Quantum Mechanics/Molecular Mechanics Method Combined with Hybrid All-Atom and Coarse-Grained Model: Theory and Application on Redox Potential Calculations.

PubMed

Shen, Lin; Yang, Weitao

2016-04-12

We developed a new multiresolution method that spans three levels of resolution with quantum mechanical, atomistic molecular mechanical, and coarse-grained models. The resolution-adapted all-atom and coarse-grained water model, in which an all-atom structural description of the entire system is maintained during the simulations, is combined with the ab initio quantum mechanics and molecular mechanics method. We apply this model to calculate the redox potentials of the aqueous ruthenium and iron complexes by using the fractional number of electrons approach and thermodynamic integration simulations. The redox potentials are recovered in excellent accordance with the experimental data. The speed-up of the hybrid all-atom and coarse-grained water model renders it computationally more attractive. The accuracy depends on the hybrid all-atom and coarse-grained water model used in the combined quantum mechanical and molecular mechanical method. We have used another multiresolution model, in which an atomic-level layer of water molecules around redox center is solvated in supramolecular coarse-grained waters for the redox potential calculations. Compared with the experimental data, this alternative multilayer model leads to less accurate results when used with the coarse-grained polarizable MARTINI water or big multipole water model for the coarse-grained layer.

Development of Pantothenate Analogs That Can Treat Combat-Related Infections

DTIC Science & Technology

2014-04-01

determined by the molecular replacement method using the structure of S. aureus PanK excluding bound AMPPNP as a search model ( PDB code 2EWS). The...were solved by molecular replacement using the program PHASER11 and the EcPanK structure as a search model ( PDB : 1SQ5). The models went through...aureus PanK (SaPanK) complexed with N5- Pan (months 1-3) We solved the structure of the SaPanK�N5-Pan complex by the molecular replacement method

Coestimation of recombination, substitution and molecular adaptation rates by approximate Bayesian computation.

PubMed

Lopes, J S; Arenas, M; Posada, D; Beaumont, M A

2014-03-01

The estimation of parameters in molecular evolution may be biased when some processes are not considered. For example, the estimation of selection at the molecular level using codon-substitution models can have an upward bias when recombination is ignored. Here we address the joint estimation of recombination, molecular adaptation and substitution rates from coding sequences using approximate Bayesian computation (ABC). We describe the implementation of a regression-based strategy for choosing subsets of summary statistics for coding data, and show that this approach can accurately infer recombination allowing for intracodon recombination breakpoints, molecular adaptation and codon substitution rates. We demonstrate that our ABC approach can outperform other analytical methods under a variety of evolutionary scenarios. We also show that although the choice of the codon-substitution model is important, our inferences are robust to a moderate degree of model misspecification. In addition, we demonstrate that our approach can accurately choose the evolutionary model that best fits the data, providing an alternative for when the use of full-likelihood methods is impracticable. Finally, we applied our ABC method to co-estimate recombination, substitution and molecular adaptation rates from 24 published human immunodeficiency virus 1 coding data sets.

Extending rule-based methods to model molecular geometry and 3D model resolution.

PubMed

Hoard, Brittany; Jacobson, Bruna; Manavi, Kasra; Tapia, Lydia

2016-08-01

Computational modeling is an important tool for the study of complex biochemical processes associated with cell signaling networks. However, it is challenging to simulate processes that involve hundreds of large molecules due to the high computational cost of such simulations. Rule-based modeling is a method that can be used to simulate these processes with reasonably low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry. The incorporation of geometry into biochemical models can more accurately capture details of these processes, and may lead to insights into how geometry affects the products that form. Furthermore, geometric rule-based modeling can be used to complement other computational methods that explicitly represent molecular geometry in order to quantify binding site accessibility and steric effects. We propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and binding rates. We demonstrate how rules are constructed according to the molecular curvature. We then perform a study of antigen-antibody aggregation using our proposed method. We simulate the binding of antibody complexes to binding regions of the shrimp allergen Pen a 1 using a previously developed 3D rigid-body Monte Carlo simulation, and we analyze the aggregate sizes. Then, using our novel approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. We use the distances between the binding regions of Pen a 1 to optimize the rules and binding rates. We perform this procedure for multiple conformations of Pen a 1 and analyze the impact of conformation and resolution on the optimal rule-based model. We find that the optimized rule-based models provide information about the average steric hindrance between binding regions and the probability that antibodies will bind to these regions. These optimized models quantify the variation in aggregate size that results from differences in molecular geometry and from model resolution.

Multiscale Modeling for the Analysis for Grain-Scale Fracture Within Aluminum Microstructures

NASA Technical Reports Server (NTRS)

Glaessgen, Edward H.; Phillips, Dawn R.; Yamakov, Vesselin; Saether, Erik

2005-01-01

Multiscale modeling methods for the analysis of metallic microstructures are discussed. Both molecular dynamics and the finite element method are used to analyze crack propagation and stress distribution in a nanoscale aluminum bicrystal model subjected to hydrostatic loading. Quantitative similarity is observed between the results from the two very different analysis methods. A bilinear traction-displacement relationship that may be embedded into cohesive zone finite elements is extracted from the nanoscale molecular dynamics results.

Simultaneous construction of PCR-DGGE-based predictive models of Listeria monocytogenes and Vibrio parahaemolyticus on cooked shrimps.

PubMed

Liao, C; Peng, Z Y; Li, J B; Cui, X W; Zhang, Z H; Malakar, P K; Zhang, W J; Pan, Y J; Zhao, Y

2015-03-01

The aim of this study was to simultaneously construct PCR-DGGE-based predictive models of Listeria monocytogenes and Vibrio parahaemolyticus on cooked shrimps at 4 and 10°C. Calibration curves were established to correlate peak density of DGGE bands with microbial counts. Microbial counts derived from PCR-DGGE and plate methods were fitted by Baranyi model to obtain molecular and traditional predictive models. For L. monocytogenes, growing at 4 and 10°C, molecular predictive models were constructed. It showed good evaluations of correlation coefficients (R(2) > 0.92), bias factors (Bf ) and accuracy factors (Af ) (1.0 ≤ Bf ≤ Af ≤ 1.1). Moreover, no significant difference was found between molecular and traditional predictive models when analysed on lag phase (λ), maximum growth rate (μmax ) and growth data (P > 0.05). But for V. parahaemolyticus, inactivated at 4 and 10°C, molecular models show significant difference when compared with traditional models. Taken together, these results suggest that PCR-DGGE based on DNA can be used to construct growth models, but it is inappropriate for inactivation models yet. This is the first report of developing PCR-DGGE to simultaneously construct multiple molecular models. It has been known for a long time that microbial predictive models based on traditional plate methods are time-consuming and labour-intensive. Denaturing gradient gel electrophoresis (DGGE) has been widely used as a semiquantitative method to describe complex microbial community. In our study, we developed DGGE to quantify bacterial counts and simultaneously established two molecular predictive models to describe the growth and survival of two bacteria (Listeria monocytogenes and Vibrio parahaemolyticus) at 4 and 10°C. We demonstrated that PCR-DGGE could be used to construct growth models. This work provides a new approach to construct molecular predictive models and thereby facilitates predictive microbiology and QMRA (Quantitative Microbial Risk Assessment). © 2014 The Society for Applied Microbiology.

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

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.

Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.

PubMed

DiMaio, Frank

2017-01-01

Molecular replacement (MR), a method for solving the crystallographic phase problem using phases derived from a model of the target structure, has proven extremely valuable, accounting for the vast majority of structures solved by X-ray crystallography. However, when the resolution of data is low, or the starting model is very dissimilar to the target protein, solving structures via molecular replacement may be very challenging. In recent years, protein structure prediction methodology has emerged as a powerful tool in model building and model refinement for difficult molecular replacement problems. This chapter describes some of the tools available in Rosetta for model building and model refinement specifically geared toward difficult molecular replacement cases.

Complex molecular assemblies at hand via interactive simulations.

PubMed

Delalande, Olivier; Férey, Nicolas; Grasseau, Gilles; Baaden, Marc

2009-11-30

Studying complex molecular assemblies interactively is becoming an increasingly appealing approach to molecular modeling. Here we focus on interactive molecular dynamics (IMD) as a textbook example for interactive simulation methods. Such simulations can be useful in exploring and generating hypotheses about the structural and mechanical aspects of biomolecular interactions. For the first time, we carry out low-resolution coarse-grain IMD simulations. Such simplified modeling methods currently appear to be more suitable for interactive experiments and represent a well-balanced compromise between an important gain in computational speed versus a moderate loss in modeling accuracy compared to higher resolution all-atom simulations. This is particularly useful for initial exploration and hypothesis development for rare molecular interaction events. We evaluate which applications are currently feasible using molecular assemblies from 1900 to over 300,000 particles. Three biochemical systems are discussed: the guanylate kinase (GK) enzyme, the outer membrane protease T and the soluble N-ethylmaleimide-sensitive factor attachment protein receptors complex involved in membrane fusion. We induce large conformational changes, carry out interactive docking experiments, probe lipid-protein interactions and are able to sense the mechanical properties of a molecular model. Furthermore, such interactive simulations facilitate exploration of modeling parameters for method improvement. For the purpose of these simulations, we have developed a freely available software library called MDDriver. It uses the IMD protocol from NAMD and facilitates the implementation and application of interactive simulations. With MDDriver it becomes very easy to render any particle-based molecular simulation engine interactive. Here we use its implementation in the Gromacs software as an example. Copyright 2009 Wiley Periodicals, Inc.

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.

Molecular graph convolutions: moving beyond fingerprints

NASA Astrophysics Data System (ADS)

Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick

2016-08-01

Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph—atoms, bonds, distances, etc.—which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.

Molecular graph convolutions: moving beyond fingerprints.

PubMed

Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick

2016-08-01

Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph-atoms, bonds, distances, etc.-which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.

A pharmacophore model specific to active site of CYP1A2 with a novel molecular modeling explorer and CoMFA.

PubMed

Zhang, Tao; Wei, Dong-Qing; Chou, Kuo-Chen

2012-03-01

Comparative molecular field analysis (CoMFA) is a widely used 3D-QSAR method by which we can investigate the potential relation between biological activity of compounds and their structural features. In this study, a new application of this approach is presented by combining the molecular modeling with a new developed pharmacophore model specific to CYP1A2 active site. During constructing the model, we used the molecular dynamics simulation and molecular docking method to select the sensible binding conformations for 17 CYP1A2 substrates based on the experimental data. Subsequently, the results obtained via the alignment of binding conformations of substrates were projected onto the active- site residues, upon which a simple blueprint of active site was produced. It was validated by the experimental and computational results that the model did exhibit the high degree of rationality and provide useful insights into the substrate binding. It is anticipated that our approach can be extended to investigate the protein-ligand interactions for many other enzyme-catalyzed systems as well.

Biological intuition in alignment-free methods: response to Posada.

PubMed

Ragan, Mark A; Chan, Cheong Xin

2013-08-01

A recent editorial in Journal of Molecular Evolution highlights opportunities and challenges facing molecular evolution in the era of next-generation sequencing. Abundant sequence data should allow more-complex models to be fit at higher confidence, making phylogenetic inference more reliable and improving our understanding of evolution at the molecular level. However, concern that approaches based on multiple sequence alignment may be computationally infeasible for large datasets is driving the development of so-called alignment-free methods for sequence comparison and phylogenetic inference. The recent editorial characterized these approaches as model-free, not based on the concept of homology, and lacking in biological intuition. We argue here that alignment-free methods have not abandoned models or homology, and can be biologically intuitive.

Thermodynamic properties for applications in chemical industry via classical force fields.

PubMed

Guevara-Carrion, Gabriela; Hasse, Hans; Vrabec, Jadran

2012-01-01

Thermodynamic properties of fluids are of key importance for the chemical industry. Presently, the fluid property models used in process design and optimization are mostly equations of state or G (E) models, which are parameterized using experimental data. Molecular modeling and simulation based on classical force fields is a promising alternative route, which in many cases reasonably complements the well established methods. This chapter gives an introduction to the state-of-the-art in this field regarding molecular models, simulation methods, and tools. Attention is given to the way modeling and simulation on the scale of molecular force fields interact with other scales, which is mainly by parameter inheritance. Parameters for molecular force fields are determined both bottom-up from quantum chemistry and top-down from experimental data. Commonly used functional forms for describing the intra- and intermolecular interactions are presented. Several approaches for ab initio to empirical force field parameterization are discussed. Some transferable force field families, which are frequently used in chemical engineering applications, are described. Furthermore, some examples of force fields that were parameterized for specific molecules are given. Molecular dynamics and Monte Carlo methods for the calculation of transport properties and vapor-liquid equilibria are introduced. Two case studies are presented. First, using liquid ammonia as an example, the capabilities of semi-empirical force fields, parameterized on the basis of quantum chemical information and experimental data, are discussed with respect to thermodynamic properties that are relevant for the chemical industry. Second, the ability of molecular simulation methods to describe accurately vapor-liquid equilibrium properties of binary mixtures containing CO(2) is shown.

Visualizing functional motions of membrane transporters with molecular dynamics simulations.

PubMed

Shaikh, Saher A; Li, Jing; Enkavi, Giray; Wen, Po-Chao; Huang, Zhijian; Tajkhorshid, Emad

2013-01-29

Computational modeling and molecular simulation techniques have become an integral part of modern molecular research. Various areas of molecular sciences continue to benefit from, indeed rely on, the unparalleled spatial and temporal resolutions offered by these technologies, to provide a more complete picture of the molecular problems at hand. Because of the continuous development of more efficient algorithms harvesting ever-expanding computational resources, and the emergence of more advanced and novel theories and methodologies, the scope of computational studies has expanded significantly over the past decade, now including much larger molecular systems and far more complex molecular phenomena. Among the various computer modeling techniques, the application of molecular dynamics (MD) simulation and related techniques has particularly drawn attention in biomolecular research, because of the ability of the method to describe the dynamical nature of the molecular systems and thereby to provide a more realistic representation, which is often needed for understanding fundamental molecular properties. The method has proven to be remarkably successful in capturing molecular events and structural transitions highly relevant to the function and/or physicochemical properties of biomolecular systems. Herein, after a brief introduction to the method of MD, we use a number of membrane transport proteins studied in our laboratory as examples to showcase the scope and applicability of the method and its power in characterizing molecular motions of various magnitudes and time scales that are involved in the function of this important class of membrane proteins.

Visualizing Functional Motions of Membrane Transporters with Molecular Dynamics Simulations

PubMed Central

2013-01-01

Computational modeling and molecular simulation techniques have become an integral part of modern molecular research. Various areas of molecular sciences continue to benefit from, indeed rely on, the unparalleled spatial and temporal resolutions offered by these technologies, to provide a more complete picture of the molecular problems at hand. Because of the continuous development of more efficient algorithms harvesting ever-expanding computational resources, and the emergence of more advanced and novel theories and methodologies, the scope of computational studies has expanded significantly over the past decade, now including much larger molecular systems and far more complex molecular phenomena. Among the various computer modeling techniques, the application of molecular dynamics (MD) simulation and related techniques has particularly drawn attention in biomolecular research, because of the ability of the method to describe the dynamical nature of the molecular systems and thereby to provide a more realistic representation, which is often needed for understanding fundamental molecular properties. The method has proven to be remarkably successful in capturing molecular events and structural transitions highly relevant to the function and/or physicochemical properties of biomolecular systems. Herein, after a brief introduction to the method of MD, we use a number of membrane transport proteins studied in our laboratory as examples to showcase the scope and applicability of the method and its power in characterizing molecular motions of various magnitudes and time scales that are involved in the function of this important class of membrane proteins. PMID:23298176

Modeling of diatomic molecule using the Morse potential and the Verlet algorithm

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

Fidiani, Elok

Performing molecular modeling usually uses special software for Molecular Dynamics (MD) such as: GROMACS, NAMD, JMOL etc. Molecular dynamics is a computational method to calculate the time dependent behavior of a molecular system. In this work, MATLAB was used as numerical method for a simple modeling of some diatomic molecules: HCl, H{sub 2} and O{sub 2}. MATLAB is a matrix based numerical software, in order to do numerical analysis, all the functions and equations describing properties of atoms and molecules must be developed manually in MATLAB. In this work, a Morse potential was generated to describe the bond interaction betweenmore » the two atoms. In order to analyze the simultaneous motion of molecules, the Verlet Algorithm derived from Newton’s Equations of Motion (classical mechanics) was operated. Both the Morse potential and the Verlet algorithm were integrated using MATLAB to derive physical properties and the trajectory of the molecules. The data computed by MATLAB is always in the form of a matrix. To visualize it, Visualized Molecular Dynamics (VMD) was performed. Such method is useful for development and testing some types of interaction on a molecular scale. Besides, this can be very helpful for describing some basic principles of molecular interaction for educational purposes.« less

A study of some non-equilibrium driven models and their contribution to the understanding of molecular motors

NASA Astrophysics Data System (ADS)

Mazilu, Irina; Gonzalez, Joshua

2008-03-01

From the point of view of a physicist, a bio-molecular motor represents an interesting non-equilibrium system and it is directly amenable to an analysis using standard methods of non-equilibrium statistical physics. We conduct a rigorous Monte Carlo study of three different driven lattice gas models that retain the basic behavior of three types of cytoskeletal molecular motors. Our models incorporate novel features such as realistic dynamics rules and complex motor-motor interactions. We are interested to have a deeper understanding of how various parameters influence the macroscopic behavior of these systems, what is the density profile and if the system undergoes a phase transition. On the analytical front, we computed the steady-state probability distributions exactly for the one of the models using the matrix method that was established in 1993 by B. Derrida et al. We also explored the possibilities offered by the ``Bethe ansatz'' method by mapping some well studied spin models into asymmetric simple exclusion models (already analyzed using computer simulations), and to use the results obtained for the spin models in finding an exact solution for our problem. We have exhaustive computational studies of the kinesin and dynein molecular motor models that prove to be very useful in checking our analytical work.

Molecular graph convolutions: moving beyond fingerprints

PubMed Central

Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick

2016-01-01

Molecular “fingerprints” encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph—atoms, bonds, distances, etc.—which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement. PMID:27558503

Quantum mechanical/molecular mechanical/continuum style solvation model: time-dependent density functional theory.

PubMed

Thellamurege, Nandun M; Cui, Fengchao; Li, Hui

2013-08-28

A combined quantum mechanical/molecular mechanical/continuum (QM/MMpol/C) style method is developed for time-dependent density functional theory (TDDFT, including long-range corrected TDDFT) method, induced dipole polarizable force field, and induced surface charge continuum model. Induced dipoles and induced charges are included in the TDDFT equations to solve for the transition energies, relaxed density, and transition density. Analytic gradient is derived and implemented for geometry optimization and molecular dynamics simulation. QM/MMpol/C style DFT and TDDFT methods are used to study the hydrogen bonding of the photoactive yellow protein chromopore in ground state and excited state.

Interaction of methotrexate with trypsin analyzed by spectroscopic and molecular modeling methods

NASA Astrophysics Data System (ADS)

Wang, Yanqing; Zhang, Hongmei; Cao, Jian; Zhou, Qiuhua

2013-11-01

Trypsin is one of important digestive enzymes that have intimate correlation with human health and illness. In this work, the interaction of trypsin with methotrexate was investigated by spectroscopic and molecular modeling methods. The results revealed that methotrexate could interact with trypsin with about one binding site. Methotrexate molecule could enter into the primary substrate-binding pocket, resulting in inhibition of trypsin activity. Furthermore, the thermodynamic analysis implied that electrostatic force, hydrogen bonding, van der Waals and hydrophobic interactions were the main interactions for stabilizing the trypsin-methotrexate system, which agreed well with the results from the molecular modeling study.

Bond-valence methods for pKa prediction. II. Bond-valence, electrostatic, molecular geometry, and solvation effects

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

Bickmore, Barry R.; Rosso, Kevin M.; Tadanier, Christopher J.

2006-08-15

In a previous contribution, we outlined a method for predicting (hydr)oxy-acid and oxide surface acidity constants based on three main factors: bond valence, Me?O bond ionicity, and molecular shape. Here electrostatics calculations and ab initio molecular dynamics simulations are used to qualitatively show that Me?O bond ionicity controls the extent to which the electrostatic work of proton removal departs from ideality, bond valence controls the extent of solvation of individual functional groups, and bond valence and molecular shape controls local dielectric response. These results are consistent with our model of acidity, but completely at odds with other methods of predictingmore » acidity constants for use in multisite complexation models. In particular, our ab initio molecular dynamics simulations of solvated monomers clearly indicate that hydrogen bonding between (hydr)oxo-groups and water molecules adjusts to obey the valence sum rule, rather than maintaining a fixed valence based on the coordination of the oxygen atom as predicted by the standard MUSIC model.« less

Using Molecular Modeling in Teaching Group Theory Analysis of the Infrared Spectra of Organometallic Compounds

ERIC Educational Resources Information Center

Wang, Lihua

2012-01-01

A new method is introduced for teaching group theory analysis of the infrared spectra of organometallic compounds using molecular modeling. The main focus of this method is to enhance student understanding of the symmetry properties of vibrational modes and of the group theory analysis of infrared (IR) spectra by using visual aids provided by…

Peridynamic Multiscale Finite Element Methods

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

Costa, Timothy; Bond, Stephen D.; Littlewood, David John

The problem of computing quantum-accurate design-scale solutions to mechanics problems is rich with applications and serves as the background to modern multiscale science research. The prob- lem can be broken into component problems comprised of communicating across adjacent scales, which when strung together create a pipeline for information to travel from quantum scales to design scales. Traditionally, this involves connections between a) quantum electronic structure calculations and molecular dynamics and between b) molecular dynamics and local partial differ- ential equation models at the design scale. The second step, b), is particularly challenging since the appropriate scales of molecular dynamic andmore » local partial differential equation models do not overlap. The peridynamic model for continuum mechanics provides an advantage in this endeavor, as the basic equations of peridynamics are valid at a wide range of scales limiting from the classical partial differential equation models valid at the design scale to the scale of molecular dynamics. In this work we focus on the development of multiscale finite element methods for the peridynamic model, in an effort to create a mathematically consistent channel for microscale information to travel from the upper limits of the molecular dynamics scale to the design scale. In particular, we first develop a Nonlocal Multiscale Finite Element Method which solves the peridynamic model at multiple scales to include microscale information at the coarse-scale. We then consider a method that solves a fine-scale peridynamic model to build element-support basis functions for a coarse- scale local partial differential equation model, called the Mixed Locality Multiscale Finite Element Method. Given decades of research and development into finite element codes for the local partial differential equation models of continuum mechanics there is a strong desire to couple local and nonlocal models to leverage the speed and state of the art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.« less

The Use of Molecular Modeling as "Pseudoexperimental" Data for Teaching VSEPR as a Hands-On General Chemistry Activity

ERIC Educational Resources Information Center

Martin, Christopher B.; Vandehoef, Crissie; Cook, Allison

2015-01-01

A hands-on activity appropriate for first-semester general chemistry students is presented that combines traditional VSEPR methods of predicting molecular geometries with introductory use of molecular modeling. Students analyze a series of previously calculated output files consisting of several molecules each in various geometries. Each structure…

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.

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

Semi-Automated Curation Allows Causal Network Model Building for the Quantification of Age-Dependent Plaque Progression in ApoE-/- Mouse.

PubMed

Szostak, Justyna; Martin, Florian; Talikka, Marja; Peitsch, Manuel C; Hoeng, Julia

2016-01-01

The cellular and molecular mechanisms behind the process of atherosclerotic plaque destabilization are complex, and molecular data from aortic plaques are difficult to interpret. Biological network models may overcome these difficulties and precisely quantify the molecular mechanisms impacted during disease progression. The atherosclerosis plaque destabilization biological network model was constructed with the semiautomated curation pipeline, BELIEF. Cellular and molecular mechanisms promoting plaque destabilization or rupture were captured in the network model. Public transcriptomic data sets were used to demonstrate the specificity of the network model and to capture the different mechanisms that were impacted in ApoE -/- mouse aorta at 6 and 32 weeks. We concluded that network models combined with the network perturbation amplitude algorithm provide a sensitive, quantitative method to follow disease progression at the molecular level. This approach can be used to investigate and quantify molecular mechanisms during plaque progression.

Coarse-Grained Structural Modeling of Molecular Motors Using Multibody Dynamics

PubMed Central

Parker, David; Bryant, Zev; Delp, Scott L.

2010-01-01

Experimental and computational approaches are needed to uncover the mechanisms by which molecular motors convert chemical energy into mechanical work. In this article, we describe methods and software to generate structurally realistic models of molecular motor conformations compatible with experimental data from different sources. Coarse-grained models of molecular structures are constructed by combining groups of atoms into a system of rigid bodies connected by joints. Contacts between rigid bodies enforce excluded volume constraints, and spring potentials model system elasticity. This simplified representation allows the conformations of complex molecular motors to be simulated interactively, providing a tool for hypothesis building and quantitative comparisons between models and experiments. In an example calculation, we have used the software to construct atomically detailed models of the myosin V molecular motor bound to its actin track. The software is available at www.simtk.org. PMID:20428469

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

McLaughlin, E.; Gupta, S.

This project mainly involves a molecular dynamics and Monte Carlo study of the effect of molecular shape on thermophysical properties of bulk fluids with an emphasis on the aromatic hydrocarbon liquids. In this regard we have studied the modeling, simulation methodologies, and predictive and correlating methods for thermodynamic properties of fluids of nonspherical molecules. In connection with modeling we have studied the use of anisotropic site-site potentials, through a modification of the Gay-Berne Gaussian overlap potential, to successfully model the aromatic rings after adding the necessary electrostatic moments. We have also shown these interaction sites should be located at themore » geometric centers of the chemical groups. In connection with predictive methods, we have shown two perturbation type theories to work well for fluids modeled using one-center anisotropic potentials and the possibility exists for extending these to anisotropic site-site models. In connection with correlation methods, we have studied, through simulations, the effect of molecular shape on the attraction term in the generalized van der Waals equation of state for fluids of nonspherical molecules and proposed a possible form which is to be studied further. We have successfully studied the vector and parallel processing aspects of molecular simulations for fluids of nonspherical molecules.« less

Molecular activity prediction by means of supervised subspace projection based ensembles of classifiers.

PubMed

Cerruela García, G; García-Pedrajas, N; Luque Ruiz, I; Gómez-Nieto, M Á

2018-03-01

This paper proposes a method for molecular activity prediction in QSAR studies using ensembles of classifiers constructed by means of two supervised subspace projection methods, namely nonparametric discriminant analysis (NDA) and hybrid discriminant analysis (HDA). We studied the performance of the proposed ensembles compared to classical ensemble methods using four molecular datasets and eight different models for the representation of the molecular structure. Using several measures and statistical tests for classifier comparison, we observe that our proposal improves the classification results with respect to classical ensemble methods. Therefore, we show that ensembles constructed using supervised subspace projections offer an effective way of creating classifiers in cheminformatics.

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.

System and methods for predicting transmembrane domains in membrane proteins and mining the genome for recognizing G-protein coupled receptors

DOEpatents

Trabanino, Rene J; Vaidehi, Nagarajan; Hall, Spencer E; Goddard, William A; Floriano, Wely

2013-02-05

The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.

Treatment of atomic and molecular line blanketing by opacity sampling

NASA Technical Reports Server (NTRS)

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

1976-01-01

A sampling technique for treating the radiative opacity of large numbers of atomic and molecular lines in cool stellar atmospheres is subjected to several tests. In this opacity sampling (OS) technique, the global opacity is sampled at only a selected set of frequencies, and at each of these frequencies the total monochromatic opacity is obtained by summing the contribution of every relevant atomic and molecular line. In accord with previous results, we find that the structure of atmospheric models is accurately fixed by the use of 1000 frequency points, and 100 frequency points are adequate for many purposes. The effects of atomic and molecular lines are separately studied. A test model computed using the OS method agrees very well with a model having identical atmospheric parameters, but computed with the giant line (opacity distribution function) method.

Molecular Weight and Molecular Weight Distributions in Synthetic Polymers.

ERIC Educational Resources Information Center

Ward, Thomas Carl

1981-01-01

Focuses on molecular weight and molecular weight distributions (MWD) and models for predicting MWD in a pedagogical way. In addition, instrumental methods used to characterize MWD are reviewed with emphasis on physical chemistry of each, including end-group determination, osmometry, light scattering, solution viscosity, fractionation, and…

Implementing a modeling software for animated protein-complex interactions using a physics simulation library.

PubMed

Ueno, Yutaka; Ito, Shuntaro; Konagaya, Akihiko

2014-12-01

To better understand the behaviors and structural dynamics of proteins within a cell, novel software tools are being developed that can create molecular animations based on the findings of structural biology. This study proposes our method developed based on our prototypes to detect collisions and examine the soft-body dynamics of molecular models. The code was implemented with a software development toolkit for rigid-body dynamics simulation and a three-dimensional graphics library. The essential functions of the target software system included the basic molecular modeling environment, collision detection in the molecular models, and physical simulations of the movement of the model. Taking advantage of recent software technologies such as physics simulation modules and interpreted scripting language, the functions required for accurate and meaningful molecular animation were implemented efficiently.

Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β

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

Li, Xiaolin; Ye, Li; Wang, Xiaoxiang

2012-12-15

Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q{sup 2}) was 0.571 andmore » non-cross-validation correlation coefficient (r{sup 2}) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results. -- Highlights: ► The thyroid hormone activities of HO-PBDEs were studied by 3D-QSAR. ► The binding modes between HO-PBDEs and TRβ were explored. ► 3D-QSAR, molecular docking, and molecular dynamics (MD) methods were performed.« less

Quantitative structure-retention relationship models for the prediction of the reversed-phase HPLC gradient retention based on the heuristic method and support vector machine.

PubMed

Du, Hongying; Wang, Jie; Yao, Xiaojun; Hu, Zhide

2009-01-01

The heuristic method (HM) and support vector machine (SVM) were used to construct quantitative structure-retention relationship models by a series of compounds to predict the gradient retention times of reversed-phase high-performance liquid chromatography (HPLC) in three different columns. The aims of this investigation were to predict the retention times of multifarious compounds, to find the main properties of the three columns, and to indicate the theory of separation procedures. In our method, we correlated the retention times of many diverse structural analytes in three columns (Symmetry C18, Chromolith, and SG-MIX) with their representative molecular descriptors, calculated from the molecular structures alone. HM was used to select the most important molecular descriptors and build linear regression models. Furthermore, non-linear regression models were built using the SVM method; the performance of the SVM models were better than that of the HM models, and the prediction results were in good agreement with the experimental values. This paper could give some insights into the factors that were likely to govern the gradient retention process of the three investigated HPLC columns, which could theoretically supervise the practical experiment.

Teaching macromolecular modeling.

PubMed Central

Harvey, S C; Tan, R K

1992-01-01

Training newcomers to the field of macromolecular modeling is as difficult as is training beginners in x-ray crystallography, nuclear magnetic resonance, or other methods in structural biology. In one or two lectures, the most that can be conveyed is a general sense of the relationship between modeling and other structural methods. If a full semester is available, then students can be taught how molecular structures are built, manipulated, refined, and analyzed on a computer. Here we describe a one-semester modeling course that combines lectures, discussions, and a laboratory using a commercial modeling package. In the laboratory, students carry out prescribed exercises that are coordinated to the lectures, and they complete a term project on a modeling problem of their choice. The goal is to give students an understanding of what kinds of problems can be attacked by molecular modeling methods and which problems are beyond the current capabilities of those methods. PMID:1489919

Geochemical Reaction Mechanism Discovery from Molecular Simulation

DOE PAGES

Stack, Andrew G.; Kent, Paul R. C.

2014-11-10

Methods to explore reactions using computer simulation are becoming increasingly quantitative, versatile, and robust. In this review, a rationale for how molecular simulation can help build better geochemical kinetics models is first given. We summarize some common methods that geochemists use to simulate reaction mechanisms, specifically classical molecular dynamics and quantum chemical methods and discuss their strengths and weaknesses. Useful tools such as umbrella sampling and metadynamics that enable one to explore reactions are discussed. Several case studies wherein geochemists have used these tools to understand reaction mechanisms are presented, including water exchange and sorption on aqueous species and mineralmore » surfaces, surface charging, crystal growth and dissolution, and electron transfer. The impact that molecular simulation has had on our understanding of geochemical reactivity are highlighted in each case. In the future, it is anticipated that molecular simulation of geochemical reaction mechanisms will become more commonplace as a tool to validate and interpret experimental data, and provide a check on the plausibility of geochemical kinetic models.« less

Study of homogeneous bubble nucleation in liquid carbon dioxide by a hybrid approach combining molecular dynamics simulation and density gradient theory

NASA Astrophysics Data System (ADS)

Langenbach, K.; Heilig, M.; Horsch, M.; Hasse, H.

2018-03-01

A new method for predicting homogeneous bubble nucleation rates of pure compounds from vapor-liquid equilibrium (VLE) data is presented. It combines molecular dynamics simulation on the one side with density gradient theory using an equation of state (EOS) on the other. The new method is applied here to predict bubble nucleation rates in metastable liquid carbon dioxide (CO2). The molecular model of CO2 is taken from previous work of our group. PC-SAFT is used as an EOS. The consistency between the molecular model and the EOS is achieved by adjusting the PC-SAFT parameters to VLE data obtained from the molecular model. The influence parameter of density gradient theory is fitted to the surface tension of the molecular model. Massively parallel molecular dynamics simulations are performed close to the spinodal to compute bubble nucleation rates. From these simulations, the kinetic prefactor of the hybrid nucleation theory is estimated, whereas the nucleation barrier is calculated from density gradient theory. This enables the extrapolation of molecular simulation data to the whole metastable range including technically relevant densities. The results are tested against available experimental data and found to be in good agreement. The new method does not suffer from typical deficiencies of classical nucleation theory concerning the thermodynamic barrier at the spinodal and the bubble size dependence of surface tension, which is typically neglected in classical nucleation theory. In addition, the density in the center of critical bubbles and their surface tension is determined as a function of their radius. The usual linear Tolman correction to the capillarity approximation is found to be invalid.

Study of homogeneous bubble nucleation in liquid carbon dioxide by a hybrid approach combining molecular dynamics simulation and density gradient theory.

PubMed

Langenbach, K; Heilig, M; Horsch, M; Hasse, H

2018-03-28

A new method for predicting homogeneous bubble nucleation rates of pure compounds from vapor-liquid equilibrium (VLE) data is presented. It combines molecular dynamics simulation on the one side with density gradient theory using an equation of state (EOS) on the other. The new method is applied here to predict bubble nucleation rates in metastable liquid carbon dioxide (CO 2 ). The molecular model of CO 2 is taken from previous work of our group. PC-SAFT is used as an EOS. The consistency between the molecular model and the EOS is achieved by adjusting the PC-SAFT parameters to VLE data obtained from the molecular model. The influence parameter of density gradient theory is fitted to the surface tension of the molecular model. Massively parallel molecular dynamics simulations are performed close to the spinodal to compute bubble nucleation rates. From these simulations, the kinetic prefactor of the hybrid nucleation theory is estimated, whereas the nucleation barrier is calculated from density gradient theory. This enables the extrapolation of molecular simulation data to the whole metastable range including technically relevant densities. The results are tested against available experimental data and found to be in good agreement. The new method does not suffer from typical deficiencies of classical nucleation theory concerning the thermodynamic barrier at the spinodal and the bubble size dependence of surface tension, which is typically neglected in classical nucleation theory. In addition, the density in the center of critical bubbles and their surface tension is determined as a function of their radius. The usual linear Tolman correction to the capillarity approximation is found to be invalid.

Turbulence in molecular clouds - A new diagnostic tool to probe their origin

NASA Technical Reports Server (NTRS)

Canuto, V. M.; Battaglia, A.

1985-01-01

A method is presented to uncover the instability responsible for the type of turbulence observed in molecular clouds and the value of the physical parameters of the 'placental medium' from which turbulence originated. The method utilizes the observational relation between velocities and sizes of molecular clouds, together with a recent model for large-scale turbulence (constructed by Canuto and Goldman, 1985).

Evaluation of Contamination Inspection and Analysis Methods through Modeling System Performance

NASA Technical Reports Server (NTRS)

Seasly, Elaine; Dever, Jason; Stuban, Steven M. F.

2016-01-01

Contamination is usually identified as a risk on the risk register for sensitive space systems hardware. Despite detailed, time-consuming, and costly contamination control efforts during assembly, integration, and test of space systems, contaminants are still found during visual inspections of hardware. Improved methods are needed to gather information during systems integration to catch potential contamination issues earlier and manage contamination risks better. This research explores evaluation of contamination inspection and analysis methods to determine optical system sensitivity to minimum detectable molecular contamination levels based on IEST-STD-CC1246E non-volatile residue (NVR) cleanliness levels. Potential future degradation of the system is modeled given chosen modules representative of optical elements in an optical system, minimum detectable molecular contamination levels for a chosen inspection and analysis method, and determining the effect of contamination on the system. By modeling system performance based on when molecular contamination is detected during systems integration and at what cleanliness level, the decision maker can perform trades amongst different inspection and analysis methods and determine if a planned method is adequate to meet system requirements and manage contamination risk.

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

PubMed Central

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations. PMID:25999313

SIMPLE METHOD FOR THE REPRESENTATION, QUANTIFICATION, AND COMPARISON OF THE VOLUMES AND SHAPES OF CHEMICAL COMPOUNDS

EPA Science Inventory

A conceptually and computationally simple method for the definition, display, quantification, and comparison of the shapes of three-dimensional mathematical molecular models is presented. Molecular or solvent-accessible volume and surface area can also be calculated. Algorithms, ...

Coarse-grained molecular dynamics simulations for giant protein-DNA complexes

NASA Astrophysics Data System (ADS)

Takada, Shoji

Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.

Exploring the site-selective binding of jatrorrhizine to human serum albumin: spectroscopic and molecular modeling approaches.

PubMed

Mi, Ran; Hu, Yan-Jun; Fan, Xiao-Yang; Ouyang, Yu; Bai, Ai-Min

2014-01-03

This paper exploring the site-selective binding of jatrorrhizine to human serum albumin (HSA) under physiological conditions (pH=7.4). The investigation was carried out using fluorescence spectroscopy, UV-vis spectroscopy, and molecular modeling. The results of fluorescence quenching and UV-vis absorption spectra experiments indicated the formation of the complex of HSA-jatrorrhizine. Binding parameters calculating from Stern-Volmer method and Scatchard method were calculated at 298, 304 and 310 K, with the corresponding thermodynamic parameters ΔG, ΔH and ΔS as well. Binding parameters calculating from Stern-Volmer method and Scatchard method showed that jatrorrhizine bind to HSA with the binding affinities of the order 10(4) L mol(-1). The thermodynamic parameters studies revealed that the binding was characterized by negative enthalpy and positive entropy changes and the electrostatic interactions play a major role for jatrorrhizine-HSA association. Site marker competitive displacement experiments and molecular modeling calculation demonstrating that jatrorrhizine is mainly located within the hydrophobic pocket of the subdomain IIIA of HSA. Furthermore, the synchronous fluorescence spectra suggested that the association between jatrorrhizine and HSA changed molecular conformation of HSA. Copyright © 2013. Published by Elsevier B.V.

Combined Monte Carlo/torsion-angle molecular dynamics for ensemble modeling of proteins, nucleic acids and carbohydrates.

PubMed

Zhang, Weihong; Howell, Steven C; Wright, David W; Heindel, Andrew; Qiu, Xiangyun; Chen, Jianhan; Curtis, Joseph E

2017-05-01

We describe a general method to use Monte Carlo simulation followed by torsion-angle molecular dynamics simulations to create ensembles of structures to model a wide variety of soft-matter biological systems. Our particular emphasis is focused on modeling low-resolution small-angle scattering and reflectivity structural data. We provide examples of this method applied to HIV-1 Gag protein and derived fragment proteins, TraI protein, linear B-DNA, a nucleosome core particle, and a glycosylated monoclonal antibody. This procedure will enable a large community of researchers to model low-resolution experimental data with greater accuracy by using robust physics based simulation and sampling methods which are a significant improvement over traditional methods used to interpret such data. Published by Elsevier Inc.

3D-QSAR, homology modeling, and molecular docking studies on spiropiperidines analogues as agonists of nociceptin/orphanin FQ receptor.

PubMed

Liu, Ming; He, Lin; Hu, Xiaopeng; Liu, Peiqing; Luo, Hai-Bin

2010-12-01

The nociceptin/orphanin FQ receptor (NOP) has been implicated in a wide range of biological functions, including pain, anxiety, depression and drug abuse. Especially, its agonists have a great potential to be developed into anxiolytics. However, the crystal structure of NOP is still not available. In the present work, both structure-based and ligand-based modeling methods have been used to achieve a comprehensive understanding on 67N-substituted spiropiperidine analogues as NOP agonists. The comparative molecular-field analysis method was performed to formulate a reasonable 3D-QSAR model (cross-validated coefficient q(2)=0.819 and conventional r(2)=0.950), whose robustness and predictability were further verified by leave-eight-out, Y-randomization, and external test-set validations. The excellent performance of CoMFA to the affinity differences among these compounds was attributed to the contributions of electrostatic/hydrogen-bonding and steric/hydrophobic interactions, which was supported by the Surflex-Dock and CDOCKER molecular-docking simulations based on the 3D model of NOP built by the homology modeling method. The CoMFA contour maps and the molecular docking simulations were integrated to propose a binding mode for the spiropiperidine analogues at the binding site of NOP. Copyright © 2010 Elsevier Ltd. All rights reserved.

Integrating a Smartphone and Molecular Modeling for Determining the Binding Constant and Stoichiometry Ratio of the Iron(II)-Phenanthroline Complex: An Activity for Analytical and Physical Chemistry Laboratories

ERIC Educational Resources Information Center

de Morais, Camilo de L. M.; Silva, Se´rgio R. B.; Vieira, Davi S.; Lima, Ka´ssio M. G.

2016-01-01

The binding constant and stoichiometry ratio for the formation of iron(II)-(1,10-phenanthroline) or iron(II)-o-phenanthroline complexes has been determined by a combination of a low-cost analytical method using a smartphone and a molecular modeling method as a laboratory experiment designed for analytical and physical chemistry courses. Intensity…

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.

In silico method for modelling metabolism and gene product expression at genome scale

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

Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem

2012-07-03

Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome andmore » transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.« less

Modeling hole transport in wet and dry DNA.

PubMed

Pavanello, Michele; Adamowicz, Ludwik; Volobuyev, Maksym; Mennucci, Benedetta

2010-04-08

We present a DFT/classical molecular dynamics model of DNA charge conductivity. The model involves a temperature-driven, hole-hopping charge transfer and includes the time-dependent nonequilibrium interaction of DNA with its molecular environment. We validate our method against a variety of hole transport experiments. The method predicts a significant hole-transfer slowdown of approximately 35% from dry to wet DNA with and without electric field bias. In addition, in agreement with experiments, it also predicts an insulating behavior of (GC)(N) oligomers for 40 < N < 1000, depending on the experimental setup.

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.

A self-consistent transport model for molecular conduction based on extended Hückel theory with full three-dimensional electrostatics

NASA Astrophysics Data System (ADS)

Zahid, F.; Paulsson, M.; Polizzi, E.; Ghosh, A. W.; Siddiqui, L.; Datta, S.

2005-08-01

We present a transport model for molecular conduction involving an extended Hückel theoretical treatment of the molecular chemistry combined with a nonequilibrium Green's function treatment of quantum transport. The self-consistent potential is approximated by CNDO (complete neglect of differential overlap) method and the electrostatic effects of metallic leads (bias and image charges) are included through a three-dimensional finite element method. This allows us to capture spatial details of the electrostatic potential profile, including effects of charging, screening, and complicated electrode configurations employing only a single adjustable parameter to locate the Fermi energy. As this model is based on semiempirical methods it is computationally inexpensive and flexible compared to ab initio models, yet at the same time it is able to capture salient qualitative features as well as several relevant quantitative details of transport. We apply our model to investigate recent experimental data on alkane dithiol molecules obtained in a nanopore setup. We also present a comparison study of single molecule transistors and identify electronic properties that control their performance.

Multiscale Modeling of Multiphase Fluid Flow

DTIC Science & Technology

2016-08-01

the disparate time and length scales involved in modeling fluid flow and heat transfer. Molecular dynamics simulations were carried out to provide a...fluid dynamics methods were used to investigate the heat transfer process in open-cell micro-foam with phase change material; enhancement of natural...Computational fluid dynamics, Heat transfer, Phase change material in Micro-foam, Molecular Dynamics, Multiphase flow, Multiscale modeling, Natural

Moving Beyond the Single Center--Ways to Reinforce Molecular Orbital Theory in an Inorganic Course

ERIC Educational Resources Information Center

Cass, Marion E.; Hollingsworth, William E.

2004-01-01

It is suggested that molecular theory should be taught earlier in the inorganic chemistry curriculum even in the introductory chemistry course in order to integrate molecular orbital arguments more effectively throughout the curriculum. The method of teaching relies on having access to molecular modeling software as having access to such software…

A theoretical-electron-density databank using a model of real and virtual spherical atoms.

PubMed

Nassour, Ayoub; Domagala, Slawomir; Guillot, Benoit; Leduc, Theo; Lecomte, Claude; Jelsch, Christian

2017-08-01

A database describing the electron density of common chemical groups using combinations of real and virtual spherical atoms is proposed, as an alternative to the multipolar atom modelling of the molecular charge density. Theoretical structure factors were computed from periodic density functional theory calculations on 38 crystal structures of small molecules and the charge density was subsequently refined using a density model based on real spherical atoms and additional dummy charges on the covalent bonds and on electron lone-pair sites. The electron-density parameters of real and dummy atoms present in a similar chemical environment were averaged on all the molecules studied to build a database of transferable spherical atoms. Compared with the now-popular databases of transferable multipolar parameters, the spherical charge modelling needs fewer parameters to describe the molecular electron density and can be more easily incorporated in molecular modelling software for the computation of electrostatic properties. The construction method of the database is described. In order to analyse to what extent this modelling method can be used to derive meaningful molecular properties, it has been applied to the urea molecule and to biotin/streptavidin, a protein/ligand complex.

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

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.

DEVELOPMENT OF A MODEL THAT CONTAINS BOTH MULTIPOLE MOMENTS AND GAUSSIANS FOR THE CALCULATION OF MOLECULAR ELECTROSTATIC POTENTIALS

EPA Science Inventory

The electrostatic interaction is a critical component of intermolecular interactions in biological processes. Rapid methods for the computation and characterization of the molecular electrostatic potential (MEP) that segment the molecular charge distribution and replace this cont...

Structural Refinement of Proteins by Restrained Molecular Dynamics Simulations with Non-interacting Molecular Fragments.

PubMed

Shen, Rong; Han, Wei; Fiorin, Giacomo; Islam, Shahidul M; Schulten, Klaus; Roux, Benoît

2015-10-01

The knowledge of multiple conformational states is a prerequisite to understand the function of membrane transport proteins. Unfortunately, the determination of detailed atomic structures for all these functionally important conformational states with conventional high-resolution approaches is often difficult and unsuccessful. In some cases, biophysical and biochemical approaches can provide important complementary structural information that can be exploited with the help of advanced computational methods to derive structural models of specific conformational states. In particular, functional and spectroscopic measurements in combination with site-directed mutations constitute one important source of information to obtain these mixed-resolution structural models. A very common problem with this strategy, however, is the difficulty to simultaneously integrate all the information from multiple independent experiments involving different mutations or chemical labels to derive a unique structural model consistent with the data. To resolve this issue, a novel restrained molecular dynamics structural refinement method is developed to simultaneously incorporate multiple experimentally determined constraints (e.g., engineered metal bridges or spin-labels), each treated as an individual molecular fragment with all atomic details. The internal structure of each of the molecular fragments is treated realistically, while there is no interaction between different molecular fragments to avoid unphysical steric clashes. The information from all the molecular fragments is exploited simultaneously to constrain the backbone to refine a three-dimensional model of the conformational state of the protein. The method is illustrated by refining the structure of the voltage-sensing domain (VSD) of the Kv1.2 potassium channel in the resting state and by exploring the distance histograms between spin-labels attached to T4 lysozyme. The resulting VSD structures are in good agreement with the consensus model of the resting state VSD and the spin-spin distance histograms from ESR/DEER experiments on T4 lysozyme are accurately reproduced.

Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model.

PubMed

Ni, Jingchao; Koyuturk, Mehmet; Tong, Hanghang; Haines, Jonathan; Xu, Rong; Zhang, Xiang

2016-11-10

Accurately prioritizing candidate disease genes is an important and challenging problem. Various network-based methods have been developed to predict potential disease genes by utilizing the disease similarity network and molecular networks such as protein interaction or gene co-expression networks. Although successful, a common limitation of the existing methods is that they assume all diseases share the same molecular network and a single generic molecular network is used to predict candidate genes for all diseases. However, different diseases tend to manifest in different tissues, and the molecular networks in different tissues are usually different. An ideal method should be able to incorporate tissue-specific molecular networks for different diseases. In this paper, we develop a robust and flexible method to integrate tissue-specific molecular networks for disease gene prioritization. Our method allows each disease to have its own tissue-specific network(s). We formulate the problem of candidate gene prioritization as an optimization problem based on network propagation. When there are multiple tissue-specific networks available for a disease, our method can automatically infer the relative importance of each tissue-specific network. Thus it is robust to the noisy and incomplete network data. To solve the optimization problem, we develop fast algorithms which have linear time complexities in the number of nodes in the molecular networks. We also provide rigorous theoretical foundations for our algorithms in terms of their optimality and convergence properties. Extensive experimental results show that our method can significantly improve the accuracy of candidate gene prioritization compared with the state-of-the-art methods. In our experiments, we compare our methods with 7 popular network-based disease gene prioritization algorithms on diseases from Online Mendelian Inheritance in Man (OMIM) database. The experimental results demonstrate that our methods recover true associations more accurately than other methods in terms of AUC values, and the performance differences are significant (with paired t-test p-values less than 0.05). This validates the importance to integrate tissue-specific molecular networks for studying disease gene prioritization and show the superiority of our network models and ranking algorithms toward this purpose. The source code and datasets are available at http://nijingchao.github.io/CRstar/ .

