores offers a significant acceleration of the overall process involving the iterative methods within the context of spme and a noticeable improvement of the memory management giving access to very large systems (hundreds of thousands of atoms) as the algorithm naturally distributes the data on different cores. Coupled with advanced MD techniques, gains ranging from 2 to 3 orders of magnitude in time are now possible compared to non-optimized, sequential implementations giving new directions for polarizable molecular dynamics in periodic boundary conditions using massively parallel implementations. PMID:26512230

Interaction of an antiepileptic drug, lamotrigine with human serum albumin (HSA): Application of spectroscopic techniques and molecular modeling methods.

PubMed

Poureshghi, Fatemeh; Ghandforoushan, Parisa; Safarnejad, Azam; Soltani, Somaieh

2017-01-01

Lamotrigine (an epileptic drug) interaction with human serum albumin (HSA) was investigated by fluorescence, UV-Vis, FTIR, CD spectroscopic techniques, and molecular modeling methods. Binding constant (K b ) of 5.74×10 3 and number of binding site of 0.97 showed that there is a slight interaction between lamotrigine and HSA. Thermodynamic studies was constructed using the flourimetric titrations in three different temperatures and the resulted data used to calculate the parameters using Vant Hoff equation. Decreased Stern Volmer quenching constant by enhanced temperature revealed the static quenching mechanism. Negative standard enthalpy (ΔH) and standard entropy (ΔS) changes indicated that van der Waals interactions and hydrogen bonds were dominant forces which facilitate the binding of Lamotrigine to HSA, the results were confirmed by molecular docking studies which showed no hydrogen binding. The FRET studies showed that there is a possibility of energy transfer between Trp214 and lamotrigine. Also the binding of lamotrigine to HSA in the studied concentrations was not as much as many other drugs, but the secondary structure of the HSA was significantly changed following the interaction in a way that α-helix percentage was reduced from 67% to 57% after the addition of lamotrigine in the molar ratio of 4:1 to HSA. According to the docking studies, lamotrigine binds to IB site preferably. Copyright © 2016. Published by Elsevier B.V.

A Research Project-Based and Self-Determined Teaching System of Molecular Biology Techniques for Undergraduates

ERIC Educational Resources Information Center

Zhang, Shuping

2008-01-01

Molecular biology techniques play a very important role in understanding the biological activity. Students who major in biology should know not only how to perform experiments, but also the reasons for performing them. Having the concept of conducting research by integrating various techniques is especially important. This paper introduces a…

Molecular dynamics reveal BCR-ABL1 polymutants as a unique mechanism of resistance to PAN-BCR-ABL1 kinase inhibitor therapy

PubMed Central

Gibbons, Don L.; Pricl, Sabrina; Posocco, Paola; Laurini, Erik; Fermeglia, Maurizio; Sun, Hanshi; Talpaz, Moshe; Donato, Nicholas; Quintás-Cardama, Alfonso

2014-01-01

The acquisition of mutations within the BCR-ABL1 kinase domain is frequently associated with tyrosine kinase inhibitor (TKI) failure in chronic myeloid leukemia. Sensitive sequencing techniques have revealed a high prevalence of compound BCR-ABL1 mutations (polymutants) in patients failing TKI therapy. To investigate the molecular consequences of such complex mutant proteins with regards to TKI resistance, we determined by cloning techniques the presence of polymutants in a cohort of chronic-phase patients receiving imatinib followed by dasatinib therapy. The analysis revealed a high frequency of polymutant BCR-ABL1 alleles even after failure of frontline imatinib, and also the progressive exhaustion of the pool of unmutated BCR-ABL1 alleles over the course of sequential TKI therapy. Molecular dynamics analyses of the most frequent polymutants in complex with TKIs revealed the basis of TKI resistance. Modeling of BCR-ABL1 in complex with the potent pan-BCR-ABL1 TKI ponatinib highlighted potentially effective therapeutic strategies for patients carrying these recalcitrant and complex BCR-ABL1 mutant proteins while unveiling unique mechanisms of escape to ponatinib therapy. PMID:24550512

Improving the leakage current of polyimide-based resistive memory by tuning the molecular chain stack of the polyimide film

NASA Astrophysics Data System (ADS)

Wu, Chi-Chang; Hsiao, Yu-Ping; You, Hsin-Chiang; Lin, Guan-Wei; Kao, Min-Fang; Manga, Yankuba B.; Yang, Wen-Luh

2018-02-01

We have developed an organic-based resistive random access memory (ReRAM) by using spin-coated polyimide (PI) as the resistive layer. In this study, the chain distance and number of chain stacks of PI molecules are investigated. We employed different solid contents of polyamic acid (PAA) to synthesize various PI films, which served as the resistive layer of ReRAM, the electrical performance of which was evaluated. By tuning the PAA solid content, the intermolecular interaction energy of the PI films is changed without altering the molecular structure. Our results show that the leakage current in the high-resistance state and the memory window of the PI-based ReRAM can be substantially improved using this technique. The superior properties of the PI-based ReRAM are ascribed to fewer molecular chain stacks in the PI films when the PAA solid content is decreased, hence suppressing the leakage current. In addition, a device retention time of more than 107 s can be achieved using this technique. Finally, the conduction mechanism in the PI-based ReRAM was analyzed using hopping and conduction models.

Advances in sarcoma diagnostics and treatment

PubMed Central

Dancsok, Amanda R; Asleh-Aburaya, Karama; Nielsen, Torsten O

2017-01-01

The heterogeneity of sarcomas with regard to molecular genesis, histology, clinical characteristics, and response to treatment makes management of these rare yet diverse neoplasms particularly challenging. This review encompasses recent developments in sarcoma diagnostics and treatment, including cytotoxic, targeted, epigenetic, and immune therapy agents. In the past year, groups internationally explored the impact of adding mandatory molecular testing to histological diagnosis, reporting some changes in diagnosis and/or management; however, the impact on outcomes could not be adequately assessed. Transcriptome sequencing techniques have brought forward new diagnostic tools for identifying fusions and/or characterizing unclassified entities. Next-generation sequencing and advanced molecular techniques were also applied to identify potential targets for directed and epigenetic therapy, where preclinical studies reported results for agents active within the receptor tyrosine kinase, mTOR, Notch, Wnt, Hedgehog, Hsp90, and MDM2 signaling networks. At the level of clinical practice, modest developments were seen for some sarcoma subtypes in conventional chemotherapy and in therapies targeting the pathways activated by various receptor tyrosine kinases. In the burgeoning field of immune therapy, sarcoma work is in its infancy; however, elaborate protocols for immune stimulation are being explored, and checkpoint blockade agents advance from preclinical models to clinical studies. PMID:27732970

Raman Doppler velocimetry - A unified approach for measuring molecular flow velocity, temperature, and pressure

NASA Technical Reports Server (NTRS)

Exton, R. J.; Hillard, M. E.

1986-01-01

Molecular flow velocity (one component), translational temperature, and static pressure of N2 are measured in a supersonic wind tunnel using inverse Raman spectroscopy. For velocity, the technique employs the large Doppler shift exhibited by the molecules when the pump and probe laser beams are counterpropagating (backward scattering). A retrometer system is employed to yield an optical configuration insensitive to mechanical vibration, which has the additional advantage of simultaneously obtaining both the forward and backward scattered spectra. The forward and backward line breadths and their relative Doppler shift can be used to determine the static pressure, translational temperature, and molecular flow velocity. A demonstration of the technique was performed in a continuous airflow supersonic wind tunnel in which data were obtained under the following conditions: (1) free-stream operation at five set Mach number levels over the 2.50-4.63 range; (2) free-stream operation over a range of Reynolds number (at a fixed Mach number) to vary systematically the static pressure; and (3) operation in the flow field of a simple aerodynamic model to assess beam steering effects in traversing the attached shock layer.

Linear solvation energy relationships (LSER) for adsorption of organic compounds by carbon nanotubes.

PubMed

Ersan, Gamze; Apul, Onur G; Karanfil, Tanju

2016-07-01

The objective of this paper was to create a comprehensive database for the adsorption of organic compounds by carbon nanotubes (CNTs) and to use the Linear Solvation Energy Relationship (LSER) technique for developing predictive adsorption models of organic compounds (OCs) by multi-walled carbon nanotubes (MWCNTs) and single-walled carbon nanotubes (SWCNTs). Adsorption data for 123 OCs by MWCNTs and 48 OCs by SWCNTs were compiled from the literature, including some experimental results obtained in our laboratory. The roles of selected OCs properties and CNT types were examined with LSER models. The results showed that the r(2) values of the LSER models displayed small variability for aromatic compounds smaller than 220 g/mol, after which a decreasing trend was observed. The data available for aliphatics was mainly for molecular weights smaller than 250 g/mol, which showed a similar trend to that of aromatics. The r(2) values for the LSER model on the adsorption of aromatic and aliphatic OCs by SWCNTs and MWCNTs were relatively similar indicating the linearity of LSER models did not depend on the CNT types. Among all LSER model descriptors, V term (molecular volume) for aromatic OCs and B term (basicity) for aliphatic OCs were the most predominant descriptors on both type of CNTs. The presence of R term (excess molar refractivity) in LSER model equations resulted in decreases for both V and P (polarizability) parameters without affecting the r(2) values. Overall, the results demonstrate that successful predictive models can be developed for the adsorption of OCs by MWCNTs and SWCNTs with LSER techniques. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion–ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Lastly, another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.« less

Molecular Modeling of Thermodynamic and Transport Properties for CO2 and Aqueous Brines.

PubMed

Jiang, Hao; Economou, Ioannis G; Panagiotopoulos, Athanassios Z

2017-04-18

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models for water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2 , and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2 -rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion-ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.

Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

DOE PAGES

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

2017-02-24

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion–ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Lastly, another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.« less

Macromolecular recognition: Structural aspects of the origin of the genetic system

NASA Technical Reports Server (NTRS)

Rein, Robert; Sokalski, W. Andrzej; Barak, Dov; Luo, Ning; Zielinski, Theresa Julia; Shibata, Masayuki

1991-01-01

Theoretical simulation of prebiotic chemical processes is an invaluable tool for probing the phenomenon of the evolution of life. Using computational and modeling techniques and guided by analogies from present day systems, we seek to understand the emergence of the genetic apparatus, enzymatic catalysis and protein synthesis under prebiotic conditions. Modeling of the ancestral aminoacyl-tRNA-synthetases (aRS) may provide important clues to the emergence of the genetic code and the protein synthetic machinery. The minimal structural requirements for the catalysis of tRNA aminoacylation are being explored. A formation of an aminoacyl adenylate was studied in the framework of ab initio molecular orbital theory. The role of individual residues in the vicinity of the TyrRS active site was examined, and the effect of all possible amino acids substitutions near the active site was examined. A formation of aminoacyl tRNA was studied by the molecular modeling system SYBYL with the high resolution crystallographic structures of the present day tRNA, aRS's complexes. The ultimate goal is to propose a simple RNA segment that is small enough to be build in the primordial chemical environment but maintains the specificity and catalytic activity of the contemporary RNA enzyme. To understand the mechanism of ribozyme catalyzed reactions, ab initio and semi-empirical (ZINDO) programs were used to investigate the reaction path of transphosphorylation. A special emphasis was placed on the possible catalytic and structural roles played by the coordinated magnesium cation. Both the inline and adjacent mechanisms of transphosphorylation were studied. The structural characteristics of the target helices, particularly a possible role for the G-T pair, is also studied by a molecular dynamics (MD) simulation technique.

[Advances of Molecular Diagnostic Techniques Application in Clinical Diagnosis.

PubMed

Ying, Bin-Wu

2016-11-01

Over the past 20 years,clinical molecular diagnostic technology has made rapid development,and became the most promising field in clinical laboratory medicine.In particular,with the development of genomics,clinical molecular diagnostic methods will reveal the nature of clinical diseases in a deeper level,thus guiding the clinical diagnosis and treatments.Many molecular diagnostic projects have been routinely applied in clinical works.This paper reviews the advances on application of clinical diagnostic techniques in infectious disease,tumor and genetic disorders,including nucleic acid amplification,biochip,next-generation sequencing,and automation molecular system,and so on.

Automated Illustration of Molecular Flexibility.

PubMed

Bryden, A; Phillips, George N; Gleicher, M

2012-01-01

In this paper, we present an approach to creating illustrations of molecular flexibility using normal mode analysis (NMA). The output of NMA is a collection of points corresponding to the locations of atoms and associated motion vectors, where a vector for each point is known. Our approach abstracts the complex object and its motion by grouping the points, models the motion of each group as an affine velocity, and depicts the motion of each group by automatically choosing glyphs such as arrows. Affine exponentials allow the extrapolation of nonlinear effects such as near rotations and spirals from the linear velocities. Our approach automatically groups points by finding sets of neighboring points whose motions fit the motion model. The geometry and motion models for each group are used to determine glyphs that depict the motion, with various aspects of the motion mapped to each glyph. We evaluated the utility of our system in real work done by structural biologists both by utilizing it in our own structural biology work and quantitatively measuring its usefulness on a set of known protein conformation changes. Additionally, in order to allow ourselves and our collaborators to effectively use our techniques we integrated our system with commonly used tools for molecular visualization.

A 3D visualization system for molecular structures

NASA Technical Reports Server (NTRS)

Green, Terry J.

1989-01-01

The properties of molecules derive in part from their structures. Because of the importance of understanding molecular structures various methodologies, ranging from first principles to empirical technique, were developed for computing the structure of molecules. For large molecules such as polymer model compounds, the structural information is difficult to comprehend by examining tabulated data. Therefore, a molecular graphics display system, called MOLDS, was developed to help interpret the data. MOLDS is a menu-driven program developed to run on the LADC SNS computer systems. This program can read a data file generated by the modeling programs or data can be entered using the keyboard. MOLDS has the following capabilities: draws the 3-D representation of a molecule using stick, ball and ball, or space filled model from Cartesian coordinates, draws different perspective views of the molecule; rotates the molecule on the X, Y, Z axis or about some arbitrary line in space, zooms in on a small area of the molecule in order to obtain a better view of a specific region; and makes hard copy representation of molecules on a graphic printer. In addition, MOLDS can be easily updated and readily adapted to run on most computer systems.

Discovery of simian virus 40 (SV40) and its relationship to poliomyelitis virus vaccines.

PubMed

Hilleman, M R

1998-01-01

Simian Virus 40 (SV40) was discovered in 1959 as a covert contaminant of poliovirus vaccines prepared using Macacus monkey renal cell cultures. This inapparent polyoma virus of monkeys was detected using Cercopithecus renal cell cultures and was eliminated from poliovaccines. There has been no evidence to implicate SV40 virus of vaccine origin in long- or short-term consequences in human subjects. Of importance, SV40 virus provided a new model for basic studies of viral pathogenesis and for cell transformation and neoplasia. Neoplastic transformation is fixed on the promiscuous binding of SV40 large T antigen to anti-oncogene cellular protein elements. SV40 also served as a valuable model for defining the immunology of virus-induced cancer and in its prevention and cure. Further, it has been a prime tool for elucidating the molecular details of eukaryotic cell processes. Numerous techniques now used in molecular biology were pioneered in the SV40 system. The SV40 promoter is commonly used in vector expression constructs and it has continued to be a model to develop new tools for site-specific mutagenesis. The virus has been critically important to studies in modern genetics and in molecular biology.

An End-to-End Model of Plant Pheromone Channel for Long Range Molecular Communication.

PubMed

Unluturk, Bige D; Akyildiz, Ian F

2017-01-01

A new track in molecular communication is using pheromones which can scale up the range of diffusion-based communication from μm meters to meters and enable new applications requiring long range. Pheromone communication is the emission of molecules in the air which trigger behavioral or physiological responses in receiving organisms. The objective of this paper is to introduce a new end-to-end model which incorporates pheromone behavior with communication theory for plants. The proposed model includes both the transmission and reception processes as well as the propagation channel. The transmission process is the emission of pheromones from the leaves of plants. The dispersion of pheromones by the flow of wind constitutes the propagation process. The reception process is the sensing of pheromones by the pheromone receptors of plants. The major difference of pheromone communication from other molecular communication techniques is the dispersion channel acting under the laws of turbulent diffusion. In this paper, the pheromone channel is modeled as a Gaussian puff, i.e., a cloud of pheromone released instantaneously from the source whose dispersion follows a Gaussian distribution. Numerical results on the performance of the overall end-to-end pheromone channel in terms of normalized gain and delay are provided.

Examining the Self-Assembly of Rod-Coil Block Copolymers via Physics Based Polymer Models and Polarized X-Ray Scattering

NASA Astrophysics Data System (ADS)

Hannon, Adam; Sunday, Daniel; Windover, Donald; Liman, Christopher; Bowen, Alec; Khaira, Gurdaman; de Pablo, Juan; Delongchamp, Dean; Kline, R. Joseph

Photovoltaics, flexible electronics, and stimuli-responsive materials all require enhanced methodology to examine their nanoscale molecular orientation. The mechanical, electronic, optical, and transport properties of devices made from these materials are all a function of this orientation. The polymer chains in these materials are best modeled as semi-flexible to rigid rods. Characterizing the rigidity and molecular orientation of these polymers non-invasively is currently being pursued by using polarized resonant soft X-ray scattering (P-RSoXS). In this presentation, we show recent work on implementing such a characterization process using a rod-coil block copolymer system in the rigid-rod limit. We first demonstrate how we have used physics based models such as self-consistent field theory (SCFT) in non-polarized RSoXS work to fit scattering profiles for thin film coil-coil PS- b-PMMA block copolymer systems. We then show by using a wormlike chain partition function in the SCFT formulism to model the rigid-rod block, the methodology can be used there as well to extract the molecular orientation of the rod block from a simulated P-RSoXS experiment. The results from the work show the potential of the technique to extract thermodynamic and morphological sample information.

Molecular Simulation of the Free Energy for the Accurate Determination of Phase Transition Properties of Molecular Solids

NASA Astrophysics Data System (ADS)

Sellers, Michael; Lisal, Martin; Brennan, John

2015-06-01

Investigating the ability of a molecular model to accurately represent a real material is crucial to model development and use. When the model simulates materials in extreme conditions, one such property worth evaluating is the phase transition point. However, phase transitions are often overlooked or approximated because of difficulty or inaccuracy when simulating them. Techniques such as super-heating or super-squeezing a material to induce a phase change suffer from inherent timescale limitations leading to ``over-driving,'' and dual-phase simulations require many long-time runs to seek out what frequently results in an inexact location of phase-coexistence. We present a compilation of methods for the determination of solid-solid and solid-liquid phase transition points through the accurate calculation of the chemical potential. The methods are applied to the Smith-Bharadwaj atomistic potential's representation of cyclotrimethylene trinitramine (RDX) to accurately determine its melting point (Tm) and the alpha to gamma solid phase transition pressure. We also determine Tm for a coarse-grain model of RDX, and compare its value to experiment and atomistic counterpart. All methods are employed via the LAMMPS simulator, resulting in 60-70 simulations that total 30-50 ns. Approved for public release. Distribution is unlimited.

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

PubMed

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

2010-02-01

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell biology has advanced rapidly with increasing availability of new data and powerful simulation techniques, a quantitative orientation is still lacking in life sciences education to make efficient use of these new tools to implement the new toxicity testing paradigm. A revamped undergraduate curriculum in the biological sciences including compulsory courses in mathematics and analysis of dynamical systems is required to address this gap. In parallel, dissemination of computational systems biology techniques and other analytical tools among practicing toxicologists and risk assessment professionals will help accelerate implementation of the new toxicity testing vision.

