Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids.

PubMed

Aradi, Bálint; Niklasson, Anders M N; Frauenheim, Thomas

2015-07-14

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born-Oppenheimer molecular dynamics. For systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can be applied to a broad range of problems in materials science, chemistry, and biology.

A Fast Algorithm for Massively Parallel, Long-Term, Simulation of Complex Molecular Dynamics Systems

NASA Technical Reports Server (NTRS)

Jaramillo-Botero, Andres; Goddard, William A, III; Fijany, Amir

1997-01-01

The advances in theory and computing technology over the last decade have led to enormous progress in applying atomistic molecular dynamics (MD) methods to the characterization, prediction, and design of chemical, biological, and material systems,.

An autonomous molecular computer for logical control of gene expression.

PubMed

Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud

2004-05-27

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems. Recently, simple molecular-scale autonomous programmable computers were demonstrated allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for 'logical' control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.

Computational drug discovery

PubMed Central

Ou-Yang, Si-sheng; Lu, Jun-yan; Kong, Xiang-qian; Liang, Zhong-jie; Luo, Cheng; Jiang, Hualiang

2012-01-01

Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field. PMID:22922346

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids

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

Aradi, Bálint; Niklasson, Anders M. N.; Frauenheim, Thomas

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born–Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materialsmore » science, chemistry, and biology.« less

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids

DOE PAGES

Aradi, Bálint; Niklasson, Anders M. N.; Frauenheim, Thomas

2015-06-26

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born–Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materialsmore » science, chemistry, and biology.« less

Protein Dynamics from NMR and Computer Simulation

NASA Astrophysics Data System (ADS)

Wu, Qiong; Kravchenko, Olga; Kemple, Marvin; Likic, Vladimir; Klimtchuk, Elena; Prendergast, Franklyn

2002-03-01

Proteins exhibit internal motions from the millisecond to sub-nanosecond time scale. The challenge is to relate these internal motions to biological function. A strategy to address this aim is to apply a combination of several techniques including high-resolution NMR, computer simulation of molecular dynamics (MD), molecular graphics, and finally molecular biology, the latter to generate appropriate samples. Two difficulties that arise are: (1) the time scale which is most directly biologically relevant (ms to μs) is not readily accessible by these techniques and (2) the techniques focus on local and not collective motions. We will outline methods using ^13C-NMR to help alleviate the second problem, as applied to intestinal fatty acid binding protein, a relatively small intracellular protein believed to be involved in fatty acid transport and metabolism. This work is supported in part by PHS Grant GM34847 (FGP) and by a fellowship from the American Heart Association (QW).

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.

Elucidation of the Chromatographic Enantiomer Elution Order Through Computational Studies.

PubMed

Sardella, Roccaldo; Ianni, Federica; Macchiarulo, Antonio; Pucciarini, Lucia; Carotti, Andrea; Natalini, Benedetto

2018-01-01

During the last twenty years, the interest towards the development of chiral compound has exponentially been increased. Indeed, the set-up of suitable asymmetric enantioselective synthesis protocols is currently one of the focuses of many pharmaceutical research projects. In this scenario, chiral HPLC separations have gained great importance as well, both for analytical- and preparative-scale applications, the latter devoted to the quantitative isolation of enantiopure compounds. Molecular modelling and quantum chemistry methods can be fruitfully applied to solve chirality related problems especially when enantiomerically pure reference standards are missing. In this framework, with the aim to explain the molecular basis of the enantioselective retention, we performed computational studies to rationalize the enantiomer elution order with both low- and high-molecular weight chiral selectors. Semi-empirical and quantum mechanical computational procedures were successfully applied in the domains of chiral ligand-exchange and chiral ion-exchange chromatography, as well as in studies dealing with the use of polysaccharide-based enantioresolving materials. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

An autonomous molecular computer for logical control of gene expression

PubMed Central

Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud

2013-01-01

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems1–7. Recently, simple molecular-scale autonomous programmable computers were demonstrated8–15 allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for ‘logical’ control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton12–17; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes18–22 associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug. PMID:15116117

The Use of Molecular Modeling Programs in Medicinal Chemistry Instruction.

ERIC Educational Resources Information Center

Harrold, Marc W.

1992-01-01

This paper describes and evaluates the use of a molecular modeling computer program (Alchemy II) in a pharmaceutical education program. Provided are the hardware requirements and basic program features as well as several examples of how this program and its features have been applied in the classroom. (GLR)

Non-Adiabatic Molecular Dynamics Methods for Materials Discovery

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

Furche, Filipp; Parker, Shane M.; Muuronen, Mikko J.

2017-04-04

The flow of radiative energy in light-driven materials such as photosensitizer dyes or photocatalysts is governed by non-adiabatic transitions between electronic states and cannot be described within the Born-Oppenheimer approximation commonly used in electronic structure theory. The non-adiabatic molecular dynamics (NAMD) methods based on Tully surface hopping and time-dependent density functional theory developed in this project have greatly extended the range of molecular materials that can be tackled by NAMD simulations. New algorithms to compute molecular excited state and response properties efficiently were developed. Fundamental limitations of common non-linear response methods were discovered and characterized. Methods for accurate computations ofmore » vibronic spectra of materials such as black absorbers were developed and applied. It was shown that open-shell TDDFT methods capture bond breaking in NAMD simulations, a longstanding challenge for single-reference molecular dynamics simulations. The methods developed in this project were applied to study the photodissociation of acetaldehyde and revealed that non-adiabatic effects are experimentally observable in fragment kinetic energy distributions. Finally, the project enabled the first detailed NAMD simulations of photocatalytic water oxidation by titania nanoclusters, uncovering the mechanism of this fundamentally important reaction for fuel generation and storage.« less

Computing pKa Values in Different Solvents by Electrostatic Transformation.

PubMed

Rossini, Emanuele; Netz, Roland R; Knapp, Ernst-Walter

2016-07-12

We introduce a method that requires only moderate computational effort to compute pKa values of small molecules in different solvents with an average accuracy of better than 0.7 pH units. With a known pKa value in one solvent, the electrostatic transform method computes the pKa value in any other solvent if the proton solvation energy is known in both considered solvents. To apply the electrostatic transform method to a molecule, the electrostatic solvation energies of the protonated and deprotonated molecular species are computed in the two considered solvents using a dielectric continuum to describe the solvent. This is demonstrated for 30 molecules belonging to 10 different molecular families by considering 77 measured pKa values in 4 different solvents: water, acetonitrile, dimethyl sulfoxide, and methanol. The electrostatic transform method can be applied to any other solvent if the proton solvation energy is known. It is exclusively based on physicochemical principles, not using any empirical fetch factors or explicit solvent molecules, to obtain agreement with measured pKa values and is therefore ready to be generalized to other solute molecules and solvents. From the computed pKa values, we obtained relative proton solvation energies, which agree very well with the proton solvation energies computed recently by ab initio methods, and used these energies in the present study.

Molecular dynamics simulations and applications in computational toxicology and nanotoxicology.

PubMed

Selvaraj, Chandrabose; Sakkiah, Sugunadevi; Tong, Weida; Hong, Huixiao

2018-02-01

Nanotoxicology studies toxicity of nanomaterials and has been widely applied in biomedical researches to explore toxicity of various biological systems. Investigating biological systems through in vivo and in vitro methods is expensive and time taking. Therefore, computational toxicology, a multi-discipline field that utilizes computational power and algorithms to examine toxicology of biological systems, has gained attractions to scientists. Molecular dynamics (MD) simulations of biomolecules such as proteins and DNA are popular for understanding of interactions between biological systems and chemicals in computational toxicology. In this paper, we review MD simulation methods, protocol for running MD simulations and their applications in studies of toxicity and nanotechnology. We also briefly summarize some popular software tools for execution of MD simulations. Published by Elsevier Ltd.

Thermodynamic and transport properties of nitrogen fluid: Molecular theory and computer simulations

NASA Astrophysics Data System (ADS)

Eskandari Nasrabad, A.; Laghaei, R.

2018-04-01

Computer simulations and various theories are applied to compute the thermodynamic and transport properties of nitrogen fluid. To model the nitrogen interaction, an existing potential in the literature is modified to obtain a close agreement between the simulation results and experimental data for the orthobaric densities. We use the Generic van der Waals theory to calculate the mean free volume and apply the results within the modified Cohen-Turnbull relation to obtain the self-diffusion coefficient. Compared to experimental data, excellent results are obtained via computer simulations for the orthobaric densities, the vapor pressure, the equation of state, and the shear viscosity. We analyze the results of the theory and computer simulations for the various thermophysical properties.

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

Analysing and Rationalising Molecular and Materials Databases Using Machine-Learning

NASA Astrophysics Data System (ADS)

de, Sandip; Ceriotti, Michele

Computational materials design promises to greatly accelerate the process of discovering new or more performant materials. Several collaborative efforts are contributing to this goal by building databases of structures, containing between thousands and millions of distinct hypothetical compounds, whose properties are computed by high-throughput electronic-structure calculations. The complexity and sheer amount of information has made manual exploration, interpretation and maintenance of these databases a formidable challenge, making it necessary to resort to automatic analysis tools. Here we will demonstrate how, starting from a measure of (dis)similarity between database items built from a combination of local environment descriptors, it is possible to apply hierarchical clustering algorithms, as well as dimensionality reduction methods such as sketchmap, to analyse, classify and interpret trends in molecular and materials databases, as well as to detect inconsistencies and errors. Thanks to the agnostic and flexible nature of the underlying metric, we will show how our framework can be applied transparently to different kinds of systems ranging from organic molecules and oligopeptides to inorganic crystal structures as well as molecular crystals. Funded by National Center for Computational Design and Discovery of Novel Materials (MARVEL) and Swiss National Science Foundation.

Computational efficiency and Amdahl’s law for the adaptive resolution simulation technique

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

Junghans, Christoph; Agarwal, Animesh; Delle Site, Luigi

Here, we discuss the computational performance of the adaptive resolution technique in molecular simulation when it is compared with equivalent full coarse-grained and full atomistic simulations. We show that an estimate of its efficiency, within 10%–15% accuracy, is given by the Amdahl’s Law adapted to the specific quantities involved in the problem. The derivation of the predictive formula is general enough that it may be applied to the general case of molecular dynamics approaches where a reduction of degrees of freedom in a multi scale fashion occurs.

Computational efficiency and Amdahl’s law for the adaptive resolution simulation technique

DOE PAGES

Junghans, Christoph; Agarwal, Animesh; Delle Site, Luigi

2017-06-01

Here, we discuss the computational performance of the adaptive resolution technique in molecular simulation when it is compared with equivalent full coarse-grained and full atomistic simulations. We show that an estimate of its efficiency, within 10%–15% accuracy, is given by the Amdahl’s Law adapted to the specific quantities involved in the problem. The derivation of the predictive formula is general enough that it may be applied to the general case of molecular dynamics approaches where a reduction of degrees of freedom in a multi scale fashion occurs.

Efficient electron open boundaries for simulating electrochemical cells

NASA Astrophysics Data System (ADS)

Zauchner, Mario G.; Horsfield, Andrew P.; Todorov, Tchavdar N.

2018-01-01

Nonequilibrium electrochemistry raises new challenges for atomistic simulation: we need to perform molecular dynamics for the nuclear degrees of freedom with an explicit description of the electrons, which in turn must be free to enter and leave the computational cell. Here we present a limiting form for electron open boundaries that we expect to apply when the magnitude of the electric current is determined by the drift and diffusion of ions in a solution and which is sufficiently computationally efficient to be used with molecular dynamics. We present tight-binding simulations of a parallel-plate capacitor with nothing, a dimer, or an atomic wire situated in the space between the plates. These simulations demonstrate that this scheme can be used to perform molecular dynamics simulations when there is an applied bias between two metal plates with, at most, weak electronic coupling between them. This simple system captures some of the essential features of an electrochemical cell, suggesting this approach might be suitable for simulations of electrochemical cells out of equilibrium.

Computational and experimental investigation of molecular imprinted polymers for selective extraction of dimethoate and its metabolite omethoate from olive oil.

PubMed

Bakas, Idriss; Oujji, Najwa Ben; Moczko, Ewa; Istamboulie, Georges; Piletsky, Sergey; Piletska, Elena; Ait-Addi, Elhabib; Ait-Ichou, Ihya; Noguer, Thierry; Rouillon, Régis

2013-01-25

This work presents the development of molecularly imprinted polymers (MIPs) for the selective extraction of dimethoate from olive oil. Computational simulations allowed selecting itaconic acid as the monomer showing the highest affinity towards dimethoate. Experimental validation confirmed modelling predictions and showed that the polymer based on IA as functional monomer and omethoate as template molecule displays the highest selectivity for the structurally similar pesticides dimethoate, omethoate and monocrotophos. Molecularly imprinted solid phase extraction (MISPE) method was developed and applied to the clean-up of olive oil extracts. It was found that the most suitable solvents for loading, washing and elution step were respectively hexane, hexane-dichloromethane (85:15%) and methanol. The developed MIPSE was successfully applied to extraction of dimethoate from olive oil, with recovery rates up to 94%. The limits of detection and quantification of the described method were respectively 0.012 and 0.05 μg g(-1). Copyright © 2012 Elsevier B.V. All rights reserved.

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.

Clustering molecular dynamics trajectories for optimizing docking experiments.

PubMed

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

2015-01-01

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

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide-and-conquer, density-functional tight-binding, and massively parallel computation.

PubMed

Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi

2016-08-05

The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Fast parallel molecular algorithms for DNA-based computation: solving the elliptic curve discrete logarithm problem over GF2.

PubMed

Li, Kenli; Zou, Shuting; Xv, Jin

2008-01-01

Elliptic curve cryptographic algorithms convert input data to unrecognizable encryption and the unrecognizable data back again into its original decrypted form. The security of this form of encryption hinges on the enormous difficulty that is required to solve the elliptic curve discrete logarithm problem (ECDLP), especially over GF(2(n)), n in Z+. This paper describes an effective method to find solutions to the ECDLP by means of a molecular computer. We propose that this research accomplishment would represent a breakthrough for applied biological computation and this paper demonstrates that in principle this is possible. Three DNA-based algorithms: a parallel adder, a parallel multiplier, and a parallel inverse over GF(2(n)) are described. The biological operation time of all of these algorithms is polynomial with respect to n. Considering this analysis, cryptography using a public key might be less secure. In this respect, a principal contribution of this paper is to provide enhanced evidence of the potential of molecular computing to tackle such ambitious computations.

Fast Parallel Molecular Algorithms for DNA-Based Computation: Solving the Elliptic Curve Discrete Logarithm Problem over GF(2n)

PubMed Central

Li, Kenli; Zou, Shuting; Xv, Jin

2008-01-01

Elliptic curve cryptographic algorithms convert input data to unrecognizable encryption and the unrecognizable data back again into its original decrypted form. The security of this form of encryption hinges on the enormous difficulty that is required to solve the elliptic curve discrete logarithm problem (ECDLP), especially over GF(2n), n ∈ Z+. This paper describes an effective method to find solutions to the ECDLP by means of a molecular computer. We propose that this research accomplishment would represent a breakthrough for applied biological computation and this paper demonstrates that in principle this is possible. Three DNA-based algorithms: a parallel adder, a parallel multiplier, and a parallel inverse over GF(2n) are described. The biological operation time of all of these algorithms is polynomial with respect to n. Considering this analysis, cryptography using a public key might be less secure. In this respect, a principal contribution of this paper is to provide enhanced evidence of the potential of molecular computing to tackle such ambitious computations. PMID:18431451

Genomics, proteomics, MEMS and SAIF: which role for diagnostic imaging?

PubMed

Grassi, R; Lagalla, R; Rotondo, A

2008-09-01

In these three words--genomics, proteomics and nanotechnologies--is the future of medicine of the third millennium, which will be characterised by more careful attention to disease prevention, diagnosis and treatment. Molecular imaging appears to satisfy this requirement. It is emerging as a new science that brings together molecular biology and in vivo imaging and represents the key for the application of personalized medicine. Micro-PET (positron emission tomography), micro-SPECT (single photon emission computed tomography), micro-CT (computed tomography), micro-MR (magnetic resonance), micro-US (ultrasound) and optical imaging are all molecular imaging techniques, several of which are applied only in preclinical settings on animal models. Others, however, are applied routinely in both clinical and preclinical setting. Research on small animals allows investigation of the genesis and development of diseases, as well as drug efficacy and the development of personalized therapies, through the study of biological processes that precede the expression of common symptoms of a pathology. Advances in molecular imaging were made possible only by collaboration among scientists in the fields of radiology, chemistry, molecular and cell biology, physics, mathematics, pharmacology, gene therapy and oncology. Although until now researchers have traditionally limited their interactions, it is only by increasing these connections that the current gaps in terminology, methods and approaches that inhibit scientific progress can be eliminated.

Simulated quantum computation of molecular energies.

PubMed

Aspuru-Guzik, Alán; Dutoi, Anthony D; Love, Peter J; Head-Gordon, Martin

2005-09-09

The calculation time for the energy of atoms and molecules scales exponentially with system size on a classical computer but polynomially using quantum algorithms. We demonstrate that such algorithms can be applied to problems of chemical interest using modest numbers of quantum bits. Calculations of the water and lithium hydride molecular ground-state energies have been carried out on a quantum computer simulator using a recursive phase-estimation algorithm. The recursive algorithm reduces the number of quantum bits required for the readout register from about 20 to 4. Mappings of the molecular wave function to the quantum bits are described. An adiabatic method for the preparation of a good approximate ground-state wave function is described and demonstrated for a stretched hydrogen molecule. The number of quantum bits required scales linearly with the number of basis functions, and the number of gates required grows polynomially with the number of quantum bits.

Integrated Multiscale Modeling of Molecular Computing Devices. Final Report

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

Tim Schulze

2012-11-01

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

Rapid communication: Computational simulation and analysis of a candidate for the design of a novel silk-based biopolymer.

PubMed

Golas, Ewa I; Czaplewski, Cezary

2014-09-01

This work theoretically investigates the mechanical properties of a novel silk-derived biopolymer as polymerized in silico from sericin and elastin-like monomers. Molecular Dynamics simulations and Steered Molecular Dynamics were the principal computational methods used, the latter of which applies an external force onto the system and thereby enables an observation of its response to stress. The models explored herein are single-molecule approximations, and primarily serve as tools in a rational design process for the preliminary assessment of properties in a new material candidate. © 2014 Wiley Periodicals, Inc.

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing.

PubMed

Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

2015-10-23

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation.

Computational approaches in the design of synthetic receptors - A review.

PubMed

Cowen, Todd; Karim, Kal; Piletsky, Sergey

2016-09-14

The rational design of molecularly imprinted polymers (MIPs) has been a major contributor to their reputation as "plastic antibodies" - high affinity robust synthetic receptors which can be optimally designed, and produced for a much reduced cost than their biological equivalents. Computational design has become a routine procedure in the production of MIPs, and has led to major advances in functional monomer screening, selection of cross-linker and solvent, optimisation of monomer(s)-template ratio and selectivity analysis. In this review the various computational methods will be discussed with reference to all the published relevant literature since the end of 2013, with each article described by the target molecule, the computational approach applied (whether molecular mechanics/molecular dynamics, semi-empirical quantum mechanics, ab initio quantum mechanics (Hartree-Fock, Møller-Plesset, etc.) or DFT) and the purpose for which they were used. Detailed analysis is given to novel techniques including analysis of polymer binding sites, the use of novel screening programs and simulations of MIP polymerisation reaction. The further advances in molecular modelling and computational design of synthetic receptors in particular will have serious impact on the future of nanotechnology and biotechnology, permitting the further translation of MIPs into the realms of analytics and medical technology. Copyright © 2016 Elsevier B.V. All rights reserved.

From transistor to trapped-ion computers for quantum chemistry.

PubMed

Yung, M-H; Casanova, J; Mezzacapo, A; McClean, J; Lamata, L; Aspuru-Guzik, A; Solano, E

2014-01-07

Over the last few decades, quantum chemistry has progressed through the development of computational methods based on modern digital computers. However, these methods can hardly fulfill the exponentially-growing resource requirements when applied to large quantum systems. As pointed out by Feynman, this restriction is intrinsic to all computational models based on classical physics. Recently, the rapid advancement of trapped-ion technologies has opened new possibilities for quantum control and quantum simulations. Here, we present an efficient toolkit that exploits both the internal and motional degrees of freedom of trapped ions for solving problems in quantum chemistry, including molecular electronic structure, molecular dynamics, and vibronic coupling. We focus on applications that go beyond the capacity of classical computers, but may be realizable on state-of-the-art trapped-ion systems. These results allow us to envision a new paradigm of quantum chemistry that shifts from the current transistor to a near-future trapped-ion-based technology.

From transistor to trapped-ion computers for quantum chemistry

PubMed Central

Yung, M.-H.; Casanova, J.; Mezzacapo, A.; McClean, J.; Lamata, L.; Aspuru-Guzik, A.; Solano, E.

2014-01-01

Over the last few decades, quantum chemistry has progressed through the development of computational methods based on modern digital computers. However, these methods can hardly fulfill the exponentially-growing resource requirements when applied to large quantum systems. As pointed out by Feynman, this restriction is intrinsic to all computational models based on classical physics. Recently, the rapid advancement of trapped-ion technologies has opened new possibilities for quantum control and quantum simulations. Here, we present an efficient toolkit that exploits both the internal and motional degrees of freedom of trapped ions for solving problems in quantum chemistry, including molecular electronic structure, molecular dynamics, and vibronic coupling. We focus on applications that go beyond the capacity of classical computers, but may be realizable on state-of-the-art trapped-ion systems. These results allow us to envision a new paradigm of quantum chemistry that shifts from the current transistor to a near-future trapped-ion-based technology. PMID:24395054

Accelerating MP2C dispersion corrections for dimers and molecular crystals

NASA Astrophysics Data System (ADS)

Huang, Yuanhang; Shao, Yihan; Beran, Gregory J. O.

2013-06-01

The MP2C dispersion correction of Pitonak and Hesselmann [J. Chem. Theory Comput. 6, 168 (2010)], 10.1021/ct9005882 substantially improves the performance of second-order Møller-Plesset perturbation theory for non-covalent interactions, albeit with non-trivial computational cost. Here, the MP2C correction is computed in a monomer-centered basis instead of a dimer-centered one. When applied to a single dimer MP2 calculation, this change accelerates the MP2C dispersion correction several-fold while introducing only trivial new errors. More significantly, in the context of fragment-based molecular crystal studies, combination of the new monomer basis algorithm and the periodic symmetry of the crystal reduces the cost of computing the dispersion correction by two orders of magnitude. This speed-up reduces the MP2C dispersion correction calculation from a significant computational expense to a negligible one in crystals like aspirin or oxalyl dihydrazide, without compromising accuracy.

Communication: A method to compute the transport coefficient of pure fluids diffusing through planar interfaces from equilibrium molecular dynamics simulations.

PubMed

Vermorel, Romain; Oulebsir, Fouad; Galliero, Guillaume

2017-09-14

The computation of diffusion coefficients in molecular systems ranks among the most useful applications of equilibrium molecular dynamics simulations. However, when dealing with the problem of fluid diffusion through vanishingly thin interfaces, classical techniques are not applicable. This is because the volume of space in which molecules diffuse is ill-defined. In such conditions, non-equilibrium techniques allow for the computation of transport coefficients per unit interface width, but their weak point lies in their inability to isolate the contribution of the different physical mechanisms prone to impact the flux of permeating molecules. In this work, we propose a simple and accurate method to compute the diffusional transport coefficient of a pure fluid through a planar interface from equilibrium molecular dynamics simulations, in the form of a diffusion coefficient per unit interface width. In order to demonstrate its validity and accuracy, we apply our method to the case study of a dilute gas diffusing through a smoothly repulsive single-layer porous solid. We believe this complementary technique can benefit to the interpretation of the results obtained on single-layer membranes by means of complex non-equilibrium methods.

Density functional theory calculation of refractive indices of liquid-forming silicon oil compounds

NASA Astrophysics Data System (ADS)

Lee, Sanghun; Park, Sung Soo; Hagelberg, Frank

2012-02-01

A combination of quantum chemical calculation and molecular dynamics simulation is applied to compute refractive indices of liquid-forming silicon oils. The densities of these species are obtained from molecular dynamics simulations based on the NPT ensemble while the molecular polarizabilities are evaluated by density functional theory. This procedure is shown to yield results well compatible with available experimental data, suggesting that it represents a robust and economic route for determining the refractive indices of liquid-forming organic complexes containing silicon.

Molecular Sticker Model Stimulation on Silicon for a Maximum Clique Problem

PubMed Central

Ning, Jianguo; Li, Yanmei; Yu, Wen

2015-01-01

Molecular computers (also called DNA computers), as an alternative to traditional electronic computers, are smaller in size but more energy efficient, and have massive parallel processing capacity. However, DNA computers may not outperform electronic computers owing to their higher error rates and some limitations of the biological laboratory. The stickers model, as a typical DNA-based computer, is computationally complete and universal, and can be viewed as a bit-vertically operating machine. This makes it attractive for silicon implementation. Inspired by the information processing method on the stickers computer, we propose a novel parallel computing model called DEM (DNA Electronic Computing Model) on System-on-a-Programmable-Chip (SOPC) architecture. Except for the significant difference in the computing medium—transistor chips rather than bio-molecules—the DEM works similarly to DNA computers in immense parallel information processing. Additionally, a plasma display panel (PDP) is used to show the change of solutions, and helps us directly see the distribution of assignments. The feasibility of the DEM is tested by applying it to compute a maximum clique problem (MCP) with eight vertices. Owing to the limited computing sources on SOPC architecture, the DEM could solve moderate-size problems in polynomial time. PMID:26075867

Long range Debye-Hückel correction for computation of grid-based electrostatic forces between biomacromolecules

PubMed Central

2014-01-01

Background Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulate solutions of bovine serum albumin and of hen egg white lysozyme. Results We found that the inclusion of the long-range electrostatic correction increased the accuracy of both the protein-protein interaction profiles and the protein diffusion coefficients at low ionic strength. Conclusions An advantage of this method is the low additional computational cost required to treat long-range electrostatic interactions in large biomacromolecular systems. Moreover, the implementation described here for BD simulations of protein solutions can also be applied in implicit solvent molecular dynamics simulations that make use of gridded interaction potentials. PMID:25045516

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

PubMed

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

2015-11-01

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

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

PubMed Central

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

2015-01-01

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

Computation of repetitions and regularities of biologically weighted sequences.

PubMed

Christodoulakis, M; Iliopoulos, C; Mouchard, L; Perdikuri, K; Tsakalidis, A; Tsichlas, K

2006-01-01

Biological weighted sequences are used extensively in molecular biology as profiles for protein families, in the representation of binding sites and often for the representation of sequences produced by a shotgun sequencing strategy. In this paper, we address three fundamental problems in the area of biologically weighted sequences: (i) computation of repetitions, (ii) pattern matching, and (iii) computation of regularities. Our algorithms can be used as basic building blocks for more sophisticated algorithms applied on weighted sequences.

Multipole Algorithms for Molecular Dynamics Simulation on High Performance Computers.

NASA Astrophysics Data System (ADS)

Elliott, William Dewey

1995-01-01

A fundamental problem in modeling large molecular systems with molecular dynamics (MD) simulations is the underlying N-body problem of computing the interactions between all pairs of N atoms. The simplest algorithm to compute pair-wise atomic interactions scales in runtime {cal O}(N^2), making it impractical for interesting biomolecular systems, which can contain millions of atoms. Recently, several algorithms have become available that solve the N-body problem by computing the effects of all pair-wise interactions while scaling in runtime less than {cal O}(N^2). One algorithm, which scales {cal O}(N) for a uniform distribution of particles, is called the Greengard-Rokhlin Fast Multipole Algorithm (FMA). This work describes an FMA-like algorithm called the Molecular Dynamics Multipole Algorithm (MDMA). The algorithm contains several features that are new to N-body algorithms. MDMA uses new, efficient series expansion equations to compute general 1/r^{n } potentials to arbitrary accuracy. In particular, the 1/r Coulomb potential and the 1/r^6 portion of the Lennard-Jones potential are implemented. The new equations are based on multivariate Taylor series expansions. In addition, MDMA uses a cell-to-cell interaction region of cells that is closely tied to worst case error bounds. The worst case error bounds for MDMA are derived in this work also. These bounds apply to other multipole algorithms as well. Several implementation enhancements are described which apply to MDMA as well as other N-body algorithms such as FMA and tree codes. The mathematics of the cell -to-cell interactions are converted to the Fourier domain for reduced operation count and faster computation. A relative indexing scheme was devised to locate cells in the interaction region which allows efficient pre-computation of redundant information and prestorage of much of the cell-to-cell interaction. Also, MDMA was integrated into the MD program SIgMA to demonstrate the performance of the program over several simulation timesteps. One MD application described here highlights the utility of including long range contributions to Lennard-Jones potential in constant pressure simulations. Another application shows the time dependence of long range forces in a multiple time step MD simulation.

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.

A Parallel Biological Optimization Algorithm to Solve the Unbalanced Assignment Problem Based on DNA Molecular Computing

PubMed Central

Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian

2015-01-01

The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m < n), such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP) complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. PMID:26512650

Numerical analysis of the photo-injection time-of-flight curves in molecularly doped polymers

NASA Astrophysics Data System (ADS)

Tyutnev, A. P.; Ikhsanov, R. Sh.; Saenko, V. S.; Nikerov, D. V.

2018-03-01

We have performed numerical analysis of the charge carrier transport in a specific molecularly doped polymer using the multiple trapping model. The computations covered a wide range of applied electric fields, temperatures and most importantly, of the initial energies of photo injected one-sign carriers (in our case, holes). Special attention has been given to comparison of time of flight curves measured by the photo-injection and radiation-induced techniques which has led to a problematic situation concerning an interpretation of the experimental data. Computational results have been compared with both analytical and experimental results available in literature.