A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters: Theory and application to microfilaments

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

Li, Tong; Gu, YuanTong, E-mail: yuantong.gu@qut.edu.au

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grainedmore » level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.« less

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.

Exploring oxidative ageing behaviour of hydrocarbons using ab initio molecular dynamics analysis

NASA Astrophysics Data System (ADS)

Pan, Tongyan; Cheng, Cheng

2016-06-01

With a proper approximate solution to the Schrödinger Equation of a multi-electron system, the method of ab initio molecular dynamics (AIMD) performs first-principles molecular dynamics analysis without pre-defining interatomic potentials as are mandatory in traditional molecular dynamics analyses. The objective of this study is to determine the oxidative-ageing pathway of petroleum asphalt as a typical hydrocarbon system, using the AIMD method. This objective was accomplished in three steps, including (1) identifying a group of representative asphalt molecules to model, (2) determining an atomistic modelling method that can effectively simulate the production of critical functional groups in oxidative ageing of hydrocarbons and (3) evaluating the oxidative-ageing pathway of a hydrocarbon system. The determination of oxidative-ageing pathway of hydrocarbons was done by tracking the generations of critical functional groups in the course of oxidative ageing. The chemical elements of carbon, nitrogen and sulphur all experience oxidative reactions, producing polarised functional groups such as ketones, aldehydes or carboxylic acids, pyrrolic groups and sulphoxides. The electrostatic forces of the polarised groups generated in oxidation are responsible for the behaviour of aged hydrocarbons. The developed AIMD model can be used for modelling the ageing of generic hydrocarbon polymers and developing antioxidants without running expensive experiments.

Carbohydrate-protein interactions: molecular modeling insights.

PubMed

Pérez, Serge; Tvaroška, Igor

2014-01-01

The article reviews the significant contributions to, and the present status of, applications of computational methods for the characterization and prediction of protein-carbohydrate interactions. After a presentation of the specific features of carbohydrate modeling, along with a brief description of the experimental data and general features of carbohydrate-protein interactions, the survey provides a thorough coverage of the available computational methods and tools. At the quantum-mechanical level, the use of both molecular orbitals and density-functional theory is critically assessed. These are followed by a presentation and critical evaluation of the applications of semiempirical and empirical methods: QM/MM, molecular dynamics, free-energy calculations, metadynamics, molecular robotics, and others. The usefulness of molecular docking in structural glycobiology is evaluated by considering recent docking- validation studies on a range of protein targets. The range of applications of these theoretical methods provides insights into the structural, energetic, and mechanistic facets that occur in the course of the recognition processes. Selected examples are provided to exemplify the usefulness and the present limitations of these computational methods in their ability to assist in elucidation of the structural basis underlying the diverse function and biological roles of carbohydrates in their dialogue with proteins. These test cases cover the field of both carbohydrate biosynthesis and glycosyltransferases, as well as glycoside hydrolases. The phenomenon of (macro)molecular recognition is illustrated for the interactions of carbohydrates with such proteins as lectins, monoclonal antibodies, GAG-binding proteins, porins, and viruses. © 2014 Elsevier Inc. All rights reserved.

A Stochastic Mixing Model for Predicting Emissions in a Direct Injection Diesel Engine.

DTIC Science & Technology

1986-09-01

of chemical reactors. The fundamental concept of these models is coalescence/dis- persion micromixing . C1] Details of this method are provided in Appen...Togby,A.H., "Monte Carlo Methods of Simulating Micromixing in Chemical Reactors", Chemical Engineering Science, Vol.27, p.1 4 97, 1972. 46. Kattan,A...on a molecular level. 2. Micromixing or stream mixing refers to the mixing of particles on a molecular level. Until the coalescence and dispersion

Chemical insight from density functional modeling of molecular adsorption: Tracking the bonding and diffusion of anthracene derivatives on Cu(111) with molecular orbitals

NASA Astrophysics Data System (ADS)

Wyrick, Jonathan; Einstein, T. L.; Bartels, Ludwig

2015-03-01

We present a method of analyzing the results of density functional modeling of molecular adsorption in terms of an analogue of molecular orbitals. This approach permits intuitive chemical insight into the adsorption process. Applied to a set of anthracene derivates (anthracene, 9,10-anthraquinone, 9,10-dithioanthracene, and 9,10-diselenonanthracene), we follow the electronic states of the molecules that are involved in the bonding process and correlate them to both the molecular adsorption geometry and the species' diffusive behavior. We additionally provide computational code to easily repeat this analysis on any system.

Diffusion-Based Model for Synaptic Molecular Communication Channel.

PubMed

Khan, Tooba; Bilgin, Bilgesu A; Akan, Ozgur B

2017-06-01

Computational methods have been extensively used to understand the underlying dynamics of molecular communication methods employed by nature. One very effective and popular approach is to utilize a Monte Carlo simulation. Although it is very reliable, this method can have a very high computational cost, which in some cases renders the simulation impractical. Therefore, in this paper, for the special case of an excitatory synaptic molecular communication channel, we present a novel mathematical model for the diffusion and binding of neurotransmitters that takes into account the effects of synaptic geometry in 3-D space and re-absorption of neurotransmitters by the transmitting neuron. Based on this model we develop a fast deterministic algorithm, which calculates expected value of the output of this channel, namely, the amplitude of excitatory postsynaptic potential (EPSP), for given synaptic parameters. We validate our algorithm by a Monte Carlo simulation, which shows total agreement between the results of the two methods. Finally, we utilize our model to quantify the effects of variation in synaptic parameters, such as position of release site, receptor density, size of postsynaptic density, diffusion coefficient, uptake probability, and number of neurotransmitters in a vesicle, on maximum number of bound receptors that directly affect the peak amplitude of EPSP.

Quantum mechanical/molecular mechanical/continuum style solvation model: second order Møller-Plesset perturbation theory.

PubMed

Thellamurege, Nandun M; Si, Dejun; Cui, Fengchao; Li, Hui

2014-05-07

A combined quantum mechanical/molecular mechanical/continuum (QM/MM/C) style second order Møller-Plesset perturbation theory (MP2) method that incorporates induced dipole polarizable force field and induced surface charge continuum solvation model is established. The Z-vector method is modified to include induced dipoles and induced surface charges to determine the MP2 response density matrix, which can be used to evaluate MP2 properties. In particular, analytic nuclear gradient is derived and implemented for this method. Using the Assisted Model Building with Energy Refinement induced dipole polarizable protein force field, the QM/MM/C style MP2 method is used to study the hydrogen bonding distances and strengths of the photoactive yellow protein chromopore in the wild type and the Glu46Gln mutant.

Prioritization of in silico models and molecular descriptors for the assessment of ready biodegradability.

PubMed

Fernández, Alberto; Rallo, Robert; Giralt, Francesc

2015-10-01

Ready biodegradability is a key property for evaluating the long-term effects of chemicals on the environment and human health. As such, it is used as a screening test for the assessment of persistent, bioaccumulative and toxic substances. Regulators encourage the use of non-testing methods, such as in silico models, to save money and time. A dataset of 757 chemicals was collected to assess the performance of four freely available in silico models that predict ready biodegradability. They were applied to develop a new consensus method that prioritizes the use of each individual model according to its performance on chemical subsets driven by the presence or absence of different molecular descriptors. This consensus method was capable of almost eliminating unpredictable chemicals, while the performance of combined models was substantially improved with respect to that of the individual models. Copyright © 2015 Elsevier Inc. All rights reserved.

Generalized theoretical method for the interaction between arbitrary nonuniform electric field and molecular vibrations: Toward near-field infrared spectroscopy and microscopy

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

Iwasa, Takeshi, E-mail: tiwasa@mail.sci.hokudai.ac.jp; Takenaka, Masato; Taketsugu, Tetsuya

A theoretical method to compute infrared absorption spectra when a molecule is interacting with an arbitrary nonuniform electric field such as near-fields is developed and numerically applied to simple model systems. The method is based on the multipolar Hamiltonian where the light-matter interaction is described by a spatial integral of the inner product of the molecular polarization and applied electric field. The computation scheme is developed under the harmonic approximation for the molecular vibrations and the framework of modern electronic structure calculations such as the density functional theory. Infrared reflection absorption and near-field infrared absorption are considered as model systems.more » The obtained IR spectra successfully reflect the spatial structure of the applied electric field and corresponding vibrational modes, demonstrating applicability of the present method to analyze modern nanovibrational spectroscopy using near-fields. The present method can use arbitral electric fields and thus can integrate two fields such as computational chemistry and electromagnetics.« less

Generalized theoretical method for the interaction between arbitrary nonuniform electric field and molecular vibrations: Toward near-field infrared spectroscopy and microscopy.

PubMed

Iwasa, Takeshi; Takenaka, Masato; Taketsugu, Tetsuya

2016-03-28

A theoretical method to compute infrared absorption spectra when a molecule is interacting with an arbitrary nonuniform electric field such as near-fields is developed and numerically applied to simple model systems. The method is based on the multipolar Hamiltonian where the light-matter interaction is described by a spatial integral of the inner product of the molecular polarization and applied electric field. The computation scheme is developed under the harmonic approximation for the molecular vibrations and the framework of modern electronic structure calculations such as the density functional theory. Infrared reflection absorption and near-field infrared absorption are considered as model systems. The obtained IR spectra successfully reflect the spatial structure of the applied electric field and corresponding vibrational modes, demonstrating applicability of the present method to analyze modern nanovibrational spectroscopy using near-fields. The present method can use arbitral electric fields and thus can integrate two fields such as computational chemistry and electromagnetics.

Information engineering for molecular diagnostics.

PubMed Central

Sorace, J. M.; Ritondo, M.; Canfield, K.

1994-01-01

Clinical laboratories are beginning to apply the recent advances in molecular biology to the testing of patient samples. The emerging field of Molecular Diagnostics will require a new Molecular Diagnostics Laboratory Information System which handles the data types, samples and test methods found in this field. The system must be very flexible in regards to supporting ad-hoc queries. The requirements which are shaping the developments in this field are reviewed and a data model developed. Several queries which demonstrate the data models ability to support the information needs of this area have been developed and run. These results demonstrate the ability of the purposed data model to meet the current and projected needs of this rapidly expanding field. PMID:7949937

Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

PubMed

Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

2018-03-21

Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

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.

FDDO and DSMC analyses of rarefied gas flow through 2D nozzles

NASA Technical Reports Server (NTRS)

Chung, Chan-Hong; De Witt, Kenneth J.; Jeng, Duen-Ren; Penko, Paul F.

1992-01-01

Two different approaches, the finite-difference method coupled with the discrete-ordinate method (FDDO), and the direct-simulation Monte Carlo (DSMC) method, are used in the analysis of the flow of a rarefied gas expanding through a two-dimensional nozzle and into a surrounding low-density environment. In the FDDO analysis, by employing the discrete-ordinate method, the Boltzmann equation simplified by a model collision integral is transformed to a set of partial differential equations which are continuous in physical space but are point functions in molecular velocity space. The set of partial differential equations are solved by means of a finite-difference approximation. In the DSMC analysis, the variable hard sphere model is used as a molecular model and the no time counter method is employed as a collision sampling technique. The results of both the FDDO and the DSMC methods show good agreement. The FDDO method requires less computational effort than the DSMC method by factors of 10 to 40 in CPU time, depending on the degree of rarefaction.

Computer simulation and experimental study of the polysaccharide-polysaccharide interaction in the bacteria Azospirillum brasilense Sp245

NASA Astrophysics Data System (ADS)

Arefeva, Oksana A.; Kuznetsov, Pavel E.; Tolmachev, Sergey A.; Kupadze, Machammad S.; Khlebtsov, Boris N.; Rogacheva, Svetlana M.

2003-09-01

We have studied the conformational properties and molecular dynamics of polysaccharides by using molecular modeling methods. Theoretical and experimental results of polysaccharide-polysaccharide interactions are described.

Transitioning NWChem to the Next Generation of Manycore Machines

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

Bylaska, Eric J.; Apra, E; Kowalski, Karol

The NorthWest chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers [1-3]. It contains an umbrella of modules that today includes self-consistent eld (SCF), second order Møller-Plesset perturbation theory (MP2), coupled cluster (CC), multiconguration self-consistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real-time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics (AIMD), Car-Parrinello molecular dynamics (MD), classical MD, hybrid quantum mechanicsmore » molecular mechanics (QM/MM), hybrid ab initio molecular dynamics molecular mechanics (AIMD/MM), gauge independent atomic orbital nuclear magnetic resonance (GIAO NMR), conductor like screening solvation model (COSMO), conductor-like screening solvation model based on density (COSMO-SMD), and reference interaction site model (RISM) solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities [4]. Moreover, new capabilities continue to be added with each new release.« less

Molecular modelling studies on the ORL1-receptor and ORL1-agonists

NASA Astrophysics Data System (ADS)

Bröer, Britta M.; Gurrath, Marion; Höltje, Hans-Dieter

2003-11-01

The ORL1 ( opioid receptor like 1)- receptor is a member of the family of rhodopsin-like G protein-coupled receptors (GPCR) and represents an interesting new therapeutical target since it is involved in a variety of biomedical important processes, such as anxiety, nociception, feeding, and memory. In order to shed light on the molecular basis of the interactions of the GPCR with its ligands, the receptor protein and a dataset of specific agonists were examined using molecular modelling methods. For that purpose, the conformational space of a very potent non-peptide ORL1-receptor agonist (Ro 64-6198) with a small number of rotatable bonds was analysed in order to derive a pharmacophoric arrangement. The conformational analyses yielded a conformation that served as template for the superposition of a set of related analogues. Structural superposition was achieved by employing the program FlexS. Using the experimental binding data and the superposition of the ligands, a 3D-QSAR analysis applying the GRID/GOLPE method was carried out. After the ligand-based modelling approach, a 3D model of the ORL1-receptor has been constructed using homology modelling methods based on the crystal structure of bovine rhodopsin. A representative structure of the model taken from molecular dynamics simulations was used for a manual docking procedure. Asp-130 and Thr-305 within the ORL1-receptor model served as important hydrophilic interaction partners. Furthermore, a hydrophobic cavity was identified stabilizing the agonists within their binding site. The manual docking results were supported using FlexX, which identified the same protein-ligand interaction points.

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.

Modeling and enhanced sampling of molecular systems with smooth and nonlinear data-driven collective variables

NASA Astrophysics Data System (ADS)

Hashemian, Behrooz; Millán, Daniel; Arroyo, Marino

2013-12-01

Collective variables (CVs) are low-dimensional representations of the state of a complex system, which help us rationalize molecular conformations and sample free energy landscapes with molecular dynamics simulations. Given their importance, there is need for systematic methods that effectively identify CVs for complex systems. In recent years, nonlinear manifold learning has shown its ability to automatically characterize molecular collective behavior. Unfortunately, these methods fail to provide a differentiable function mapping high-dimensional configurations to their low-dimensional representation, as required in enhanced sampling methods. We introduce a methodology that, starting from an ensemble representative of molecular flexibility, builds smooth and nonlinear data-driven collective variables (SandCV) from the output of nonlinear manifold learning algorithms. We demonstrate the method with a standard benchmark molecule, alanine dipeptide, and show how it can be non-intrusively combined with off-the-shelf enhanced sampling methods, here the adaptive biasing force method. We illustrate how enhanced sampling simulations with SandCV can explore regions that were poorly sampled in the original molecular ensemble. We further explore the transferability of SandCV from a simpler system, alanine dipeptide in vacuum, to a more complex system, alanine dipeptide in explicit water.

Modeling and enhanced sampling of molecular systems with smooth and nonlinear data-driven collective variables.

PubMed

Hashemian, Behrooz; Millán, Daniel; Arroyo, Marino

2013-12-07

Collective variables (CVs) are low-dimensional representations of the state of a complex system, which help us rationalize molecular conformations and sample free energy landscapes with molecular dynamics simulations. Given their importance, there is need for systematic methods that effectively identify CVs for complex systems. In recent years, nonlinear manifold learning has shown its ability to automatically characterize molecular collective behavior. Unfortunately, these methods fail to provide a differentiable function mapping high-dimensional configurations to their low-dimensional representation, as required in enhanced sampling methods. We introduce a methodology that, starting from an ensemble representative of molecular flexibility, builds smooth and nonlinear data-driven collective variables (SandCV) from the output of nonlinear manifold learning algorithms. We demonstrate the method with a standard benchmark molecule, alanine dipeptide, and show how it can be non-intrusively combined with off-the-shelf enhanced sampling methods, here the adaptive biasing force method. We illustrate how enhanced sampling simulations with SandCV can explore regions that were poorly sampled in the original molecular ensemble. We further explore the transferability of SandCV from a simpler system, alanine dipeptide in vacuum, to a more complex system, alanine dipeptide in explicit water.

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.

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...

Assessment of PDF Micromixing Models Using DNS Data for a Two-Step Reaction

NASA Astrophysics Data System (ADS)

Tsai, Kuochen; Chakrabarti, Mitali; Fox, Rodney O.; Hill, James C.

1996-11-01

Although the probability density function (PDF) method is known to treat the chemical reaction terms exactly, its application to turbulent reacting flows have been overshadowed by the ability to model the molecular mixing terms satisfactorily. In this study, two PDF molecular mixing models, the linear-mean-square-estimation (LMSE or IEM) model and the generalized interaction-by-exchange-with-the-mean (GIEM) model, are compared with the DNS data in decaying turbulence with a two-step parallel-consecutive reaction and two segregated initial conditions: ``slabs" and ``blobs". Since the molecular mixing model is expected to have a strong effect on the mean values of chemical species under such initial conditions, the model evaluation is intended to answer the following questions: Can the PDF models predict the mean values of chemical species correctly with completely segregated initial conditions? (2) Is a single molecular mixing timescale sufficient for the PDF models to predict the mean values with different initial conditions? (3) Will the chemical reactions change the molecular mixing timescales of the reacting species enough to affect the accuracy of the model's prediction for the mean values of chemical species?

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.

Receptor Surface Models in the Classroom: Introducing Molecular Modeling to Students in a 3-D World

ERIC Educational Resources Information Center

Geldenhuys, Werner J.; Hayes, Michael; Van der Schyf, Cornelis J.; Allen, David D.; Malan, Sarel F.

2007-01-01

A simple, novel and generally applicable method to demonstrate structure-activity associations of a group of biologically interesting compounds in relation to receptor binding is described. This method is useful for undergraduates and graduate students in medicinal chemistry and computer modeling programs.

Towards structural models of molecular recognition in olfactory receptors.

PubMed

Afshar, M; Hubbard, R E; Demaille, J

1998-02-01

The G protein coupled receptors (GPCR) are an important class of proteins that act as signal transducers through the cytoplasmic membrane. Understanding the structure and activation mechanism of these proteins is crucial for understanding many different aspects of cellular signalling. The olfactory receptors correspond to the largest family of GPCRs. Very little is known about how the structures of the receptors govern the specificity of interaction which enables identification of particular odorant molecules. In this paper, we review recent developments in two areas of molecular modelling: methods for modelling the configuration of trans-membrane helices and methods for automatic docking of ligands into receptor structures. We then show how a subset of these methods can be combined to construct a model of a rat odorant receptor interacting with lyral for which experimental data are available. This modelling can help us make progress towards elucidating the specificity of interactions between receptors and odorant molecules.

Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications

PubMed Central

2016-01-01

Semiempirical (SE) methods can be derived from either Hartree–Fock or density functional theory by applying systematic approximations, leading to efficient computational schemes that are several orders of magnitude faster than ab initio calculations. Such numerical efficiency, in combination with modern computational facilities and linear scaling algorithms, allows application of SE methods to very large molecular systems with extensive conformational sampling. To reliably model the structure, dynamics, and reactivity of biological and other soft matter systems, however, good accuracy for the description of noncovalent interactions is required. In this review, we analyze popular SE approaches in terms of their ability to model noncovalent interactions, especially in the context of describing biomolecules, water solution, and organic materials. We discuss the most significant errors and proposed correction schemes, and we review their performance using standard test sets of molecular systems for quantum chemical methods and several recent applications. The general goal is to highlight both the value and limitations of SE methods and stimulate further developments that allow them to effectively complement ab initio methods in the analysis of complex molecular systems. PMID:27074247

Quantum mechanical/molecular mechanical/continuum style solvation model: Second order Møller-Plesset perturbation theory

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

Thellamurege, Nandun M.; Si, Dejun; Cui, Fengchao

A combined quantum mechanical/molecular mechanical/continuum (QM/MM/C) style second order Møller-Plesset perturbation theory (MP2) method that incorporates induced dipole polarizable force field and induced surface charge continuum solvation model is established. The Z-vector method is modified to include induced dipoles and induced surface charges to determine the MP2 response density matrix, which can be used to evaluate MP2 properties. In particular, analytic nuclear gradient is derived and implemented for this method. Using the Assisted Model Building with Energy Refinement induced dipole polarizable protein force field, the QM/MM/C style MP2 method is used to study the hydrogen bonding distances and strengths ofmore » the photoactive yellow protein chromopore in the wild type and the Glu46Gln mutant.« less

The anesthetic action of some polyhalogenated ethers-Monte Carlo method based QSAR study.

PubMed

Golubović, Mlađan; Lazarević, Milan; Zlatanović, Dragan; Krtinić, Dane; Stoičkov, Viktor; Mladenović, Bojan; Milić, Dragan J; Sokolović, Dušan; Veselinović, Aleksandar M

2018-04-13

Up to this date, there has been an ongoing debate about the mode of action of general anesthetics, which have postulated many biological sites as targets for their action. However, postoperative nausea and vomiting are common problems in which inhalational agents may have a role in their development. When a mode of action is unknown, QSAR modelling is essential in drug development. To investigate the aspects of their anesthetic, QSAR models based on the Monte Carlo method were developed for a set of polyhalogenated ethers. Until now, their anesthetic action has not been completely defined, although some hypotheses have been suggested. Therefore, a QSAR model should be developed on molecular fragments that contribute to anesthetic action. QSAR models were built on the basis of optimal molecular descriptors based on the SMILES notation and local graph invariants, whereas the Monte Carlo optimization method with three random splits into the training and test set was applied for model development. Different methods, including novel Index of ideality correlation, were applied for the determination of the robustness of the model and its predictive potential. The Monte Carlo optimization process was capable of being an efficient in silico tool for building up a robust model of good statistical quality. Molecular fragments which have both positive and negative influence on anesthetic action were determined. The presented study can be useful in the search for novel anesthetics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Efficient approach to include molecular polarizations using charge and atom dipole response kernels to calculate free energy gradients in the QM/MM scheme.

PubMed

Asada, Toshio; Ando, Kanta; Sakurai, Koji; Koseki, Shiro; Nagaoka, Masataka

2015-10-28

An efficient approach to evaluate free energy gradients (FEGs) within the quantum mechanical/molecular mechanical (QM/MM) framework has been proposed to clarify reaction processes on the free energy surface (FES) in molecular assemblies. The method is based on response kernel approximations denoted as the charge and the atom dipole response kernel (CDRK) model that include explicitly induced atom dipoles. The CDRK model was able to reproduce polarization effects for both electrostatic interactions between QM and MM regions and internal energies in the QM region obtained by conventional QM/MM methods. In contrast to charge response kernel (CRK) models, CDRK models could be applied to various kinds of molecules, even linear or planer molecules, without using imaginary interaction sites. Use of the CDRK model enabled us to obtain FEGs on QM atoms in significantly reduced computational time. It was also clearly demonstrated that the time development of QM forces of the solvated propylene carbonate radical cation (PC˙(+)) provided reliable results for 1 ns molecular dynamics (MD) simulation, which were quantitatively in good agreement with expensive QM/MM results. Using FEG and nudged elastic band (NEB) methods, we found two optimized reaction paths on the FES for decomposition reactions to generate CO2 molecules from PC˙(+), whose reaction is known as one of the degradation mechanisms in the lithium-ion battery. Two of these reactions proceed through an identical intermediate structure whose molecular dipole moment is larger than that of the reactant to be stabilized in the solvent, which has a high relative dielectric constant. Thus, in order to prevent decomposition reactions, PC˙(+) should be modified to have a smaller dipole moment along two reaction paths.

Molecular structure and the EPR calculation of the gas phase succinonitrile molecule

NASA Astrophysics Data System (ADS)

Kepceoǧlu, A.; Kılıç, H. Ş.; Dereli, Ö.

2017-02-01

Succinonitrile (i.e. butanedinitrile) is a colorless nitrile compound that can be used in the gel polymer batteries as a solid-state solvent electrolytes and has a plastic crystal structure. Prior to the molecular structure calculation of the succinonitrile molecule, the conformer analysis were calculated by using semi empirical method PM3 core type Hamiltonian and eight different conformer structures were determined. Molecular structure with energy related properties of these conformers having the lowest energy was calculated by using DFT (B3LYP) methods with 6-311++G(d,p) basis set. Possible radicals, can be formed experimentally, were modeled in this study. EPR parameters of these model radicals were calculated and then compared with that obtained experimentally.

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

Modeling Aromatic Liquids:  Toluene, Phenol, and Pyridine.

PubMed

Baker, Christopher M; Grant, Guy H

2007-03-01

Aromatic groups are now acknowledged to play an important role in many systems of interest. However, existing molecular mechanics methods provide a poor representation of these groups. In a previous paper, we have shown that the molecular mechanics treatment of benzene can be improved by the incorporation of an explicit representation of the aromatic π electrons. Here, we develop this concept further, developing charge-separation models for toluene, phenol, and pyridine. Monte Carlo simulations are used to parametrize the models, via the reproduction of experimental thermodynamic data, and our models are shown to outperform an existing atom-centered model. The models are then used to make predictions about the structures of the liquids at the molecular level and are tested further through their application to the modeling of gas-phase dimers and cation-π interactions.

An Efficient Variable Screening Method for Effective Surrogate Models for Reliability-Based Design Optimization

DTIC Science & Technology

2014-04-01

surrogate model generation is difficult for high -dimensional problems, due to the curse of dimensionality. Variable screening methods have been...a variable screening model was developed for the quasi-molecular treatment of ion-atom collision [16]. In engineering, a confidence interval of...for high -level radioactive waste [18]. Moreover, the design sensitivity method can be extended to the variable screening method because vital

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.

Quantitative ultrasound molecular imaging by modeling the binding kinetics of targeted contrast agent

NASA Astrophysics Data System (ADS)

Turco, Simona; Tardy, Isabelle; Frinking, Peter; Wijkstra, Hessel; Mischi, Massimo

2017-03-01

Ultrasound molecular imaging (USMI) is an emerging technique to monitor diseases at the molecular level by the use of novel targeted ultrasound contrast agents (tUCA). These consist of microbubbles functionalized with targeting ligands with high-affinity for molecular markers of specific disease processes, such as cancer-related angiogenesis. Among the molecular markers of angiogenesis, the vascular endothelial growth factor receptor 2 (VEGFR2) is recognized to play a major role. In response, the clinical-grade tUCA BR55 was recently developed, consisting of VEGFR2-targeting microbubbles which can flow through the entire circulation and accumulate where VEGFR2 is over-expressed, thus causing selective enhancement in areas of active angiogenesis. Discrimination between bound and free microbubbles is crucial to assess cancer angiogenesis. Currently, this is done non-quantitatively by looking at the late enhancement, about 10 min after injection, or by calculation of the differential targeted enhancement, requiring the application of a high-pressure ultrasound (US) burst to destroy all the microbubbles in the acoustic field and isolate the signal coming only from bound microbubbles. In this work, we propose a novel method based on mathematical modeling of the binding kinetics during the tUCA first pass, thus reducing the acquisition time and with no need for a destructive US burst. Fitting time-intensity curves measured with USMI by the proposed model enables the assessment of cancer angiogenesis at both the vascular and molecular levels. This is achieved by estimation of quantitative parameters related to the microvascular architecture and microbubble binding. The proposed method was tested in 11 prostate-tumor bearing rats by performing USMI after injection of BR55, and showed good agreement with current USMI methods. The novel information provided by the proposed method, possibly combined with the current non-quantitative methods, may bring deeper insight into cancer angiogenesis, and thus potentially improve cancer diagnosis and management.

Multipole correction of atomic monopole models of molecular charge distribution. I. Peptides

NASA Technical Reports Server (NTRS)

Sokalski, W. A.; Keller, D. A.; Ornstein, R. L.; Rein, R.

1993-01-01

The defects in atomic monopole models of molecular charge distribution have been analyzed for several model-blocked peptides and compared with accurate quantum chemical values. The results indicate that the angular characteristics of the molecular electrostatic potential around functional groups capable of forming hydrogen bonds can be considerably distorted within various models relying upon isotropic atomic charges only. It is shown that these defects can be corrected by augmenting the atomic point charge models by cumulative atomic multipole moments (CAMMs). Alternatively, sets of off-center atomic point charges could be automatically derived from respective multipoles, providing approximately equivalent corrections. For the first time, correlated atomic multipoles have been calculated for N-acetyl, N'-methylamide-blocked derivatives of glycine, alanine, cysteine, threonine, leucine, lysine, and serine using the MP2 method. The role of the correlation effects in the peptide molecular charge distribution are discussed.

Many-Body Descriptors for Predicting Molecular Properties with Machine Learning: Analysis of Pairwise and Three-Body Interactions in Molecules.

PubMed

Pronobis, Wiktor; Tkatchenko, Alexandre; Müller, Klaus-Robert

2018-06-12

Machine learning (ML) based prediction of molecular properties across chemical compound space is an important and alternative approach to efficiently estimate the solutions of highly complex many-electron problems in chemistry and physics. Statistical methods represent molecules as descriptors that should encode molecular symmetries and interactions between atoms. Many such descriptors have been proposed; all of them have advantages and limitations. Here, we propose a set of general two-body and three-body interaction descriptors which are invariant to translation, rotation, and atomic indexing. By adapting the successfully used kernel ridge regression methods of machine learning, we evaluate our descriptors on predicting several properties of small organic molecules calculated using density-functional theory. We use two data sets. The GDB-7 set contains 6868 molecules with up to 7 heavy atoms of type CNO. The GDB-9 set is composed of 131722 molecules with up to 9 heavy atoms containing CNO. When trained on 5000 random molecules, our best model achieves an accuracy of 0.8 kcal/mol (on the remaining 1868 molecules of GDB-7) and 1.5 kcal/mol (on the remaining 126722 molecules of GDB-9) respectively. Applying a linear regression model on our novel many-body descriptors performs almost equal to a nonlinear kernelized model. Linear models are readily interpretable: a feature importance ranking measure helps to obtain qualitative and quantitative insights on the importance of two- and three-body molecular interactions for predicting molecular properties computed with quantum-mechanical methods.

General molecular mechanics method for transition metal carboxylates and its application to the multiple coordination modes in mono- and dinuclear Mn(II) complexes.

PubMed

Deeth, Robert J

2008-08-04

A general molecular mechanics method is presented for modeling the symmetric bidentate, asymmetric bidentate, and bridging modes of metal-carboxylates with a single parameter set by using a double-minimum M-O-C angle-bending potential. The method is implemented within the Molecular Operating Environment (MOE) with parameters based on the Merck molecular force field although, with suitable modifications, other MM packages and force fields could easily be used. Parameters for high-spin d (5) manganese(II) bound to carboxylate and water plus amine, pyridyl, imidazolyl, and pyrazolyl donors are developed based on 26 mononuclear and 29 dinuclear crystallographically characterized complexes. The average rmsd for Mn-L distances is 0.08 A, which is comparable to the experimental uncertainty required to cover multiple binding modes, and the average rmsd in heavy atom positions is around 0.5 A. In all cases, whatever binding mode is reported is also computed to be a stable local minimum. In addition, the structure-based parametrization implicitly captures the energetics and gives the same relative energies of symmetric and asymmetric coordination modes as density functional theory calculations in model and "real" complexes. Molecular dynamics simulations show that carboxylate rotation is favored over "flipping" while a stochastic search algorithm is described for randomly searching conformational space. The model reproduces Mn-Mn distances in dinuclear systems especially accurately, and this feature is employed to illustrate how MM calculations on models for the dimanganese active site of methionine aminopeptidase can help determine some of the details which may be missing from the experimental structure.

Girsanov reweighting for path ensembles and Markov state models

NASA Astrophysics Data System (ADS)

Donati, L.; Hartmann, C.; Keller, B. G.

2017-06-01

The sensitivity of molecular dynamics on changes in the potential energy function plays an important role in understanding the dynamics and function of complex molecules. We present a method to obtain path ensemble averages of a perturbed dynamics from a set of paths generated by a reference dynamics. It is based on the concept of path probability measure and the Girsanov theorem, a result from stochastic analysis to estimate a change of measure of a path ensemble. Since Markov state models (MSMs) of the molecular dynamics can be formulated as a combined phase-space and path ensemble average, the method can be extended to reweight MSMs by combining it with a reweighting of the Boltzmann distribution. We demonstrate how to efficiently implement the Girsanov reweighting in a molecular dynamics simulation program by calculating parts of the reweighting factor "on the fly" during the simulation, and we benchmark the method on test systems ranging from a two-dimensional diffusion process and an artificial many-body system to alanine dipeptide and valine dipeptide in implicit and explicit water. The method can be used to study the sensitivity of molecular dynamics on external perturbations as well as to reweight trajectories generated by enhanced sampling schemes to the original dynamics.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling

NASA Astrophysics Data System (ADS)

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling.

PubMed

Bhakat, Soumendranath; Åberg, Emil; Söderhjelm, Pär

2018-01-01

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.

Novel method for the determination of average molecular weight of natural polymers based on 2D DOSY NMR and chemometrics: Example of heparin.

PubMed

Monakhova, Yulia B; Diehl, Bernd W K; Do, Tung X; Schulze, Margit; Witzleben, Steffen

2018-02-05

Apart from the characterization of impurities, the full characterization of heparin and low molecular weight heparin (LMWH) also requires the determination of average molecular weight, which is closely related to the pharmaceutical properties of anticoagulant drugs. To determine average molecular weight of these animal-derived polymer products, partial least squares regression (PLS) was utilized for modelling of diffused-ordered spectroscopy NMR data (DOSY) of a representative set of heparin (n=32) and LMWH (n=30) samples. The same sets of samples were measured by gel permeation chromatography (GPC) to obtain reference data. The application of PLS to the data led to calibration models with root mean square error of prediction of 498Da and 179Da for heparin and LMWH, respectively. The average coefficients of variation (CVs) did not exceed 2.1% excluding sample preparation (by successive measuring one solution, n=5) and 2.5% including sample preparation (by preparing and analyzing separate samples, n=5). An advantage of the method is that the sample after standard 1D NMR characterization can be used for the molecular weight determination without further manipulation. The accuracy of multivariate models is better than the previous results for other matrices employing internal standards. Therefore, DOSY experiment is recommended to be employed for the calculation of molecular weight of heparin products as a complementary measurement to standard 1D NMR quality control. The method can be easily transferred to other matrices as well. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Insights into the interaction of methotrexate and human serum albumin: A spectroscopic and molecular modeling approach.

PubMed

Cheng, Li-Yang; Fang, Min; Bai, Ai-Min; Ouyang, Yu; Hu, Yan-Jun

2017-08-01

In this study, fluorescence spectroscopy and molecular modeling approaches were employed to investigate the binding of methotrexate to human serum albumin (HSA) under physiological conditions. From the mechanism, it was demonstrated that fluorescence quenching of HSA by methotrexate results from the formation of a methotrexate/HSA complex. Binding parameters calculated using the Stern-Volmer method and the Scatchard method showed that methotrexate binds to HSA with binding affinities in the order 10 4  L·mol -1 . Thermodynamic parameter studies revealed that the binding reaction is spontaneous, and that hydrogen bonds and van der Waals interactions play a major role in the reaction. Site marker competitive displacement experiments and a molecular modeling approach demonstrated that methotrexate binds with appropriate affinity to site I (subdomain IIA) of HSA. Furthermore, we discuss some factors that influence methotrexate binding to HSA. Copyright © 2017 John Wiley & Sons, Ltd.

Energetics using the single point IMOMO (integrated molecular orbital+molecular orbital) calculations: Choices of computational levels and model system

NASA Astrophysics Data System (ADS)

Svensson, Mats; Humbel, Stéphane; Morokuma, Keiji

1996-09-01

The integrated MO+MO (IMOMO) method, recently proposed for geometry optimization, is tested for accurate single point calculations. The principle idea of the IMOMO method is to reproduce results of a high level MO calculation for a large ``real'' system by dividing it into a small ``model'' system and the rest and applying different levels of MO theory for the two parts. Test examples are the activation barrier of the SN2 reaction of Cl-+alkyl chlorides, the C=C double bond dissociation of olefins and the energy of reaction for epoxidation of benzene. The effects of basis set and method in the lower level calculation as well as the effects of the choice of model system are investigated in detail. The IMOMO method gives an approximation to the high level MO energetics on the real system, in most cases with very small errors, with a small additional cost over the low level calculation. For instance, when the MP2 (Møller-Plesset second-order perturbation) method is used as the lower level method, the IMOMO method reproduces the results of very high level MO method within 2 kcal/mol, with less than 50% of additional computer time, for the first two test examples. When the HF (Hartree-Fock) method is used as the lower level method, it is less accurate and depends more on the choice of model system, though the improvement over the HF energy is still very significant. Thus the IMOMO single point calculation provides a method for obtaining reliable local energetics such as bond energies and activation barriers for a large molecular system.

A comparison of machine learning and Bayesian modelling for molecular serotyping.

PubMed

Newton, Richard; Wernisch, Lorenz

2017-08-11

Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological insights, which we illustrate with an example.

Modeling of the phase equilibria of polystyrene in methylcyclohexane with semi-empirical quantum mechanical methods I.

PubMed

Wilczura-Wachnik, Hanna; Jónsdóttir, Svava Osk

2003-04-01

A method for calculating interaction parameters traditionally used in phase-equilibrium computations in low-molecular systems has been extended for the prediction of solvent activities of aromatic polymer solutions (polystyrene+methylcyclohexane). Using ethylbenzene as a model compound for the repeating unit of the polymer, the intermolecular interaction energies between the solvent molecule and the polymer were simulated. The semiempirical quantum chemical method AM1, and a method for sampling relevant internal orientations for a pair of molecules developed previously were used. Interaction energies are determined for three molecular pairs, the solvent and the model molecule, two solvent molecules and two model molecules, and used to calculated UNIQUAC interaction parameters, a(ij) and a(ji). Using these parameters, the solvent activities of the polystyrene 90,000 amu+methylcyclohexane system, and the total vapor pressures of the methylcyclohexane+ethylbenzene system were calculated. The latter system was compared to experimental data, giving qualitative agreement. Figure Solvent activities for the methylcylcohexane(1)+polystyrene(2) system at 316 K. Parameters aij (blue line) obtained with the AM1 method; parameters aij (pink line) from VLE data for the ethylbenzene+methylcyclohexane system. The abscissa is the polymer weight fraction defined as y2(x1)=(1mx1)M2/[x1M1+(1mx1)M2], where x1 is the solvent mole fraction and Mi are the molecular weights of the components.

Diamond-like nanoparticles influence on flavonoids transport: molecular modelling

NASA Astrophysics Data System (ADS)

Plastun, Inna L.; Agandeeva, Ksenia E.; Bokarev, Andrey N.; Zenkin, Nikita S.

2017-03-01

Intermolecular interaction of diamond-like nanoparticles and flavonoids is investigated by numerical simulation. Using molecular modelling by the density functional theory method, we analyze hydrogen bonds formation and their influence on IR - spectra and structure of molecular complex which is formed due to interaction between flavonoids and nanodiamonds surrounded with carboxylic groups. Enriched adamantane (1,3,5,7 - adamantanetetracarboxylic acid) is used as an example of diamond-like nanoparticles. Intermolecular forces and structure of hydrogen bonds are investigated. IR - spectra and structure parameters of quercetin - adamantanetetracarboxylic acid molecular complex are obtained by numerical simulation using the Gaussian software complex. Received data coincide well with experimental results. Intermolecular interactions and hydrogen bonding structure in the obtained molecular complex are examined. Possibilities of flavonoids interaction with DNA at the molecular level are also considered.

Evaluation of protein-protein docking model structures using all-atom molecular dynamics simulations combined with the solution theory in the energy representation

NASA Astrophysics Data System (ADS)

Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio

2012-12-01

We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.

Evaluation of protein-protein docking model structures using all-atom molecular dynamics simulations combined with the solution theory in the energy representation.

PubMed

Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio

2012-12-07

We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.

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.

Multiscale methods for computational RNA enzymology

PubMed Central

Panteva, Maria T.; Dissanayake, Thakshila; Chen, Haoyuan; Radak, Brian K.; Kuechler, Erich R.; Giambaşu, George M.; Lee, Tai-Sung; York, Darrin M.

2016-01-01

RNA catalysis is of fundamental importance to biology and yet remains ill-understood due to its complex nature. The multi-dimensional “problem space” of RNA catalysis includes both local and global conformational rearrangements, changes in the ion atmosphere around nucleic acids and metal ion binding, dependence on potentially correlated protonation states of key residues and bond breaking/forming in the chemical steps of the reaction. The goal of this article is to summarize and apply multiscale modeling methods in an effort to target the different parts of the RNA catalysis problem space while also addressing the limitations and pitfalls of these methods. Classical molecular dynamics (MD) simulations, reference interaction site model (RISM) calculations, constant pH molecular dynamics (CpHMD) simulations, Hamiltonian replica exchange molecular dynamics (HREMD) and quantum mechanical/molecular mechanical (QM/MM) simulations will be discussed in the context of the study of RNA backbone cleavage transesterification. This reaction is catalyzed by both RNA and protein enzymes, and here we examine the different mechanistic strategies taken by the hepatitis delta virus ribozyme (HDVr) and RNase A. PMID:25726472

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.

Parametrization of an Orbital-Based Linear-Scaling Quantum Force Field for Noncovalent Interactions

PubMed Central

2015-01-01

We parametrize a linear-scaling quantum mechanical force field called mDC for the accurate reproduction of nonbonded interactions. We provide a new benchmark database of accurate ab initio interactions between sulfur-containing molecules. A variety of nonbond databases are used to compare the new mDC method with other semiempirical, molecular mechanical, ab initio, and combined semiempirical quantum mechanical/molecular mechanical methods. It is shown that the molecular mechanical force field significantly and consistently reproduces the benchmark results with greater accuracy than the semiempirical models and our mDC model produces errors twice as small as the molecular mechanical force field. The comparisons between the methods are extended to the docking of drug candidates to the Cyclin-Dependent Kinase 2 protein receptor. We correlate the protein–ligand binding energies to their experimental inhibition constants and find that the mDC produces the best correlation. Condensed phase simulation of mDC water is performed and shown to produce O–O radial distribution functions similar to TIP4P-EW. PMID:24803856

[Quantitative relationship between gas chromatographic retention time and structural parameters of alkylphenols].

PubMed

Ruan, Xiaofang; Zhang, Ruisheng; Yao, Xiaojun; Liu, Mancang; Fan, Botao

2007-03-01

Alkylphenols are a group of permanent pollutants in the environment and could adversely disturb the human endocrine system. It is therefore important to effectively separate and measure the alkylphenols. To guide the chromatographic analysis of these compounds in practice, the development of quantitative relationship between the molecular structure and the retention time of alkylphenols becomes necessary. In this study, topological, constitutional, geometrical, electrostatic and quantum-chemical descriptors of 44 alkylphenols were calculated using a software, CODESSA, and these descriptors were pre-selected using the heuristic method. As a result, three-descriptor linear model (LM) was developed to describe the relationship between the molecular structure and the retention time of alkylphenols. Meanwhile, the non-linear regression model was also developed based on support vector machine (SVM) using the same three descriptors. The correlation coefficient (R(2)) for the LM and SVM was 0.98 and 0. 92, and the corresponding root-mean-square error was 0. 99 and 2. 77, respectively. By comparing the stability and prediction ability of the two models, it was found that the linear model was a better method for describing the quantitative relationship between the retention time of alkylphenols and the molecular structure. The results obtained suggested that the linear model could be applied for the chromatographic analysis of alkylphenols with known molecular structural parameters.

GPU accelerated Discrete Element Method (DEM) molecular dynamics for conservative, faceted particle simulations

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

Spellings, Matthew; Biointerfaces Institute, University of Michigan, 2800 Plymouth Rd., Ann Arbor, MI 48109; Marson, Ryan L.

Faceted shapes, such as polyhedra, are commonly found in systems of nanoscale, colloidal, and granular particles. Many interesting physical phenomena, like crystal nucleation and growth, vacancy motion, and glassy dynamics are challenging to model in these systems because they require detailed dynamical information at the individual particle level. Within the granular materials community the Discrete Element Method has been used extensively to model systems of anisotropic particles under gravity, with friction. We provide an implementation of this method intended for simulation of hard, faceted nanoparticles, with a conservative Weeks–Chandler–Andersen (WCA) interparticle potential, coupled to a thermodynamic ensemble. This method ismore » a natural extension of classical molecular dynamics and enables rigorous thermodynamic calculations for faceted particles.« less

Silanol-assisted carbinolamine formation in an amine-functionalized mesoporous silica surface: Theoretical investigation by fragmentation methods

DOE PAGES

de Lima Batista, Ana P.; Zahariev, Federico; Slowing, Igor I.; ...

2015-12-15

The aldol reaction catalyzed by an amine-substituted mesoporous silica nanoparticle (amine-MSN) surface was investigated using a large molecular cluster model (Si 392O 958C 6NH 361) combined with the surface integrated molecular orbital/molecular mechanics (SIMOMM) and fragment molecular orbital (FMO) methods. Three distinct pathways for the carbinolamine formation, the first step of the amine-catalyzed aldol reaction, are proposed and investigated in order to elucidate the role of the silanol environment on the catalytic capability of the amine-MSN material. Here the computational study reveals that the most likely mechanism involves the silanol groups actively participating in the reaction, forming and breaking covalentmore » bonds in the carbinolamine step. Furthermore, the active participation of MSN silanol groups in the reaction mechanism leads to a significant reduction in the overall energy barrier for the carbinolamine formation. In addition, a comparison between the findings using a minimal cluster model and the Si 392O 958C 6NH 361 cluster suggests that the use of larger models is important when heterogeneous catalysis problems are the target.« less

Mesoscale energy deposition footprint model for kiloelectronvolt cluster bombardment of solids.

PubMed

Russo, Michael F; Garrison, Barbara J

2006-10-15

Molecular dynamics simulations have been performed to model 5-keV C60 and Au3 projectile bombardment of an amorphous water substrate. The goal is to obtain detailed insights into the dynamics of motion in order to develop a straightforward and less computationally demanding model of the process of ejection. The molecular dynamics results provide the basis for the mesoscale energy deposition footprint model. This model provides a method for predicting relative yields based on information from less than 1 ps of simulation time.

A Simple and Accurate Method To Calculate Free Energy Profiles and Reaction Rates from Restrained Molecular Simulations of Diffusive Processes.

PubMed

Ovchinnikov, Victor; Nam, Kwangho; Karplus, Martin

2016-08-25

A method is developed to obtain simultaneously free energy profiles and diffusion constants from restrained molecular simulations in diffusive systems. The method is based on low-order expansions of the free energy and diffusivity as functions of the reaction coordinate. These expansions lead to simple analytical relationships between simulation statistics and model parameters. The method is tested on 1D and 2D model systems; its accuracy is found to be comparable to or better than that of the existing alternatives, which are briefly discussed. An important aspect of the method is that the free energy is constructed by integrating its derivatives, which can be computed without need for overlapping sampling windows. The implementation of the method in any molecular simulation program that supports external umbrella potentials (e.g., CHARMM) requires modification of only a few lines of code. As a demonstration of its applicability to realistic biomolecular systems, the method is applied to model the α-helix ↔ β-sheet transition in a 16-residue peptide in implicit solvent, with the reaction coordinate provided by the string method. Possible modifications of the method are briefly discussed; they include generalization to multidimensional reaction coordinates [in the spirit of the model of Ermak and McCammon (Ermak, D. L.; McCammon, J. A. J. Chem. Phys. 1978, 69, 1352-1360)], a higher-order expansion of the free energy surface, applicability in nonequilibrium systems, and a simple test for Markovianity. In view of the small overhead of the method relative to standard umbrella sampling, we suggest its routine application in the cases where umbrella potential simulations are appropriate.

From Geometry Optimization to Time Dependent Molecular Structure Modeling: Method Developments, ab initio Theories and Applications

NASA Astrophysics Data System (ADS)

Liang, Wenkel

This dissertation consists of two general parts: (I) developments of optimization algorithms (both nuclear and electronic degrees of freedom) for time-independent molecules and (II) novel methods, first-principle theories and applications in time dependent molecular structure modeling. In the first part, we discuss in specific two new algorithms for static geometry optimization, the eigenspace update (ESU) method in nonredundant internal coordinate that exhibits an enhanced performace with up to a factor of 3 savings in computational cost for large-sized molecular systems; the Car-Parrinello density matrix search (CP-DMS) method that enables direct minimization of the SCF energy as an effective alternative to conventional diagonalization approach. For the second part, we consider the time dependence and first presents two nonadiabatic dynamic studies that model laser controlled molecular photo-dissociation for qualitative understandings of intense laser-molecule interaction, using ab initio direct Ehrenfest dynamics scheme implemented with real-time time-dependent density functional theory (RT-TDDFT) approach developed in our group. Furthermore, we place our special interest on the nonadiabatic electronic dynamics in the ultrafast time scale, and presents (1) a novel technique that can not only obtain energies but also the electron densities of doubly excited states within a single determinant framework, by combining methods of CP-DMS with RT-TDDFT; (2) a solvated first-principles electronic dynamics method by incorporating the polarizable continuum solvation model (PCM) to RT-TDDFT, which is found to be very effective in describing the dynamical solvation effect in the charge transfer process and yields a consistent absorption spectrum in comparison to the conventional linear response results in solution. (3) applications of the PCM-RT-TDDFT method to study the intramolecular charge-transfer (CT) dynamics in a C60 derivative. Such work provides insights into the characteristics of ultrafast dynamics in photoexcited fullerene derivatives, and aids in the rational design for pre-dissociative exciton in the intramolecular CT process in organic solar cells.