Resonance Energy Transfer-Based Molecular Switch Designed Using a Systematic Design Process Based on Monte Carlo Methods and Markov Chains

NASA Astrophysics Data System (ADS)

Rallapalli, Arjun

A RET network consists of a network of photo-active molecules called chromophores that can participate in inter-molecular energy transfer called resonance energy transfer (RET). RET networks are used in a variety of applications including cryptographic devices, storage systems, light harvesting complexes, biological sensors, and molecular rulers. In this dissertation, we focus on creating a RET device called closed-diffusive exciton valve (C-DEV) in which the input to output transfer function is controlled by an external energy source, similar to a semiconductor transistor like the MOSFET. Due to their biocompatibility, molecular devices like the C-DEVs can be used to introduce computing power in biological, organic, and aqueous environments such as living cells. Furthermore, the underlying physics in RET devices are stochastic in nature, making them suitable for stochastic computing in which true random distribution generation is critical. In order to determine a valid configuration of chromophores for the C-DEV, we developed a systematic process based on user-guided design space pruning techniques and built-in simulation tools. We show that our C-DEV is 15x better than C-DEVs designed using ad hoc methods that rely on limited data from prior experiments. We also show ways in which the C-DEV can be improved further and how different varieties of C-DEVs can be combined to form more complex logic circuits. Moreover, the systematic design process can be used to search for valid chromophore network configurations for a variety of RET applications. We also describe a feasibility study for a technique used to control the orientation of chromophores attached to DNA. Being able to control the orientation can expand the design space for RET networks because it provides another parameter to tune their collective behavior. While results showed limited control over orientation, the analysis required the development of a mathematical model that can be used to determine the distribution of dipoles in a given sample of chromophore constructs. The model can be used to evaluate the feasibility of other potential orientation control techniques.

Single Nucleobase Identification Using Biophysical Signatures from Nanoelectronic Quantum Tunneling.

PubMed

Korshoj, Lee E; Afsari, Sepideh; Khan, Sajida; Chatterjee, Anushree; Nagpal, Prashant

2017-03-01

Nanoelectronic DNA sequencing can provide an important alternative to sequencing-by-synthesis by reducing sample preparation time, cost, and complexity as a high-throughput next-generation technique with accurate single-molecule identification. However, sample noise and signature overlap continue to prevent high-resolution and accurate sequencing results. Probing the molecular orbitals of chemically distinct DNA nucleobases offers a path for facile sequence identification, but molecular entropy (from nucleotide conformations) makes such identification difficult when relying only on the energies of lowest-unoccupied and highest-occupied molecular orbitals (LUMO and HOMO). Here, nine biophysical parameters are developed to better characterize molecular orbitals of individual nucleobases, intended for single-molecule DNA sequencing using quantum tunneling of charges. For this analysis, theoretical models for quantum tunneling are combined with transition voltage spectroscopy to obtain measurable parameters unique to the molecule within an electronic junction. Scanning tunneling spectroscopy is then used to measure these nine biophysical parameters for DNA nucleotides, and a modified machine learning algorithm identified nucleobases. The new parameters significantly improve base calling over merely using LUMO and HOMO frontier orbital energies. Furthermore, high accuracies for identifying DNA nucleobases were observed at different pH conditions. These results have significant implications for developing a robust and accurate high-throughput nanoelectronic DNA sequencing technique. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advanced imaging techniques for the study of plant growth and development.

PubMed

Sozzani, Rosangela; Busch, Wolfgang; Spalding, Edgar P; Benfey, Philip N

2014-05-01

A variety of imaging methodologies are being used to collect data for quantitative studies of plant growth and development from living plants. Multi-level data, from macroscopic to molecular, and from weeks to seconds, can be acquired. Furthermore, advances in parallelized and automated image acquisition enable the throughput to capture images from large populations of plants under specific growth conditions. Image-processing capabilities allow for 3D or 4D reconstruction of image data and automated quantification of biological features. These advances facilitate the integration of imaging data with genome-wide molecular data to enable systems-level modeling. Copyright © 2013 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nabeel, A.; Khan, M.A.; Husain, S.

Coal is the most abundant source of energy. However, there is a need to develop cleaner, and more efficient, economical, and convenient coal conversion technologies. It is important to understand the organic chemical structure of coal for achieving real breakthroughs in the development of such coal conversion technologies. A novel computer-assisted modeling technique based on the analysis of {sup 13}C NMR and gel permeation chromatography has been applied to predict the average molecular structure of the acetylated product of a depolymerized bituminous Indian coal. The proposed molecular structure may be of practical use in understanding the mechanism of coal conversionsmore » during the processes of liquefaction, gasification, combustion, and carbonization.« less

Numerical analysis of the photo-injection time-of-flight curves in molecularly doped polymers

NASA Astrophysics Data System (ADS)

Tyutnev, A. P.; Ikhsanov, R. Sh.; Saenko, V. S.; Nikerov, D. V.

2018-03-01

We have performed numerical analysis of the charge carrier transport in a specific molecularly doped polymer using the multiple trapping model. The computations covered a wide range of applied electric fields, temperatures and most importantly, of the initial energies of photo injected one-sign carriers (in our case, holes). Special attention has been given to comparison of time of flight curves measured by the photo-injection and radiation-induced techniques which has led to a problematic situation concerning an interpretation of the experimental data. Computational results have been compared with both analytical and experimental results available in literature.

Quantum electron-vibrational dynamics at finite temperature: Thermo field dynamics approach

NASA Astrophysics Data System (ADS)

Borrelli, Raffaele; Gelin, Maxim F.

2016-12-01

Quantum electron-vibrational dynamics in molecular systems at finite temperature is described using an approach based on the thermo field dynamics theory. This formulation treats temperature effects in the Hilbert space without introducing the Liouville space. A comparison with the theoretically equivalent density matrix formulation shows the key numerical advantages of the present approach. The solution of thermo field dynamics equations with a novel technique for the propagation of tensor trains (matrix product states) is discussed. Numerical applications to model spin-boson systems show that the present approach is a promising tool for the description of quantum dynamics of complex molecular systems at finite temperature.

Mirrored continuum and molecular scale simulations of the ignition of high-pressure phases of RDX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Kibaek; Stewart, D. Scott, E-mail: santc@illinois.edu, E-mail: dss@illinois.edu; Joshi, Kaushik

2016-05-14

We present a mirrored atomistic and continuum framework that is used to describe the ignition of energetic materials, and a high-pressure phase of RDX in particular. The continuum formulation uses meaningful averages of thermodynamic properties obtained from the atomistic simulation and a simplification of enormously complex reaction kinetics. In particular, components are identified based on molecular weight bin averages and our methodology assumes that both the averaged atomistic and continuum simulations are represented on the same time and length scales. The atomistic simulations of thermally initiated ignition of RDX are performed using reactive molecular dynamics (RMD). The continuum model ismore » based on multi-component thermodynamics and uses a kinetics scheme that describes observed chemical changes of the averaged atomistic simulations. Thus the mirrored continuum simulations mimic the rapid change in pressure, temperature, and average molecular weight of species in the reactive mixture. This mirroring enables a new technique to simplify the chemistry obtained from reactive MD simulations while retaining the observed features and spatial and temporal scales from both the RMD and continuum model. The primary benefit of this approach is a potentially powerful, but familiar way to interpret the atomistic simulations and understand the chemical events and reaction rates. The approach is quite general and thus can provide a way to model chemistry based on atomistic simulations and extend the reach of those simulations.« less

Ligand-based 3D QSAR analysis of reactivation potency of mono- and bis-pyridinium aldoximes toward VX-inhibited rat acetylcholinesterase.

PubMed

Dolezal, Rafael; Korabecny, Jan; Malinak, David; Honegr, Jan; Musilek, Kamil; Kuca, Kamil

2015-03-01

To predict unknown reactivation potencies of 12 mono- and bis-pyridinium aldoximes for VX-inhibited rat acetylcholinesterase (rAChE), three-dimensional quantitative structure-activity relationship (3D QSAR) analysis has been carried out. Utilizing molecular interaction fields (MIFs) calculated by molecular mechanical (MMFF94) and quantum chemical (B3LYP/6-31G*) methods, two satisfactory ligand-based CoMFA models have been developed: 1. R(2)=0.9989, Q(LOO)(2)=0.9090, Q(LTO)(2)=0.8921, Q(LMO(20%))(2)=0.8853, R(ext)(2)=0.9259, SDEP(ext)=6.8938; 2. R(2)=0.9962, Q(LOO)(2)=0.9368, Q(LTO)(2)=0.9298, Q(LMO(20%))(2)=0.9248, R(ext)(2)=0.8905, SDEP(ext)=6.6756. High statistical significance of the 3D QSAR models has been achieved through the application of several data noise reduction techniques (i.e. smart region definition SRD, fractional factor design FFD, uninformative/iterative variable elimination UVE/IVE) on the original MIFs. Besides the ligand-based CoMFA models, an alignment molecular set constructed by flexible molecular docking has been also studied. The contour maps as well as the predicted reactivation potencies resulting from 3D QSAR analyses help better understand which structural features are associated with increased reactivation potency of studied compounds. Copyright © 2014 Elsevier Inc. All rights reserved.

A Quantitative Structure-Property Relationship (QSPR) Study of Aliphatic Alcohols by the Method of Dividing the Molecular Structure into Substructure

PubMed Central

Liu, Fengping; Cao, Chenzhong; Cheng, Bin

2011-01-01

A quantitative structure–property relationship (QSPR) analysis of aliphatic alcohols is presented. Four physicochemical properties were studied: boiling point (BP), n-octanol–water partition coefficient (lg POW), water solubility (lg W) and the chromatographic retention indices (RI) on different polar stationary phases. In order to investigate the quantitative structure–property relationship of aliphatic alcohols, the molecular structure ROH is divided into two parts, R and OH to generate structural parameter. It was proposed that the property is affected by three main factors for aliphatic alcohols, alkyl group R, substituted group OH, and interaction between R and OH. On the basis of the polarizability effect index (PEI), previously developed by Cao, the novel molecular polarizability effect index (MPEI) combined with odd-even index (OEI), the sum eigenvalues of bond-connecting matrix (SX1CH) previously developed in our team, were used to predict the property of aliphatic alcohols. The sets of molecular descriptors were derived directly from the structure of the compounds based on graph theory. QSPR models were generated using only calculated descriptors and multiple linear regression techniques. These QSPR models showed high values of multiple correlation coefficient (R > 0.99) and Fisher-ratio statistics. The leave-one-out cross-validation demonstrated the final models to be statistically significant and reliable. PMID:21731451

Small-angle neutron scattering study of a monoclonal antibody using free-energy constraints.