Evaluation of synthetic linear motor-molecule actuation energetics

PubMed Central

Brough, Branden; Northrop, Brian H.; Schmidt, Jacob J.; Tseng, Hsian-Rong; Houk, Kendall N.; Stoddart, J. Fraser; Ho, Chih-Ming

2006-01-01

By applying atomic force microscope (AFM)-based force spectroscopy together with computational modeling in the form of molecular force-field simulations, we have determined quantitatively the actuation energetics of a synthetic motor-molecule. This multidisciplinary approach was performed on specifically designed, bistable, redox-controllable [2]rotaxanes to probe the steric and electrostatic interactions that dictate their mechanical switching at the single-molecule level. The fusion of experimental force spectroscopy and theoretical computational modeling has revealed that the repulsive electrostatic interaction, which is responsible for the molecular actuation, is as high as 65 kcal·mol−1, a result that is supported by ab initio calculations. PMID:16735470

Quantum Fragment Based ab Initio Molecular Dynamics for Proteins.

PubMed

Liu, Jinfeng; Zhu, Tong; Wang, Xianwei; He, Xiao; Zhang, John Z H

2015-12-08

Developing ab initio molecular dynamics (AIMD) methods for practical application in protein dynamics is of significant interest. Due to the large size of biomolecules, applying standard quantum chemical methods to compute energies for dynamic simulation is computationally prohibitive. In this work, a fragment based ab initio molecular dynamics approach is presented for practical application in protein dynamics study. In this approach, the energy and forces of the protein are calculated by a recently developed electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method. For simulation in explicit solvent, mechanical embedding is introduced to treat protein interaction with explicit water molecules. This AIMD approach has been applied to MD simulations of a small benchmark protein Trpcage (with 20 residues and 304 atoms) in both the gas phase and in solution. Comparison to the simulation result using the AMBER force field shows that the AIMD gives a more stable protein structure in the simulation, indicating that quantum chemical energy is more reliable. Importantly, the present fragment-based AIMD simulation captures quantum effects including electrostatic polarization and charge transfer that are missing in standard classical MD simulations. The current approach is linear-scaling, trivially parallel, and applicable to performing the AIMD simulation of proteins with a large size.

ChemoPy: freely available python package for computational biology and chemoinformatics.

PubMed

Cao, Dong-Sheng; Xu, Qing-Song; Hu, Qian-Nan; Liang, Yi-Zeng

2013-04-15

Molecular representation for small molecules has been routinely used in QSAR/SAR, virtual screening, database search, ranking, drug ADME/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently. The python package, ChemoPy, is freely available via http://code.google.com/p/pychem/downloads/list, and it runs on Linux and MS-Windows. Supplementary data are available at Bioinformatics online.

Computational Enzymology and Organophosphorus Degrading Enzymes: Promising Approaches Toward Remediation Technologies of Warfare Agents and Pesticides

DOE PAGES

Ramalho, Teodorico C.; DeCastro, Alexandre A.; Silva, Daniela R.; ...

2015-08-26

The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and helpmore » in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.« less

Computational Enzymology and Organophosphorus Degrading Enzymes: Promising Approaches Toward Remediation Technologies of Warfare Agents and Pesticides

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

Ramalho, Teodorico C.; DeCastro, Alexandre A.; Silva, Daniela R.

The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and helpmore » in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.« less

Reticular synthesis of porous molecular 1D nanotubes and 3D networks.

PubMed

Slater, A G; Little, M A; Pulido, A; Chong, S Y; Holden, D; Chen, L; Morgan, C; Wu, X; Cheng, G; Clowes, R; Briggs, M E; Hasell, T; Jelfs, K E; Day, G M; Cooper, A I

2017-01-01

Synthetic control over pore size and pore connectivity is the crowning achievement for porous metal-organic frameworks (MOFs). The same level of control has not been achieved for molecular crystals, which are not defined by strong, directional intermolecular coordination bonds. Hence, molecular crystallization is inherently less controllable than framework crystallization, and there are fewer examples of 'reticular synthesis', in which multiple building blocks can be assembled according to a common assembly motif. Here we apply a chiral recognition strategy to a new family of tubular covalent cages to create both 1D porous nanotubes and 3D diamondoid pillared porous networks. The diamondoid networks are analogous to MOFs prepared from tetrahedral metal nodes and linear ditopic organic linkers. The crystal structures can be rationalized by computational lattice-energy searches, which provide an in silico screening method to evaluate candidate molecular building blocks. These results are a blueprint for applying the 'node and strut' principles of reticular synthesis to molecular crystals.

Reticular synthesis of porous molecular 1D nanotubes and 3D networks

NASA Astrophysics Data System (ADS)

Slater, A. G.; Little, M. A.; Pulido, A.; Chong, S. Y.; Holden, D.; Chen, L.; Morgan, C.; Wu, X.; Cheng, G.; Clowes, R.; Briggs, M. E.; Hasell, T.; Jelfs, K. E.; Day, G. M.; Cooper, A. I.

2017-01-01

Synthetic control over pore size and pore connectivity is the crowning achievement for porous metal-organic frameworks (MOFs). The same level of control has not been achieved for molecular crystals, which are not defined by strong, directional intermolecular coordination bonds. Hence, molecular crystallization is inherently less controllable than framework crystallization, and there are fewer examples of 'reticular synthesis', in which multiple building blocks can be assembled according to a common assembly motif. Here we apply a chiral recognition strategy to a new family of tubular covalent cages to create both 1D porous nanotubes and 3D diamondoid pillared porous networks. The diamondoid networks are analogous to MOFs prepared from tetrahedral metal nodes and linear ditopic organic linkers. The crystal structures can be rationalized by computational lattice-energy searches, which provide an in silico screening method to evaluate candidate molecular building blocks. These results are a blueprint for applying the 'node and strut' principles of reticular synthesis to molecular crystals.

Orchestration of Molecular Information through Higher Order Chemical Recognition

NASA Astrophysics Data System (ADS)

Frezza, Brian M.

Broadly defined, higher order chemical recognition is the process whereby discrete chemical building blocks capable of specifically binding to cognate moieties are covalently linked into oligomeric chains. These chains, or sequences, are then able to recognize and bind to their cognate sequences with a high degree of cooperativity. Principally speaking, DNA and RNA are the most readily obtained examples of this chemical phenomenon, and function via Watson-Crick cognate pairing: guanine pairs with cytosine and adenine with thymine (DNA) or uracil (RNA), in an anti-parallel manner. While the theoretical principles, techniques, and equations derived herein apply generally to any higher-order chemical recognition system, in practice we utilize DNA oligomers as a model-building material to experimentally investigate and validate our hypotheses. Historically, general purpose information processing has been a task limited to semiconductor electronics. Molecular computing on the other hand has been limited to ad hoc approaches designed to solve highly specific and unique computation problems, often involving components or techniques that cannot be applied generally in a manner suitable for precise and predictable engineering. Herein, we provide a fundamental framework for harnessing high-order recognition in a modular and programmable fashion to synthesize molecular information process networks of arbitrary construction and complexity. This document provides a solid foundation for routinely embedding computational capability into chemical and biological systems where semiconductor electronics are unsuitable for practical application.

Molecular dynamics simulations through GPU video games technologies

PubMed Central

Loukatou, Styliani; Papageorgiou, Louis; Fakourelis, Paraskevas; Filntisi, Arianna; Polychronidou, Eleftheria; Bassis, Ioannis; Megalooikonomou, Vasileios; Makałowski, Wojciech; Vlachakis, Dimitrios; Kossida, Sophia

2016-01-01

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations. PMID:27525251

Ab Initio Infrared and Raman Spectra.

DTIC Science & Technology

1982-08-01

equilibrium and non -equilibrium systems. It b pointed out that a similar ab !ni- te QFC molecular dynamic approach could be used to compute other types of...applied to -2- equilibrium and non -equilibrium system. It is pointed out that a similar oh im- ib QFCT molecular dynamic approach could be used to...desire to be able to experimentally identify and understand transient species or states (such as those existing during the course of chemical

Computational Molecular Modeling Methods Applied to Screening for Toxicity

EPA Science Inventory

The risk to human health and the environment of chemicals that result from human activity often must be evaluated when relevant elements of the preferred data set are unavailable. Therefore, strategies are needed that estimate this information and prioritize the outstanding data...

High-throughput screening, predictive modeling and computational embryology - Abstract

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...

QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computations.

PubMed

Valdés-Martiní, José R; Marrero-Ponce, Yovani; García-Jacas, César R; Martinez-Mayorga, Karina; Barigye, Stephen J; Vaz d'Almeida, Yasser Silveira; Pham-The, Hai; Pérez-Giménez, Facundo; Morell, Carlos A

2017-06-07

In previous reports, Marrero-Ponce et al. proposed algebraic formalisms for characterizing topological (2D) and chiral (2.5D) molecular features through atom- and bond-based ToMoCoMD-CARDD (acronym for Topological Molecular Computational Design-Computer Aided Rational Drug Design) molecular descriptors. These MDs codify molecular information based on the bilinear, quadratic and linear algebraic forms and the graph-theoretical electronic-density and edge-adjacency matrices in order to consider atom- and bond-based relations, respectively. These MDs have been successfully applied in the screening of chemical compounds of different therapeutic applications ranging from antimalarials, antibacterials, tyrosinase inhibitors and so on. To compute these MDs, a computational program with the same name was initially developed. However, this in house software barely offered the functionalities required in contemporary molecular modeling tasks, in addition to the inherent limitations that made its usability impractical. Therefore, the present manuscript introduces the QuBiLS-MAS (acronym for Quadratic, Bilinear and N-Linear mapS based on graph-theoretic electronic-density Matrices and Atomic weightingS) software designed to compute topological (0-2.5D) molecular descriptors based on bilinear, quadratic and linear algebraic forms for atom- and bond-based relations. The QuBiLS-MAS module was designed as standalone software, in which extensions and generalizations of the former ToMoCoMD-CARDD 2D-algebraic indices are implemented, considering the following aspects: (a) two new matrix normalization approaches based on double-stochastic and mutual probability formalisms; (b) topological constraints (cut-offs) to take into account particular inter-atomic relations; (c) six additional atomic properties to be used as weighting schemes in the calculation of the molecular vectors; (d) four new local-fragments to consider molecular regions of interest; (e) number of lone-pair electrons in chemical structure defined by diagonal coefficients in matrix representations; and (f) several aggregation operators (invariants) applied over atom/bond-level descriptors in order to compute global indices. This software permits the parallel computation of the indices, contains a batch processing module and data curation functionalities. This program was developed in Java v1.7 using the Chemistry Development Kit library (version 1.4.19). The QuBiLS-MAS software consists of two components: a desktop interface (GUI) and an API library allowing for the easy integration of the latter in chemoinformatics applications. The relevance of the novel extensions and generalizations implemented in this software is demonstrated through three studies. Firstly, a comparative Shannon's entropy based variability study for the proposed QuBiLS-MAS and the DRAGON indices demonstrates superior performance for the former. A principal component analysis reveals that the QuBiLS-MAS approach captures chemical information orthogonal to that codified by the DRAGON descriptors. Lastly, a QSAR study for the binding affinity to the corticosteroid-binding globulin using Cramer's steroid dataset is carried out. From these analyses, it is revealed that the QuBiLS-MAS approach for atom-pair relations yields similar-to-superior performance with regard to other QSAR methodologies reported in the literature. Therefore, the QuBiLS-MAS approach constitutes a useful tool for the diversity analysis of chemical compound datasets and high-throughput screening of structure-activity data.

Path Integral Computation of Quantum Free Energy Differences Due to Alchemical Transformations Involving Mass and Potential.

PubMed

Pérez, Alejandro; von Lilienfeld, O Anatole

2011-08-09

Thermodynamic integration, perturbation theory, and λ-dynamics methods were applied to path integral molecular dynamics calculations to investigate free energy differences due to "alchemical" transformations. Several estimators were formulated to compute free energy differences in solvable model systems undergoing changes in mass and/or potential. Linear and nonlinear alchemical interpolations were used for the thermodynamic integration. We find improved convergence for the virial estimators, as well as for the thermodynamic integration over nonlinear interpolation paths. Numerical results for the perturbative treatment of changes in mass and electric field strength in model systems are presented. We used thermodynamic integration in ab initio path integral molecular dynamics to compute the quantum free energy difference of the isotope transformation in the Zundel cation. The performance of different free energy methods is discussed.

ISMB 2016 offers outstanding science, networking, and celebration

PubMed Central

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas. PMID:27347392

ISMB 2016 offers outstanding science, networking, and celebration.

PubMed

Fogg, Christiana

2016-01-01

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community.  ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas.

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).

A machine learning approach to computer-aided molecular design

NASA Astrophysics Data System (ADS)

Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo

1991-12-01

Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.

Brønsted acidity of protic ionic liquids: a modern ab initio valence bond theory perspective.

PubMed

Patil, Amol Baliram; Mahadeo Bhanage, Bhalchandra

2016-09-21

Room temperature ionic liquids (ILs), especially protic ionic liquids (PILs), are used in many areas of the chemical sciences. Ionicity, the extent of proton transfer, is a key parameter which determines many physicochemical properties and in turn the suitability of PILs for various applications. The spectrum of computational chemistry techniques applied to investigate ionic liquids includes classical molecular dynamics, Monte Carlo simulations, ab initio molecular dynamics, Density Functional Theory (DFT), CCSD(t) etc. At the other end of the spectrum is another computational approach: modern ab initio Valence Bond Theory (VBT). VBT differs from molecular orbital theory based methods in the expression of the molecular wave function. The molecular wave function in the valence bond ansatz is expressed as a linear combination of valence bond structures. These structures include covalent and ionic structures explicitly. Modern ab initio valence bond theory calculations of representative primary and tertiary ammonium protic ionic liquids indicate that modern ab initio valence bond theory can be employed to assess the acidity and ionicity of protic ionic liquids a priori.

Applications of computational models to better understand microvascular remodelling: a focus on biomechanical integration across scales

PubMed Central

Murfee, Walter L.; Sweat, Richard S.; Tsubota, Ken-ichi; Gabhann, Feilim Mac; Khismatullin, Damir; Peirce, Shayn M.

2015-01-01

Microvascular network remodelling is a common denominator for multiple pathologies and involves both angiogenesis, defined as the sprouting of new capillaries, and network patterning associated with the organization and connectivity of existing vessels. Much of what we know about microvascular remodelling at the network, cellular and molecular scales has been derived from reductionist biological experiments, yet what happens when the experiments provide incomplete (or only qualitative) information? This review will emphasize the value of applying computational approaches to advance our understanding of the underlying mechanisms and effects of microvascular remodelling. Examples of individual computational models applied to each of the scales will highlight the potential of answering specific questions that cannot be answered using typical biological experimentation alone. Looking into the future, we will also identify the needs and challenges associated with integrating computational models across scales. PMID:25844149

Kernel approach to molecular similarity based on iterative graph similarity.

PubMed

Rupp, Matthias; Proschak, Ewgenij; Schneider, Gisbert

2007-01-01

Similarity measures for molecules are of basic importance in chemical, biological, and pharmaceutical applications. We introduce a molecular similarity measure defined directly on the annotated molecular graph, based on iterative graph similarity and optimal assignments. We give an iterative algorithm for the computation of the proposed molecular similarity measure, prove its convergence and the uniqueness of the solution, and provide an upper bound on the required number of iterations necessary to achieve a desired precision. Empirical evidence for the positive semidefiniteness of certain parametrizations of our function is presented. We evaluated our molecular similarity measure by using it as a kernel in support vector machine classification and regression applied to several pharmaceutical and toxicological data sets, with encouraging results.

Computer Simulations of Intrinsically Disordered Proteins

NASA Astrophysics Data System (ADS)

Chong, Song-Ho; Chatterjee, Prathit; Ham, Sihyun

2017-05-01

The investigation of intrinsically disordered proteins (IDPs) is a new frontier in structural and molecular biology that requires a new paradigm to connect structural disorder to function. Molecular dynamics simulations and statistical thermodynamics potentially offer ideal tools for atomic-level characterizations and thermodynamic descriptions of this fascinating class of proteins that will complement experimental studies. However, IDPs display sensitivity to inaccuracies in the underlying molecular mechanics force fields. Thus, achieving an accurate structural characterization of IDPs via simulations is a challenge. It is also daunting to perform a configuration-space integration over heterogeneous structural ensembles sampled by IDPs to extract, in particular, protein configurational entropy. In this review, we summarize recent efforts devoted to the development of force fields and the critical evaluations of their performance when applied to IDPs. We also survey recent advances in computational methods for protein configurational entropy that aim to provide a thermodynamic link between structural disorder and protein activity.

Hybrid Steered Molecular Dynamics-Docking: An Efficient Solution to the Problem of Ranking Inhibitor Affinities Against a Flexible Drug Target.

PubMed

Whalen, Katie L; Chang, Kevin M; Spies, M Ashley

2011-05-16

Existing techniques which attempt to predict the affinity of protein-ligand interactions have demonstrated a direct relationship between computational cost and prediction accuracy. We present here the first application of a hybrid ensemble docking and steered molecular dynamics scheme (with a minimized computational cost), which achieves a binding affinity rank-ordering of ligands with a Spearman correlation coefficient of 0.79 and an RMS error of 0.7 kcal/mol. The scheme, termed Flexible Enzyme Receptor Method by Steered Molecular Dynamics (FERM-SMD), is applied to an in-house collection of 17 validated ligands of glutamate racemase. The resulting improved accuracy in affinity prediction allows elucidation of the key structural components of a heretofore unreported glutamate racemase inhibitor (K(i) = 9 µM), a promising new lead in the development of antibacterial therapeutics.

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.

Computational Enzymology and Organophosphorus Degrading Enzymes: Promising Approaches Toward Remediation Technologies of Warfare Agents and Pesticides.

PubMed

Ramalho, Teodorico C; de Castro, Alexandre A; Silva, Daniela R; Silva, Maria Cristina; Franca, Tanos C C; Bennion, Brian J; Kuca, Kamil

2016-01-01

The re-emergence of chemical weapons as a global threat in hands of terrorist groups, together with an increasing number of pesticides intoxications and environmental contaminations worldwide, has called the attention of the scientific community for the need of improvement in the technologies for detoxification of organophosphorus (OP) compounds. A compelling strategy is the use of bioremediation by enzymes that are able to hydrolyze these molecules to harmless chemical species. Several enzymes have been studied and engineered for this purpose. However, their mechanisms of action are not well understood. Theoretical investigations may help elucidate important aspects of these mechanisms and help in the development of more efficient bio-remediators. In this review, we point out the major contributions of computational methodologies applied to enzyme based detoxification of OPs. Furthermore, we highlight the use of PTE, PON, DFP, and BuChE as enzymes used in OP detoxification process and how computational tools such as molecular docking, molecular dynamics simulations and combined quantum mechanical/molecular mechanics have and will continue to contribute to this very important area of research.

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

Bacterial computing: a form of natural computing and its applications.

PubMed

Lahoz-Beltra, Rafael; Navarro, Jorge; Marijuán, Pedro C

2014-01-01

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular "learning" along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems.

Bacterial computing: a form of natural computing and its applications

PubMed Central

Lahoz-Beltra, Rafael; Navarro, Jorge; Marijuán, Pedro C.

2014-01-01

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular “learning” along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems. PMID:24723912

An interactive computer lab of the galvanic cell for students in biochemistry.

PubMed

Ahlstrand, Emma; Buetti-Dinh, Antoine; Friedman, Ran

2018-01-01

We describe an interactive module that can be used to teach basic concepts in electrochemistry and thermodynamics to first year natural science students. The module is used together with an experimental laboratory and improves the students' understanding of thermodynamic quantities such as Δ r G, Δ r H, and Δ r S that are calculated but not directly measured in the lab. We also discuss how new technologies can substitute some parts of experimental chemistry courses, and improve accessibility to course material. Cloud computing platforms such as CoCalc facilitate the distribution of computer codes and allow students to access and apply interactive course tools beyond the course's scope. Despite some limitations imposed by cloud computing, the students appreciated the approach and the enhanced opportunities to discuss study questions with their classmates and instructor as facilitated by the interactive tools. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):58-65, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

Adaptive frozen orbital treatment for the fragment molecular orbital method combined with density-functional tight-binding

NASA Astrophysics Data System (ADS)

Nishimoto, Yoshio; Fedorov, Dmitri G.

2018-02-01

The exactly analytic gradient is derived and implemented for the fragment molecular orbital (FMO) method combined with density-functional tight-binding (DFTB) using adaptive frozen orbitals. The response contributions which arise from freezing detached molecular orbitals on the border between fragments are computed by solving Z-vector equations. The accuracy of the energy, its gradient, and optimized structures is verified on a set of representative inorganic materials and polypeptides. FMO-DFTB is applied to optimize the structure of a silicon nano-wire, and the results are compared to those of density functional theory and experiment. FMO accelerates the DFTB calculation of a boron nitride nano-ring with 7872 atoms by a factor of 406. Molecular dynamics simulations using FMO-DFTB applied to a 10.7 μm chain of boron nitride nano-rings, consisting of about 1.2 × 106 atoms, reveal the rippling and twisting of nano-rings at room temperature.

A DAG Scheduling Scheme on Heterogeneous Computing Systems Using Tuple-Based Chemical Reaction Optimization

PubMed Central

Jiang, Yuyi; Shao, Zhiqing; Guo, Yi

2014-01-01

A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems. PMID:25143977

A DAG scheduling scheme on heterogeneous computing systems using tuple-based chemical reaction optimization.

PubMed

Jiang, Yuyi; Shao, Zhiqing; Guo, Yi

2014-01-01

A complex computing problem can be solved efficiently on a system with multiple computing nodes by dividing its implementation code into several parallel processing modules or tasks that can be formulated as directed acyclic graph (DAG) problems. The DAG jobs may be mapped to and scheduled on the computing nodes to minimize the total execution time. Searching an optimal DAG scheduling solution is considered to be NP-complete. This paper proposed a tuple molecular structure-based chemical reaction optimization (TMSCRO) method for DAG scheduling on heterogeneous computing systems, based on a very recently proposed metaheuristic method, chemical reaction optimization (CRO). Comparing with other CRO-based algorithms for DAG scheduling, the design of tuple reaction molecular structure and four elementary reaction operators of TMSCRO is more reasonable. TMSCRO also applies the concept of constrained critical paths (CCPs), constrained-critical-path directed acyclic graph (CCPDAG) and super molecule for accelerating convergence. In this paper, we have also conducted simulation experiments to verify the effectiveness and efficiency of TMSCRO upon a large set of randomly generated graphs and the graphs for real world problems.

Hardware accelerator for molecular dynamics: MDGRAPE-2

NASA Astrophysics Data System (ADS)

Susukita, Ryutaro; Ebisuzaki, Toshikazu; Elmegreen, Bruce G.; Furusawa, Hideaki; Kato, Kenya; Kawai, Atsushi; Kobayashi, Yoshinao; Koishi, Takahiro; McNiven, Geoffrey D.; Narumi, Tetsu; Yasuoka, Kenji

2003-10-01

We developed MDGRAPE-2, a hardware accelerator that calculates forces at high speed in molecular dynamics (MD) simulations. MDGRAPE-2 is connected to a PC or a workstation as an extension board. The sustained performance of one MDGRAPE-2 board is 15 Gflops, roughly equivalent to the peak performance of the fastest supercomputer processing element. One board is able to calculate all forces between 10 000 particles in 0.28 s (i.e. 310000 time steps per day). If 16 boards are connected to one computer and operated in parallel, this calculation speed becomes ˜10 times faster. In addition to MD, MDGRAPE-2 can be applied to gravitational N-body simulations, the vortex method and smoothed particle hydrodynamics in computational fluid dynamics.

Molecular computation: RNA solutions to chess problems.

PubMed

Faulhammer, D; Cukras, A R; Lipton, R J; Landweber, L F

2000-02-15

We have expanded the field of "DNA computers" to RNA and present a general approach for the solution of satisfiability problems. As an example, we consider a variant of the "Knight problem," which asks generally what configurations of knights can one place on an n x n chess board such that no knight is attacking any other knight on the board. Using specific ribonuclease digestion to manipulate strands of a 10-bit binary RNA library, we developed a molecular algorithm and applied it to a 3 x 3 chessboard as a 9-bit instance of this problem. Here, the nine spaces on the board correspond to nine "bits" or placeholders in a combinatorial RNA library. We recovered a set of "winning" molecules that describe solutions to this problem.

Mono-, di-, and tri- tert-butyl ethers of glycerol . A molecular spectroscopic study

NASA Astrophysics Data System (ADS)

Jamróz, Małgorzata E.; Jarosz, Małgorzata; Witowska-Jarosz, Janina; Bednarek, Elżbieta; Tęcza, Witold; Jamróz, Michał H.; Dobrowolski, Jan Cz.; Kijeński, Jacek

2007-07-01

MS, NMR, IR and Raman molecular spectroscopy techniques were applied to characterize 3- tert-butoxy-propane-1,2-diol, 1,3-di- tert-butoxy-propan-2-ol, and 1,2,3-tri- tert-butoxy-propane. These ethers are the main products of glycerol etherification reaction and are excellent oxygen additives for diesel fuel. Computational DFT/ B3LYP/6-31G ** studies were performed to support and rationalize both vibrational spectroscopy analysis and the isomer ratio.

Nanomicrointerface to read molecular potentials into current-voltage based electronics.

PubMed

Rangel, Norma L; Seminario, Jorge M

2008-03-21

Molecular potentials are unreadable and unaddressable by any present technology. It is known that the proper assembly of molecules can implement an entire numerical processing system based on digital or even analogical computation. In turn, the outputs of this molecular processing unit need to be amplified in order to be useful. We have developed a nanomicrointerface to read information encoded in molecular level potentials and to amplify this signal to microelectronic levels. The amplification is performed by making the output molecular potential slightly twist the torsional angle between two rings of a pyridazine, 3,6-bis(phenylethynyl) (aza-OPE) molecule, requiring only fractions of kcal/mol energies. In addition, even if the signal from the molecular potentials is not enough to turn the ring or even if the angles are the same for different combinations of outputs, still the current output yields results that resemble the device as a field effect transistor, providing the possibility to reduce channel lengths to the range of just 1 or 2 nm. The slight change in the torsional angle yields readable changes in the current through the aza-OPE biased by an external applied voltage. Using ab initio methods, we computationally demonstrate the amplification of molecular potential signals into currents that can be read by standard circuits.

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP),

Communication: Influence of external static and alternating electric fields on water from long-time non-equilibrium ab initio molecular dynamics

NASA Astrophysics Data System (ADS)

Futera, Zdenek; English, Niall J.

2017-07-01

The response of water to externally applied electric fields is of central relevance in the modern world, where many extraneous electric fields are ubiquitous. Historically, the application of external fields in non-equilibrium molecular dynamics has been restricted, by and large, to relatively inexpensive, more or less sophisticated, empirical models. Here, we report long-time non-equilibrium ab initio molecular dynamics in both static and oscillating (time-dependent) external electric fields, therefore opening up a new vista in rigorous studies of electric-field effects on dynamical systems with the full arsenal of electronic-structure methods. In so doing, we apply this to liquid water with state-of-the-art non-local treatment of dispersion, and we compute a range of field effects on structural and dynamical properties, such as diffusivities and hydrogen-bond kinetics.

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations

PubMed Central

Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro

2015-01-01

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic. PMID:26177039

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations.

PubMed

Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro

2015-01-01

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.

A novel integrated framework and improved methodology of computer-aided drug design.

PubMed

Chen, Calvin Yu-Chian

2013-01-01

Computer-aided drug design (CADD) is a critical initiating step of drug development, but a single model capable of covering all designing aspects remains to be elucidated. Hence, we developed a drug design modeling framework that integrates multiple approaches, including machine learning based quantitative structure-activity relationship (QSAR) analysis, 3D-QSAR, Bayesian network, pharmacophore modeling, and structure-based docking algorithm. Restrictions for each model were defined for improved individual and overall accuracy. An integration method was applied to join the results from each model to minimize bias and errors. In addition, the integrated model adopts both static and dynamic analysis to validate the intermolecular stabilities of the receptor-ligand conformation. The proposed protocol was applied to identifying HER2 inhibitors from traditional Chinese medicine (TCM) as an example for validating our new protocol. Eight potent leads were identified from six TCM sources. A joint validation system comprised of comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular dynamics simulation further characterized the candidates into three potential binding conformations and validated the binding stability of each protein-ligand complex. The ligand pathway was also performed to predict the ligand "in" and "exit" from the binding site. In summary, we propose a novel systematic CADD methodology for the identification, analysis, and characterization of drug-like candidates.

Incorporation of local structure into kriging models for the prediction of atomistic properties in the water decamer.