Numerical study of influence of molecular diffusion in the Mild combustion regime

NASA Astrophysics Data System (ADS)

Mardani, Amir; Tabejamaat, Sadegh; Ghamari, Mohsen

2010-09-01

In this paper, the importance of molecular diffusion versus turbulent transport in the moderate or intense low-oxygen dilution (Mild) combustion mode has been numerically studied. The experimental conditions of Dally et al. [Proc. Combust. Inst. 29 (2002) 1147-1154] were used for modelling. The EDC model was used to describe the turbulence-chemistry interaction. The DRM-22 reduced mechanism and the GRI 2.11 full mechanism were used to represent the chemical reactions of an H2/methane jet flame. The importance of molecular diffusion for various O2 levels, jet Reynolds numbers and H2 fuel contents was investigated. Results show that the molecular diffusion in Mild combustion cannot be ignored in comparison with the turbulent transport. Also, the method of inclusion of molecular diffusion in combustion modelling has a considerable effect on the accuracy of numerical modelling of Mild combustion. By decreasing the jet Reynolds number, decreasing the oxygen concentration in the airflow or increasing H2 in the fuel mixture, the influence of molecular diffusion on Mild combustion increases.

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

Multi-level molecular modelling for plasma medicine

NASA Astrophysics Data System (ADS)

Bogaerts, Annemie; Khosravian, Narjes; Van der Paal, Jonas; Verlackt, Christof C. W.; Yusupov, Maksudbek; Kamaraj, Balu; Neyts, Erik C.

2016-02-01

Modelling at the molecular or atomic scale can be very useful for obtaining a better insight in plasma medicine. This paper gives an overview of different atomic/molecular scale modelling approaches that can be used to study the direct interaction of plasma species with biomolecules or the consequences of these interactions for the biomolecules on a somewhat longer time-scale. These approaches include density functional theory (DFT), density functional based tight binding (DFTB), classical reactive and non-reactive molecular dynamics (MD) and united-atom or coarse-grained MD, as well as hybrid quantum mechanics/molecular mechanics (QM/MM) methods. Specific examples will be given for three important types of biomolecules, present in human cells, i.e. proteins, DNA and phospholipids found in the cell membrane. The results show that each of these modelling approaches has its specific strengths and limitations, and is particularly useful for certain applications. A multi-level approach is therefore most suitable for obtaining a global picture of the plasma-biomolecule interactions.

Study on the activity of non-purine xanthine oxidase inhibitor by 3D-QSAR modeling and molecular docking

NASA Astrophysics Data System (ADS)

Li, Peizhen; Tian, Yueli; Zhai, Honglin; Deng, Fangfang; Xie, Meihong; Zhang, Xiaoyun

2013-11-01

Non-purine derivatives have been shown to be promising novel drug candidates as xanthine oxidase inhibitors. Based on three-dimensional quantitative structure-activity relationship (3D-QSAR) methods including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), two 3D-QSAR models for a series of non-purine xanthine oxidase (XO) inhibitors were established, and their reliability was supported by statistical parameters. Combined 3D-QSAR modeling and the results of molecular docking between non-purine xanthine oxidase inhibitors and XO, the main factors that influenced activity of inhibitors were investigated, and the obtained results could explain known experimental facts. Furthermore, several new potential inhibitors with higher activity predicted were designed, which based on our analyses, and were supported by the simulation of molecular docking. This study provided some useful information for the development of non-purine xanthine oxidase inhibitors with novel structures.

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Investigation on the protein-binding properties of icotinib by spectroscopic and molecular modeling method

NASA Astrophysics Data System (ADS)

Zhang, Hua-xin; Xiong, Hang-xing; Li, Li-wei

2016-05-01

Icotinib is a highly-selective epidermal growth factor receptor tyrosine kinase inhibitor with preclinical and clinical activity in non-small cell lung cancer, which has been developed as a new targeted anti-tumor drug in China. In this work, the interaction of icotinib and human serum albumin (HSA) were studied by three-dimensional fluorescence spectra, ultraviolet spectra, circular dichroism (CD) spectra, molecular probe and molecular modeling methods. The results showed that icotinib binds to Sudlow's site I in subdomain IIA of HSA molecule, resulting in icotinib-HSA complexes formed at ground state. The number of binding sites, equilibrium constants, and thermodynamic parameters of the reaction were calculated at different temperatures. The negative enthalpy change (ΔHθ) and entropy change (ΔSθ) indicated that the structure of new complexes was stabilized by hydrogen bonds and van der Waals power. The distance between donor and acceptor was calculated according to Förster's non-radiation resonance energy transfer theory. The structural changes of HSA caused by icotinib binding were detected by synchronous spectra and circular dichroism (CD) spectra. Molecular modeling method was employed to unfold full details of the interaction at molecular level, most of which could be supported by experimental results. The study analyzed the probability that serum albumins act as carriers for this new anticarcinogen and provided fundamental information on the process of delivering icotinib to its target tissues, which might be helpful in understanding the mechanism of icotinib in cancer therapy.

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.

Prioritization of in silico models and molecular descriptors for the assessment of ready biodegradability

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

Fernández, Alberto; Rallo, Robert; Giralt, Francesc

2015-10-15

Ready biodegradability is a key property for evaluating the long-term effects of chemicals on the environment and human health. As such, it is used as a screening test for the assessment of persistent, bioaccumulative and toxic substances. Regulators encourage the use of non-testing methods, such as in silico models, to save money and time. A dataset of 757 chemicals was collected to assess the performance of four freely available in silico models that predict ready biodegradability. They were applied to develop a new consensus method that prioritizes the use of each individual model according to its performance on chemical subsetsmore » driven by the presence or absence of different molecular descriptors. This consensus method was capable of almost eliminating unpredictable chemicals, while the performance of combined models was substantially improved with respect to that of the individual models. - Highlights: • Consensus method to predict ready biodegradability by prioritizing multiple QSARs. • Consensus reduced the amount of unpredictable chemicals to less than 2%. • Performance increased with the number of QSAR models considered. • The absence of 2D atom pairs contributed significantly to the consensus model.« less

Advances in Time Estimation Methods for Molecular Data.

PubMed

Kumar, Sudhir; Hedges, S Blair

2016-04-01

Molecular dating has become central to placing a temporal dimension on the tree of life. Methods for estimating divergence times have been developed for over 50 years, beginning with the proposal of molecular clock in 1962. We categorize the chronological development of these methods into four generations based on the timing of their origin. In the first generation approaches (1960s-1980s), a strict molecular clock was assumed to date divergences. In the second generation approaches (1990s), the equality of evolutionary rates between species was first tested and then a strict molecular clock applied to estimate divergence times. The third generation approaches (since ∼2000) account for differences in evolutionary rates across the tree by using a statistical model, obviating the need to assume a clock or to test the equality of evolutionary rates among species. Bayesian methods in the third generation require a specific or uniform prior on the speciation-process and enable the inclusion of uncertainty in clock calibrations. The fourth generation approaches (since 2012) allow rates to vary from branch to branch, but do not need prior selection of a statistical model to describe the rate variation or the specification of speciation model. With high accuracy, comparable to Bayesian approaches, and speeds that are orders of magnitude faster, fourth generation methods are able to produce reliable timetrees of thousands of species using genome scale data. We found that early time estimates from second generation studies are similar to those of third and fourth generation studies, indicating that methodological advances have not fundamentally altered the timetree of life, but rather have facilitated time estimation by enabling the inclusion of more species. Nonetheless, we feel an urgent need for testing the accuracy and precision of third and fourth generation methods, including their robustness to misspecification of priors in the analysis of large phylogenies and data sets. © The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Bayesian approach to estimating hidden variables as well as missing and wrong molecular interactions in ordinary differential equation-based mathematical models.

PubMed

Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger

2017-06-01

Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).

Kernel optimization for short-range molecular dynamics

NASA Astrophysics Data System (ADS)

Hu, Changjun; Wang, Xianmeng; Li, Jianjiang; He, Xinfu; Li, Shigang; Feng, Yangde; Yang, Shaofeng; Bai, He

2017-02-01

To optimize short-range force computations in Molecular Dynamics (MD) simulations, multi-threading and SIMD optimizations are presented in this paper. With respect to multi-threading optimization, a Partition-and-Separate-Calculation (PSC) method is designed to avoid write conflicts caused by using Newton's third law. Serial bottlenecks are eliminated with no additional memory usage. The method is implemented by using the OpenMP model. Furthermore, the PSC method is employed on Intel Xeon Phi coprocessors in both native and offload models. We also evaluate the performance of the PSC method under different thread affinities on the MIC architecture. In the SIMD execution, we explain the performance influence in the PSC method, considering the "if-clause" of the cutoff radius check. The experiment results show that our PSC method is relatively more efficient compared to some traditional methods. In double precision, our 256-bit SIMD implementation is about 3 times faster than the scalar version.

A review on nanomechanical resonators and their applications in sensors and molecular transportation

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

Arash, Behrouz; Rabczuk, Timon, E-mail: timon.rabczuk@uni-weimar.de; Jiang, Jin-Wu

2015-06-15

Nanotechnology has opened a new area in science and engineering, leading to the development of novel nano-electromechanical systems such as nanoresonators with ultra-high resonant frequencies. The ultra-high-frequency resonators facilitate wide-ranging applications such as ultra-high sensitive sensing, molecular transportation, molecular separation, high-frequency signal processing, and biological imaging. This paper reviews recent studies on dynamic characteristics of nanoresonators. A variety of theoretical approaches, i.e., continuum modeling, molecular simulations, and multiscale methods, in modeling of nanoresonators are reviewed. The potential application of nanoresonators in design of sensor devices and molecular transportation systems is introduced. The essence of nanoresonator sensors for detection of atomsmore » and molecules with vibration and wave propagation analyses is outlined. The sensitivity of the resonator sensors and their feasibility in detecting different atoms and molecules are particularly discussed. Furthermore, the applicability of molecular transportation using the propagation of mechanical waves in nanoresonators is presented. An extended application of the transportation methods for building nanofiltering systems with ultra-high selectivity is surveyed. The article aims to provide an up-to-date review on the mechanical properties and applications of nanoresonators, and inspire additional potential of the resonators.« less

A SAR and QSAR study of new artemisinin compounds with antimalarial activity.

PubMed

Santos, Cleydson Breno R; Vieira, Josinete B; Lobato, Cleison C; Hage-Melim, Lorane I S; Souto, Raimundo N P; Lima, Clarissa S; Costa, Elizabeth V M; Brasil, Davi S B; Macêdo, Williams Jorge C; Carvalho, José Carlos T

2013-12-30

The Hartree-Fock method and the 6-31G** basis set were employed to calculate the molecular properties of artemisinin and 20 derivatives with antimalarial activity. Maps of molecular electrostatic potential (MEPs) and molecular docking were used to investigate the interaction between ligands and the receptor (heme). Principal component analysis and hierarchical cluster analysis were employed to select the most important descriptors related to activity. The correlation between biological activity and molecular properties was obtained using the partial least squares and principal component regression methods. The regression PLS and PCR models built in this study were also used to predict the antimalarial activity of 30 new artemisinin compounds with unknown activity. The models obtained showed not only statistical significance but also predictive ability. The significant molecular descriptors related to the compounds with antimalarial activity were the hydration energy (HE), the charge on the O11 oxygen atom (QO11), the torsion angle O1-O2-Fe-N2 (D2) and the maximum rate of R/Sanderson Electronegativity (RTe+). These variables led to a physical and structural explanation of the molecular properties that should be selected for when designing new ligands to be used as antimalarial agents.

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.

Geometric analysis characterizes molecular rigidity in generic and non-generic protein configurations

PubMed Central

Budday, Dominik; Leyendecker, Sigrid; van den Bedem, Henry

2015-01-01

Proteins operate and interact with partners by dynamically exchanging between functional substates of a conformational ensemble on a rugged free energy landscape. Understanding how these substates are linked by coordinated, collective motions requires exploring a high-dimensional space, which remains a tremendous challenge. While molecular dynamics simulations can provide atomically detailed insight into the dynamics, computational demands to adequately sample conformational ensembles of large biomolecules and their complexes often require tremendous resources. Kinematic models can provide high-level insights into conformational ensembles and molecular rigidity beyond the reach of molecular dynamics by reducing the dimensionality of the search space. Here, we model a protein as a kinematic linkage and present a new geometric method to characterize molecular rigidity from the constraint manifold Q and its tangent space Q at the current configuration q. In contrast to methods based on combinatorial constraint counting, our method is valid for both generic and non-generic, e.g., singular configurations. Importantly, our geometric approach provides an explicit basis for collective motions along floppy modes, resulting in an efficient procedure to probe conformational space. An atomically detailed structural characterization of coordinated, collective motions would allow us to engineer or allosterically modulate biomolecules by selectively stabilizing conformations that enhance or inhibit function with broad implications for human health. PMID:26213417

Geometric analysis characterizes molecular rigidity in generic and non-generic protein configurations

NASA Astrophysics Data System (ADS)

Budday, Dominik; Leyendecker, Sigrid; van den Bedem, Henry

2015-10-01

Proteins operate and interact with partners by dynamically exchanging between functional substates of a conformational ensemble on a rugged free energy landscape. Understanding how these substates are linked by coordinated, collective motions requires exploring a high-dimensional space, which remains a tremendous challenge. While molecular dynamics simulations can provide atomically detailed insight into the dynamics, computational demands to adequately sample conformational ensembles of large biomolecules and their complexes often require tremendous resources. Kinematic models can provide high-level insights into conformational ensembles and molecular rigidity beyond the reach of molecular dynamics by reducing the dimensionality of the search space. Here, we model a protein as a kinematic linkage and present a new geometric method to characterize molecular rigidity from the constraint manifold Q and its tangent space Tq Q at the current configuration q. In contrast to methods based on combinatorial constraint counting, our method is valid for both generic and non-generic, e.g., singular configurations. Importantly, our geometric approach provides an explicit basis for collective motions along floppy modes, resulting in an efficient procedure to probe conformational space. An atomically detailed structural characterization of coordinated, collective motions would allow us to engineer or allosterically modulate biomolecules by selectively stabilizing conformations that enhance or inhibit function with broad implications for human health.

Discrimination between native and intentionally misfolded conformations of proteins: ES/IS, a new method for calculating conformational free energy that uses both dynamics simulations with an explicit solvent and an implicit solvent continuum model.

PubMed

Vorobjev, Y N; Almagro, J C; Hermans, J

1998-09-01

A new method for calculating the total conformational free energy of proteins in water solvent is presented. The method consists of a relatively brief simulation by molecular dynamics with explicit solvent (ES) molecules to produce a set of microstates of the macroscopic conformation. Conformational energy and entropy are obtained from the simulation, the latter in the quasi-harmonic approximation by analysis of the covariance matrix. The implicit solvent (IS) dielectric continuum model is used to calculate the average solvation free energy as the sum of the free energies of creating the solute-size hydrophobic cavity, of the van der Waals solute-solvent interactions, and of the polarization of water solvent by the solute's charges. The reliability of the solvation free energy depends on a number of factors: the details of arrangement of the protein's charges, especially those near the surface; the definition of the molecular surface; and the method chosen for solving the Poisson equation. Molecular dynamics simulation in explicit solvent relaxes the protein's conformation and allows polar surface groups to assume conformations compatible with interaction with solvent, while averaging of internal energy and solvation free energy tend to enhance the precision. Two recently developed methods--SIMS, for calculation of a smooth invariant molecular surface, and FAMBE, for solution of the Poisson equation via a fast adaptive multigrid boundary element--have been employed. The SIMS and FAMBE programs scale linearly with the number of atoms. SIMS is superior to Connolly's MS (molecular surface) program: it is faster, more accurate, and more stable, and it smooths singularities of the molecular surface. Solvation free energies calculated with these two programs do not depend on molecular position or orientation and are stable along a molecular dynamics trajectory. We have applied this method to calculate the conformational free energy of native and intentionally misfolded globular conformations of proteins (the EMBL set of deliberately misfolded proteins) and have obtained good discrimination in favor of the native conformations in all instances.

Prediction of molecular crystal structures by a crystallographic QM/MM model with full space-group symmetry.

PubMed

Mörschel, Philipp; Schmidt, Martin U

2015-01-01

A crystallographic quantum-mechanical/molecular-mechanical model (c-QM/MM model) with full space-group symmetry has been developed for molecular crystals. The lattice energy was calculated by quantum-mechanical methods for short-range interactions and force-field methods for long-range interactions. The quantum-mechanical calculations covered the interactions within the molecule and the interactions of a reference molecule with each of the surrounding 12-15 molecules. The interactions with all other molecules were treated by force-field methods. In each optimization step the energies in the QM and MM shells were calculated separately as single-point energies; after adding both energy contributions, the crystal structure (including the lattice parameters) was optimized accordingly. The space-group symmetry was maintained throughout. Crystal structures with more than one molecule per asymmetric unit, e.g. structures with Z' = 2, hydrates and solvates, have been optimized as well. Test calculations with different quantum-mechanical methods on nine small organic molecules revealed that the density functional theory methods with dispersion correction using the B97-D functional with 6-31G* basis set in combination with the DREIDING force field reproduced the experimental crystal structures with good accuracy. Subsequently the c-QM/MM method was applied to nine compounds from the CCDC blind tests resulting in good energy rankings and excellent geometric accuracies.

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.

A software platform for continuum modeling of ion channels based on unstructured mesh

NASA Astrophysics Data System (ADS)

Tu, B.; Bai, S. Y.; Chen, M. X.; Xie, Y.; Zhang, L. B.; Lu, B. Z.

2014-01-01

Most traditional continuum molecular modeling adopted finite difference or finite volume methods which were based on a structured mesh (grid). Unstructured meshes were only occasionally used, but an increased number of applications emerge in molecular simulations. To facilitate the continuum modeling of biomolecular systems based on unstructured meshes, we are developing a software platform with tools which are particularly beneficial to those approaches. This work describes the software system specifically for the simulation of a typical, complex molecular procedure: ion transport through a three-dimensional channel system that consists of a protein and a membrane. The platform contains three parts: a meshing tool chain for ion channel systems, a parallel finite element solver for the Poisson-Nernst-Planck equations describing the electrodiffusion process of ion transport, and a visualization program for continuum molecular modeling. The meshing tool chain in the platform, which consists of a set of mesh generation tools, is able to generate high-quality surface and volume meshes for ion channel systems. The parallel finite element solver in our platform is based on the parallel adaptive finite element package PHG which wass developed by one of the authors [1]. As a featured component of the platform, a new visualization program, VCMM, has specifically been developed for continuum molecular modeling with an emphasis on providing useful facilities for unstructured mesh-based methods and for their output analysis and visualization. VCMM provides a graphic user interface and consists of three modules: a molecular module, a meshing module and a numerical module. A demonstration of the platform is provided with a study of two real proteins, the connexin 26 and hemolysin ion channels.

Rotational relaxation of molecular hydrogen at moderate temperatures

NASA Technical Reports Server (NTRS)

Sharma, S. P.

1994-01-01

Using a coupled rotation-vibration-dissociation model the rotational relaxation times for molecular hydrogen as a function of final temperature (500-5000 K), in a hypothetical scenario of sudden compression, are computed. The theoretical model is based on a master equation solver. The bound-bound and bound-free transition rates have been computed using a quasiclassical trajectory method. A review of the available experimental data on the rotational relaxation of hydrogen is presented, with a critical overview of the method of measurements and data reduction, including the sources of errors. These experimental data are then compared with the computed results.

Molecular simulations of carbohydrates and protein-carbohydrate interactions: motivation, issues and prospects.

PubMed

Fadda, Elisa; Woods, Robert J

2010-08-01

The characterization of the 3D structure of oligosaccharides, their conjugates and analogs is particularly challenging for traditional experimental methods. Molecular simulation methods provide a basis for interpreting sparse experimental data and for independently predicting conformational and dynamic properties of glycans. Here, we summarize and analyze the issues associated with modeling carbohydrates, with a detailed discussion of four of the most recently developed carbohydrate force fields, reviewed in terms of applicability to natural glycans, carbohydrate-protein complexes and the emerging area of glycomimetic drugs. In addition, we discuss prospectives and new applications of carbohydrate modeling in drug discovery.

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.

Uncovering molecular processes in crystal nucleation and growth by using molecular simulation.

PubMed

Anwar, Jamshed; Zahn, Dirk

2011-02-25

Exploring nucleation processes by molecular simulation provides a mechanistic understanding at the atomic level and also enables kinetic and thermodynamic quantities to be estimated. However, whilst the potential for modeling crystal nucleation and growth processes is immense, there are specific technical challenges to modeling. In general, rare events, such as nucleation cannot be simulated using a direct "brute force" molecular dynamics approach. The limited time and length scales that are accessible by conventional molecular dynamics simulations have inspired a number of advances to tackle problems that were considered outside the scope of molecular simulation. While general insights and features could be explored from efficient generic models, new methods paved the way to realistic crystal nucleation scenarios. The association of single ions in solvent environments, the mechanisms of motif formation, ripening reactions, and the self-organization of nanocrystals can now be investigated at the molecular level. The analysis of interactions with growth-controlling additives gives a new understanding of functionalized nanocrystals and the precipitation of composite materials. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Progress toward bridging from atomistic to continuum modeling to predict nuclear waste glass dissolution.

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

Zapol, Peter; Bourg, Ian; Criscenti, Louise Jacqueline

2011-10-01

This report summarizes research performed for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Subcontinuum and Upscaling Task. The work conducted focused on developing a roadmap to include molecular scale, mechanistic information in continuum-scale models of nuclear waste glass dissolution. This information is derived from molecular-scale modeling efforts that are validated through comparison with experimental data. In addition to developing a master plan to incorporate a subcontinuum mechanistic understanding of glass dissolution into continuum models, methods were developed to generate constitutive dissolution rate expressions from quantum calculations, force field models were selected to generate multicomponent glass structures and gel layers,more » classical molecular modeling was used to study diffusion through nanopores analogous to those in the interfacial gel layer, and a micro-continuum model (K{mu}C) was developed to study coupled diffusion and reaction at the glass-gel-solution interface.« less

Panel 4: Recent Advances in Otitis Media in Molecular Biology, Biochemistry, Genetics, and Animal Models

PubMed Central

Li, Jian-Dong; Hermansson, Ann; Ryan, Allen F.; Bakaletz, Lauren O.; Brown, Steve D.; Cheeseman, Michael T.; Juhn, Steven K.; Jung, Timothy T. K.; Lim, David J.; Lim, Jae Hyang; Lin, Jizhen; Moon, Sung-Kyun; Post, J. Christopher

2014-01-01

Background Otitis media (OM) is the most common childhood bacterial infection and also the leading cause of conductive hearing loss in children. Currently, there is an urgent need for developing novel therapeutic agents for treating OM based on full understanding of molecular pathogenesis in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Objective To provide a state-of-the-art review concerning recent advances in OM in the areas of molecular biology, biochemistry, genetics, and animal model studies and to discuss the future directions of OM studies in these areas. Data Sources and Review Methods A structured search of the current literature (since June 2007). The authors searched PubMed for published literature in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Results Over the past 4 years, significant progress has been made in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. These studies brought new insights into our understanding of the molecular and biochemical mechanisms underlying the molecular pathogenesis of OM and helped identify novel therapeutic targets for OM. Conclusions and Implications for Practice Our understanding of the molecular pathogenesis of OM has been significantly advanced, particularly in the areas of inflammation, innate immunity, mucus overproduction, mucosal hyperplasia, middle ear and inner ear interaction, genetics, genome sequencing, and animal model studies. Although these studies are still in their experimental stages, they help identify new potential therapeutic targets. Future preclinical and clinical studies will help to translate these exciting experimental research findings into clinical applications. PMID:23536532

Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations.

PubMed

Hou, Tingjun; Wang, Junmei; Li, Youyong; Wang, Wei

2011-01-24

The Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) methods calculate binding free energies for macromolecules by combining molecular mechanics calculations and continuum solvation models. To systematically evaluate the performance of these methods, we report here an extensive study of 59 ligands interacting with six different proteins. First, we explored the effects of the length of the molecular dynamics (MD) simulation, ranging from 400 to 4800 ps, and the solute dielectric constant (1, 2, or 4) on the binding free energies predicted by MM/PBSA. The following three important conclusions could be observed: (1) MD simulation length has an obvious impact on the predictions, and longer MD simulation is not always necessary to achieve better predictions. (2) The predictions are quite sensitive to the solute dielectric constant, and this parameter should be carefully determined according to the characteristics of the protein/ligand binding interface. (3) Conformational entropy often show large fluctuations in MD trajectories, and a large number of snapshots are necessary to achieve stable predictions. Next, we evaluated the accuracy of the binding free energies calculated by three Generalized Born (GB) models. We found that the GB model developed by Onufriev and Case was the most successful model in ranking the binding affinities of the studied inhibitors. Finally, we evaluated the performance of MM/GBSA and MM/PBSA in predicting binding free energies. Our results showed that MM/PBSA performed better in calculating absolute, but not necessarily relative, binding free energies than MM/GBSA. Considering its computational efficiency, MM/GBSA can serve as a powerful tool in drug design, where correct ranking of inhibitors is often emphasized.

Model of twelve properties of a set of organic solvents with graph-theoretical and/or experimental parameters.

PubMed

Pogliani, Lionello

2010-01-30

Twelve properties of a highly heterogeneous class of organic solvents have been modeled with a graph-theoretical molecular connectivity modified (MC) method, which allows to encode the core electrons and the hydrogen atoms. The graph-theoretical method uses the concepts of simple, general, and complete graphs, where these last types of graphs are used to encode the core electrons. The hydrogen atoms have been encoded by the aid of a graph-theoretical perturbation parameter, which contributes to the definition of the valence delta, delta(v), a key parameter in molecular connectivity studies. The model of the twelve properties done with a stepwise search algorithm is always satisfactory, and it allows to check the influence of the hydrogen content of the solvent molecules on the choice of the type of descriptor. A similar argument holds for the influence of the halogen atoms on the type of core electron representation. In some cases the molar mass, and in a minor way, special "ad hoc" parameters have been used to improve the model. A very good model of the surface tension could be obtained by the aid of five experimental parameters. A mixed model method based on experimental parameters plus molecular connectivity indices achieved, instead, to consistently improve the model quality of five properties. To underline is the importance of the boiling point temperatures as descriptors in these last two model methodologies. Copyright 2009 Wiley Periodicals, Inc.

Development of the relaxation-assisted 2DIR method for accessing structures of molecules and its application for studying the energy transport on a molecular level

NASA Astrophysics Data System (ADS)

Kasyanenko, Valeriy Mitrofanovich

Measuring the three-dimensional structure of molecules, dynamics of structural changes, and energy transport on a molecular scale is important for many areas of natural science. Supplementing the widely used methods of x-ray diffraction, NMR, and optical spectroscopies, a two-dimensional infrared spectroscopy (2DIR) method was introduced about a decade ago. The 2DIR method measures pair-wise interactions between vibrational modes in molecules, thus acquiring molecular structural constraints such as distances between vibrating groups and the angles between their transition dipoles. The 2DIR method has been applied to a variety of molecular systems but in studying larger molecules such as proteins and peptides the method is facing challenges associated with the congestion of their vibrational spectra and delocalized character of their vibrational modes. To help extract structural information from such spectra and make efficient use of vibrational modes separated by large distances, a novel relaxation-assisted 2DIR method (RA 2DIR) has recently been proposed, which exploits the transport of excess vibrational energy from the initially excited mode. With the goal of further development of RA 2DIR, we applied it to a variety of molecular systems, including model compounds, transition-metal complexes, and isomers. The experiments revealed several novel effects which both enhance the power of RA 2DIR and bring a deeper understanding to the fundamental process of energy transport on a molecular level. We demonstrated that RA 2DIR can enhance greatly (27-fold) the cross-peak amplitude among spatially remote modes, which leads to an increase of the range of distances accessible for structural measurements by several fold. We demonstrated that the energy transport time correlates with the intermode distance. This correlation offers a new way for identifying connectivity patterns in molecules. We developed two models of energy transport in molecules. In one, a spatial overlap of vibrational modes determines the rate of energy transfer. Another model uses generalizations of Marcus theory of electron transfer applied to anharmonic vibrational transitions. These theoretical models reproduce well the main features of RA 2DIR measurements in a set of isomers where the energy transport is found to be affected by the three-dimensional structure as well as in transition-metal complexes, where the energy transport has to go through relatively weak coordination bonds and can be different from that occurring via covalent bonds.

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.

Predicting Molecular Crystal Properties from First Principles: Finite-Temperature Thermochemistry to NMR Crystallography.

PubMed

Beran, Gregory J O; Hartman, Joshua D; Heit, Yonaton N

2016-11-15

Molecular crystals occur widely in pharmaceuticals, foods, explosives, organic semiconductors, and many other applications. Thanks to substantial progress in electronic structure modeling of molecular crystals, attention is now shifting from basic crystal structure prediction and lattice energy modeling toward the accurate prediction of experimentally observable properties at finite temperatures and pressures. This Account discusses how fragment-based electronic structure methods can be used to model a variety of experimentally relevant molecular crystal properties. First, it describes the coupling of fragment electronic structure models with quasi-harmonic techniques for modeling the thermal expansion of molecular crystals, and what effects this expansion has on thermochemical and mechanical properties. Excellent agreement with experiment is demonstrated for the molar volume, sublimation enthalpy, entropy, and free energy, and the bulk modulus of phase I carbon dioxide when large basis second-order Møller-Plesset perturbation theory (MP2) or coupled cluster theories (CCSD(T)) are used. In addition, physical insight is offered into how neglect of thermal expansion affects these properties. Zero-point vibrational motion leads to an appreciable expansion in the molar volume; in carbon dioxide, it accounts for around 30% of the overall volume expansion between the electronic structure energy minimum and the molar volume at the sublimation point. In addition, because thermal expansion typically weakens the intermolecular interactions, neglecting thermal expansion artificially stabilizes the solid and causes the sublimation enthalpy to be too large at higher temperatures. Thermal expansion also frequently weakens the lower-frequency lattice phonon modes; neglecting thermal expansion causes the entropy of sublimation to be overestimated. Interestingly, the sublimation free energy is less significantly affected by neglecting thermal expansion because the systematic errors in the enthalpy and entropy cancel somewhat. Second, because solid state nuclear magnetic resonance (NMR) plays an increasingly important role in molecular crystal studies, this Account discusses how fragment methods can be used to achieve higher-accuracy chemical shifts in molecular crystals. Whereas widely used plane wave density functional theory models are largely restricted to generalized gradient approximation (GGA) functionals like PBE in practice, fragment methods allow the routine use of hybrid density functionals with only modest increases in computational cost. In extensive molecular crystal benchmarks, hybrid functionals like PBE0 predict chemical shifts with 20-30% higher accuracy than GGAs, particularly for 1 H, 13 C, and 15 N nuclei. Due to their higher sensitivity to polarization effects, 17 O chemical shifts prove slightly harder to predict with fragment methods. Nevertheless, the fragment model results are still competitive with those from GIPAW. The improved accuracy achievable with fragment approaches and hybrid density functionals increases discrimination between different potential assignments of individual shifts or crystal structures, which is critical in NMR crystallography applications. This higher accuracy and greater discrimination are highlighted in application to the solid state NMR of different acetaminophen and testosterone crystal forms.

An Observation of Diamond-Shaped Particle Structure in a Soya Phosphatidylcohline and Bacteriorhodopsin Composite Langmuir Blodgett Film Fabricated by Multilayer Molecular Thin Film Method

NASA Astrophysics Data System (ADS)

Tsujiuchi, Y.; Makino, Y.

A composite film of soya phosphatidylcohline (soya PC) and bacteriorhodopsin (BR) was fabricated by the multilayer molecular thin film method using fatty acid and lipid on a quartz substrate. Direct Force Microscopy (DFM), UV absorption spectra and IR absorption spectra of the film were characterized on the detail of surface structure of the film. The DFM data revealed that many rhombus (diamond-shaped) particles were observed in the film. The spectroscopic data exhibited the yield of M-intermediate of BR in the film. On our modelling of molecular configuration indicate that the coexistence of the strong inter-molecular interaction and the strong inter-molecular interaction between BR trimmers attributed to form the particles.

Coarse-graining to the meso and continuum scales with molecular-dynamics-like models

NASA Astrophysics Data System (ADS)

Plimpton, Steve

Many engineering-scale problems that industry or the national labs try to address with particle-based simulations occur at length and time scales well beyond the most optimistic hopes of traditional coarse-graining methods for molecular dynamics (MD), which typically start at the atomic scale and build upward. However classical MD can be viewed as an engine for simulating particles at literally any length or time scale, depending on the models used for individual particles and their interactions. To illustrate I'll highlight several coarse-grained (CG) materials models, some of which are likely familiar to molecular-scale modelers, but others probably not. These include models for water droplet freezing on surfaces, dissipative particle dynamics (DPD) models of explosives where particles have internal state, CG models of nano or colloidal particles in solution, models for aspherical particles, Peridynamics models for fracture, and models of granular materials at the scale of industrial processing. All of these can be implemented as MD-style models for either soft or hard materials; in fact they are all part of our LAMMPS MD package, added either by our group or contributed by collaborators. Unlike most all-atom MD simulations, CG simulations at these scales often involve highly non-uniform particle densities. So I'll also discuss a load-balancing method we've implemented for these kinds of models, which can improve parallel efficiencies. From the physics point-of-view, these models may be viewed as non-traditional or ad hoc. But because they are MD-style simulations, there's an opportunity for physicists to add statistical mechanics rigor to individual models. Or, in keeping with a theme of this session, to devise methods that more accurately bridge models from one scale to the next.

Hierarchical equations of motion method applied to nonequilibrium heat transport in model molecular junctions: Transient heat current and high-order moments of the current operator

NASA Astrophysics Data System (ADS)

Song, Linze; Shi, Qiang

2017-02-01

We present a theoretical approach to study nonequilibrium quantum heat transport in molecular junctions described by a spin-boson type model. Based on the Feynman-Vernon path integral influence functional formalism, expressions for the average value and high-order moments of the heat current operators are derived, which are further obtained directly from the auxiliary density operators (ADOs) in the hierarchical equations of motion (HEOM) method. Distribution of the heat current is then derived from the high-order moments. As the HEOM method is nonperturbative and capable of treating non-Markovian system-environment interactions, the method can be applied to various problems of nonequilibrium quantum heat transport beyond the weak coupling regime.

Theory of wavelet-based coarse-graining hierarchies for molecular dynamics.

PubMed

Rinderspacher, Berend Christopher; Bardhan, Jaydeep P; Ismail, Ahmed E

2017-07-01

We present a multiresolution approach to compressing the degrees of freedom and potentials associated with molecular dynamics, such as the bond potentials. The approach suggests a systematic way to accelerate large-scale molecular simulations with more than two levels of coarse graining, particularly applications of polymeric materials. In particular, we derive explicit models for (arbitrarily large) linear (homo)polymers and iterative methods to compute large-scale wavelet decompositions from fragment solutions. This approach does not require explicit preparation of atomistic-to-coarse-grained mappings, but instead uses the theory of diffusion wavelets for graph Laplacians to develop system-specific mappings. Our methodology leads to a hierarchy of system-specific coarse-grained degrees of freedom that provides a conceptually clear and mathematically rigorous framework for modeling chemical systems at relevant model scales. The approach is capable of automatically generating as many coarse-grained model scales as necessary, that is, to go beyond the two scales in conventional coarse-grained strategies; furthermore, the wavelet-based coarse-grained models explicitly link time and length scales. Furthermore, a straightforward method for the reintroduction of omitted degrees of freedom is presented, which plays a major role in maintaining model fidelity in long-time simulations and in capturing emergent behaviors.

Probing amyloid protein aggregation with optical superresolution methods: from the test tube to models of disease

PubMed Central

Kaminski, Clemens F.; Kaminski Schierle, Gabriele S.

2016-01-01

Abstract. The misfolding and self-assembly of intrinsically disordered proteins into insoluble amyloid structures are central to many neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases. Optical imaging of this self-assembly process in vitro and in cells is revolutionizing our understanding of the molecular mechanisms behind these devastating conditions. In contrast to conventional biophysical methods, optical imaging and, in particular, optical superresolution imaging, permits the dynamic investigation of the molecular self-assembly process in vitro and in cells, at molecular-level resolution. In this article, current state-of-the-art imaging methods are reviewed and discussed in the context of research into neurodegeneration. PMID:27413767

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

New analytic results for speciation times in neutral models.

PubMed

Gernhard, Tanja

2008-05-01

In this paper, we investigate the standard Yule model, and a recently studied model of speciation and extinction, the "critical branching process." We develop an analytic way-as opposed to the common simulation approach-for calculating the speciation times in a reconstructed phylogenetic tree. Simple expressions for the density and the moments of the speciation times are obtained. Methods for dating a speciation event become valuable, if for the reconstructed phylogenetic trees, no time scale is available. A missing time scale could be due to supertree methods, morphological data, or molecular data which violates the molecular clock. Our analytic approach is, in particular, useful for the model with extinction, since simulations of birth-death processes which are conditioned on obtaining n extant species today are quite delicate. Further, simulations are very time consuming for big n under both models.

Testing the molecular clock using mechanistic models of fossil preservation and molecular evolution

PubMed Central

2017-01-01

Molecular sequence data provide information about relative times only, and fossil-based age constraints are the ultimate source of information about absolute times in molecular clock dating analyses. Thus, fossil calibrations are critical to molecular clock dating, but competing methods are difficult to evaluate empirically because the true evolutionary time scale is never known. Here, we combine mechanistic models of fossil preservation and sequence evolution in simulations to evaluate different approaches to constructing fossil calibrations and their impact on Bayesian molecular clock dating, and the relative impact of fossil versus molecular sampling. We show that divergence time estimation is impacted by the model of fossil preservation, sampling intensity and tree shape. The addition of sequence data may improve molecular clock estimates, but accuracy and precision is dominated by the quality of the fossil calibrations. Posterior means and medians are poor representatives of true divergence times; posterior intervals provide a much more accurate estimate of divergence times, though they may be wide and often do not have high coverage probability. Our results highlight the importance of increased fossil sampling and improved statistical approaches to generating calibrations, which should incorporate the non-uniform nature of ecological and temporal fossil species distributions. PMID:28637852

The Computer Simulation of Liquids by Molecular Dynamics.

ERIC Educational Resources Information Center

Smith, W.

1987-01-01

Proposes a mathematical computer model for the behavior of liquids using the classical dynamic principles of Sir Isaac Newton and the molecular dynamics method invented by other scientists. Concludes that other applications will be successful using supercomputers to go beyond simple Newtonian physics. (CW)

Revealing chemophoric sites in organophosphorus insecticides through the MIA-QSPR modeling of soil sorption data.

PubMed

Daré, Joyce K; Silva, Cristina F; Freitas, Matheus P

2017-10-01

Soil sorption of insecticides employed in agriculture is an important parameter to probe the environmental fate of organic chemicals. Therefore, methods for the prediction of soil sorption of new agrochemical candidates, as well as for the rationalization of the molecular characteristics responsible for a given sorption profile, are extremely beneficial for the environment. A quantitative structure-property relationship method based on chemical structure images as molecular descriptors provided a reliable model for the soil sorption prediction of 24 widely used organophosphorus insecticides. By means of contour maps obtained from the partial least squares regression coefficients and the variable importance in projection scores, key molecular moieties were targeted for possible structural modification, in order to obtain novel and more environmentally friendly insecticide candidates. The image-based descriptors applied encode molecular arrangement, atoms connectivity, groups size, and polarity; consequently, the findings in this work cannot be achieved by a simple relationship with hydrophobicity, usually described by the octanol-water partition coefficient. Copyright © 2017 Elsevier Inc. All rights reserved.

Linear Response Path Following: A Molecular Dynamics Method To Simulate Global Conformational Changes of Protein upon Ligand Binding.

PubMed

Tamura, Koichi; Hayashi, Shigehiko

2015-07-14

Molecular functions of proteins are often fulfilled by global conformational changes that couple with local events such as the binding of ligand molecules. High molecular complexity of proteins has, however, been an obstacle to obtain an atomistic view of the global conformational transitions, imposing a limitation on the mechanistic understanding of the functional processes. In this study, we developed a new method of molecular dynamics (MD) simulation called the linear response path following (LRPF) to simulate a protein's global conformational changes upon ligand binding. The method introduces a biasing force based on a linear response theory, which determines a local reaction coordinate in the configuration space that represents linear coupling between local events of ligand binding and global conformational changes and thus provides one with fully atomistic models undergoing large conformational changes without knowledge of a target structure. The overall transition process involving nonlinear conformational changes is simulated through iterative cycles consisting of a biased MD simulation with an updated linear response force and a following unbiased MD simulation for relaxation. We applied the method to the simulation of global conformational changes of the yeast calmodulin N-terminal domain and successfully searched out the end conformation. The atomistically detailed trajectories revealed a sequence of molecular events that properly lead to the global conformational changes and identified key steps of local-global coupling that induce the conformational transitions. The LRPF method provides one with a powerful means to model conformational changes of proteins such as motors and transporters where local-global coupling plays a pivotal role in their functional processes.

Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

NASA Astrophysics Data System (ADS)

Zhang, Linfeng; Han, Jiequn; Wang, Han; Car, Roberto; E, Weinan

2018-04-01

We introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size.

A method of solid-solid phase equilibrium calculation by molecular dynamics

NASA Astrophysics Data System (ADS)

Karavaev, A. V.; Dremov, V. V.

2016-12-01

A method for evaluation of solid-solid phase equilibrium curves in molecular dynamics simulation for a given model of interatomic interaction is proposed. The method allows to calculate entropies of crystal phases and provides an accuracy comparable with that of the thermodynamic integration method by Frenkel and Ladd while it is much simpler in realization and less intense computationally. The accuracy of the proposed method was demonstrated in MD calculations of entropies for EAM potential for iron and for MEAM potential for beryllium. The bcc-hcp equilibrium curves for iron calculated for the EAM potential by the thermodynamic integration method and by the proposed one agree quite well.

Modeling Molecules

NASA Technical Reports Server (NTRS)

2000-01-01

The molecule modeling method known as Multibody Order (N) Dynamics, or MBO(N)D, was developed by Moldyn, Inc. at Goddard Space Flight Center through funding provided by the SBIR program. The software can model the dynamics of molecules through technology which stimulates low-frequency molecular motions and properties, such as movements among a molecule's constituent parts. With MBO(N)D, a molecule is substructured into a set of interconnected rigid and flexible bodies. These bodies replace the computation burden of mapping individual atoms. Moldyn's technology cuts computation time while increasing accuracy. The MBO(N)D technology is available as Insight II 97.0 from Molecular Simulations, Inc. Currently the technology is used to account for forces on spacecraft parts and to perform molecular analyses for pharmaceutical purposes. It permits the solution of molecular dynamics problems on a moderate workstation, as opposed to on a supercomputer.

Estimation of the molecular characteristics of polymers by the SPRT method and study of their influence on the properties of compositions

NASA Astrophysics Data System (ADS)

Kimel'blat, V. I.; Volfson, S. I.; Chebotareva, I. G.; Malysheva, T. V.

1998-09-01

Pressure relaxation was examined in the cylinder of an MPT Monsanto processability tester after stopping the piston. The experimental function of the pressure drop F(t) was smoothed over and approximated by cubic splines. The spectra of pressure relaxation times (SPRT) were obtained according to the method of Schwarzl-Staverman. The SPRT method served well for estimating the spectra of the molecular-mass distribution (MMD) of polymers close in their physical sense to the SPRT. The correlation of the characteristic relaxation times and average molecular mass of ethylene-propylene rubbers and polyethylenes obtained by gel permeation chromatography was approximated by optimum models used for calculating the the molecular mass of rubbers according to the measurement results of the relaxation pressure of melts. The SPRT and characteristic relaxation times were used to analyze the significant technical properties of compositions based on polyethylene and rubber. The SPRT method was used to examine the failure of the cure network of butyl rubber and the dependence of the mechanical properties of thermoplastic elastomers on the molecular features of the decomposite.

Hyper-polyhedron model applied to molecular screening of guanidines as Na/H exchange inhibitors.

PubMed

Bao, Xin-Hua; Lu, Wen-Cong; Liu, Liang; Chen, Nian-Yi

2003-05-01

To investigate structure-activity relationships of N-(3-Oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-carbonyl) guanidines in Na/H exchange inhibitory activities and probe into a new method of the computer-aided molecular screening. The hyper-polyhedron model (HPM) was proposed in our lab. The samples with probably higher activities could be determined in such a way that their representing points should be in the hyper-polyhedron region where all known samples with high activities were distributed. And the predictive ability of different methods available was tested by the cross-validation experiment. The accurate rate of molecular screening of N-(3-Oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-carbonyl) guanidines by HPM was much higher than that obtained by PCA (principal component analysis) and Fisher methods for the data set available here. Therefore, HPM could be used as a powerful tool for screening new compounds with probably higher activities.

Diffusion Coefficients from Molecular Dynamics Simulations in Binary and Ternary Mixtures

NASA Astrophysics Data System (ADS)

Liu, Xin; Schnell, Sondre K.; Simon, Jean-Marc; Krüger, Peter; Bedeaux, Dick; Kjelstrup, Signe; Bardow, André; Vlugt, Thijs J. H.

2013-07-01

Multicomponent diffusion in liquids is ubiquitous in (bio)chemical processes. It has gained considerable and increasing interest as it is often the rate limiting step in a process. In this paper, we review methods for calculating diffusion coefficients from molecular simulation and predictive engineering models. The main achievements of our research during the past years can be summarized as follows: (1) we introduced a consistent method for computing Fick diffusion coefficients using equilibrium molecular dynamics simulations; (2) we developed a multicomponent Darken equation for the description of the concentration dependence of Maxwell-Stefan diffusivities. In the case of infinite dilution, the multicomponent Darken equation provides an expression for [InlineEquation not available: see fulltext.] which can be used to parametrize the generalized Vignes equation; and (3) a predictive model for self-diffusivities was proposed for the parametrization of the multicomponent Darken equation. This equation accurately describes the concentration dependence of self-diffusivities in weakly associating systems. With these methods, a sound framework for the prediction of mutual diffusion in liquids is achieved.

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.

K-distribution models for gas mixtures in hypersonic nonequilibrium flows

NASA Astrophysics Data System (ADS)

Bansal, Ankit

Calculation of nonequilibrium radiation field in plasmas around a spacecraft entering into an atmosphere at hypersonic velocities is a very complicated and computationally expensive task. The objective of this Dissertation is to collect state-of-the art spectroscopic data for the evaluation of spectral absorption and emission coefficients of atomic and molecular gases, develop efficient and accurate spectral models and databases, and study the effect of radiation on wall heat loads and flowfield around the spacecraft. The most accurate simulation of radiative transport in the shock layer requires calculating the gas properties at a large number of wavelengths and solving the Radiative Transfer Equation (RTE) in a line-by-line (LBL) fashion, which is prohibitively expensive for coupled simulations. A number of k-distribution based spectral models are developed for atomic lines, continuum and molecular bands that allow efficient evaluation of radiative properties and heat loads in hypersonic shock layer plasma. Molecular radiation poses very different challenges than atomic radiation. A molecular spectrum is governed by simultaneous electronic, vibrational and rotational transitions, making the spectrum very strongly dependent on wavelength. In contrast to an atomic spectrum, where line wings play a major role in heat transfer, most of the heat transfer in molecular spectra occurs near line centers. As the first step, k-distribution models are developed separately for atomic and molecular species, taking advantage of the fact that in the Earth's atmosphere the radiative field is dominated by atomic species (N and O) and in Titan's and Mars' atmospheres molecular bands of CN and CO are dominant. There are a number of practical applications where both atomic and molecular species are present, for example, the vacuum-ultra-violet spectrum during Earth's reentry conditions is marked by emission from atomic bound-bound lines and continuum and simultaneous absorption by strong bands of N2. For such cases, a new model is developed for the treatment of gas mixtures containing atomic lines, continuum and molecular bands. Full-spectrum k-distribution (FSK) method provides very accurate results compared to those obtained from the exact line-by-line method. For cases involving more extreme gradients in species concentrations and temperature, full-spectrum k-distribution model is relatively less accurate, and the method is refined by dividing the spectrum into a number of groups or scales, leading to the development of multi-scale models. The detailed methodology of splitting the gas mixture into scales is presented. To utilize the full potential of the k-distribution methods, pre-calculated values of k-distributions are stored in databases, which can later be interpolated at local flow conditions. Accurate and compact part-spectrum k-distribution databases are developed for atomic species and molecular bands. These databases allow users to calculate desired full-spectrum k-distributions through look-up and interpolation. Application of the new spectral models and databases to shock layer plasma radiation is demonstrated by solving the radiative transfer equation along typical one-dimensional flowfields in Earth's, Titan's and Mars' atmospheres. The k-distribution methods are vastly more efficient than the line-by-line method. The efficiency of the method is compared with the line-by-line method by measuring computational times for a number of test problems, showing typical reduction in computational time by a factor of more than 500 for property evaluation and a factor of about 32,000 for the solution of the RTE. A large percentage of radiative energy emitted in the shock-layer is likely to escape the region, resulting in cooling of the shock layer. This may change the flow parameters in the flowfield and, in turn, can affect radiative as well as convective heat loads. A new flow solver is constructed to simulate coupled hypersonic flow-radiation over a reentry vehicle. The flow solver employs a number of existing schemes and tools available in OpenFOAM; along with a number of additional features for high temperature, compressible and chemically reacting flows, and k-distribution models for radiative calculations. The radiative transport is solved with the one-dimensional tangent slab and P1 solvers, and also with the two-dimensional P1 solver. The new solver is applied to simulate flow around an entry vehicle in Martian atmosphere. Results for uncoupled and coupled flow-radiation simulations are presented, highlighting the effects of radiative cooling on flowfield and wall fluxes.

Initiating heavy-atom-based phasing by multi-dimensional molecular replacement.