PubMed

Clark, Nicholas J; Zhang, Hailiang; Krueger, Susan; Lee, Hyo Jin; Ketchem, Randal R; Kerwin, Bruce; Kanapuram, Sekhar R; Treuheit, Michael J; McAuley, Arnold; Curtis, Joseph E

2013-11-14

Monoclonal antibodies (mAbs) contain hinge-like regions that enable structural flexibility of globular domains that have a direct effect on biological function. A subclass of mAbs, IgG2, have several interchain disulfide bonds in the hinge region that could potentially limit structural flexibility of the globular domains and affect the overall configuration space available to the mAb. We have characterized human IgG2 mAb in solution via small-angle neutron scattering (SANS) and interpreted the scattering data using atomistic models. Molecular Monte Carlo combined with molecular dynamics simulations of a model mAb indicate that a wide range of structural configurations are plausible, spanning radius of gyration values from ∼39 to ∼55 Å. Structural ensembles and representative single structure solutions were derived by comparison of theoretical SANS profiles of mAb models to experimental SANS data. Additionally, molecular mechanical and solvation free-energy calculations were carried out on the ensemble of best-fitting mAb structures. The results of this study indicate that low-resolution techniques like small-angle scattering combined with atomistic molecular simulations with free-energy analysis may be helpful to determine the types of intramolecular interactions that influence function and could lead to deleterious changes to mAb structure. This methodology will be useful to analyze small-angle scattering data of many macromolecular systems.

Molecular tagging techniques and their applications to the study of complex thermal flow phenomena

NASA Astrophysics Data System (ADS)

Chen, Fang; Li, Haixing; Hu, Hui

2015-08-01

This review article reports the recent progress in the development of a new group of molecule-based flow diagnostic techniques, which include molecular tagging velocimetry (MTV) and molecular tagging thermometry (MTT), for both qualitative flow visualization of thermally induced flow structures and quantitative whole-field measurements of flow velocity and temperature distributions. The MTV and MTT techniques can also be easily combined to result in a so-called molecular tagging velocimetry and thermometry (MTV&T) technique, which is capble of achieving simultaneous measurements of flow velocity and temperature distribution in fluid flows. Instead of using tiny particles, the molecular tagging techniques (MTV, MTT, and MTV&T) use phosphorescent molecules, which can be turned into long-lasting glowing marks upon excitation by photons of appropriate wavelength, as the tracers for the flow velocity and temperature measurements. The unique attraction and implementation of the molecular tagging techniques are demonstrated by three application examples, which include: (1) to quantify the unsteady heat transfer process from a heated cylinder to the surrounding fluid flow in order to examine the thermal effects on the wake instabilities behind the heated cylinder operating in mixed and forced heat convection regimes, (2) to reveal the time evolution of unsteady heat transfer and phase changing process inside micro-sized, icing water droplets in order to elucidate the underlying physics pertinent to aircraft icing phenomena, and (3) to achieve simultaneous droplet size, velocity and temperature measurements of "in-flight" droplets to characterize the dynamic and thermodynamic behaviors of flying droplets in spray flows.

Photoacoustic imaging of fluorophores using pump-probe excitation

PubMed Central

Märk, Julia; Schmitt, Franz-Josef; Theiss, Christoph; Dortay, Hakan; Friedrich, Thomas; Laufer, Jan

2015-01-01

A pump-probe technique for the detection of fluorophores in tomographic PA images is introduced. It is based on inducing stimulated emission in fluorescent molecules, which in turn modulates the amount of thermalized energy, and hence the PA signal amplitude. A theoretical model of the PA signal generation in fluorophores is presented and experimentally validated on cuvette measurements made in solutions of Rhodamine 6G, a fluorophore of known optical and molecular properties. The application of this technique to deep tissue tomographic PA imaging is demonstrated by determining the spatial distribution of a near-infrared fluorophore in a tissue phantom. PMID:26203378

Multiscale modeling of a rectifying bipolar nanopore: explicit-water versus implicit-water simulations.

PubMed

Ható, Zoltán; Valiskó, Mónika; Kristóf, Tamás; Gillespie, Dirk; Boda, Dezsö

2017-07-21

In a multiscale modeling approach, we present computer simulation results for a rectifying bipolar nanopore at two modeling levels. In an all-atom model, we use explicit water to simulate ion transport directly with the molecular dynamics technique. In a reduced model, we use implicit water and apply the Local Equilibrium Monte Carlo method together with the Nernst-Planck transport equation. This hybrid method makes the fast calculation of ion transport possible at the price of lost details. We show that the implicit-water model is an appropriate representation of the explicit-water model when we look at the system at the device (i.e., input vs. output) level. The two models produce qualitatively similar behavior of the electrical current for different voltages and model parameters. Looking at the details of concentration and potential profiles, we find profound differences between the two models. These differences, however, do not influence the basic behavior of the model as a device because they do not influence the z-dependence of the concentration profiles which are the main determinants of current. These results then address an old paradox: how do reduced models, whose assumptions should break down in a nanoscale device, predict experimental data? Our simulations show that reduced models can still capture the overall device physics correctly, even though they get some important aspects of the molecular-scale physics quite wrong; reduced models work because they include the physics that is necessary from the point of view of device function. Therefore, reduced models can suffice for general device understanding and device design, but more detailed models might be needed for molecular level understanding.

Measurement of surface stay times for physical adsorption of gases. Ph.D. Thesis - Va. Univ.; [using molecular beam time of flight technique

NASA Technical Reports Server (NTRS)

Wilmoth, R. G.

1973-01-01

A molecular beam time-of-flight technique is studied as a means of determining surface stay times for physical adsorption. The experimental approach consists of pulsing a molecular beam, allowing the pulse to strike an adsorbing surface and detecting the molecular pulse after it has subsequently desorbed. The technique is also found to be useful for general studies of adsorption under nonequilibrium conditions including the study of adsorbate-adsorbate interactions. The shape of the detected pulse is analyzed in detail for a first-order desorption process. For mean stay times, tau, less than the mean molecular transit times involved, the peak of the detected pulse is delayed by an amount approximately equal to tau. For tau much greater than these transit times, the detected pulse should decay as exp(-t/tau). However, for stay times of the order of the transit times, both the molecular speed distributions and the incident pulse duration time must be taken into account.

CGDM: collaborative genomic data model for molecular profiling data using NoSQL.

PubMed

Wang, Shicai; Mares, Mihaela A; Guo, Yi-Ke

2016-12-01

High-throughput molecular profiling has greatly improved patient stratification and mechanistic understanding of diseases. With the increasing amount of data used in translational medicine studies in recent years, there is a need to improve the performance of data warehouses in terms of data retrieval and statistical processing. Both relational and Key Value models have been used for managing molecular profiling data. Key Value models such as SeqWare have been shown to be particularly advantageous in terms of query processing speed for large datasets. However, more improvement can be achieved, particularly through better indexing techniques of the Key Value models, taking advantage of the types of queries which are specific for the high-throughput molecular profiling data. In this article, we introduce a Collaborative Genomic Data Model (CGDM), aimed at significantly increasing the query processing speed for the main classes of queries on genomic databases. CGDM creates three Collaborative Global Clustering Index Tables (CGCITs) to solve the velocity and variety issues at the cost of limited extra volume. Several benchmarking experiments were carried out, comparing CGDM implemented on HBase to the traditional SQL data model (TDM) implemented on both HBase and MySQL Cluster, using large publicly available molecular profiling datasets taken from NCBI and HapMap. In the microarray case, CGDM on HBase performed up to 246 times faster than TDM on HBase and 7 times faster than TDM on MySQL Cluster. In single nucleotide polymorphism case, CGDM on HBase outperformed TDM on HBase by up to 351 times and TDM on MySQL Cluster by up to 9 times. The CGDM source code is available at https://github.com/evanswang/CGDM. y.guo@imperial.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Molecular contributions to conservation

USGS Publications Warehouse

Haig, Susan M.

1998-01-01

Recent advances in molecular technology have opened a new chapter in species conservation efforts, as well as population biology. DNA sequencing, MHC (major histocompatibility complex), minisatellite, microsatellite, and RAPD (random amplified polymorphic DNA) procedures allow for identification of parentage, more distant relatives, founders to new populations, unidentified individuals, population structure, effective population size, population-specific markers, etc. PCR (polymerase chain reaction) amplification of mitochondrial DNA, nuclear DNA, ribosomal DNA, chloroplast DNA, and other systems provide for more sophisticated analyses of metapopulation structure, hybridization events, and delineation of species, subspecies, and races, all of which aid in setting species recovery priorities. Each technique can be powerful in its own right but is most credible when used in conjunction with other molecular techniques and, most importantly, with ecological and demographic data collected from the field. Surprisingly few taxa of concern have been assayed with any molecular technique. Thus, rather than showcasing exhaustive details from a few well-known examples, this paper attempts to present a broad range of cases in which molecular techniques have been used to provide insight into conservation efforts.

Free-Energy Profiles of Membrane Insertion of the M2 Transmembrane Peptide from Influenza A Virus

DTIC Science & Technology

2008-12-01

ABSTRACT The insertion of the M2 transmembrane peptide from influenza A virus into a membrane has been studied with molecular - dynamics simulations ...performed replica-exchange molecular - dynamics simulations with umbrella-sampling techniques to characterize the probability distribution and conformation...atomic- detailed molecular dynamics (MD) simulation techniques represent a valuable complementary methodology to inves- tigate membrane-insertion of

Recent Advances in Particulate Matter and Nanoparticle Toxicology: A Review of the In Vivo and In Vitro Studies

PubMed Central

Nemmar, Abderrahim; Holme, Jørn A.; Rosas, Irma; Schwarze, Per E.

2013-01-01

Epidemiological and clinical studies have linked exposure to particulate matter (PM) to adverse health effects, which may be registered as increased mortality and morbidity from various cardiopulmonary diseases. Despite the evidence relating PM to health effects, the physiological, cellular, and molecular mechanisms causing such effects are still not fully characterized. Two main approaches are used to elucidate the mechanisms of toxicity. One is the use of in vivo experimental models, where various effects of PM on respiratory, cardiovascular, and nervous systems can be evaluated. To more closely examine the molecular and cellular mechanisms behind the different physiological effects, the use of various in vitro models has proven to be valuable. In the present review, we discuss the current advances on the toxicology of particulate matter and nanoparticles based on these techniques. PMID:23865044

Recent advances in collisional effects on spectra of molecular gases and their practical consequences

NASA Astrophysics Data System (ADS)

Hartmann, Jean-Michel; Tran, Ha; Armante, Raymond; Boulet, Christian; Campargue, Alain; Forget, François; Gianfrani, Livio; Gordon, Iouli; Guerlet, Sandrine; Gustafsson, Magnus; Hodges, Joseph T.; Kassi, Samir; Lisak, Daniel; Thibault, Franck; Toon, Geoffrey C.