PubMed

Davie, Stuart J; Di Pasquale, Nicodemo; Popelier, Paul L A

2016-10-15

Machine learning algorithms have been demonstrated to predict atomistic properties approaching the accuracy of quantum chemical calculations at significantly less computational cost. Difficulties arise, however, when attempting to apply these techniques to large systems, or systems possessing excessive conformational freedom. In this article, the machine learning method kriging is applied to predict both the intra-atomic and interatomic energies, as well as the electrostatic multipole moments, of the atoms of a water molecule at the center of a 10 water molecule (decamer) cluster. Unlike previous work, where the properties of small water clusters were predicted using a molecular local frame, and where training set inputs (features) were based on atomic index, a variety of feature definitions and coordinate frames are considered here to increase prediction accuracy. It is shown that, for a water molecule at the center of a decamer, no single method of defining features or coordinate schemes is optimal for every property. However, explicitly accounting for the structure of the first solvation shell in the definition of the features of the kriging training set, and centring the coordinate frame on the atom-of-interest will, in general, return better predictions than models that apply the standard methods of feature definition, or a molecular coordinate frame. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Combining molecular dynamics and an electrodiffusion model to calculate ion channel conductance

NASA Astrophysics Data System (ADS)

Wilson, Michael A.; Nguyen, Thuy Hien; Pohorille, Andrew

2014-12-01

Establishing the relation between the structures and functions of protein ion channels, which are protein assemblies that facilitate transmembrane ion transport through water-filled pores, is at the forefront of biological and medical sciences. A reliable way to determine whether our understanding of this relation is satisfactory is to reproduce the measured ionic conductance over a broad range of applied voltages. This can be done in molecular dynamics simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. Since this approach is computationally very expensive we develop a markedly more efficient alternative in which molecular dynamics is combined with an electrodiffusion equation. This alternative approach applies if steady-state ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. The theory refers only to line densities of ions in the channel and, therefore, avoids ambiguities related to determining the surface area of the channel near its endpoints or other procedures connecting the line and bulk ion densities. We apply the theory to a simple, model system based on the trichotoxin channel. We test the assumptions of the electrodiffusion equation, and determine the precision and consistency of the calculated conductance. We demonstrate that it is possible to calculate current/voltage dependence and accurately reconstruct the underlying (equilibrium) free energy profile, all from molecular dynamics simulations at a single voltage. The approach developed here applies to other channels that satisfy the conditions of the electrodiffusion equation.

Molecular Risk Factors for Schizophrenia.

PubMed

Modai, Shira; Shomron, Noam

2016-03-01

Schizophrenia (SZ) is a complex and strongly heritable mental disorder, which is also associated with developmental-environmental triggers. As opposed to most diagnosable diseases (yet similar to other mental disorders), SZ diagnosis is commonly based on psychiatric evaluations. Recently, large-scale genetic and epigenetic approaches have been applied to SZ research with the goal of potentially improving diagnosis. Increased computational analyses and applied statistical algorithms may shed some light on the complex genetic and epigenetic pathways contributing to SZ pathogenesis. This review discusses the latest advances in molecular risk factors and diagnostics for SZ. Approaches such as these may lead to a more accurate definition of SZ and assist in creating extended and reliable clinical diagnoses with the potential for personalized treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Statistical Inference for Big Data Problems in Molecular Biophysics

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

Ramanathan, Arvind; Savol, Andrej; Burger, Virginia

2012-01-01

We highlight the role of statistical inference techniques in providing biological insights from analyzing long time-scale molecular simulation data. Technologi- cal and algorithmic improvements in computation have brought molecular simu- lations to the forefront of techniques applied to investigating the basis of living systems. While these longer simulations, increasingly complex reaching petabyte scales presently, promise a detailed view into microscopic behavior, teasing out the important information has now become a true challenge on its own. Mining this data for important patterns is critical to automating therapeutic intervention discovery, improving protein design, and fundamentally understanding the mech- anistic basis of cellularmore » homeostasis.« less

Bennett clocking of quantum-dot cellular automata and the limits to binary logic scaling.

PubMed

Lent, Craig S; Liu, Mo; Lu, Yuhui

2006-08-28

We examine power dissipation in different clocking schemes for molecular quantum-dot cellular automata (QCA) circuits. 'Landauer clocking' involves the adiabatic transition of a molecular cell from the null state to an active state carrying data. Cell layout creates devices which allow data in cells to interact and thereby perform useful computation. We perform direct solutions of the equation of motion for the system in contact with the thermal environment and see that Landauer's Principle applies: one must dissipate an energy of at least k(B)T per bit only when the information is erased. The ideas of Bennett can be applied to keep copies of the bit information by echoing inputs to outputs, thus embedding any logically irreversible circuit in a logically reversible circuit, at the cost of added circuit complexity. A promising alternative which we term 'Bennett clocking' requires only altering the timing of the clocking signals so that bit information is simply held in place by the clock until a computational block is complete, then erased in the reverse order of computation. This approach results in ultralow power dissipation without additional circuit complexity. These results offer a concrete example in which to consider recent claims regarding the fundamental limits of binary logic scaling.

Bennett clocking of quantum-dot cellular automata and the limits to binary logic scaling

NASA Astrophysics Data System (ADS)

Lent, Craig S.; Liu, Mo; Lu, Yuhui

2006-08-01

We examine power dissipation in different clocking schemes for molecular quantum-dot cellular automata (QCA) circuits. 'Landauer clocking' involves the adiabatic transition of a molecular cell from the null state to an active state carrying data. Cell layout creates devices which allow data in cells to interact and thereby perform useful computation. We perform direct solutions of the equation of motion for the system in contact with the thermal environment and see that Landauer's Principle applies: one must dissipate an energy of at least kBT per bit only when the information is erased. The ideas of Bennett can be applied to keep copies of the bit information by echoing inputs to outputs, thus embedding any logically irreversible circuit in a logically reversible circuit, at the cost of added circuit complexity. A promising alternative which we term 'Bennett clocking' requires only altering the timing of the clocking signals so that bit information is simply held in place by the clock until a computational block is complete, then erased in the reverse order of computation. This approach results in ultralow power dissipation without additional circuit complexity. These results offer a concrete example in which to consider recent claims regarding the fundamental limits of binary logic scaling.

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

PubMed

Yang, Guang-Fu; Huang, Xiaoqin

2006-01-01

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

A Model Structure for the Heterodimer apoA-IMilano–apoA-II Supports Its Peculiar Susceptibility to Proteolysis

PubMed Central

Rocco, Alessandro Guerini; Mollica, Luca; Gianazza, Elisabetta; Calabresi, Laura; Franceschini, Guido; Sirtori, Cesare R.; Eberini, Ivano

2006-01-01

In this study, we propose a structure for the heterodimer between apolipoprotein A-IMilano and apolipoprotein A-II (apoA-IM–apoA-II) in a synthetic high-density lipoprotein (HDL) containing L-α-palmitoyloleoyl phosphatidylcholine. We applied bioinformatics/computational tools and procedures, such as molecular docking, molecular and essential dynamics, starting from published crystal structures for apolipoprotein A-I and apolipoprotein A-II. Structural and energetic analyses onto the simulated system showed that the molecular dynamics produced a stabilized synthetic HDL. The essential dynamic analysis showed a deviation from the starting belt structure. Our structural results were validated by limited proteolysis experiments on HDL from apoA-IM carriers in comparison with control HDL. The high sensitivity of apoA-IM–apoA-II to proteases was in agreement with the high root mean-square fluctuation values and the reduction in secondary structure content from molecular dynamics data. Circular dichroism on synthetic HDL containing apoA-IM–apoA-II was consistent with the α-helix content computed on the proposed model. PMID:16891368

Breaking the bottleneck: Use of molecular tailoring approach for the estimation of binding energies at MP2/CBS limit for large water clusters

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

Singh, Gurmeet; Nandi, Apurba; Gadre, Shridhar R., E-mail: gadre@iitk.ac.in

2016-03-14

A pragmatic method based on the molecular tailoring approach (MTA) for estimating the complete basis set (CBS) limit at Møller-Plesset second order perturbation (MP2) theory accurately for large molecular clusters with limited computational resources is developed. It is applied to water clusters, (H{sub 2}O){sub n} (n = 7, 8, 10, 16, 17, and 25) optimized employing aug-cc-pVDZ (aVDZ) basis-set. Binding energies (BEs) of these clusters are estimated at the MP2/aug-cc-pVNZ (aVNZ) [N = T, Q, and 5 (whenever possible)] levels of theory employing grafted MTA (GMTA) methodology and are found to lie within 0.2 kcal/mol of the corresponding full calculationmore » MP2 BE, wherever available. The results are extrapolated to CBS limit using a three point formula. The GMTA-MP2 calculations are feasible on off-the-shelf hardware and show around 50%–65% saving of computational time. The methodology has a potential for application to molecular clusters containing ∼100 atoms.« less

Computer-Aided Drug Design in Epigenetics

NASA Astrophysics Data System (ADS)

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-03-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.

Computer-Aided Drug Design in Epigenetics

PubMed Central

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-01-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field. PMID:29594101

An Ensemble-Based Protocol for the Computational Prediction of Helix-Helix Interactions in G Protein-Coupled Receptors using Coarse-Grained Molecular Dynamics.

PubMed

Altwaijry, Nojood A; Baron, Michael; Wright, David W; Coveney, Peter V; Townsend-Nicholson, Andrea

2017-05-09

The accurate identification of the specific points of interaction between G protein-coupled receptor (GPCR) oligomers is essential for the design of receptor ligands targeting oligomeric receptor targets. A coarse-grained molecular dynamics computer simulation approach would provide a compelling means of identifying these specific protein-protein interactions and could be applied both for known oligomers of interest and as a high-throughput screen to identify novel oligomeric targets. However, to be effective, this in silico modeling must provide accurate, precise, and reproducible information. This has been achieved recently in numerous biological systems using an ensemble-based all-atom molecular dynamics approach. In this study, we describe an equivalent methodology for ensemble-based coarse-grained simulations. We report the performance of this method when applied to four different GPCRs known to oligomerize using error analysis to determine the ensemble size and individual replica simulation time required. Our measurements of distance between residues shown to be involved in oligomerization of the fifth transmembrane domain from the adenosine A 2A receptor are in very good agreement with the existing biophysical data and provide information about the nature of the contact interface that cannot be determined experimentally. Calculations of distance between rhodopsin, CXCR4, and β 1 AR transmembrane domains reported to form contact points in homodimers correlate well with the corresponding measurements obtained from experimental structural data, providing an ability to predict contact interfaces computationally. Interestingly, error analysis enables identification of noninteracting regions. Our results confirm that GPCR interactions can be reliably predicted using this novel methodology.

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.

Reliable Viscosity Calculation from Equilibrium Molecular Dynamics Simulations: A Time Decomposition Method.

PubMed

Zhang, Yong; Otani, Akihito; Maginn, Edward J

2015-08-11

Equilibrium molecular dynamics is often used in conjunction with a Green-Kubo integral of the pressure tensor autocorrelation function to compute the shear viscosity of fluids. This approach is computationally expensive and is subject to a large amount of variability because the plateau region of the Green-Kubo integral is difficult to identify unambiguously. Here, we propose a time decomposition approach for computing the shear viscosity using the Green-Kubo formalism. Instead of one long trajectory, multiple independent trajectories are run and the Green-Kubo relation is applied to each trajectory. The averaged running integral as a function of time is fit to a double-exponential function with a weighting function derived from the standard deviation of the running integrals. Such a weighting function minimizes the uncertainty of the estimated shear viscosity and provides an objective means of estimating the viscosity. While the formal Green-Kubo integral requires an integration to infinite time, we suggest an integration cutoff time tcut, which can be determined by the relative values of the running integral and the corresponding standard deviation. This approach for computing the shear viscosity can be easily automated and used in computational screening studies where human judgment and intervention in the data analysis are impractical. The method has been applied to the calculation of the shear viscosity of a relatively low-viscosity liquid, ethanol, and relatively high-viscosity ionic liquid, 1-n-butyl-3-methylimidazolium bis(trifluoromethane-sulfonyl)imide ([BMIM][Tf2N]), over a range of temperatures. These test cases show that the method is robust and yields reproducible and reliable shear viscosity values.

Transport coefficients of liquid CF4 and SF6 computed by molecular dynamics using polycenter Lennard-Jones potentials

NASA Astrophysics Data System (ADS)

Hoheisel, C.

1989-01-01

For several liquid states of CF4 and SF4, the shear and the bulk viscosity as well as the thermal conductivity were determined by equilibrium molecular dynamics (MD) calculations. Lennard-Jones four- and six-center pair potentials were applied, and the method of constraints was chosen for the MD. The computed Green-Kubo integrands show a steep time decay, and no particular longtime behavior occurs. The molecule number dependence of the results is found to be small, and 3×105 integration steps allow an accuracy of about 10% for the shear viscosity and the thermal conductivity coefficient. Comparison with experimental data shows a fair agreement for CF4, while for SF6 the transport coefficients fall below the experimental ones by about 30%.

Computer simulation studies of the growth of strained layers by molecular-beam epitaxy

NASA Astrophysics Data System (ADS)

Faux, D. A.; Gaynor, G.; Carson, C. L.; Hall, C. K.; Bernholc, J.

1990-08-01

Two new types of discrete-space Monte Carlo computer simulation are presented for the modeling of the early stages of strained-layer growth by molecular-beam epitaxy. The simulations are more economical on computer resources than continuous-space Monte Carlo or molecular dynamics. Each model is applied to the study of growth onto a substrate in two dimensions with use of Lennard-Jones interatomic potentials. Up to seven layers are deposited for a variety of lattice mismatches, temperatures, and growth rates. Both simulations give similar results. At small lattice mismatches (<~4%) the growth is in registry with the substrate, while at high mismatches (>~6%) the growth is incommensurate with the substrate. At intermediate mismatches, a transition from registered to incommensurate growth is observed which commences at the top of the crystal and propagates down to the first layer. Faster growth rates are seen to inhibit this transition. The growth mode is van der Merwe (layer-by-layer) at 2% lattice mismatch, but at larger mismatches Volmer-Weber (island) growth is preferred. The Monte Carlo simulations are assessed in the light of these results and the ease at which they can be extended to three dimensions and to more sophisticated potentials is discussed.

Towards an ab initio theory for metal L-edge soft X-ray spectroscopy of molecular aggregates.

PubMed

Preuße, Marie; Bokarev, Sergey I; Aziz, Saadullah G; Kühn, Oliver

2016-11-01

The Frenkel exciton model was adapted to describe X-ray absorption and resonant inelastic scattering spectra of polynuclear transition metal complexes by means of the restricted active space self-consistent field method. The proposed approach allows to substantially decrease the requirements on computational resources if compared to a full supermolecular quantum chemical treatment. This holds true, in particular, in cases where the dipole approximation to the electronic transition charge density can be applied. The computational protocol was applied to the calculation of X-ray spectra of the hemin complex, which forms dimers in aqueous solution. The aggregation effects were found to be comparable to the spectral alterations due to the replacement of the axial ligand by solvent molecules.

Path integral Liouville dynamics: Applications to infrared spectra of OH, water, ammonia, and methane

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

Liu, Jian, E-mail: jianliupku@pku.edu.cn; State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871; Zhang, Zhijun

Path integral Liouville dynamics (PILD) is applied to vibrational dynamics of several simple but representative realistic molecular systems (OH, water, ammonia, and methane). The dipole-derivative autocorrelation function is employed to obtain the infrared spectrum as a function of temperature and isotopic substitution. Comparison to the exact vibrational frequency shows that PILD produces a reasonably accurate peak position with a relatively small full width at half maximum. PILD offers a potentially useful trajectory-based quantum dynamics approach to compute vibrational spectra of molecular systems.

THERANOSTICS: From Molecular Imaging Using Ga-68 Labeled Tracers and PET/CT to Personalized Radionuclide Therapy - The Bad Berka Experience

PubMed Central

Baum, Richard P.; Kulkarni, Harshad R.

2012-01-01

The acronym THERANOSTICS epitomizes the inseparability of diagnosis and therapy, the pillars of medicine and takes into account personalized management of disease for a specific patient. Molecular phenotypes of neoplasms can be determined by molecular imaging with specific probes using positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), or optical methods, so that the treatment is specifically targeted against the tumor and its environment. To meet these demands, we need to define the targets, ligands, coupling and labeling chemistry, the most appropriate radionuclides, biodistribution modifiers, and finally select the right patients for the personalized treatment. THERANOSTICS of neuroendocrine tumors (NETs) using Ga-68 labeled tracers for diagnostics with positron emission tomography/ computed tomography (PET/CT), and using Lu-177 or other metallic radionuclides for radionuclide therapy by applying the same peptide proves that personalized radionuclide therapy today is already a fact and not a fiction. PMID:22768024

THERANOSTICS: From Molecular Imaging Using Ga-68 Labeled Tracers and PET/CT to Personalized Radionuclide Therapy - The Bad Berka Experience.

PubMed

Baum, Richard P; Kulkarni, Harshad R

2012-01-01

The acronym THERANOSTICS epitomizes the inseparability of diagnosis and therapy, the pillars of medicine and takes into account personalized management of disease for a specific patient. Molecular phenotypes of neoplasms can be determined by molecular imaging with specific probes using positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), or optical methods, so that the treatment is specifically targeted against the tumor and its environment. To meet these demands, we need to define the targets, ligands, coupling and labeling chemistry, the most appropriate radionuclides, biodistribution modifiers, and finally select the right patients for the personalized treatment. THERANOSTICS of neuroendocrine tumors (NETs) using Ga-68 labeled tracers for diagnostics with positron emission tomography/ computed tomography (PET/CT), and using Lu-177 or other metallic radionuclides for radionuclide therapy by applying the same peptide proves that personalized radionuclide therapy today is already a fact and not a fiction.

A Statistical Approach for the Concurrent Coupling of Molecular Dynamics and Finite Element Methods

NASA Technical Reports Server (NTRS)

Saether, E.; Yamakov, V.; Glaessgen, E.

2007-01-01

Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, increasing the size of the MD domain quickly presents intractable computational demands. A robust approach to surmount this computational limitation has been to unite continuum modeling procedures such as the finite element method (FEM) with MD analyses thereby reducing the region of atomic scale refinement. The challenging problem is to seamlessly connect the two inherently different simulation techniques at their interface. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the typical boundary value problem used to define a coupled domain. The method uses statistical averaging of the atomistic MD domain to provide displacement interface boundary conditions to the surrounding continuum FEM region, which, in return, generates interface reaction forces applied as piecewise constant traction boundary conditions to the MD domain. The two systems are computationally disconnected and communicate only through a continuous update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM) as opposed to a direct coupling method where interface atoms and FEM nodes are individually related. The methodology is inherently applicable to three-dimensional domains, avoids discretization of the continuum model down to atomic scales, and permits arbitrary temperatures to be applied.

Measurement Frontiers in Molecular Biology

NASA Astrophysics Data System (ADS)

Laderman, Stephen

2009-03-01

Developments of molecular measurements and manipulations have long enabled forefront research in evolution, genetics, biological development and its dysfunction, and the impact of external factors on the behavior of cells. Measurement remains at the heart of exciting and challenging basic and applied problems in molecular and cell biology. Methods to precisely determine the identity and abundance of particular molecules amongst a complex mixture of similar and dissimilar types require the successful design and integration of multiple steps involving biochemical manipulations, separations, physical probing, and data processing. Accordingly, today's most powerful methods for characterizing life at the molecular level depend on coordinated advances in applied physics, biochemistry, chemistry, computer science, and engineering. This is well illustrated by recent approaches to the measurement of DNA, RNA, proteins, and intact cells. Such successes underlie well founded visions of how molecular biology can further assist in answering compelling scientific questions and in enabling the development of remarkable advances in human health. These visions, in turn, are motivating the interdisciplinary creation of even more comprehensive measurements. As a further and closely related consequence, they are motivating innovations in the conceptual and practical approaches to organizing and visualizing large, complex sets of interrelated experimental results and distilling from those data compelling, informative conclusions.

Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

PubMed

Makeneni, Spandana; Thieker, David F; Woods, Robert J

2018-03-26

In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.

Lattice dynamics calculations based on density-functional perturbation theory in real space

NASA Astrophysics Data System (ADS)

Shang, Honghui; Carbogno, Christian; Rinke, Patrick; Scheffler, Matthias

2017-06-01

A real-space formalism for density-functional perturbation theory (DFPT) is derived and applied for the computation of harmonic vibrational properties in molecules and solids. The practical implementation using numeric atom-centered orbitals as basis functions is demonstrated exemplarily for the all-electron Fritz Haber Institute ab initio molecular simulations (FHI-aims) package. The convergence of the calculations with respect to numerical parameters is carefully investigated and a systematic comparison with finite-difference approaches is performed both for finite (molecules) and extended (periodic) systems. Finally, the scaling tests and scalability tests on massively parallel computer systems demonstrate the computational efficiency.

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies.

PubMed

Hansen, Katja; Montavon, Grégoire; Biegler, Franziska; Fazli, Siamac; Rupp, Matthias; Scheffler, Matthias; von Lilienfeld, O Anatole; Tkatchenko, Alexandre; Müller, Klaus-Robert

2013-08-13

The accurate and reliable prediction of properties of molecules typically requires computationally intensive quantum-chemical calculations. Recently, machine learning techniques applied to ab initio calculations have been proposed as an efficient approach for describing the energies of molecules in their given ground-state structure throughout chemical compound space (Rupp et al. Phys. Rev. Lett. 2012, 108, 058301). In this paper we outline a number of established machine learning techniques and investigate the influence of the molecular representation on the methods performance. The best methods achieve prediction errors of 3 kcal/mol for the atomization energies of a wide variety of molecules. Rationales for this performance improvement are given together with pitfalls and challenges when applying machine learning approaches to the prediction of quantum-mechanical observables.

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.

Efficient algorithms for the simulation of non-adiabatic electron transfer in complex molecular systems: application to DNA.

PubMed

Kubař, Tomáš; Elstner, Marcus

2013-04-28

In this work, a fragment-orbital density functional theory-based method is combined with two different non-adiabatic schemes for the propagation of the electronic degrees of freedom. This allows us to perform unbiased simulations of electron transfer processes in complex media, and the computational scheme is applied to the transfer of a hole in solvated DNA. It turns out that the mean-field approach, where the wave function of the hole is driven into a superposition of adiabatic states, leads to over-delocalization of the hole charge. This problem is avoided using a surface hopping scheme, resulting in a smaller rate of hole transfer. The method is highly efficient due to the on-the-fly computation of the coarse-grained DFT Hamiltonian for the nucleobases, which is coupled to the environment using a QM/MM approach. The computational efficiency and partial parallel character of the methodology make it possible to simulate electron transfer in systems of relevant biochemical size on a nanosecond time scale. Since standard non-polarizable force fields are applied in the molecular-mechanics part of the calculation, a simple scaling scheme was introduced into the electrostatic potential in order to simulate the effect of electronic polarization. It is shown that electronic polarization has an important effect on the features of charge transfer. The methodology is applied to two kinds of DNA sequences, illustrating the features of transfer along a flat energy landscape as well as over an energy barrier. The performance and relative merit of the mean-field scheme and the surface hopping for this application are discussed.

Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

PubMed

Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

2016-08-11

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis.

PubMed

Kumar, Sudhir; Stecher, Glen; Peterson, Daniel; Tamura, Koichiro

2012-10-15

There is a growing need in the research community to apply the molecular evolutionary genetics analysis (MEGA) software tool for batch processing a large number of datasets and to integrate it into analysis workflows. Therefore, we now make available the computing core of the MEGA software as a stand-alone executable (MEGA-CC), along with an analysis prototyper (MEGA-Proto). MEGA-CC provides users with access to all the computational analyses available through MEGA's graphical user interface version. This includes methods for multiple sequence alignment, substitution model selection, evolutionary distance estimation, phylogeny inference, substitution rate and pattern estimation, tests of natural selection and ancestral sequence inference. Additionally, we have upgraded the source code for phylogenetic analysis using the maximum likelihood methods for parallel execution on multiple processors and cores. Here, we describe MEGA-CC and outline the steps for using MEGA-CC in tandem with MEGA-Proto for iterative and automated data analysis. http://www.megasoftware.net/.

Let's get honest about sampling.

PubMed

Mobley, David L

2012-01-01

Molecular simulations see widespread and increasing use in computation and molecular design, especially within the area of molecular simulations applied to biomolecular binding and interactions, our focus here. However, force field accuracy remains a concern for many practitioners, and it is often not clear what level of accuracy is really needed for payoffs in a discovery setting. Here, I argue that despite limitations of today's force fields, current simulation tools and force fields now provide the potential for real benefits in a variety of applications. However, these same tools also provide irreproducible results which are often poorly interpreted. Continued progress in the field requires more honesty in assessment and care in evaluation of simulation results, especially with respect to convergence.

Coulomb interactions in charged fluids.

PubMed

Vernizzi, Graziano; Guerrero-García, Guillermo Iván; de la Cruz, Monica Olvera

2011-07-01

The use of Ewald summation schemes for calculating long-range Coulomb interactions, originally applied to ionic crystalline solids, is a very common practice in molecular simulations of charged fluids at present. Such a choice imposes an artificial periodicity which is generally absent in the liquid state. In this paper we propose a simple analytical O(N(2)) method which is based on Gauss's law for computing exactly the Coulomb interaction between charged particles in a simulation box, when it is averaged over all possible orientations of a surrounding infinite lattice. This method mitigates the periodicity typical of crystalline systems and it is suitable for numerical studies of ionic liquids, charged molecular fluids, and colloidal systems with Monte Carlo and molecular dynamics simulations.

Electric-field-driven electron-transfer in mixed-valence molecules.

PubMed

Blair, Enrique P; Corcelli, Steven A; Lent, Craig S

2016-07-07

Molecular quantum-dot cellular automata is a computing paradigm in which digital information is encoded by the charge configuration of a mixed-valence molecule. General-purpose computing can be achieved by arranging these compounds on a substrate and exploiting intermolecular Coulombic coupling. The operation of such a device relies on nonequilibrium electron transfer (ET), whereby the time-varying electric field of one molecule induces an ET event in a neighboring molecule. The magnitude of the electric fields can be quite large because of close spatial proximity, and the induced ET rate is a measure of the nonequilibrium response of the molecule. We calculate the electric-field-driven ET rate for a model mixed-valence compound. The mixed-valence molecule is regarded as a two-state electronic system coupled to a molecular vibrational mode, which is, in turn, coupled to a thermal environment. Both the electronic and vibrational degrees-of-freedom are treated quantum mechanically, and the dissipative vibrational-bath interaction is modeled with the Lindblad equation. This approach captures both tunneling and nonadiabatic dynamics. Relationships between microscopic molecular properties and the driven ET rate are explored for two time-dependent applied fields: an abruptly switched field and a linearly ramped field. In both cases, the driven ET rate is only weakly temperature dependent. When the model is applied using parameters appropriate to a specific mixed-valence molecule, diferrocenylacetylene, terahertz-range ET transfer rates are predicted.

Exhaustively sampling peptide adsorption with metadynamics.

PubMed

Deighan, Michael; Pfaendtner, Jim

2013-06-25

Simulating the adsorption of a peptide or protein and obtaining quantitative estimates of thermodynamic observables remains challenging for many reasons. One reason is the dearth of molecular scale experimental data available for validating such computational models. We also lack simulation methodologies that effectively address the dual challenges of simulating protein adsorption: overcoming strong surface binding and sampling conformational changes. Unbiased classical simulations do not address either of these challenges. Previous attempts that apply enhanced sampling generally focus on only one of the two issues, leaving the other to chance or brute force computing. To improve our ability to accurately resolve adsorbed protein orientation and conformational states, we have applied the Parallel Tempering Metadynamics in the Well-Tempered Ensemble (PTMetaD-WTE) method to several explicitly solvated protein/surface systems. We simulated the adsorption behavior of two peptides, LKα14 and LKβ15, onto two self-assembled monolayer (SAM) surfaces with carboxyl and methyl terminal functionalities. PTMetaD-WTE proved effective at achieving rapid convergence of the simulations, whose results elucidated different aspects of peptide adsorption including: binding free energies, side chain orientations, and preferred conformations. We investigated how specific molecular features of the surface/protein interface change the shape of the multidimensional peptide binding free energy landscape. Additionally, we compared our enhanced sampling technique with umbrella sampling and also evaluated three commonly used molecular dynamics force fields.

Lattice enumeration for inverse molecular design using the signature descriptor.

PubMed

Martin, Shawn

2012-07-23

We describe an inverse quantitative structure-activity relationship (QSAR) framework developed for the design of molecular structures with desired properties. This framework uses chemical fragments encoded with a molecular descriptor known as a signature. It solves a system of linear constrained Diophantine equations to reorganize the fragments into novel molecular structures. The method has been previously applied to problems in drug and materials design but has inherent computational limitations due to the necessity of solving the Diophantine constraints. We propose a new approach to overcome these limitations using the Fincke-Pohst algorithm for lattice enumeration. We benchmark the new approach against previous results on LFA-1/ICAM-1 inhibitory peptides, linear homopolymers, and hydrofluoroether foam blowing agents. Software implementing the new approach is available at www.cs.otago.ac.nz/homepages/smartin.

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.

Discovering the intelligence in molecular biology.

PubMed

Uberbacher, E

1995-12-01

The Third International Conference on Intelligent Systems in Molecular Biology was truly an outstanding event. Computational methods in molecular biology have reached a new level of maturity and utility, resulting in many high-impact applications. The success of this meeting bodes well for the rapid and continuing development of computational methods, intelligent systems and information-based approaches for the biosciences. The basic technology, originally most often applied to 'feasibility' problems, is now dealing effectively with the most difficult real-world problems. Significant progress has been made in understanding protein-structure information, structural classification, and how functional information and the relevant features of active-site geometry can be gleaned from structures by automated computational approaches. The value and limits of homology-based methods, and the ability to classify proteins by structure in the absence of homology, have reached a new level of sophistication. New methods for covariation analysis in the folding of large structures such as RNAs have shown remarkably good results, indicating the long-term potential to understand very complicated molecules and multimolecular complexes using computational means. Novel methods, such as HMMs, context-free grammars and the uses of mutual information theory, have taken center stage as highly valuable tools in our quest to represent and characterize biological information. A focus on creative uses of intelligent systems technologies and the trend toward biological application will undoubtedly continue and grow at the 1996 ISMB meeting in St Louis.

MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation.