PubMed

Pedersen, Bjørn Panyella; Gourdon, Pontus; Liu, Xiangyu; Karlsen, Jesper Lykkegaard; Nissen, Poul

2016-03-01

To obtain an electron-density map from a macromolecular crystal the phase problem needs to be solved, which often involves the use of heavy-atom derivative crystals and concomitant heavy-atom substructure determination. This is typically performed by dual-space methods, direct methods or Patterson-based approaches, which however may fail when only poorly diffracting derivative crystals are available. This is often the case for, for example, membrane proteins. Here, an approach for heavy-atom site identification based on a molecular-replacement parameter matrix (MRPM) is presented. It involves an n-dimensional search to test a wide spectrum of molecular-replacement parameters, such as different data sets and search models with different conformations. Results are scored by the ability to identify heavy-atom positions from anomalous difference Fourier maps. The strategy was successfully applied in the determination of a membrane-protein structure, the copper-transporting P-type ATPase CopA, when other methods had failed to determine the heavy-atom substructure. MRPM is well suited to proteins undergoing large conformational changes where multiple search models should be considered, and it enables the identification of weak but correct molecular-replacement solutions with maximum contrast to prime experimental phasing efforts.

Initiating heavy-atom-based phasing by multi-dimensional molecular replacement

PubMed Central

Pedersen, Bjørn Panyella; Gourdon, Pontus; Liu, Xiangyu; Karlsen, Jesper Lykkegaard; Nissen, Poul

2016-01-01

To obtain an electron-density map from a macromolecular crystal the phase problem needs to be solved, which often involves the use of heavy-atom derivative crystals and concomitant heavy-atom substructure determination. This is typically performed by dual-space methods, direct methods or Patterson-based approaches, which however may fail when only poorly diffracting derivative crystals are available. This is often the case for, for example, membrane proteins. Here, an approach for heavy-atom site identification based on a molecular-replacement parameter matrix (MRPM) is presented. It involves an n-dimensional search to test a wide spectrum of molecular-replacement parameters, such as different data sets and search models with different conformations. Results are scored by the ability to identify heavy-atom positions from anomalous difference Fourier maps. The strategy was successfully applied in the determination of a membrane-protein structure, the copper-transporting P-type ATPase CopA, when other methods had failed to determine the heavy-atom substructure. MRPM is well suited to proteins undergoing large conformational changes where multiple search models should be considered, and it enables the identification of weak but correct molecular-replacement solutions with maximum contrast to prime experimental phasing efforts. PMID:26960131

Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement

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

Bibby, Jaclyn; Keegan, Ronan M.; Mayans, Olga

2013-11-01

Processing of NMR structures for molecular replacement by AMPLE works well. AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

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.

Knowledge environments representing molecular entities for the virtual physiological human.

PubMed

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

Histories of molecules: Reconciling the past.

PubMed

O'Malley, Maureen A

2016-02-01

Molecular data and methods have become centrally important to evolutionary analysis, largely because they have enabled global phylogenetic reconstructions of the relationships between organisms in the tree of life. Often, however, molecular stories conflict dramatically with morphology-based histories of lineages. The evolutionary origin of animal groups provides one such case. In other instances, different molecular analyses have so far proved irreconcilable. The ancient and major divergence of eukaryotes from prokaryotic ancestors is an example of this sort of problem. Efforts to overcome these conflicts highlight the role models play in phylogenetic reconstruction. One crucial model is the molecular clock; another is that of 'simple-to-complex' modification. I will examine animal and eukaryote evolution against a backdrop of increasing methodological sophistication in molecular phylogeny, and conclude with some reflections on the nature of historical science in the molecular era of phylogeny. Copyright © 2015 Elsevier Ltd. All rights reserved.

A model of how different biology experts explain molecular and cellular mechanisms.

PubMed

Trujillo, Caleb M; Anderson, Trevor R; Pelaez, Nancy J

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations. © 2015 C. M. Trujillo et al. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Investigation on the protein-binding properties of icotinib by spectroscopic and molecular modeling method.

PubMed

Zhang, Hua-xin; Xiong, Hang-xing; Li, Li-wei

2016-05-15

Icotinib is a highly-selective epidermal growth factor receptor tyrosine kinase inhibitor with preclinical and clinical activity in non-small cell lung cancer, which has been developed as a new targeted anti-tumor drug in China. In this work, the interaction of icotinib and human serum albumin (HSA) were studied by three-dimensional fluorescence spectra, ultraviolet spectra, circular dichroism (CD) spectra, molecular probe and molecular modeling methods. The results showed that icotinib binds to Sudlow's site I in subdomain IIA of HSA molecule, resulting in icotinib-HSA complexes formed at ground state. The number of binding sites, equilibrium constants, and thermodynamic parameters of the reaction were calculated at different temperatures. The negative enthalpy change (ΔH(θ)) and entropy change (ΔS(θ)) indicated that the structure of new complexes was stabilized by hydrogen bonds and van der Waals power. The distance between donor and acceptor was calculated according to Förster's non-radiation resonance energy transfer theory. The structural changes of HSA caused by icotinib binding were detected by synchronous spectra and circular dichroism (CD) spectra. Molecular modeling method was employed to unfold full details of the interaction at molecular level, most of which could be supported by experimental results. The study analyzed the probability that serum albumins act as carriers for this new anticarcinogen and provided fundamental information on the process of delivering icotinib to its target tissues, which might be helpful in understanding the mechanism of icotinib in cancer therapy. Copyright © 2016 Elsevier B.V. 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.

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.

Prediction of quantum interference in molecular junctions using a parabolic diagram: Understanding the origin of Fano and anti- resonances

NASA Astrophysics Data System (ADS)

Nozaki, Daijiro; Avdoshenko, Stanislav M.; Sevinçli, Hâldun; Gutierrez, Rafael; Cuniberti, Gianaurelio

2013-03-01

Recently the interest in quantum interference (QI) phenomena in molecular devices (molecular junctions) has been growing due to the unique features observed in the transmission spectra. In order to design single molecular devices exploiting QI effects as desired, it is necessary to provide simple rules for predicting the appearance of QI effects such as anti-resonances or Fano line shapes and for controlling them. In this study, we derive a transmission function of a generic molecular junction with a side group (T-shaped molecular junction) using a minimal toy model. We developed a simple method to predict the appearance of quantum interference, Fano resonances or anti- resonances, and its position in the conductance spectrum by introducing a simple graphical representation (parabolic model). Using it we can easily visualize the relation between the key electronic parameters and the positions of normal resonant peaks and anti-resonant peaks induced by quantum interference in the conductance spectrum. We also demonstrate Fano and anti-resonance in T-shaped molecular junctions using a simple tight-binding model. This parabolic model enables one to infer on-site energies of T-shaped molecules and the coupling between side group and main conduction channel from transmission spectra.

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.

Determining polarizable force fields with electrostatic potentials from quantum mechanical linear response theory

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

Wang, Hao; Yang, Weitao, E-mail: weitao.yang@duke.edu; Department of Physics, Duke University, Durham, North Carolina 27708

We developed a new method to calculate the atomic polarizabilities by fitting to the electrostatic potentials (ESPs) obtained from quantum mechanical (QM) calculations within the linear response theory. This parallels the conventional approach of fitting atomic charges based on electrostatic potentials from the electron density. Our ESP fitting is combined with the induced dipole model under the perturbation of uniform external electric fields of all orientations. QM calculations for the linear response to the external electric fields are used as input, fully consistent with the induced dipole model, which itself is a linear response model. The orientation of the uniformmore » external electric fields is integrated in all directions. The integration of orientation and QM linear response calculations together makes the fitting results independent of the orientations and magnitudes of the uniform external electric fields applied. Another advantage of our method is that QM calculation is only needed once, in contrast to the conventional approach, where many QM calculations are needed for many different applied electric fields. The molecular polarizabilities obtained from our method show comparable accuracy with those from fitting directly to the experimental or theoretical molecular polarizabilities. Since ESP is directly fitted, atomic polarizabilities obtained from our method are expected to reproduce the electrostatic interactions better. Our method was used to calculate both transferable atomic polarizabilities for polarizable molecular mechanics’ force fields and nontransferable molecule-specific atomic polarizabilities.« less

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

Free energy landscapes of small peptides in an implicit solvent model determined by force-biased multicanonical molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Watanabe, Yukihisa S.; Kim, Jae Gil; Fukunishi, Yoshifumi; Nakamura, Haruki

2004-12-01

In order to investigate whether the implicit solvent (GB/SA) model could reproduce the free energy landscapes of peptides, the potential of mean forces (PMFs) of eight tripeptides was examined and compared with the PMFs of the explicit water model. The force-biased multicanonical molecular dynamics method was used for the enhanced conformational sampling. Consequently, the GB/SA model reproduced almost all the global and local minima in the PMFs observed with the explicit water model. However, the GB/SA model overestimated frequencies of the structures that are stabilized by intra-peptide hydrogen bonds.

Advances in the mechanical modeling of filamentous actin and its cross-linked networks on multiple scales.

PubMed

Unterberger, Michael J; Holzapfel, Gerhard A

2014-11-01

The protein actin is a part of the cytoskeleton and, therefore, responsible for the mechanical properties of the cells. Starting with the single molecule up to the final structure, actin creates a hierarchical structure of several levels exhibiting a remarkable behavior. The hierarchy spans several length scales and limitations in computational power; therefore, there is a call for different mechanical modeling approaches for the different scales. On the molecular level, we may consider each atom in molecular dynamics simulations. Actin forms filaments by combining the molecules into a double helix. In a model, we replace molecular subdomains using coarse-graining methods, allowing the investigation of larger systems of several atoms. These models on the nanoscale inform continuum mechanical models of large filaments, which are based on worm-like chain models for polymers. Assemblies of actin filaments are connected with cross-linker proteins. Models with discrete filaments, so-called Mikado models, allow us to investigate the dependence of the properties of networks on the parameters of the constituents. Microstructurally motivated continuum models of the networks provide insights into larger systems containing cross-linked actin networks. Modeling of such systems helps to gain insight into the processes on such small scales. On the other hand, they call for verification and hence trigger the improvement of established experiments and the development of new methods.

Transport properties and efficiency of elastically coupled particles in asymmetric periodic potentials

NASA Astrophysics Data System (ADS)

Igarashi, Akito; Tsukamoto, Shinji

2000-02-01

Biological molecular motors drive unidirectional transport and transduce chemical energy to mechanical work. In order to identify this energy conversion which is a common feature of molecular motors, many workers have studied various physical models, which consist of Brownian particles in spatially periodic potentials. Most of the models are, however, based on "single-particle" dynamics and too simple as models for biological motors, especially for actin-myosin motors, which cause muscle contraction. In this paper, particles coupled by elastic strings in an asymmetric periodic potential are considered as a model for the motors. We investigate the dynamics of the model and calculate the efficiency of energy conversion with the use of molecular dynamical method. In particular, we find that the velocity and efficiency of the elastically coupled particles where the natural length of the springs is incommensurable with the period of the periodic potential are larger than those of the corresponding single particle model.

Simulating the flow of entangled polymers.

PubMed

Masubuchi, Yuichi

2014-01-01

To optimize automation for polymer processing, attempts have been made to simulate the flow of entangled polymers. In industry, fluid dynamics simulations with phenomenological constitutive equations have been practically established. However, to account for molecular characteristics, a method to obtain the constitutive relationship from the molecular structure is required. Molecular dynamics simulations with atomic description are not practical for this purpose; accordingly, coarse-grained models with reduced degrees of freedom have been developed. Although the modeling of entanglement is still a challenge, mesoscopic models with a priori settings to reproduce entangled polymer dynamics, such as tube models, have achieved remarkable success. To use the mesoscopic models as staging posts between atomistic and fluid dynamics simulations, studies have been undertaken to establish links from the coarse-grained model to the atomistic and macroscopic simulations. Consequently, integrated simulations from materials chemistry to predict the macroscopic flow in polymer processing are forthcoming.

Recent Developments and Applications of the MMPBSA Method

PubMed Central

Wang, Changhao; Greene, D'Artagnan; Xiao, Li; Qi, Ruxi; Luo, Ray

2018-01-01

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method. PMID:29367919

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%.

Nonholonomic Hamiltonian Method for Molecular Dynamics Simulations of Reacting Shocks

NASA Astrophysics Data System (ADS)

Fahrenthold, Eric; Bass, Joseph

2015-06-01

Conventional molecular dynamics simulations of reacting shocks employ a holonomic Hamiltonian formulation: the breaking and forming of covalent bonds is described by potential functions. In general these potential functions: (a) are algebraically complex, (b) must satisfy strict smoothness requirements, and (c) contain many fitted parameters. In recent research the authors have developed a new noholonomic formulation of reacting molecular dynamics. In this formulation bond orders are determined by rate equations and the bonding-debonding process need not be described by differentiable functions. This simplifies the representation of complex chemistry and reduces the number of fitted model parameters. Example applications of the method show molecular level shock to detonation simulations in nitromethane and RDX. Research supported by the Defense Threat Reduction Agency.

Molecular simulations of carbohydrates and protein-carbohydrate interactions: motivation, issues and prospects

PubMed Central

Fadda, Elisa; Woods, Robert J.

2014-01-01

The characterization of the 3D structure of oligosaccharides, their conjugates and analogs is particularly challenging for traditional experimental methods. Molecular simulation methods provide a basis for interpreting sparse experimental data and for independently predicting conformational and dynamic properties of glycans. Here, we summarize and analyze the issues associated with modeling carbohydrates, with a detailed discussion of four of the most recently developed carbohydrate force fields, reviewed in terms of applicability to natural glycans, carbohydrate–protein complexes and the emerging area of glycomimetic drugs. In addition, we discuss prospectives and new applications of carbohydrate modeling in drug discovery. PMID:20594934

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

NASA Astrophysics Data System (ADS)

Petsev, Nikolai D.; Leal, L. Gary; Shell, M. Scott

2017-12-01

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely resolved (e.g., molecular dynamics) and coarse-grained (e.g., continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 084115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics. An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.

DNA-binding study of anticancer drug cytarabine by spectroscopic and molecular docking techniques.

PubMed

Shahabadi, Nahid; Falsafi, Monireh; Maghsudi, Maryam

2017-01-02

The interaction of anticancer drug cytarabine with calf thymus DNA (CT-DNA) was investigated in vitro under simulated physiological conditions by multispectroscopic techniques and molecular modeling study. The fluorescence spectroscopy and UV absorption spectroscopy indicated drug interacted with CT-DNA in a groove-binding mode, while the binding constant of UV-vis and the number of binding sites were 4.0 ± 0.2 × 10 4 L mol -1 and 1.39, respectively. The fluorimetric studies showed that the reaction between the drugs with CT-DNA is exothermic. Circular dichroism spectroscopy was employed to measure the conformational change of DNA in the presence of cytarabine. Furthermore, the drug induces detectable changes in its viscosity for DNA interaction. The molecular modeling results illustrated that cytarabine strongly binds to groove of DNA by relative binding energy of docked structure -20.61 KJ mol -1 . This combination of multiple spectroscopic techniques and molecular modeling methods can be widely used in the investigation on the interaction of small molecular pollutants and drugs with biomacromolecules for clarifying the molecular mechanism of toxicity or side effect in vivo.

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

A fast recursive algorithm for molecular dynamics simulation

NASA Technical Reports Server (NTRS)

Jain, A.; Vaidehi, N.; Rodriguez, G.

1993-01-01

The present recursive algorithm for solving molecular systems' dynamical equations of motion employs internal variable models that reduce such simulations' computation time by an order of magnitude, relative to Cartesian models. Extensive use is made of spatial operator methods recently developed for analysis and simulation of the dynamics of multibody systems. A factor-of-450 speedup over the conventional O(N-cubed) algorithm is demonstrated for the case of a polypeptide molecule with 400 residues.

Modeling charge transport in organic photovoltaic materials.

PubMed

Nelson, Jenny; Kwiatkowski, Joe J; Kirkpatrick, James; Frost, Jarvist M

2009-11-17

The performance of an organic photovoltaic cell depends critically on the mobility of charge carriers within the constituent molecular semiconductor materials. However, a complex combination of phenomena that span a range of length and time scales control charge transport in disordered organic semiconductors. As a result, it is difficult to rationalize charge transport properties in terms of material parameters. Until now, efforts to improve charge mobilities in molecular semiconductors have proceeded largely by trial and error rather than through systematic design. However, recent developments have enabled the first predictive simulation studies of charge transport in disordered organic semiconductors. This Account describes a set of computational methods, specifically molecular modeling methods, to simulate molecular packing, quantum chemical calculations of charge transfer rates, and Monte Carlo simulations of charge transport. Using case studies, we show how this combination of methods can reproduce experimental mobilities with few or no fitting parameters. Although currently applied to material systems of high symmetry or well-defined structure, further developments of this approach could address more complex systems such anisotropic or multicomponent solids and conjugated polymers. Even with an approximate treatment of packing disorder, these computational methods simulate experimental mobilities within an order of magnitude at high electric fields. We can both reproduce the relative values of electron and hole mobility in a conjugated small molecule and rationalize those values based on the symmetry of frontier orbitals. Using fully atomistic molecular dynamics simulations of molecular packing, we can quantitatively replicate vertical charge transport along stacks of discotic liquid crystals which vary only in the structure of their side chains. We can reproduce the trends in mobility with molecular weight for self-organizing polymers using a cheap, coarse-grained structural simulation method. Finally, we quantitatively reproduce the field-effect mobility in disordered C60 films. On the basis of these results, we conclude that all of the necessary building blocks are in place for the predictive simulation of charge transport in macromolecular electronic materials and that such methods can be used as a tool toward the future rational design of functional organic electronic materials.

Fragmentation-based QM/MM simulations: length dependence of chain dynamics and hydrogen bonding of polyethylene oxide and polyethylene in aqueous solutions.

PubMed

Li, Hui; Li, Wei; Li, Shuhua; Ma, Jing

2008-06-12

Molecular fragmentation quantum mechanics (QM) calculations have been combined with molecular mechanics (MM) to construct the fragmentation QM/MM method for simulations of dilute solutions of macromolecules. We adopt the electrostatics embedding QM/MM model, where the low-cost generalized energy-based fragmentation calculations are employed for the QM part. Conformation energy calculations, geometry optimizations, and Born-Oppenheimer molecular dynamics simulations of poly(ethylene oxide), PEO(n) (n = 6-20), and polyethylene, PE(n) ( n = 9-30), in aqueous solution have been performed within the framework of both fragmentation and conventional QM/MM methods. The intermolecular hydrogen bonding and chain configurations obtained from the fragmentation QM/MM simulations are consistent with the conventional QM/MM method. The length dependence of chain conformations and dynamics of PEO and PE oligomers in aqueous solutions is also investigated through the fragmentation QM/MM molecular dynamics simulations.

Application of the artificial neural network in quantitative structure-gradient elution retention relationship of phenylthiocarbamyl amino acids derivatives.

PubMed

Tham, S Y; Agatonovic-Kustrin, S

2002-05-15

Quantitative structure-retention relationship(QSRR) method was used to model reversed-phase high-performance liquid chromatography (RP-HPLC) separation of 18 selected amino acids. Retention data for phenylthiocarbamyl (PTC) amino acids derivatives were obtained using gradient elution on ODS column with mobile phase of varying acetonitrile, acetate buffer and containing 0.5 ml/l of triethylamine (TEA). Molecular structure of each amino acid was encoded with 36 calculated molecular descriptors. The correlation between the molecular descriptors and the retention time of the compounds in the calibration set was established using the genetic neural network method. A genetic algorithm (GA) was used to select important molecular descriptors and supervised artificial neural network (ANN) was used to correlate mobile phase composition and selected descriptors with the experimentally derived retention times. Retention time values were used as the network's output and calculated molecular descriptors and mobile phase composition as the inputs. The best model with five input descriptors was chosen, and the significance of the selected descriptors for amino acid separation was examined. Results confirmed the dominant role of the organic modifier in such chromatographic systems in addition to lipophilicity (log P) and molecular size and shape (topological indices) of investigated solutes.

A study on the plasticity of soda-lime silica glass via molecular dynamics simulations.

PubMed

Urata, Shingo; Sato, Yosuke

2017-11-07

Molecular dynamics (MD) simulations were applied to construct a plasticity model, which enables one to simulate deformations of soda-lime silica glass (SLSG) by using continuum methods. To model the plasticity, stress induced by uniaxial and a variety of biaxial deformations was measured by MD simulations. We found that the surfaces of yield and maximum stresses, which are evaluated from the equivalent stress-strain curves, are reasonably represented by the Mohr-Coulomb ellipsoid. Comparing a finite element model using the constructed plasticity model to a large scale atomistic model on a nanoindentation simulation of SLSG reveals that the empirical method is accurate enough to evaluate the SLSG mechanical responses. Furthermore, the effect of ion-exchange on the SLSG plasticity was examined by using MD simulations. As a result, it was demonstrated that the effects of the initial compressive stress on the yield and maximum stresses are anisotropic contrary to our expectations.

A study on the plasticity of soda-lime silica glass via molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Urata, Shingo; Sato, Yosuke

2017-11-01

Molecular dynamics (MD) simulations were applied to construct a plasticity model, which enables one to simulate deformations of soda-lime silica glass (SLSG) by using continuum methods. To model the plasticity, stress induced by uniaxial and a variety of biaxial deformations was measured by MD simulations. We found that the surfaces of yield and maximum stresses, which are evaluated from the equivalent stress-strain curves, are reasonably represented by the Mohr-Coulomb ellipsoid. Comparing a finite element model using the constructed plasticity model to a large scale atomistic model on a nanoindentation simulation of SLSG reveals that the empirical method is accurate enough to evaluate the SLSG mechanical responses. Furthermore, the effect of ion-exchange on the SLSG plasticity was examined by using MD simulations. As a result, it was demonstrated that the effects of the initial compressive stress on the yield and maximum stresses are anisotropic contrary to our expectations.

Predicting absorption and dispersion in acoustics by direct simulation Monte Carlo: Quantum and classical models for molecular relaxation.

PubMed

Hanford, Amanda D; O'Connor, Patrick D; Anderson, James B; Long, Lyle N

2008-06-01

In the current study, real gas effects in the propagation of sound waves are simulated using the direct simulation Monte Carlo method for a wide range of frequencies. This particle method allows for treatment of acoustic phenomena at high Knudsen numbers, corresponding to low densities and a high ratio of the molecular mean free path to wavelength. Different methods to model the internal degrees of freedom of diatomic molecules and the exchange of translational, rotational and vibrational energies in collisions are employed in the current simulations of a diatomic gas. One of these methods is the fully classical rigid-rotor/harmonic-oscillator model for rotation and vibration. A second method takes into account the discrete quantum energy levels for vibration with the closely spaced rotational levels classically treated. This method gives a more realistic representation of the internal structure of diatomic and polyatomic molecules. Applications of these methods are investigated in diatomic nitrogen gas in order to study the propagation of sound and its attenuation and dispersion along with their dependence on temperature. With the direct simulation method, significant deviations from continuum predictions are also observed for high Knudsen number flows.

Photoluminescence of Ta2O5 films formed by the molecular layer deposition method

NASA Astrophysics Data System (ADS)

Baraban, A. P.; Dmitriev, V. A.; Prokof'ev, V. A.; Drozd, V. E.; Filatova, E. O.

2016-04-01

Ta2O5 films of different thicknesses (20-100 nm) synthesized by the molecular layer deposition method on p-type silicon substrates and thermally oxidized silicon substrates have been studied by the methods of high-frequency capacitance-voltage characteristics and photoluminescence. A hole-conduction channel is found to form in the Si-Ta2O5-field electrode system. A model of the electronic structure of Ta2O5 films is proposed based on an analysis of the measured PL spectra and performed electrical investigations.

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 modeling of polycarbonate materials: Glass transition and mechanical properties

NASA Astrophysics Data System (ADS)

Palczynski, Karol; Wilke, Andreas; Paeschke, Manfred; Dzubiella, Joachim

2017-09-01

Linking the experimentally accessible macroscopic properties of thermoplastic polymers to their microscopic static and dynamic properties is a key requirement for targeted material design. Classical molecular dynamics simulations enable us to study the structural and dynamic behavior of molecules on microscopic scales, and statistical physics provides a framework for relating these properties to the macroscopic properties. We take a first step toward creating an automated workflow for the theoretical prediction of thermoplastic material properties by developing an expeditious method for parameterizing a simple yet surprisingly powerful coarse-grained bisphenol-A polycarbonate model which goes beyond previous coarse-grained models and successfully reproduces the thermal expansion behavior, the glass transition temperature as a function of the molecular weight, and several elastic properties.

Statistical physics approaches to Alzheimer's disease

NASA Astrophysics Data System (ADS)

Peng, Shouyong

Alzheimer's disease (AD) is the most common cause of late life dementia. In the brain of an AD patient, neurons are lost and spatial neuronal organizations (microcolumns) are disrupted. An adequate quantitative analysis of microcolumns requires that we automate the neuron recognition stage in the analysis of microscopic images of human brain tissue. We propose a recognition method based on statistical physics. Specifically, Monte Carlo simulations of an inhomogeneous Potts model are applied for image segmentation. Unlike most traditional methods, this method improves the recognition of overlapped neurons, and thus improves the overall recognition percentage. Although the exact causes of AD are unknown, as experimental advances have revealed the molecular origin of AD, they have continued to support the amyloid cascade hypothesis, which states that early stages of aggregation of amyloid beta (Abeta) peptides lead to neurodegeneration and death. X-ray diffraction studies reveal the common cross-beta structural features of the final stable aggregates-amyloid fibrils. Solid-state NMR studies also reveal structural features for some well-ordered fibrils. But currently there is no feasible experimental technique that can reveal the exact structure or the precise dynamics of assembly and thus help us understand the aggregation mechanism. Computer simulation offers a way to understand the aggregation mechanism on the molecular level. Because traditional all-atom continuous molecular dynamics simulations are not fast enough to investigate the whole aggregation process, we apply coarse-grained models and discrete molecular dynamics methods to increase the simulation speed. First we use a coarse-grained two-bead (two beads per amino acid) model. Simulations show that peptides can aggregate into multilayer beta-sheet structures, which agree with X-ray diffraction experiments. To better represent the secondary structure transition happening during aggregation, we refine the model to four beads per amino acid. Typical essential interactions, such as backbone hydrogen bond, hydrophobic and electrostatic interactions, are incorporated into our model. We study the aggregation of Abeta16-22, a peptide that can aggregate into a well-ordered fibrillar structure in experiments. Our results show that randomly-oriented monomers can aggregate into fibrillar subunits, which agree not only with X-ray diffraction experiments but also with solid-state NMR studies. Our findings demonstrate that coarse-grained models and discrete molecular dynamics simulations can help researchers understand the aggregation mechanism of amyloid peptides.

Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models

NASA Astrophysics Data System (ADS)

Zang, Tianwu

Predicting the 3-dimentional structure of protein has been a major interest in the modern computational biology. While lots of successful methods can generate models with 3˜5A root-mean-square deviation (RMSD) from the solution, the progress of refining these models is quite slow. It is therefore urgently needed to develop effective methods to bring low-quality models to higher-accuracy ranges (e.g., less than 2 A RMSD). In this thesis, I present several novel computational methods to address the high-accuracy refinement problem. First, an enhanced sampling method, named parallel continuous simulated tempering (PCST), is developed to accelerate the molecular dynamics (MD) simulation. Second, two energy biasing methods, Structure-Based Model (SBM) and Ensemble-Based Model (EBM), are introduced to perform targeted sampling around important conformations. Third, a three-step method is developed to blindly select high-quality models along the MD simulation. These methods work together to make significant refinement of low-quality models without any knowledge of the solution. The effectiveness of these methods is examined in different applications. Using the PCST-SBM method, models with higher global distance test scores (GDT_TS) are generated and selected in the MD simulation of 18 targets from the refinement category of the 10th Critical Assessment of Structure Prediction (CASP10). In addition, in the refinement test of two CASP10 targets using the PCST-EBM method, it is indicated that EBM may bring the initial model to even higher-quality levels. Furthermore, a multi-round refinement protocol of PCST-SBM improves the model quality of a protein to the level that is sufficient high for the molecular replacement in X-ray crystallography. Our results justify the crucial position of enhanced sampling in the protein structure prediction and demonstrate that a considerable improvement of low-accuracy structures is still achievable with current force fields.

SAMPL4 & DOCK3.7: lessons for automated docking procedures

NASA Astrophysics Data System (ADS)

Coleman, Ryan G.; Sterling, Teague; Weiss, Dahlia R.

2014-03-01

The SAMPL4 challenges were used to test current automated methods for solvation energy, virtual screening, pose and affinity prediction of the molecular docking pipeline DOCK 3.7. Additionally, first-order models of binding affinity were proposed as milestones for any method predicting binding affinity. Several important discoveries about the molecular docking software were made during the challenge: (1) Solvation energies of ligands were five-fold worse than any other method used in SAMPL4, including methods that were similarly fast, (2) HIV Integrase is a challenging target, but automated docking on the correct allosteric site performed well in terms of virtual screening and pose prediction (compared to other methods) but affinity prediction, as expected, was very poor, (3) Molecular docking grid sizes can be very important, serious errors were discovered with default settings that have been adjusted for all future work. Overall, lessons from SAMPL4 suggest many changes to molecular docking tools, not just DOCK 3.7, that could improve the state of the art. Future difficulties and projects will be discussed.

`Inter-Arrival Time' Inspired Algorithm and its Application in Clustering and Molecular Phylogeny

NASA Astrophysics Data System (ADS)

Kolekar, Pandurang S.; Kale, Mohan M.; Kulkarni-Kale, Urmila

2010-10-01

Bioinformatics, being multidisciplinary field, involves applications of various methods from allied areas of Science for data mining using computational approaches. Clustering and molecular phylogeny is one of the key areas in Bioinformatics, which help in study of classification and evolution of organisms. Molecular phylogeny algorithms can be divided into distance based and character based methods. But most of these methods are dependent on pre-alignment of sequences and become computationally intensive with increase in size of data and hence demand alternative efficient approaches. `Inter arrival time distribution' (IATD) is a popular concept in the theory of stochastic system modeling but its potential in molecular data analysis has not been fully explored. The present study reports application of IATD in Bioinformatics for clustering and molecular phylogeny. The proposed method provides IATDs of nucleotides in genomic sequences. The distance function based on statistical parameters of IATDs is proposed and distance matrix thus obtained is used for the purpose of clustering and molecular phylogeny. The method is applied on a dataset of 3' non-coding region sequences (NCR) of Dengue virus type 3 (DENV-3), subtype III, reported in 2008. The phylogram thus obtained revealed the geographical distribution of DENV-3 isolates. Sri Lankan DENV-3 isolates were further observed to be clustered in two sub-clades corresponding to pre and post Dengue hemorrhagic fever emergence groups. These results are consistent with those reported earlier, which are obtained using pre-aligned sequence data as an input. These findings encourage applications of the IATD based method in molecular phylogenetic analysis in particular and data mining in general.

Quantitative computational models of molecular self-assembly in systems biology

PubMed Central

Thomas, Marcus; Schwartz, Russell

2017-01-01

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally. PMID:28535149

Quantitative computational models of molecular self-assembly in systems biology.

PubMed

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

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.

Testing the molecular clock using mechanistic models of fossil preservation and molecular evolution.

PubMed

Warnock, Rachel C M; Yang, Ziheng; Donoghue, Philip C J

2017-06-28

Molecular sequence data provide information about relative times only, and fossil-based age constraints are the ultimate source of information about absolute times in molecular clock dating analyses. Thus, fossil calibrations are critical to molecular clock dating, but competing methods are difficult to evaluate empirically because the true evolutionary time scale is never known. Here, we combine mechanistic models of fossil preservation and sequence evolution in simulations to evaluate different approaches to constructing fossil calibrations and their impact on Bayesian molecular clock dating, and the relative impact of fossil versus molecular sampling. We show that divergence time estimation is impacted by the model of fossil preservation, sampling intensity and tree shape. The addition of sequence data may improve molecular clock estimates, but accuracy and precision is dominated by the quality of the fossil calibrations. Posterior means and medians are poor representatives of true divergence times; posterior intervals provide a much more accurate estimate of divergence times, though they may be wide and often do not have high coverage probability. Our results highlight the importance of increased fossil sampling and improved statistical approaches to generating calibrations, which should incorporate the non-uniform nature of ecological and temporal fossil species distributions. © 2017 The Authors.

Path-space variational inference for non-equilibrium coarse-grained systems

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

Harmandaris, Vagelis, E-mail: harman@uoc.gr; Institute of Applied and Computational Mathematics; Kalligiannaki, Evangelia, E-mail: ekalligian@tem.uoc.gr

In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirelymore » data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.« less

Cross-validation to select Bayesian hierarchical models in phylogenetics.

PubMed

Duchêne, Sebastián; Duchêne, David A; Di Giallonardo, Francesca; Eden, John-Sebastian; Geoghegan, Jemma L; Holt, Kathryn E; Ho, Simon Y W; Holmes, Edward C

2016-05-26

Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance. We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models. Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult.

A Lattice Boltzmann Method for Turbomachinery Simulations

NASA Technical Reports Server (NTRS)

Hsu, A. T.; Lopez, I.

2003-01-01

Lattice Boltzmann (LB) Method is a relatively new method for flow simulations. The start point of LB method is statistic mechanics and Boltzmann equation. The LB method tries to set up its model at molecular scale and simulate the flow at macroscopic scale. LBM has been applied to mostly incompressible flows and simple geometry.

MIDG-Emerging grid technologies for multi-site preclinical molecular imaging research communities.

PubMed

Lee, Jasper; Documet, Jorge; Liu, Brent; Park, Ryan; Tank, Archana; Huang, H K

2011-03-01

Molecular imaging is the visualization and identification of specific molecules in anatomy for insight into metabolic pathways, tissue consistency, and tracing of solute transport mechanisms. This paper presents the Molecular Imaging Data Grid (MIDG) which utilizes emerging grid technologies in preclinical molecular imaging to facilitate data sharing and discovery between preclinical molecular imaging facilities and their collaborating investigator institutions to expedite translational sciences research. Grid-enabled archiving, management, and distribution of animal-model imaging datasets help preclinical investigators to monitor, access and share their imaging data remotely, and promote preclinical imaging facilities to share published imaging datasets as resources for new investigators. The system architecture of the Molecular Imaging Data Grid is described in a four layer diagram. A data model for preclinical molecular imaging datasets is also presented based on imaging modalities currently used in a molecular imaging center. The MIDG system components and connectivity are presented. And finally, the workflow steps for grid-based archiving, management, and retrieval of preclincial molecular imaging data are described. Initial performance tests of the Molecular Imaging Data Grid system have been conducted at the USC IPILab using dedicated VMware servers. System connectivity, evaluated datasets, and preliminary results are presented. The results show the system's feasibility, limitations, direction of future research. Translational and interdisciplinary research in medicine is increasingly interested in cellular and molecular biology activity at the preclinical levels, utilizing molecular imaging methods on animal models. The task of integrated archiving, management, and distribution of these preclinical molecular imaging datasets at preclinical molecular imaging facilities is challenging due to disparate imaging systems and multiple off-site investigators. A Molecular Imaging Data Grid design, implementation, and initial evaluation is presented to demonstrate the secure and novel data grid solution for sharing preclinical molecular imaging data across the wide-area-network (WAN).

Indirect measurement of diluents in a multi-component natural gas

DOEpatents

Morrow, Thomas B.; Owen, Thomas E.

2006-03-07

A method of indirectly measuring the diluent (nitrogen and carbon dioxide) concentrations in a natural gas mixture. The molecular weight of the gas is modeled as a function of the speed of sound in the gas, the diluent concentrations in the gas, and constant values, resulting in a model equation. A set of reference gas mixtures with known molecular weights and diluent concentrations is used to calculate the constant values. For the gas in question, if the speed of sound in the gas is measured at three states, the three resulting expressions of molecular weight can be solved for the nitrogen and carbon dioxide concentrations in the gas mixture.

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.

Ultra-Low Threshold Vertical-Cavity Surface-Emitting Lasers for USAF Applications

DTIC Science & Technology

2005-01-01

molecular beam epitaxy , semiconductors, finite element method, modeling and simulation, oxidation furnace 16. SECURITY CLASSIFICATION OF: 19a. NAME OF...Patterson Air Force Base). Device material growth was accomplished by means of molecular beam epitaxy (MBE) using a Varian GENII MBE system owned by the...grown by molecular beam epitaxy on a GaAs substrate. Vertical posts, with square and circular cross sections ranging in size from 5 to 40 microns

Molecular Modeling on Berberine Derivatives toward BuChE: An Integrated Study with Quantitative Structure-Activity Relationships Models, Molecular Docking, and Molecular Dynamics Simulations.

PubMed

Fang, Jiansong; Pang, Xiaocong; Wu, Ping; Yan, Rong; Gao, Li; Li, Chao; Lian, Wenwen; Wang, Qi; Liu, Ai-lin; Du, Guan-hua

2016-05-01

A dataset of 67 berberine derivatives for the inhibition of butyrylcholinesterase (BuChE) was studied based on the combination of quantitative structure-activity relationships models, molecular docking, and molecular dynamics methods. First, a series of berberine derivatives were reported, and their inhibitory activities toward butyrylcholinesterase (BuChE) were evaluated. By 2D- quantitative structure-activity relationships studies, the best model built by partial least-square had a conventional correlation coefficient of the training set (R(2)) of 0.883, a cross-validation correlation coefficient (Qcv2) of 0.777, and a conventional correlation coefficient of the test set (Rpred2) of 0.775. The model was also confirmed by Y-randomization examination. In addition, the molecular docking and molecular dynamics simulation were performed to better elucidate the inhibitory mechanism of three typical berberine derivatives (berberine, C2, and C55) toward BuChE. The predicted binding free energy results were consistent with the experimental data and showed that the van der Waals energy term (ΔEvdw) difference played the most important role in differentiating the activity among the three inhibitors (berberine, C2, and C55). The developed quantitative structure-activity relationships models provide details on the fine relationship linking structure and activity and offer clues for structural modifications, and the molecular simulation helps to understand the inhibitory mechanism of the three typical inhibitors. In conclusion, the results of this study provide useful clues for new drug design and discovery of BuChE inhibitors from berberine derivatives. © 2015 John Wiley & Sons A/S.

3D-QSAR modeling and molecular docking studies on a series of 2,5 disubstituted 1,3,4-oxadiazoles

NASA Astrophysics Data System (ADS)

Ghaleb, Adib; Aouidate, Adnane; Ghamali, Mounir; Sbai, Abdelouahid; Bouachrine, Mohammed; Lakhlifi, Tahar

2017-10-01

3D-QSAR (comparative molecular field analysis (CoMFA)) and comparative molecular similarity indices analysis (CoMSIA) were performed on novel 2,5 disubstituted 1,3,4-oxadiazoles analogues as anti-fungal agents. The CoMFA and CoMSIA models using 13 compounds in the training set gives Q2 values of 0.52 and 0.51 respectively, while R2 values of 0.92. The adapted alignment method with the suitable parameters resulted in reliable models. The contour maps produced by the CoMFA and CoMSIA models were employed to determine a three-dimensional quantitative structure-activity relationship. Based on this study a set of new molecules with high predicted activities were designed. Surflex-docking confirmed the stability of predicted molecules in the receptor.

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.

Elucidation of the molecular mechanisms underlying adverse reactions associated with a kinase inhibitor using systems toxicology

PubMed Central

Amemiya, Takahiro; Honma, Masashi; Kariya, Yoshiaki; Ghosh, Samik; Kitano, Hiroaki; Kurachi, Yoshihisa; Fujita, Ken-ichi; Sasaki, Yasutsuna; Homma, Yukio; Abernethy, Darrel R; Kume, Haruki; Suzuki, Hiroshi

2015-01-01

Background/Objectives: Targeted kinase inhibitors are an important class of agents in anticancer therapeutics, but their limited tolerability hampers their clinical performance. Identification of the molecular mechanisms underlying the development of adverse reactions will be helpful in establishing a rational method for the management of clinically adverse reactions. Here, we selected sunitinib as a model and demonstrated that the molecular mechanisms underlying the adverse reactions associated with kinase inhibitors can efficiently be identified using a systems toxicological approach. Methods: First, toxicological target candidates were short-listed by comparing the human kinase occupancy profiles of sunitinib and sorafenib, and the molecular mechanisms underlying adverse reactions were predicted by sequential simulations using publicly available mathematical models. Next, to evaluate the probability of these predictions, a clinical observation study was conducted in six patients treated with sunitinib. Finally, mouse experiments were performed for detailed confirmation of the hypothesized molecular mechanisms and to evaluate the efficacy of a proposed countermeasure against adverse reactions to sunitinib. Results: In silico simulations indicated the possibility that sunitinib-mediated off-target inhibition of phosphorylase kinase leads to the generation of oxidative stress in various tissues. Clinical observations of patients and mouse experiments confirmed the validity of this prediction. The simulation further suggested that concomitant use of an antioxidant may prevent sunitinib-mediated adverse reactions, which was confirmed in mouse experiments. Conclusions: A systems toxicological approach successfully predicted the molecular mechanisms underlying clinically adverse reactions associated with sunitinib and was used to plan a rational method for the management of these adverse reactions. PMID:28725458

Accelerated molecular dynamics and protein conformational change: a theoretical and practical guide using a membrane embedded model neurotransmitter transporter.

PubMed

Gedeon, Patrick C; Thomas, James R; Madura, Jeffry D

2015-01-01

Molecular dynamics simulation provides a powerful and accurate method to model protein conformational change, yet timescale limitations often prevent direct assessment of the kinetic properties of interest. A large number of molecular dynamic steps are necessary for rare events to occur, which allow a system to overcome energy barriers and conformationally transition from one potential energy minimum to another. For many proteins, the energy landscape is further complicated by a multitude of potential energy wells, each separated by high free-energy barriers and each potentially representative of a functionally important protein conformation. To overcome these obstacles, accelerated molecular dynamics utilizes a robust bias potential function to simulate the transition between different potential energy minima. This straightforward approach more efficiently samples conformational space in comparison to classical molecular dynamics simulation, does not require advanced knowledge of the potential energy landscape and converges to the proper canonical distribution. Here, we review the theory behind accelerated molecular dynamics and discuss the approach in the context of modeling protein conformational change. As a practical example, we provide a detailed, step-by-step explanation of how to perform an accelerated molecular dynamics simulation using a model neurotransmitter transporter embedded in a lipid cell membrane. Changes in protein conformation of relevance to the substrate transport cycle are then examined using principle component analysis.

The structure of PX3 (X = Cl, Br, I) molecular liquids from X-ray diffraction, molecular dynamics simulations, and reverse Monte Carlo modeling.

PubMed

Pothoczki, Szilvia; Temleitner, László; Pusztai, László

2014-02-07

Synchrotron X-ray diffraction measurements have been conducted on liquid phosphorus trichloride, tribromide, and triiodide. Molecular Dynamics simulations for these molecular liquids were performed with a dual purpose: (1) to establish whether existing intermolecular potential functions can provide a picture that is consistent with diffraction data and (2) to generate reliable starting configurations for subsequent Reverse Monte Carlo modelling. Structural models (i.e., sets of coordinates of thousands of atoms) that were fully consistent with experimental diffraction information, within errors, have been prepared by means of the Reverse Monte Carlo method. Comparison with reference systems, generated by hard sphere-like Monte Carlo simulations, was also carried out to demonstrate the extent to which simple space filling effects determine the structure of the liquids (and thus, also estimating the information content of measured data). Total scattering structure factors, partial radial distribution functions and orientational correlations as a function of distances between the molecular centres have been calculated from the models. In general, more or less antiparallel arrangements of the primary molecular axes that are found to be the most favourable orientation of two neighbouring molecules. In liquid PBr3 electrostatic interactions seem to play a more important role in determining intermolecular correlations than in the other two liquids; molecular arrangements in both PCl3 and PI3 are largely driven by steric effects.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

NASA Astrophysics Data System (ADS)

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; Stuehn, Torsten

2017-11-01

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. These two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.

Application of computational methods to the design and characterisation of porous molecular materials.

PubMed

Evans, Jack D; Jelfs, Kim E; Day, Graeme M; Doonan, Christian J

2017-06-06

Composed from discrete units, porous molecular materials (PMMs) possess unique properties not observed for conventional, extended, solids, such as solution processibility and permanent porosity in the liquid phase. However, identifying the origin of porosity is not a trivial process, especially for amorphous or liquid phases. Furthermore, the assembly of molecular components is typically governed by a subtle balance of weak intermolecular forces that makes structure prediction challenging. Accordingly, in this review we canvass the crucial role of molecular simulations in the characterisation and design of PMMs. We will outline strategies for modelling porosity in crystalline, amorphous and liquid phases and also describe the state-of-the-art methods used for high-throughput screening of large datasets to identify materials that exhibit novel performance characteristics.

Two-dimensional model of resonant electron collisions with diatomic molecules and molecular cations

NASA Astrophysics Data System (ADS)

Vana, Martin; Hvizdos, David; Houfek, Karel; Curik, Roman; Greene, Chris H.; Rescigno, Thomas N.; McCurdy, C. William

2016-05-01

A simple model for resonant collisions of electrons with diatomic molecules with one electronic and one nuclear degree of freedom (2D model) which was solved numerically exactly within the time-independent approach was used to probe the local complex potential approximation and nonlocal approximation to nuclear dynamics of these collisions. This model was reformulated in the time-dependent picture and extended to model also electron collisions with molecular cations, especially with H2+.This model enables an assessment of approximate methods, such as the boomerang model or the frame transformation theory. We will present both time-dependent and time-independent results and show how we can use the model to extract deeper insight into the dynamics of the resonant collisions.

ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems.

PubMed

Niethammer, Christoph; Becker, Stefan; Bernreuther, Martin; Buchholz, Martin; Eckhardt, Wolfgang; Heinecke, Alexander; Werth, Stephan; Bungartz, Hans-Joachim; Glass, Colin W; Hasse, Hans; Vrabec, Jadran; Horsch, Martin

2014-10-14

The molecular dynamics simulation code ls1 mardyn is presented. It is a highly scalable code, optimized for massively parallel execution on supercomputing architectures and currently holds the world record for the largest molecular simulation with over four trillion particles. It enables the application of pair potentials to length and time scales that were previously out of scope for molecular dynamics simulation. With an efficient dynamic load balancing scheme, it delivers high scalability even for challenging heterogeneous configurations. Presently, multicenter rigid potential models based on Lennard-Jones sites, point charges, and higher-order polarities are supported. Due to its modular design, ls1 mardyn can be extended to new physical models, methods, and algorithms, allowing future users to tailor it to suit their respective needs. Possible applications include scenarios with complex geometries, such as fluids at interfaces, as well as nonequilibrium molecular dynamics simulation of heat and mass transfer.

Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors.

PubMed

Sundar, Vikram; Gelbwaser-Klimovsky, David; Aspuru-Guzik, Alán

2018-04-05

Modeling nuclear quantum effects is required for accurate molecular dynamics (MD) simulations of molecules. The community has paid special attention to water and other biomolecules that show hydrogen bonding. Standard methods of modeling nuclear quantum effects like Ring Polymer Molecular Dynamics (RPMD) are computationally costlier than running classical trajectories. A force-field functor (FFF) is an alternative method that computes an effective force field that replicates quantum properties of the original force field. In this work, we propose an efficient method of computing FFF using the Wigner-Kirkwood expansion. As a test case, we calculate a range of thermodynamic properties of Neon, obtaining the same level of accuracy as RPMD, but with the shorter runtime of classical simulations. By modifying existing MD programs, the proposed method could be used in the future to increase the efficiency and accuracy of MD simulations involving water and proteins.

Detection of DNA damage by using hairpin molecular beacon probes and graphene oxide.

PubMed

Zhou, Jie; Lu, Qian; Tong, Ying; Wei, Wei; Liu, Songqin

2012-09-15

A hairpin molecular beacon tagged with carboxyfluorescein in combination with graphene oxide as a quencher reagent was used to detect the DNA damage by chemical reagents. The fluorescence of molecular beacon was quenched sharply by graphene oxide; while in the presence of its complementary DNA the quenching efficiency decreased because their hybridization prevented the strong adsorbability of molecular beacon on graphene oxide. If the complementary DNA was damaged by a chemical reagent and could not form intact duplex structure with molecular beacon, more molecular beacon would adsorb on graphene oxide increasing the quenching efficiency. Thus, damaged DNA could be detected based on different quenching efficiencies afforded by damaged and intact complementary DNA. The damage effects of chlorpyrifos-methyl and three metabolites of styrene such as mandelieaeids, phenylglyoxylieaeids and epoxystyrene on DNA were studied as models. The method for detection of DNA damage was reliable, rapid and simple compared to the biological methods. Copyright © 2012 Elsevier B.V. All rights reserved.

Fast and reliable prediction of domain-peptide binding affinity using coarse-grained structure models.

PubMed

Tian, Feifei; Tan, Rui; Guo, Tailin; Zhou, Peng; Yang, Li

2013-07-01

Domain-peptide recognition and interaction are fundamentally important for eukaryotic signaling and regulatory networks. It is thus essential to quantitatively infer the binding stability and specificity of such interaction based upon large-scale but low-accurate complex structure models which could be readily obtained from sophisticated molecular modeling procedure. In the present study, a new method is described for the fast and reliable prediction of domain-peptide binding affinity with coarse-grained structure models. This method is designed to tolerate strong random noises involved in domain-peptide complex structures and uses statistical modeling approach to eliminate systematic bias associated with a group of investigated samples. As a paradigm, this method was employed to model and predict the binding behavior of various peptides to four evolutionarily unrelated peptide-recognition domains (PRDs), i.e. human amph SH3, human nherf PDZ, yeast syh GYF and yeast bmh 14-3-3, and moreover, we explored the molecular mechanism and biological implication underlying the binding of cognate and noncognate peptide ligands to their domain receptors. It is expected that the newly proposed method could be further used to perform genome-wide inference of domain-peptide binding at three-dimensional structure level. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Markov State Models of gene regulatory networks.