2018-07-01

We review progress, since publication of the book ``Collisional effects on molecular spectra: Laboratory experiments and models, consequences for applications" (Elsevier, Amsterdam, 2008), on measuring, modeling and predicting the influence of pressure (ie of intermolecular collisions) on the spectra of gas molecules. We first introduce recently developed experimental techniques of high accuracy and sensitivity. We then complement the aforementioned book by presenting the theoretical approaches, results and data proposed (mostly) in the last decade on the topics of isolated line shapes, line-broadening and -shifting, line-mixing, the far wings and associated continua, and collision-induced absorption. Examples of recently demonstrated consequences of the progress in the description of spectral shapes for some practical applications (metrology, probing of gas media, climate predictions) are then given. Remaining issues and directions for future research are finally discussed.

Modeling of the Reaction Mechanism of Enzymatic Radical C–C Coupling by Benzylsuccinate Synthase

PubMed Central

Szaleniec, Maciej; Heider, Johann

2016-01-01

Molecular modeling techniques and density functional theory calculations were performed to study the mechanism of enzymatic radical C–C coupling catalyzed by benzylsuccinate synthase (BSS). BSS has been identified as a glycyl radical enzyme that catalyzes the enantiospecific fumarate addition to toluene initiating its anaerobic metabolism in the denitrifying bacterium Thauera aromatica, and this reaction represents the general mechanism of toluene degradation in all known anaerobic degraders. In this work docking calculations, classical molecular dynamics (MD) simulations, and DFT+D2 cluster modeling was employed to address the following questions: (i) What mechanistic details of the BSS reaction yield the most probable molecular model? (ii) What is the molecular basis of enantiospecificity of BSS? (iii) Is the proposed mechanism consistent with experimental observations, such as an inversion of the stereochemistry of the benzylic protons, syn addition of toluene to fumarate, exclusive production of (R)-benzylsuccinate as a product and a kinetic isotope effect (KIE) ranging between 2 and 4? The quantum mechanics (QM) modeling confirms that the previously proposed hypothetical mechanism is the most probable among several variants considered, although C–H activation and not C–C coupling turns out to be the rate limiting step. The enantiospecificity of the enzyme seems to be enforced by a thermodynamic preference for binding of fumarate in the pro(R) orientation and reverse preference of benzyl radical attack on fumarate in pro(S) pathway which results with prohibitively high energy barrier of the radical quenching. Finally, the proposed mechanism agrees with most of the experimental observations, although the calculated intrinsic KIE from the model (6.5) is still higher than the experimentally observed values (4.0) which suggests that both C–H activation and radical quenching may jointly be involved in the kinetic control of the reaction. PMID:27070573

Molecular and Cellular Quantitative Microscopy: theoretical investigations, technological developments and applications to neurobiology

NASA Astrophysics Data System (ADS)

Esposito, Alessandro

2006-05-01

This PhD project aims at the development and evaluation of microscopy techniques for the quantitative detection of molecular interactions and cellular features. The primarily investigated techniques are Fαrster Resonance Energy Transfer imaging and Fluorescence Lifetime Imaging Microscopy. These techniques have the capability to quantitatively probe the biochemical environment of fluorophores. An automated microscope capable of unsupervised operation has been developed that enables the investigation of molecular and cellular properties at high throughput levels and the analysis of cellular heterogeneity. State-of-the-art Förster Resonance Energy Transfer imaging, Fluorescence Lifetime Imaging Microscopy, Confocal Laser Scanning Microscopy and the newly developed tools have been combined with cellular and molecular biology techniques for the investigation of protein-protein interactions, oligomerization and post-translational modifications of α-Synuclein and Tau, two proteins involved in Parkinson’s and Alzheimer’s disease, respectively. The high inter-disciplinarity of this project required the merging of the expertise of both the Molecular Biophysics Group at the Debye Institute - Utrecht University and the Cell Biophysics Group at the European Neuroscience Institute - Gαttingen University. This project was conducted also with the support and the collaboration of the Center for the Molecular Physiology of the Brain (Göttingen), particularly with the groups associated with the Molecular Quantitative Microscopy and Parkinson’s Disease and Aggregopathies areas. This work demonstrates that molecular and cellular quantitative microscopy can be used in combination with high-throughput screening as a powerful tool for the investigation of the molecular mechanisms of complex biological phenomena like those occurring in neurodegenerative diseases.

Experimental and computational prediction of glass transition temperature of drugs.

PubMed

Alzghoul, Ahmad; Alhalaweh, Amjad; Mahlin, Denny; Bergström, Christel A S

2014-12-22

Glass transition temperature (Tg) is an important inherent property of an amorphous solid material which is usually determined experimentally. In this study, the relation between Tg and melting temperature (Tm) was evaluated using a data set of 71 structurally diverse druglike compounds. Further, in silico models for prediction of Tg were developed based on calculated molecular descriptors and linear (multilinear regression, partial least-squares, principal component regression) and nonlinear (neural network, support vector regression) modeling techniques. The models based on Tm predicted Tg with an RMSE of 19.5 K for the test set. Among the five computational models developed herein the support vector regression gave the best result with RMSE of 18.7 K for the test set using only four chemical descriptors. Hence, two different models that predict Tg of drug-like molecules with high accuracy were developed. If Tm is available, a simple linear regression can be used to predict Tg. However, the results also suggest that support vector regression and calculated molecular descriptors can predict Tg with equal accuracy, already before compound synthesis.

Modeling L2,3-Edge X-ray Absorption Spectroscopy with Real-Time Exact Two-Component Relativistic Time-Dependent Density Functional Theory.

PubMed

Kasper, Joseph M; Lestrange, Patrick J; Stetina, Torin F; Li, Xiaosong

2018-04-10

X-ray absorption spectroscopy is a powerful technique to probe local electronic and nuclear structure. There has been extensive theoretical work modeling K-edge spectra from first principles. However, modeling L-edge spectra directly with density functional theory poses a unique challenge requiring further study. Spin-orbit coupling must be included in the model, and a noncollinear density functional theory is required. Using the real-time exact two-component method, we are able to variationally include one-electron spin-orbit coupling terms when calculating the absorption spectrum. The abilities of different basis sets and density functionals to model spectra for both closed- and open-shell systems are investigated using SiCl 4 and three transition metal complexes, TiCl 4 , CrO 2 Cl 2 , and [FeCl 6 ] 3- . Although we are working in the real-time framework, individual molecular orbital transitions can still be recovered by projecting the density onto the ground state molecular orbital space and separating contributions to the time evolving dipole moment.

Techniques for Investigating Molecular Toxicology of Nanomaterials.

PubMed

Wang, Yanli; Li, Chenchen; Yao, Chenjie; Ding, Lin; Lei, Zhendong; Wu, Minghong

2016-06-01

Nanotechnology has been a rapidly developing field in the past few decades, resulting in the more and more exposure of nanomaterials to human. The increased applications of nanomaterials for industrial, commercial and life purposes, such as fillers, catalysts, semiconductors, paints, cosmetic additives and drug carriers, have caused both obvious and potential impacts on human health and environment. Nanotoxicology is used to study the safety of nanomaterials and has grown at the historic moment. Molecular toxicology is a new subdiscipline to study the interactions and impacts of materials at the molecular level. To better understand the relationship between the molecular toxicology and nanomaterials, this review summarizes the typical techniques and methods in molecular toxicology which are applied when investigating the toxicology of nanomaterials and include six categories: namely; genetic mutation detection, gene expression analysis, DNA damage detection, chromosomal aberration analysis, proteomics, and metabolomics. Each category involves several experimental techniques and methods.

Molecular ecology of aquatic communities: Reflections and future directions

USGS Publications Warehouse

Zehr, J.P.; Voytek, M.A.

1999-01-01

During the 1980s, many new molecular biology techniques were developed, providing new capabilities for studying the genetics and activities of organisms. Biologists and ecologists saw the promise that these techniques held for studying different aspects of organisms, both in culture and in the natural environment. In less than a decade, these techniques were adopted by a large number of researchers studying many types of organisms in diverse environments. Much of the molecular-level information acquired has been used to address questions of evolution, biogeography, population structure and biodiversity. At this juncture, molecular ecologists are poised to contribute to the study of the fundamental characteristics underlying aquatic community structure. The goal of this overview is to assess where we have been, where we are now and what the future holds for revealing the basis of community structure and function with molecular-level information.

A comprehensive pharmacokinetic/pharmacodynamics analysis of the novel IGF1R/INSR inhibitor BI 893923 applying in vitro, in vivo and in silico modeling techniques.

PubMed

Titze, Melanie I; Schaaf, Otmar; Hofmann, Marco H; Sanderson, Michael P; Zahn, Stephan K; Quant, Jens; Lehr, Thorsten

2016-06-01

BI 893923 is a novel IGF1R/INSR tyrosine kinase inhibitor demonstrating anti-tumor efficacy and good tolerability. We aimed to characterize the relationship between BI 893923 plasma concentration, tumor biomarker modulation, tumor growth and hyperglycemia in mice using in silico modeling analyses. In vitro molecular and cellular assays were used to demonstrate the potency and selectivity of BI 893923. Diverse in vitro DMPK assays were used to characterize the compound's drug-like properties. Mice xenografted with human GEO tumors were treated with different doses of BI 893923 to demonstrate the compound's efficacy, biomarker modulation and tolerability. PK/PD analyses were performed using nonlinear mixed-effects modeling. BI 893923 demonstrated potent and selective molecular inhibition of the IGF1R and INSR and demonstrated attractive drug-like properties (permeability, bioavailability). BI 893923 dose-dependently reduced GEO tumor growth and demonstrated good tolerability, characterized by transient hyperglycemia and normal body weight gain. A population PK/PD model was developed, which established relationships between BI 893923 pharmacokinetics, hyperglycemia, pIGF1R reduction and tumor growth. BI 893923 demonstrates molecular properties consistent with a highly attractive inhibitor of the IGF1R/INSR. A generic PK/PD model was developed to support preclinical drug development and dose finding in mice.

Measuring CAMD technique performance. 2. How "druglike" are drugs? Implications of Random test set selection exemplified using druglikeness classification models.