PubMed

Oetjen, Janina; Aichler, Michaela; Trede, Dennis; Strehlow, Jan; Berger, Judith; Heldmann, Stefan; Becker, Michael; Gottschalk, Michael; Kobarg, Jan Hendrik; Wirtz, Stefan; Schiffler, Stefan; Thiele, Herbert; Walch, Axel; Maass, Peter; Alexandrov, Theodore

2013-09-02

MALDI imaging mass spectrometry (MALDI-imaging) has emerged as a spatially-resolved label-free bioanalytical technique for direct analysis of biological samples and was recently introduced for analysis of 3D tissue specimens. We present a new experimental and computational pipeline for molecular analysis of tissue specimens which integrates 3D MALDI-imaging, magnetic resonance imaging (MRI), and histological staining and microscopy, and evaluate the pipeline by applying it to analysis of a mouse kidney. To ensure sample integrity and reproducible sectioning, we utilized the PAXgene fixation and paraffin embedding and proved its compatibility with MRI. Altogether, 122 serial sections of the kidney were analyzed using MALDI-imaging, resulting in a 3D dataset of 200GB comprised of 2million spectra. We show that elastic image registration better compensates for local distortions of tissue sections. The computational analysis of 3D MALDI-imaging data was performed using our spatial segmentation pipeline which determines regions of distinct molecular composition and finds m/z-values co-localized with these regions. For facilitated interpretation of 3D distribution of ions, we evaluated isosurfaces providing simplified visualization. We present the data in a multimodal fashion combining 3D MALDI-imaging with the MRI volume rendering and with light microscopic images of histologically stained sections. Our novel experimental and computational pipeline for 3D MALDI-imaging can be applied to address clinical questions such as proteomic analysis of the tumor morphologic heterogeneity. Examining the protein distribution as well as the drug distribution throughout an entire tumor using our pipeline will facilitate understanding of the molecular mechanisms of carcinogenesis. Copyright © 2013 Elsevier B.V. All rights reserved.

An Ensemble-Based Protocol for the Computational Prediction of Helix–Helix Interactions in G Protein-Coupled Receptors using Coarse-Grained Molecular Dynamics

PubMed Central

2017-01-01

The accurate identification of the specific points of interaction between G protein-coupled receptor (GPCR) oligomers is essential for the design of receptor ligands targeting oligomeric receptor targets. A coarse-grained molecular dynamics computer simulation approach would provide a compelling means of identifying these specific protein–protein interactions and could be applied both for known oligomers of interest and as a high-throughput screen to identify novel oligomeric targets. However, to be effective, this in silico modeling must provide accurate, precise, and reproducible information. This has been achieved recently in numerous biological systems using an ensemble-based all-atom molecular dynamics approach. In this study, we describe an equivalent methodology for ensemble-based coarse-grained simulations. We report the performance of this method when applied to four different GPCRs known to oligomerize using error analysis to determine the ensemble size and individual replica simulation time required. Our measurements of distance between residues shown to be involved in oligomerization of the fifth transmembrane domain from the adenosine A2A receptor are in very good agreement with the existing biophysical data and provide information about the nature of the contact interface that cannot be determined experimentally. Calculations of distance between rhodopsin, CXCR4, and β1AR transmembrane domains reported to form contact points in homodimers correlate well with the corresponding measurements obtained from experimental structural data, providing an ability to predict contact interfaces computationally. Interestingly, error analysis enables identification of noninteracting regions. Our results confirm that GPCR interactions can be reliably predicted using this novel methodology. PMID:28383913

Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

PubMed

San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul

2014-12-01

Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.

Computational Modeling of Molecular Effects of Mutations Causing Snyder-Robinson Syndrome

NASA Astrophysics Data System (ADS)

Zhang, Zhe; Teng, Shaolei; Alexov, Emil

2009-11-01

Snyder-Robinson syndrome is an X-linked mental retardation disorder disease. The disease is associated with defects in a particular biomolecule, the spermine synthase (SMS) protein. Specifically, three missense mutations, G56S, I150T and V132G in SMS were identified to cause the disease, but molecular mechanism of their effect is unknown. We apply single-point energy calculations, molecular dynamics simulations and pKa calculations to reveal the effects of these mutations on SMS's stability, flexibility and interactions. It is demonstrated that even saddle changes as very conservative mutations can significantly affect wild type properties of SMS protein. While the mutations do not involve ionizable groups, still slight changes in the protonation of neighboring amino acids are suggested by the computational protocol. The dynamics of SMS was also affected by the mutations resulting in larger structural fluctuations in the mutant protein compared to the wild type. At the same time, the effect on SMS's stability was found to depend on the location of the mutation site with respect to the surface of the protein. Our investigation suggests that the disease is caused by diverse molecular mechanisms depending on the site of mutation and amino acid type substitution.

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.

Application of artificial neural networks to identify equilibration in computer simulations

NASA Astrophysics Data System (ADS)

Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

2017-11-01

Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

Interaction of charge carriers with lattice and molecular phonons in crystalline pentacene

NASA Astrophysics Data System (ADS)

Girlando, Alberto; Grisanti, Luca; Masino, Matteo; Brillante, Aldo; Della Valle, Raffaele G.; Venuti, Elisabetta

2011-08-01

The computational protocol we have developed for the calculation of local (Holstein) and non-local (Peierls) carrier-phonon coupling in molecular organic semiconductors is applied to both the low temperature and high temperature bulk crystalline phases of pentacene. The electronic structure is calculated by the semimpirical INDO/S (Intermediate Neglect of Differential Overlap with Spectroscopic parametrization) method. In the phonon description, the rigid molecule approximation is removed, allowing mixing of low-frequency intra-molecular modes with inter-molecular (lattice) phonons. A clear distinction remains between the low-frequency phonons, which essentially modulate the transfer integral from a molecule to another (Peierls coupling), and the high-frequency intra-molecular phonons, which modulate the on-site energy (Holstein coupling). The results of calculation agree well with the values extracted from experiment. The comparison with similar calculations made for rubrene allows us to discuss the implications for the current models of mobility.

Quantification of the effect of cross-shear and applied nominal contact pressure on the wear of moderately cross-linked polyethylene.

PubMed

Abdelgaied, Abdellatif; Brockett, Claire L; Liu, Feng; Jennings, Louise M; Fisher, John; Jin, Zhongmin

2013-01-01

Polyethylene wear is a great concern in total joint replacement. It is now considered a major limiting factor to the long life of such prostheses. Cross-linking has been introduced to reduce the wear of ultra-high-molecular-weight polyethylene (UHMWPE). Computational models have been used extensively for wear prediction and optimization of artificial knee designs. However, in order to be independent and have general applicability and predictability, computational wear models should be based on inputs from independent experimentally determined wear parameters (wear factors or wear coefficients). The objective of this study was to investigate moderately cross-linked UHMWPE, using a multidirectional pin-on-plate wear test machine, under a wide range of applied nominal contact pressure (from 1 to 11 MPa) and under five different kinematic inputs, varying from a purely linear track to a maximum rotation of +/- 55 degrees. A computational model, based on a direct simulation of the multidirectional pin-on-plate wear tester, was developed to quantify the degree of cross-shear (CS) of the polyethylene pins articulating against the metallic plates. The moderately cross-linked UHMWPE showed wear factors less than half of that reported in the literature for, the conventional UHMWPE, under the same loading and kinematic inputs. In addition, under high applied nominal contact stress, the moderately crosslinked UHMWPE wear showed lower dependence on the degree of CS compared to that under low applied nominal contact stress. The calculated wear coefficients were found to be independent of the applied nominal contact stress, in contrast to the wear factors that were shown to be highly pressure dependent. This study provided independent wear data for inputs into computational models for moderately cross-linked polyethylene and supported the application of wear coefficient-based computational wear models.

Systems Biology Approaches for Discovering Biomarkers for Traumatic Brain Injury

PubMed Central

Feala, Jacob D.; AbdulHameed, Mohamed Diwan M.; Yu, Chenggang; Dutta, Bhaskar; Yu, Xueping; Schmid, Kara; Dave, Jitendra; Tortella, Frank

2013-01-01

Abstract The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates. PMID:23510232

Helium Atom Scattering from C2H6, F2HCCH3, F3CCH2F and C2F6 in Crossed Molecular Beams

NASA Astrophysics Data System (ADS)

Hammer, Markus; Seidel, Wolfhart

1997-10-01

Rotationally unresolved differential cross sections were measured in crossed molecular beam experiments by scattering Helium atoms from Ethane, 1,1-Difluoroethane, 1,1,1,2-Tetrafluoroethane and Hexafluoroethane. The damping of observed diffraction oscillations was used to extract anisotropic interaction potentials for these scattering systems applying the infinite order sudden approximation (IOSA). Binary macroscopic parameters such as second heterogeneous virial coefficients and the coefficients of diffusion and viscosity were computed from these potentials and compared to results from macroscopic experiments.

A computational neural approach to support the discovery of gene function and classes of cancer.

PubMed

Azuaje, F

2001-03-01

Advances in molecular classification of tumours may play a central role in cancer treatment. Here, a novel approach to genome expression pattern interpretation is described and applied to the recognition of B-cell malignancies as a test set. Using cDNA microarrays data generated by a previous study, a neural network model known as simplified fuzzy ARTMAP is able to identify normal and diffuse large B-cell lymphoma (DLBCL) patients. Furthermore, it discovers the distinction between patients with molecularly distinct forms of DLBCL without previous knowledge of those subtypes.

Molecular robots with sensors and intelligence.

PubMed

Hagiya, Masami; Konagaya, Akihiko; Kobayashi, Satoshi; Saito, Hirohide; Murata, Satoshi

2014-06-17

CONSPECTUS: What we can call a molecular robot is a set of molecular devices such as sensors, logic gates, and actuators integrated into a consistent system. The molecular robot is supposed to react autonomously to its environment by receiving molecular signals and making decisions by molecular computation. Building such a system has long been a dream of scientists; however, despite extensive efforts, systems having all three functions (sensing, computation, and actuation) have not been realized yet. This Account introduces an ongoing research project that focuses on the development of molecular robotics funded by MEXT (Ministry of Education, Culture, Sports, Science and Technology, Japan). This 5 year project started in July 2012 and is titled "Development of Molecular Robots Equipped with Sensors and Intelligence". The major issues in the field of molecular robotics all correspond to a feedback (i.e., plan-do-see) cycle of a robotic system. More specifically, these issues are (1) developing molecular sensors capable of handling a wide array of signals, (2) developing amplification methods of signals to drive molecular computing devices, (3) accelerating molecular computing, (4) developing actuators that are controllable by molecular computers, and (5) providing bodies of molecular robots encapsulating the above molecular devices, which implement the conformational changes and locomotion of the robots. In this Account, the latest contributions to the project are reported. There are four research teams in the project that specialize on sensing, intelligence, amoeba-like actuation, and slime-like actuation, respectively. The molecular sensor team is focusing on the development of molecular sensors that can handle a variety of signals. This team is also investigating methods to amplify signals from the molecular sensors. The molecular intelligence team is developing molecular computers and is currently focusing on a new photochemical technology for accelerating DNA-based computations. They also introduce novel computational models behind various kinds of molecular computers necessary for designing such computers. The amoeba robot team aims at constructing amoeba-like robots. The team is trying to incorporate motor proteins, including kinesin and microtubules (MTs), for use as actuators implemented in a liposomal compartment as a robot body. They are also developing a methodology to link DNA-based computation and molecular motor control. The slime robot team focuses on the development of slime-like robots. The team is evaluating various gels, including DNA gel and BZ gel, for use as actuators, as well as the body material to disperse various molecular devices in it. They also try to control the gel actuators by DNA signals coming from molecular computers.

A new fast algorithm for solving the minimum spanning tree problem based on DNA molecules computation.

PubMed

Wang, Zhaocai; Huang, Dongmei; Meng, Huajun; Tang, Chengpei

2013-10-01

The minimum spanning tree (MST) problem is to find minimum edge connected subsets containing all the vertex of a given undirected graph. It is a vitally important NP-complete problem in graph theory and applied mathematics, having numerous real life applications. Moreover in previous studies, DNA molecular operations usually were used to solve NP-complete head-to-tail path search problems, rarely for NP-hard problems with multi-lateral path solutions result, such as the minimum spanning tree problem. In this paper, we present a new fast DNA algorithm for solving the MST problem using DNA molecular operations. For an undirected graph with n vertex and m edges, we reasonably design flexible length DNA strands representing the vertex and edges, take appropriate steps and get the solutions of the MST problem in proper length range and O(3m+n) time complexity. We extend the application of DNA molecular operations and simultaneity simplify the complexity of the computation. Results of computer simulative experiments show that the proposed method updates some of the best known values with very short time and that the proposed method provides a better performance with solution accuracy over existing algorithms. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

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

PubMed

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

2018-06-01

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

Crystal structure of channelrhodopsin, a light-gated cation channel – all cations lead through the monomer –

PubMed Central

Kato, Hideaki E.; Nureki, Osamu

2013-01-01

Channelrhodopsin (ChR) is a light-gated cation channel derived from green algae. Since the inward flow of cations triggers the neuron firing, neurons expressing ChRs can be optically controlled even within freely moving mammals. Although ChR has been broadly applied to neuro-science research, little is known about its molecular mechanisms. We determined the crystal structure of chimeric ChR at 2.3 Å resolution and revealed its molecular architecture. The integration of structural, electrophysio-logical, and computational analyses provided insight into the molecular basis for the channel function of ChR, and paved the way for the principled design of ChR variants with novel properties. PMID:27493541

Molecular three-body Brauner-Briggs-Klar theory for ion-impact ionization of molecules

NASA Astrophysics Data System (ADS)

Ghanbari-Adivi, E.

2016-12-01

Molecular three-body Brauner-Briggs-Klar (M3BBK) theory is developed to study the single ionization of diatomic molecules by ion impact. The orientation-averaged molecular orbital (OAMO) approximation is used to reduce the required computer time without sacrificing the performance of the method. The post-collision interaction (PCI) between the scattered projectile and the ejected electron is included. The theory is applied to collision of protons with hydrogen molecules. Results are obtained for two different kinematical regimes: i) fast collisions and low emission energies, and ii) not so fast collisions and higher emission energies. For both considered regimes, experimental fully differential cross-sections as well as different theoretical calculations are available for comparison. These comparisons are carried out and discussed.

Site-specific recoil-induced effects on inner-shell photoionization of linear triatomic molecules: N 1 s photoelectron spectra of N2 O

NASA Astrophysics Data System (ADS)

Krivosenko, Yu. S.; Pavlychev, A. A.

2016-11-01

We investigate hard X-ray ionization of linear triatomic molecules accenting recoil-induced effects on the dynamics of molecular frame. This dynamics is studied within the two-springs and harmonic approximations. The mode-channel relationship connecting the excitations of vibrational, rotational and translational degrees of freedom with the Σ → Σ and Σ → Π photoionization channels is applied to compute the N 1s-1 photoelectron spectra of molecular N2 O for various photon energies. The distinct ionized-site- and molecular-orientation-specific changes in the vibration structure of the 1 s photoelectron lines of terminal and central nitrogen atoms are revealed and discussed.

Determination of partial molar volumes from free energy perturbation theory†

PubMed Central

Vilseck, Jonah Z.; Tirado-Rives, Julian

2016-01-01

Partial molar volume is an important thermodynamic property that gives insights into molecular size and intermolecular interactions in solution. Theoretical frameworks for determining the partial molar volume (V°) of a solvated molecule generally apply Scaled Particle Theory or Kirkwood–Buff theory. With the current abilities to perform long molecular dynamics and Monte Carlo simulations, more direct methods are gaining popularity, such as computing V° directly as the difference in computed volume from two simulations, one with a solute present and another without. Thermodynamically, V° can also be determined as the pressure derivative of the free energy of solvation in the limit of infinite dilution. Both approaches are considered herein with the use of free energy perturbation (FEP) calculations to compute the necessary free energies of solvation at elevated pressures. Absolute and relative partial molar volumes are computed for benzene and benzene derivatives using the OPLS-AA force field. The mean unsigned error for all molecules is 2.8 cm3 mol−1. The present methodology should find use in many contexts such as the development and testing of force fields for use in computer simulations of organic and biomolecular systems, as a complement to related experimental studies, and to develop a deeper understanding of solute–solvent interactions. PMID:25589343

Determination of partial molar volumes from free energy perturbation theory.

PubMed

Vilseck, Jonah Z; Tirado-Rives, Julian; Jorgensen, William L

2015-04-07

Partial molar volume is an important thermodynamic property that gives insights into molecular size and intermolecular interactions in solution. Theoretical frameworks for determining the partial molar volume (V°) of a solvated molecule generally apply Scaled Particle Theory or Kirkwood-Buff theory. With the current abilities to perform long molecular dynamics and Monte Carlo simulations, more direct methods are gaining popularity, such as computing V° directly as the difference in computed volume from two simulations, one with a solute present and another without. Thermodynamically, V° can also be determined as the pressure derivative of the free energy of solvation in the limit of infinite dilution. Both approaches are considered herein with the use of free energy perturbation (FEP) calculations to compute the necessary free energies of solvation at elevated pressures. Absolute and relative partial molar volumes are computed for benzene and benzene derivatives using the OPLS-AA force field. The mean unsigned error for all molecules is 2.8 cm(3) mol(-1). The present methodology should find use in many contexts such as the development and testing of force fields for use in computer simulations of organic and biomolecular systems, as a complement to related experimental studies, and to develop a deeper understanding of solute-solvent interactions.

Conformational free energies of methyl-α-L-iduronic and methyl-β-D-glucuronic acids in water

NASA Astrophysics Data System (ADS)

Babin, Volodymyr; Sagui, Celeste

2010-03-01

We present a simulation protocol that allows for efficient sampling of the degrees of freedom of a solute in explicit solvent. The protocol involves using a nonequilibrium umbrella sampling method, in this case, the recently developed adaptively biased molecular dynamics method, to compute an approximate free energy for the slow modes of the solute in explicit solvent. This approximate free energy is then used to set up a Hamiltonian replica exchange scheme that samples both from biased and unbiased distributions. The final accurate free energy is recovered via the weighted histogram analysis technique applied to all the replicas, and equilibrium properties of the solute are computed from the unbiased trajectory. We illustrate the approach by applying it to the study of the puckering landscapes of the methyl glycosides of α-L-iduronic acid and its C5 epimer β-D-glucuronic acid in water. Big savings in computational resources are gained in comparison to the standard parallel tempering method.

Conformational free energies of methyl-alpha-L-iduronic and methyl-beta-D-glucuronic acids in water.

PubMed

Babin, Volodymyr; Sagui, Celeste

2010-03-14

We present a simulation protocol that allows for efficient sampling of the degrees of freedom of a solute in explicit solvent. The protocol involves using a nonequilibrium umbrella sampling method, in this case, the recently developed adaptively biased molecular dynamics method, to compute an approximate free energy for the slow modes of the solute in explicit solvent. This approximate free energy is then used to set up a Hamiltonian replica exchange scheme that samples both from biased and unbiased distributions. The final accurate free energy is recovered via the weighted histogram analysis technique applied to all the replicas, and equilibrium properties of the solute are computed from the unbiased trajectory. We illustrate the approach by applying it to the study of the puckering landscapes of the methyl glycosides of alpha-L-iduronic acid and its C5 epimer beta-D-glucuronic acid in water. Big savings in computational resources are gained in comparison to the standard parallel tempering method.

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

Distributed information system on molecular spectroscopy

NASA Astrophysics Data System (ADS)

Bykov, A. D.; Fazliev, A. Z.; Kozodoev, A. V.; Privezentsev, A. I.; Sinitsa, L. N.; Tonkov, M. V.; Filippov, N. N.; Tretyakov, M. Yu.

2006-12-01

The urgency of creating the information-computational systems (ICS) on molecular spectroscopy follows from the circumstance that for some molecules the number of calculated energy levels counts hundreds of thousands, and the number of spectral lines sometimes reaches hundreds of millions. Publication of such data volumes in regular journals is inappropriate. Comparison of different calculated spectral characteristics or their comparison with experimental data beyond computer processing is hopeless. We find information systems to be an adequate form for holding such data volumes and a toolkit for handling them. Correct digital data processing requires appropriate sets of metadata arranged in the form of ontology of molecular spectroscopy. Our information system provides the data on spectral line parameters, water molecule energy levels, and absorption coefficients. Within this distributed IS one can solve two types of problems: manipulation with data and calculation of spectral functions. Among the latest experimental data in the IS there are data obtained at the Institute of Applied Physics RAS. To calculate the absorption coefficients for the molecules of carbonic acid gas, we take into consideration spectral line interference.

Tidal disruption of open clusters in their parent molecular clouds

NASA Technical Reports Server (NTRS)

Long, Kevin

1989-01-01

A simple model of tidal encounters has been applied to the problem of an open cluster in a clumpy molecular cloud. The parameters of the clumps are taken from the Blitz, Stark, and Long (1988) catalog of clumps in the Rosette molecular cloud. Encounters are modeled as impulsive, rectilinear collisions between Plummer spheres, but the tidal approximation is not invoked. Mass and binding energy changes during an encounter are computed by considering the velocity impulses given to individual stars in a random realization of a Plummer sphere. Mean rates of mass and binding energy loss are then computed by integrating over many encounters. Self-similar evolutionary calculations using these rates indicate that the disruption process is most sensitive to the cluster radius and relatively insensitive to cluster mass. The calculations indicate that clusters which are born in a cloud similar to the Rosette with a cluster radius greater than about 2.5 pc will not survive long enough to leave the cloud. The majority of clusters, however, have smaller radii and will survive the passage through their parent cloud.

Hidden Markov models and other machine learning approaches in computational molecular biology

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

Baldi, P.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In thismore » tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.« less

Computational approach for designing thermostable Candida antarctica lipase B by molecular dynamics simulation.

PubMed

Park, Hyun June; Park, Kyungmoon; Kim, Yong Hwan; Yoo, Young Je

2014-12-20

Candida antarctica lipase B (CalB) is one of the most useful enzyme for various reactions and bioconversions. Enhancing thermostability of CalB is required for industrial applications. In this study, we propose a computational design strategy to improve the thermostability of CalB. Molecular dynamics simulations at various temperatures were used to investigate the common fluctuation sites in CalB, which are considered to be thermally weak points. The RosettaDesign algorithm was used to design the selected residues. The redesigned CalB was simulated to verify both the enhancement of intramolecular interactions and the lowering of the overall root-mean-square deviation (RMSD) values. The A251E mutant designed using this strategy showed a 2.5-fold higher thermostability than the wild-type CalB. This strategy could apply to other industry applicable enzymes. Copyright © 2014 Elsevier B.V. All rights reserved.

Solutions of burnt-bridge models for molecular motor transport.

PubMed

Morozov, Alexander Yu; Pronina, Ekaterina; Kolomeisky, Anatoly B; Artyomov, Maxim N

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called "bridges"), is investigated theoretically by analyzing discrete-state stochastic "burnt-bridge" models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed ("burned") with a probability p , creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into a one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For the general case of p<1 a theoretical method is developed and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics for periodic distribution of bridges and different burning dynamics are analyzed and compared. Analytical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

Exact Solutions of Burnt-Bridge Models for Molecular Motor Transport

NASA Astrophysics Data System (ADS)

Morozov, Alexander; Pronina, Ekaterina; Kolomeisky, Anatoly; Artyomov, Maxim

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called ``bridges''), is investigated theoretically by analyzing discrete-state stochastic ``burnt-bridge'' models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed (``burned'') with a probability p, creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For general case of p<1 a new theoretical method is developed, and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics, periodic and random distribution of bridges and different burning dynamics are analyzed and compared. Theoretical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

Solutions of burnt-bridge models for molecular motor transport

NASA Astrophysics Data System (ADS)

Morozov, Alexander Yu.; Pronina, Ekaterina; Kolomeisky, Anatoly B.; Artyomov, Maxim N.

2007-03-01

Transport of molecular motors, stimulated by interactions with specific links between consecutive binding sites (called “bridges”), is investigated theoretically by analyzing discrete-state stochastic “burnt-bridge” models. When an unbiased diffusing particle crosses the bridge, the link can be destroyed (“burned”) with a probability p , creating a biased directed motion for the particle. It is shown that for probability of burning p=1 the system can be mapped into a one-dimensional single-particle hopping model along the periodic infinite lattice that allows one to calculate exactly all dynamic properties. For the general case of p<1 a theoretical method is developed and dynamic properties are computed explicitly. Discrete-time and continuous-time dynamics for periodic distribution of bridges and different burning dynamics are analyzed and compared. Analytical predictions are supported by extensive Monte Carlo computer simulations. Theoretical results are applied for analysis of the experiments on collagenase motor proteins.

A Force Balanced Fragmentation Method for ab Initio Molecular Dynamic Simulation of Protein.

PubMed

Xu, Mingyuan; Zhu, Tong; Zhang, John Z H

2018-01-01

A force balanced generalized molecular fractionation with conjugate caps (FB-GMFCC) method is proposed for ab initio molecular dynamic simulation of proteins. In this approach, the energy of the protein is computed by a linear combination of the QM energies of individual residues and molecular fragments that account for the two-body interaction of hydrogen bond between backbone peptides. The atomic forces on the caped H atoms were corrected to conserve the total force of the protein. Using this approach, ab initio molecular dynamic simulation of an Ace-(ALA) 9 -NME linear peptide showed the conservation of the total energy of the system throughout the simulation. Further a more robust 110 ps ab initio molecular dynamic simulation was performed for a protein with 56 residues and 862 atoms in explicit water. Compared with the classical force field, the ab initio molecular dynamic simulations gave better description of the geometry of peptide bonds. Although further development is still needed, the current approach is highly efficient, trivially parallel, and can be applied to ab initio molecular dynamic simulation study of large proteins.

Analogs of methyllycaconitine as novel noncompetitive inhibitors of nicotinic receptors: pharmacological characterization, computational modeling, and pharmacophore development.

PubMed

McKay, Dennis B; Chang, Cheng; González-Cestari, Tatiana F; McKay, Susan B; El-Hajj, Raed A; Bryant, Darrell L; Zhu, Michael X; Swaan, Peter W; Arason, Kristjan M; Pulipaka, Aravinda B; Orac, Crina M; Bergmeier, Stephen C

2007-05-01

As a novel approach to drug discovery involving neuronal nicotinic acetylcholine receptors (nAChRs), our laboratory targeted nonagonist binding sites (i.e., noncompetitive binding sites, negative allosteric binding sites) located on nAChRs. Cultured bovine adrenal cells were used as neuronal models to investigate interactions of 67 analogs of methyllycaconitine (MLA) on native alpha3beta4* nAChRs. The availability of large numbers of structurally related molecules presents a unique opportunity for the development of pharmacophore models for noncompetitive binding sites. Our MLA analogs inhibited nicotine-mediated functional activation of both native and recombinant alpha3beta4* nAChRs with a wide range of IC(50) values (0.9-115 microM). These analogs had little or no inhibitory effects on agonist binding to native or recombinant nAChRs, supporting noncompetitive inhibitory activity. Based on these data, two highly predictive 3D quantitative structure-activity relationship (comparative molecular field analysis and comparative molecular similarity index analysis) models were generated. These computational models were successfully validated and provided insights into the molecular interactions of MLA analogs with nAChRs. In addition, a pharmacophore model was constructed to analyze and visualize the binding requirements to the analog binding site. The pharmacophore model was subsequently applied to search structurally diverse molecular databases to prospectively identify novel inhibitors. The rapid identification of eight molecules from database mining and our successful demonstration of in vitro inhibitory activity support the utility of these computational models as novel tools for the efficient retrieval of inhibitors. These results demonstrate the effectiveness of computational modeling and pharmacophore development, which may lead to the identification of new therapeutic drugs that target novel sites on nAChRs.

Long Range Debye-Hückel Correction for Computation of Grid-based Electrostatic Forces Between Biomacromolecules

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

Mereghetti, Paolo; Martinez, M.; Wade, Rebecca C.

Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulatemore » solutions of bovine serum albumin and of hen egg white lysozyme.« less

Car and Parrinello meet Green and Kubo: simulating atomic heat transport from equilibrium ab initio molecular dynamics

NASA Astrophysics Data System (ADS)

Baroni, Stefano

Modern simulation methods based on electronic-structure theory have long been deemed unfit to compute heat transport coefficients within the Green-Kubo formalism. This is so because the quantum-mechanical energy density from which the heat flux is derived is inherently ill defined, thus allegedly hampering the use of the Green-Kubo formula. While this objection would actually apply to classical systems as well, I will demonstrate that the thermal conductivity is indeed independent of the specific microscopic expression for the energy density and current from which it is derived. This fact results from a kind of gauge invariance stemming from energy conservation and extensivity, which I will illustrate numerically for a classical Lennard-Jones fluid. I will then introduce an expression for the adiabatic energy flux, derived within density-functional theory, that allows simulating atomic heat transport using equilibrium ab initio molecular dynamics. The resulting methodology is demonstrated by comparing results from ab-initio and classical molecular-dynamics simulations of a model liquid-Argon system, for which accurate inter-atomic potentials are derived by the force-matching method, and applied to compute the thermal conductivity of heavy water at ambient conditions. The problem of evaluating transport coefficients along with their accuracy from relatively short trajectories is finally addressed and discussed with a few representative examples. Partially funded by the European Union through the MaX Centre of Excellence (Grant No. 676598).

Electric-field-driven electron-transfer in mixed-valence molecules

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

Blair, Enrique P., E-mail: enrique-blair@baylor.edu; Corcelli, Steven A., E-mail: scorcell@nd.edu; Lent, Craig S., E-mail: lent@nd.edu

2016-07-07

Molecular quantum-dot cellular automata is a computing paradigm in which digital information is encoded by the charge configuration of a mixed-valence molecule. General-purpose computing can be achieved by arranging these compounds on a substrate and exploiting intermolecular Coulombic coupling. The operation of such a device relies on nonequilibrium electron transfer (ET), whereby the time-varying electric field of one molecule induces an ET event in a neighboring molecule. The magnitude of the electric fields can be quite large because of close spatial proximity, and the induced ET rate is a measure of the nonequilibrium response of the molecule. We calculate themore » electric-field-driven ET rate for a model mixed-valence compound. The mixed-valence molecule is regarded as a two-state electronic system coupled to a molecular vibrational mode, which is, in turn, coupled to a thermal environment. Both the electronic and vibrational degrees-of-freedom are treated quantum mechanically, and the dissipative vibrational-bath interaction is modeled with the Lindblad equation. This approach captures both tunneling and nonadiabatic dynamics. Relationships between microscopic molecular properties and the driven ET rate are explored for two time-dependent applied fields: an abruptly switched field and a linearly ramped field. In both cases, the driven ET rate is only weakly temperature dependent. When the model is applied using parameters appropriate to a specific mixed-valence molecule, diferrocenylacetylene, terahertz-range ET transfer rates are predicted.« less

High-Performance Computational Analysis of Glioblastoma Pathology Images with Database Support Identifies Molecular and Survival Correlates.