PubMed

Chu, Brian K; Tse, Margaret J; Sato, Royce R; Read, Elizabeth L

2017-02-06

Gene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have the potential to guide cell-reprogramming strategies. Networks are often modeled by the stochastic Chemical Master Equation, but methods for systematic identification of key properties of the global dynamics are currently lacking. The method identifies the number, phenotypes, and lifetimes of long-lived states for a set of common gene regulatory network models. Application of transition path theory to the constructed Markov State Model decomposes global dynamics into a set of dominant transition paths and associated relative probabilities for stochastic state-switching. In this proof-of-concept study, we found that the Markov State Model provides a general framework for analyzing and visualizing stochastic multistability and state-transitions in gene networks. Our results suggest that this framework-adopted from the field of atomistic Molecular Dynamics-can be a useful tool for quantitative Systems Biology at the network scale.

Improved Electrostatic Embedding for Fragment-Based Chemical Shift Calculations in Molecular Crystals.

PubMed

Hartman, Joshua D; Balaji, Ashwin; Beran, Gregory J O

2017-12-12

Fragment-based methods predict nuclear magnetic resonance (NMR) chemical shielding tensors in molecular crystals with high accuracy and computational efficiency. Such methods typically employ electrostatic embedding to mimic the crystalline environment, and the quality of the results can be sensitive to the embedding treatment. To improve the quality of this embedding environment for fragment-based molecular crystal property calculations, we borrow ideas from the embedded ion method to incorporate self-consistently polarized Madelung field effects. The self-consistent reproduction of the Madelung potential (SCRMP) model developed here constructs an array of point charges that incorporates self-consistent lattice polarization and which reproduces the Madelung potential at all atomic sites involved in the quantum mechanical region of the system. The performance of fragment- and cluster-based 1 H, 13 C, 14 N, and 17 O chemical shift predictions using SCRMP and density functionals like PBE and PBE0 are assessed. The improved embedding model results in substantial improvements in the predicted 17 O chemical shifts and modest improvements in the 15 N ones. Finally, the performance of the model is demonstrated by examining the assignment of the two oxygen chemical shifts in the challenging γ-polymorph of glycine. Overall, the SCRMP-embedded NMR chemical shift predictions are on par with or more accurate than those obtained with the widely used gauge-including projector augmented wave (GIPAW) model.

Modelling and enhanced molecular dynamics to steer structure-based drug discovery.

PubMed

Kalyaanamoorthy, Subha; Chen, Yi-Ping Phoebe

2014-05-01

The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes. Copyright © 2013 Elsevier Ltd. All rights reserved.

DemQSAR: predicting human volume of distribution and clearance of drugs

NASA Astrophysics Data System (ADS)

Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter

2011-12-01

In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VDss) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VDss and CL is available on the webpage of DemPRED: http://agknapp.chemie.fu-berlin.de/dempred/.

DemQSAR: predicting human volume of distribution and clearance of drugs.

PubMed

Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter

2011-12-01

In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VD(ss)) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VD(ss) and CL is available on the webpage of DemPRED: http://agknapp.chemie.fu-berlin.de/dempred/ .

QSAR, molecular docking studies of thiophene and imidazopyridine derivatives as polo-like kinase 1 inhibitors

NASA Astrophysics Data System (ADS)

Cao, Shandong

2012-08-01

The purpose of the present study was to develop in silico models allowing for a reliable prediction of polo-like kinase inhibitors based on a large diverse dataset of 136 compounds. As an effective method, quantitative structure activity relationship (QSAR) was applied using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The proposed QSAR models showed reasonable predictivity of thiophene analogs (Rcv2=0.533, Rpred2=0.845) and included four molecular descriptors, namely IC3, RDF075m, Mor02m and R4e+. The optimal model for imidazopyridine derivatives (Rcv2=0.776, Rpred2=0.876) was shown to perform good in prediction accuracy, using GATS2m and BEHe1 descriptors. Analysis of the contour maps helped to identify structural requirements for the inhibitors and served as a basis for the design of the next generation of the inhibitor analogues. Docking studies were also employed to position the inhibitors into the polo-like kinase active site to determine the most probable binding mode. These studies may help to understand the factors influencing the binding affinity of chemicals and to develop alternative methods for prescreening and designing of polo-like kinase inhibitors.

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

PubMed

Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

2015-01-01

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

Use of noncrystallographic symmetry for automated model building at medium to low resolution.

PubMed

Wiegels, Tim; Lamzin, Victor S

2012-04-01

A novel method is presented for the automatic detection of noncrystallographic symmetry (NCS) in macromolecular crystal structure determination which does not require the derivation of molecular masks or the segmentation of density. It was found that throughout structure determination the NCS-related parts may be differently pronounced in the electron density. This often results in the modelling of molecular fragments of variable length and accuracy, especially during automated model-building procedures. These fragments were used to identify NCS relations in order to aid automated model building and refinement. In a number of test cases higher completeness and greater accuracy of the obtained structures were achieved, specifically at a crystallographic resolution of 2.3 Å or poorer. In the best case, the method allowed the building of up to 15% more residues automatically and a tripling of the average length of the built fragments.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation.

PubMed

Bardhan, Jaydeep P; Knepley, Matthew G; Anitescu, Mihai

2009-03-14

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation

NASA Astrophysics Data System (ADS)

Bardhan, Jaydeep P.; Knepley, Matthew G.; Anitescu, Mihai

2009-03-01

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Evaluating the solution from MrBUMP and BALBES

PubMed Central

Keegan, Ronan M.; Long, Fei; Fazio, Vincent J.; Winn, Martyn D.; Murshudov, Garib N.; Vagin, Alexei A.

2011-01-01

Molecular replacement is one of the key methods used to solve the problem of determining the phases of structure factors in protein structure solution from X-ray image diffraction data. Its success rate has been steadily improving with the development of improved software methods and the increasing number of structures available in the PDB for use as search models. Despite this, in cases where there is low sequence identity between the target-structure sequence and that of its set of possible homologues it can be a difficult and time-consuming chore to isolate and prepare the best search model for molecular replacement. MrBUMP and BALBES are two recent developments from CCP4 that have been designed to automate and speed up the process of determining and preparing the best search models and putting them through molecular replacement. Their intention is to provide the user with a broad set of results using many search models and to highlight the best of these for further processing. An overview of both programs is presented along with a description of how best to use them, citing case studies and the results of large-scale testing of the software. PMID:21460449

Molecular Modeling of Nucleic Acid Structure: Electrostatics and Solvation

PubMed Central

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E.

2014-01-01

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand the structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as means to sample conformational space for a better understanding of the relevance of a given model. From this discussion, the major limitations with modeling, in general, were highlighted. These are the difficult issues in sampling conformational space effectively—the multiple minima or conformational sampling problems—and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These are discussed in detail in this unit. PMID:18428877

Molecular modeling of nucleic Acid structure: electrostatics and solvation.

PubMed

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E

2014-12-19

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand its structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as a way of sampling conformational space for a better understanding of the relevance of a given model. This discussion highlighted the major limitations with modeling in general. When sampling conformational space effectively, difficult issues are encountered, such as multiple minima or conformational sampling problems, and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These subjects are discussed in detail in this unit. Copyright © 2014 John Wiley & Sons, Inc.

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

Combined quantum and molecular mechanics (QM/MM).

PubMed

Friesner, Richard A

2004-12-01

We describe the current state of the art of mixed quantum mechanics/molecular mechanics (QM/MM) methodology, with a particular focus on modeling of enzymatic reactions. Over the past decade, the effectiveness of these methods has increased dramatically, based on improved quantum chemical methods, advances in the description of the QM/MM interface, and reductions in the cost/performance of computing hardware. Two examples of pharmaceutically relevant applications, cytochrome P450 and class C β-lactamase, are presented.: © 2004 Elsevier Ltd . All rights reserved.

New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

PubMed

Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

2012-01-21

Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction: Metabolic networks (72.3%), Parasite-Host networks (93.3%), CoCoMac brain cortex co-activation network (89.6%), NW Spain fasciolosis spreading network (97.2%), Spanish financial law network (89.9%) and World trade network for Intelligent & Active Food Packaging (92.8%). In order to seek these models, we studied an average of 55,388 pairs of nodes in each model and a total of 332,326 pairs of nodes in all models. Finally, this method was used to solve a more complicated problem. A model was developed to score the connectivity quality in the Drug-Target network of US FDA approved drugs. In this last model the θ(k) values were calculated for three types of molecular networks representing different levels of organization: drug molecular graphs (atom-atom bonds), protein residue networks (amino acid interactions), and drug-target network (compound-protein binding). The overall accuracy of this model was 76.3%. This work opens a new door to the computational reevaluation of network connectivity quality (collation) for complex systems in molecular, biomedical, technological, and legal-social sciences as well as in world trade and industry. Copyright © 2011 Elsevier Ltd. All rights reserved.

Molecular design of new aggrecanases-2 inhibitors.

PubMed

Shan, Zhi Jie; Zhai, Hong Lin; Huang, Xiao Yan; Li, Li Na; Zhang, Xiao Yun

2013-10-01

Aggrecanases-2 is a very important potential drug target for the treatment of osteoarthritis. In this study, a series of known aggrecanases-2 inhibitors was analyzed by the technologies of three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking. Two 3D-QSAR models, which based on comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods, were established. Molecular docking was employed to explore the details of the interaction between inhibitors and aggrecanases-2 protein. According to the analyses for these models, several new potential inhibitors with higher activity predicted were designed, and were supported by the simulation of molecular docking. This work propose the fast and effective approach to design and prediction for new potential inhibitors, and the study of the interaction mechanism provide a better understanding for the inhibitors binding into the target protein, which will be useful for the structure-based drug design and modifications. Copyright © 2013 Elsevier Ltd. All rights reserved.

Impact-parameter dependence of the energy loss of fast molecular clusters in hydrogen

NASA Astrophysics Data System (ADS)

Fadanelli, R. C.; Grande, P. L.; Schiwietz, G.

2008-03-01

The electronic energy loss of molecular clusters as a function of impact parameter is far less understood than atomic energy losses. For instance, there are no analytical expressions for the energy loss as a function of impact parameter for cluster ions. In this work, we describe two procedures to evaluate the combined energy loss of molecules: Ab initio calculations within the semiclassical approximation and the coupled-channels method using atomic orbitals; and simplified models for the electronic cluster energy loss as a function of the impact parameter, namely the molecular perturbative convolution approximation (MPCA, an extension of the corresponding atomic model PCA) and the molecular unitary convolution approximation (MUCA, a molecular extension of the previous unitary convolution approximation UCA). In this work, an improved ansatz for MPCA is proposed, extending its validity for very compact clusters. For the simplified models, the physical inputs are the oscillators strengths of the target atoms and the target-electron density. The results from these models applied to an atomic hydrogen target yield remarkable agreement with their corresponding ab initio counterparts for different angles between cluster axis and velocity direction at specific energies of 150 and 300 keV/u.

Simple model of a coherent molecular photocell

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

Ernzerhof, Matthias, E-mail: Matthias.Ernzerhof@UMontreal.ca; Bélanger, Marc-André; Mayou, Didier

2016-04-07

Electron transport in molecular electronic devices is often dominated by a coherent mechanism in which the wave function extends from the left contact over the molecule to the right contact. If the device is exposed to light, photon absorption in the molecule might occur, turning the device into a molecular photocell. The photon absorption promotes an electron to higher energy levels and thus modifies the electron transmission probability through the device. A model for such a molecular photocell is presented that minimizes the complexity of the problem while providing a non-trivial description of the device mechanism. In particular, the rolemore » of the molecule in the photocell is investigated. It is described within the Hückel method and the source-sink potential approach [F. Goyer, M. Ernzerhof, and M. Zhuang, J. Chem. Phys. 126, 144104 (2007)] is used to eliminate the contacts in favor of complex-valued potentials. Furthermore, the photons are explicitly incorporated into the model through a second-quantized field. This facilitates the description of the photon absorption process with a stationary state calculation, where eigenvalues and eigenvectors are determined. The model developed is applied to various generic molecular photocells.« less

Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis

PubMed Central

Gherib, Rami; Dokainish, Hisham M.; Gauld, James W.

2014-01-01

Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis. PMID:24384841

Simulation of meso-damage of refractory based on cohesion model and molecular dynamics method

NASA Astrophysics Data System (ADS)

Zhao, Jiuling; Shang, Hehao; Zhu, Zhaojun; Zhang, Guoxing; Duan, Leiguang; Sun, Xinya

2018-06-01

In order to describe the meso-damage of the refractories more accurately, and to study of the relationship between the mesostructured of the refractories and the macro-mechanics, this paper takes the magnesia-carbon refractories as the research object and uses the molecular dynamics method to instead the traditional sequential algorithm to establish the meso-particles filling model including small and large particles. Finally, the finite element software-ABAQUS is used to conducts numerical simulation on the meso-damage evolution process of refractory materials. From the results, the process of initiation and propagation of microscopic interface cracks can be observed intuitively, and the macroscopic stress-strain curve of the refractory material is obtained. The results show that the combination of molecular dynamics modeling and the use of Python in the interface to insert the cohesive element numerical simulation, obtaining of more accurate interface parameters through parameter inversion, can be more accurate to observe the interface of the meso-damage evolution process and effective to consider the effect of the mesostructured of the refractory material on its macroscopic mechanical properties.

Advances in modelling of biomimetic fluid flow at different scales

PubMed Central

2011-01-01

The biomimetic flow at different scales has been discussed at length. The need of looking into the biological surfaces and morphologies and both geometrical and physical similarities to imitate the technological products and processes has been emphasized. The complex fluid flow and heat transfer problems, the fluid-interface and the physics involved at multiscale and macro-, meso-, micro- and nano-scales have been discussed. The flow and heat transfer simulation is done by various CFD solvers including Navier-Stokes and energy equations, lattice Boltzmann method and molecular dynamics method. Combined continuum-molecular dynamics method is also reviewed. PMID:21711847

Effect of Material Ion Exchanges on the Mechanical Stiffness Properties and Shear Deformation of Hydrated Cement Material Chemistry Structure C-S-H Jennit - A Computational Modeling Study

DTIC Science & Technology

2014-01-01

Study Material properties and performance are governed by material molecular chemistry structures and molecular level interactions. Methods to...understand relationships between the material properties and performance and their correlation to the molecular level chemistry and morphology, and thus...find ways of manipulating and adjusting matters at the atomistic level in order to improve material performance are required. A computational material

Molecular Treatment of Nano-Kaolinite Generations.

PubMed

Táborosi, Attila; Szilagyi, Robert K; Zsirka, Balázs; Fónagy, Orsolya; Horváth, Erzsébet; Kristóf, János

2018-06-18

A procedure is developed for defining a compositionally and structurally realistic, atomic-scale description of exfoliated clay nanoparticles from the kaolinite family of phylloaluminosilicates. By use of coordination chemical principles, chemical environments within a nanoparticle can be separated into inner, outer, and peripheral spheres. The edges of the molecular models of nanoparticles were protonated in a validated manner to achieve charge neutrality. Structural optimizations using semiempirical methods (NDDO Hamiltonians and DFTB formalism) and ab initio density functionals with a saturated basis set revealed previously overlooked molecular origins of morphological changes as a result of exfoliation. While the use of semiempirical methods is desirable for the treatment of nanoparticles composed of tens of thousands of atoms, the structural accuracy is rather modest in comparison to DFT methods. We report a comparative survey of our infrared data for untreated crystalline and various exfoliated states of kaolinite and halloysite. Given the limited availability of experimental techniques for providing direct structural information about nano-kaolinite, the vibrational spectra can be considered as an essential tool for validating structural models. The comparison of experimental and calculated stretching and bending frequencies further justified the use of the preferred level of theory. Overall, an optimal molecular model of the defect-free, ideal nano-kaolinite can be composed with respect to stationary structure and curvature of the potential energy surface using the PW91/SVP level of theory with empirical dispersion correction (PW91+D) and polarizable continuum solvation model (PCM) without the need for a scaled quantum chemical force field. This validated theoretical approach is essential in order to follow the formation of exfoliated clays and their surface reactivity that is experimentally unattainable.

Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-Field.

PubMed

Jamroz, Michal; Orozco, Modesto; Kolinski, Andrzej; Kmiecik, Sebastian

2013-01-08

It is widely recognized that atomistic Molecular Dynamics (MD), a classical simulation method, captures the essential physics of protein dynamics. That idea is supported by a theoretical study showing that various MD force-fields provide a consensus picture of protein fluctuations in aqueous solution [Rueda, M. et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 796-801]. However, atomistic MD cannot be applied to most biologically relevant processes due to its limitation to relatively short time scales. Much longer time scales can be accessed by properly designed coarse-grained models. We demonstrate that the aforementioned consensus view of protein dynamics from short (nanosecond) time scale MD simulations is fairly consistent with the dynamics of the coarse-grained protein model - the CABS model. The CABS model employs stochastic dynamics (a Monte Carlo method) and a knowledge-based force-field, which is not biased toward the native structure of a simulated protein. Since CABS-based dynamics allows for the simulation of entire folding (or multiple folding events) in a single run, integration of the CABS approach with all-atom MD promises a convenient (and computationally feasible) means for the long-time multiscale molecular modeling of protein systems with atomistic resolution.

KECSA-Movable Type Implicit Solvation Model (KMTISM)

PubMed Central

2015-01-01

Computation of the solvation free energy for chemical and biological processes has long been of significant interest. The key challenges to effective solvation modeling center on the choice of potential function and configurational sampling. Herein, an energy sampling approach termed the “Movable Type” (MT) method, and a statistical energy function for solvation modeling, “Knowledge-based and Empirical Combined Scoring Algorithm” (KECSA) are developed and utilized to create an implicit solvation model: KECSA-Movable Type Implicit Solvation Model (KMTISM) suitable for the study of chemical and biological systems. KMTISM is an implicit solvation model, but the MT method performs energy sampling at the atom pairwise level. For a specific molecular system, the MT method collects energies from prebuilt databases for the requisite atom pairs at all relevant distance ranges, which by its very construction encodes all possible molecular configurations simultaneously. Unlike traditional statistical energy functions, KECSA converts structural statistical information into categorized atom pairwise interaction energies as a function of the radial distance instead of a mean force energy function. Within the implicit solvent model approximation, aqueous solvation free energies are then obtained from the NVT ensemble partition function generated by the MT method. Validation is performed against several subsets selected from the Minnesota Solvation Database v2012. Results are compared with several solvation free energy calculation methods, including a one-to-one comparison against two commonly used classical implicit solvation models: MM-GBSA and MM-PBSA. Comparison against a quantum mechanics based polarizable continuum model is also discussed (Cramer and Truhlar’s Solvation Model 12). PMID:25691832

Partial unfolding and refolding for structure refinement: A unified approach of geometric simulations and molecular dynamics.

PubMed

Kumar, Avishek; Campitelli, Paul; Thorpe, M F; Ozkan, S Banu

2015-12-01

The most successful protein structure prediction methods to date have been template-based modeling (TBM) or homology modeling, which predicts protein structure based on experimental structures. These high accuracy predictions sometimes retain structural errors due to incorrect templates or a lack of accurate templates in the case of low sequence similarity, making these structures inadequate in drug-design studies or molecular dynamics simulations. We have developed a new physics based approach to the protein refinement problem by mimicking the mechanism of chaperons that rehabilitate misfolded proteins. The template structure is unfolded by selectively (targeted) pulling on different portions of the protein using the geometric based technique FRODA, and then refolded using hierarchically restrained replica exchange molecular dynamics simulations (hr-REMD). FRODA unfolding is used to create a diverse set of topologies for surveying near native-like structures from a template and to provide a set of persistent contacts to be employed during re-folding. We have tested our approach on 13 previous CASP targets and observed that this method of folding an ensemble of partially unfolded structures, through the hierarchical addition of contact restraints (that is, first local and then nonlocal interactions), leads to a refolding of the structure along with refinement in most cases (12/13). Although this approach yields refined models through advancement in sampling, the task of blind selection of the best refined models still needs to be solved. Overall, the method can be useful for improved sampling for low resolution models where certain of the portions of the structure are incorrectly modeled. © 2015 Wiley Periodicals, Inc.

Bayesian molecular dating: opening up the black box.

PubMed

Bromham, Lindell; Duchêne, Sebastián; Hua, Xia; Ritchie, Andrew M; Duchêne, David A; Ho, Simon Y W

2018-05-01

Molecular dating analyses allow evolutionary timescales to be estimated from genetic data, offering an unprecedented capacity for investigating the evolutionary past of all species. These methods require us to make assumptions about the relationship between genetic change and evolutionary time, often referred to as a 'molecular clock'. Although initially regarded with scepticism, molecular dating has now been adopted in many areas of biology. This broad uptake has been due partly to the development of Bayesian methods that allow complex aspects of molecular evolution, such as variation in rates of change across lineages, to be taken into account. But in order to do this, Bayesian dating methods rely on a range of assumptions about the evolutionary process, which vary in their degree of biological realism and empirical support. These assumptions can have substantial impacts on the estimates produced by molecular dating analyses. The aim of this review is to open the 'black box' of Bayesian molecular dating and have a look at the machinery inside. We explain the components of these dating methods, the important decisions that researchers must make in their analyses, and the factors that need to be considered when interpreting results. We illustrate the effects that the choices of different models and priors can have on the outcome of the analysis, and suggest ways to explore these impacts. We describe some major research directions that may improve the reliability of Bayesian dating. The goal of our review is to help researchers to make informed choices when using Bayesian phylogenetic methods to estimate evolutionary rates and timescales. © 2017 Cambridge Philosophical Society.

Computer-Assisted Drug Formulation Design: Novel Approach in Drug Delivery.

PubMed

Metwally, Abdelkader A; Hathout, Rania M

2015-08-03

We hypothesize that, by using several chemo/bio informatics tools and statistical computational methods, we can study and then predict the behavior of several drugs in model nanoparticulate lipid and polymeric systems. Accordingly, two different matrices comprising tripalmitin, a core component of solid lipid nanoparticles (SLN), and PLGA were first modeled using molecular dynamics simulation, and then the interaction of drugs with these systems was studied by means of computing the free energy of binding using the molecular docking technique. These binding energies were hence correlated with the loadings of these drugs in the nanoparticles obtained experimentally from the available literature. The obtained relations were verified experimentally in our laboratory using curcumin as a model drug. Artificial neural networks were then used to establish the effect of the drugs' molecular descriptors on the binding energies and hence on the drug loading. The results showed that the used soft computing methods can provide an accurate method for in silico prediction of drug loading in tripalmitin-based and PLGA nanoparticulate systems. These results have the prospective of being applied to other nano drug-carrier systems, and this integrated statistical and chemo/bio informatics approach offers a new toolbox to the formulation science by proposing what we present as computer-assisted drug formulation design (CADFD).

Predicting critical micelle concentration and micelle molecular weight of polysorbate 80 using compendial methods.

PubMed

Braun, Alexandra C; Ilko, David; Merget, Benjamin; Gieseler, Henning; Germershaus, Oliver; Holzgrabe, Ulrike; Meinel, Lorenz

2015-08-01

This manuscript addresses the capability of compendial methods in controlling polysorbate 80 (PS80) functionality. Based on the analysis of sixteen batches, functionality related characteristics (FRC) including critical micelle concentration (CMC), cloud point, hydrophilic-lipophilic balance (HLB) value and micelle molecular weight were correlated to chemical composition including fatty acids before and after hydrolysis, content of non-esterified polyethylene glycols and sorbitan polyethoxylates, sorbitan- and isosorbide polyethoxylate fatty acid mono- and diesters, polyoxyethylene diesters, and peroxide values. Batches from some suppliers had a high variability in functionality related characteristic (FRC), questioning the ability of the current monograph in controlling these. Interestingly, the combined use of the input parameters oleic acid content and peroxide value - both of which being monographed methods - resulted in a model adequately predicting CMC. Confining the batches to those complying with specifications for peroxide value proved oleic acid content alone as being predictive for CMC. Similarly, a four parameter model based on chemical analyses alone was instrumental in predicting the molecular weight of PS80 micelles. Improved models based on analytical outcome from fingerprint analyses are also presented. A road map controlling PS80 batches with respect to FRC and based on chemical analyses alone is provided for the formulator. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantitative structure-property relationships for octanol-water partition coefficients of polybrominated diphenyl ethers.

PubMed

Li, Linnan; Xie, Shaodong; Cai, Hao; Bai, Xuetao; Xue, Zhao

2008-08-01

Theoretical molecular descriptors were tested against logK(OW) values for polybrominated diphenyl ethers (PBDEs) using the Partial Least-Squares Regression method which can be used to analyze data with many variables and few observations. A quantitative structure-property relationship (QSPR) model was successfully developed with a high cross-validated value (Q(cum)(2)) of 0.961, indicating a good predictive ability and stability of the model. The predictive power of the QSPR model was further cross-validated. The values of logK(OW) for PBDEs are mainly governed by molecular surface area, energy of the lowest unoccupied molecular orbital and the net atomic charges on the oxygen atom. All these descriptors have been discussed to interpret the partitioning mechanism of PBDE chemicals. The bulk property of the molecules represented by molecular surface area is the leading factor, and K(OW) values increase with the increase of molecular surface area. Higher energy of the lowest unoccupied molecular orbital and higher net atomic charge on the oxygen atom of PBDEs result in smaller K(OW). The energy of the lowest unoccupied molecular orbital and the net atomic charge on PBDEs oxygen also play important roles in affecting the partition of PBDEs between octanol and water by influencing the interactions between PBDEs and solvent molecules.

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

DOE PAGES

Petsev, Nikolai Dimitrov; Leal, L. Gary; Shell, M. Scott

2017-12-21

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulatedmore » using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.« less

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

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

Petsev, Nikolai Dimitrov; Leal, L. Gary; Shell, M. Scott

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulatedmore » using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.« less

Molecular level in silico studies for oncology. Direct models review

NASA Astrophysics Data System (ADS)

Psakhie, S. G.; Tsukanov, A. A.

2017-09-01

The combination of therapy and diagnostics in one process "theranostics" is a trend in a modern medicine, especially in oncology. Such an approach requires development and usage of multifunctional hybrid nanoparticles with a hierarchical structure. Numerical methods and mathematical models play a significant role in the design of the hierarchical nanoparticles and allow looking inside the nanoscale mechanisms of agent-cell interactions. The current position of in silico approach in biomedicine and oncology is discussed. The review of the molecular level in silico studies in oncology, which are using the direct models, is presented.

Multiensemble Markov models of molecular thermodynamics and kinetics.

PubMed

Wu, Hao; Paul, Fabian; Wehmeyer, Christoph; Noé, Frank

2016-06-07

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models-clustering of high-dimensional spaces and modeling of complex many-state systems-with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein-ligand binding model.

Relation between cooperative molecular motors and active Brownian particles.

PubMed

Touya, Clément; Schwalger, Tilo; Lindner, Benjamin

2011-05-01

Active Brownian particles (ABPs), obeying a nonlinear Langevin equation with speed-dependent drift and noise amplitude, are well-known models used to describe self-propelled motion in biology. In this paper we study a model describing the stochastic dynamics of a group of coupled molecular motors (CMMs). Using two independent numerical methods, one based on the stationary velocity distribution of the motors and the other one on the local increments (also known as the Kramers-Moyal coefficients) of the velocity, we establish a connection between the CMM and the ABP models. The parameters extracted for the ABP via the two methods show good agreement for both symmetric and asymmetric cases and are independent of N, the number of motors, provided that N is not too small. This indicates that one can indeed describe the CMM problem with a simpler ABP model. However, the power spectrum of velocity fluctuations in the CMM model reveals a peak at a finite frequency, a peak which is absent in the velocity spectrum of the ABP model. This implies richer dynamic features of the CMM model which cannot be captured by an ABP model.

Relation between cooperative molecular motors and active Brownian particles

NASA Astrophysics Data System (ADS)

Touya, Clément; Schwalger, Tilo; Lindner, Benjamin

2011-05-01

Active Brownian particles (ABPs), obeying a nonlinear Langevin equation with speed-dependent drift and noise amplitude, are well-known models used to describe self-propelled motion in biology. In this paper we study a model describing the stochastic dynamics of a group of coupled molecular motors (CMMs). Using two independent numerical methods, one based on the stationary velocity distribution of the motors and the other one on the local increments (also known as the Kramers-Moyal coefficients) of the velocity, we establish a connection between the CMM and the ABP models. The parameters extracted for the ABP via the two methods show good agreement for both symmetric and asymmetric cases and are independent of N, the number of motors, provided that N is not too small. This indicates that one can indeed describe the CMM problem with a simpler ABP model. However, the power spectrum of velocity fluctuations in the CMM model reveals a peak at a finite frequency, a peak which is absent in the velocity spectrum of the ABP model. This implies richer dynamic features of the CMM model which cannot be captured by an ABP model.

Quantum Mechanical Modeling: A Tool for the Understanding of Enzyme Reactions

PubMed Central

Náray-Szabó, Gábor; Oláh, Julianna; Krámos, Balázs

2013-01-01

Most enzyme reactions involve formation and cleavage of covalent bonds, while electrostatic effects, as well as dynamics of the active site and surrounding protein regions, may also be crucial. Accordingly, special computational methods are needed to provide an adequate description, which combine quantum mechanics for the reactive region with molecular mechanics and molecular dynamics describing the environment and dynamic effects, respectively. In this review we intend to give an overview to non-specialists on various enzyme models as well as established computational methods and describe applications to some specific cases. For the treatment of various enzyme mechanisms, special approaches are often needed to obtain results, which adequately refer to experimental data. As a result of the spectacular progress in the last two decades, most enzyme reactions can be quite precisely treated by various computational methods. PMID:24970187

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.

Hydration of Li+ -ion in atom-bond electronegativity equalization method-7P water: a molecular dynamics simulation study.

PubMed

Li, Xin; Yang, Zhong-Zhi

2005-02-22

We have carried out molecular dynamics simulations of a Li(+) ion in water over a wide range of temperature (from 248 to 368 K). The simulations make use of the atom-bond electronegativity equalization method-7P water model, a seven-site flexible model with fluctuating charges, which has accurately reproduced many bulk water properties. The recently constructed Li(+)-water interaction potential through fitting to the experimental and ab initio gas-phase binding energies and to the measured structures for Li(+)-water clusters is adopted in the simulations. ABEEM was proposed and developed in terms of partitioning the electron density into atom and bond regions and using the electronegativity equalization method (EEM) and the density functional theory (DFT). Based on a combination of the atom-bond electronegativity equalization method and molecular mechanics (ABEEM/MM), a new set of water-water and Li(+)-water potentials, successfully applied to ionic clusters Li(+)(H(2)O)(n)(n=1-6,8), are further investigated in an aqueous solution of Li(+) in the present paper. Two points must be emphasized in the simulations: first, the model allows for the charges on the interacting sites fluctuating as a function of time; second, the ABEEM-7P model has applied the parameter k(lp,H)(R(lp,H)) to explicitly describe the short-range interaction of hydrogen bond in the hydrogen bond interaction region, and has a new description for the hydrogen bond. The static, dynamic, and thermodynamic properties have been studied in detail. In addition, at different temperatures, the structural properties such as radial distribution functions, and the dynamical properties such as diffusion coefficients and residence times of the water molecules in the first hydration shell of Li(+), are also simulated well. These simulation results show that the ABEEM/MM-based water-water and Li(+)-water potentials appear to be robust giving the overall characteristic hydration properties in excellent agreement with experiments and other molecular dynamics simulations on similar system.

Realistic molecular model of kerogen's nanostructure

NASA Astrophysics Data System (ADS)

Bousige, Colin; Ghimbeu, Camélia Matei; Vix-Guterl, Cathie; Pomerantz, Andrew E.; Suleimenova, Assiya; Vaughan, Gavin; Garbarino, Gaston; Feygenson, Mikhail; Wildgruber, Christoph; Ulm, Franz-Josef; Pellenq, Roland J.-M.; Coasne, Benoit

2016-05-01

Despite kerogen's importance as the organic backbone for hydrocarbon production from source rocks such as gas shale, the interplay between kerogen's chemistry, morphology and mechanics remains unexplored. As the environmental impact of shale gas rises, identifying functional relations between its geochemical, transport, elastic and fracture properties from realistic molecular models of kerogens becomes all the more important. Here, by using a hybrid experimental-simulation method, we propose a panel of realistic molecular models of mature and immature kerogens that provide a detailed picture of kerogen's nanostructure without considering the presence of clays and other minerals in shales. We probe the models' strengths and limitations, and show that they predict essential features amenable to experimental validation, including pore distribution, vibrational density of states and stiffness. We also show that kerogen's maturation, which manifests itself as an increase in the sp2/sp3 hybridization ratio, entails a crossover from plastic-to-brittle rupture mechanisms.

Realistic molecular model of kerogen's nanostructure.

PubMed

Bousige, Colin; Ghimbeu, Camélia Matei; Vix-Guterl, Cathie; Pomerantz, Andrew E; Suleimenova, Assiya; Vaughan, Gavin; Garbarino, Gaston; Feygenson, Mikhail; Wildgruber, Christoph; Ulm, Franz-Josef; Pellenq, Roland J-M; Coasne, Benoit

2016-05-01

Despite kerogen's importance as the organic backbone for hydrocarbon production from source rocks such as gas shale, the interplay between kerogen's chemistry, morphology and mechanics remains unexplored. As the environmental impact of shale gas rises, identifying functional relations between its geochemical, transport, elastic and fracture properties from realistic molecular models of kerogens becomes all the more important. Here, by using a hybrid experimental-simulation method, we propose a panel of realistic molecular models of mature and immature kerogens that provide a detailed picture of kerogen's nanostructure without considering the presence of clays and other minerals in shales. We probe the models' strengths and limitations, and show that they predict essential features amenable to experimental validation, including pore distribution, vibrational density of states and stiffness. We also show that kerogen's maturation, which manifests itself as an increase in the sp(2)/sp(3) hybridization ratio, entails a crossover from plastic-to-brittle rupture mechanisms.

Extended Finite Element Method with Simplified Spherical Harmonics Approximation for the Forward Model of Optical Molecular Imaging

PubMed Central

Li, Wei; Yi, Huangjian; Zhang, Qitan; Chen, Duofang; Liang, Jimin

2012-01-01

An extended finite element method (XFEM) for the forward model of 3D optical molecular imaging is developed with simplified spherical harmonics approximation (SPN). In XFEM scheme of SPN equations, the signed distance function is employed to accurately represent the internal tissue boundary, and then it is used to construct the enriched basis function of the finite element scheme. Therefore, the finite element calculation can be carried out without the time-consuming internal boundary mesh generation. Moreover, the required overly fine mesh conforming to the complex tissue boundary which leads to excess time cost can be avoided. XFEM conveniences its application to tissues with complex internal structure and improves the computational efficiency. Phantom and digital mouse experiments were carried out to validate the efficiency of the proposed method. Compared with standard finite element method and classical Monte Carlo (MC) method, the validation results show the merits and potential of the XFEM for optical imaging. PMID:23227108

Extended finite element method with simplified spherical harmonics approximation for the forward model of optical molecular imaging.

PubMed

Li, Wei; Yi, Huangjian; Zhang, Qitan; Chen, Duofang; Liang, Jimin

2012-01-01

An extended finite element method (XFEM) for the forward model of 3D optical molecular imaging is developed with simplified spherical harmonics approximation (SP(N)). In XFEM scheme of SP(N) equations, the signed distance function is employed to accurately represent the internal tissue boundary, and then it is used to construct the enriched basis function of the finite element scheme. Therefore, the finite element calculation can be carried out without the time-consuming internal boundary mesh generation. Moreover, the required overly fine mesh conforming to the complex tissue boundary which leads to excess time cost can be avoided. XFEM conveniences its application to tissues with complex internal structure and improves the computational efficiency. Phantom and digital mouse experiments were carried out to validate the efficiency of the proposed method. Compared with standard finite element method and classical Monte Carlo (MC) method, the validation results show the merits and potential of the XFEM for optical imaging.

Solution of the Wang Chang-Uhlenbeck equation for molecular hydrogen

NASA Astrophysics Data System (ADS)

Anikin, Yu. A.

2017-06-01

Molecular hydrogen is modeled by numerically solving the Wang Chang-Uhlenbeck equation. The differential scattering cross sections of molecules are calculated using the quantum mechanical scattering theory of rigid rotors. The collision integral is computed by applying a fully conservative projection method. Numerical results for relaxation, heat conduction, and a one-dimensional shock wave are presented.

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.

Population subdivision and molecular sequence variation: theory and analysis of Drosophila ananassae data.

PubMed

Vogl, Claus; Das, Aparup; Beaumont, Mark; Mohanty, Sujata; Stephan, Wolfgang

2003-11-01

Population subdivision complicates analysis of molecular variation. Even if neutrality is assumed, three evolutionary forces need to be considered: migration, mutation, and drift. Simplification can be achieved by assuming that the process of migration among and drift within subpopulations is occurring fast compared to mutation and drift in the entire population. This allows a two-step approach in the analysis: (i) analysis of population subdivision and (ii) analysis of molecular variation in the migrant pool. We model population subdivision using an infinite island model, where we allow the migration/drift parameter Theta to vary among populations. Thus, central and peripheral populations can be differentiated. For inference of Theta, we use a coalescence approach, implemented via a Markov chain Monte Carlo (MCMC) integration method that allows estimation of allele frequencies in the migrant pool. The second step of this approach (analysis of molecular variation in the migrant pool) uses the estimated allele frequencies in the migrant pool for the study of molecular variation. We apply this method to a Drosophila ananassae sequence data set. We find little indication of isolation by distance, but large differences in the migration parameter among populations. The population as a whole seems to be expanding. A population from Bogor (Java, Indonesia) shows the highest variation and seems closest to the species center.

Molecular Modeling of Ammonium, Calcium, Sulfur, and Sodium Lignosulphonates in Acid and Basic Aqueous Environments

NASA Astrophysics Data System (ADS)

Salazar Valencia, P. J.; Bolívar Marinez, L. E.; Pérez Merchancano, S. T.

2015-12-01

Lignosulphonates (LS), also known as lignin sulfonates or sulfite lignin, are lignins in sulfonated forms, obtained from the "sulfite liquors," a residue of the wood pulp extraction process. Their main utility lies in its wide range of properties, they can be used as additives, dispersants, binders, fluxing, binder agents, etc. in fields ranging from food to fertilizer manufacture and even as agents in the preparation of ion exchange membranes. Since they can be manufactured relatively easy and quickly, and that its molecular size can be manipulated to obtain fragments of very low molecular weight, they are used as transport agents in the food industry, cosmetics, pharmaceutical and drug development, and as molecular elements for the treatment of health problems. In this paper, we study the electronic structural and optical characteristics of LS incorporating ammonium, sulfur, calcium, and sodium ions in acidic and basic aqueous media in order to gain a better understanding of their behavior and the very interesting properties exhibit. The studies were performed using the molecular modeling program HyperChem 5 using the semiempirical method PM3 of the NDO Family (neglect of differential overlap), to calculate the structural properties. We calculated the electronic and optical properties using the semiempirical method ZINDO / CI.

Theoretical modeling of UV-Vis absorption and emission spectra in liquid state systems including vibrational and conformational effects: explicit treatment of the vibronic transitions.

PubMed

D'Abramo, Marco; Aschi, Massimiliano; Amadei, Andrea

2014-04-28

Here, we extend a recently introduced theoretical-computational procedure [M. D'Alessandro, M. Aschi, C. Mazzuca, A. Palleschi, and A. Amadei, J. Chem. Phys. 139, 114102 (2013)] to include quantum vibrational transitions in modelling electronic spectra of atomic molecular systems in condensed phase. The method is based on the combination of Molecular Dynamics simulations and quantum chemical calculations within the Perturbed Matrix Method approach. The main aim of the presented approach is to reproduce as much as possible the spectral line shape which results from a subtle combination of environmental and intrinsic (chromophore) mechanical-dynamical features. As a case study, we were able to model the low energy UV-vis transitions of pyrene in liquid acetonitrile in good agreement with the experimental data.

The Impact of the Tree Prior on Molecular Dating of Data Sets Containing a Mixture of Inter- and Intraspecies Sampling.

PubMed

Ritchie, Andrew M; Lo, Nathan; Ho, Simon Y W

2017-05-01

In Bayesian phylogenetic analyses of genetic data, prior probability distributions need to be specified for the model parameters, including the tree. When Bayesian methods are used for molecular dating, available tree priors include those designed for species-level data, such as the pure-birth and birth-death priors, and coalescent-based priors designed for population-level data. However, molecular dating methods are frequently applied to data sets that include multiple individuals across multiple species. Such data sets violate the assumptions of both the speciation and coalescent-based tree priors, making it unclear which should be chosen and whether this choice can affect the estimation of node times. To investigate this problem, we used a simulation approach to produce data sets with different proportions of within- and between-species sampling under the multispecies coalescent model. These data sets were then analyzed under pure-birth, birth-death, constant-size coalescent, and skyline coalescent tree priors. We also explored the ability of Bayesian model testing to select the best-performing priors. We confirmed the applicability of our results to empirical data sets from cetaceans, phocids, and coregonid whitefish. Estimates of node times were generally robust to the choice of tree prior, but some combinations of tree priors and sampling schemes led to large differences in the age estimates. In particular, the pure-birth tree prior frequently led to inaccurate estimates for data sets containing a mixture of inter- and intraspecific sampling, whereas the birth-death and skyline coalescent priors produced stable results across all scenarios. Model testing provided an adequate means of rejecting inappropriate tree priors. Our results suggest that tree priors do not strongly affect Bayesian molecular dating results in most cases, even when severely misspecified. However, the choice of tree prior can be significant for the accuracy of dating results in the case of data sets with mixed inter- and intraspecies sampling. [Bayesian phylogenetic methods; model testing; molecular dating; node time; tree prior.]. © The authors 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Enhanced conformational sampling via novel variable transformations and very large time-step molecular dynamics

NASA Astrophysics Data System (ADS)

Tuckerman, Mark

2006-03-01

One of the computational grand challenge problems is to develop methodology capable of sampling conformational equilibria in systems with rough energy landscapes. If met, many important problems, most notably protein folding, could be significantly impacted. In this talk, two new approaches for addressing this problem will be presented. First, it will be shown how molecular dynamics can be combined with a novel variable transformation designed to warp configuration space in such a way that barriers are reduced and attractive basins stretched. This method rigorously preserves equilibrium properties while leading to very large enhancements in sampling efficiency. Extensions of this approach to the calculation/exploration of free energy surfaces will be discussed. Next, a new very large time-step molecular dynamics method will be introduced that overcomes the resonances which plague many molecular dynamics algorithms. The performance of the methods is demonstrated on a variety of systems including liquid water, long polymer chains simple protein models, and oligopeptides.

Prediction of Mutagenicity of Chemicals from Their Calculated Molecular Descriptors: A Case Study with Structurally Homogeneous versus Diverse Datasets.

PubMed

Basak, Subhash C; Majumdar, Subhabrata

2015-01-01

Variation in high-dimensional data is often caused by a few latent factors, and hence dimension reduction or variable selection techniques are often useful in gathering useful information from the data. In this paper we consider two such recent methods: Interrelated two-way clustering and envelope models. We couple these methods with traditional statistical procedures like ridge regression and linear discriminant analysis, and apply them on two data sets which have more predictors than samples (i.e. n < p scenario) and several types of molecular descriptors. One of these datasets consists of a congeneric group of Amines while the other has a much diverse collection compounds. The difference of prediction results between these two datasets for both the methods supports the hypothesis that for a congeneric set of compounds, descriptors of a certain type are enough to provide good QSAR models, but as the data set grows diverse including a variety of descriptors can improve model quality considerably.

Quantum chemical approach for condensed-phase thermochemistry (V): Development of rigid-body type harmonic solvation model

NASA Astrophysics Data System (ADS)

Tarumi, Moto; Nakai, Hiromi

2018-05-01

This letter proposes an approximate treatment of the harmonic solvation model (HSM) assuming the solute to be a rigid body (RB-HSM). The HSM method can appropriately estimate the Gibbs free energy for condensed phases even where an ideal gas model used by standard quantum chemical programs fails. The RB-HSM method eliminates calculations for intra-molecular vibrations in order to reduce the computational costs. Numerical assessments indicated that the RB-HSM method can evaluate entropies and internal energies with the same accuracy as the HSM method but with lower calculation costs.

Towards cheminformatics-based estimation of drug therapeutic index: Predicting the protective index of anticonvulsants using a new quantitative structure-index relationship approach.

PubMed

Chen, Shangying; Zhang, Peng; Liu, Xin; Qin, Chu; Tao, Lin; Zhang, Cheng; Yang, Sheng Yong; Chen, Yu Zong; Chui, Wai Keung

2016-06-01

The overall efficacy and safety profile of a new drug is partially evaluated by the therapeutic index in clinical studies and by the protective index (PI) in preclinical studies. In-silico predictive methods may facilitate the assessment of these indicators. Although QSAR and QSTR models can be used for predicting PI, their predictive capability has not been evaluated. To test this capability, we developed QSAR and QSTR models for predicting the activity and toxicity of anticonvulsants at accuracy levels above the literature-reported threshold (LT) of good QSAR models as tested by both the internal 5-fold cross validation and external validation method. These models showed significantly compromised PI predictive capability due to the cumulative errors of the QSAR and QSTR models. Therefore, in this investigation a new quantitative structure-index relationship (QSIR) model was devised and it showed improved PI predictive capability that superseded the LT of good QSAR models. The QSAR, QSTR and QSIR models were developed using support vector regression (SVR) method with the parameters optimized by using the greedy search method. The molecular descriptors relevant to the prediction of anticonvulsant activities, toxicities and PIs were analyzed by a recursive feature elimination method. The selected molecular descriptors are primarily associated with the drug-like, pharmacological and toxicological features and those used in the published anticonvulsant QSAR and QSTR models. This study suggested that QSIR is useful for estimating the therapeutic index of drug candidates. Copyright © 2016. Published by Elsevier Inc.

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.

The structure of molten CuCl: Reverse Monte Carlo modeling with high-energy X-ray diffraction data and molecular dynamics of a polarizable ion model

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

Alcaraz, Olga; Trullàs, Joaquim, E-mail: quim.trullas@upc.edu; Tahara, Shuta

2016-09-07

The results of the structural properties of molten copper chloride are reported from high-energy X-ray diffraction measurements, reverse Monte Carlo modeling method, and molecular dynamics simulations using a polarizable ion model. The simulated X-ray structure factor reproduces all trends observed experimentally, in particular the shoulder at around 1 Å{sup −1} related to intermediate range ordering, as well as the partial copper-copper correlations from the reverse Monte Carlo modeling, which cannot be reproduced by using a simple rigid ion model. It is shown that the shoulder comes from intermediate range copper-copper correlations caused by the polarized chlorides.

PyEvolve: a toolkit for statistical modelling of molecular evolution.

PubMed

Butterfield, Andrew; Vedagiri, Vivek; Lang, Edward; Lawrence, Cath; Wakefield, Matthew J; Isaev, Alexander; Huttley, Gavin A

2004-01-05

Examining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences - ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The number of different problems to which phylogeny-based maximum likelihood calculations can be applied is extensive. Available software packages that can perform likelihood calculations suffer from a lack of flexibility and scalability, or employ error-prone approaches to model parameterisation. Here we describe the implementation of PyEvolve, a toolkit for the application of existing, and development of new, statistical methods for molecular evolution. We present the object architecture and design schema of PyEvolve, which includes an adaptable multi-level parallelisation schema. The approach for defining new methods is illustrated by implementing a novel dinucleotide model of substitution that includes a parameter for mutation of methylated CpG's, which required 8 lines of standard Python code to define. Benchmarking was performed using either a dinucleotide or codon substitution model applied to an alignment of BRCA1 sequences from 20 mammals, or a 10 species subset. Up to five-fold parallel performance gains over serial were recorded. Compared to leading alternative software, PyEvolve exhibited significantly better real world performance for parameter rich models with a large data set, reducing the time required for optimisation from approximately 10 days to approximately 6 hours. PyEvolve provides flexible functionality that can be used either for statistical modelling of molecular evolution, or the development of new methods in the field. The toolkit can be used interactively or by writing and executing scripts. The toolkit uses efficient processes for specifying the parameterisation of statistical models, and implements numerous optimisations that make highly parameter rich likelihood functions solvable within hours on multi-cpu hardware. PyEvolve can be readily adapted in response to changing computational demands and hardware configurations to maximise performance. PyEvolve is released under the GPL and can be downloaded from http://cbis.anu.edu.au/software.

Predicting drug-induced liver injury using ensemble learning methods and molecular fingerprints.

PubMed

Ai, Haixin; Chen, Wen; Zhang, Li; Huang, Liangchao; Yin, Zimo; Hu, Huan; Zhao, Qi; Zhao, Jian; Liu, Hongsheng

2018-05-21

Drug-induced liver injury (DILI) is a major safety concern in the drug-development process, and various methods have been proposed to predict the hepatotoxicity of compounds during the early stages of drug trials. In this study, we developed an ensemble model using three machine learning algorithms and 12 molecular fingerprints from a dataset containing 1,241 diverse compounds. The ensemble model achieved an average accuracy of 71.1±2.6%, sensitivity of 79.9±3.6%, specificity of 60.3±4.8%, and area under the receiver operating characteristic curve (AUC) of 0.764±0.026 in five-fold cross-validation and an accuracy of 84.3%, sensitivity of 86.9%, specificity of 75.4%, and AUC of 0.904 in an external validation dataset of 286 compounds collected from the Liver Toxicity Knowledge Base (LTKB). Compared with previous methods, the ensemble model achieved relatively high accuracy and sensitivity. We also identified several substructures related to DILI. In addition, we provide a web server offering access to our models (http://ccsipb.lnu.edu.cn/toxicity/HepatoPred-EL/).

Applications and assessment of QM:QM electronic embedding using generalized asymmetric Mulliken atomic charges.