PubMed

Good, Andrew C; Hermsmeier, Mark A

2007-01-01

Research into the advancement of computer-aided molecular design (CAMD) has a tendency to focus on the discipline of algorithm development. Such efforts are often wrought to the detriment of the data set selection and analysis used in said algorithm validation. Here we highlight the potential problems this can cause in the context of druglikeness classification. More rigorous efforts are applied to the selection of decoy (nondruglike) molecules from the ACD. Comparisons are made between model performance using the standard technique of random test set creation with test sets derived from explicit ontological separation by drug class. The dangers of viewing druglike space as sufficiently coherent to permit simple classification are highlighted. In addition the issues inherent in applying unfiltered data and random test set selection to (Q)SAR models utilizing large and supposedly heterogeneous databases are discussed.

Preclinical Imaging for the Study of Mouse Models of Thyroid Cancer

PubMed Central

Greco, Adelaide; Orlandella, Francesca Maria; Iervolino, Paola Lucia Chiara; Klain, Michele; Salvatore, Giuliana

2017-01-01

Thyroid cancer, which represents the most common tumors among endocrine malignancies, comprises a wide range of neoplasms with different clinical aggressiveness. One of the most important challenges in research is to identify mouse models that most closely resemble human pathology; other goals include finding a way to detect markers of disease that common to humans and mice and to identify the most appropriate and least invasive therapeutic strategies for specific tumor types. Preclinical thyroid imaging includes a wide range of techniques that allow for morphological and functional characterization of thyroid disease as well as targeting and in most cases, this imaging allows quantitative analysis of the molecular pattern of the thyroid cancer. The aim of this review paper is to provide an overview of all of the imaging techniques used to date both for diagnosis and theranostic purposes in mouse models of thyroid cancer. PMID:29258188

Novel cationic lipid nanoparticles as an ophthalmic delivery system for multicomponent drugs: development, characterization, in vitro permeation, in vivo pharmacokinetic, and molecular dynamics studies.

PubMed

Wang, Jialu; Zhao, Fang; Liu, Rui; Chen, Jingjing; Zhang, Qinghua; Lao, Ruijuan; Wang, Ze; Jin, Xin; Liu, Changxiao

2017-01-01

The purpose of this study was to prepare, optimize, and characterize a cationic lipid nanoparticle (CLN) system containing multicomponent drugs using a molecular dynamics model as a novel method of evaluating formulations. Puerarin (PUE) and scutellarin (SCU) were used as model drugs. CLNs were successfully prepared using melt-emulsion ultrasonication and low temperature-solidification technique. The properties of CLNs such as morphology, particle size, zeta potential, entrapment efficiency (EE), drug loading (DL), and drug release behavior were investigated. The CLNs were evaluated by corneal permeation, preocular retention time, and pharmacokinetics in the aqueous humor. Additionally, a molecular dynamics model was used to evaluate the formulation. Electron microscopy results showed that the nanoparticles were approximately spherical in shape. The EE (%) and DL (%) values of PUE and SCU in the optimal formulation were 56.60±3.73, 72.31±1.96 and 1.68±0.17, 2.44±1.14, respectively. The pharmacokinetic study in the aqueous humor showed that compared with the PUE and SCU solution, the area under the concentration-time curve (AUC) value of PUE was enhanced by 2.33-fold for PUE-SCU CLNs ( p <0.01), and the SCU AUC was enhanced by 2.32-fold ( p <0.01). In the molecular dynamics model, PUE and SCU passed through the POPC bilayer, with an obvious difference in the free energy well depth. It was found that the maximum free energy required for PUE and SCU transmembrane movement was ~15 and 88 kJ·mol -1 , respectively. These findings indicated that compared with SCU, PUE easily passed through the membrane. The diffusion coefficient for PUE and SCU were 4.1×10 -3 ±0.0027 and 1.0×10 -3 ±0.0006 e -5 cm 2 ·s -1 , respectively. Data from the molecular dynamics model were consistent with the experimental data. All data indicated that CLNs have a great potential for ocular administration and can be used as an ocular delivery system for multicomponent drugs. Moreover, the molecular dynamics model can also be used as a novel method for evaluating formulations.

A Matter of the Heart: The African Clawed Frog Xenopus as a Model for Studying Vertebrate Cardiogenesis and Congenital Heart Defects

PubMed Central

Hempel, Annemarie; Kühl, Michael

2016-01-01

The African clawed frog, Xenopus, is a valuable non-mammalian model organism to investigate vertebrate heart development and to explore the underlying molecular mechanisms of human congenital heart defects (CHDs). In this review, we outline the similarities between Xenopus and mammalian cardiogenesis, and provide an overview of well-studied cardiac genes in Xenopus, which have been associated with congenital heart conditions. Additionally, we highlight advantages of modeling candidate genes derived from genome wide association studies (GWAS) in Xenopus and discuss commonly used techniques. PMID:29367567

Free-stream temperature, density, and pressure measurements in an expansion tube flow

NASA Technical Reports Server (NTRS)

Haggard, K. V.

1973-01-01

An experimental study was conducted to determine test-flow conditions in the Langley pilot model expansion tube. Measurements of temperature, density, wall pressure, pitot pressure, and shock and interface velocities were compared with theoretical calculations based on various models of the flow cycle. The vibrational temperature and integrated density of the molecular oxygen component of the flow were measured by use of vacuum ultraviolet absorption techniques. These measurements indicate both the presence and possible degree of nonequilibrium in the flow. Data are compared with several simplified models of the flow cycle, and data trends are discussed.

Hybrid schemes based on quantum mechanics/molecular mechanics simulations goals to success, problems, and perspectives.

PubMed

Ferrer, Silvia; Ruiz-Pernía, Javier; Martí, Sergio; Moliner, Vicent; Tuñón, Iñaki; Bertrán, Juan; Andrés, Juan

2011-01-01

The development of characterization techniques, advanced synthesis methods, as well as molecular modeling has transformed the study of systems in a well-established research field. The current research challenges in biocatalysis and biotransformation evolve around enzyme discovery, design, and optimization. How can we find or create enzymes that catalyze important synthetic reactions, even reactions that may not exist in nature? What is the source of enzyme catalytic power? To answer these and other related questions, the standard strategies have evolved from trial-and-error methodologies based on chemical knowledge, accumulated experience, and common sense into a clearly multidisciplinary science that allows one to reach the molecular design of tailor-made enzyme catalysts. This is even more so when one refers to enzyme catalysts, for which the detailed structure and composition are known and can be manipulated to introduce well-defined residues which can be implicated in the chemical rearrangements taking place in the active site. The methods and techniques of theoretical and computational chemistry are becoming more and more important in both understanding the fundamental biological roles of enzymes and facilitating their utilization in biotechnology. Improvement of the catalytic function of enzymes is important from scientific and industrial viewpoints, and to put this fact in the actual perspective as well as the potentialities, we recommend the very recent report of Sanderson [Sanderson, K. (2011). Chemistry: enzyme expertise. Nature 471, 397.]. Great fundamental advances have been made toward the ab initio design of enzyme catalysts based on molecular modeling. This has been based on the molecular mechanistic knowledge of the reactions to be catalyzed, together with the development of advanced synthesis and characterization techniques. The corresponding molecular mechanism can be studied by means of powerful quantum chemical calculations. The catalytic active site can be optimized to improve the transition state analogues (TSA) and to enhance the catalytic activity, even improve the active site to favor a desired direction of some promiscuous enzymes. In this chapter, we give a brief introduction, the state of the art, and future prospects and implications of enzyme design. Current computational tools to assist experimentalists for the design and engineering of proteins with desired catalytic properties are described. The interplay between enzyme design, molecular simulations, and experiments will be presented to emphasize the interdisciplinary nature of this research field. This text highlights the recent advances and examples selected from our laboratory are shown, of how the applications of these tools are a first attempt to de novo design of protein active sites. Identification of neutral/advantageous/deleterious mutation platforms can be exploited to penetrate some of Nature's closely guarded secrets of chemical reactivity. In this chapter, we give a brief introduction, the state of the art, and future prospects and implications of enzyme design. The first part describes briefly how the molecular modeling is carried out. Then, we discuss the requirements of hybrid quantum mechanical/molecular mechanics molecular dynamics (QM/MM MD) simulations, analyzing what are the basis of these theoretical methodologies, how we can use them with a view to its application in the study of enzyme catalysis, and what are the best methodologies for assessing its catalytic potential. In the second part, we focus on some selected examples, taking as a common guide the chorismate to prephenate rearrangement, studying the corresponding molecular mechanism in vacuo, in solution and in an enzyme environment. In addition, examples involving catalytic antibodies (CAs) and promiscuous enzymes will be presented. Finally, a special emphasis is made to provide some hints about the logical evolution that can be anticipated in this research field. Moreover, it helps in understanding the open directions in this area of knowledge and highlights the importance of computational approaches in discovering specific drugs and the impact on the rational design of tailor-made enzymes. Copyright © 2011 Elsevier Inc. All rights reserved.

Nonholonomic Hamiltonian Method for Meso-macroscale Simulations of Reacting Shocks

NASA Astrophysics Data System (ADS)

Fahrenthold, Eric; Lee, Sangyup

2015-06-01

The seamless integration of macroscale, mesoscale, and molecular scale models of reacting shock physics has been hindered by dramatic differences in the model formulation techniques normally used at different scales. In recent research the authors have developed the first unified discrete Hamiltonian approach to multiscale simulation of reacting shock physics. Unlike previous work, the formulation employs reacting themomechanical Hamiltonian formulations at all scales, including the continuum. Unlike previous work, the formulation employs a nonholonomic modeling approach to systematically couple the models developed at all scales. Example applications of the method show meso-macroscale shock to detonation simulations in nitromethane and RDX. Research supported by the Defense Threat Reduction Agency.