PubMed

Kong, Jun; Wang, Fusheng; Teodoro, George; Cooper, Lee; Moreno, Carlos S; Kurc, Tahsin; Pan, Tony; Saltz, Joel; Brat, Daniel

2013-12-01

In this paper, we present a novel framework for microscopic image analysis of nuclei, data management, and high performance computation to support translational research involving nuclear morphometry features, molecular data, and clinical outcomes. Our image analysis pipeline consists of nuclei segmentation and feature computation facilitated by high performance computing with coordinated execution in multi-core CPUs and Graphical Processor Units (GPUs). All data derived from image analysis are managed in a spatial relational database supporting highly efficient scientific queries. We applied our image analysis workflow to 159 glioblastomas (GBM) from The Cancer Genome Atlas dataset. With integrative studies, we found statistics of four specific nuclear features were significantly associated with patient survival. Additionally, we correlated nuclear features with molecular data and found interesting results that support pathologic domain knowledge. We found that Proneural subtype GBMs had the smallest mean of nuclear Eccentricity and the largest mean of nuclear Extent, and MinorAxisLength. We also found gene expressions of stem cell marker MYC and cell proliferation maker MKI67 were correlated with nuclear features. To complement and inform pathologists of relevant diagnostic features, we queried the most representative nuclear instances from each patient population based on genetic and transcriptional classes. Our results demonstrate that specific nuclear features carry prognostic significance and associations with transcriptional and genetic classes, highlighting the potential of high throughput pathology image analysis as a complementary approach to human-based review and translational research.

Computational design of protein interactions: designing proteins that neutralize influenza by inhibiting its hemagglutinin surface protein

NASA Astrophysics Data System (ADS)

Fleishman, Sarel

2012-02-01

Molecular recognition underlies all life processes. Design of interactions not seen in nature is a test of our understanding of molecular recognition and could unlock the vast potential of subtle control over molecular interaction networks, allowing the design of novel diagnostics and therapeutics for basic and applied research. We developed the first general method for designing protein interactions. The method starts by computing a region of high affinity interactions between dismembered amino acid residues and the target surface and then identifying proteins that can harbor these residues. Designs are tested experimentally for binding the target surface and successful ones are affinity matured using yeast cell surface display. Applied to the conserved stem region of influenza hemagglutinin we designed two unrelated proteins that, following affinity maturation, bound hemagglutinin at subnanomolar dissociation constants. Co-crystal structures of hemagglutinin bound to the two designed binders were within 1Angstrom RMSd of their models, validating the accuracy of the design strategy. One of the designed proteins inhibits the conformational changes that underlie hemagglutinin's cell-invasion functions and blocks virus infectivity in cell culture, suggesting that such proteins may in future serve as diagnostics and antivirals against a wide range of pathogenic influenza strains. We have used this method to obtain experimentally validated binders of several other target proteins, demonstrating the generality of the approach. We discuss the combination of modeling and high-throughput characterization of design variants which has been key to the success of this approach, as well as how we have used the data obtained in this project to enhance our understanding of molecular recognition. References: Science 332:816 JMB, in press Protein Sci 20:753

DROIDS 1.20: A GUI-Based Pipeline for GPU-Accelerated Comparative Protein Dynamics.

PubMed

Babbitt, Gregory A; Mortensen, Jamie S; Coppola, Erin E; Adams, Lily E; Liao, Justin K

2018-03-13

Traditional informatics in comparative genomics work only with static representations of biomolecules (i.e., sequence and structure), thereby ignoring the molecular dynamics (MD) of proteins that define function in the cell. A comparative approach applied to MD would connect this very short timescale process, defined in femtoseconds, to one of the longest in the universe: molecular evolution measured in millions of years. Here, we leverage advances in graphics-processing-unit-accelerated MD simulation software to develop a comparative method of MD analysis and visualization that can be applied to any two homologous Protein Data Bank structures. Our open-source pipeline, DROIDS (Detecting Relative Outlier Impacts in Dynamic Simulations), works in conjunction with existing molecular modeling software to convert any Linux gaming personal computer into a "comparative computational microscope" for observing the biophysical effects of mutations and other chemical changes in proteins. DROIDS implements structural alignment and Benjamini-Hochberg-corrected Kolmogorov-Smirnov statistics to compare nanosecond-scale atom bond fluctuations on the protein backbone, color mapping the significant differences identified in protein MD with single-amino-acid resolution. DROIDS is simple to use, incorporating graphical user interface control for Amber16 MD simulations, cpptraj analysis, and the final statistical and visual representations in R graphics and UCSF Chimera. We demonstrate that DROIDS can be utilized to visually investigate molecular evolution and disease-related functional changes in MD due to genetic mutation and epigenetic modification. DROIDS can also be used to potentially investigate binding interactions of pharmaceuticals, toxins, or other biomolecules in a functional evolutionary context as well. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Analytic second derivative of the energy for density functional theory based on the three-body fragment molecular orbital method

NASA Astrophysics Data System (ADS)

Nakata, Hiroya; Fedorov, Dmitri G.; Zahariev, Federico; Schmidt, Michael W.; Kitaura, Kazuo; Gordon, Mark S.; Nakamura, Shinichiro

2015-03-01

Analytic second derivatives of the energy with respect to nuclear coordinates have been developed for spin restricted density functional theory (DFT) based on the fragment molecular orbital method (FMO). The derivations were carried out for the three-body expansion (FMO3), and the two-body expressions can be obtained by neglecting the three-body corrections. Also, the restricted Hartree-Fock (RHF) Hessian for FMO3 can be obtained by neglecting the density-functional related terms. In both the FMO-RHF and FMO-DFT Hessians, certain terms with small magnitudes are neglected for computational efficiency. The accuracy of the FMO-DFT Hessian in terms of the Gibbs free energy is evaluated for a set of polypeptides and water clusters and found to be within 1 kcal/mol of the corresponding full (non-fragmented) ab initio calculation. The FMO-DFT method is also applied to transition states in SN2 reactions and for the computation of the IR and Raman spectra of a small Trp-cage protein (PDB: 1L2Y). Some computational timing analysis is also presented.

A systematic molecular dynamics approach to the study of peptide Keap1-Nrf2 protein-protein interaction inhibitors and its application to p62 peptides.

PubMed

Lu, Meng-Chen; Yuan, Zhen-Wei; Jiang, Yong-Lin; Chen, Zhi-Yun; You, Qi-Dong; Jiang, Zheng-Yu

2016-04-01

Protein-protein interactions (PPIs) as drug targets have been gaining growing interest, though developing drug-like small molecule PPI inhibitors remains challenging. Peptide PPI inhibitors, which can provide informative data on the PPI interface, are good starting points to develop small molecule modulators. Computational methods combining molecular dynamics simulations and binding energy calculations could give both the structural and the energetic perspective of peptide PPI inhibitors. Herein, we set up a computational workflow to investigate Keap1-Nrf2 peptide PPI inhibitors and predict the activity of novel sequences. Furthermore, we applied this method to investigate p62 peptides as PPI inhibitors of Keap1-Nrf2 and explored the activity change induced by the phosphorylation of serine. Our results showed that because of the unfavorable solvation effects, the binding affinity of the phosphorylated p62 peptide is lower than the Nrf2 ETGE peptide. Our research results not only provide a useful method to investigate the Keap1-Nrf2 peptide inhibitors, but also give a good example to show how to incorporate computational methods into the study of peptide PPI inhibitors. Besides, applying this method to p62 peptides provides a detailed explanation for the expression of cytoprotective Nrf2 targets induced by p62 phosphorylation, which may benefit the further study of the crosstalk between the Keap1-Nrf2 pathway and p62-mediated selective autophagy.

Self-consistent molecular dynamics formulation for electric-field-mediated electrolyte transport through nanochannels

NASA Astrophysics Data System (ADS)

Raghunathan, A. V.; Aluru, N. R.

2007-07-01

A self-consistent molecular dynamics (SCMD) formulation is presented for electric-field-mediated transport of water and ions through a nanochannel connected to reservoirs or baths. The SCMD formulation is compared with a uniform field MD approach, where the applied electric field is assumed to be uniform, for 2nm and 3.5nm wide nanochannels immersed in a 0.5M KCl solution. Reservoir ionic concentrations are maintained using the dual-control-volume grand canonical molecular dynamics technique. Simulation results with varying channel height indicate that the SCMD approach calculates the electrostatic potential in the simulation domain more accurately compared to the uniform field approach, with the deviation in results increasing with the channel height. The translocation times and ionic fluxes predicted by uniform field MD can be substantially different from those predicted by the SCMD approach. Our results also indicate that during a 2ns simulation time K+ ions can permeate through a 1nm channel when the applied electric field is computed self-consistently, while the permeation is not observed when the electric field is assumed to be uniform.

Nuclear quadrupole resonance lineshape analysis for different motional models: Stochastic Liouville approach

NASA Astrophysics Data System (ADS)

Kruk, D.; Earle, K. A.; Mielczarek, A.; Kubica, A.; Milewska, A.; Moscicki, J.

2011-12-01

A general theory of lineshapes in nuclear quadrupole resonance (NQR), based on the stochastic Liouville equation, is presented. The description is valid for arbitrary motional conditions (particularly beyond the valid range of perturbation approaches) and interaction strengths. It can be applied to the computation of NQR spectra for any spin quantum number and for any applied magnetic field. The treatment presented here is an adaptation of the "Swedish slow motion theory," [T. Nilsson and J. Kowalewski, J. Magn. Reson. 146, 345 (2000), 10.1006/jmre.2000.2125] originally formulated for paramagnetic systems, to NQR spectral analysis. The description is formulated for simple (Brownian) diffusion, free diffusion, and jump diffusion models. The two latter models account for molecular cooperativity effects in dense systems (such as liquids of high viscosity or molecular glasses). The sensitivity of NQR slow motion spectra to the mechanism of the motional processes modulating the nuclear quadrupole interaction is discussed.

Computational Nanotechnology of Molecular Materials, Electronics, and Actuators with Carbon Nanotubes and Fullerenes

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Menon, Madhu; Cho, Kyeongjae; Biegel, Bryan (Technical Monitor)

2001-01-01

The role of computational nanotechnology in developing next generation of multifunctional materials, molecular scale electronic and computing devices, sensors, actuators, and machines is described through a brief review of enabling computational techniques and few recent examples derived from computer simulations of carbon nanotube based molecular nanotechnology.

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

PubMed

Hathout, Rania M; Metwally, Abdelkader A

2016-11-01

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

Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations.

PubMed

Wu, Jingheng; Shen, Lin; Yang, Weitao

2017-10-28

Ab initio quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulation is a useful tool to calculate thermodynamic properties such as potential of mean force for chemical reactions but intensely time consuming. In this paper, we developed a new method using the internal force correction for low-level semiempirical QM/MM molecular dynamics samplings with a predefined reaction coordinate. As a correction term, the internal force was predicted with a machine learning scheme, which provides a sophisticated force field, and added to the atomic forces on the reaction coordinate related atoms at each integration step. We applied this method to two reactions in aqueous solution and reproduced potentials of mean force at the ab initio QM/MM level. The saving in computational cost is about 2 orders of magnitude. The present work reveals great potentials for machine learning in QM/MM simulations to study complex chemical processes.

`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.

A computer model for one-dimensional mass and energy transport in and around chemically reacting particles, including complex gas-phase chemistry, multicomponent molecular diffusion, surface evaporation, and heterogeneous reaction

NASA Technical Reports Server (NTRS)

Cho, S. Y.; Yetter, R. A.; Dryer, F. L.

1992-01-01

Various chemically reacting flow problems highlighting chemical and physical fundamentals rather than flow geometry are presently investigated by means of a comprehensive mathematical model that incorporates multicomponent molecular diffusion, complex chemistry, and heterogeneous processes, in the interest of obtaining sensitivity-related information. The sensitivity equations were decoupled from those of the model, and then integrated one time-step behind the integration of the model equations, and analytical Jacobian matrices were applied to improve the accuracy of sensitivity coefficients that are calculated together with model solutions.

Theoretical study of optical activity of 1:1 hydrogen bond complexes of water with S-warfarin

NASA Astrophysics Data System (ADS)

Dadsetani, Mehrdad; Abdolmaleki, Ahmad; Zabardasti, Abedin

2016-11-01

The molecular interaction between S-warfarin (SW) and a single water molecule was investigated using the B3LYP method at 6-311 ++G(d,p) basis set. The vibrational spectra of the optimized complexes have been investigated for stabilization checking. Quantum theories of atoms in molecules, natural bond orbitals, molecular electrostatic potentials and energy decomposition analysis methods have been applied to analyze the intermolecular interactions. The intermolecular charge transfer in the most stable complex is in the opposite direction from those in the other complexes. The optical spectra and the hyperpolarizabilities of SW-water hydrogen bond complexes have been computed.

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

Nabeel, A.; Khan, M.A.; Husain, S.

Coal is the most abundant source of energy. However, there is a need to develop cleaner, and more efficient, economical, and convenient coal conversion technologies. It is important to understand the organic chemical structure of coal for achieving real breakthroughs in the development of such coal conversion technologies. A novel computer-assisted modeling technique based on the analysis of {sup 13}C NMR and gel permeation chromatography has been applied to predict the average molecular structure of the acetylated product of a depolymerized bituminous Indian coal. The proposed molecular structure may be of practical use in understanding the mechanism of coal conversionsmore » during the processes of liquefaction, gasification, combustion, and carbonization.« less

Nonlinear electromagnetic interactions in energetic materials

DOE PAGES

Wood, Mitchell Anthony; Dalvit, Diego Alejandro; Moore, David Steven

2016-01-12

We study the scattering of electromagnetic waves in anisotropic energetic materials. Nonlinear light-matter interactions in molecular crystals result in frequency-conversion and polarization changes. Applied electromagnetic fields of moderate intensity can induce these nonlinear effects without triggering chemical decomposition, offering a mechanism for the nonionizing identification of explosives. We use molecular-dynamics simulations to compute such two-dimensional THz spectra for planar slabs made of pentaerythritol tetranitrate and ammonium nitrate. Finally, we discuss third-harmonic generation and polarization-conversion processes in such materials. These observed far-field spectral features of the reflected or transmitted light may serve as an alternative tool for standoff explosive detection.

Carrier mobility in double-helix DNA and RNA: A quantum chemistry study with Marcus-Hush theory.

PubMed

Wu, Tao; Sun, Lei; Shi, Qi; Deng, Kaiming; Deng, Weiqiao; Lu, Ruifeng

2016-12-21

Charge mobilities of six DNAs and RNAs have been computed using quantum chemistry calculation combined with the Marcus-Hush theory. Based on this simulation model, we obtained quite reasonable results when compared with the experiment, and the obtained charge mobility strongly depends on the molecular reorganization and electronic coupling. Besides, we find that hole mobilities are larger than electron mobilities no matter in DNAs or in RNAs, and the hole mobility of 2L8I can reach 1.09 × 10 -1 cm 2 V -1 s -1 which can be applied in the molecular wire. The findings also show that our theoretical model can be regarded as a promising candidate for screening DNA- and RNA-based molecular electronic devices.

Carrier mobility in double-helix DNA and RNA: A quantum chemistry study with Marcus-Hush theory

NASA Astrophysics Data System (ADS)

Wu, Tao; Sun, Lei; Shi, Qi; Deng, Kaiming; Deng, Weiqiao; Lu, Ruifeng

2016-12-01

Charge mobilities of six DNAs and RNAs have been computed using quantum chemistry calculation combined with the Marcus-Hush theory. Based on this simulation model, we obtained quite reasonable results when compared with the experiment, and the obtained charge mobility strongly depends on the molecular reorganization and electronic coupling. Besides, we find that hole mobilities are larger than electron mobilities no matter in DNAs or in RNAs, and the hole mobility of 2L8I can reach 1.09 × 10-1 cm2 V-1 s-1 which can be applied in the molecular wire. The findings also show that our theoretical model can be regarded as a promising candidate for screening DNA- and RNA-based molecular electronic devices.

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

DOE PAGES

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.; ...

2017-02-23

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

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

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

Molecular dynamics coupled with a virtual system for effective conformational sampling.

PubMed

Hayami, Tomonori; Kasahara, Kota; Nakamura, Haruki; Higo, Junichi

2018-07-15

An enhanced conformational sampling method is proposed: virtual-system coupled canonical molecular dynamics (VcMD). Although VcMD enhances sampling along a reaction coordinate, this method is free from estimation of a canonical distribution function along the reaction coordinate. This method introduces a virtual system that does not necessarily obey a physical law. To enhance sampling the virtual system couples with a molecular system to be studied. Resultant snapshots produce a canonical ensemble. This method was applied to a system consisting of two short peptides in an explicit solvent. Conventional molecular dynamics simulation, which is ten times longer than VcMD, was performed along with adaptive umbrella sampling. Free-energy landscapes computed from the three simulations mutually converged well. The VcMD provided quicker association/dissociation motions of peptides than the conventional molecular dynamics did. The VcMD method is applicable to various complicated systems because of its methodological simplicity. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

Selection of effective cocrystals former for dissolution rate improvement of active pharmaceutical ingredients based on lipoaffinity index.

PubMed

Cysewski, Piotr; Przybyłek, Maciej

2017-09-30

New theoretical screening procedure was proposed for appropriate selection of potential cocrystal formers possessing the ability of enhancing dissolution rates of drugs. The procedure relies on the training set comprising 102 positive and 17 negative cases of cocrystals found in the literature. Despite the fact that the only available data were of qualitative character, performed statistical analysis using binary classification allowed to formulate quantitative criterions. Among considered 3679 molecular descriptors the relative value of lipoaffinity index, expressed as the difference between values calculated for active compound and excipient, has been found as the most appropriate measure suited for discrimination of positive and negative cases. Assuming 5% precision, the applied classification criterion led to inclusion of 70% positive cases in the final prediction. Since lipoaffinity index is a molecular descriptor computed using only 2D information about a chemical structure, its estimation is straightforward and computationally inexpensive. The inclusion of an additional criterion quantifying the cocrystallization probability leads to the following conjunction criterions H mix <-0.18 and ΔLA>3.61, allowing for identification of dissolution rate enhancers. The screening procedure was applied for finding the most promising coformers of such drugs as Iloperidone, Ritonavir, Carbamazepine and Enthenzamide. Copyright © 2017 Elsevier B.V. All rights reserved.

Monte Carlo estimation of total variation distance of Markov chains on large spaces, with application to phylogenetics.

PubMed

Herbei, Radu; Kubatko, Laura

2013-03-26

Markov chains are widely used for modeling in many areas of molecular biology and genetics. As the complexity of such models advances, it becomes increasingly important to assess the rate at which a Markov chain converges to its stationary distribution in order to carry out accurate inference. A common measure of convergence to the stationary distribution is the total variation distance, but this measure can be difficult to compute when the state space of the chain is large. We propose a Monte Carlo method to estimate the total variation distance that can be applied in this situation, and we demonstrate how the method can be efficiently implemented by taking advantage of GPU computing techniques. We apply the method to two Markov chains on the space of phylogenetic trees, and discuss the implications of our findings for the development of algorithms for phylogenetic inference.

Molecular-dynamics simulations of self-assembled monolayers (SAM) on parallel computers

NASA Astrophysics Data System (ADS)

Vemparala, Satyavani

The purpose of this dissertation is to investigate the properties of self-assembled monolayers, particularly alkanethiols and Poly (ethylene glycol) terminated alkanethiols. These simulations are based on realistic interatomic potentials and require scalable and portable multiresolution algorithms implemented on parallel computers. Large-scale molecular dynamics simulations of self-assembled alkanethiol monolayer systems have been carried out using an all-atom model involving a million atoms to investigate their structural properties as a function of temperature, lattice spacing and molecular chain-length. Results show that the alkanethiol chains tilt from the surface normal by a collective angle of 25° along next-nearest neighbor direction at 300K. At 350K the system transforms to a disordered phase characterized by small tilt angle, flexible tilt direction, and random distribution of backbone planes. With increasing lattice spacing, a, the tilt angle increases rapidly from a nearly zero value at a = 4.7A to as high as 34° at a = 5.3A at 300K. We also studied the effect of end groups on the tilt structure of SAM films. We characterized the system with respect to temperature, the alkane chain length, lattice spacing, and the length of the end group. We found that the gauche defects were predominant only in the tails, and the gauche defects increased with the temperature and number of EG units. Effect of electric field on the structure of poly (ethylene glycol) (PEG) terminated alkanethiol self assembled monolayer (SAM) on gold has been studied using parallel molecular dynamics method. An applied electric field triggers a conformational transition from all-trans to a mostly gauche conformation. The polarity of the electric field has a significant effect on the surface structure of PEG leading to a profound effect on the hydrophilicity of the surface. The electric field applied anti-parallel to the surface normal causes a reversible transition to an ordered state in which the oxygen atoms are exposed. On the other hand, an electric field applied in a direction parallel to the surface normal introduces considerable disorder in the system and the oxygen atoms are buried inside.

Probability distributions of molecular observables computed from Markov models. II. Uncertainties in observables and their time-evolution

NASA Astrophysics Data System (ADS)

Chodera, John D.; Noé, Frank

2010-09-01

Discrete-state Markov (or master equation) models provide a useful simplified representation for characterizing the long-time statistical evolution of biomolecules in a manner that allows direct comparison with experiments as well as the elucidation of mechanistic pathways for an inherently stochastic process. A vital part of meaningful comparison with experiment is the characterization of the statistical uncertainty in the predicted experimental measurement, which may take the form of an equilibrium measurement of some spectroscopic signal, the time-evolution of this signal following a perturbation, or the observation of some statistic (such as the correlation function) of the equilibrium dynamics of a single molecule. Without meaningful error bars (which arise from both approximation and statistical error), there is no way to determine whether the deviations between model and experiment are statistically meaningful. Previous work has demonstrated that a Bayesian method that enforces microscopic reversibility can be used to characterize the statistical component of correlated uncertainties in state-to-state transition probabilities (and functions thereof) for a model inferred from molecular simulation data. Here, we extend this approach to include the uncertainty in observables that are functions of molecular conformation (such as surrogate spectroscopic signals) characterizing each state, permitting the full statistical uncertainty in computed spectroscopic experiments to be assessed. We test the approach in a simple model system to demonstrate that the computed uncertainties provide a useful indicator of statistical variation, and then apply it to the computation of the fluorescence autocorrelation function measured for a dye-labeled peptide previously studied by both experiment and simulation.

Universal programmable quantum circuit schemes to emulate an operator

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

Daskin, Anmer; Grama, Ananth; Kollias, Giorgos

Unlike fixed designs, programmable circuit designs support an infinite number of operators. The functionality of a programmable circuit can be altered by simply changing the angle values of the rotation gates in the circuit. Here, we present a new quantum circuit design technique resulting in two general programmable circuit schemes. The circuit schemes can be used to simulate any given operator by setting the angle values in the circuit. This provides a fixed circuit design whose angles are determined from the elements of the given matrix-which can be non-unitary-in an efficient way. We also give both the classical and quantummore » complexity analysis for these circuits and show that the circuits require a few classical computations. For the electronic structure simulation on a quantum computer, one has to perform the following steps: prepare the initial wave function of the system; present the evolution operator U=e{sup -iHt} for a given atomic and molecular Hamiltonian H in terms of quantum gates array and apply the phase estimation algorithm to find the energy eigenvalues. Thus, in the circuit model of quantum computing for quantum chemistry, a crucial step is presenting the evolution operator for the atomic and molecular Hamiltonians in terms of quantum gate arrays. Since the presented circuit designs are independent from the matrix decomposition techniques and the global optimization processes used to find quantum circuits for a given operator, high accuracy simulations can be done for the unitary propagators of molecular Hamiltonians on quantum computers. As an example, we show how to build the circuit design for the hydrogen molecule.« less

78 FR 59927 - Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-30

... Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology..., Computational, and Systems Biology [External Review Draft]'' (EPA/600/R-13/214A). EPA is also announcing that... Advances in Molecular, Computational, and Systems Biology [External Review Draft]'' is available primarily...

78 FR 68058 - Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-13

... Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology... Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology..., computational, and systems biology data can better inform risk assessment. This draft document is available for...

Discover binding pathways using the sliding binding-box docking approach: application to binding pathways of oseltamivir to avian influenza H5N1 neuraminidase

NASA Astrophysics Data System (ADS)

Tran, Diem-Trang T.; Le, Ly T.; Truong, Thanh N.

2013-08-01

Drug binding and unbinding are transient processes which are hardly observed by experiment and difficult to analyze by computational techniques. In this paper, we employed a cost-effective method called "pathway docking" in which molecular docking was used to screen ligand-receptor binding free energy surface to reveal possible paths of ligand approaching protein binding pocket. A case study was applied on oseltamivir, the key drug against influenza a virus. The equilibrium pathways identified by this method are found to be similar to those identified in prior studies using highly expensive computational approaches.

In Silico Exploration of 1,7-Diazacarbazole Analogs as Checkpoint Kinase 1 Inhibitors by Using 3D QSAR, Molecular Docking Study, and Molecular Dynamics Simulations.

PubMed

Gao, Xiaodong; Han, Liping; Ren, Yujie

2016-05-05

Checkpoint kinase 1 (Chk1) is an important serine/threonine kinase with a self-protection function. The combination of Chk1 inhibitors and anti-cancer drugs can enhance the selectivity of tumor therapy. In this work, a set of 1,7-diazacarbazole analogs were identified as potent Chk1 inhibitors through a series of computer-aided drug design processes, including three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking, and molecular dynamics simulations. The optimal QSAR models showed significant cross-validated correlation q² values (0.531, 0.726), fitted correlation r² coefficients (higher than 0.90), and standard error of prediction (less than 0.250). These results suggested that the developed models possess good predictive ability. Moreover, molecular docking and molecular dynamics simulations were applied to highlight the important interactions between the ligand and the Chk1 receptor protein. This study shows that hydrogen bonding and electrostatic forces are key interactions that confer bioactivity.

Molecular Modeling Studies of 4,5-Dihydro-1H-pyrazolo[4,3-h] quinazoline Derivatives as Potent CDK2/Cyclin A Inhibitors Using 3D-QSAR and Docking

PubMed Central

Ai, Yong; Wang, Shao-Teng; Sun, Ping-Hua; Song, Fa-Jun

2010-01-01

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r2cv values of 0.747 and 0.518 and r2 values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity. PMID:21152296

Molecular modeling studies of 4,5-dihydro-1H-pyrazolo[4,3-h] quinazoline derivatives as potent CDK2/Cyclin a inhibitors using 3D-QSAR and docking.

PubMed

Ai, Yong; Wang, Shao-Teng; Sun, Ping-Hua; Song, Fa-Jun

2010-09-28

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r(2) (cv) values of 0.747 and 0.518 and r(2) values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.

Computational deconvolution of genome wide expression data from Parkinson's and Huntington's disease brain tissues using population-specific expression analysis

PubMed Central

Capurro, Alberto; Bodea, Liviu-Gabriel; Schaefer, Patrick; Luthi-Carter, Ruth; Perreau, Victoria M.

2015-01-01

The characterization of molecular changes in diseased tissues gives insight into pathophysiological mechanisms and is important for therapeutic development. Genome-wide gene expression analysis has proven valuable for identifying biological processes in neurodegenerative diseases using post mortem human brain tissue and numerous datasets are publically available. However, many studies utilize heterogeneous tissue samples consisting of multiple cell types, all of which contribute to global gene expression values, confounding biological interpretation of the data. In particular, changes in numbers of neuronal and glial cells occurring in neurodegeneration confound transcriptomic analyses, particularly in human brain tissues where sample availability and controls are limited. To identify cell specific gene expression changes in neurodegenerative disease, we have applied our recently published computational deconvolution method, population specific expression analysis (PSEA). PSEA estimates cell-type-specific expression values using reference expression measures, which in the case of brain tissue comprises mRNAs with cell-type-specific expression in neurons, astrocytes, oligodendrocytes and microglia. As an exercise in PSEA implementation and hypothesis development regarding neurodegenerative diseases, we applied PSEA to Parkinson's and Huntington's disease (PD, HD) datasets. Genes identified as differentially expressed in substantia nigra pars compacta neurons by PSEA were validated using external laser capture microdissection data. Network analysis and Annotation Clustering (DAVID) identified molecular processes implicated by differential gene expression in specific cell types. The results of these analyses provided new insights into the implementation of PSEA in brain tissues and additional refinement of molecular signatures in human HD and PD. PMID:25620908

Extended polarization in 3rd order SCC-DFTB from chemical potential equilization

PubMed Central

Kaminski, Steve; Giese, Timothy J.; Gaus, Michael; York, Darrin M.; Elstner, Marcus

2012-01-01

In this work we augment the approximate density functional method SCC-DFTB (DFTB3) with the chemical potential equilization (CPE) approach in order to improve the performance for molecular electronic polarizabilities. The CPE method, originally implemented for NDDO type methods by Giese and York, has been shown to emend minimal basis methods wrt response properties significantly, and has been applied to SCC-DFTB recently. CPE allows to overcome this inherent limitation of minimal basis methods by supplying an additional response density. The systematic underestimation is thereby corrected quantitatively without the need to extend the atomic orbital basis, i.e. without increasing the overall computational cost significantly. Especially the dependency of polarizability as a function of molecular charge state was significantly improved from the CPE extension of DFTB3. The empirical parameters introduced by the CPE approach were optimized for 172 organic molecules in order to match the results from density functional methods (DFT) methods using large basis sets. However, the first order derivatives of molecular polarizabilities, as e.g. required to compute Raman activities, are not improved by the current CPE implementation, i.e. Raman spectra are not improved. PMID:22894819

From Mollusks to Medicine: A Venomics Approach for the Discovery and Characterization of Therapeutics from Terebridae Peptide Toxins.