PubMed

Parandekar, Priya V; Hratchian, Hrant P; Raghavachari, Krishnan

2008-10-14

Hybrid QM:QM (quantum mechanics:quantum mechanics) and QM:MM (quantum mechanics:molecular mechanics) methods are widely used to calculate the electronic structure of large systems where a full quantum mechanical treatment at a desired high level of theory is computationally prohibitive. The ONIOM (our own N-layer integrated molecular orbital molecular mechanics) approximation is one of the more popular hybrid methods, where the total molecular system is divided into multiple layers, each treated at a different level of theory. In a previous publication, we developed a novel QM:QM electronic embedding scheme within the ONIOM framework, where the model system is embedded in the external Mulliken point charges of the surrounding low-level region to account for the polarization of the model system wave function. Therein, we derived and implemented a rigorous expression for the embedding energy as well as analytic gradients that depend on the derivatives of the external Mulliken point charges. In this work, we demonstrate the applicability of our QM:QM method with point charge embedding and assess its accuracy. We study two challenging systems--zinc metalloenzymes and silicon oxide cages--and demonstrate that electronic embedding shows significant improvement over mechanical embedding. We also develop a modified technique for the energy and analytic gradients using a generalized asymmetric Mulliken embedding method involving an unequal splitting of the Mulliken overlap populations to offer improvement in situations where the Mulliken charges may be deficient.

Mixed QM/MM molecular electrostatic potentials.

PubMed

Hernández, B; Luque, F J; Orozco, M

2000-05-01

A new method is presented for the calculation of the Molecular Electrostatic Potential (MEP) in large systems. Based on the mixed Quantum Mechanics/Molecular Mechanics (QM/MM) approach, the method assumes both a quantum and classical description for the molecule, and the calculation of the MEP in the space surrounding the molecule is made using this dual treatment. The MEP at points close to the molecule is computed using a full QM formalism, while a pure classical evaluation of the MEP is used for points located at large distances from the molecule. The algorithm allows the user to select the desired level of accuracy in the MEP, so that the definition of the regions where the MEP is computed at the classical or QM levels is adjusted automatically. The potential use of this QM/MM MEP in molecular modeling studies is discussed.

Sensitivity of electrospray molecular dynamics simulations to long-range Coulomb interaction models

NASA Astrophysics Data System (ADS)

Mehta, Neil A.; Levin, Deborah A.

2018-03-01

Molecular dynamics (MD) electrospray simulations of 1-ethyl-3-methylimidazolium tetrafluoroborate (EMIM-BF4) ion liquid were performed with the goal of evaluating the influence of long-range Coulomb models on ion emission characteristics. The direct Coulomb (DC), shifted force Coulomb sum (SFCS), and particle-particle particle-mesh (PPPM) long-range Coulomb models were considered in this work. The DC method with a sufficiently large cutoff radius was found to be the most accurate approach for modeling electrosprays, but, it is computationally expensive. The Coulomb potential energy modeled by the DC method in combination with the radial electric fields were found to be necessary to generate the Taylor cone. The differences observed between the SFCS and the DC in terms of predicting the total ion emission suggest that the former should not be used in MD electrospray simulations. Furthermore, the common assumption of domain periodicity was observed to be detrimental to the accuracy of the capillary-based electrospray simulations.

Sensitivity of electrospray molecular dynamics simulations to long-range Coulomb interaction models.

PubMed

Mehta, Neil A; Levin, Deborah A

2018-03-01

Molecular dynamics (MD) electrospray simulations of 1-ethyl-3-methylimidazolium tetrafluoroborate (EMIM-BF_{4}) ion liquid were performed with the goal of evaluating the influence of long-range Coulomb models on ion emission characteristics. The direct Coulomb (DC), shifted force Coulomb sum (SFCS), and particle-particle particle-mesh (PPPM) long-range Coulomb models were considered in this work. The DC method with a sufficiently large cutoff radius was found to be the most accurate approach for modeling electrosprays, but, it is computationally expensive. The Coulomb potential energy modeled by the DC method in combination with the radial electric fields were found to be necessary to generate the Taylor cone. The differences observed between the SFCS and the DC in terms of predicting the total ion emission suggest that the former should not be used in MD electrospray simulations. Furthermore, the common assumption of domain periodicity was observed to be detrimental to the accuracy of the capillary-based electrospray simulations.

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

Comparative systems biology between human and animal models based on next-generation sequencing methods.

PubMed

Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

2013-04-01

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

A Practical Quantum Mechanics Molecular Mechanics Method for the Dynamical Study of Reactions in Biomolecules.

PubMed

Mendieta-Moreno, Jesús I; Marcos-Alcalde, Iñigo; Trabada, Daniel G; Gómez-Puertas, Paulino; Ortega, José; Mendieta, Jesús

2015-01-01

Quantum mechanics/molecular mechanics (QM/MM) methods are excellent tools for the modeling of biomolecular reactions. Recently, we have implemented a new QM/MM method (Fireball/Amber), which combines an efficient density functional theory method (Fireball) and a well-recognized molecular dynamics package (Amber), offering an excellent balance between accuracy and sampling capabilities. Here, we present a detailed explanation of the Fireball method and Fireball/Amber implementation. We also discuss how this tool can be used to analyze reactions in biomolecules using steered molecular dynamics simulations. The potential of this approach is shown by the analysis of a reaction catalyzed by the enzyme triose-phosphate isomerase (TIM). The conformational space and energetic landscape for this reaction are analyzed without a priori assumptions about the protonation states of the different residues during the reaction. The results offer a detailed description of the reaction and reveal some new features of the catalytic mechanism. In particular, we find a new reaction mechanism that is characterized by the intramolecular proton transfer from O1 to O2 and the simultaneous proton transfer from Glu 165 to C2. Copyright © 2015 Elsevier Inc. All rights reserved.

A hybrid framework of first principles molecular orbital calculations and a three-dimensional integral equation theory for molecular liquids: Multi-center molecular Ornstein-Zernike self-consistent field approach

NASA Astrophysics Data System (ADS)

Kido, Kentaro; Kasahara, Kento; Yokogawa, Daisuke; Sato, Hirofumi

2015-07-01

In this study, we reported the development of a new quantum mechanics/molecular mechanics (QM/MM)-type framework to describe chemical processes in solution by combining standard molecular-orbital calculations with a three-dimensional formalism of integral equation theory for molecular liquids (multi-center molecular Ornstein-Zernike (MC-MOZ) method). The theoretical procedure is very similar to the 3D-reference interaction site model self-consistent field (RISM-SCF) approach. Since the MC-MOZ method is highly parallelized for computation, the present approach has the potential to be one of the most efficient procedures to treat chemical processes in solution. Benchmark tests to check the validity of this approach were performed for two solute (solute water and formaldehyde) systems and a simple SN2 reaction (Cl- + CH3Cl → ClCH3 + Cl-) in aqueous solution. The results for solute molecular properties and solvation structures obtained by the present approach were in reasonable agreement with those obtained by other hybrid frameworks and experiments. In particular, the results of the proposed approach are in excellent agreements with those of 3D-RISM-SCF.

A hybrid framework of first principles molecular orbital calculations and a three-dimensional integral equation theory for molecular liquids: multi-center molecular Ornstein-Zernike self-consistent field approach.

PubMed

Kido, Kentaro; Kasahara, Kento; Yokogawa, Daisuke; Sato, Hirofumi

2015-07-07

In this study, we reported the development of a new quantum mechanics/molecular mechanics (QM/MM)-type framework to describe chemical processes in solution by combining standard molecular-orbital calculations with a three-dimensional formalism of integral equation theory for molecular liquids (multi-center molecular Ornstein-Zernike (MC-MOZ) method). The theoretical procedure is very similar to the 3D-reference interaction site model self-consistent field (RISM-SCF) approach. Since the MC-MOZ method is highly parallelized for computation, the present approach has the potential to be one of the most efficient procedures to treat chemical processes in solution. Benchmark tests to check the validity of this approach were performed for two solute (solute water and formaldehyde) systems and a simple SN2 reaction (Cl(-) + CH3Cl → ClCH3 + Cl(-)) in aqueous solution. The results for solute molecular properties and solvation structures obtained by the present approach were in reasonable agreement with those obtained by other hybrid frameworks and experiments. In particular, the results of the proposed approach are in excellent agreements with those of 3D-RISM-SCF.

Application of the Fokker-Planck molecular mixing model to turbulent scalar mixing using moment methods

NASA Astrophysics Data System (ADS)

Madadi-Kandjani, E.; Fox, R. O.; Passalacqua, A.

2017-06-01

An extended quadrature method of moments using the β kernel density function (β -EQMOM) is used to approximate solutions to the evolution equation for univariate and bivariate composition probability distribution functions (PDFs) of a passive scalar for binary and ternary mixing. The key element of interest is the molecular mixing term, which is described using the Fokker-Planck (FP) molecular mixing model. The direct numerical simulations (DNSs) of Eswaran and Pope ["Direct numerical simulations of the turbulent mixing of a passive scalar," Phys. Fluids 31, 506 (1988)] and the amplitude mapping closure (AMC) of Pope ["Mapping closures for turbulent mixing and reaction," Theor. Comput. Fluid Dyn. 2, 255 (1991)] are taken as reference solutions to establish the accuracy of the FP model in the case of binary mixing. The DNSs of Juneja and Pope ["A DNS study of turbulent mixing of two passive scalars," Phys. Fluids 8, 2161 (1996)] are used to validate the results obtained for ternary mixing. Simulations are performed with both the conditional scalar dissipation rate (CSDR) proposed by Fox [Computational Methods for Turbulent Reacting Flows (Cambridge University Press, 2003)] and the CSDR from AMC, with the scalar dissipation rate provided as input and obtained from the DNS. Using scalar moments up to fourth order, the ability of the FP model to capture the evolution of the shape of the PDF, important in turbulent mixing problems, is demonstrated. Compared to the widely used assumed β -PDF model [S. S. Girimaji, "Assumed β-pdf model for turbulent mixing: Validation and extension to multiple scalar mixing," Combust. Sci. Technol. 78, 177 (1991)], the β -EQMOM solution to the FP model more accurately describes the initial mixing process with a relatively small increase in computational cost.

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.

Interactions of cephalexin with bovine serum albumin: displacement reaction and molecular docking.

PubMed

Hamishehkar, Hamed; Hosseini, Soheila; Naseri, Abdolhossein; Safarnejad, Azam; Rasoulzadeh, Farzaneh

2016-01-01

Introduction: The drug-plasma protein interaction is a fundamental issue in guessing and checking the serious drug side effects related with other drugs. The purpose of this research was to study the interaction of cephalexin with bovine serum albumin (BSA) and displacement reaction using site probes. Methods: The interaction mechanism concerning cephalexin (CPL) with BSA was investigated using various spectroscopic methods and molecular modeling method. The binding sites number, n, apparent binding constant, K, and thermodynamic parameters, ΔG 0 , ΔH 0 , and ΔS 0 were considered at different temperatures. To evaluate the experimental results, molecular docking modeling was calculated. Results: The distance, r=1.156 nm between BSA and CPL were found in accordance with the Forster theory of non-radiation energy transfer (FRET) indicating energy transfer occurs between BSA and CPL. According to the binding parameters and ΔG 0 = negative values and ΔS 0 = 28.275 j mol -1 K -1 , a static quenching process is effective in the CPL-BSA interaction spontaneously. ΔG 0 for the CPL-BSA complex obtained from the docking simulation is -28.99 kj mol -1 , which is close to experimental ΔG of binding, -21.349 kj mol -1 that indicates a good agreement between the results of docking methods and experimental data. Conclusion: The outcomes of spectroscopic methods revealed that the conformation of BSA changed during drug-BSA interaction. The results of FRET propose that CPL quenches the fluorescence of BSA by static quenching and FRET. The displacement study showed that phenylbutazon and ketoprofen displaced CPL, indicating that its binding site on albumin is site I and Gentamicin cannot be displaced from the binding site of CPL. All results of molecular docking method agreed with the results of experimental data.

Overview of the SAMPL5 host–guest challenge: Are we doing better?

PubMed Central

Yin, Jian; Henriksen, Niel M.; Slochower, David R.; Shirts, Michael R.; Chiu, Michael W.; Mobley, David L.; Gilson, Michael K.

2016-01-01

The ability to computationally predict protein-small molecule binding affinities with high accuracy would accelerate drug discovery and reduce its cost by eliminating rounds of trial-and-error synthesis and experimental evaluation of candidate ligands. As academic and industrial groups work toward this capability, there is an ongoing need for datasets that can be used to rigorously test new computational methods. Although protein–ligand data are clearly important for this purpose, their size and complexity make it difficult to obtain well-converged results and to troubleshoot computational methods. Host–guest systems offer a valuable alternative class of test cases, as they exemplify noncovalent molecular recognition but are far smaller and simpler. As a consequence, host–guest systems have been part of the prior two rounds of SAMPL prediction exercises, and they also figure in the present SAMPL5 round. In addition to being blinded, and thus avoiding biases that may arise in retrospective studies, the SAMPL challenges have the merit of focusing multiple researchers on a common set of molecular systems, so that methods may be compared and ideas exchanged. The present paper provides an overview of the host–guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution. A range of methods were applied, including electronic structure calculations with implicit solvent models; methods that combine empirical force fields with implicit solvent models; and explicit solvent free energy simulations. The most reliable methods tend to fall in the latter class, consistent with results in prior SAMPL rounds, but the level of accuracy is still below that sought for reliable computer-aided drug design. Advances in force field accuracy, modeling of protonation equilibria, electronic structure methods, and solvent models, hold promise for future improvements. PMID:27658802

Overview of the SAMPL5 host-guest challenge: Are we doing better?

PubMed

Yin, Jian; Henriksen, Niel M; Slochower, David R; Shirts, Michael R; Chiu, Michael W; Mobley, David L; Gilson, Michael K

2017-01-01

The ability to computationally predict protein-small molecule binding affinities with high accuracy would accelerate drug discovery and reduce its cost by eliminating rounds of trial-and-error synthesis and experimental evaluation of candidate ligands. As academic and industrial groups work toward this capability, there is an ongoing need for datasets that can be used to rigorously test new computational methods. Although protein-ligand data are clearly important for this purpose, their size and complexity make it difficult to obtain well-converged results and to troubleshoot computational methods. Host-guest systems offer a valuable alternative class of test cases, as they exemplify noncovalent molecular recognition but are far smaller and simpler. As a consequence, host-guest systems have been part of the prior two rounds of SAMPL prediction exercises, and they also figure in the present SAMPL5 round. In addition to being blinded, and thus avoiding biases that may arise in retrospective studies, the SAMPL challenges have the merit of focusing multiple researchers on a common set of molecular systems, so that methods may be compared and ideas exchanged. The present paper provides an overview of the host-guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution. A range of methods were applied, including electronic structure calculations with implicit solvent models; methods that combine empirical force fields with implicit solvent models; and explicit solvent free energy simulations. The most reliable methods tend to fall in the latter class, consistent with results in prior SAMPL rounds, but the level of accuracy is still below that sought for reliable computer-aided drug design. Advances in force field accuracy, modeling of protonation equilibria, electronic structure methods, and solvent models, hold promise for future improvements.

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

Features of Extrusion Processing of Ultrahigh Molecular Weight Polyethylene. Experiment and Theory

NASA Astrophysics Data System (ADS)

Skul‧skii, O. I.; Slavnov, E. V.

2018-05-01

Experimental studies have been made of the permissible regimes of processing ultrahigh molecular weight polyethylene GUR 2122 with molecular mass of 4.5 million g/moles in a laboratory extruder with an auger diameter 32 mm and a ratio L/D = 20 at temperatures of 155-165oC. On the basis of rotational viscometry, the rheological properties of the melt are described. A mathematical model and a numerical method for calculating the motion of ultrahigh molecular weight polyethylene melt in the auger and in the moulding rigging are proposed. The velocity and stress fields have been determined.

Optical spectroscopy and system-bath interactions in molecular aggregates with full configuration interaction Frenkel exciton model

NASA Astrophysics Data System (ADS)

Seibt, Joachim; Sláma, Vladislav; Mančal, Tomáš

2016-12-01

Standard application of the Frenkel exciton model neglects resonance coupling between collective molecular aggregate states with different number of excitations. These inter-band coupling terms are, however, of the same magnitude as the intra-band coupling between singly excited states. We systematically derive the Frenkel exciton model from quantum chemical considerations, and identify it as a variant of the configuration interaction method. We discuss all non-negligible couplings between collective aggregate states, and provide compact formulae for their calculation. We calculate absorption spectra of molecular aggregate of carotenoids and identify significant band shifts as a result of inter-band coupling. The presence of inter-band coupling terms requires renormalization of the system-bath coupling with respect to standard formulation, but renormalization effects are found to be weak. We present detailed discussion of molecular dimer and calculate its time-resolved two-dimensional Fourier transformed spectra to find weak but noticeable effects of peak amplitude redistribution due to inter-band coupling.

Tabletop Molecular Communication: Text Messages through Chemical Signals

PubMed Central

Farsad, Nariman; Guo, Weisi; Eckford, Andrew W.

2013-01-01

In this work, we describe the first modular, and programmable platform capable of transmitting a text message using chemical signalling – a method also known as molecular communication. This form of communication is attractive for applications where conventional wireless systems perform poorly, from nanotechnology to urban health monitoring. Using examples, we demonstrate the use of our platform as a testbed for molecular communication, and illustrate the features of these communication systems using experiments. By providing a simple and inexpensive means of performing experiments, our system fills an important gap in the molecular communication literature, where much current work is done in simulation with simplified system models. A key finding in this paper is that these systems are often nonlinear in practice, whereas current simulations and analysis often assume that the system is linear. However, as we show in this work, despite the nonlinearity, reliable communication is still possible. Furthermore, this work motivates future studies on more realistic modelling, analysis, and design of theoretical models and algorithms for these systems. PMID:24367571

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.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

PubMed

Armen, Roger S; Chen, Jianhan; Brooks, Charles L

2009-10-13

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics

PubMed Central

Armen, Roger S.; Chen, Jianhan; Brooks, Charles L.

2009-01-01

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and “noise” that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds. PMID:20160879

Molecular modeling-driven approach for identification of Janus kinase 1 inhibitors through 3D-QSAR, docking and molecular dynamics simulations.

PubMed

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2017-10-01

Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r 2 ncv and q 2 loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r 2 Pred ) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.

Multiensemble Markov models of molecular thermodynamics and kinetics

PubMed Central

Wu, Hao; Paul, Fabian; Noé, Frank

2016-01-01

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models—clustering of high-dimensional spaces and modeling of complex many-state systems—with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein–ligand binding model. PMID:27226302

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation.

PubMed

Paluch, Andrew S; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L

2015-01-28

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation

NASA Astrophysics Data System (ADS)

Paluch, Andrew S.; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L.

2015-01-01

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

Calibration and validation of coarse-grained models of atomic systems: application to semiconductor manufacturing

NASA Astrophysics Data System (ADS)

Farrell, Kathryn; Oden, J. Tinsley

2014-07-01

Coarse-grained models of atomic systems, created by aggregating groups of atoms into molecules to reduce the number of degrees of freedom, have been used for decades in important scientific and technological applications. In recent years, interest in developing a more rigorous theory for coarse graining and in assessing the predictivity of coarse-grained models has arisen. In this work, Bayesian methods for the calibration and validation of coarse-grained models of atomistic systems in thermodynamic equilibrium are developed. For specificity, only configurational models of systems in canonical ensembles are considered. Among major challenges in validating coarse-grained models are (1) the development of validation processes that lead to information essential in establishing confidence in the model's ability predict key quantities of interest and (2), above all, the determination of the coarse-grained model itself; that is, the characterization of the molecular architecture, the choice of interaction potentials and thus parameters, which best fit available data. The all-atom model is treated as the "ground truth," and it provides the basis with respect to which properties of the coarse-grained model are compared. This base all-atom model is characterized by an appropriate statistical mechanics framework in this work by canonical ensembles involving only configurational energies. The all-atom model thus supplies data for Bayesian calibration and validation methods for the molecular model. To address the first challenge, we develop priors based on the maximum entropy principle and likelihood functions based on Gaussian approximations of the uncertainties in the parameter-to-observation error. To address challenge (2), we introduce the notion of model plausibilities as a means for model selection. This methodology provides a powerful approach toward constructing coarse-grained models which are most plausible for given all-atom data. We demonstrate the theory and methods through applications to representative atomic structures and we discuss extensions to the validation process for molecular models of polymer structures encountered in certain semiconductor nanomanufacturing processes. The powerful method of model plausibility as a means for selecting interaction potentials for coarse-grained models is discussed in connection with a coarse-grained hexane molecule. Discussions of how all-atom information is used to construct priors are contained in an appendix.

A Density Functional Approach to Polarizable Models: A Kim-Gordon-Response Density Interaction Potential for Molecular Simulations

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

Tabacchi, G; Hutter, J; Mundy, C

2005-04-07

A combined linear response--frozen electron density model has been implemented in a molecular dynamics scheme derived from an extended Lagrangian formalism. This approach is based on a partition of the electronic charge distribution into a frozen region described by Kim-Gordon theory, and a response contribution determined by the instaneous ionic configuration of the system. The method is free from empirical pair-potentials and the parameterization protocol involves only calculations on properly chosen subsystems. They apply this method to a series of alkali halides in different physical phases and are able to reproduce experimental structural and thermodynamic properties with an accuracy comparablemore » to Kohn-Sham density functional calculations.« less

In silico environmental chemical science: properties and processes from statistical and computational modelling

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

Tratnyek, Paul G.; Bylaska, Eric J.; Weber, Eric J.

2017-01-01

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs usingmore » descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.« less

From deep TLS validation to ensembles of atomic models built from elemental motions

DOE PAGES

Urzhumtsev, Alexandre; Afonine, Pavel V.; Van Benschoten, Andrew H.; ...

2015-07-28

The translation–libration–screw model first introduced by Cruickshank, Schomaker and Trueblood describes the concerted motions of atomic groups. Using TLS models can improve the agreement between calculated and experimental diffraction data. Because the T, L and S matrices describe a combination of atomic vibrations and librations, TLS models can also potentially shed light on molecular mechanisms involving correlated motions. However, this use of TLS models in mechanistic studies is hampered by the difficulties in translating the results of refinement into molecular movement or a structural ensemble. To convert the matrices into a constituent molecular movement, the matrix elements must satisfy severalmore » conditions. Refining the T, L and S matrix elements as independent parameters without taking these conditions into account may result in matrices that do not represent concerted molecular movements. Here, a mathematical framework and the computational tools to analyze TLS matrices, resulting in either explicit decomposition into descriptions of the underlying motions or a report of broken conditions, are described. The description of valid underlying motions can then be output as a structural ensemble. All methods are implemented as part of the PHENIX project.« less

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.

Bottom-up derivation of conservative and dissipative interactions for coarse-grained molecular liquids with the conditional reversible work method

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

Deichmann, Gregor; Marcon, Valentina; Vegt, Nico F. A. van der, E-mail: vandervegt@csi.tu-darmstadt.de

Molecular simulations of soft matter systems have been performed in recent years using a variety of systematically coarse-grained models. With these models, structural or thermodynamic properties can be quite accurately represented while the prediction of dynamic properties remains difficult, especially for multi-component systems. In this work, we use constraint molecular dynamics simulations for calculating dissipative pair forces which are used together with conditional reversible work (CRW) conservative forces in dissipative particle dynamics (DPD) simulations. The combined CRW-DPD approach aims to extend the representability of CRW models to dynamic properties and uses a bottom-up approach. Dissipative pair forces are derived frommore » fluctuations of the direct atomistic forces between mapped groups. The conservative CRW potential is obtained from a similar series of constraint dynamics simulations and represents the reversible work performed to couple the direct atomistic interactions between the mapped atom groups. Neopentane, tetrachloromethane, cyclohexane, and n-hexane have been considered as model systems. These molecular liquids are simulated with atomistic molecular dynamics, coarse-grained molecular dynamics, and DPD. We find that the CRW-DPD models reproduce the liquid structure and diffusive dynamics of the liquid systems in reasonable agreement with the atomistic models when using single-site mapping schemes with beads containing five or six heavy atoms. For a two-site representation of n-hexane (3 carbons per bead), time scale separation can no longer be assumed and the DPD approach consequently fails to reproduce the atomistic dynamics.« less

Use of the Monte Carlo Method for OECD Principles-Guided QSAR Modeling of SIRT1 Inhibitors.

PubMed

Kumar, Ashwani; Chauhan, Shilpi

2017-01-01

SIRT1 inhibitors offer therapeutic potential for the treatment of a number of diseases including cancer and human immunodeficiency virus infection. A diverse series of 45 compounds with reported SIRT1 inhibitory activity has been employed for the development of quantitative structure-activity relationship (QSAR) models using the Monte Carlo optimization method. This method makes use of simplified molecular input line entry system notation of the molecular structure. The QSAR models were built up according to OECD principles. Three subsets of three splits were examined and validated by respective external sets. All the three described models have good statistical quality. The best model has the following statistical characteristics: R 2  = 0.8350, Q 2 test  = 0.7491 for the test set and R 2  = 0.9655, Q 2 ext  = 0.9261 for the validation set. In the mechanistic interpretation, structural attributes responsible for the endpoint increase and decrease are defined. Further, the design of some prospective SIRT1 inhibitors is also presented on the basis of these structural attributes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling disordered protein interactions from biophysical principles

PubMed Central

Christoffer, Charles; Terashi, Genki

2017-01-01

Disordered protein-protein interactions (PPIs), those involving a folded protein and an intrinsically disordered protein (IDP), are prevalent in the cell, including important signaling and regulatory pathways. IDPs do not adopt a single dominant structure in isolation but often become ordered upon binding. To aid understanding of the molecular mechanisms of disordered PPIs, it is crucial to obtain the tertiary structure of the PPIs. However, experimental methods have difficulty in solving disordered PPIs and existing protein-protein and protein-peptide docking methods are not able to model them. Here we present a novel computational method, IDP-LZerD, which models the conformation of a disordered PPI by considering the biophysical binding mechanism of an IDP to a structured protein, whereby a local segment of the IDP initiates the interaction and subsequently the remaining IDP regions explore and coalesce around the initial binding site. On a dataset of 22 disordered PPIs with IDPs up to 69 amino acids, successful predictions were made for 21 bound and 18 unbound receptors. The successful modeling provides additional support for biophysical principles. Moreover, the new technique significantly expands the capability of protein structure modeling and provides crucial insights into the molecular mechanisms of disordered PPIs. PMID:28394890

Combined 3D-QSAR modeling and molecular docking study on azacycles CCR5 antagonists

NASA Astrophysics Data System (ADS)

Ji, Yongjun; Shu, Mao; Lin, Yong; Wang, Yuanqiang; Wang, Rui; Hu, Yong; Lin, Zhihua

2013-08-01

The beta chemokine receptor 5 (CCR5) is an attractive target for pharmaceutical industry in the HIV-1, inflammation and cancer therapeutic areas. In this study, we have developed quantitative structure activity relationship (QSAR) models for a series of 41 azacycles CCR5 antagonists using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and Topomer CoMFA methods. The cross-validated coefficient q2 values of 3D-QASR (CoMFA, CoMSIA, and Topomer CoMFA) methods were 0.630, 0.758, and 0.852, respectively, the non-cross-validated R2 values were 0.979, 0.978, and 0.990, respectively. Docking studies were also employed to determine the most probable binding mode. 3D contour maps and docking results suggested that bulky groups and electron-withdrawing groups on the core part would decrease antiviral activity. Furthermore, docking results indicated that H-bonds and π bonds were favorable for antiviral activities. Finally, a set of novel derivatives with predicted activities were designed.

Using molecular dynamics simulations and finite element method to study the mechanical properties of nanotube reinforced polyethylene and polyketone

NASA Astrophysics Data System (ADS)

Rouhi, S.; Alizadeh, Y.; Ansari, R.; Aryayi, M.

2015-09-01

Molecular dynamics simulations are used to study the mechanical behavior of single-walled carbon nanotube reinforced composites. Polyethylene and polyketone are selected as the polymer matrices. The effects of nanotube atomic structure and diameter on the mechanical properties of polymer matrix nanocomposites are investigated. It is shown that although adding nanotube to the polymer matrix raises the longitudinal elastic modulus significantly, the transverse tensile and shear moduli do not experience important change. As the previous finite element models could not be used for polymer matrices with the atom types other than carbon, molecular dynamics simulations are used to propose a finite element model which can be used for any polymer matrices. It is shown that this model can predict Young’s modulus with an acceptable accuracy.

Atomic-scale modeling of cellulose nanocrystals

NASA Astrophysics Data System (ADS)

Wu, Xiawa

Cellulose nanocrystals (CNCs), the most abundant nanomaterials in nature, are recognized as one of the most promising candidates to meet the growing demand of green, bio-degradable and sustainable nanomaterials for future applications. CNCs draw significant interest due to their high axial elasticity and low density-elasticity ratio, both of which are extensively researched over the years. In spite of the great potential of CNCs as functional nanoparticles for nanocomposite materials, a fundamental understanding of CNC properties and their role in composite property enhancement is not available. In this work, CNCs are studied using molecular dynamics simulation method to predict their material' behaviors in the nanoscale. (a) Mechanical properties include tensile deformation in the elastic and plastic regions using molecular mechanics, molecular dynamics and nanoindentation methods. This allows comparisons between the methods and closer connectivity to experimental measurement techniques. The elastic moduli in the axial and transverse directions are obtained and the results are found to be in good agreement with previous research. The ultimate properties in plastic deformation are reported for the first time and failure mechanism are analyzed in details. (b) The thermal expansion of CNC crystals and films are studied. It is proposed that CNC film thermal expansion is due primarily to single crystal expansion and CNC-CNC interfacial motion. The relative contributions of inter- and intra-crystal responses to heating are explored. (c) Friction at cellulose-CNCs and diamond-CNCs interfaces is studied. The effects of sliding velocity, normal load, and relative angle between sliding surfaces are predicted. The Cellulose-CNC model is analyzed in terms of hydrogen bonding effect, and the diamond-CNC model compliments some of the discussion of the previous model. In summary, CNC's material properties and molecular models are both studied in this research, contributing to the present understanding of this material and leading to some possible future work.

Development of the Next Generation of Biogeochemistry Simulations Using EMSL's NWChem Molecular Modeling Software

NASA Astrophysics Data System (ADS)

Bylaska, E. J.; Kowalski, K.; Apra, E.; Govind, N.; Valiev, M.

2017-12-01

Methods of directly simulating the behavior of complex strongly interacting atomic systems (molecular dynamics, Monte Carlo) have provided important insight into the behavior of nanoparticles, biogeochemical systems, mineral/fluid systems, nanoparticles, actinide systems and geofluids. The limitation of these methods to even wider applications is the difficulty of developing accurate potential interactions in these systems at the molecular level that capture their complex chemistry. The well-developed tools of quantum chemistry and physics have been shown to approach the accuracy required. However, despite the continuous effort being put into improving their accuracy and efficiency, these tools will be of little value to condensed matter problems without continued improvements in techniques to traverse and sample the high-dimensional phase space needed to span the ˜10^12 time scale differences between molecular simulation and chemical events. In recent years, we have made considerable progress in developing electronic structure and AIMD methods tailored to treat biochemical and geochemical problems, including very efficient implementations of many-body methods, fast exact exchange methods, electron-transfer methods, excited state methods, QM/MM, and new parallel algorithms that scale to +100,000 cores. The poster will focus on the fundamentals of these methods and the realities in terms of system size, computational requirements and simulation times that are required for their application to complex biogeochemical systems.

Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation

PubMed Central

Garcia Lopez, Sebastian; Kim, Philip M.

2014-01-01

Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT) algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases. PMID:25243403

The Renormalization Group and Its Applications to Generating Coarse-Grained Models of Large Biological Molecular Systems.

PubMed

Koehl, Patrice; Poitevin, Frédéric; Navaza, Rafael; Delarue, Marc

2017-03-14

Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.

Molecular replacement: tricks and treats

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

Abergel, Chantal, E-mail: chantal.abergel@igs.cnrs-mrs.fr

2013-11-01

To be successful, molecular replacement relies on the quality of the model and of the crystallographic data. Some tricks that could be applied to the models or to the crystal to increase the success rate of MR are discussed here. Molecular replacement is the method of choice for X-ray crystallographic structure determination provided that suitable structural homologues are available in the PDB. Presently, there are ∼80 000 structures in the PDB (8074 were deposited in the year 2012 alone), of which ∼70% have been solved by molecular replacement. For successful molecular replacement the model must cover at least 50% ofmore » the total structure and the C{sub α} r.m.s.d. between the core model and the structure to be solved must be less than 2 Å. Here, an approach originally implemented in the CaspR server (http://www.igs.cnrs-mrs.fr/Caspr2/index.cgi) based on homology modelling to search for a molecular-replacement solution is discussed. How the use of as much information as possible from different sources can improve the model(s) is briefly described. The combination of structural information with distantly related sequences is crucial to optimize the multiple alignment that will define the boundaries of the core domains. PDB clusters (sequences with ≥30% identical residues) can also provide information on the eventual changes in conformation and will help to explore the relative orientations assumed by protein subdomains. Normal-mode analysis can also help in generating series of conformational models in the search for a molecular-replacement solution. Of course, finding a correct solution is only the first step and the accuracy of the identified solution is as important as the data quality to proceed through refinement. Here, some possible reasons for failure are discussed and solutions are proposed using a set of successful examples.« less

The numerical modelling of MHD astrophysical flows with chemistry

NASA Astrophysics Data System (ADS)

Kulikov, I.; Chernykh, I.; Protasov, V.

2017-10-01

The new code for numerical simulation of magnetic hydrodynamical astrophysical flows with consideration of chemical reactions is given in the paper. At the heart of the code - the new original low-dissipation numerical method based on a combination of operator splitting approach and piecewise-parabolic method on the local stencil. The chemodynamics of the hydrogen while the turbulent formation of molecular clouds is modeled.

Atomistic models for free energy evaluation of drug binding to membrane proteins.

PubMed

Durdagi, S; Zhao, C; Cuervo, J E; Noskov, S Y

2011-01-01

The binding of various molecules to integral membrane proteins with optimal affinity and specificity is central to normal function of cell. While membrane proteins represent about one third of the whole cell proteome, they are a majority of common drug targets. The quest for the development of computational models capable of accurate evaluation of binding affinities, decomposition of the binding into its principal components and thus mapping molecular mechanisms of binding remains one of the main goals of modern computational biophysics and related drug development. The primary scope of this review will be on the recent extension of computational methods for the study of drug binding to membrane proteins. Several examples of such applications will be provided ranging from secondary transporters to voltage gated channels. In this mini-review, we will provide a short summary on the breadth of different methods for binding affinity evaluation. These methods include molecular docking with docking scoring functions, molecular dynamics (MD) simulations combined with post-processing analysis using Molecular Mechanics/Poisson Boltzmann (Generalized Born) Surface Area (MM/PB(GB)SA), as well as direct evaluation of free energies from Free Energy Perturbation (FEP) with constraining schemes, and Potential of Mean Force (PMF) computations. We will compare advantages and shortcomings of popular techniques and provide discussion on the integrative strategies for drug development aimed at targeting membrane proteins.

Electronic and transport properties of a molecular junction with asymmetric contacts.

PubMed

Tsai, M-H; Lu, T-H

2010-02-10

Asymmetric molecular junctions have been shown experimentally to exhibit a dual-conductance transport property with a pulse-like current-voltage characteristic, by Reed and co-workers. Using a recently developed first-principles integrated piecewise thermal equilibrium current calculation method and a gold-benzene-1-olate-4-thiolate-gold model molecular junction, this unusual transport property has been reproduced. Analysis of the electrostatics and the electronic structure reveals that the high-current state results from subtle bias induced charge transfer at the electrode-molecule contacts that raises molecular orbital energies and enhances the current-contributing molecular density of states and the probabilities of resonance tunneling of conduction electrons from one electrode to another.

Polarizable Force Fields and Polarizable Continuum Model: A Fluctuating Charges/PCM Approach. 1. Theory and Implementation.

PubMed

Lipparini, Filippo; Barone, Vincenzo

2011-11-08

We present a combined fluctuating charges-polarizable continuum model approach to describe molecules in solution. Both static and dynamic approaches are discussed: analytical first and second derivatives are shown as well as an extended lagrangian for molecular dynamics simluations. In particular, we use the polarizable continuum model to provide nonperiodic boundary conditions for molecular dynamics simulations of aqueous solutions. The extended lagrangian method is extensively discussed, with specific reference to the fluctuating charge model, from a numerical point of view by means of several examples, and a rationalization of the behavior found is presented. Several prototypical applications are shown, especially regarding solvation of ions and polar molecules in water.

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.

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

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

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

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

DOE PAGES

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; ...

2017-11-27

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

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.

Isobaric molecular dynamics version of the generalized replica exchange method (gREM): Liquid–vapor equilibrium

DOE PAGES

Malolepsza, Edyta; Secor, Maxim; Keyes, Tom

2015-09-23

A prescription for sampling isobaric generalized ensembles with molecular dynamics is presented and applied to the generalized replica exchange method (gREM), which was designed for simulating first-order phase transitions. The properties of the isobaric gREM ensemble are discussed and a study is presented of the liquid-vapor equilibrium of the guest molecules given for gas hydrate formation with the mW water model. As a result, phase diagrams, critical parameters, and a law of corresponding states are obtained.

Hybrid Quantum Mechanics/Molecular Mechanics Solvation Scheme for Computing Free Energies of Reactions at Metal-Water Interfaces.

PubMed

Faheem, Muhammad; Heyden, Andreas

2014-08-12

We report the development of a quantum mechanics/molecular mechanics free energy perturbation (QM/MM-FEP) method for modeling chemical reactions at metal-water interfaces. This novel solvation scheme combines planewave density function theory (DFT), periodic electrostatic embedded cluster method (PEECM) calculations using Gaussian-type orbitals, and classical molecular dynamics (MD) simulations to obtain a free energy description of a complex metal-water system. We derive a potential of mean force (PMF) of the reaction system within the QM/MM framework. A fixed-size, finite ensemble of MM conformations is used to permit precise evaluation of the PMF of QM coordinates and its gradient defined within this ensemble. Local conformations of adsorbed reaction moieties are optimized using sequential MD-sampling and QM-optimization steps. An approximate reaction coordinate is constructed using a number of interpolated states and the free energy difference between adjacent states is calculated using the QM/MM-FEP method. By avoiding on-the-fly QM calculations and by circumventing the challenges associated with statistical averaging during MD sampling, a computational speedup of multiple orders of magnitude is realized. The method is systematically validated against the results of ab initio QM calculations and demonstrated for C-C cleavage in double-dehydrogenated ethylene glycol on a Pt (111) model surface.

Comparison of methods of DNA extraction for real-time PCR in a model of pleural tuberculosis.

PubMed

Santos, Ana; Cremades, Rosa; Rodríguez, Juan Carlos; García-Pachón, Eduardo; Ruiz, Montserrat; Royo, Gloria

2010-01-01

Molecular methods have been reported to have different sensitivities in the diagnosis of pleural tuberculosis and this may in part be caused by the use of different methods of DNA extraction. Our study compares nine DNA extraction systems in an experimental model of pleural tuberculosis. An inoculum of Mycobacterium tuberculosis was added to 23 pleural liquid samples with different characteristics. DNA was subsequently extracted using nine different methods (seven manual and two automatic) for analysis with real-time PCR. Only two methods were able to detect the presence of M. tuberculosis DNA in all the samples: extraction using columns (Qiagen) and automated extraction with the TNAI system (Roche). The automatic method is more expensive, but requires less time. Almost all the false negatives were because of the difficulty involved in extracting M. tuberculosis DNA, as in general, all the methods studied are capable of eliminating inhibitory substances that block the amplification reaction. The method of M. tuberculosis DNA extraction used affects the results of the diagnosis of pleural tuberculosis by molecular methods. DNA extraction systems that have been shown to be effective in pleural liquid should be used.

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.

The Hartree-Fock calculation of the magnetic properties of molecular solutes

NASA Astrophysics Data System (ADS)

Cammi, R.

1998-08-01

In this paper we set the formal bases for the calculation of the magnetic susceptibility and of the nuclear magnetic shielding tensors for molecular solutes described within the framework of the polarizable continuum model (PCM). The theory has been developed at self-consistent field (SCF) level and adapted to be used within the framework of some of the computational procedures of larger use, i.e., the gauge invariant atomic orbital method (GIAO) and the continuous set gauge transformation method (CSGT). The numerical results relative to the magnetizabilities and chemical shielding of acetonitrile and nitrometane in various solvents computed with the PCM-CSGT method are also presented.

Communication: On the consistency of approximate quantum dynamics simulation methods for vibrational spectra in the condensed phase.

PubMed

Rossi, Mariana; Liu, Hanchao; Paesani, Francesco; Bowman, Joel; Ceriotti, Michele

2014-11-14

Including quantum mechanical effects on the dynamics of nuclei in the condensed phase is challenging, because the complexity of exact methods grows exponentially with the number of quantum degrees of freedom. Efforts to circumvent these limitations can be traced down to two approaches: methods that treat a small subset of the degrees of freedom with rigorous quantum mechanics, considering the rest of the system as a static or classical environment, and methods that treat the whole system quantum mechanically, but using approximate dynamics. Here, we perform a systematic comparison between these two philosophies for the description of quantum effects in vibrational spectroscopy, taking the Embedded Local Monomer model and a mixed quantum-classical model as representatives of the first family of methods, and centroid molecular dynamics and thermostatted ring polymer molecular dynamics as examples of the latter. We use as benchmarks D2O doped with HOD and pure H2O at three distinct thermodynamic state points (ice Ih at 150 K, and the liquid at 300 K and 600 K), modeled with the simple q-TIP4P/F potential energy and dipole moment surfaces. With few exceptions the different techniques yield IR absorption frequencies that are consistent with one another within a few tens of cm(-1). Comparison with classical molecular dynamics demonstrates the importance of nuclear quantum effects up to the highest temperature, and a detailed discussion of the discrepancies between the various methods let us draw some (circumstantial) conclusions about the impact of the very different approximations that underlie them. Such cross validation between radically different approaches could indicate a way forward to further improve the state of the art in simulations of condensed-phase quantum dynamics.

Atomistic simulation of solid-liquid coexistence for molecular systems: application to triazole and benzene.

PubMed

Eike, David M; Maginn, Edward J

2006-04-28

A method recently developed to rigorously determine solid-liquid equilibrium using a free-energy-based analysis has been extended to analyze multiatom molecular systems. This method is based on using a pseudosupercritical transformation path to reversibly transform between solid and liquid phases. Integration along this path yields the free energy difference at a single state point, which can then be used to determine the free energy difference as a function of temperature and therefore locate the coexistence temperature at a fixed pressure. The primary extension reported here is the introduction of an external potential field capable of inducing center of mass order along with secondary orientational order for molecules. The method is used to calculate the melting point of 1-H-1,2,4-triazole and benzene. Despite the fact that the triazole model gives accurate bulk densities for the liquid and crystal phases, it is found to do a poor job of reproducing the experimental crystal structure and heat of fusion. Consequently, it yields a melting point that is 100 K lower than the experimental value. On the other hand, the benzene model has been parametrized extensively to match a wide range of properties and yields a melting point that is only 20 K lower than the experimental value. Previous work in which a simple "direct heating" method was used actually found that the melting point of the benzene model was 50 K higher than the experimental value. This demonstrates the importance of using proper free energy methods to compute phase behavior. It also shows that the melting point is a very sensitive measure of force field quality that should be considered in parametrization efforts. The method described here provides a relatively simple approach for computing melting points of molecular systems.

Zebrafish for the Study of the Biological Effects of Nicotine

PubMed Central

Klee, Eric W.; Schneider, Henning; Hurt, Richard D.; Ekker, Stephen C.

2011-01-01

Introduction: Zebrafish are emerging as a powerful animal model for studying the molecular and physiological effects of nicotine exposure. The zebrafish have many advantageous physical characteristics, including small size, high fecundity rates, and externally developing transparent embryos. When combined with a battery of molecular–genetic tools and behavioral assays, these attributes enable studies to be conducted that are not practical using traditional animal models. Methods: We reviewed the literature on the application of the zebrafish model as a preclinical model to study the biological effects of nicotine exposure. Results: The identified studies used zebrafish to examine the effects of nicotine exposure on early development, addiction, anxiety, and learning. The methods used included green fluorescent protein–labeled proteins to track in vivo nicotine-altered neuron development, nicotine-conditioned place preference, and locomotive sensitization linked with high-throughput molecular and genetic screens and behavioral models of learning and stress response to nicotine. Data are presented on the complete homology of all known human neural nicotinic acetylcholine receptors in zebrafish and on the biological similarity of human and zebrafish dopaminergic signaling. Conclusions: Tobacco dependence remains a major health problem worldwide. Further understanding of the molecular effects of nicotine exposure and genetic contributions to dependence may lead to improvement in patient treatment strategies. While there are limitations to the use of zebrafish as a preclinical model, it should provide a valuable tool to complement existing model systems. The reviewed studies demonstrate the enormous opportunity zebrafish have to advance the science of nicotine and tobacco research. PMID:21385906

Hybrid quantum and molecular mechanics embedded cluster models for chemistry on silicon and silicon carbide surfaces

NASA Astrophysics Data System (ADS)

Shoemaker, James Richard

Fabrication of silicon carbide (SiC) semiconductor devices are of interest for aerospace applications because of their high-temperature tolerance. Growth of an insulating SiO2 layer on SiC by oxidation is a poorly understood process, and sometimes produces interface defects that degrade device performance. Accurate theoretical models of surface chemistry, using quantum mechanics (QM), do not exist because of the huge computational cost of solving Schrodinger's equation for a molecular cluster large enough to represent a surface. Molecular mechanics (MM), which describes a molecule as a collection of atoms interacting through classical potentials, is a fast computational method, good at predicting molecular structure, but cannot accurately model chemical reactions. A new hybrid QM/MM computational method for surface chemistry was developed and applied to silicon and SiC surfaces. The addition of MM steric constraints was shown to have a large effect on the energetics of O atom adsorption on SiC. Adsorption of O atoms on Si-terminated SiC(111) favors above surface sites, in contrast to Si(111), but favors subsurface adsorption sites on C- terminated SiC(111). This difference, and the energetics of C atom etching via CO2 desorption, can explain the observed poor performance of SiC devices in which insulating layers were grown on C-terminated surfaces.

A Geometric Method for Model Reduction of Biochemical Networks with Polynomial Rate Functions.

PubMed

Samal, Satya Swarup; Grigoriev, Dima; Fröhlich, Holger; Weber, Andreas; Radulescu, Ovidiu

2015-12-01

Model reduction of biochemical networks relies on the knowledge of slow and fast variables. We provide a geometric method, based on the Newton polytope, to identify slow variables of a biochemical network with polynomial rate functions. The gist of the method is the notion of tropical equilibration that provides approximate descriptions of slow invariant manifolds. Compared to extant numerical algorithms such as the intrinsic low-dimensional manifold method, our approach is symbolic and utilizes orders of magnitude instead of precise values of the model parameters. Application of this method to a large collection of biochemical network models supports the idea that the number of dynamical variables in minimal models of cell physiology can be small, in spite of the large number of molecular regulatory actors.

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.

Simulation of electric double-layer capacitors: evaluation of constant potential method

NASA Astrophysics Data System (ADS)

Wang, Zhenxing; Laird, Brian; Yang, Yang; Olmsted, David; Asta, Mark

2014-03-01

Atomistic simulations can play an important role in understanding electric double-layer capacitors (EDLCs) at a molecular level. In such simulations, typically the electrode surface is modeled using fixed surface charges, which ignores the charge fluctuation induced by local fluctuations in the electrolyte solution. In this work we evaluate an explicit treatment of charges, namely constant potential method (CPM)[1], in which the electrode charges are dynamically updated to maintain constant electrode potential. We employ a model system with a graphite electrode and a LiClO4/acetonitrile electrolyte, examined as a function of electrode potential differences. Using various molecular and macroscopic properties as metrics, we compare CPM simulations on this system to results using fixed surface charges. Specifically, results for predicted capacity, electric potential gradient and solvent density profile are identical between the two methods; However, ion density profiles and solvation structure yield significantly different results.

Carbon chemistry in dense molecular clouds: Theory and observational constraints

NASA Technical Reports Server (NTRS)

Blake, Geoffrey A.

1990-01-01

For the most part, gas phase models of the chemistry of dense molecular clouds predict the abundances of simple species rather well. However, for larger molecules and even for small systems rich in carbon these models often fail spectacularly. Researchers present a brief review of the basic assumptions and results of large scale modeling of the carbon chemistry in dense molecular clouds. Particular attention is to the influence of the gas phase C/O ratio in molecular clouds, and the likely role grains play in maintaining this ratio as clouds evolve from initially diffuse objects to denser cores with associated stellar and planetary formation. Recent spectral line surveys at centimeter and millimeter wavelengths along with selected observations in the submillimeter have now produced an accurate inventory of the gas phase carbon budget in several different types of molecular clouds, though gaps in our knowledge clearly remain. The constraints these observations place on theoretical models of interstellar chemistry can be used to gain insights into why the models fail, and show also which neglected processes must be included in more complete analyses. Looking toward the future, larger molecules are especially difficult to study both experimentally and theoretically in such dense, cold regions, and some new methods are therefore outlined which may ultimately push the detectability of small carbon chains and rings to much heavier species.

Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

PubMed

Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

2015-12-15

Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to emulate one ATP cycle of a molecular motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, we simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concentration-dependent compaction. Finally, we discuss many of limitations in the current approaches and future directions. Especially, more accurate electrostatic treatment and a phospholipid model that matches our CG resolutions are of immediate importance.

Conformational analysis of methylphenidate: comparison of molecular orbital and molecular mechanics methods

NASA Astrophysics Data System (ADS)

Gilbert, Kathleen M.; Skawinski, William J.; Misra, Milind; Paris, Kristina A.; Naik, Neelam H.; Buono, Ronald A.; Deutsch, Howard M.; Venanzi, Carol A.