Challenges for Complex Microbial Ecosystems: Combination of Experimental Approaches with Mathematical Modeling

PubMed Central

Haruta, Shin; Yoshida, Takehito; Aoi, Yoshiteru; Kaneko, Kunihiko; Futamata, Hiroyuki

2013-01-01

In the past couple of decades, molecular ecological techniques have been developed to elucidate microbial diversity and distribution in microbial ecosystems. Currently, modern techniques, represented by meta-omics and single cell observations, are revealing the incredible complexity of microbial ecosystems and the large degree of phenotypic variation. These studies propound that microbiological techniques are insufficient to untangle the complex microbial network. This minireview introduces the application of advanced mathematical approaches in combination with microbiological experiments to microbial ecological studies. These combinational approaches have successfully elucidated novel microbial behaviors that had not been recognized previously. Furthermore, the theoretical perspective also provides an understanding of the plasticity, robustness and stability of complex microbial ecosystems in nature. PMID:23995424

Efficient grid-based techniques for density functional theory

NASA Astrophysics Data System (ADS)

Rodriguez-Hernandez, Juan Ignacio

Understanding the chemical and physical properties of molecules and materials at a fundamental level often requires quantum-mechanical models for these substance's electronic structure. This type of many body quantum mechanics calculation is computationally demanding, hindering its application to substances with more than a few hundreds atoms. The supreme goal of many researches in quantum chemistry---and the topic of this dissertation---is to develop more efficient computational algorithms for electronic structure calculations. In particular, this dissertation develops two new numerical integration techniques for computing molecular and atomic properties within conventional Kohn-Sham-Density Functional Theory (KS-DFT) of molecular electronic structure. The first of these grid-based techniques is based on the transformed sparse grid construction. In this construction, a sparse grid is generated in the unit cube and then mapped to real space according to the pro-molecular density using the conditional distribution transformation. The transformed sparse grid was implemented in program deMon2k, where it is used as the numerical integrator for the exchange-correlation energy and potential in the KS-DFT procedure. We tested our grid by computing ground state energies, equilibrium geometries, and atomization energies. The accuracy on these test calculations shows that our grid is more efficient than some previous integration methods: our grids use fewer points to obtain the same accuracy. The transformed sparse grids were also tested for integrating, interpolating and differentiating in different dimensions (n = 1,2,3,6). The second technique is a grid-based method for computing atomic properties within QTAIM. It was also implemented in deMon2k. The performance of the method was tested by computing QTAIM atomic energies, charges, dipole moments, and quadrupole moments. For medium accuracy, our method is the fastest one we know of.

Undergraduate virology exercises demonstrate conventional and real-time PCR using commercially available HIV primers and noninfectious target.

PubMed

Sulzinski, Michael A; Wasilewski, Melissa A; Farrell, James C; Glick, David L

2009-07-01

It is an extraordinary challenge to offer an undergraduate laboratory course in virology that teaches hands-on, relevant molecular biology techniques using nonpathogenic models of human virus detection. To our knowledge, there exists no inexpensive kits or reagent sets that are appropriate for demonstrating real-time PCR (RT-PCR) in an undergraduate laboratory course in virology. Here we describe simple procedures for student exercises that demonstrate the PCR detection of an HIV target nucleic acid. Our procedures combine a commercially available kit for conventional PCR with a modification for RT-PCR using the same reagents in the kit, making it possible for an instructor with access to a LightCycler® instrument to implement a relevant student exercise on RT-PCR detection of HIV nucleic acid targets. This combination of techniques is useful for demonstrating and comparing conventional PCR amplification and detection with agarose gel electrophoresis, with real-time PCR over a series of three laboratory periods. The series of laboratory periods also is used to provide the foundation for teaching the concept of PCR primer design, optimization of PCR detection systems, and introduction to nucleic acid queries using NCBI-BLAST to find and identify primers, amplicons, and other potential amplification targets within the HIV viral genome. The techniques were successfully implemented at the Biology 364 undergraduate virology course at the University of Scranton during the Fall 2008 semester. The techniques are particularly targeted to students who intend to pursue either postgraduate technical employment or graduate studies in the molecular life sciences. Copyright © 2009 International Union of Biochemistry and Molecular Biology, Inc.

Molecular Diode Studies Based on a Highly Sensitive Molecular Measurement Technique.

PubMed

Iwane, Madoka; Fujii, Shintaro; Kiguchi, Manabu

2017-04-26

In 1974, molecular electronics pioneers Mark Ratner and Arieh Aviram predicted that a single molecule could act as a diode, in which electronic current can be rectified. The electronic rectification property of the diode is one of basic functions of electronic components and since then, the molecular diode has been investigated as a first single-molecule device that would have a practical application. In this review, we first describe the experimental fabrication and electronic characterization techniques of molecular diodes consisting of a small number of molecules or a single molecule. Then, two main mechanisms of the rectification property of the molecular diode are discussed. Finally, representative results for the molecular diode are reviewed and a brief outlook on crucial issues that need to be addressed in future research is discussed.

Molecular Diode Studies Based on a Highly Sensitive Molecular Measurement Technique

PubMed Central

Iwane, Madoka; Fujii, Shintaro; Kiguchi, Manabu

2017-01-01

In 1974, molecular electronics pioneers Mark Ratner and Arieh Aviram predicted that a single molecule could act as a diode, in which electronic current can be rectified. The electronic rectification property of the diode is one of basic functions of electronic components and since then, the molecular diode has been investigated as a first single-molecule device that would have a practical application. In this review, we first describe the experimental fabrication and electronic characterization techniques of molecular diodes consisting of a small number of molecules or a single molecule. Then, two main mechanisms of the rectification property of the molecular diode are discussed. Finally, representative results for the molecular diode are reviewed and a brief outlook on crucial issues that need to be addressed in future research is discussed. PMID:28445393

Study of Barley Grain Molecular Structure for Ruminants Using DRIFT, FTIR-ATR and Synchrotron Radiation Infrared Microspectroscopy (SR-IMS): A Review

NASA Astrophysics Data System (ADS)

Yu, Peiqiang

2012-05-01

Barley inherent structures are highly associated with nutrient utilization and availability in both humans and animals. Barley has different degradation kinetics compared with other cereal grains. It has a relatively higher degradation rate and extent, which often cause digestive disorder in the rumen. Therefore understanding barley inherent structure at cellular and molecular levels and processing-induced structure changes is important, because we can manipulate barley inherent structures and digestive behaviors. Several molecular spectroscopy techniques can be used to detect barley inherent structures at cellular and molecular levels. This article reviews several applications of the IR molecular spectral bioanalytical techniques - DRIFT, FT/IR-ATR and SR-IMS for barley chemistry, molecular structure and molecular nutrition research

Methods to study maternal regulation of germ cell specification in zebrafish

PubMed Central

Kaufman, O.H.; Marlow, F.L.

2016-01-01

The process by which the germ line is specified in the zebrafish embryo is under the control of maternal gene products that were produced during oogenesis. Zebrafish are highly amenable to microscopic observation of the processes governing maternal germ cell specification because early embryos are transparent, and the germ line is specified rapidly (within 4–5 h post fertilization). Advantages of zebrafish over other models used to study vertebrate germ cell formation include their genetic tractability, the large numbers of progeny, and the easily manipulable genome, all of which make zebrafish an ideal system for studying the genetic regulators and cellular basis of germ cell formation and maintenance. Classical molecular biology techniques, including expression analysis through in situ hybridization and forward genetic screens, have laid the foundation for our understanding of germ cell development in zebrafish. In this chapter, we discuss some of these classic techniques, as well as recent cutting-edge methodologies that have improved our ability to visualize the process of germ cell specification and differentiation, and the tracking of specific molecules involved in these processes. Additionally, we discuss traditional and novel technologies for manipulating the zebrafish genome to identify new components through loss-of-function studies of putative germ cell regulators. Together with the numerous aforementioned advantages of zebrafish as a genetic model for studying development, we believe these new techniques will continue to advance zebrafish to the forefront for investigation of the molecular regulators of germ cell specification and germ line biology. PMID:27312489

Three Dimensional Projection Environment for Molecular Design and Surgical Simulation

DTIC Science & Technology

2011-08-01

bypasses the cumbersome meshing process . The deformation model is only comprised of mass nodes, which are generated by sampling the object volume before...force should minimize the penetration volume, the haptic feedback force is derived directly. Additionally, a post- processing technique is developed to...render distinct physi-cal tissue properties across different interaction areas. The proposed approach does not require any pre- processing and is

A Biochemistry and Molecular Biology Experiment and Evaluation System for Biotechnology Specialty Students: An Effective Evaluation System to Improve the Biochemistry and Molecular Biology Experiment Teaching

ERIC Educational Resources Information Center

Li, Suxia; Wu, Haizhen; Zhao, Jian; Ou, Ling; Zhang, Yuanxing

2010-01-01

In an effort to achieve high success in knowledge and technique acquisition as a whole, a biochemistry and molecular biology experiment was established for high-grade biotechnology specialty students after they had studied essential theory and received proper technique training. The experiment was based on cloning and expression of alkaline…

Using NMR chemical shift imaging to monitor swelling and molecular transport in drug-loaded tablets of hydrophobically modified poly(acrylic acid): methodology and effects of polymer (in)solubility.

PubMed

Knöös, Patrik; Topgaard, Daniel; Wahlgren, Marie; Ulvenlund, Stefan; Piculell, Lennart

2013-11-12

A new technique has been developed using NMR chemical shift imaging (CSI) to monitor water penetration and molecular transport in initially dry polymer tablets that also contain small low-molecular weight compounds to be released from the tablets. Concentration profiles of components contained in the swelling tablets could be extracted via the intensities and chemical shift changes of peaks corresponding to protons of the components. The studied tablets contained hydrophobically modified poly(acrylic acid) (HMPAA) as the polymer component and griseofulvin and ethanol as hydrophobic and hydrophilic, respectively, low-molecular weight model compounds. The water solubility of HMPAA could be altered by titration with NaOH. In the pure acid form, HMPAA tablets only underwent a finite swelling until the maximum water content of the polymer-rich phase, as confirmed by independent phase studies, had been reached. By contrast, after partial neutralization with NaOH, the polyacid became fully miscible with water. The solubility of the polymer affected the water penetration, the polymer release, and the releases of both ethanol and griseofulvin. The detailed NMR CSI concentration profiles obtained highlighted the clear differences in the disintegration/dissolution/release behavior for the two types of tablet and provided insights into their molecular origin. The study illustrates the potential of the NMR CSI technique to give information of importance for the development of pharmaceutical tablets and, more broadly, for the general understanding of any operation that involves the immersion and ultimate disintegration of a dry polymer matrix in a solvent.