PubMed

Verdes, Aida; Anand, Prachi; Gorson, Juliette; Jannetti, Stephen; Kelly, Patrick; Leffler, Abba; Simpson, Danny; Ramrattan, Girish; Holford, Mandë

2016-04-19

Animal venoms comprise a diversity of peptide toxins that manipulate molecular targets such as ion channels and receptors, making venom peptides attractive candidates for the development of therapeutics to benefit human health. However, identifying bioactive venom peptides remains a significant challenge. In this review we describe our particular venomics strategy for the discovery, characterization, and optimization of Terebridae venom peptides, teretoxins. Our strategy reflects the scientific path from mollusks to medicine in an integrative sequential approach with the following steps: (1) delimitation of venomous Terebridae lineages through taxonomic and phylogenetic analyses; (2) identification and classification of putative teretoxins through omics methodologies, including genomics, transcriptomics, and proteomics; (3) chemical and recombinant synthesis of promising peptide toxins; (4) structural characterization through experimental and computational methods; (5) determination of teretoxin bioactivity and molecular function through biological assays and computational modeling; (6) optimization of peptide toxin affinity and selectivity to molecular target; and (7) development of strategies for effective delivery of venom peptide therapeutics. While our research focuses on terebrids, the venomics approach outlined here can be applied to the discovery and characterization of peptide toxins from any venomous taxa.

In vitro molecular machine learning algorithm via symmetric internal loops of DNA.

PubMed

Lee, Ji-Hoon; Lee, Seung Hwan; Baek, Christina; Chun, Hyosun; Ryu, Je-Hwan; Kim, Jin-Woo; Deaton, Russell; Zhang, Byoung-Tak

2017-08-01

Programmable biomolecules, such as DNA strands, deoxyribozymes, and restriction enzymes, have been used to solve computational problems, construct large-scale logic circuits, and program simple molecular games. Although studies have shown the potential of molecular computing, the capability of computational learning with DNA molecules, i.e., molecular machine learning, has yet to be experimentally verified. Here, we present a novel molecular learning in vitro model in which symmetric internal loops of double-stranded DNA are exploited to measure the differences between training instances, thus enabling the molecules to learn from small errors. The model was evaluated on a data set of twenty dialogue sentences obtained from the television shows Friends and Prison Break. The wet DNA-computing experiments confirmed that the molecular learning machine was able to generalize the dialogue patterns of each show and successfully identify the show from which the sentences originated. The molecular machine learning model described here opens the way for solving machine learning problems in computer science and biology using in vitro molecular computing with the data encoded in DNA molecules. Copyright © 2017. Published by Elsevier B.V.

Determination of structure and properties of molecular crystals from first principles.

PubMed

Szalewicz, Krzysztof

2014-11-18

CONSPECTUS: Until recently, it had been impossible to predict structures of molecular crystals just from the knowledge of the chemical formula for the constituent molecule(s). A solution of this problem has been achieved using intermolecular force fields computed from first principles. These fields were developed by calculating interaction energies of molecular dimers and trimers using an ab initio method called symmetry-adapted perturbation theory (SAPT) based on density-functional theory (DFT) description of monomers [SAPT(DFT)]. For clusters containing up to a dozen or so atoms, interaction energies computed using SAPT(DFT) are comparable in accuracy to the results of the best wave function-based methods, whereas the former approach can be applied to systems an order of magnitude larger than the latter. In fact, for monomers with a couple dozen atoms, SAPT(DFT) is about equally time-consuming as the supermolecular DFT approach. To develop a force field, SAPT(DFT) calculations are performed for a large number of dimer and possibly also trimer configurations (grid points in intermolecular coordinates), and the interaction energies are then fitted by analytic functions. The resulting force fields can be used to determine crystal structures and properties by applying them in molecular packing, lattice energy minimization, and molecular dynamics calculations. In this way, some of the first successful determinations of crystal structures were achieved from first principles, with crystal densities and lattice parameters agreeing with experimental values to within about 1%. Crystal properties obtained using similar procedures but empirical force fields fitted to crystal data have typical errors of several percent due to low sensitivity of empirical fits to interactions beyond those of the nearest neighbors. The first-principles approach has additional advantages over the empirical approach for notional crystals and cocrystals since empirical force fields can only be extrapolated to such cases. As an alternative to applying SAPT(DFT) in crystal structure calculations, one can use supermolecular DFT interaction energies combined with scaled dispersion energies computed from simple atom-atom functions, that is, use the so-called DFT+D approach. Whereas the standard DFT methods fail for intermolecular interactions, DFT+D performs reasonably well since the dispersion correction is used not only to provide the missing dispersion contribution but also to fix other deficiencies of DFT. The latter cancellation of errors is unphysical and can be avoided by applying the so-called dispersionless density functional, dlDF. In this case, the dispersion energies are added without any scaling. The dlDF+D method is also one of the best performing DFT+D methods. The SAPT(DFT)-based approach has been applied so far only to crystals with rigid monomers. It can be extended to partly flexible monomers, that is, to monomers with only a few internal coordinates allowed to vary. However, the costs will increase relative to rigid monomer cases since the number of grid points increases exponentially with the number of dimensions. One way around this problem is to construct force fields with approximate couplings between inter- and intramonomer degrees of freedom. Another way is to calculate interaction energies (and possibly forces) "on the fly", i.e., in each step of lattice energy minimization procedure. Such an approach would be prohibitively expensive if it replaced analytic force fields at all stages of the crystal predictions procedure, but it can be used to optimize a few dozen candidate structures determined by other methods.

Shape optimization of self-avoiding curves

NASA Astrophysics Data System (ADS)

Walker, Shawn W.

2016-04-01

This paper presents a softened notion of proximity (or self-avoidance) for curves. We then derive a sensitivity result, based on shape differential calculus, for the proximity. This is combined with a gradient-based optimization approach to compute three-dimensional, parameterized curves that minimize the sum of an elastic (bending) energy and a proximity energy that maintains self-avoidance by a penalization technique. Minimizers are computed by a sequential-quadratic-programming (SQP) method where the bending energy and proximity energy are approximated by a finite element method. We then apply this method to two problems. First, we simulate adsorbed polymer strands that are constrained to be bound to a surface and be (locally) inextensible. This is a basic model of semi-flexible polymers adsorbed onto a surface (a current topic in material science). Several examples of minimizing curve shapes on a variety of surfaces are shown. An advantage of the method is that it can be much faster than using molecular dynamics for simulating polymer strands on surfaces. Second, we apply our proximity penalization to the computation of ideal knots. We present a heuristic scheme, utilizing the SQP method above, for minimizing rope-length and apply it in the case of the trefoil knot. Applications of this method could be for generating good initial guesses to a more accurate (but expensive) knot-tightening algorithm.

HIV-TRACE (Transmission Cluster Engine): a tool for large scale molecular epidemiology of HIV-1 and other rapidly evolving pathogens.

PubMed

Kosakovsky Pond, Sergei L; Weaver, Steven; Leigh Brown, Andrew J; Wertheim, Joel O

2018-01-31

In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoeleather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, i.e., on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from github.com/veg/hivtrace, along with the accompanying result visualization module from github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens. © The Author 2018. 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.

Molecular engineering of cyanine dyes to design a panchromatic response in Co-sensitized dye-sensitized solar cells

DOE PAGES

Pepe, Giulio; Cole, Jacqueline M.; Waddell, Paul G.; ...

2016-04-05

Cyanines are optically tunable dyes with high molar extinction coefficients, suitable for applications in co-sensitized dye-sensitized solar cells (DSCs); yet, barely thus applied. This might be due to the lack of a rational molecular design strategy that efficiently exploits cyanine properties. This study computationally re-designs these dyes, to broaden their optical absorption spectrum and create dye···TiO 2 binding and co-sensitization functionality. This is achieved via a stepwise molecular engineering approach. Firstly, the structural and optical properties of four parent dyes are experimentally and computationally investigated: 3,3’-diethyloxacarbocyanine iodide, 3,3’-diethylthiacarbocyanine iodide, 3,3’-diethylthiadicarbocyanine iodide and 3,3’-diethylthiatricarbocyanine iodide. Secondly, the molecules are theoretically modifiedmore » and their energetics are analyzed and compared to the parent dyes. A dye···TiO 2 anchoring group (carboxylic or cyanoacrylic acid), absent from the parent dyes, is chemically substituted at different molecular positions to investigate changes in optical absorption. We find that cyanoacrylic acid substitution at the para-quinoidal position affects the absorption wavelength of all parent dyes, with an optimal bathochromic shift of ca. 40 nm. The theoretical lengthening of the polymethine chain is also shown to effect dye absorption. Two molecularly engineered dyes are proposed as promising co-sensitizers. Finally, corresponding dye···TiO 2 adsorption energy calculations corroborate their applicability, demonstrating the potential of cyanine dyes in DSC research.« less

Computational modeling of the effective Young's modulus values of fullerene molecules: a combined molecular dynamics simulation and continuum shell model.

PubMed

Ghavanloo, Esmaeal; Izadi, Razie; Nayebi, Ali

2018-02-28

Estimating the Young's modulus of a structure in the nanometer size range is a difficult task. The reliable determination of this parameter is, however, important in both basic and applied research. In this study, by combining molecular dynamics (MD) simulations and continuum shell theory, we designed a new approach to determining the Young's modulus values of different spherical fullerenes. The results indicate that the Young's modulus values of fullerene molecules decrease nonlinearly with increasing molecule size and understandably tend to the Young's modulus of an ideal flat graphene sheet at large molecular radii. To the best of our knowledge, this is first time that a combined atomistic-continuum method which can predict the Young's modulus values of fullerene molecules with high precision has been reported.

Evaluating data mining algorithms using molecular dynamics trajectories.

PubMed

Tatsis, Vasileios A; Tjortjis, Christos; Tzirakis, Panagiotis

2013-01-01

Molecular dynamics simulations provide a sample of a molecule's conformational space. Experiments on the mus time scale, resulting in large amounts of data, are nowadays routine. Data mining techniques such as classification provide a way to analyse such data. In this work, we evaluate and compare several classification algorithms using three data sets which resulted from computer simulations, of a potential enzyme mimetic biomolecule. We evaluated 65 classifiers available in the well-known data mining toolkit Weka, using 'classification' errors to assess algorithmic performance. Results suggest that: (i) 'meta' classifiers perform better than the other groups, when applied to molecular dynamics data sets; (ii) Random Forest and Rotation Forest are the best classifiers for all three data sets; and (iii) classification via clustering yields the highest classification error. Our findings are consistent with bibliographic evidence, suggesting a 'roadmap' for dealing with such data.

Potential energy curves of the Na2+ molecular ion from all-electron ab initio relativistic calculations

NASA Astrophysics Data System (ADS)

Bewicz, Anna; Musiał, Monika; Kucharski, Stanisław A.

2017-11-01

The equation-of-motion coupled-cluster method for electron affinity calculations has been used to study potential energy curves (PECs) for the Na+2 molecular ion. Although the studied molecule represents the open shell system the applied approach employs the closed shell Na+ 22 ion as the reference. In addition the Na+ 22 system dissociates into the closed shell fragments; hence, the restricted Hartree-Fock scheme can be used within the whole range of interatomic distances, from 2 to 45 Å. We used large basis set engaging 268 basis functions with all 21 electrons correlated. The relativistic effects are included via second-order Douglas-Kroll method. The computed PECs, spectroscopic molecular constants and vibrational energy levels agree well with experimental values if the latter are available or with other theoretical data.

Application of molecular dynamics simulation to predict the compatability between water-insoluble drugs and self-associating poly(ethylene oxide)-b-poly(epsilon-caprolactone) block copolymers.

PubMed

Patel, Sarthak; Lavasanifar, Afsaneh; Choi, Phillip

2008-11-01

In the present work, molecular dynamics (MD) simulation was applied to study the solubility of two water-insoluble drugs, fenofibrate and nimodipine, in a series of micelle-forming PEO-b-PCL block copolymers with combinations of blocks having different molecular weights. The solubility predictions based on the MD results were then compared with those obtained from solubility experiments and by the commonly used group contribution method (GCM). The results showed that Flory-Huggins interaction parameters computed by the MD simulations are consistent with the solubility data of the drug/PEO-b-PCL systems, whereas those calculated by the GCM significantly deviate from the experimental observation. We have also accounted for the possibility of drug solubilization in the PEO block of PEO-b-PCL.

Communication: Quantum molecular dynamics simulation of liquid para-hydrogen by nuclear and electron wave packet approach.

PubMed

Hyeon-Deuk, Kim; Ando, Koji

2014-05-07

Liquid para-hydrogen (p-H2) is a typical quantum liquid which exhibits strong nuclear quantum effects (NQEs) and thus anomalous static and dynamic properties. We propose a real-time simulation method of wave packet (WP) molecular dynamics (MD) based on non-empirical intra- and inter-molecular interactions of non-spherical hydrogen molecules, and apply it to condensed-phase p-H2. The NQEs, such as WP delocalization and zero-point energy, are taken into account without perturbative expansion of prepared model potential functions but with explicit interactions between nuclear and electron WPs. The developed MD simulation for 100 ps with 1200 hydrogen molecules is realized at feasible computational cost, by which basic experimental properties of p-H2 liquid such as radial distribution functions, self-diffusion coefficients, and shear viscosities are all well reproduced.

DFTBaby: A software package for non-adiabatic molecular dynamics simulations based on long-range corrected tight-binding TD-DFT(B)

NASA Astrophysics Data System (ADS)

Humeniuk, Alexander; Mitrić, Roland

2017-12-01

A software package, called DFTBaby, is published, which provides the electronic structure needed for running non-adiabatic molecular dynamics simulations at the level of tight-binding DFT. A long-range correction is incorporated to avoid spurious charge transfer states. Excited state energies, their analytic gradients and scalar non-adiabatic couplings are computed using tight-binding TD-DFT. These quantities are fed into a molecular dynamics code, which integrates Newton's equations of motion for the nuclei together with the electronic Schrödinger equation. Non-adiabatic effects are included by surface hopping. As an example, the program is applied to the optimization of excited states and non-adiabatic dynamics of polyfluorene. The python and Fortran source code is available at http://www.dftbaby.chemie.uni-wuerzburg.de.

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

PubMed Central

Donovan, Rory M.; Tapia, Jose-Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel M.

2016-01-01

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables. PMID:26845334

Principles of Protein Stability and Their Application in Computational Design.

PubMed

Goldenzweig, Adi; Fleishman, Sarel

2018-01-26

Proteins are increasingly used in basic and applied biomedical research.Many proteins, however, are only marginally stable and can be expressed in limited amounts, thus hampering research and applications. Research has revealed the thermodynamic, cellular, and evolutionary principles and mechanisms that underlie marginal stability. With this growing understanding, computational stability design methods have advanced over the past two decades starting from methods that selectively addressed only some aspects of marginal stability. Current methods are more general and, by combining phylogenetic analysis with atomistic design, have shown drastic improvements in solubility, thermal stability, and aggregation resistance while maintaining the protein's primary molecular activity. Stability design is opening the way to rational engineering of improved enzymes, therapeutics, and vaccines and to the application of protein design methodology to large proteins and molecular activities that have proven challenging in the past. Expected final online publication date for the Annual Review of Biochemistry Volume 87 is June 20, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Fluorescence-Guided Probes of Aptamer-Targeted Gold Nanoparticles with Computed Tomography Imaging Accesses for in Vivo Tumor Resection.

PubMed

Li, Cheng-Hung; Kuo, Tsung-Rong; Su, Hsin-Jan; Lai, Wei-Yun; Yang, Pan-Chyr; Chen, Jinn-Shiun; Wang, Di-Yan; Wu, Yi-Chun; Chen, Chia-Chun

2015-10-28

Recent development of molecular imaging probes for fluorescence-guided surgery has shown great progresses for determining tumor margin to execute the tissue resection. Here we synthesize the fluorescent gold nanoparticles conjugated with diatrizoic acid and nucleolin-targeted AS1411 aptamer. The nanoparticle conjugates exhibit high water-solubility, good biocompatibility, visible fluorescence and strong X-ray attenuation for computed tomography (CT) contrast enhancement. The fluorescent nanoparticle conjugates are applied as a molecular contrast agent to reveal the tumor location in CL1-5 tumor-bearing mice by CT imaging. Furthermore, the orange-red fluorescence emitting from the conjugates in the CL1-5 tumor can be easily visualized by the naked eyes. After the resection, the IVIS measurements show that the fluorescence signal of the nanoparticle conjugates in the tumor is greatly enhanced in comparison to that in the controlled experiment. Our work has shown potential application of functionalized nanoparticles as a dual-function imaging agent in clinical fluorescence-guided surgery.

Virtual-system-coupled adaptive umbrella sampling to compute free-energy landscape for flexible molecular docking.

PubMed

Higo, Junichi; Dasgupta, Bhaskar; Mashimo, Tadaaki; Kasahara, Kota; Fukunishi, Yoshifumi; Nakamura, Haruki

2015-07-30

A novel enhanced conformational sampling method, virtual-system-coupled adaptive umbrella sampling (V-AUS), was proposed to compute 300-K free-energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V-AUS was applied to complex formation of two disordered amyloid-β (Aβ30-35 ) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300-K free-energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β-sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V-AUS converged to uniform distribution more effectively than conventional AUS sampling did. © 2015 Wiley Periodicals, Inc.

Ab-initio molecular dynamics in electric fields via Wannier functions: Dielectric properties of liquid water.

NASA Astrophysics Data System (ADS)

Sharma, Manu; Resta, Raffaele; Car, Roberto

2004-03-01

We have implemented a modified Car-Parrinello molecular dynamics scheme in which maximally localized Wannier functions, instead of delocalized Bloch orbitals, are used to represent ``on the fly'' the electronic wavefunction of an insulating system. Within our scheme, we account for the effects of a finite homogeneous field applied to the simulation cell; we then use the ideas of the modern theory of polarization to investigate the system's response. The dielectric response (linear and nonlinear) of a given material is thus directly accessible at a reasonable computational cost. We have performed a thorough study of the behavior of a computational sample of liquid water under the effect of an electric field. We used norm-conserving pseudopotentials, the PBE exchange-correlation potential, and supercell containing water 64 molecules. Besides providing the static response of the liquid at a given temperature, our simulations yield microscopic insight into features wich are not easily measured in experiments, particularly regarding relaxation phenomena.

FMT-XCT: in vivo animal studies with hybrid fluorescence molecular tomography-X-ray computed tomography.

PubMed

Ale, Angelique; Ermolayev, Vladimir; Herzog, Eva; Cohrs, Christian; de Angelis, Martin Hrabé; Ntziachristos, Vasilis

2012-06-01

The development of hybrid optical tomography methods to improve imaging performance has been suggested over a decade ago and has been experimentally demonstrated in animals and humans. Here we examined in vivo performance of a camera-based hybrid fluorescence molecular tomography (FMT) system for 360° imaging combined with X-ray computed tomography (XCT). Offering an accurately co-registered, information-rich hybrid data set, FMT-XCT has new imaging possibilities compared to stand-alone FMT and XCT. We applied FMT-XCT to a subcutaneous 4T1 tumor mouse model, an Aga2 osteogenesis imperfecta model and a Kras lung cancer mouse model, using XCT information during FMT inversion. We validated in vivo imaging results against post-mortem planar fluorescence images of cryoslices and histology data. Besides offering concurrent anatomical and functional information, FMT-XCT resulted in the most accurate FMT performance to date. These findings indicate that addition of FMT optics into the XCT gantry may be a potent upgrade for small-animal XCT systems.

Fluorescence-Guided Probes of Aptamer-Targeted Gold Nanoparticles with Computed Tomography Imaging Accesses for in Vivo Tumor Resection

PubMed Central

Li, Cheng-Hung; Kuo, Tsung-Rong; Su, Hsin-Jan; Lai, Wei-Yun; Yang, Pan-Chyr; Chen, Jinn-Shiun; Wang, Di-Yan; Wu, Yi-Chun; Chen, Chia-Chun

2015-01-01

Recent development of molecular imaging probes for fluorescence-guided surgery has shown great progresses for determining tumor margin to execute the tissue resection. Here we synthesize the fluorescent gold nanoparticles conjugated with diatrizoic acid and nucleolin-targeted AS1411 aptamer. The nanoparticle conjugates exhibit high water-solubility, good biocompatibility, visible fluorescence and strong X-ray attenuation for computed tomography (CT) contrast enhancement. The fluorescent nanoparticle conjugates are applied as a molecular contrast agent to reveal the tumor location in CL1-5 tumor-bearing mice by CT imaging. Furthermore, the orange-red fluorescence emitting from the conjugates in the CL1-5 tumor can be easily visualized by the naked eyes. After the resection, the IVIS measurements show that the fluorescence signal of the nanoparticle conjugates in the tumor is greatly enhanced in comparison to that in the controlled experiment. Our work has shown potential application of functionalized nanoparticles as a dual-function imaging agent in clinical fluorescence-guided surgery. PMID:26507179

Molecular Sieve Bench Testing and Computer Modeling

NASA Technical Reports Server (NTRS)

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

1995-01-01

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

Linearly scaling and almost Hamiltonian dielectric continuum molecular dynamics simulations through fast multipole expansions

NASA Astrophysics Data System (ADS)

Lorenzen, Konstantin; Mathias, Gerald; Tavan, Paul

2015-11-01

Hamiltonian Dielectric Solvent (HADES) is a recent method [S. Bauer et al., J. Chem. Phys. 140, 104103 (2014)] which enables atomistic Hamiltonian molecular dynamics (MD) simulations of peptides and proteins in dielectric solvent continua. Such simulations become rapidly impractical for large proteins, because the computational effort of HADES scales quadratically with the number N of atoms. If one tries to achieve linear scaling by applying a fast multipole method (FMM) to the computation of the HADES electrostatics, the Hamiltonian character (conservation of total energy, linear, and angular momenta) may get lost. Here, we show that the Hamiltonian character of HADES can be almost completely preserved, if the structure-adapted fast multipole method (SAMM) as recently redesigned by Lorenzen et al. [J. Chem. Theory Comput. 10, 3244-3259 (2014)] is suitably extended and is chosen as the FMM module. By this extension, the HADES/SAMM forces become exact gradients of the HADES/SAMM energy. Their translational and rotational invariance then guarantees (within the limits of numerical accuracy) the exact conservation of the linear and angular momenta. Also, the total energy is essentially conserved—up to residual algorithmic noise, which is caused by the periodically repeated SAMM interaction list updates. These updates entail very small temporal discontinuities of the force description, because the employed SAMM approximations represent deliberately balanced compromises between accuracy and efficiency. The energy-gradient corrected version of SAMM can also be applied, of course, to MD simulations of all-atom solvent-solute systems enclosed by periodic boundary conditions. However, as we demonstrate in passing, this choice does not offer any serious advantages.

Tyramine Hydrochloride Based Label-Free System for Operating Various DNA Logic Gates and a DNA Caliper for Base Number Measurements.

PubMed

Fan, Daoqing; Zhu, Xiaoqing; Dong, Shaojun; Wang, Erkang

2017-07-05

DNA is believed to be a promising candidate for molecular logic computation, and the fluorogenic/colorimetric substrates of G-quadruplex DNAzyme (G4zyme) are broadly used as label-free output reporters of DNA logic circuits. Herein, for the first time, tyramine-HCl (a fluorogenic substrate of G4zyme) is applied to DNA logic computation and a series of label-free DNA-input logic gates, including elementary AND, OR, and INHIBIT logic gates, as well as a two to one encoder, are constructed. Furthermore, a DNA caliper that can measure the base number of target DNA as low as three bases is also fabricated. This DNA caliper can also perform concatenated AND-AND logic computation to fulfil the requirements of sophisticated logic computing. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

All-atom calculation of protein free-energy profiles

NASA Astrophysics Data System (ADS)

Orioli, S.; Ianeselli, A.; Spagnolli, G.; Faccioli, P.

2017-10-01

The Bias Functional (BF) approach is a variational method which enables one to efficiently generate ensembles of reactive trajectories for complex biomolecular transitions, using ordinary computer clusters. For example, this scheme was applied to simulate in atomistic detail the folding of proteins consisting of several hundreds of amino acids and with experimental folding time of several minutes. A drawback of the BF approach is that it produces trajectories which do not satisfy microscopic reversibility. Consequently, this method cannot be used to directly compute equilibrium observables, such as free energy landscapes or equilibrium constants. In this work, we develop a statistical analysis which permits us to compute the potential of mean-force (PMF) along an arbitrary collective coordinate, by exploiting the information contained in the reactive trajectories calculated with the BF approach. We assess the accuracy and computational efficiency of this scheme by comparing its results with the PMF obtained for a small protein by means of plain molecular dynamics.

Efficient Computation of Difference Vibrational Spectra in Isothermal-Isobaric Ensemble.

PubMed

Joutsuka, Tatsuya; Morita, Akihiro

2016-11-03

Difference spectroscopy between two close systems is widely used to augment its selectivity to the different parts of the observed system, though the molecular dynamics calculation of tiny difference spectra would be computationally extraordinary demanding by subtraction of two spectra. Therefore, we have proposed an efficient computational algorithm of difference spectra without resorting to the subtraction. The present paper reports our extension of the theoretical method in the isothermal-isobaric (NPT) ensemble. The present theory expands our applications of analysis including pressure dependence of the spectra. We verified that the present theory yields accurate difference spectra in the NPT condition as well, with remarkable computational efficiency over the straightforward subtraction by several orders of magnitude. This method is further applied to vibrational spectra of liquid water with varying pressure and succeeded in reproducing tiny difference spectra by pressure change. The anomalous pressure dependence is elucidated in relation to other properties of liquid water.

Bioinformatics/biostatistics: microarray analysis.

PubMed

Eichler, Gabriel S

2012-01-01

The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).

Time-Dependent Wave Packet Dynamics Calculations of Cross Sections for Ultracold Scattering of Molecules

NASA Astrophysics Data System (ADS)

Huang, Jiayu; Liu, Shu; Zhang, Dong H.; Krems, Roman V.

2018-04-01

Because the de Broglie wavelength of ultracold molecules is very large, the cross sections for collisions of molecules at ultracold temperatures are always computed by the time-independent quantum scattering approach. Here, we report the first accurate time-dependent wave packet dynamics calculation for reactive scattering of ultracold molecules. Wave packet dynamics calculations can be applied to molecular systems with more dimensions and provide real-time information on the process of bond rearrangement and/or energy exchange in molecular collisions. Our work thus makes possible the extension of rigorous quantum calculations of ultracold reaction properties to polyatomic molecules and adds a new powerful tool for the study of ultracold chemistry.

Photoelectron Diffraction from Valence States of Oriented Molecules

NASA Astrophysics Data System (ADS)

Krüger, Peter

2018-06-01

The angular distribution of photoelectrons emitted from valence states of oriented molecules is investigated. The principles underlying the angular pattern formation are explained in terms of photoelectron wave interference, caused by initial state delocalization and final state photoelectron scattering. Computational approaches to photoelectron spectroscopy from molecules are briefly reviewed. Here a combination of molecular orbital calculations for the initial state and multiple scattering theory for the photoelectron final state is used and applied to the 3σ and 4σ orbitals of nitrogen and the highest occupied molecular orbital of pentacene. Appreciable perpendicular emission and circular dichroism in angular distributions is found, two effects that cannot be described by the popular plane wave approximation to the photoelectron final state.

The development of a revised version of multi-center molecular Ornstein-Zernike equation

NASA Astrophysics Data System (ADS)

Kido, Kentaro; Yokogawa, Daisuke; Sato, Hirofumi

2012-04-01

Ornstein-Zernike (OZ)-type theory is a powerful tool to obtain 3-dimensional solvent distribution around solute molecule. Recently, we proposed multi-center molecular OZ method, which is suitable for parallel computing of 3D solvation structure. The distribution function in this method consists of two components, namely reference and residue parts. Several types of the function were examined as the reference part to investigate the numerical robustness of the method. As the benchmark, the method is applied to water, benzene in aqueous solution and single-walled carbon nanotube in chloroform solution. The results indicate that fully-parallelization is achieved by utilizing the newly proposed reference functions.

Time-Dependent Wave Packet Dynamics Calculations of Cross Sections for Ultracold Scattering of Molecules.

PubMed

Huang, Jiayu; Liu, Shu; Zhang, Dong H; Krems, Roman V

2018-04-06

Because the de Broglie wavelength of ultracold molecules is very large, the cross sections for collisions of molecules at ultracold temperatures are always computed by the time-independent quantum scattering approach. Here, we report the first accurate time-dependent wave packet dynamics calculation for reactive scattering of ultracold molecules. Wave packet dynamics calculations can be applied to molecular systems with more dimensions and provide real-time information on the process of bond rearrangement and/or energy exchange in molecular collisions. Our work thus makes possible the extension of rigorous quantum calculations of ultracold reaction properties to polyatomic molecules and adds a new powerful tool for the study of ultracold chemistry.

The Bravyi-Kitaev transformation for quantum computation of electronic structure

NASA Astrophysics Data System (ADS)

Seeley, Jacob T.; Richard, Martin J.; Love, Peter J.