2004-11-01

Methylphenidate (MP) binds to the cocaine binding site on the dopamine transporter and inhibits reuptake of dopamine, but does not appear to have the same abuse potential as cocaine. This study, part of a comprehensive effort to identify a drug treatment for cocaine abuse, investigates the effect of choice of calculation technique and of solvent model on the conformational potential energy surface (PES) of MP and a rigid methylphenidate (RMP) analogue which exhibits the same dopamine transporter binding affinity as MP. Conformational analysis was carried out by the AM1 and AM1/SM5.4 semiempirical molecular orbital methods, a molecular mechanics method (Tripos force field with the dielectric set equal to that of vacuum or water) and the HF/6-31G* molecular orbital method in vacuum phase. Although all three methods differ somewhat in the local details of the PES, the general trends are the same for neutral and protonated MP. In vacuum phase, protonation has a distinctive effect in decreasing the regions of space available to the local conformational minima. Solvent has little effect on the PES of the neutral molecule and tends to stabilize the protonated species. The random search (RS) conformational analysis technique using the Tripos force field was found to be capable of locating the minima found by the molecular orbital methods using systematic grid search. This suggests that the RS/Tripos force field/vacuum phase protocol is a reasonable choice for locating the local minima of MP. However, the Tripos force field gave significantly larger phenyl ring rotational barriers than the molecular orbital methods for MP and RMP. For both the neutral and protonated cases, all three methods found the phenyl ring rotational barriers for the RMP conformers/invertamers (denoted as cte, tte, and cta) to be: cte, tte> MP > cta. Solvation has negligible effect on the phenyl ring rotational barrier of RMP. The B3LYP/6-31G* density functional method was used to calculate the phenyl ring rotational barrier for neutral MP and gave results very similar to those of the HF/6-31G* method.

Energy transport pathway in proteins: Insights from non-equilibrium molecular dynamics with elastic network model.

PubMed

Wang, Wei Bu; Liang, Yu; Zhang, Jing; Wu, Yi Dong; Du, Jian Jun; Li, Qi Ming; Zhu, Jian Zhuo; Su, Ji Guo

2018-06-22

Intra-molecular energy transport between distant functional sites plays important roles in allosterically regulating the biochemical activity of proteins. How to identify the specific intra-molecular signaling pathway from protein tertiary structure remains a challenging problem. In the present work, a non-equilibrium dynamics method based on the elastic network model (ENM) was proposed to simulate the energy propagation process and identify the specific signaling pathways within proteins. In this method, a given residue was perturbed and the propagation of energy was simulated by non-equilibrium dynamics in the normal modes space of ENM. After that, the simulation results were transformed from the normal modes space to the Cartesian coordinate space to identify the intra-protein energy transduction pathways. The proposed method was applied to myosin and the third PDZ domain (PDZ3) of PSD-95 as case studies. For myosin, two signaling pathways were identified, which mediate the energy transductions form the nucleotide binding site to the 50 kDa cleft and the converter subdomain, respectively. For PDZ3, one specific signaling pathway was identified, through which the intra-protein energy was transduced from ligand binding site to the distant opposite side of the protein. It is also found that comparing with the commonly used cross-correlation analysis method, the proposed method can identify the anisotropic energy transduction pathways more effectively.

Quantum Mechanics/Molecular Mechanics Modeling of Drug Metabolism: Mexiletine N-Hydroxylation by Cytochrome P450 1A2.

PubMed

Lonsdale, Richard; Fort, Rachel M; Rydberg, Patrik; Harvey, Jeremy N; Mulholland, Adrian J

2016-06-20

The mechanism of cytochrome P450(CYP)-catalyzed hydroxylation of primary amines is currently unclear and is relevant to drug metabolism; previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (R)-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM(B3LYP-D)/MM(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site, but this is not a prerequisite for reaction via either mechanism. Several active site residues play a role in the binding of mexiletine in the active site, including Thr124 and Phe226. This work reveals key details of the N-hydroxylation of mexiletine and further demonstrates that mechanistic studies using QM/MM methods are useful for understanding drug metabolism.

Study of lithium cation in water clusters: based on atom-bond electronegativity equalization method fused into molecular mechanics.

PubMed

Li, Xin; Yang, Zhong-Zhi

2005-05-12

We present a potential model for Li(+)-water clusters based on a combination of the atom-bond electronegativity equalization and molecular mechanics (ABEEM/MM) that is to take ABEEM charges of the cation and all atoms, bonds, and lone pairs of water molecules into the intermolecular electrostatic interaction term in molecular mechanics. The model allows point charges on cationic site and seven sites of an ABEEM-7P water molecule to fluctuate responding to the cluster geometry. The water molecules in the first sphere of Li(+) are strongly structured and there is obvious charge transfer between the cation and the water molecules; therefore, the charge constraint on the ionic cluster includes the charged constraint on the Li(+) and the first-shell water molecules and the charge neutrality constraint on each water molecule in the external hydration shells. The newly constructed potential model based on ABEEM/MM is first applied to ionic clusters and reproduces gas-phase state properties of Li(+)(H(2)O)(n) (n = 1-6 and 8) including optimized geometries, ABEEM charges, binding energies, frequencies, and so on, which are in fair agreement with those measured by available experiments and calculated by ab initio methods. Prospects and benefits introduced by this potential model are pointed out.

Quantum mechanical force fields for condensed phase molecular simulations

NASA Astrophysics Data System (ADS)

Giese, Timothy J.; York, Darrin M.

2017-09-01

Molecular simulations are powerful tools for providing atomic-level details into complex chemical and physical processes that occur in the condensed phase. For strongly interacting systems where quantum many-body effects are known to play an important role, density-functional methods are often used to provide the model with the potential energy used to drive dynamics. These methods, however, suffer from two major drawbacks. First, they are often too computationally intensive to practically apply to large systems over long time scales, limiting their scope of application. Second, there remain challenges for these models to obtain the necessary level of accuracy for weak non-bonded interactions to obtain quantitative accuracy for a wide range of condensed phase properties. Quantum mechanical force fields (QMFFs) provide a potential solution to both of these limitations. In this review, we address recent advances in the development of QMFFs for condensed phase simulations. In particular, we examine the development of QMFF models using both approximate and ab initio density-functional models, the treatment of short-ranged non-bonded and long-ranged electrostatic interactions, and stability issues in molecular dynamics calculations. Example calculations are provided for crystalline systems, liquid water, and ionic liquids. We conclude with a perspective for emerging challenges and future research directions.

High-Efficiency Multiscale Modeling of Cell Deformations in Confined Microenvironments in Microcirculation and Microfluidics

NASA Astrophysics Data System (ADS)

Lu, Huijie; Peng, Zhangli

2017-11-01

We developed a high-efficiency multiscale modeling method to predict the stress and deformation of cells during the interactions with their microenvironments in microcirculation and microfluidics, including red blood cells (RBCs) and circulating tumor cells (CTCs). There are more than 1 billion people in the world suffering from RBC diseases. The mechanical properties of RBCs are changed in these diseases due to molecular structure alternations, which is not only important for understanding the disease pathology but also provides an opportunity for diagnostics. On the other hand, the mechanical properties of cancer cells are also altered compared to healthy cells. This can lead to acquired ability to cross the narrow capillary networks and endothelial gaps, which is crucial for metastasis, the leading cause of cancer mortality. Therefore, it is important to predict the deformation and stress of RBCs and CTCs in microcirculations. We develop a high-efficiency multiscale model of cell-fluid interaction. We pass the information from our molecular scale models to the cell scale to study the effect of molecular mutations. Using our high-efficiency boundary element methods of fluids, we will be able to run 3D simulations using a single CPU within several hours, which will enable us to run extensive parametric studies and optimization.

Targeting the cell wall of Mycobacterium tuberculosis: a molecular modeling investigation of the interaction of imipenem and meropenem with L,D-transpeptidase 2.

PubMed

Silva, José Rogério A; Bishai, William R; Govender, Thavendran; Lamichhane, Gyanu; Maguire, Glenn E M; Kruger, Hendrik G; Lameira, Jeronimo; Alves, Cláudio N

2016-01-01

The single crystal X-ray structure of the extracellular portion of the L,D-transpeptidase (ex-LdtMt2 - residues 120-408) enzyme was recently reported. It was observed that imipenem and meropenem inhibit activity of this enzyme, responsible for generating L,D-transpeptide linkages in the peptidoglycan layer of Mycobacterium tuberculosis. Imipenem is more active and isothermal titration calorimetry experiments revealed that meropenem is subjected to an entropy penalty upon binding to the enzyme. Herein, we report a molecular modeling approach to obtain a molecular view of the inhibitor/enzyme interactions. The average binding free energies for nine commercially available inhibitors were calculated using MM/GBSA and Solvation Interaction Energy (SIE) approaches and the calculated energies corresponded well with the available experimentally observed results. The method reproduces the same order of binding energies as experimentally observed for imipenem and meropenem. We have also demonstrated that SIE is a reasonably accurate and cost-effective free energy method, which can be used to predict carbapenem affinities for this enzyme. A theoretical explanation was offered for the experimental entropy penalty observed for meropenem, creating optimism that this computational model can serve as a potential computational model for other researchers in the field.

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.

Vibronic coupling effect on the electron transport through molecules

NASA Astrophysics Data System (ADS)

Tsukada, Masaru; Mitsutake, Kunihiro

2007-03-01

Electron transport through molecular bridges or molecular layers connected to nano-electrodes is determined by the combination of coherent and dissipative processes, controlled by the electron-vibron coupling, transfer integrals between the molecular orbitals, applied electric field and temperature. We propose a novel theoretical approach, which combines ab initio molecular orbital method with analytical many-boson model. As a case study, the long chain model of the thiophene oligomer is solved by a variation approach. Mixed states of moderately extended molecular orbital states mediated and localised by dress of vibron cloud are found as eigen-states. All the excited states accompanied by multiple quanta of vibration can be solved, and the overall carrier transport properties including the conductance, mobility, dissipation spectra are analyzed by solving the master equation with the transition rates estimated by the golden rule. We clarify obtained in a uniform systematic way, how the transport mode changes from a dominantly coherent transport to the dissipative hopping transport.

Development of simulation approach for two-dimensional chiral molecular self-assembly driven by hydrogen bond at the liquid/solid interface

NASA Astrophysics Data System (ADS)

Qin, Yuan; Yao, Man; Hao, Ce; Wan, Lijun; Wang, Yunhe; Chen, Ting; Wang, Dong; Wang, Xudong; Chen, Yonggang

2017-09-01

Two-dimensional (2D) chiral self-assembly system of 5-(benzyloxy)-isophthalic acid derivative/(S)-(+)-2-octanol/highly oriented pyrolytic graphite was studied. A combined density functional theory/molecular mechanics/molecular dynamics (DFT/MM/MD) approach for system of 2D chiral molecular self-assembly driven by hydrogen bond at the liquid/solid interface was thus proposed. Structural models of the chiral assembly were built on the basis of scanning tunneling microscopy (STM) images and simplified for DFT geometry optimization. Merck Molecular Force Field (MMFF) was singled out as the suitable force field by comparing the optimized configurations of MM and DFT. MM and MD simulations for hexagonal unit model which better represented the 2D assemble network were then preformed with MMFF. The adhesion energy, evolution of self-assembly process and characteristic parameters of hydrogen bond were obtained and analyzed. According to the above simulation, the stabilities of the clockwise and counterclockwise enantiomorphous networks were evaluated. The calculational results were supported by STM observations and the feasibility of the simulation method was confirmed by two other systems in the presence of chiral co-absorbers (R)-(-)-2-octanol and achiral co-absorbers 1-octanol. This theoretical simulation method assesses the stability trend of 2D enantiomorphous assemblies with atomic scale and can be applied to the similar hydrogen bond driven 2D chirality of molecular self-assembly system.

Combining Coarse-Grained Protein Models with Replica-Exchange All-Atom Molecular Dynamics

PubMed Central

Wabik, Jacek; Kmiecik, Sebastian; Gront, Dominik; Kouza, Maksim; Koliński, Andrzej

2013-01-01

We describe a combination of all-atom simulations with CABS, a well-established coarse-grained protein modeling tool, into a single multiscale protocol. The simulation method has been tested on the C-terminal beta hairpin of protein G, a model system of protein folding. After reconstructing atomistic details, conformations derived from the CABS simulation were subjected to replica-exchange molecular dynamics simulations with OPLS-AA and AMBER99sb force fields in explicit solvent. Such a combination accelerates system convergence several times in comparison with all-atom simulations starting from the extended chain conformation, demonstrated by the analysis of melting curves, the number of native-like conformations as a function of time and secondary structure propagation. The results strongly suggest that the proposed multiscale method could be an efficient and accurate tool for high-resolution studies of protein folding dynamics in larger systems. PMID:23665897

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/.

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.

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.

Adaptive selection and validation of models of complex systems in the presence of uncertainty

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

Farrell-Maupin, Kathryn; Oden, J. T.

This study describes versions of OPAL, the Occam-Plausibility Algorithm in which the use of Bayesian model plausibilities is replaced with information theoretic methods, such as the Akaike Information Criterion and the Bayes Information Criterion. Applications to complex systems of coarse-grained molecular models approximating atomistic models of polyethylene materials are described. All of these model selection methods take into account uncertainties in the model, the observational data, the model parameters, and the predicted quantities of interest. A comparison of the models chosen by Bayesian model selection criteria and those chosen by the information-theoretic criteria is given.

Adaptive selection and validation of models of complex systems in the presence of uncertainty

DOE PAGES

Farrell-Maupin, Kathryn; Oden, J. T.

2017-08-01

This study describes versions of OPAL, the Occam-Plausibility Algorithm in which the use of Bayesian model plausibilities is replaced with information theoretic methods, such as the Akaike Information Criterion and the Bayes Information Criterion. Applications to complex systems of coarse-grained molecular models approximating atomistic models of polyethylene materials are described. All of these model selection methods take into account uncertainties in the model, the observational data, the model parameters, and the predicted quantities of interest. A comparison of the models chosen by Bayesian model selection criteria and those chosen by the information-theoretic criteria is given.

A combined molecular dynamics/micromechanics/finite element approach for multiscale constitutive modeling of nanocomposites with interface effects

NASA Astrophysics Data System (ADS)

Yang, B. J.; Shin, H.; Lee, H. K.; Kim, H.

2013-12-01

We introduce a multiscale framework based on molecular dynamic (MD) simulation, micromechanics, and finite element method (FEM). A micromechanical model, which considers influences of the interface properties, nanoparticle (NP) size, and microcracks, is developed. Then, we perform MD simulations to characterize the mechanical properties of the nanocomposite system (silica/nylon 6) with varying volume fraction and size of NPs. By comparing the MD with micromechanics results, intrinsic physical properties at interfacial region are derived. Finally, we implement the developed model in the FEM code with the derived interfacial parameters, and predict the mechanical behavior of the nanocomposite at the macroscopic scale.

Challenges in Materials Transformation Modeling for Polyolefins Industry

NASA Astrophysics Data System (ADS)

Lai, Shih-Yaw; Swogger, Kurt W.

2004-06-01

Unlike most published polymer processing and/or forming research, the transformation of polyolefins to fabricated articles often involves non-confined flow or so-called free surface flow (e.g. fiber spinning, blown films, and cast films) in which elongational flow takes place during a fabrication process. Obviously, the characterization and validation of extensional rheological parameters and their use to develop rheological constitutive models are the focus of polyolefins materials transformation research. Unfortunately, there are challenges that remain with limited validation for non-linear, non-isothermal constitutive models for polyolefins. Further complexity arises in the transformation of polyolefins in the elongational flow system as it involves stress-induced crystallization process. The complicated nature of elongational, non-linear rheology and non-isothermal crystallization kinetics make the development of numerical methods very challenging for the polyolefins materials forming modeling. From the product based company standpoint, the challenges of materials transformation research go beyond elongational rheology, crystallization kinetics and its numerical modeling. In order to make models useful for the polyolefin industry, it is critical to develop links between molecular parameters to both equipment and materials forming parameters. The recent advances in the constrained geometry catalysis and materials sciences understanding (INSITE technology and molecular design capability) has made industrial polyolefinic materials forming modeling more viable due to the fact that the molecular structure of the polymer can be well predicted and controlled during the polymerization. In this paper, we will discuss inter-relationship (models) among molecular parameters such as polymer molecular weight (Mw), molecular weight distribution (MWD), long chain branching (LCB), short chain branching (SCB or comonomer types and distribution) and their affects on shear and elongational rheologies, on tie-molecules probabilities, on non-isothermal stress-induced crystallization, on crystalline/amorphous orientation vs. mechanical property relationship, etc. All of the above mentioned inter-relationships (models) are critical to the successful development of a knowledge based industrial model. Dow Polyolefins and Elastomers business is one of the world largest polyolefins resin producers with the most advanced INSITE technology and a "6-Day model" molecular design capability. Dow also offers one of the broadest polyolefinic product ranges and applications to the market.

Numerical solution of boundary-integral equations for molecular electrostatics.

PubMed

Bardhan, Jaydeep P

2009-03-07

Numerous molecular processes, such as ion permeation through channel proteins, are governed by relatively small changes in energetics. As a result, theoretical investigations of these processes require accurate numerical methods. In the present paper, we evaluate the accuracy of two approaches to simulating boundary-integral equations for continuum models of the electrostatics of solvation. The analysis emphasizes boundary-element method simulations of the integral-equation formulation known as the apparent-surface-charge (ASC) method or polarizable-continuum model (PCM). In many numerical implementations of the ASC/PCM model, one forces the integral equation to be satisfied exactly at a set of discrete points on the boundary. We demonstrate in this paper that this approach to discretization, known as point collocation, is significantly less accurate than an alternative approach known as qualocation. Furthermore, the qualocation method offers this improvement in accuracy without increasing simulation time. Numerical examples demonstrate that electrostatic part of the solvation free energy, when calculated using the collocation and qualocation methods, can differ significantly; for a polypeptide, the answers can differ by as much as 10 kcal/mol (approximately 4% of the total electrostatic contribution to solvation). The applicability of the qualocation discretization to other integral-equation formulations is also discussed, and two equivalences between integral-equation methods are derived.

Effect of Molecular Rotation on Charge Transport Phenomena

NASA Astrophysics Data System (ADS)

Garg, O. P.; Lamba, Vijay Kr; Kaushik, D. K.

2015-12-01

The study of electron transport properties of molecular systems could be explained on the basis of the Landauer formalism. Unfortunately, due to the complexity of the experimental setup, most of these measurements have no control over the details of the electrode geometry, rotation of molecules, variation in angle of contacts, effect of fano resonances associated with side groups attached to rigid backbones, which results in a spectrum of IV-characteristics. Theoretical models can therefore help to understand and helps to develop new applications such as molecular sensors, etc. Thus we used simulation methods that generate the required structural ensemble, which is then analyzed with Green’s function methods to characterize the electronic transport properties. In present work we had discussed applications of this approach to understand the conductance in molecular system in the direction of controlling electron transport through molecules and studied the effect of rotation of sandwiched molecule.

Computational assignment of redox states to Coulomb blockade diamonds.

PubMed

Olsen, Stine T; Arcisauskaite, Vaida; Hansen, Thorsten; Kongsted, Jacob; Mikkelsen, Kurt V

2014-09-07

With the advent of molecular transistors, electrochemistry can now be studied at the single-molecule level. Experimentally, the redox chemistry of the molecule manifests itself as features in the observed Coulomb blockade diamonds. We present a simple theoretical method for explicit construction of the Coulomb blockade diamonds of a molecule. A combined quantum mechanical/molecular mechanical method is invoked to calculate redox energies and polarizabilities of the molecules, including the screening effect of the metal leads. This direct approach circumvents the need for explicit modelling of the gate electrode. From the calculated parameters the Coulomb blockade diamonds are constructed using simple theory. We offer a theoretical tool for assignment of Coulomb blockade diamonds to specific redox states in particular, and a study of chemical details in the diamonds in general. With the ongoing experimental developments in molecular transistor experiments, our tool could find use in molecular electronics, electrochemistry, and electrocatalysis.

Comparative Investigation of Normal Modes and Molecular Dynamics of Hepatitis C NS5B Protein

NASA Astrophysics Data System (ADS)

Asafi, M. S.; Yildirim, A.; Tekpinar, M.

2016-04-01

Understanding dynamics of proteins has many practical implications in terms of finding a cure for many protein related diseases. Normal mode analysis and molecular dynamics methods are widely used physics-based computational methods for investigating dynamics of proteins. In this work, we studied dynamics of Hepatitis C NS5B protein with molecular dynamics and normal mode analysis. Principal components obtained from a 100 nanoseconds molecular dynamics simulation show good overlaps with normal modes calculated with a coarse-grained elastic network model. Coarse-grained normal mode analysis takes at least an order of magnitude shorter time. Encouraged by this good overlaps and short computation times, we analyzed further low frequency normal modes of Hepatitis C NS5B. Motion directions and average spatial fluctuations have been analyzed in detail. Finally, biological implications of these motions in drug design efforts against Hepatitis C infections have been elaborated.

Starting from the bench--prevention and control of foodborne and zoonotic diseases.

PubMed

Vongkamjan, Kitiya; Wiedmann, Martin

2015-02-01

Foodborne diseases are estimated to cause around 50 million disease cases and 3000 deaths a year in the US. Worldwide, food and waterborne diseases are estimated to cause more than 2 million deaths per year. Lab-based research is a key component of efforts to prevent and control foodborne diseases. Over the last two decades, molecular characterization of pathogen isolates has emerged as a key component of foodborne and zoonotic disease prevention and control. Characterization methods have evolved from banding pattern-based subtyping methods to sequenced-based approaches, including full genome sequencing. Molecular subtyping methods not only play a key role for characterizing pathogen transmission and detection of disease outbreaks, but also allow for identification of clonal pathogen groups that show distinct transmission characteristics. Importantly, the data generated from molecular characterization of foodborne pathogens also represent critical inputs for epidemiological and modeling studies. Continued and enhanced collaborations between infectious disease related laboratory sciences and epidemiologists, modelers, and other quantitative scientists will be critical to a One-Health approach that delivers societal benefits, including improved surveillance systems and prevention approaches for zoonotic and foodborne pathogens. Copyright © 2014 Elsevier B.V. All rights reserved.

Transition Pathway and Its Free-Energy Profile: A Protocol for Protein Folding Simulations

PubMed Central

Lee, In-Ho; Kim, Seung-Yeon; Lee, Jooyoung

2013-01-01

We propose a protocol that provides a systematic definition of reaction coordinate and related free-energy profile as the function of temperature for the protein-folding simulation. First, using action-derived molecular dynamics (ADMD), we investigate the dynamic folding pathway model of a protein between a fixed extended conformation and a compact conformation. We choose the pathway model to be the reaction coordinate, and the folding and unfolding processes are characterized by the ADMD step index, in contrast to the common a priori reaction coordinate as used in conventional studies. Second, we calculate free-energy profile as the function of temperature, by employing the replica-exchange molecular dynamics (REMD) method. The current method provides efficient exploration of conformational space and proper characterization of protein folding/unfolding dynamics from/to an arbitrary extended conformation. We demonstrate that combination of the two simulation methods, ADMD and REMD, provides understanding on molecular conformational changes in proteins. The protocol is tested on a small protein, penta-peptide of met-enkephalin. For the neuropeptide met-enkephalin system, folded, extended, and intermediate sates are well-defined through the free-energy profile over the reaction coordinate. Results are consistent with those in the literature. PMID:23917881

A general intermolecular force field based on tight-binding quantum chemical calculations

NASA Astrophysics Data System (ADS)

Grimme, Stefan; Bannwarth, Christoph; Caldeweyher, Eike; Pisarek, Jana; Hansen, Andreas

2017-10-01

A black-box type procedure is presented for the generation of a molecule-specific, intermolecular potential energy function. The method uses quantum chemical (QC) information from our recently published extended tight-binding semi-empirical scheme (GFN-xTB) and can treat non-covalently bound complexes and aggregates with almost arbitrary chemical structure. The necessary QC information consists of the equilibrium structure, Mulliken atomic charges, charge centers of localized molecular orbitals, and also of frontier orbitals and orbital energies. The molecular pair potential includes model density dependent Pauli repulsion, penetration, as well as point charge electrostatics, the newly developed D4 dispersion energy model, Drude oscillators for polarization, and a charge-transfer term. Only one element-specific and about 20 global empirical parameters are needed to cover systems with nuclear charges up to radon (Z = 86). The method is tested for standard small molecule interaction energy benchmark sets where it provides accurate intermolecular energies and equilibrium distances. Examples for structures with a few hundred atoms including charged systems demonstrate the versatility of the approach. The method is implemented in a stand-alone computer code which enables rigid-body, global minimum energy searches for molecular aggregation or alignment.

Essential energy space random walk via energy space metadynamics method to accelerate molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Li, Hongzhi; Min, Donghong; Liu, Yusong; Yang, Wei

2007-09-01

To overcome the possible pseudoergodicity problem, molecular dynamic simulation can be accelerated via the realization of an energy space random walk. To achieve this, a biased free energy function (BFEF) needs to be priori obtained. Although the quality of BFEF is essential for sampling efficiency, its generation is usually tedious and nontrivial. In this work, we present an energy space metadynamics algorithm to efficiently and robustly obtain BFEFs. Moreover, in order to deal with the associated diffusion sampling problem caused by the random walk in the total energy space, the idea in the original umbrella sampling method is generalized to be the random walk in the essential energy space, which only includes the energy terms determining the conformation of a region of interest. This essential energy space generalization allows the realization of efficient localized enhanced sampling and also offers the possibility of further sampling efficiency improvement when high frequency energy terms irrelevant to the target events are free of activation. The energy space metadynamics method and its generalization in the essential energy space for the molecular dynamics acceleration are demonstrated in the simulation of a pentanelike system, the blocked alanine dipeptide model, and the leucine model.

Parallel Discrete Molecular Dynamics Simulation With Speculation and In-Order Commitment*†

PubMed Central

Khan, Md. Ashfaquzzaman; Herbordt, Martin C.

2011-01-01

Discrete molecular dynamics simulation (DMD) uses simplified and discretized models enabling simulations to advance by event rather than by timestep. DMD is an instance of discrete event simulation and so is difficult to scale: even in this multi-core era, all reported DMD codes are serial. In this paper we discuss the inherent difficulties of scaling DMD and present our method of parallelizing DMD through event-based decomposition. Our method is microarchitecture inspired: speculative processing of events exposes parallelism, while in-order commitment ensures correctness. We analyze the potential of this parallelization method for shared-memory multiprocessors. Achieving scalability required extensive experimentation with scheduling and synchronization methods to mitigate serialization. The speed-up achieved for a variety of system sizes and complexities is nearly 6× on an 8-core and over 9× on a 12-core processor. We present and verify analytical models that account for the achieved performance as a function of available concurrency and architectural limitations. PMID:21822327

Parallel Discrete Molecular Dynamics Simulation With Speculation and In-Order Commitment.

PubMed

Khan, Md Ashfaquzzaman; Herbordt, Martin C

2011-07-20

Discrete molecular dynamics simulation (DMD) uses simplified and discretized models enabling simulations to advance by event rather than by timestep. DMD is an instance of discrete event simulation and so is difficult to scale: even in this multi-core era, all reported DMD codes are serial. In this paper we discuss the inherent difficulties of scaling DMD and present our method of parallelizing DMD through event-based decomposition. Our method is microarchitecture inspired: speculative processing of events exposes parallelism, while in-order commitment ensures correctness. We analyze the potential of this parallelization method for shared-memory multiprocessors. Achieving scalability required extensive experimentation with scheduling and synchronization methods to mitigate serialization. The speed-up achieved for a variety of system sizes and complexities is nearly 6× on an 8-core and over 9× on a 12-core processor. We present and verify analytical models that account for the achieved performance as a function of available concurrency and architectural limitations.

Toward Measuring Galactic Dense Molecular Gas Properties and 3D Distribution with Hi-GAL

NASA Astrophysics Data System (ADS)

Zetterlund, Erika; Glenn, Jason; Maloney, Phil

2016-01-01

The Herschel Space Observatory's submillimeter dust continuum survey Hi-GAL provides a powerful new dataset for characterizing the structure of the dense interstellar medium of the Milky Way. Hi-GAL observed a 2° wide strip covering the entire 360° of the Galactic plane in broad bands centered at 70, 160, 250, 350, and 500 μm, with angular resolution ranging from 10 to 40 arcseconds. We are adapting a molecular cloud clump-finding algorithm and a distance probability density function distance-determination method developed for the Bolocam Galactic Plane Survey (BGPS) to the Hi-GAL data. Using these methods we expect to generate a database of 105 cloud clumps, derive distance information for roughly half the clumps, and derive precise distances for approximately 20% of them. With five-color photometry and distances, we will measure the cloud clump properties, such as luminosities, physical sizes, and masses, and construct a three-dimensional map of the Milky Way's dense molecular gas distribution.The cloud clump properties and the dense gas distribution will provide critical ground truths for comparison to theoretical models of molecular cloud structure formation and galaxy evolution models that seek to emulate spiral galaxies. For example, such models cannot resolve star formation and use prescriptive recipes, such as converting a fixed fraction of interstellar gas to stars at a specified interstellar medium density threshold. The models should be compared to observed dense molecular gas properties and galactic distributions.As a pilot survey to refine the clump-finding and distance measurement algorithms developed for BGPS, we have identified molecular cloud clumps in six 2° × 2° patches of the Galactic plane, including one in the inner Galaxy along the line of sight through the Molecular Ring and the termination of the Galactic bar and one toward the outer Galaxy. Distances have been derived for the inner Galaxy clumps and compared to Bolocam Galactic Plane Survey results. We present the pilot survey clump catalog, distances, clump properties, and a comparison to BGPS.

MoCha: Molecular Characterization of Unknown Pathways.

PubMed

Lobo, Daniel; Hammelman, Jennifer; Levin, Michael

2016-04-01

Automated methods for the reverse-engineering of complex regulatory networks are paving the way for the inference of mechanistic comprehensive models directly from experimental data. These novel methods can infer not only the relations and parameters of the known molecules defined in their input datasets, but also unknown components and pathways identified as necessary by the automated algorithms. Identifying the molecular nature of these unknown components is a crucial step for making testable predictions and experimentally validating the models, yet no specific and efficient tools exist to aid in this process. To this end, we present here MoCha (Molecular Characterization), a tool optimized for the search of unknown proteins and their pathways from a given set of known interacting proteins. MoCha uses the comprehensive dataset of protein-protein interactions provided by the STRING database, which currently includes more than a billion interactions from over 2,000 organisms. MoCha is highly optimized, performing typical searches within seconds. We demonstrate the use of MoCha with the characterization of unknown components from reverse-engineered models from the literature. MoCha is useful for working on network models by hand or as a downstream step of a model inference engine workflow and represents a valuable and efficient tool for the characterization of unknown pathways using known data from thousands of organisms. MoCha and its source code are freely available online under the GPLv3 license.

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

Point charge representation of multicenter multipole moments in calculation of electrostatic properties

NASA Technical Reports Server (NTRS)

Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.

1993-01-01

Distributed Point Charge Models (PCM) for CO, (H2O)2, and HS-SH molecules have been computed from analytical expressions using multi-center multipole moments. The point charges (set of charges including both atomic and non-atomic positions) exactly reproduce both molecular and segmental multipole moments, thus constituting an accurate representation of the local anisotropy of electrostatic properties. In contrast to other known point charge models, PCM can be used to calculate not only intermolecular, but also intramolecular interactions. Comparison of these results with more accurate calculations demonstrated that PCM can correctly represent both weak and strong (intramolecular) interactions, thus indicating the merit of extending PCM to obtain improved potentials for molecular mechanics and molecular dynamics computational methods.

Estimation of Nanodiamond Surface Charge Density from Zeta Potential and Molecular Dynamics Simulations.

PubMed

Ge, Zhenpeng; Wang, Yi

2017-04-20

Molecular dynamics simulations of nanoparticles (NPs) are increasingly used to study their interactions with various biological macromolecules. Such simulations generally require detailed knowledge of the surface composition of the NP under investigation. Even for some well-characterized nanoparticles, however, this knowledge is not always available. An example is nanodiamond, a nanoscale diamond particle with surface dominated by oxygen-containing functional groups. In this work, we explore using the harmonic restraint method developed by Venable et al., to estimate the surface charge density (σ) of nanodiamonds. Based on the Gouy-Chapman theory, we convert the experimentally determined zeta potential of a nanodiamond to an effective charge density (σ eff ), and then use the latter to estimate σ via molecular dynamics simulations. Through scanning a series of nanodiamond models, we show that the above method provides a straightforward protocol to determine the surface charge density of relatively large (> ∼100 nm) NPs. Overall, our results suggest that despite certain limitation, the above protocol can be readily employed to guide the model construction for MD simulations, which is particularly useful when only limited experimental information on the NP surface composition is available to a modeler.

Small business development for molecular diagnostics.

PubMed

Anagostou, Anthanasia; Liotta, Lance A

2012-01-01

Molecular profiling, which is the application of molecular diagnostics technology to tissue and blood -specimens, is an integral element in the new era of molecular medicine and individualized therapy. Molecular diagnostics is a fertile ground for small business development because it can generate products that meet immediate demands in the health-care sector: (a) Detection of disease risk, or early-stage disease, with a higher specificity and sensitivity compared to previous testing methods, and (b) "Companion diagnostics" for stratifying patients to receive a treatment choice optimized to their individual disease. This chapter reviews the promise and challenges of business development in this field. Guidelines are provided for the creation of a business model and the generation of a marketing plan around a candidate molecular diagnostic product. Steps to commercialization are outlined using existing molecular diagnostics companies as learning examples.

Germline Transgenic Methods for Tracking Cells and Testing Gene Function during Regeneration in the Axolotl

PubMed Central

Khattak, Shahryar; Schuez, Maritta; Richter, Tobias; Knapp, Dunja; Haigo, Saori L.; Sandoval-Guzmán, Tatiana; Hradlikova, Kristyna; Duemmler, Annett; Kerney, Ryan; Tanaka, Elly M.

2013-01-01

The salamander is the only tetrapod that regenerates complex body structures throughout life. Deciphering the underlying molecular processes of regeneration is fundamental for regenerative medicine and developmental biology, but the model organism had limited tools for molecular analysis. We describe a comprehensive set of germline transgenic strains in the laboratory-bred salamander Ambystoma mexicanum (axolotl) that open up the cellular and molecular genetic dissection of regeneration. We demonstrate tissue-dependent control of gene expression in nerve, Schwann cells, oligodendrocytes, muscle, epidermis, and cartilage. Furthermore, we demonstrate the use of tamoxifen-induced Cre/loxP-mediated recombination to indelibly mark different cell types. Finally, we inducibly overexpress the cell-cycle inhibitor p16INK4a, which negatively regulates spinal cord regeneration. These tissue-specific germline axolotl lines and tightly inducible Cre drivers and LoxP reporter lines render this classical regeneration model molecularly accessible. PMID:24052945

Transitioning NWChem to the Next Generation of Manycore Machines

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

Bylaska, Eric J.; Apra, Edoardo; Kowalski, Karol

The NorthWest Chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers[6, 28, 49]. It contains an umbrella of modules that today includes Self Consistent Field (SCF), second order Mller-Plesset perturbation theory (MP2), Coupled Cluster, multi-conguration selfconsistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics, Car-Parrinello molecular dynamics, classical molecular dynamics (MD), QM/MM,more » AIMD/MM, GIAO NMR, COSMO, COSMO-SMD, and RISM solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities[ 22]. Moreover new capabilities continue to be added with each new release.« less

Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level

NASA Astrophysics Data System (ADS)

Thakar, Juilee; Albert, Réka

The following sections are included: * Introduction * Boolean Network Concepts and History * Extensions of the Classical Boolean Framework * Boolean Inference Methods and Examples in Biology * Dynamic Boolean Models: Examples in Plant Biology, Developmental Biology and Immunology * Conclusions * References

Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning

PubMed Central

Matsunaga, Yasuhiro

2018-01-01

Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide time-series data, such as donor-acceptor distances, whereas the latter give atomistic information, although this information is often biased by model parameters. Here, we devise a machine-learning method to combine the complementary information from the two approaches and construct a consistent model of conformational dynamics. It is applied to the folding dynamics of the formin-binding protein WW domain. MD simulations over 400 μs led to an initial Markov state model (MSM), which was then "refined" using single-molecule Förster resonance energy transfer (FRET) data through hidden Markov modeling. The refined or data-assimilated MSM reproduces the FRET data and features hairpin one in the transition-state ensemble, consistent with mutation experiments. The folding pathway in the data-assimilated MSM suggests interplay between hydrophobic contacts and turn formation. Our method provides a general framework for investigating conformational transitions in other proteins. PMID:29723137

Linking time-series of single-molecule experiments with molecular dynamics simulations by machine learning.

PubMed

Matsunaga, Yasuhiro; Sugita, Yuji

2018-05-03

Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide time-series data, such as donor-acceptor distances, whereas the latter give atomistic information, although this information is often biased by model parameters. Here, we devise a machine-learning method to combine the complementary information from the two approaches and construct a consistent model of conformational dynamics. It is applied to the folding dynamics of the formin-binding protein WW domain. MD simulations over 400 μs led to an initial Markov state model (MSM), which was then "refined" using single-molecule Förster resonance energy transfer (FRET) data through hidden Markov modeling. The refined or data-assimilated MSM reproduces the FRET data and features hairpin one in the transition-state ensemble, consistent with mutation experiments. The folding pathway in the data-assimilated MSM suggests interplay between hydrophobic contacts and turn formation. Our method provides a general framework for investigating conformational transitions in other proteins. © 2018, Matsunaga et al.

Electrospray-assisted encapsulation of caffeine in alginate microhydrogels.

PubMed

Nikoo, Alireza Mehregan; Kadkhodaee, Rassoul; Ghorani, Behrouz; Razzaq, Hussam; Tucker, Nick

2018-05-02

One of the major challenges with microencapsulation and delivery of low molecular weight bioactive compounds is their diffusional loss during storage and process conditions as well as under gastric conditions. In an attempt to slow down the release rate of core material, electrospray fabricated calcium alginate microhydrogels were coated with low molecular weight and high molecular weight chitosans. Caffeine as a hydrophilic model compound was used due to its several advantages on human behavior especially increasing consciousness. Mathematical modeling of the caffeine release by fitting the data with Korsmeyer-Peppas model showed that Fick's diffusion law could be the prevalent mechanism of the release. Electrostatic interaction between alginate and chitosan (particularly in the presence of 1% low molecular weight chitosan) provided an effective barrier against caffeine release and significantly reduced swelling of particles compared to control samples. The results of this study demonstrated that calcium alginate microhydrogels coated by chitosan could be used for encapsulation of low molecular compounds. However, more complementary research must be done in this field. In addition, electrospray, by producing monodisperse particles, would be as an alternative method for fabrication of microparticles based on natural polymers. Copyright © 2018. Published by Elsevier B.V.

Search for Length Dependent Stable Structures of Polyglutamaine Proteins with Replica Exchange Molecular Dynamic

NASA Astrophysics Data System (ADS)

Kluber, Alexander; Hayre, Robert; Cox, Daniel

2012-02-01

Motivated by the need to find beta-structure aggregation nuclei for the polyQ diseases such as Huntington's, we have undertaken a search for length dependent structure in model polyglutamine proteins. We use the Onufriev-Bashford-Case (OBC) generalized Born implicit solvent GPU based AMBER11 molecular dynamics with the parm96 force field coupled with a replica exchange method to characterize monomeric strands of polyglutamine as a function of chain length and temperature. This force field and solvation method has been shown among other methods to accurately reproduce folded metastability in certain small peptides, and to yield accurately de novo folded structures in a millisecond time-scale protein. Using GPU molecular dynamics we can sample out into the microsecond range. Additionally, explicit solvent runs will be used to verify results from the implicit solvent runs. We will assess order using measures of secondary structure and hydrogen bond content.

Automated Protein Biomarker Analysis: on-line extraction of clinical samples by Molecularly Imprinted Polymers

NASA Astrophysics Data System (ADS)

Rossetti, Cecilia; Świtnicka-Plak, Magdalena A.; Grønhaug Halvorsen, Trine; Cormack, Peter A. G.; Sellergren, Börje; Reubsaet, Léon

2017-03-01

Robust biomarker quantification is essential for the accurate diagnosis of diseases and is of great value in cancer management. In this paper, an innovative diagnostic platform is presented which provides automated molecularly imprinted solid-phase extraction (MISPE) followed by liquid chromatography-mass spectrometry (LC-MS) for biomarker determination using ProGastrin Releasing Peptide (ProGRP), a highly sensitive biomarker for Small Cell Lung Cancer, as a model. Molecularly imprinted polymer microspheres were synthesized by precipitation polymerization and analytical optimization of the most promising material led to the development of an automated quantification method for ProGRP. The method enabled analysis of patient serum samples with elevated ProGRP levels. Particularly low sample volumes were permitted using the automated extraction within a method which was time-efficient, thereby demonstrating the potential of such a strategy in a clinical setting.

Molecular dispersion spectroscopy for chemical sensing using chirped mid-infrared quantum cascade laser.

PubMed

Wysocki, Gerard; Weidmann, Damien

2010-12-06

A spectroscopic method of molecular detection based on dispersion measurements using a frequency-chirped laser source is presented. An infrared quantum cascade laser emitting around 1912 cm(-1) is used as a tunable spectroscopic source to measure dispersion that occurs in the vicinity of molecular ro-vibrational transitions. The sample under study is a mixture of nitric oxide in dry nitrogen. Two experimental configurations based on a coherent detection scheme are investigated and discussed. The theoretical models, which describe the observed spectral signals, are developed and verified experimentally. The method is particularly relevant to optical sensing based on mid-infrared quantum cascade lasers as the high chirp rates available with those sources can significantly enhance the magnitude of the measured dispersion signals. The method relies on heterodyne beatnote frequency measurements and shows high immunity to variations in the optical power received by the photodetector.

Density-based cluster algorithms for the identification of core sets

NASA Astrophysics Data System (ADS)

Lemke, Oliver; Keller, Bettina G.

2016-10-01

The core-set approach is a discretization method for Markov state models of complex molecular dynamics. Core sets are disjoint metastable regions in the conformational space, which need to be known prior to the construction of the core-set model. We propose to use density-based cluster algorithms to identify the cores. We compare three different density-based cluster algorithms: the CNN, the DBSCAN, and the Jarvis-Patrick algorithm. While the core-set models based on the CNN and DBSCAN clustering are well-converged, constructing core-set models based on the Jarvis-Patrick clustering cannot be recommended. In a well-converged core-set model, the number of core sets is up to an order of magnitude smaller than the number of states in a conventional Markov state model with comparable approximation error. Moreover, using the density-based clustering one can extend the core-set method to systems which are not strongly metastable. This is important for the practical application of the core-set method because most biologically interesting systems are only marginally metastable. The key point is to perform a hierarchical density-based clustering while monitoring the structure of the metric matrix which appears in the core-set method. We test this approach on a molecular-dynamics simulation of a highly flexible 14-residue peptide. The resulting core-set models have a high spatial resolution and can distinguish between conformationally similar yet chemically different structures, such as register-shifted hairpin structures.

A two-dimensional spectrum analysis for sedimentation velocity experiments of mixtures with heterogeneity in molecular weight and shape.

PubMed

Brookes, Emre; Cao, Weiming; Demeler, Borries

2010-02-01

We report a model-independent analysis approach for fitting sedimentation velocity data which permits simultaneous determination of shape and molecular weight distributions for mono- and polydisperse solutions of macromolecules. Our approach allows for heterogeneity in the frictional domain, providing a more faithful description of the experimental data for cases where frictional ratios are not identical for all components. Because of increased accuracy in the frictional properties of each component, our method also provides more reliable molecular weight distributions in the general case. The method is based on a fine grained two-dimensional grid search over s and f/f (0), where the grid is a linear combination of whole boundary models represented by finite element solutions of the Lamm equation with sedimentation and diffusion parameters corresponding to the grid points. A Monte Carlo approach is used to characterize confidence limits for the determined solutes. Computational algorithms addressing the very large memory needs for a fine grained search are discussed. The method is suitable for globally fitting multi-speed experiments, and constraints based on prior knowledge about the experimental system can be imposed. Time- and radially invariant noise can be eliminated. Serial and parallel implementations of the method are presented. We demonstrate with simulated and experimental data of known composition that our method provides superior accuracy and lower variance fits to experimental data compared to other methods in use today, and show that it can be used to identify modes of aggregation and slow polymerization.

Application of the Monte Carlo method for building up models for octanol-water partition coefficient of platinum complexes

NASA Astrophysics Data System (ADS)

Toropov, Andrey A.; Toropova, Alla P.

2018-06-01

Predictive model of logP for Pt(II) and Pt(IV) complexes built up with the Monte Carlo method using the CORAL software has been validated with six different splits into the training and validation sets. The improving of the predictive potential of models for six different splits has been obtained using so-called index of ideality of correlation. The suggested models give possibility to extract molecular features, which cause the increase or vice versa decrease of the logP.

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

Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation

PubMed Central

Paluch, Andrew S.; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L.

2015-01-01

We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes. PMID:25637996

Structure and Stability of Molecular Crystals with Many-Body Dispersion-Inclusive Density Functional Tight Binding.

PubMed

Mortazavi, Majid; Brandenburg, Jan Gerit; Maurer, Reinhard J; Tkatchenko, Alexandre

2018-01-18

Accurate prediction of structure and stability of molecular crystals is crucial in materials science and requires reliable modeling of long-range dispersion interactions. Semiempirical electronic structure methods are computationally more efficient than their ab initio counterparts, allowing structure sampling with significant speedups. We combine the Tkatchenko-Scheffler van der Waals method (TS) and the many-body dispersion method (MBD) with third-order density functional tight-binding (DFTB3) via a charge population-based method. We find an overall good performance for the X23 benchmark database of molecular crystals, despite an underestimation of crystal volume that can be traced to the DFTB parametrization. We achieve accurate lattice energy predictions with DFT+MBD energetics on top of vdW-inclusive DFTB3 structures, resulting in a speedup of up to 3000 times compared with a full DFT treatment. This suggests that vdW-inclusive DFTB3 can serve as a viable structural prescreening tool in crystal structure prediction.

Towards Efficient and Accurate Description of Many-Electron Problems: Developments of Static and Time-Dependent Electronic Structure Methods

NASA Astrophysics Data System (ADS)

Ding, Feizhi

Understanding electronic behavior in molecular and nano-scale systems is fundamental to the development and design of novel technologies and materials for application in a variety of scientific contexts from fundamental research to energy conversion. This dissertation aims to provide insights into this goal by developing novel methods and applications of first-principle electronic structure theory. Specifically, we will present new methods and applications of excited state multi-electron dynamics based on the real-time (RT) time-dependent Hartree-Fock (TDHF) and time-dependent density functional theory (TDDFT) formalism, and new development of the multi-configuration self-consist field theory (MCSCF) for modeling ground-state electronic structure. The RT-TDHF/TDDFT based developments and applications can be categorized into three broad and coherently integrated research areas: (1) modeling of the interaction between moleculars and external electromagnetic perturbations. In this part we will first prove both analytically and numerically the gauge invariance of the TDHF/TDDFT formalisms, then we will present a novel, efficient method for calculating molecular nonlinear optical properties, and last we will study quantum coherent plasmon in metal namowires using RT-TDDFT; (2) modeling of excited-state charge transfer in molecules. In this part, we will investigate the mechanisms of bridge-mediated electron transfer, and then we will introduce a newly developed non-equilibrium quantum/continuum embedding method for studying charge transfer dynamics in solution; (3) developments of first-principles spin-dependent many-electron dynamics. In this part, we will present an ab initio non-relativistic spin dynamics method based on the two-component generalized Hartree-Fock approach, and then we will generalized it to the two-component TDDFT framework and combine it with the Ehrenfest molecular dynamics approach for modeling the interaction between electron spins and nuclear motion. All these developments and applications will open up new computational and theoretical tools to be applied to the development and understanding of chemical reactions, nonlinear optics, electromagnetism, and spintronics. Lastly, we present a new algorithm for large-scale MCSCF calculations that can utilize massively parallel machines while still maintaining optimal performance for each single processor. This will great improve the efficiency in the MCSCF calculations for studying chemical dissociation and high-accuracy quantum-mechanical simulations.

Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM)

NASA Astrophysics Data System (ADS)

Sinitskiy, Anton V.; Voth, Gregory A.

2018-01-01

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.

Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM).

PubMed

Sinitskiy, Anton V; Voth, Gregory A

2018-01-07

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.

Molecular simulation of the thermophysical properties and phase behaviour of impure CO2 relevant to CCS.

PubMed

Cresswell, Alexander J; Wheatley, Richard J; Wilkinson, Richard D; Graham, Richard S

2016-10-20

Impurities from the CCS chain can greatly influence the physical properties of CO 2 . This has important design, safety and cost implications for the compression, transport and storage of CO 2 . There is an urgent need to understand and predict the properties of impure CO 2 to assist with CCS implementation. However, CCS presents demanding modelling requirements. A suitable model must both accurately and robustly predict CO 2 phase behaviour over a wide range of temperatures and pressures, and maintain that predictive power for CO 2 mixtures with numerous, mutually interacting chemical species. A promising technique to address this task is molecular simulation. It offers a molecular approach, with foundations in firmly established physical principles, along with the potential to predict the wide range of physical properties required for CCS. The quality of predictions from molecular simulation depends on accurate force-fields to describe the interactions between CO 2 and other molecules. Unfortunately, there is currently no universally applicable method to obtain force-fields suitable for molecular simulation. In this paper we present two methods of obtaining force-fields: the first being semi-empirical and the second using ab initio quantum-chemical calculations. In the first approach we optimise the impurity force-field against measurements of the phase and pressure-volume behaviour of CO 2 binary mixtures with N 2 , O 2 , Ar and H 2 . A gradient-free optimiser allows us to use the simulation itself as the underlying model. This leads to accurate and robust predictions under conditions relevant to CCS. In the second approach we use quantum-chemical calculations to produce ab initio evaluations of the interactions between CO 2 and relevant impurities, taking N 2 as an exemplar. We use a modest number of these calculations to train a machine-learning algorithm, known as a Gaussian process, to describe these data. The resulting model is then able to accurately predict a much broader set of ab initio force-field calculations at comparatively low numerical cost. Although our method is not yet ready to be implemented in a molecular simulation, we outline the necessary steps here. Such simulations have the potential to deliver first-principles simulation of the thermodynamic properties of impure CO 2 , without fitting to experimental data.