Mapping molecular orientational distributions for biological sample in 3D (Conference Presentation)

NASA Astrophysics Data System (ADS)

HE, Wei; Ferrand, Patrick; Richter, Benjamin; Bastmeyer, Martin; Brasselet, Sophie

2016-04-01

Measuring molecular orientation properties is very appealing for scientists in molecular and cell biology, as well as biomedical research. Orientational organization at the molecular scale is indeed an important brick to cells and tissues morphology, mechanics, functions and pathologies. Recent work has shown that polarized fluorescence imaging, based on excitation polarization tuning in the sample plane, is able to probe molecular orientational order in biological samples; however this applies only to information in 2D, projected in the sample plane. To surpass this limitation, we extended this approach to excitation polarization tuning in 3D. The principle is based on the decomposition of any arbitrary 3D linear excitation in a polarization along the longitudinal z-axis, and a polarization in the transverse xy-sample plane. We designed an interferometer with one arm generating radial polarization light (thus producing longitudinal polarization under high numerical aperture focusing), the other arm controlling a linear polarization in the transverse plane. The amplitude ratio between the two arms can vary so as to get any linear polarized excitation in 3D at the focus of a high NA objective. This technique has been characterized by polarimetry imaging at the back focal plane of the focusing objective, and modeled theoretically. 3D polarized fluorescence microscopy is demonstrated on actin stress fibers in non-flat cells suspended on synthetic polymer structures forming supporting pillars, for which heterogeneous actin orientational order could be identified. This technique shows a great potential in structural investigations in 3D biological systems, such as cell spheroids and tissues.

Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore

PubMed Central

Ibrahim, Bashar; Henze, Richard; Gruenert, Gerd; Egbert, Matthew; Huwald, Jan; Dittrich, Peter

2013-01-01

A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models. PMID:24709796

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

NASA Astrophysics Data System (ADS)

Zhi, Hui; Zheng, Junxia; Chang, Yiqun; Li, Qingguo; Liao, Guochao; Wang, Qi; Sun, Pinghua

2015-10-01

Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q2 value of 0.792 and an r2 value of 0.985. The best CoMSIA model predicted a q2 value of 0.633 and an r2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients (rpred2) of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted.

A study of the Interaction of bovine Hemoglobin with Synthetic dyes using Spectroscopic techniques and Molecular docking

NASA Astrophysics Data System (ADS)

Kamaljeet; Bansal, Saurabh; SenGupta, Uttara

2016-12-01

Synthetic dyes are a very efficient class of dyes that are ingested or come into contact with the skin from numerous sources (cosmetics, textiles, leather, paper, drugs). An important component of their safety profile is the interactions that they form after they enter the body. Hemoglobin is a functionally important protein that can form multiple interactions with soluble compounds present in the blood, and hence forms an important aspect of the toxicological or safety profile of the dyes. Here we study the interaction between bovine haemoglobin and organic dyes using UV-Vis absorbance and fluorescence spectroscopy. Molecular modelling was used to visualise the binding site and partners of the dye molecules, within the hemoglobin molecule. We find that all four dyes studied form sufficiently strong interactions with haemoglobin to allow for the formation of potentially toxic interactions. Molecular modelling showed that all 4 dyes bound within the central cavity of the haemoglobin molecule. However, binding partners could not be identified as multiple binding conformations with very similar energies were possible for each dye.

A Study of the Interaction of Bovine Hemoglobin with Synthetic Dyes Using Spectroscopic Techniques and Molecular Docking.

PubMed

Kamaljeet; Bansal, Saurabh; SenGupta, Uttara

2016-01-01

Synthetic dyes are a very efficient class of dyes that are ingested or come into contact with the skin from numerous sources (cosmetics, textiles, leather, paper, and drugs). An important component of their safety profile is the interactions that they form after they enter the body. Hemoglobin is a functionally important protein that can form multiple interactions with soluble compounds present in the blood, and hence forms an important aspect of the toxicological or safety profile of the dyes. Here we study the interaction between bovine hemoglobin and organic dyes using UV-Vis absorbance and fluorescence spectroscopy. Molecular modeling was used to visualize the binding site and partners of the dye molecules, within the hemoglobin molecule. We find that all four dyes studied form sufficiently strong interactions with hemoglobin to allow for the formation of potentially toxic interactions. Molecular modeling showed that all four dyes bind within the central cavity of the hemoglobin molecule. However, binding partners could not be identified as multiple binding conformations with very similar energies were possible for each dye.

A Catalog of Distances to Molecular Clouds from Pan-STARRS1

NASA Astrophysics Data System (ADS)

Schlafly, Eddie; Green, G.; Finkbeiner, D. P.; Rix, H.

2014-01-01

We present a catalog of distances to molecular clouds, derived from PanSTARRS-1 photometry. We simultaneously infer the full probability distribution function of reddening and distance of the stars towards these clouds using the technique of Green et al. (2013) (see neighboring poster). We fit the resulting measurements using a simple dust screen model to infer the distance to each cloud. The result is a large, homogeneous catalog of distances to molecular clouds. For clouds with heliocentric distances greater than about 200 pc, typical statistical uncertainties in the distances are 5%, with systematic uncertainty stemming from the quality of our stellar models of about 10%. We have applied this analysis to many of the most well-studied clouds in the δ > -30° sky, including Orion, California, Taurus, Perseus, and Cepheus. We have also studied the entire catalog of Magnani, Blitz, and Mundy (1985; MBM), though for about half of those clouds we can provide only upper limits on the distances. We compare our distances with distances from the literature, when available, and find good agreement.

Molecular modeling and spectroscopic studies on the interaction of the chiral drug venlafaxine hydrochloride with bovine serum albumin

NASA Astrophysics Data System (ADS)

Shahabadi, Nahid; Hadidi, Saba

2014-03-01

This study was designed to examine the interaction of racemic antidepressant drug "S,R-venlafaxine hydrochloride (VEN)" with bovine serum albumin (BSA) under physiological conditions. The mechanism of interaction was studied by spectroscopic techniques combination with molecular modeling. Stern-Volmer analysis of fluorescence quenching data shows the presence of the static quenching mechanism. The thermodynamic parameters indicated that the hydrogen bonding and weak van der Waals interactions are the predominant intermolecular forces stabilizing the complex. The number of binding sites (n) was calculated. Through the site marker competitive experiment, VEN was confirmed to be located in subdomain IIIA of BSA. The binding distance (r = 4.93 nm) between the donor BSA and acceptor VEN was obtained according to Förster's non-radiative energy transfer theory. According to UV-vis spectra and CD data binding of VEN leaded to conformational changes of BSA. Molecular docking simulations of S and R-VEN revealed that both isomers have similar interaction and the same binding sites, from this point of view S and R isomers are equal.

Molecularly imprinted membranes (MIMs) for selective removal of polychlorinated biphenyls (PCBs) in environmental waters: fabrication and characterization.

PubMed

Mkhize, Dennis S; Nyoni, Hlengilizwe; Quinn, Laura P; Mamba, Bhekie B; Msagati, Titus A M

2017-04-01

Molecularly imprinted membranes (MIMs) with selective removal properties for polychlorinated biphenyls (PCBs) were prepared through the phase inversion technique. The MIMs were obtained from casting the viscous solutions of molecularly imprinted polymers (MIPs), polysulfone (PSf), and N-methyl-2-pyrrolidone (NMP) as the casting solvent. Different membranes were prepared at different concentration of MIPs and PSf. The resulting MIMs were characterized by atomic force microscope (AFM), scanning electron microscope (SEM), and Fourier transform infrared spectroscopy (FTIR). Moreover, the performance of the membranes was evaluated by determining and interpreting the rejection (%), flux (F), permeability coefficient (P), permselectivity factor ( α ' PCB/DDT or anthracene ), and enrichment factors of PCBs, dichlorodiphenyltrichloroethane (p,p'-DDT), and anthracene from model contaminated water using the dead-end filtration cell. Molecularly imprinted membrane prepared with 18 wt% PSf and 20 wt% MIP 4 exhibited a well-defined porous structure, which was accompanied by enhanced PCB enrichment. Furthermore, molecularly imprinted membrane showed good enrichment factors for PCBs even from spiked natural water samples of Hartbeespoort dam.

Heuristic lipophilicity potential for computer-aided rational drug design

NASA Astrophysics Data System (ADS)

Du, Qishi; Arteca, Gustavo A.; Mezey, Paul G.

1997-09-01

In this contribution we suggest a heuristic molecular lipophilicitypotential (HMLP), which is a structure-based technique requiring noempirical indices of atomic lipophilicity. The input data used in thisapproach are molecular geometries and molecular surfaces. The HMLP is amodified electrostatic potential, combined with the averaged influences fromthe molecular environment. Quantum mechanics is used to calculate theelectron density function ρ(r) and the electrostatic potential V(r), andfrom this information a lipophilicity potential L(r) is generated. The HMLPis a unified lipophilicity and hydrophilicity potential. The interactions ofdipole and multipole moments, hydrogen bonds, and charged atoms in amolecule are included in the hydrophilic interactions in this model. TheHMLP is used to study hydrogen bonds and water-octanol partitioncoefficients in several examples. The calculated results show that the HMLPgives qualitatively and quantitatively correct, as well as chemicallyreasonable, results in cases where comparisons are available. Thesecomparisons indicate that the HMLP has advantages over the empiricallipophilicity potential in many aspects. The HMLP is a three-dimensional andeasily visualizable representation of molecular lipophilicity, suggested asa potential tool in computer-aided three-dimensional drug design.

Modeling the Dynamics of Gel Electrophorresis in the High School Classroom

NASA Astrophysics Data System (ADS)

Saucedo, Skyler R.

2013-01-01

Gel electrophoresis, used by geneticists and forensic experts alike, is an immensely popular technique that utilizes an electric field to separate molecules and proteins by size and charge. At the microscopic level, a dye or complex protein like DNA is passed through agarose, a gelatinous three-dimensional matrix of pores and nano-sized tunnels. When forced through a maze of holes, the molecule unravels, forming a long chain, slithering through the field of pores in a process colloquially coined "reputation." As a result, the smaller molecules travel farther through the gel when compared to molecules of larger molecular weight. This highly effective "molecular sieve" provides consistent data and allows scientists to compare similar sequences of DNA base pairs in a routine fashion.2 When performed at the high school level, gel electrophoresis provides students the opportunity to learn about a contemporary lab technique of great scientific relevance. Doing real science certainly excites students and motivates them to learn more.