2012-12-01

Quantum simulation is an important application of future quantum computers with applications in quantum chemistry, condensed matter, and beyond. Quantum simulation of fermionic systems presents a specific challenge. The Jordan-Wigner transformation allows for representation of a fermionic operator by O(n) qubit operations. Here, we develop an alternative method of simulating fermions with qubits, first proposed by Bravyi and Kitaev [Ann. Phys. 298, 210 (2002), 10.1006/aphy.2002.6254; e-print arXiv:quant-ph/0003137v2], that reduces the simulation cost to O(log n) qubit operations for one fermionic operation. We apply this new Bravyi-Kitaev transformation to the task of simulating quantum chemical Hamiltonians, and give a detailed example for the simplest possible case of molecular hydrogen in a minimal basis. We show that the quantum circuit for simulating a single Trotter time step of the Bravyi-Kitaev derived Hamiltonian for H2 requires fewer gate applications than the equivalent circuit derived from the Jordan-Wigner transformation. Since the scaling of the Bravyi-Kitaev method is asymptotically better than the Jordan-Wigner method, this result for molecular hydrogen in a minimal basis demonstrates the superior efficiency of the Bravyi-Kitaev method for all quantum computations of electronic structure.

Analytic second derivative of the energy for density functional theory based on the three-body fragment molecular orbital method

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

Nakata, Hiroya, E-mail: nakata.h.ab@m.titech.ac.jp; RIKEN, Research Cluster for Innovation, Nakamura Lab, 2-1 Hirosawa, Wako, Saitama 351-0198; Japan Society for the Promotion of Science, Kojimachi Business Center Building, 5-3-1 Kojimachi, Chiyoda-ku, Tokyo 102-0083

2015-03-28

Analytic second derivatives of the energy with respect to nuclear coordinates have been developed for spin restricted density functional theory (DFT) based on the fragment molecular orbital method (FMO). The derivations were carried out for the three-body expansion (FMO3), and the two-body expressions can be obtained by neglecting the three-body corrections. Also, the restricted Hartree-Fock (RHF) Hessian for FMO3 can be obtained by neglecting the density-functional related terms. In both the FMO-RHF and FMO-DFT Hessians, certain terms with small magnitudes are neglected for computational efficiency. The accuracy of the FMO-DFT Hessian in terms of the Gibbs free energy is evaluatedmore » for a set of polypeptides and water clusters and found to be within 1 kcal/mol of the corresponding full (non-fragmented) ab initio calculation. The FMO-DFT method is also applied to transition states in S{sub N}2 reactions and for the computation of the IR and Raman spectra of a small Trp-cage protein (PDB: 1L2Y). Some computational timing analysis is also presented.« less

Parallel algorithms for the molecular conformation problem

NASA Astrophysics Data System (ADS)

Rajan, Kumar

Given a set of objects, and some of the pairwise distances between them, the problem of identifying the positions of the objects in the Euclidean space is referred to as the molecular conformation problem. This problem is known to be computationally difficult. One of the most important applications of this problem is the determination of the structure of molecules. In the case of molecular structure determination, usually only the lower and upper bounds on some of the interatomic distances are available. The process of obtaining a tighter set of bounds between all pairs of atoms, using the available interatomic distance bounds is referred to as bound-smoothing . One method for bound-smoothing is to use the limits imposed by the triangle inequality. The distance bounds so obtained can often be tightened further by applying the tetrangle inequality---the limits imposed on the six pairwise distances among a set of four atoms (instead of three for the triangle inequalities). The tetrangle inequality is expressed by the Cayley-Menger determinants. The sequential tetrangle-inequality bound-smoothing algorithm considers a quadruple of atoms at a time, and tightens the bounds on each of its six distances. The sequential algorithm is computationally expensive, and its application is limited to molecules with up to a few hundred atoms. Here, we conduct an experimental study of tetrangle-inequality bound-smoothing and reduce the sequential time by identifying the most computationally expensive portions of the process. We also present a simple criterion to determine which of the quadruples of atoms are likely to be tightened the most by tetrangle-inequality bound-smoothing. This test could be used to enhance the applicability of this process to large molecules. We map the problem of parallelizing tetrangle-inequality bound-smoothing to that of generating disjoint packing designs of a certain kind. We map this, in turn, to a regular-graph coloring problem, and present a simple, parallel algorithm for tetrangle-inequality bound-smoothing. We implement the parallel algorithm on the Intel Paragon X/PS, and apply it to real-life molecules. Our results show that with this parallel algorithm, tetrangle inequality can be applied to large molecules in a reasonable amount of time. We extend the regular graph to represent more general packing designs, and present a coloring algorithm for this graph. This can be used to generate constant-weight binary codes in parallel. Once a tighter set of distance bounds is obtained, the molecular conformation problem is usually formulated as a non-linear optimization problem, and a global optimization algorithm is then used to solve the problem. Here we present a parallel, deterministic algorithm for the optimization problem based on Interval Analysis. We implement our algorithm, using dynamic load balancing, on a network of Sun Ultra-Sparc workstations. Our experience with this algorithm shows that its application is limited to small instances of the molecular conformation problem, where the number of measured, pairwise distances is close to the maximum value. However, since the interval method eliminates a substantial portion of the initial search space very quickly, it can be used to prune the search space before any of the more efficient, nondeterministic methods can be applied.

Theoretical study on the vibrational spectra of methoxy- and formyl-dihydroxy- trans-stilbenes and their hydrolytic equilibria

NASA Astrophysics Data System (ADS)

Molnár, Viktor; Billes, Ferenc; Tyihák, Ernő; Mikosch, Hans

2008-02-01

Compounds formed by exchanging one of the resveratrol hydroxy groups to methoxy or formyl groups are biologically important. Quantum chemical DFT calculations were applied for the simulation of some of their properties. Their optimized structures and charge distributions were computed. Based on the calculated vibrational force constants and optimized molecular structure infrared and Raman spectra were calculated. The characteristics of the vibrational modes were determined by normal coordinate analysis. Applying the calculated thermodynamic functions also for resveratrol, methanol, formaldehyde and water, thermodynamic equilibria were calculated for the equilibria between resveratrol and its methyl and formyl substituted derivatives, respectively.

Identifying the binding mode of a molecular scaffold

NASA Astrophysics Data System (ADS)

Chema, Doron; Eren, Doron; Yayon, Avner; Goldblum, Amiram; Zaliani, Andrea

2004-01-01

We describe a method for docking of a scaffold-based series and present its advantages over docking of individual ligands, for determining the binding mode of a molecular scaffold in a binding site. The method has been applied to eight different scaffolds of protein kinase inhibitors (PKI). A single analog of each of these eight scaffolds was previously crystallized with different protein kinases. We have used FlexX to dock a set of molecules that share the same scaffold, rather than docking a single molecule. The main mode of binding is determined by the mode of binding of the largest cluster among the docked molecules that share a scaffold. Clustering is based on our `nearest single neighbor' method [J. Chem. Inf. Comput. Sci., 43 (2003) 208-217]. Additional criteria are applied in those cases in which more than one significant binding mode is found. Using the proposed method, most of the crystallographic binding modes of these scaffolds were reconstructed. Alternative modes, that have not been detected yet by experiments, could also be identified. The method was applied to predict the binding mode of an additional molecular scaffold that was not yet reported and the predicted binding mode has been found to be very similar to experimental results for a closely related scaffold. We suggest that this approach be used as a virtual screening tool for scaffold-based design processes.

Adsorption of molecular additive onto lead halide perovskite surfaces: A computational study on Lewis base thiophene additive passivation

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yu, Fengxi; Chen, Lihong; Li, Jingfa

2018-06-01

Organic additives, such as the Lewis base thiophene, have been successfully applied to passivate halide perovskite surfaces, improving the stability and properties of perovskite devices based on CH3NH3PbI3. Yet, the detailed nanostructure of the perovskite surface passivated by additives and the mechanisms of such passivation are not well understood. This study presents a nanoscopic view on the interfacial structure of an additive/perovskite interface, consisting of a Lewis base thiophene molecular additive and a lead halide perovskite surface substrate, providing insights on the mechanisms that molecular additives can passivate the halide perovskite surfaces and enhance the perovskite-based device performance. Molecular dynamics study on the interactions between water molecules and the perovskite surfaces passivated by the investigated additive reveal the effectiveness of employing the molecular additives to improve the stability of the halide perovskite materials. The additive/perovskite surface system is further probed via molecular engineering the perovskite surfaces. This study reveals the nanoscopic structure-property relationships of the halide perovskite surface passivated by molecular additives, which helps the fundamental understanding of the surface/interface engineering strategies for the development of halide perovskite based devices.

NanoDesign: Concepts and Software for a Nanotechnology Based on Functionalized Fullerenes

NASA Technical Reports Server (NTRS)

Globus, Al; Jaffe, Richard; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Eric Drexler has proposed a hypothetical nanotechnology based on diamond and investigated the properties of such molecular systems. While attractive, diamonoid nanotechnology is not physically accessible with straightforward extensions of current laboratory techniques. We propose a nanotechnology based on functionalized fullerenes and investigate carbon nanotube based gears with teeth added via a benzyne reaction known to occur with C60. The gears are single-walled carbon nanotubes with appended coenzyme groups for teeth. Fullerenes are in widespread laboratory use and can be functionalized in many ways. Companion papers computationally demonstrate the properties of these gears (they appear to work) and the accessibility of the benzyne/nanotube reaction. This paper describes the molecular design techniques and rationale as well as the software that implements these design techniques. The software is a set of persistent C++ objects controlled by TCL command scripts. The c++/tcl interface is automatically generated by a software system called tcl_c++ developed by the author and described here. The objects keep track of different portions of the molecular machinery to allow different simulation techniques and boundary conditions to be applied as appropriate. This capability has been required to demonstrate (computationally) our gear's feasibility. A new distributed software architecture featuring a WWW universal client, CORBA distributed objects, and agent software is under consideration. The software architecture is intended to eventually enable a widely disbursed group to develop complex simulated molecular machines.

Gas-surface interactions using accommodation coefficients for a dilute and a dense gas in a micro- or nanochannel: heat flux predictions using combined molecular dynamics and Monte Carlo techniques.

PubMed

Nedea, S V; van Steenhoven, A A; Markvoort, A J; Spijker, P; Giordano, D

2014-05-01

The influence of gas-surface interactions of a dilute gas confined between two parallel walls on the heat flux predictions is investigated using a combined Monte Carlo (MC) and molecular dynamics (MD) approach. The accommodation coefficients are computed from the temperature of incident and reflected molecules in molecular dynamics and used as effective coefficients in Maxwell-like boundary conditions in Monte Carlo simulations. Hydrophobic and hydrophilic wall interactions are studied, and the effect of the gas-surface interaction potential on the heat flux and other characteristic parameters like density and temperature is shown. The heat flux dependence on the accommodation coefficient is shown for different fluid-wall mass ratios. We find that the accommodation coefficient is increasing considerably when the mass ratio is decreased. An effective map of the heat flux depending on the accommodation coefficient is given and we show that MC heat flux predictions using Maxwell boundary conditions based on the accommodation coefficient give good results when compared to pure molecular dynamics heat predictions. The accommodation coefficients computed for a dilute gas for different gas-wall interaction parameters and mass ratios are transferred to compute the heat flux predictions for a dense gas. Comparison of the heat fluxes derived using explicit MD, MC with Maxwell-like boundary conditions based on the accommodation coefficients, and pure Maxwell boundary conditions are discussed. A map of the heat flux dependence on the accommodation coefficients for a dense gas, and the effective accommodation coefficients for different gas-wall interactions are given. In the end, this approach is applied to study the gas-surface interactions of argon and xenon molecules on a platinum surface. The derived accommodation coefficients are compared with values of experimental results.

Multiscale Molecular Simulation of Solution Processing of SMDPPEH: PCBM Small-Molecule Organic Solar Cells.

PubMed

Lee, Cheng-Kuang; Pao, Chun-Wei

2016-08-17

Solution-processed small-molecule organic solar cells are a promising renewable energy source because of their low production cost, mechanical flexibility, and light weight relative to their pure inorganic counterparts. In this work, we developed a coarse-grained (CG) Gay-Berne ellipsoid molecular simulation model based on atomistic trajectories from all-atom molecular dynamics simulations of smaller system sizes to systematically study the nanomorphology of the SMDPPEH/PCBM/solvent ternary blend during solution processing, including the blade-coating process by applying external shear to the solution. With the significantly reduced overall system degrees of freedom and computational acceleration from GPU, we were able to go well beyond the limitation of conventional all-atom molecular simulations with a system size on the order of hundreds of nanometers with mesoscale molecular detail. Our simulations indicate that, similar to polymer solar cells, the optimal blending ratio in small-molecule organic solar cells must provide the highest specific interfacial area for efficient exciton dissociation, while retaining balanced hole/electron transport pathway percolation. We also reveal that blade-coating processes have a significant impact on nanomorphology. For given donor/acceptor blending ratios, applying an external shear force can effectively promote donor/acceptor phase segregation and stacking in the SMDPPEH domains. The present study demonstrated the capability of an ellipsoid-based coarse-grained model for studying the nanomorphology evolution of small-molecule organic solar cells during solution processing/blade-coating and provided links between fabrication protocols and device nanomorphologies.

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

NASA Astrophysics Data System (ADS)

Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

2015-03-01

We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

Protein-Ligand Interaction Detection with a Novel Method of Transient Induced Molecular Electronic Spectroscopy (TIMES): Experimental and Theoretical Studies.

PubMed

Zhang, Tiantian; Wei, Tao; Han, Yuanyuan; Ma, Heng; Samieegohar, Mohammadreza; Chen, Ping-Wei; Lian, Ian; Lo, Yu-Hwa

2016-11-23

Protein-ligand interaction detection without disturbances (e.g., surface immobilization, fluorescent labeling, and crystallization) presents a key question in protein chemistry and drug discovery. The emergent technology of transient induced molecular electronic spectroscopy (TIMES), which incorporates a unique design of microfluidic platform and integrated sensing electrodes, is designed to operate in a label-free and immobilization-free manner to provide crucial information for protein-ligand interactions in relevant physiological conditions. Through experiments and theoretical simulations, we demonstrate that the TIMES technique actually detects protein-ligand binding through signals generated by surface electric polarization. The accuracy and sensitivity of experiments were demonstrated by precise measurements of dissociation constant of lysozyme and N -acetyl-d-glucosamine (NAG) ligand and its trimer, NAG 3 . Computational fluid dynamics (CFD) computation is performed to demonstrate that the surface's electric polarization signal originates from the induced image charges during the transition state of surface mass transport, which is governed by the overall effects of protein concentration, hydraulic forces, and surface fouling due to protein adsorption. Hybrid atomistic molecular dynamics (MD) simulations and free energy computation show that ligand binding affects lysozyme structure and stability, producing different adsorption orientation and surface polarization to give the characteristic TIMES signals. Although the current work is focused on protein-ligand interactions, the TIMES method is a general technique that can be applied to study signals from reactions between many kinds of molecules.

Impact of tensile strain on the thermal transport of zigzag hexagonal boron nitride nanoribbon: An equilibrium molecular dynamics study

NASA Astrophysics Data System (ADS)

Navid, Ishtiaque Ahmed; Intisar Khan, Asir; Subrina, Samia

2018-02-01

The thermal conductivity of single layer strained hexagonal boron nitride nanoribbon (h-BNNR) has been computed using the Green—Kubo formulation of Equilibrium Molecular Dynamics (EMD) simulation. We have investigated the impact of strain on thermal transport of h-BNNR by varying the applied tensile strain from 1% upto 5% through uniaxial loading. The thermal conductivity of h-BNNR decreases monotonically with the increase of uniaxial tensile strain keeping the sample size and temperature constant. The thermal conductivity can be reduced upto 86% for an applied uniaxial tensile strain of 5%. The impact of temperature and width variation on the thermal conductivity of h-BNNR has also been studied under different uniaxial tensile strain conditions. With the increase in temperature, the thermal conductivity of strained h-BNNR exhibits a decaying characteristics whereas it shows an opposite pattern with the increasing width. Such study would provide a good insight on the strain tunable thermal transport for the potential device application of boron nitride nanostructures.

Overcoming the Time Limitation in Molecular Dynamics Simulation of Crystal Nucleation: A Persistent-Embryo Approach

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

Sun, Yang; Song, Huajing; Zhang, Feng

The crystal nucleation from liquid in most cases is too rare to be accessed within the limited time scales of the conventional molecular dynamics (MD) simulation. Here, we developed a “persistent embryo” method to facilitate crystal nucleation in MD simulations by preventing small crystal embryos from melting using external spring forces. We applied this method to the pure Ni case for a moderate undercooling where no nucleation can be observed in the conventional MD simulation, and obtained nucleation rate in good agreement with the experimental data. Moreover, the method is applied to simulate an even more sluggish event: the nucleationmore » of the B2 phase in a strong glass-forming Cu-Zr alloy. The nucleation rate was found to be 8 orders of magnitude smaller than Ni at the same undercooling, which well explains the good glass formability of the alloy. In conclusion, our work opens a new avenue to study solidification under realistic experimental conditions via atomistic computer simulation.« less

Overcoming the Time Limitation in Molecular Dynamics Simulation of Crystal Nucleation: A Persistent-Embryo Approach

DOE PAGES

Sun, Yang; Song, Huajing; Zhang, Feng; ...

2018-02-23

The crystal nucleation from liquid in most cases is too rare to be accessed within the limited time scales of the conventional molecular dynamics (MD) simulation. Here, we developed a “persistent embryo” method to facilitate crystal nucleation in MD simulations by preventing small crystal embryos from melting using external spring forces. We applied this method to the pure Ni case for a moderate undercooling where no nucleation can be observed in the conventional MD simulation, and obtained nucleation rate in good agreement with the experimental data. Moreover, the method is applied to simulate an even more sluggish event: the nucleationmore » of the B2 phase in a strong glass-forming Cu-Zr alloy. The nucleation rate was found to be 8 orders of magnitude smaller than Ni at the same undercooling, which well explains the good glass formability of the alloy. In conclusion, our work opens a new avenue to study solidification under realistic experimental conditions via atomistic computer simulation.« less

Overcoming the Time Limitation in Molecular Dynamics Simulation of Crystal Nucleation: A Persistent-Embryo Approach

NASA Astrophysics Data System (ADS)

Sun, Yang; Song, Huajing; Zhang, Feng; Yang, Lin; Ye, Zhuo; Mendelev, Mikhail I.; Wang, Cai-Zhuang; Ho, Kai-Ming

2018-02-01

The crystal nucleation from liquid in most cases is too rare to be accessed within the limited time scales of the conventional molecular dynamics (MD) simulation. Here, we developed a "persistent embryo" method to facilitate crystal nucleation in MD simulations by preventing small crystal embryos from melting using external spring forces. We applied this method to the pure Ni case for a moderate undercooling where no nucleation can be observed in the conventional MD simulation, and obtained nucleation rate in good agreement with the experimental data. Moreover, the method is applied to simulate an even more sluggish event: the nucleation of the B 2 phase in a strong glass-forming Cu-Zr alloy. The nucleation rate was found to be 8 orders of magnitude smaller than Ni at the same undercooling, which well explains the good glass formability of the alloy. Thus, our work opens a new avenue to study solidification under realistic experimental conditions via atomistic computer simulation.

Overcoming the Time Limitation in Molecular Dynamics Simulation of Crystal Nucleation: A Persistent-Embryo Approach.

PubMed

Sun, Yang; Song, Huajing; Zhang, Feng; Yang, Lin; Ye, Zhuo; Mendelev, Mikhail I; Wang, Cai-Zhuang; Ho, Kai-Ming

2018-02-23

The crystal nucleation from liquid in most cases is too rare to be accessed within the limited time scales of the conventional molecular dynamics (MD) simulation. Here, we developed a "persistent embryo" method to facilitate crystal nucleation in MD simulations by preventing small crystal embryos from melting using external spring forces. We applied this method to the pure Ni case for a moderate undercooling where no nucleation can be observed in the conventional MD simulation, and obtained nucleation rate in good agreement with the experimental data. Moreover, the method is applied to simulate an even more sluggish event: the nucleation of the B2 phase in a strong glass-forming Cu-Zr alloy. The nucleation rate was found to be 8 orders of magnitude smaller than Ni at the same undercooling, which well explains the good glass formability of the alloy. Thus, our work opens a new avenue to study solidification under realistic experimental conditions via atomistic computer simulation.

Magnetic polyoxometalates: from molecular magnetism to molecular spintronics and quantum computing.

PubMed

Clemente-Juan, Juan M; Coronado, Eugenio; Gaita-Ariño, Alejandro

2012-11-21

In this review we discuss the relevance of polyoxometalate (POM) chemistry to provide model objects in molecular magnetism. We present several potential applications in nanomagnetism, in particular, in molecular spintronics and quantum computing.

First-principles studies of electrical transport in nanoscale molecular junctions

NASA Astrophysics Data System (ADS)

Neaton, J. B.

2008-03-01

Understanding the conductance of individual molecular junctions is a forefront topic in theoretical nanoscience. The development of a general, efficient atomistic approach for treating an open system out of equilibrium with good accuracy, and then using it to inform experiment, is a significant open challenge in the field. Here I will describe studies where first-principles techniques, based on density functional theory (DFT) and beyond, are used to investigate some of the fundamental issues associated with single-molecule transport measurements. After a brief summary of previous work, a DFT-based scattering-state approach is presented and applied to H2 and amine-Au linked molecular junctions [1], two systems for which there exist reliable data [2]. Similar to most ab initio studies, we rely on a Landauer approach within DFT for junction conductance. Using this framework, which has proven relatively accurate for metallic point contacts, good agreement with experiment is obtained for the H2 conductance. For amine-Au linked junctions, however, the computed conductance is significantly larger than that measured,although structural trends are reproduced by the calculations. To explore this further, we draw on GW calculations of a prototypical metal-molecule contact, benzene on graphite, where interfacial polarization effects are found to drastically modify frontier orbital energies [3]. A physically motivated model self-energy correction is developed from our GW calculations,applied to the amine case, and shown to quantitatively explain the discrepancy with experiment. The importance of many-electron corrections beyond DFT for accurately computing molecular conductance and understanding experiments is thoroughly discussed. [1] S. Y. Quek et al., Nano Lett 7, 3482 (2007); K. H. Khoo et al., submitted (2007). [2] R. Smit et al., Nature 419, 906 (2002); L. Venkataraman et al., Nature 442 ,904 (2006). [3] J. B. Neaton et al., Phys. Rev. Lett. 97, 216405 (2006).

A virtual computer lab for distance biomedical technology education.

PubMed

Locatis, Craig; Vega, Anibal; Bhagwat, Medha; Liu, Wei-Li; Conde, Jose

2008-03-13

The National Library of Medicine's National Center for Biotechnology Information offers mini-courses which entail applying concepts in biochemistry and genetics to search genomics databases and other information sources. They are highly interactive and involve use of 3D molecular visualization software that can be computationally taxing. Methods were devised to offer the courses at a distance so as to provide as much functionality of a computer lab as possible, the venue where they are normally taught. The methods, which can be employed with varied videoconferencing technology and desktop sharing software, were used to deliver mini-courses at a distance in pilot applications where students could see demonstrations by the instructor and the instructor could observe and interact with students working at their remote desktops. Student ratings of the learning experience and comments to open ended questions were similar to those when the courses are offered face to face. The real time interaction and the instructor's ability to access student desktops from a distance in order to provide individual assistance and feedback were considered invaluable. The technologies and methods mimic much of the functionality of computer labs and may be usefully applied in any context where content changes frequently, training needs to be offered on complex computer applications at a distance in real time, and where it is necessary for the instructor to monitor students as they work.

Modelling the spread of innovation in wild birds.

PubMed

Shultz, Thomas R; Montrey, Marcel; Aplin, Lucy M

2017-06-01

We apply three plausible algorithms in agent-based computer simulations to recent experiments on social learning in wild birds. Although some of the phenomena are simulated by all three learning algorithms, several manifestations of social conformity bias are simulated by only the approximate majority (AM) algorithm, which has roots in chemistry, molecular biology and theoretical computer science. The simulations generate testable predictions and provide several explanatory insights into the diffusion of innovation through a population. The AM algorithm's success raises the possibility of its usefulness in studying group dynamics more generally, in several different scientific domains. Our differential-equation model matches simulation results and provides mathematical insights into the dynamics of these algorithms. © 2017 The Author(s).

Applications of genetic programming in cancer research.

PubMed

Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

2009-02-01

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

Integer Linear Programming in Computational Biology

NASA Astrophysics Data System (ADS)

Althaus, Ernst; Klau, Gunnar W.; Kohlbacher, Oliver; Lenhof, Hans-Peter; Reinert, Knut

Computational molecular biology (bioinformatics) is a young research field that is rich in NP-hard optimization problems. The problem instances encountered are often huge and comprise thousands of variables. Since their introduction into the field of bioinformatics in 1997, integer linear programming (ILP) techniques have been successfully applied to many optimization problems. These approaches have added much momentum to development and progress in related areas. In particular, ILP-based approaches have become a standard optimization technique in bioinformatics. In this review, we present applications of ILP-based techniques developed by members and former members of Kurt Mehlhorn’s group. These techniques were introduced to bioinformatics in a series of papers and popularized by demonstration of their effectiveness and potential.

Solving traveling salesman problems with DNA molecules encoding numerical values.

PubMed

Lee, Ji Youn; Shin, Soo-Yong; Park, Tai Hyun; Zhang, Byoung-Tak

2004-12-01

We introduce a DNA encoding method to represent numerical values and a biased molecular algorithm based on the thermodynamic properties of DNA. DNA strands are designed to encode real values by variation of their melting temperatures. The thermodynamic properties of DNA are used for effective local search of optimal solutions using biochemical techniques, such as denaturation temperature gradient polymerase chain reaction and temperature gradient gel electrophoresis. The proposed method was successfully applied to the traveling salesman problem, an instance of optimization problems on weighted graphs. This work extends the capability of DNA computing to solving numerical optimization problems, which is contrasted with other DNA computing methods focusing on logical problem solving.

Computational Design of Molecularly Imprinted Polymers

NASA Astrophysics Data System (ADS)

Subrahmanyam, Sreenath; Piletsky, Sergey A.

Artificial receptors have been in use for several decades as sensor elements, in affinity separation, and as models for investigation of molecular recognition. Although there have been numerous publications on the use of molecular modeling in characterization of their affinity and selectivity, very few attempts have been made on the application of molecular modeling in computational design of synthetic receptors. This chapter discusses recent successes in the use of computational design for the development of one particular branch of synthetic receptors - molecularly imprinted polymers.

A quasi-static continuum model describing interactions between plasmons and non-absorbing biomolecules

NASA Astrophysics Data System (ADS)

Salary, Mohammad Mahdi; Mosallaei, Hossein

2015-06-01

Interactions between the plasmons of noble metal nanoparticles and non-absorbing biomolecules forms the basis of the plasmonic sensors, which have received much attention. Studying these interactions can help to exploit the full potentials of plasmonic sensors in quantification and analysis of biomolecules. Here, a quasi-static continuum model is adopted for this purpose. We present a boundary-element method for computing the optical response of plasmonic particles to the molecular binding events by solving the Poisson equation. The model represents biomolecules with their molecular surfaces, thus accurately accounting for the influence of exact binding conformations as well as structural differences between different proteins on the response of plasmonic nanoparticles. The linear systems arising in the method are solved iteratively with Krylov generalized minimum residual algorithm, and the acceleration is achieved by applying precorrected-Fast Fourier Transformation technique. We apply the developed method to investigate interactions of biotinylated gold nanoparticles (nanosphere and nanorod) with four different types of biotin-binding proteins. The interactions are studied at both ensemble and single-molecule level. Computational results demonstrate the ability of presented model for analyzing realistic nanoparticle-biomolecule configurations. The method can provide comprehensive study for wide variety of applications, including protein structures, monitoring structural and conformational transitions, and quantification of protein concentrations. In addition, it is suitable for design and optimization of the nano-plasmonic sensors.

Exploring transmembrane transport through alpha-hemolysin with grid-steered molecular dynamics.

PubMed

Wells, David B; Abramkina, Volha; Aksimentiev, Aleksei

2007-09-28

The transport of biomolecules across cell boundaries is central to cellular function. While structures of many membrane channels are known, the permeation mechanism is known only for a select few. Molecular dynamics (MD) is a computational method that can provide an accurate description of permeation events at the atomic level, which is required for understanding the transport mechanism. However, due to the relatively short time scales accessible to this method, it is of limited utility. Here, we present a method for all-atom simulation of electric field-driven transport of large solutes through membrane channels, which in tens of nanoseconds can provide a realistic account of a permeation event that would require a millisecond simulation using conventional MD. In this method, the average distribution of the electrostatic potential in a membrane channel under a transmembrane bias of interest is determined first from an all-atom MD simulation. This electrostatic potential, defined on a grid, is subsequently applied to a charged solute to steer its permeation through the membrane channel. We apply this method to investigate permeation of DNA strands, DNA hairpins, and alpha-helical peptides through alpha-hemolysin. To test the accuracy of the method, we computed the relative permeation rates of DNA strands having different sequences and global orientations. The results of the G-SMD simulations were found to be in good agreement in experiment.

Enhanced conformational sampling of nucleic acids by a new Hamiltonian replica exchange molecular dynamics approach.

PubMed

Curuksu, Jeremy; Zacharias, Martin

2009-03-14

Although molecular dynamics (MD) simulations have been applied frequently to study flexible molecules, the sampling of conformational states separated by barriers is limited due to currently possible simulation time scales. Replica-exchange (Rex)MD simulations that allow for exchanges between simulations performed at different temperatures (T-RexMD) can achieve improved conformational sampling. However, in the case of T-RexMD the computational demand grows rapidly with system size. A Hamiltonian RexMD method that specifically enhances coupled dihedral angle transitions has been developed. The method employs added biasing potentials as replica parameters that destabilize available dihedral substates and was applied to study coupled dihedral transitions in nucleic acid molecules. The biasing potentials can be either fixed at the beginning of the simulation or optimized during an equilibration phase. The method was extensively tested and compared to conventional MD simulations and T-RexMD simulations on an adenine dinucleotide system and on a DNA abasic site. The biasing potential RexMD method showed improved sampling of conformational substates compared to conventional MD simulations similar to T-RexMD simulations but at a fraction of the computational demand. It is well suited to study systematically the fine structure and dynamics of large nucleic acids under realistic conditions including explicit solvent and ions and can be easily extended to other types of molecules.