On simulation of local fluxes in molecular junctions

NASA Astrophysics Data System (ADS)

Cabra, Gabriel; Jensen, Anders; Galperin, Michael

2018-05-01

We present a pedagogical review of the current density simulation in molecular junction models indicating its advantages and deficiencies in analysis of local junction transport characteristics. In particular, we argue that current density is a universal tool which provides more information than traditionally simulated bond currents, especially when discussing inelastic processes. However, current density simulations are sensitive to the choice of basis and electronic structure method. We note that while discussing the local current conservation in junctions, one has to account for the source term caused by the open character of the system and intra-molecular interactions. Our considerations are illustrated with numerical simulations of a benzenedithiol molecular junction.

Effect of long-range correlation on the metal-insulator transition in a disordered molecular crystal

NASA Astrophysics Data System (ADS)

Unge, Mikael; Stafström, Sven

2006-12-01

Localization lengths of the electronic states in a disordered two-dimensional system, resembling highly anisotropic molecular crystals such as pentacene, have been calculated numerically using the transfer matrix method. The disorder is based on a model with small random fluctuations of induced molecular dipole moments which give rise to long-range correlated disorder in the on-site energies as well as a coupling between the on-site energies and the intermolecular interactions. Our calculations show that molecular crystals such as pentacene can exhibit states with very long localization lengths with a possibility to reach a truly metallic state.

Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization.

PubMed

Turk, Samo; Merget, Benjamin; Rippmann, Friedrich; Fulle, Simone

2017-12-26

Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with machine learning (ML) approaches to extrapolate to novel compounds. The here introduced MMP/ML method combines a fragment-based MMP implementation with different machine learning methods to obtain automated SAR decomposition and prediction. To test the prediction capabilities and model transferability, two different compound optimization scenarios were designed: (1) "new fragments" which occurs when exploring new fragments for a defined compound series and (2) "new static core and transformations" which resembles for instance the identification of a new compound series. Very good results were achieved by all employed machine learning methods especially for the new fragments case, but overall deep neural network models performed best, allowing reliable predictions also for the new static core and transformations scenario, where comprehensive SAR knowledge of the compound series is missing. Furthermore, we show that models trained on all available data have a higher generalizability compared to models trained on focused series and can extend beyond chemical space covered in the training data. Thus, coupling MMP with deep neural networks provides a promising approach to make high quality predictions on various data sets and in different compound optimization scenarios.

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

PubMed Central

Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

2016-01-01

A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

Mathematical analysis of compressive/tensile molecular and nuclear structures

NASA Astrophysics Data System (ADS)

Wang, Dayu

Mathematical analysis in chemistry is a fascinating and critical tool to explain experimental observations. In this dissertation, mathematical methods to present chemical bonding and other structures for many-particle systems are discussed at different levels (molecular, atomic, and nuclear). First, the tetrahedral geometry of single, double, or triple carbon-carbon bonds gives an unsatisfying demonstration of bond lengths, compared to experimental trends. To correct this, Platonic solids and Archimedean solids were evaluated as atoms in covalent carbon or nitrogen bond systems in order to find the best solids for geometric fitting. Pentagonal solids, e.g. the dodecahedron and icosidodecahedron, give the best fit with experimental bond lengths; an ideal pyramidal solid which models covalent bonds was also generated. Second, the macroscopic compression/tension architectural approach was applied to forces at the molecular level, considering atomic interactions as compressive (repulsive) and tensile (attractive) forces. Two particle interactions were considered, followed by a model of the dihydrogen molecule (H2; two protons and two electrons). Dihydrogen was evaluated as two different types of compression/tension structures: a coaxial spring model and a ring model. Using similar methods, covalent diatomic molecules (made up of C, N, O, or F) were evaluated. Finally, the compression/tension model was extended to the nuclear level, based on the observation that nuclei with certain numbers of protons/neutrons (magic numbers) have extra stability compared to other nucleon ratios. A hollow spherical model was developed that combines elements of the classic nuclear shell model and liquid drop model. Nuclear structure and the trend of the "island of stability" for the current and extended periodic table were studied.

Importance and pitfalls of molecular analysis to parasite epidemiology.

PubMed

Constantine, Clare C

2003-08-01

Molecular tools are increasingly being used to address questions about parasite epidemiology. Parasites represent a diverse group and they might not fit traditional population genetic models. Testing hypotheses depends equally on correct sampling, appropriate tool and/or marker choice, appropriate analysis and careful interpretation. All methods of analysis make assumptions which, if violated, make the results invalid. Some guidelines to avoid common pitfalls are offered here.

Design and Implementation of a Self-Directed Stereochemistry Lesson Using Embedded Virtual Three-Dimensional Images in a Portable Document Format

ERIC Educational Resources Information Center

Cody, Jeremy A.; Craig, Paul A.; Loudermilk, Adam D.; Yacci, Paul M.; Frisco, Sarah L.; Milillo, Jennifer R.

2012-01-01

A novel stereochemistry lesson was prepared that incorporated both handheld molecular models and embedded virtual three-dimensional (3D) images. The images are fully interactive and eye-catching for the students; methods for preparing 3D molecular images in Adobe Acrobat are included. The lesson was designed and implemented to showcase the 3D…

Molecular opacities for exoplanets.

PubMed

Bernath, Peter F

2014-04-28

Spectroscopic observations of exoplanets are now possible by transit methods and direct emission. Spectroscopic requirements for exoplanets are reviewed based on existing measurements and model predictions for hot Jupiters and super-Earths. Molecular opacities needed to simulate astronomical observations can be obtained from laboratory measurements, ab initio calculations or a combination of the two approaches. This discussion article focuses mainly on laboratory measurements of hot molecules as needed for exoplanet spectroscopy.

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

The origin and diversification of eukaryotes: problems with molecular phylogenetics and molecular clock estimation

PubMed Central

Roger, Andrew J; Hug, Laura A

2006-01-01

Determining the relationships among and divergence times for the major eukaryotic lineages remains one of the most important and controversial outstanding problems in evolutionary biology. The sequencing and phylogenetic analyses of ribosomal RNA (rRNA) genes led to the first nearly comprehensive phylogenies of eukaryotes in the late 1980s, and supported a view where cellular complexity was acquired during the divergence of extant unicellular eukaryote lineages. More recently, however, refinements in analytical methods coupled with the availability of many additional genes for phylogenetic analysis showed that much of the deep structure of early rRNA trees was artefactual. Recent phylogenetic analyses of a multiple genes and the discovery of important molecular and ultrastructural phylogenetic characters have resolved eukaryotic diversity into six major hypothetical groups. Yet relationships among these groups remain poorly understood because of saturation of sequence changes on the billion-year time-scale, possible rapid radiations of major lineages, phylogenetic artefacts and endosymbiotic or lateral gene transfer among eukaryotes. Estimating the divergence dates between the major eukaryote lineages using molecular analyses is even more difficult than phylogenetic estimation. Error in such analyses comes from a myriad of sources including: (i) calibration fossil dates, (ii) the assumed phylogenetic tree, (iii) the nucleotide or amino acid substitution model, (iv) substitution number (branch length) estimates, (v) the model of how rates of evolution change over the tree, (vi) error inherent in the time estimates for a given model and (vii) how multiple gene data are treated. By reanalysing datasets from recently published molecular clock studies, we show that when errors from these various sources are properly accounted for, the confidence intervals on inferred dates can be very large. Furthermore, estimated dates of divergence vary hugely depending on the methods used and their assumptions. Accurate dating of divergence times among the major eukaryote lineages will require a robust tree of eukaryotes, a much richer Proterozoic fossil record of microbial eukaryotes assignable to extant groups for calibration, more sophisticated relaxed molecular clock methods and many more genes sampled from the full diversity of microbial eukaryotes. PMID:16754613

Void effect on mechanical properties of copper nanosheets under biaxial tension by molecular dynamics method

NASA Astrophysics Data System (ADS)

Yang, Zailin; Yang, Qinyou; Zhang, Guowei; Yang, Yong

2018-03-01

The relationship between void size/location and mechanical behavior under biaxial loading of copper nanosheets containing voids are investigated by molecular dynamics method. The void location and the void radius on the model are discussed in the paper. The main reason of break is discovered by the congruent relationship between the shear stress and its dislocations. Dislocations are nucleated at the corner of system and approached to the center of void with increased deformation. Here, a higher stress is required to fail the voided sheets when smaller voids are utilized. The void radius influences the time of destruction. The larger the void radius is, the lower the shear stress and the earlier the model breaks. The void location impacts the dislocation distribution.

3DSDSCAR--a three dimensional structural database for sialic acid-containing carbohydrates through molecular dynamics simulation.

PubMed

Veluraja, Kasinadar; Selvin, Jeyasigamani F A; Venkateshwari, Selvakumar; Priyadarzini, Thanu R K

2010-09-23

The inherent flexibility and lack of strong intramolecular interactions of oligosaccharides demand the use of theoretical methods for their structural elucidation. In spite of the developments of theoretical methods, not much research on glycoinformatics is done so far when compared to bioinformatics research on proteins and nucleic acids. We have developed three dimensional structural database for a sialic acid-containing carbohydrates (3DSDSCAR). This is an open-access database that provides 3D structural models of a given sialic acid-containing carbohydrate. At present, 3DSDSCAR contains 60 conformational models, belonging to 14 different sialic acid-containing carbohydrates, deduced through 10 ns molecular dynamics (MD) simulations. The database is available at the URL: http://www.3dsdscar.org. Copyright 2010 Elsevier Ltd. All rights reserved.

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.

Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics.

PubMed

Marquez-Lago, Tatiana T; Burrage, Kevin

2007-09-14

In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial tau-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity.

A new predictive model for the bioconcentration factors of polychlorinated biphenyls (PCBs) based on the molecular electronegativity distance vector (MEDV).

PubMed

Qin, Li-Tang; Liu, Shu-Shen; Liu, Hai-Ling; Ge, Hui-Lin

2008-02-01

Polychlorinated biphenyls (PCBs) are some of the most prevalent pollutants in the total environment and receive more and more concerns as a group of ubiquitous potential persistent organic pollutants. Using the variable selection and modeling based on prediction (VSMP), the molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was employed to develop a linear model (MI) between the bioconcentration factors (BCF) and two MEDV descriptors of 58 PCBs. The MI model showed a good estimation ability with a correlation coefficient (r) of 0.9605 and a high stability with a leave-one-out cross-validation correlation coefficient (q) of 0.9564. The MEDV-base model (MI) is easier to use than the splinoid poset method reported by Ivanciuc et al. [Ivanciuc, T., Ivanciuc, O., Klein, D.J., 2006. Modeling the bioconcentration factors and bioaccumulation factors of polychlorinated biphenyls with posetic quatitative super-structure/activity relationships (QSSAR). Mol. Divers. 10, 133-145] and gives a better statistics than molecular connectivity index (MCI)-base model developed by Hu et al. [Hu, H.Y., Xu, F.L., Li, B.G., Cao, J., Dawson, R., Tao, S., 2005. Prediction of the bioconcentration factor of PCBs in fish using the molecular connectivity index and fragment constant models. Water Environ. Res. 77, 87-97]. Main structural factors influencing the BCF of PCBs are the substructures expressed by two atomic groups >C= and -CH=. 58 PCBs were divided into an "odd set" and "even set" in order to ensure the predicted potential of the MI for the external samples. It was shown that three models, MI, MO for "odd set", and ME for "even set", can be used to predict the BCF of remaining 152 PCBs in which the experimental BCFs are not available.

Clinical identification of bacteria in human chronic wound infections: culturing vs. 16S ribosomal DNA sequencing

PubMed Central

2012-01-01

Background Chronic wounds affect millions of people and cost billions of dollars in the United States each year. These wounds harbor polymicrobial biofilm communities, which can be difficult to elucidate using culturing methods. Clinical molecular microbiological methods are increasingly being employed to investigate the microbiota of chronic infections, including wounds, as part of standard patient care. However, molecular testing is more sensitive than culturing, which results in markedly different results being reported to clinicians. This study compares the results of aerobic culturing and molecular testing (culture-free 16S ribosomal DNA sequencing), and it examines the relative abundance score that is generated by the molecular test and the usefulness of the relative abundance score in predicting the likelihood that the same organism would be detected by culture. Methods Parallel samples from 51 chronic wounds were studied using aerobic culturing and 16S DNA sequencing for the identification of bacteria. Results One hundred forty-five (145) unique genera were identified using molecular methods, and 68 of these genera were aerotolerant. Fourteen (14) unique genera were identified using aerobic culture methods. One-third (31/92) of the cultures were determined to be < 1% of the relative abundance of the wound microbiota using molecular testing. At the genus level, molecular testing identified 85% (78/92) of the bacteria that were identified by culture. Conversely, culturing detected 15.7% (78/497) of the aerotolerant bacteria and detected 54.9% of the collective aerotolerant relative abundance of the samples. Aerotolerant bacterial genera (and individual species including Staphylococcus aureus, Pseudomonas aeruginosa, and Enterococcus faecalis) with higher relative abundance scores were more likely to be detected by culture as demonstrated with regression modeling. Conclusion Discordance between molecular and culture testing is often observed. However, culture-free 16S ribosomal DNA sequencing and its relative abundance score can provide clinicians with insight into which bacteria are most abundant in a sample and which are most likely to be detected by culture. PMID:23176603

A model of lipid-free Apolipoprotein A-I revealed by iterative molecular dynamics simulation

DOE PAGES

Zhang, Xing; Lei, Dongsheng; Zhang, Lei; ...

2015-03-20

Apolipoprotein A-I (apo A-I), the major protein component of high-density lipoprotein, has been proven inversely correlated to cardiovascular risk in past decades. The lipid-free state of apo A-I is the initial stage which binds to lipids forming high-density lipoprotein. Molecular models of lipid-free apo A-I have been reported by methods like X-ray crystallography and chemical cross-linking/mass spectrometry (CCL/MS). Through structural analysis we found that those current models had limited consistency with other experimental results, such as those from hydrogen exchange with mass spectrometry. Through molecular dynamics simulations, we also found those models could not reach a stable equilibrium state. Therefore,more » by integrating various experimental results, we proposed a new structural model for lipidfree apo A-I, which contains a bundled four-helix N-terminal domain (1–192) that forms a variable hydrophobic groove and a mobile short hairpin C-terminal domain (193–243). This model exhibits an equilibrium state through molecular dynamics simulation and is consistent with most of the experimental results known from CCL/MS on lysine pairs, fluorescence resonance energy transfer and hydrogen exchange. This solution-state lipid-free apo A-I model may elucidate the possible conformational transitions of apo A-I binding with lipids in high-density lipoprotein formation.« less

Variational Identification of Markovian Transition States

NASA Astrophysics Data System (ADS)

Martini, Linda; Kells, Adam; Covino, Roberto; Hummer, Gerhard; Buchete, Nicolae-Viorel; Rosta, Edina

2017-07-01

We present a method that enables the identification and analysis of conformational Markovian transition states from atomistic or coarse-grained molecular dynamics (MD) trajectories. Our algorithm is presented by using both analytical models and examples from MD simulations of the benchmark system helix-forming peptide Ala5 , and of larger, biomedically important systems: the 15-lipoxygenase-2 enzyme (15-LOX-2), the epidermal growth factor receptor (EGFR) protein, and the Mga2 fungal transcription factor. The analysis of 15-LOX-2 uses data generated exclusively from biased umbrella sampling simulations carried out at the hybrid ab initio density functional theory (DFT) quantum mechanics/molecular mechanics (QM/MM) level of theory. In all cases, our method automatically identifies the corresponding transition states and metastable conformations in a variationally optimal way, with the input of a set of relevant coordinates, by accurately reproducing the intrinsic slowest relaxation rate of each system. Our approach offers a general yet easy-to-implement analysis method that provides unique insight into the molecular mechanism and the rare but crucial (i.e., rate-limiting) transition states occurring along conformational transition paths in complex dynamical systems such as molecular trajectories.

The Harvard Clean Energy Project: High-throughput screening of organic photovoltaic materials using cheminformatics, machine learning, and pattern recognition

NASA Astrophysics Data System (ADS)

Olivares-Amaya, Roberto; Hachmann, Johannes; Amador-Bedolla, Carlos; Daly, Aidan; Jinich, Adrian; Atahan-Evrenk, Sule; Boixo, Sergio; Aspuru-Guzik, Alán

2012-02-01

Organic photovoltaic devices have emerged as competitors to silicon-based solar cells, currently reaching efficiencies of over 9% and offering desirable properties for manufacturing and installation. We study conjugated donor polymers for high-efficiency bulk-heterojunction photovoltaic devices with a molecular library motivated by experimental feasibility. We use quantum mechanics and a distributed computing approach to explore this vast molecular space. We will detail the screening approach starting from the generation of the molecular library, which can be easily extended to other kinds of molecular systems. We will describe the screening method for these materials which ranges from descriptor models, ubiquitous in the drug discovery community, to eventually reaching first principles quantum chemistry methods. We will present results on the statistical analysis, based principally on machine learning, specifically partial least squares and Gaussian processes. Alongside, clustering methods and the use of the hypergeometric distribution reveal moieties important for the donor materials and allow us to quantify structure-property relationships. These efforts enable us to accelerate materials discovery in organic photovoltaics through our collaboration with experimental groups.

Molecular Population Genetics

PubMed Central

Casillas, Sònia; Barbadilla, Antonio

2017-01-01

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. PMID:28270526

Molecular Population Genetics.

PubMed

Casillas, Sònia; Barbadilla, Antonio

2017-03-01

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. Copyright © 2017 Casillas and Barbadilla.

Low-Density Nozzle Flow by the Direct Simulation Monte Carlo and Continuum Methods

NASA Technical Reports Server (NTRS)

Chung, Chang-Hong; Kim, Sku C.; Stubbs, Robert M.; Dewitt, Kenneth J.

1994-01-01

Two different approaches, the direct simulation Monte Carlo (DSMC) method based on molecular gasdynamics, and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gasdynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental data, in which density and rotational temperature variations along the centerline and at various locations inside a low-density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data, both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity-temperature exponent, have substantial effects on the results of the DSMC method.

Gyre and gimble: a maximum-likelihood replacement for Patterson correlation refinement.

PubMed

McCoy, Airlie J; Oeffner, Robert D; Millán, Claudia; Sammito, Massimo; Usón, Isabel; Read, Randy J

2018-04-01

Descriptions are given of the maximum-likelihood gyre method implemented in Phaser for optimizing the orientation and relative position of rigid-body fragments of a model after the orientation of the model has been identified, but before the model has been positioned in the unit cell, and also the related gimble method for the refinement of rigid-body fragments of the model after positioning. Gyre refinement helps to lower the root-mean-square atomic displacements between model and target molecular-replacement solutions for the test case of antibody Fab(26-10) and improves structure solution with ARCIMBOLDO_SHREDDER.

Geometric and electrostatic modeling using molecular rigidity functions

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

Mu, Lin; Xia, Kelin; Wei, Guowei

Geometric and electrostatic modeling is an essential component in computational biophysics and molecular biology. Commonly used geometric representations admit geometric singularities such as cusps, tips and self-intersecting facets that lead to computational instabilities in the molecular modeling. Our present work explores the use of flexibility and rigidity index (FRI), which has a proved superiority in protein B-factor prediction, for biomolecular geometric representation and associated electrostatic analysis. FRI rigidity surfaces are free of geometric singularities. We propose a rigidity based Poisson–Boltzmann equation for biomolecular electrostatic analysis. These approaches to surface and electrostatic modeling are validated by a set of 21 proteins.more » Our results are compared with those of established methods. Finally, being smooth and analytically differentiable, FRI rigidity functions offer excellent curvature analysis, which characterizes concave and convex regions on protein surfaces. Polarized curvatures constructed by using the product of minimum curvature and electrostatic potential is shown to predict potential protein–ligand binding sites.« less

Computer Modeling of the Structure and Spectra of Fluorescent Proteins

PubMed Central

Grigorenko, B.L.; Savitsky, A.P.

2009-01-01

Fluorescent proteins from the family of green fluorescent proteins are intensively used as biomarkers in living systems. The chromophore group based on the hydroxybenzylidene-imidazoline molecule, which is formed in nature from three amino-acid residues inside the protein globule and well shielded from external media, is responsible for light absorption and fluorescence. Along with the intense experimental studies of the properties of fluorescent proteins and their chromophores by biochemical, X-ray, and spectroscopic tools, in recent years, computer modeling has been used to characterize their properties and spectra. We present in this review the most interesting results of the molecular modeling of the structural parameters and optical and vibrational spectra of the chromophorecontaining domains of fluorescent proteins by methods of quantum chemistry, molecular dynamics, and combined quantum-mechanical-molecular-mechanical approaches. The main emphasis is on the correlation of theoretical and experimental data and on the predictive power of modeling, which may be useful for creating new, efficient biomarkers. PMID:22649601

Geometric and electrostatic modeling using molecular rigidity functions

DOE PAGES

Mu, Lin; Xia, Kelin; Wei, Guowei

2017-03-01

Geometric and electrostatic modeling is an essential component in computational biophysics and molecular biology. Commonly used geometric representations admit geometric singularities such as cusps, tips and self-intersecting facets that lead to computational instabilities in the molecular modeling. Our present work explores the use of flexibility and rigidity index (FRI), which has a proved superiority in protein B-factor prediction, for biomolecular geometric representation and associated electrostatic analysis. FRI rigidity surfaces are free of geometric singularities. We propose a rigidity based Poisson–Boltzmann equation for biomolecular electrostatic analysis. These approaches to surface and electrostatic modeling are validated by a set of 21 proteins.more » Our results are compared with those of established methods. Finally, being smooth and analytically differentiable, FRI rigidity functions offer excellent curvature analysis, which characterizes concave and convex regions on protein surfaces. Polarized curvatures constructed by using the product of minimum curvature and electrostatic potential is shown to predict potential protein–ligand binding sites.« less

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.

Development and application of QM/MM methods to study the solvation effects and surfaces

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

Dibya, Pooja Arora

2010-01-01

Quantum mechanical (QM) calculations have the advantage of attaining high-level accuracy, however QM calculations become computationally inefficient as the size of the system grows. Solving complex molecular problems on large systems and ensembles by using quantum mechanics still poses a challenge in terms of the computational cost. Methods that are based on classical mechanics are an inexpensive alternative, but they lack accuracy. A good trade off between accuracy and efficiency is achieved by combining QM methods with molecular mechanics (MM) methods to use the robustness of the QM methods in terms of accuracy and the MM methods to minimize themore » computational cost. Two types of QM combined with MM (QM/MM) methods are the main focus of the present dissertation: the application and development of QM/MM methods for solvation studies and reactions on the Si(100) surface. The solvation studies were performed using a discreet solvation model that is largely based on first principles called the effective fragment potential method (EFP). The main idea of combining the EFP method with quantum mechanics is to accurately treat the solute-solvent and solvent-solvent interactions, such as electrostatic, polarization, dispersion and charge transfer, that are important in correctly calculating solvent effects on systems of interest. A second QM/MM method called SIMOMM (surface integrated molecular orbital molecular mechanics) is a hybrid QM/MM embedded cluster model that mimics the real surface.3 This method was employed to calculate the potential energy surfaces for reactions of atomic O on the Si(100) surface. The hybrid QM/MM method is a computationally inexpensive approach for studying reactions on larger surfaces in a reasonably accurate and efficient manner. This thesis is comprised of four chapters: Chapter 1 describes the general overview and motivation of the dissertation and gives a broad background of the computational methods that have been employed in this work. Chapter 2 illustrates the methodology of the interface of the EFP method with the configuration interaction with single excitations (CIS) method to study solvent effects in excited states. Chapter 3 discusses the study of the adiabatic electron affinity of the hydroxyl radical in aqueous solution and in micro-solvated clusters using a QM/EFP method. Chapter 4 describes the study of etching and diffusion of oxygen atom on a reconstructed Si(100)-2 x 1 surface using a hybrid QM/MM embedded cluster model (SIMOMM). Chapter 4 elucidates the application of the EFP method towards the understanding of the aqueous ionization potential of Na atom. Finally, a general conclusion of this dissertation work and prospective future direction are presented in Chapter 6.« less

Molecular Docking for Prediction and Interpretation of Adverse Drug Reactions.

PubMed

Luo, Heng; Fokoue-Nkoutche, Achille; Singh, Nalini; Yang, Lun; Hu, Jianying; Zhang, Ping

2018-05-23

Adverse drug reactions (ADRs) present a major burden for patients and the healthcare industry. Various computational methods have been developed to predict ADRs for drug molecules. However, many of these methods require experimental or surveillance data and cannot be used when only structural information is available. We collected 1,231 small molecule drugs and 600 human proteins and utilized molecular docking to generate binding features among them. We developed machine learning models that use these docking features to make predictions for 1,533 ADRs. These models obtain an overall area under the receiver operating characteristic curve (AUROC) of 0.843 and an overall area under the precision-recall curve (AUPR) of 0.395, outperforming seven structural fingerprint-based prediction models. Using the method, we predicted skin striae for fluticasone propionate, dermatitis acneiform for mometasone, and decreased libido for irinotecan, as demonstrations. Furthermore, we analyzed the top binding proteins associated with some of the ADRs, which can help to understand and/or generate hypotheses for underlying mechanisms of ADRs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

New approach in direct-simulation of gas mixtures

NASA Technical Reports Server (NTRS)

Chung, Chan-Hong; De Witt, Kenneth J.; Jeng, Duen-Ren

1991-01-01

Results are reported for an investigation of a new direct-simulation Monte Carlo method by which energy transfer and chemical reactions are calculated. The new method, which reduces to the variable cross-section hard sphere model as a special case, allows different viscosity-temperature exponents for each species in a gas mixture when combined with a modified Larsen-Borgnakke phenomenological model. This removes the most serious limitation of the usefulness of the model for engineering simulations. The necessary kinetic theory for the application of the new method to mixtures of monatomic or polyatomic gases is presented, including gas mixtures involving chemical reactions. Calculations are made for the relaxation of a diatomic gas mixture, a plane shock wave in a gas mixture, and a chemically reacting gas flow along the stagnation streamline in front of a hypersonic vehicle. Calculated results show that the introduction of different molecular interactions for each species in a gas mixture produces significant differences in comparison with a common molecular interaction for all species in the mixture. This effect should not be neglected for accurate DSMC simulations in an engineering context.

Binding Affinity prediction with Property Encoded Shape Distribution signatures

PubMed Central

Das, Sourav; Krein, Michael P.

2010-01-01

We report the use of the molecular signatures known as “Property-Encoded Shape Distributions” (PESD) together with standard Support Vector Machine (SVM) techniques to produce validated models that can predict the binding affinity of a large number of protein ligand complexes. This “PESD-SVM” method uses PESD signatures that encode molecular shapes and property distributions on protein and ligand surfaces as features to build SVM models that require no subjective feature selection. A simple protocol was employed for tuning the SVM models during their development, and the results were compared to SFCscore – a regression-based method that was previously shown to perform better than 14 other scoring functions. Although the PESD-SVM method is based on only two surface property maps, the overall results were comparable. For most complexes with a dominant enthalpic contribution to binding (ΔH/-TΔS > 3), a good correlation between true and predicted affinities was observed. Entropy and solvent were not considered in the present approach and further improvement in accuracy would require accounting for these components rigorously. PMID:20095526

Hierarchical Coarse-Graining Via a Generalized Yvon-Born Green Framework: Many-Body Correlations, Mappings, and Structural Accuracy

NASA Astrophysics Data System (ADS)

Rudzinski, Joseph F.

Atomically-detailed molecular dynamics simulations have emerged as one of the most powerful theoretic tools for studying complex, condensed-phase systems. Despite their ability to provide incredible molecular insight, these simulations are insufficient for investigating complex biological processes, e.g., protein folding or molecular aggregation, on relevant length and time scales. The increasing scope and sophistication of atomically-detailed models has motivated the development of "hierarchical" approaches, which parameterize a low resolution, coarse-grained (CG) model based on simulations of an atomically-detailed model. The utility of hierarchical CG models depends on their ability to accurately incorporate the correct physics of the underlying model. One approach for ensuring this "consistency" between the models is to parameterize the CG model to reproduce the structural ensemble generated by the high resolution model. The many-body potential of mean force is the proper CG energy function for reproducing all structural distributions of the atomically-detailed model, at the CG level of resolution. However, this CG potential is a configuration-dependent free energy function that is generally too complicated to represent or simulate. The multiscale coarse-graining (MS-CG) method employs a generalized Yvon-Born-Green (g-YBG) relation to directly determine a variationally optimal approximation to the many-body potential of mean force. The MS-CG/g-YBG method provides a convenient and transparent framework for investigating the equilibrium structure of the system, at the CG level of resolution. In this work, we investigate the fundamental limitations and approximations of the MS-CG/g-YBG method. Throughout the work, we propose several theoretic constructs to directly relate the MS-CG/g-YBG method to other popular structure-based CG approaches. We investigate the physical interpretation of the MS-CG/g-YBG correlation matrix, the quantity responsible for disentangling the various contributions to the average force on a CG site. We then employ an iterative extension of the MS-CG/g-YBG method that improves the accuracy of a particular set of low order correlation functions relative to the original MS-CG/g-YBG model. We demonstrate that this method provides a powerful framework for identifying the precise source of error in an MS-CG/g-YBG model. We then propose a method for identifying an optimal CG representation, prior to the development of the CG model. We employ these techniques together to demonstrate that in the cases where the MS-CG/g-YBG method fails to determine an accurate model, a fundamental problem likely exists with the chosen CG representation or interaction set. Additionally, we explicitly demonstrate that while the iterative model successfully improves the accuracy of the low order structure, it does so by distorting the higher order structural correlations relative to the underlying model. Finally, we apply these methods to investigate the utility of the MS-CG/g- YBG method for developing models for systems with complex intramolecular structure. Overall, our results demonstrate the power of the g-YBG framework for developing accurate CG models and for investigating the driving forces of equilibrium structures for complex condensed-phase systems. This work also explicitly motivates future development of bottom-up CG methods and highlights some outstanding problems in the field. iii.

In Vivo Investigation of Breast Cancer Progression by Use of an Internal Control1

PubMed Central

Baeten, John; Haller, Jodi; Shih, Helen; Ntziachristos, Vasilis

2009-01-01

Optical imaging of breast cancer has been considered for detecting functional and molecular characteristics of diseases in clinical and preclinical settings. Applied to laboratory research, photonic investigations offer a highly versatile tool for preclinical imaging and drug discovery. A particular advantage of the optical method is the availability of multiple spectral bands for performing imaging. Herein, we capitalize on this feature to demonstrate how it is possible to use different wavelengths to offer internal controls and significantly improve the observation accuracy in molecular imaging applications. In particular, we show the independent in vivo detection of cysteine proteases along with tumor permeability and interstitial volume measurements using a dual-wavelength approach. To generate results with a view toward clinically geared studies, a transgenic Her2/neu mouse model that spontaneously developed mammary tumors was used. In vivo findings were validated against conventional ex vivo tests such as histology and Western blot analyses. By correcting for biodistribution parameters, the dual-wavelength method increases the accuracy of molecular observations by separating true molecular target from probe biodistribution. As such, the method is highly appropriate for molecular imaging studies where often probe delivery and target presence are not independently assessed. On the basis of these findings, we propose the dual-wavelength/normalization approach as an essential method for drug discovery and preclinical imaging studies. PMID:19242603

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

Live Cell Imaging of Viscosity in 3D Tumour Cell Models.

PubMed

Shirmanova, Marina V; Shimolina, Lubov' E; Lukina, Maria M; Zagaynova, Elena V; Kuimova, Marina K

2017-01-01

Abnormal levels of viscosity in tissues and cells are known to be associated with disease and malfunction. While methods to measure bulk macroscopic viscosity of bio-tissues are well developed, imaging viscosity at the microscopic scale remains a challenge, especially in vivo. Molecular rotors are small synthetic viscosity-sensitive fluorophores in which fluorescence parameters are strongly correlated to the microviscosity of their immediate environment. Hence, molecular rotors represent a promising instrument for mapping of viscosity in living cells and tissues at the microscopic level. Quantitative measurements of viscosity can be achieved by recording time-resolved fluorescence decays of molecular rotor using fluorescence lifetime imaging microscopy (FLIM), which is also suitable for dynamic viscosity mapping, both in cellulo and in vivo. Among tools of experimental oncology, 3D tumour cultures, or spheroids, are considered a more adequate in vitro model compared to a cellular monolayer, and represent a less labour-intensive and more unified approach compared to animal tumour models. This chapter describes a methodology for microviscosity imaging in tumour spheroids using BODIPY-based molecular rotors and two photon-excited FLIM.

Understanding the Origins of Dipolar Couplings and Correlated Motion in the Vibrational Spectrum of Water.

PubMed

Heyden, Matthias; Sun, Jian; Forbert, Harald; Mathias, Gerald; Havenith, Martina; Marx, Dominik

2012-08-16

The combination of vibrational spectroscopy and molecular dynamics simulations provides a powerful tool to obtain insights into the molecular details of water structure and dynamics in the bulk and in aqueous solutions. Applying newly developed approaches to analyze correlations of charge currents, molecular dipole fluctuations, and vibrational motion in real and k-space, we compare results from nonpolarizable water models, widely used in biomolecular modeling, to ab initio molecular dynamics. For the first time, we unfold the infrared response of bulk water into contributions from correlated fluctuations in the three-dimensional, anisotropic environment of an average water molecule, from the OH-stretching region down to the THz regime. Our findings show that the absence of electronic polarizability in the force field model not only results in differences in dipolar couplings and infrared absorption but also induces artifacts into the correlated vibrational motion between hydrogen-bonded water molecules, specifically at the intramolecular bending frequency. Consequently, vibrational motion is partially ill-described with implications for the accuracy of non-self-consistent, a posteriori methods to add polarizability.

High-resolution modeling of antibody structures by a combination of bioinformatics, expert knowledge, and molecular simulations.

PubMed

Shirai, Hiroki; Ikeda, Kazuyoshi; Yamashita, Kazuo; Tsuchiya, Yuko; Sarmiento, Jamica; Liang, Shide; Morokata, Tatsuaki; Mizuguchi, Kenji; Higo, Junichi; Standley, Daron M; Nakamura, Haruki

2014-08-01

In the second antibody modeling assessment, we used a semiautomated template-based structure modeling approach for 11 blinded antibody variable region (Fv) targets. The structural modeling method involved several steps, including template selection for framework and canonical structures of complementary determining regions (CDRs), homology modeling, energy minimization, and expert inspection. The submitted models for Fv modeling in Stage 1 had the lowest average backbone root mean square deviation (RMSD) (1.06 Å). Comparison to crystal structures showed the most accurate Fv models were generated for 4 out of 11 targets. We found that the successful modeling in Stage 1 mainly was due to expert-guided template selection for CDRs, especially for CDR-H3, based on our previously proposed empirical method (H3-rules) and the use of position specific scoring matrix-based scoring. Loop refinement using fragment assembly and multicanonical molecular dynamics (McMD) was applied to CDR-H3 loop modeling in Stage 2. Fragment assembly and McMD produced putative structural ensembles with low free energy values that were scored based on the OSCAR all-atom force field and conformation density in principal component analysis space, respectively, as well as the degree of consensus between the two sampling methods. The quality of 8 out of 10 targets improved as compared with Stage 1. For 4 out of 10 Stage-2 targets, our method generated top-scoring models with RMSD values of less than 1 Å. In this article, we discuss the strengths and weaknesses of our approach as well as possible directions for improvement to generate better predictions in the future. © 2014 Wiley Periodicals, Inc.

The fast multipole method and point dipole moment polarizable force fields.

PubMed

Coles, Jonathan P; Masella, Michel

2015-01-14

We present an implementation of the fast multipole method for computing Coulombic electrostatic and polarization forces from polarizable force-fields based on induced point dipole moments. We demonstrate the expected O(N) scaling of that approach by performing single energy point calculations on hexamer protein subunits of the mature HIV-1 capsid. We also show the long time energy conservation in molecular dynamics at the nanosecond scale by performing simulations of a protein complex embedded in a coarse-grained solvent using a standard integrator and a multiple time step integrator. Our tests show the applicability of fast multipole method combined with state-of-the-art chemical models in molecular dynamical systems.

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

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

Two-dimensional molecular line transfer for a cometary coma

NASA Astrophysics Data System (ADS)

Szutowicz, S.

2017-09-01

In the proposed axisymmetric model of the cometary coma the gas density profile is described by an angular density function. Three methods for treating two-dimensional radiative transfer are compared: the Large Velocity Gradient (LVG) (the Sobolev method), Accelerated Lambda Iteration (ALI) and accelerated Monte Carlo (MC).

Rinsing paired-agent model (RPAM) to quantify cell-surface receptor concentrations in topical staining applications of thick tissues

NASA Astrophysics Data System (ADS)

Xu, Xiaochun; Wang, Yu; Xiang, Jialing; Liu, Jonathan T. C.; Tichauer, Kenneth M.

2017-06-01

Conventional molecular assessment of tissue through histology, if adapted to fresh thicker samples, has the potential to enhance cancer detection in surgical margins and monitoring of 3D cell culture molecular environments. However, in thicker samples, substantial background staining is common despite repeated rinsing, which can significantly reduce image contrast. Recently, ‘paired-agent’ methods—which employ co-administration of a control (untargeted) imaging agent—have been applied to thick-sample staining applications to account for background staining. To date, these methods have included (1) a simple ratiometric method that is relatively insensitive to noise in the data but has accuracy that is dependent on the staining protocol and the characteristics of the sample; and (2) a complex paired-agent kinetic modeling method that is more accurate but is more noise-sensitive and requires a precise serial rinsing protocol. Here, a new simplified mathematical model—the rinsing paired-agent model (RPAM)—is derived and tested that offers a good balance between the previous models, is adaptable to arbitrary rinsing-imaging protocols, and does not require calibration of the imaging system. RPAM is evaluated against previous models and is validated by comparison to estimated concentrations of targeted biomarkers on the surface of 3D cell culture and tumor xenograft models. This work supports the use of RPAM as a preferable model to quantitatively analyze targeted biomarker concentrations in topically stained thick tissues, as it was found to match the accuracy of the complex paired-agent kinetic model while retaining the low noise-sensitivity characteristics of the ratiometric method.

Application potential of ATR-FT/IR molecular spectroscopy in animal nutrition: revelation of protein molecular structures of canola meal and presscake, as affected by heat-processing methods, in relationship with their protein digestive behavior and utilization for dairy cattle.

PubMed

Theodoridou, Katerina; Yu, Peiqiang

2013-06-12

Protein quality relies not only on total protein but also on protein inherent structures. The most commonly occurring protein secondary structures (α-helix and β-sheet) may influence protein quality, nutrient utilization, and digestive behavior. The objectives of this study were to reveal the protein molecular structures of canola meal (yellow and brown) and presscake as affected by the heat-processing methods and to investigate the relationship between structure changes and protein rumen degradations kinetics, estimated protein intestinal digestibility, degraded protein balance, and metabolizable protein. Heat-processing conditions resulted in a higher value for α-helix and β-sheet for brown canola presscake compared to brown canola meal. The multivariate molecular spectral analyses (PCA, CLA) showed that there were significant molecular structural differences in the protein amide I and II fingerprint region (ca. 1700-1480 cm(-1)) between the brown canola meal and presscake. The in situ degradation parameters, amide I and II, and α-helix to β-sheet ratio (R_a_β) were positively correlated with the degradable fraction and the degradation rate. Modeling results showed that α-helix was positively correlated with the truly absorbed rumen synthesized microbial protein in the small intestine when using both the Dutch DVE/OEB system and the NRC-2001 model. Concerning the protein profiles, R_a_β was a better predictor for crude protein (79%) and for neutral detergent insoluble crude protein (68%). In conclusion, ATR-FT/IR molecular spectroscopy may be used to rapidly characterize feed structures at the molecular level and also as a potential predictor of feed functionality, digestive behavior, and nutrient utilization of canola feed.

Designing Free Energy Surfaces That Match Experimental Data with Metadynamics

DOE PAGES

White, Andrew D.; Dama, James F.; Voth, Gregory A.

2015-04-30

Creating models that are consistent with experimental data is essential in molecular modeling. This is often done by iteratively tuning the molecular force field of a simulation to match experimental data. An alternative method is to bias a simulation, leading to a hybrid model composed of the original force field and biasing terms. Previously we introduced such a method called experiment directed simulation (EDS). EDS minimally biases simulations to match average values. We also introduce a new method called experiment directed metadynamics (EDM) that creates minimal biases for matching entire free energy surfaces such as radial distribution functions and phi/psimore » angle free energies. It is also possible with EDM to create a tunable mixture of the experimental data and free energy of the unbiased ensemble with explicit ratios. EDM can be proven to be convergent, and we also present proof, via a maximum entropy argument, that the final bias is minimal and unique. Examples of its use are given in the construction of ensembles that follow a desired free energy. Finally, the example systems studied include a Lennard-Jones fluid made to match a radial distribution function, an atomistic model augmented with bioinformatics data, and a three-component electrolyte solution where ab initio simulation data is used to improve a classical empirical model.« less

Designing free energy surfaces that match experimental data with metadynamics.

PubMed

White, Andrew D; Dama, James F; Voth, Gregory A

2015-06-09

Creating models that are consistent with experimental data is essential in molecular modeling. This is often done by iteratively tuning the molecular force field of a simulation to match experimental data. An alternative method is to bias a simulation, leading to a hybrid model composed of the original force field and biasing terms. We previously introduced such a method called experiment directed simulation (EDS). EDS minimally biases simulations to match average values. In this work, we introduce a new method called experiment directed metadynamics (EDM) that creates minimal biases for matching entire free energy surfaces such as radial distribution functions and phi/psi angle free energies. It is also possible with EDM to create a tunable mixture of the experimental data and free energy of the unbiased ensemble with explicit ratios. EDM can be proven to be convergent, and we also present proof, via a maximum entropy argument, that the final bias is minimal and unique. Examples of its use are given in the construction of ensembles that follow a desired free energy. The example systems studied include a Lennard-Jones fluid made to match a radial distribution function, an atomistic model augmented with bioinformatics data, and a three-component electrolyte solution where ab initio simulation data is used to improve a classical empirical model.

3D molecular models of whole HIV-1 virions generated with cellPACK

PubMed Central

Goodsell, David S.; Autin, Ludovic; Forli, Stefano; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

As knowledge of individual biological processes grows, it becomes increasingly useful to frame new findings within their larger biological contexts in order to generate new systems-scale hypotheses. This report highlights two major iterations of a whole virus model of HIV-1, generated with the cellPACK software. cellPACK integrates structural and systems biology data with packing algorithms to assemble comprehensive 3D models of cell-scale structures in molecular detail. This report describes the biological data, modeling parameters and cellPACK methods used to specify and construct editable models for HIV-1. Anticipating that cellPACK interfaces under development will enable researchers from diverse backgrounds to critique and improve the biological models, we discuss how cellPACK can be used as a framework to unify different types of data across all scales of biology. PMID:25253262

WDL-RF: Predicting Bioactivities of Ligand Molecules Acting with G Protein-coupled Receptors by Combining Weighted Deep Learning and Random Forest.

PubMed

Wu, Jiansheng; Zhang, Qiuming; Wu, Weijian; Pang, Tao; Hu, Haifeng; Chan, Wallace K B; Ke, Xiaoyan; Zhang, Yang; Wren, Jonathan

2018-02-08

Precise assessment of ligand bioactivities (including IC50, EC50, Ki, Kd, etc.) is essential for virtual screening and lead compound identification. However, not all ligands have experimentally-determined activities. In particular, many G protein-coupled receptors (GPCRs), which are the largest integral membrane protein family and represent targets of nearly 40% drugs on the market, lack published experimental data about ligand interactions. Computational methods with the ability to accurately predict the bioactivity of ligands can help efficiently address this problem. We proposed a new method, WDL-RF, using weighted deep learning and random forest, to model the bioactivity of GPCR-associated ligand molecules. The pipeline of our algorithm consists of two consecutive stages: 1) molecular fingerprint generation through a new weighted deep learning method, and 2) bioactivity calculations with a random forest model; where one uniqueness of the approach is that the model allows end-to-end learning of prediction pipelines with input ligands being of arbitrary size. The method was tested on a set of twenty-six non-redundant GPCRs that have a high number of active ligands, each with 200∼4000 ligand associations. The results from our benchmark show that WDL-RF can generate bioactivity predictions with an average root-mean square error 1.33 and correlation coefficient (r2) 0.80 compared to the experimental measurements, which are significantly more accurate than the control predictors with different molecular fingerprints and descriptors. In particular, data-driven molecular fingerprint features, as extracted from the weighted deep learning models, can help solve deficiencies stemming from the use of traditional hand-crafted features and significantly increase the efficiency of short molecular fingerprints in virtual screening. The WDL-RF web server, as well as source codes and datasets of WDL-RF, is freely available at https://zhanglab.ccmb.med.umich.edu/WDL-RF/ for academic purposes. Xiaoyan Ke (kexynj@hotmail.com); Yang Zhang (zhng@umich.edu). Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Animation Model to Conceptualize ATP Generation: A Mitochondrial Oxidative Phosphorylation

ERIC Educational Resources Information Center

Jena, Ananta Kumar

2015-01-01

Adenosine triphosphate (ATP) is the molecular unit of intracellular energy and it is the product of oxidative phosphorylation of cellular respiration uses in cellular processes. The study explores the growth of the misconception levels amongst the learners and evaluates the effectiveness of animation model over traditional methods. The data…

Model Building to Facilitate Understanding of Holliday Junction and Heteroduplex Formation, and Holliday Junction Resolution

ERIC Educational Resources Information Center

Selvarajah, Geeta; Selvarajah, Susila

2016-01-01

Students frequently expressed difficulty in understanding the molecular mechanisms involved in chromosomal recombination. Therefore, we explored alternative methods for presenting the two concepts of the double-strand break model: Holliday junction and heteroduplex formation, and Holliday junction resolution. In addition to a lecture and…

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.

A mixing timescale model for TPDF simulations of turbulent premixed flames

DOE PAGES

Kuron, Michael; Ren, Zhuyin; Hawkes, Evatt R.; ...

2017-02-06

Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priorimore » assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. Here, the new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure. It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. Furthermore, the EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive scalar mixing across different flame regimes are appropriately accounted for.« less

A mixing timescale model for TPDF simulations of turbulent premixed flames

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

Kuron, Michael; Ren, Zhuyin; Hawkes, Evatt R.

Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priorimore » assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. Here, the new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure. It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. Furthermore, the EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive scalar mixing across different flame regimes are appropriately accounted for.« less

Structure and conformational dynamics of scaffolded DNA origami nanoparticles

DTIC Science & Technology

2017-05-08

all-atom molecular dynamics and coarse-grained finite element modeling to DX-based nanoparticles to elucidate their fine-scale and global conforma... finite element (FE) modeling approach CanDo is also routinely used to predict the 3D equilibrium conformation of programmed DNA assemblies based on a...model with both experimental cryo-electron microscopy (cryo-EM) data and all-atom modeling. MATERIALS AND METHODS Lattice-free finite element model

Coupling all-atom molecular dynamics simulations of ions in water with Brownian dynamics.

PubMed

Erban, Radek

2016-02-01

Molecular dynamics (MD) simulations of ions (K + , Na + , Ca 2+ and Cl - ) in aqueous solutions are investigated. Water is described using the SPC/E model. A stochastic coarse-grained description for ion behaviour is presented and parametrized using MD simulations. It is given as a system of coupled stochastic and ordinary differential equations, describing the ion position, velocity and acceleration. The stochastic coarse-grained model provides an intermediate description between all-atom MD simulations and Brownian dynamics (BD) models. It is used to develop a multiscale method which uses all-atom MD simulations in parts of the computational domain and (less detailed) BD simulations in the remainder of the domain.

Indirect Measurement Of Nitrogen In A Multi-Component Gas By Measuring The Speed Of Sound At Two States Of The Gas.

DOEpatents

Morrow, Thomas B.; Behring, II, Kendricks A.

2004-10-12

A methods of indirectly measuring the nitrogen concentration in a gas mixture. The molecular weight of the gas is modeled as a function of the speed of sound in the gas, the diluent concentrations in the gas, and constant values, resulting in a model equation. Regression analysis is used to calculate the constant values, which can then be substituted into the model equation. If the speed of sound in the gas is measured at two states and diluent concentrations other than nitrogen (typically carbon dioxide) are known, two equations for molecular weight can be equated and solved for the nitrogen concentration in the gas mixture.

A systematic petri net approach for multiple-scale modeling and simulation of biochemical processes.

PubMed

Chen, Ming; Hu, Minjie; Hofestädt, Ralf

2011-06-01

A method to exploit hybrid Petri nets for modeling and simulating biochemical processes in a systematic way was introduced. Both molecular biology and biochemical engineering aspects are manipulated. With discrete and continuous elements, the hybrid Petri nets can easily handle biochemical factors such as metabolites concentration and kinetic behaviors. It is possible to translate both molecular biological behavior and biochemical processes workflow into hybrid Petri nets in a natural manner. As an example, penicillin production bioprocess is modeled to illustrate the concepts of the methodology. Results of the dynamic of production parameters in the bioprocess were simulated and observed diagrammatically. Current problems and post-genomic perspectives were also discussed.

Molecular beam mass spectrometer development

NASA Technical Reports Server (NTRS)

Brock, F. J.; Hueser, J. E.

1976-01-01

An analytical model, based on the kinetics theory of a drifting Maxwellian gas is used to determine the nonequilibrium molecular density distribution within a hemispherical shell open aft with its axis parallel to its velocity. The concept of a molecular shield in terrestrial orbit above 200 km is also analyzed using the kinetic theory of a drifting Maxwellian gas. Data are presented for the components of the gas density within the shield due to the free stream atmosphere, outgassing from the shield and enclosed experiments, and atmospheric gas scattered off a shield orbiter system. A description is given of a FORTRAN program for computating the three dimensional transition flow regime past the space shuttle orbiter that employs the Monte Carlo simulation method to model real flow by some thousands of simulated molecules.