Computer-Based Molecular Modelling: Finnish School Teachers' Experiences and Views

ERIC Educational Resources Information Center

Aksela, Maija; Lundell, Jan

2008-01-01

Modern computer-based molecular modelling opens up new possibilities for chemistry teaching at different levels. This article presents a case study seeking insight into Finnish school teachers' use of computer-based molecular modelling in teaching chemistry, into the different working and teaching methods used, and their opinions about necessary…

Symbolic derivation of high-order Rayleigh-Schroedinger perturbation energies using computer algebra: Application to vibrational-rotational analysis of diatomic molecules

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

Herbert, John M.

1997-01-01

Rayleigh-Schroedinger perturbation theory is an effective and popular tool for describing low-lying vibrational and rotational states of molecules. This method, in conjunction with ab initio techniques for computation of electronic potential energy surfaces, can be used to calculate first-principles molecular vibrational-rotational energies to successive orders of approximation. Because of mathematical complexities, however, such perturbation calculations are rarely extended beyond the second order of approximation, although recent work by Herbert has provided a formula for the nth-order energy correction. This report extends that work and furnishes the remaining theoretical details (including a general formula for the Rayleigh-Schroedinger expansion coefficients) necessary formore » calculation of energy corrections to arbitrary order. The commercial computer algebra software Mathematica is employed to perform the prohibitively tedious symbolic manipulations necessary for derivation of generalized energy formulae in terms of universal constants, molecular constants, and quantum numbers. As a pedagogical example, a Hamiltonian operator tailored specifically to diatomic molecules is derived, and the perturbation formulae obtained from this Hamiltonian are evaluated for a number of such molecules. This work provides a foundation for future analyses of polyatomic molecules, since it demonstrates that arbitrary-order perturbation theory can successfully be applied with the aid of commercially available computer algebra software.« less

Exploiting the spatial locality of electron correlation within the parametric two-electron reduced-density-matrix method

NASA Astrophysics Data System (ADS)

DePrince, A. Eugene; Mazziotti, David A.

2010-01-01

The parametric variational two-electron reduced-density-matrix (2-RDM) method is applied to computing electronic correlation energies of medium-to-large molecular systems by exploiting the spatial locality of electron correlation within the framework of the cluster-in-molecule (CIM) approximation [S. Li et al., J. Comput. Chem. 23, 238 (2002); J. Chem. Phys. 125, 074109 (2006)]. The 2-RDMs of individual molecular fragments within a molecule are determined, and selected portions of these 2-RDMs are recombined to yield an accurate approximation to the correlation energy of the entire molecule. In addition to extending CIM to the parametric 2-RDM method, we (i) suggest a more systematic selection of atomic-orbital domains than that presented in previous CIM studies and (ii) generalize the CIM method for open-shell quantum systems. The resulting method is tested with a series of polyacetylene molecules, water clusters, and diazobenzene derivatives in minimal and nonminimal basis sets. Calculations show that the computational cost of the method scales linearly with system size. We also compute hydrogen-abstraction energies for a series of hydroxyurea derivatives. Abstraction of hydrogen from hydroxyurea is thought to be a key step in its treatment of sickle cell anemia; the design of hydroxyurea derivatives that oxidize more rapidly is one approach to devising more effective treatments.

Synthesis, tautomeric stability, spectroscopy and computational study of a potential molecular switch of (Z)-4-(phenylamino)pent-3-en-2-one

NASA Astrophysics Data System (ADS)

Fahid, Farzaneh; Kanaani, Ayoub; Pourmousavi, Seied Ali; Ajloo, Davood

2017-04-01

The (Z)-4-(phenylamino) pent-3-en-2-one (PAPO) was synthesised applying carbon-based solid acid and described by experimental techniques. Calculated results reveal that its keto-amine form is more stable than its enol-imine form. A relaxed potential energy surface scan has been accomplished based on the optimised geometry of NH tautomeric form to depict the potential energy barrier related to intramolecular proton transfer. The spectroscopic results and theoretical calculations demonstrate that the intramolecular hydrogen bonding strength of PAPO is stronger than that in 4-amino-3-penten-2-one)APO(. In addition, molecular electrostatic potential, total and partial density of stats (TDOS, PDOS) and non-linear optical properties of the compound were studied using same theoretical calculations. Our calculations show that the title molecule has the potential to be used as molecular switch.

Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli

PubMed Central

Gat-Viks, Irit; Chevrier, Nicolas; Wilentzik, Roni; Eisenhaure, Thomas; Raychowdhury, Raktima; Steuerman, Yael; Shalek, Alex; Hacohen, Nir; Amit, Ido; Regev, Aviv

2013-01-01

Individual genetic variation affects gene expression in response to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness QTLs; reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant acts as an activator of the antiviral response; using RNAi, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli. PMID:23503680

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data.

PubMed

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S; Windus, Theresa L; Dick-Perez, Marilu

2017-03-27

A newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides, important for metal extraction chemistry, are parametrized using ParFit. ParFit is in an open source program available for free on GitHub ( https://github.com/fzahari/ParFit ).

A practical method to avoid zero-point leak in molecular dynamics calculations: application to the water dimer.

PubMed

Czakó, Gábor; Kaledin, Alexey L; Bowman, Joel M

2010-04-28

We report the implementation of a previously suggested method to constrain a molecular system to have mode-specific vibrational energy greater than or equal to the zero-point energy in quasiclassical trajectory calculations [J. M. Bowman et al., J. Chem. Phys. 91, 2859 (1989); W. H. Miller et al., J. Chem. Phys. 91, 2863 (1989)]. The implementation is made practical by using a technique described recently [G. Czako and J. M. Bowman, J. Chem. Phys. 131, 244302 (2009)], where a normal-mode analysis is performed during the course of a trajectory and which gives only real-valued frequencies. The method is applied to the water dimer, where its effectiveness is shown by computing mode energies as a function of integration time. Radial distribution functions are also calculated using constrained quasiclassical and standard classical molecular dynamics at low temperature and at 300 K and compared to rigorous quantum path integral calculations.

Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli.

PubMed

Gat-Viks, Irit; Chevrier, Nicolas; Wilentzik, Roni; Eisenhaure, Thomas; Raychowdhury, Raktima; Steuerman, Yael; Shalek, Alex K; Hacohen, Nir; Amit, Ido; Regev, Aviv

2013-04-01

Individual genetic variation affects gene responsiveness to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness quantitative trait loci or reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant responds as an activator of the antiviral response; using RNA interference, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli.

Flow in porous media, phase and ultralow interfacial tensions: Mechanisms of enhanced petroleum recovery

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

Davis, H.T.; Scriven, L.E.

1991-07-01

A major program of university research, longer-ranged and more fundamental in approach than industrial research, into basic mechanisms of enhancing petroleum recovery and into underlying physics, chemistry, geology, applied mathematics, computation, and engineering science has been built at Minnesota. The original focus was surfactant-based chemical flooding, but the approach taken was sufficiently fundamental that the research, longer-ranged than industrial efforts, has become quite multidirectional. Topics discussed are volume controlled porosimetry; fluid distribution and transport in porous media at low wetting phase saturation; molecular dynamics of fluids in ultranarrow pores; molecular dynamics and molecular theory of wetting and adsorption; new numericalmore » methods to handle initial and boundary conditions in immiscible displacement; electron microscopy of surfactant fluid microstructure; low cost system for animating liquid crystallites viewed with polarized light; surfaces of constant mean curvature with prescribed contact angle.« less

Laminar and dorsoventral molecular organization of the medial entorhinal cortex revealed by large-scale anatomical analysis of gene expression.

PubMed

Ramsden, Helen L; Sürmeli, Gülşen; McDonagh, Steven G; Nolan, Matthew F

2015-01-01

Neural circuits in the medial entorhinal cortex (MEC) encode an animal's position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations.

High-Performance First-Principles Molecular Dynamics for Predictive Theory and Modeling

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

Gygi, Francois; Galli, Giulia; Schwegler, Eric

This project focused on developing high-performance software tools for First-Principles Molecular Dynamics (FPMD) simulations, and applying them in investigations of materials relevant to energy conversion processes. FPMD is an atomistic simulation method that combines a quantum-mechanical description of electronic structure with the statistical description provided by molecular dynamics (MD) simulations. This reliance on fundamental principles allows FPMD simulations to provide a consistent description of structural, dynamical and electronic properties of a material. This is particularly useful in systems for which reliable empirical models are lacking. FPMD simulations are increasingly used as a predictive tool for applications such as batteries, solarmore » energy conversion, light-emitting devices, electro-chemical energy conversion devices and other materials. During the course of the project, several new features were developed and added to the open-source Qbox FPMD code. The code was further optimized for scalable operation of large-scale, Leadership-Class DOE computers. When combined with Many-Body Perturbation Theory (MBPT) calculations, this infrastructure was used to investigate structural and electronic properties of liquid water, ice, aqueous solutions, nanoparticles and solid-liquid interfaces. Computing both ionic trajectories and electronic structure in a consistent manner enabled the simulation of several spectroscopic properties, such as Raman spectra, infrared spectra, and sum-frequency generation spectra. The accuracy of the approximations used allowed for direct comparisons of results with experimental data such as optical spectra, X-ray and neutron diffraction spectra. The software infrastructure developed in this project, as applied to various investigations of solids, liquids and interfaces, demonstrates that FPMD simulations can provide a detailed, atomic-scale picture of structural, vibrational and electronic properties of complex systems relevant to energy conversion devices.« less

Laminar and Dorsoventral Molecular Organization of the Medial Entorhinal Cortex Revealed by Large-scale Anatomical Analysis of Gene Expression

PubMed Central

Ramsden, Helen L.; Sürmeli, Gülşen; McDonagh, Steven G.; Nolan, Matthew F.

2015-01-01

Neural circuits in the medial entorhinal cortex (MEC) encode an animal’s position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations. PMID:25615592

A novel in silico approach to drug discovery via computational intelligence.

PubMed

Hecht, David; Fogel, Gary B

2009-04-01

A computational intelligence drug discovery platform is introduced as an innovative technology designed to accelerate high-throughput drug screening for generalized protein-targeted drug discovery. This technology results in collections of novel small molecule compounds that bind to protein targets as well as details on predicted binding modes and molecular interactions. The approach was tested on dihydrofolate reductase (DHFR) for novel antimalarial drug discovery; however, the methods developed can be applied broadly in early stage drug discovery and development. For this purpose, an initial fragment library was defined, and an automated fragment assembly algorithm was generated. These were combined with a computational intelligence screening tool for prescreening of compounds relative to DHFR inhibition. The entire method was assayed relative to spaces of known DHFR inhibitors and with chemical feasibility in mind, leading to experimental validation in future studies.

Transport in Dynamical Astronomy and Multibody Problems

NASA Astrophysics Data System (ADS)

Dellnitz, Michael; Junge, Oliver; Koon, Wang Sang; Lekien, Francois; Lo, Martin W.; Marsden, Jerrold E.; Padberg, Kathrin; Preis, Robert; Ross, Shane D.; Thiere, Bianca

We combine the techniques of almost invariant sets (using tree structured box elimination and graph partitioning algorithms) with invariant manifold and lobe dynamics techniques. The result is a new computational technique for computing key dynamical features, including almost invariant sets, resonance regions as well as transport rates and bottlenecks between regions in dynamical systems. This methodology can be applied to a variety of multibody problems, including those in molecular modeling, chemical reaction rates and dynamical astronomy. In this paper we focus on problems in dynamical astronomy to illustrate the power of the combination of these different numerical tools and their applicability. In particular, we compute transport rates between two resonance regions for the three-body system consisting of the Sun, Jupiter and a third body (such as an asteroid). These resonance regions are appropriate for certain comets and asteroids.

The emerging role of cloud computing in molecular modelling.

PubMed

Ebejer, Jean-Paul; Fulle, Simone; Morris, Garrett M; Finn, Paul W

2013-07-01

There is a growing recognition of the importance of cloud computing for large-scale and data-intensive applications. The distinguishing features of cloud computing and their relationship to other distributed computing paradigms are described, as are the strengths and weaknesses of the approach. We review the use made to date of cloud computing for molecular modelling projects and the availability of front ends for molecular modelling applications. Although the use of cloud computing technologies for molecular modelling is still in its infancy, we demonstrate its potential by presenting several case studies. Rapid growth can be expected as more applications become available and costs continue to fall; cloud computing can make a major contribution not just in terms of the availability of on-demand computing power, but could also spur innovation in the development of novel approaches that utilize that capacity in more effective ways. Copyright © 2013 Elsevier Inc. All rights reserved.

Fragment-Based Electronic Structure Approach for Computing Nuclear Magnetic Resonance Chemical Shifts in Molecular Crystals.

PubMed

Hartman, Joshua D; Beran, Gregory J O

2014-11-11

First-principles chemical shielding tensor predictions play a critical role in studying molecular crystal structures using nuclear magnetic resonance. Fragment-based electronic structure methods have dramatically improved the ability to model molecular crystal structures and energetics using high-level electronic structure methods. Here, a many-body expansion fragment approach is applied to the calculation of chemical shielding tensors in molecular crystals. First, the impact of truncating the many-body expansion at different orders and the role of electrostatic embedding are examined on a series of molecular clusters extracted from molecular crystals. Second, the ability of these techniques to assign three polymorphic forms of the drug sulfanilamide to the corresponding experimental (13)C spectra is assessed. This challenging example requires discriminating among spectra whose (13)C chemical shifts differ by only a few parts per million (ppm) across the different polymorphs. Fragment-based PBE0/6-311+G(2d,p) level chemical shielding predictions correctly assign these three polymorphs and reproduce the sulfanilamide experimental (13)C chemical shifts with 1 ppm accuracy. The results demonstrate that fragment approaches are competitive with the widely used gauge-invariant projector augmented wave (GIPAW) periodic density functional theory calculations.

Molecular-Level Simulations of the Turbulent Taylor-Green Flow

NASA Astrophysics Data System (ADS)

Gallis, M. A.; Bitter, N. P.; Koehler, T. P.; Plimpton, S. J.; Torczynski, J. R.; Papadakis, G.

2017-11-01

The Direct Simulation Monte Carlo (DSMC) method, a statistical, molecular-level technique that provides accurate solutions to the Boltzmann equation, is applied to the turbulent Taylor-Green vortex flow. The goal of this work is to investigate whether DSMC can accurately simulate energy decay in a turbulent flow. If so, then simulating turbulent flows at the molecular level can provide new insights because the energy decay can be examined in detail from molecular to macroscopic length scales, thereby directly linking molecular relaxation processes to macroscopic transport processes. The DSMC simulations are performed on half a million cores of Sequoia, the 17 Pflop platform at Lawrence Livermore National Laboratory, and the kinetic-energy dissipation rate and the energy spectrum are computed directly from the molecular velocities. The DSMC simulations are found to reproduce the Kolmogorov -5/3 law and to agree with corresponding Navier-Stokes simulations obtained using a spectral method. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Operation of micro and molecular machines: a new concept with its origins in interface science.

PubMed

Ariga, Katsuhiko; Ishihara, Shinsuke; Izawa, Hironori; Xia, Hong; Hill, Jonathan P

2011-03-21

A landmark accomplishment of nanotechnology would be successful fabrication of ultrasmall machines that can work like tweezers, motors, or even computing devices. Now we must consider how operation of micro- and molecular machines might be implemented for a wide range of applications. If these machines function only under limited conditions and/or require specialized apparatus then they are useless for practical applications. Therefore, it is important to carefully consider the access of functionality of the molecular or nanoscale systems by conventional stimuli at the macroscopic level. In this perspective, we will outline the position of micro- and molecular machines in current science and technology. Most of these machines are operated by light irradiation, application of electrical or magnetic fields, chemical reactions, and thermal fluctuations, which cannot always be applied in remote machine operation. We also propose strategies for molecular machine operation using the most conventional of stimuli, that of macroscopic mechanical force, achieved through mechanical operation of molecular machines located at an air-water interface. The crucial roles of the characteristics of an interfacial environment, i.e. connection between macroscopic dimension and nanoscopic function, and contact of media with different dielectric natures, are also described.

Proceedings ICASS 2017

NASA Astrophysics Data System (ADS)

Fu, Qiang; Schaaf, Peter

2018-07-01

This special issue of the high impact international peer reviewed journal Applied Surface Science represents the proceedings of the 2nd International Conference on Applied Surface Science ICASS held 12-16 June 2017 in Dalian China. The conference provided a forum for researchers in all areas of applied surface science to present their work. The main topics of the conference are in line with the most popular areas of research reported in Applied Surface Science. Thus, this issue includes current research on the role and use of surfaces in chemical and physical processes, related to catalysis, electrochemistry, surface engineering and functionalization, biointerfaces, semiconductors, 2D-layered materials, surface nanotechnology, energy, new/functional materials and nanotechnology. Also the various techniques and characterization methods will be discussed. Hence, scientific research on the atomic and molecular level of material properties investigated with specific surface analytical techniques and/or computational methods is essential for any further progress in these fields.

Computer-assisted design and synthesis of a highly selective smart adsorbent for extraction of clonazepam from human serum.

PubMed

Aqababa, Heydar; Tabandeh, Mehrdad; Tabatabaei, Meisam; Hasheminejad, Meisam; Emadi, Masoomeh

2013-01-01

A computational approach was applied to screen functional monomers and polymerization solvents for rational design of molecular imprinted polymers (MIPs) as smart adsorbents for solid-phase extraction of clonazepam (CLO) form human serum. The comparison of the computed binding energies of the complexes formed between the template and functional monomers was conducted. The primary computational results were corrected by taking into calculation both the basis set superposition error (BSSE) and the effect of the polymerization solvent using the counterpoise (CP) correction and the polarizable continuum model, respectively. Based on the theoretical calculations, trifluoromethyl acrylic acid (TFMAA) and acrylonitrile (ACN) were found as the best and the worst functional monomers, correspondingly. To test the accuracy of the computational results, three MIPs were synthesized by different functional monomers and their Langmuir-Freundlich (LF) isotherms were studied. The experimental results obtained confirmed the computational results and indicated that the MIP synthesized using TFMAA had the highest affinity for CLO in human serum despite the presence of a vast spectrum of ions. Copyright © 2012 Elsevier B.V. All rights reserved.

Applicability of effective fragment potential version 2 - Molecular dynamics (EFP2-MD) simulations for predicting excess properties of mixed solvents

NASA Astrophysics Data System (ADS)

Kuroki, Nahoko; Mori, Hirotoshi

2018-02-01

Effective fragment potential version 2 - molecular dynamics (EFP2-MD) simulations, where the EFP2 is a polarizable force field based on ab initio electronic structure calculations were applied to water-methanol binary mixture. Comparing EFP2s defined with (aug-)cc-pVXZ (X = D,T) basis sets, it was found that large sets are necessary to generate sufficiently accurate EFP2 for predicting mixture properties. It was shown that EFP2-MD could predict the excess molar volume. Since the computational cost of EFP2-MD are far less than ab initio MD, the results presented herein demonstrate that EFP2-MD is promising for predicting physicochemical properties of novel mixed solvents.

A Series of Molecular Dynamics and Homology Modeling Computer Labs for an Undergraduate Molecular Modeling Course

ERIC Educational Resources Information Center

Elmore, Donald E.; Guayasamin, Ryann C.; Kieffer, Madeleine E.

2010-01-01

As computational modeling plays an increasingly central role in biochemical research, it is important to provide students with exposure to common modeling methods in their undergraduate curriculum. This article describes a series of computer labs designed to introduce undergraduate students to energy minimization, molecular dynamics simulations,…

Using a Computer Animation to Teach High School Molecular Biology

ERIC Educational Resources Information Center

Rotbain, Yosi; Marbach-Ad, Gili; Stavy, Ruth

2008-01-01

We present an active way to use a computer animation in secondary molecular genetics class. For this purpose we developed an activity booklet that helps students to work interactively with a computer animation which deals with abstract concepts and processes in molecular biology. The achievements of the experimental group were compared with those…

Cosolvent-Based Molecular Dynamics for Ensemble Docking: Practical Method for Generating Druggable Protein Conformations.

PubMed

Uehara, Shota; Tanaka, Shigenori

2017-04-24

Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures. In this study, we present a novel strategy that makes use of cosolvent-based molecular dynamics (CMD) simulations for ensemble docking. By mixing small organic molecules into a solvent, CMD can stimulate dynamic protein motions and induce partial conformational changes of binding pocket residues appropriate for the binding of diverse ligands. The present method has been applied to six diverse target proteins and assessed by VS experiments using many actives and decoys of DEKOIS 2.0. The simulation results have revealed that the CMD is beneficial for ensemble docking. Utilizing cosolvent simulation allows the generation of druggable protein conformations, improving the VS performance compared with the use of a single experimental structure or ensemble docking by standard MD with pure water as the solvent.

Molecular dynamic simulations of N2-broadened methane line shapes and comparison with experiments

NASA Astrophysics Data System (ADS)

Le, Tuong; Doménech, José-Luis; Lepère, Muriel; Tran, Ha

2017-03-01

Absorption spectra of methane transitions broadened by nitrogen have been calculated for the first time using classical molecular dynamic simulations. For that, the time evolution of the auto-correlation function of the dipole moment vector, assumed along a C-H axis, was computed using an accurate site-site intermolecular potential for CH4-N2. Quaternion coordinates were used to treat the rotation of the molecules. A requantization procedure was applied to the classical rotation and spectra were then derived as the Fourier-Laplace transform of the auto-correlation function. These computed spectra were compared with experimental ones recorded with a tunable diode laser and a difference-frequency laser spectrometer. Specifically, nine isolated methane lines broadened by nitrogen, belonging to various vibrational bands and having rotational quantum numbers J from 0 to 9, were measured at room temperature and at several pressures from 20 to 945 mbar. Comparisons between measured and calculated spectra were made through their fits using the Voigt profile. The results show that ab initio calculated spectra reproduce with very high fidelity non-Voigt effects on the measurements and that classical molecular dynamic simulations can be used to predict spectral shapes of isolated lines of methane perturbed by nitrogen.

Molecular Dynamics based on a Generalized Born solvation model: application to protein folding

NASA Astrophysics Data System (ADS)

Onufriev, Alexey

2004-03-01

An accurate description of the aqueous environment is essential for realistic biomolecular simulations, but may become very expensive computationally. We have developed a version of the Generalized Born model suitable for describing large conformational changes in macromolecules. The model represents the solvent implicitly as continuum with the dielectric properties of water, and include charge screening effects of salt. The computational cost associated with the use of this model in Molecular Dynamics simulations is generally considerably smaller than the cost of representing water explicitly. Also, compared to traditional Molecular Dynamics simulations based on explicit water representation, conformational changes occur much faster in implicit solvation environment due to the absence of viscosity. The combined speed-up allow one to probe conformational changes that occur on much longer effective time-scales. We apply the model to folding of a 46-residue three helix bundle protein (residues 10-55 of protein A, PDB ID 1BDD). Starting from an unfolded structure at 450 K, the protein folds to the lowest energy state in 6 ns of simulation time, which takes about a day on a 16 processor SGI machine. The predicted structure differs from the native one by 2.4 A (backbone RMSD). Analysis of the structures seen on the folding pathway reveals details of the folding process unavailable form experiment.

Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery.

PubMed

Thomford, Nicholas Ekow; Senthebane, Dimakatso Alice; Rowe, Arielle; Munro, Daniella; Seele, Palesa; Maroyi, Alfred; Dzobo, Kevin

2018-05-25

The therapeutic properties of plants have been recognised since time immemorial. Many pathological conditions have been treated using plant-derived medicines. These medicines are used as concoctions or concentrated plant extracts without isolation of active compounds. Modern medicine however, requires the isolation and purification of one or two active compounds. There are however a lot of global health challenges with diseases such as cancer, degenerative diseases, HIV/AIDS and diabetes, of which modern medicine is struggling to provide cures. Many times the isolation of "active compound" has made the compound ineffective. Drug discovery is a multidimensional problem requiring several parameters of both natural and synthetic compounds such as safety, pharmacokinetics and efficacy to be evaluated during drug candidate selection. The advent of latest technologies that enhance drug design hypotheses such as Artificial Intelligence, the use of 'organ-on chip' and microfluidics technologies, means that automation has become part of drug discovery. This has resulted in increased speed in drug discovery and evaluation of the safety, pharmacokinetics and efficacy of candidate compounds whilst allowing novel ways of drug design and synthesis based on natural compounds. Recent advances in analytical and computational techniques have opened new avenues to process complex natural products and to use their structures to derive new and innovative drugs. Indeed, we are in the era of computational molecular design, as applied to natural products. Predictive computational softwares have contributed to the discovery of molecular targets of natural products and their derivatives. In future the use of quantum computing, computational softwares and databases in modelling molecular interactions and predicting features and parameters needed for drug development, such as pharmacokinetic and pharmacodynamics, will result in few false positive leads in drug development. This review discusses plant-based natural product drug discovery and how innovative technologies play a role in next-generation drug discovery.

Analyzing machupo virus-receptor binding by molecular dynamics simulations.

PubMed

Meyer, Austin G; Sawyer, Sara L; Ellington, Andrew D; Wilke, Claus O

2014-01-01

In many biological applications, we would like to be able to computationally predict mutational effects on affinity in protein-protein interactions. However, many commonly used methods to predict these effects perform poorly in important test cases. In particular, the effects of multiple mutations, non alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here an existing method applied in a novel way to a new test case; we interrogate affinity differences resulting from mutations in a host-virus protein-protein interface. We use steered molecular dynamics (SMD) to computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1). We then approximate affinity using the maximum applied force of separation and the area under the force-versus-distance curve. We find, even without the rigor and planning required for free energy calculations, that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Moreover, we show that this simple SMD scheme correlates well with relative free energy differences computed via free energy perturbation. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our approach provides a framework to compare the effects of multiple mutations, individually and jointly, on protein-protein interactions.

Analyzing machupo virus-receptor binding by molecular dynamics simulations

PubMed Central

Sawyer, Sara L.; Ellington, Andrew D.; Wilke, Claus O.

2014-01-01

In many biological applications, we would like to be able to computationally predict mutational effects on affinity in protein–protein interactions. However, many commonly used methods to predict these effects perform poorly in important test cases. In particular, the effects of multiple mutations, non alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here an existing method applied in a novel way to a new test case; we interrogate affinity differences resulting from mutations in a host–virus protein–protein interface. We use steered molecular dynamics (SMD) to computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1). We then approximate affinity using the maximum applied force of separation and the area under the force-versus-distance curve. We find, even without the rigor and planning required for free energy calculations, that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Moreover, we show that this simple SMD scheme correlates well with relative free energy differences computed via free energy perturbation. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our approach provides a framework to compare the effects of multiple mutations, individually and jointly, on protein–protein interactions. PMID:24624315

Linearly scaling and almost Hamiltonian dielectric continuum molecular dynamics simulations through fast multipole expansions

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

Lorenzen, Konstantin; Mathias, Gerald; Tavan, Paul, E-mail: tavan@physik.uni-muenchen.de

2015-11-14

Hamiltonian Dielectric Solvent (HADES) is a recent method [S. Bauer et al., J. Chem. Phys. 140, 104103 (2014)] which enables atomistic Hamiltonian molecular dynamics (MD) simulations of peptides and proteins in dielectric solvent continua. Such simulations become rapidly impractical for large proteins, because the computational effort of HADES scales quadratically with the number N of atoms. If one tries to achieve linear scaling by applying a fast multipole method (FMM) to the computation of the HADES electrostatics, the Hamiltonian character (conservation of total energy, linear, and angular momenta) may get lost. Here, we show that the Hamiltonian character of HADESmore » can be almost completely preserved, if the structure-adapted fast multipole method (SAMM) as recently redesigned by Lorenzen et al. [J. Chem. Theory Comput. 10, 3244-3259 (2014)] is suitably extended and is chosen as the FMM module. By this extension, the HADES/SAMM forces become exact gradients of the HADES/SAMM energy. Their translational and rotational invariance then guarantees (within the limits of numerical accuracy) the exact conservation of the linear and angular momenta. Also, the total energy is essentially conserved—up to residual algorithmic noise, which is caused by the periodically repeated SAMM interaction list updates. These updates entail very small temporal discontinuities of the force description, because the employed SAMM approximations represent deliberately balanced compromises between accuracy and efficiency. The energy-gradient corrected version of SAMM can also be applied, of course, to MD simulations of all-atom solvent-solute systems enclosed by periodic boundary conditions. However, as we demonstrate in passing, this choice does not offer any serious advantages.« less

New Perspectives on the Charging Mechanisms of Supercapacitors

PubMed Central

2016-01-01

Supercapacitors (or electric double-layer capacitors) are high-power energy storage devices that store charge at the interface between porous carbon electrodes and an electrolyte solution. These devices are already employed in heavy electric vehicles and electronic devices, and can complement batteries in a more sustainable future. Their widespread application could be facilitated by the development of devices that can store more energy, without compromising their fast charging and discharging times. In situ characterization methods and computational modeling techniques have recently been developed to study the molecular mechanisms of charge storage, with the hope that better devices can be rationally designed. In this Perspective, we bring together recent findings from a range of experimental and computational studies to give a detailed picture of the charging mechanisms of supercapacitors. Nuclear magnetic resonance experiments and molecular dynamics simulations have revealed that the electrode pores contain a considerable number of ions in the absence of an applied charging potential. Experiments and computer simulations have shown that different charging mechanisms can then operate when a potential is applied, going beyond the traditional view of charging by counter-ion adsorption. It is shown that charging almost always involves ion exchange (swapping of co-ions for counter-ions), and rarely occurs by counter-ion adsorption alone. We introduce a charging mechanism parameter that quantifies the mechanism and allows comparisons between different systems. The mechanism is found to depend strongly on the polarization of the electrode, and the choice of the electrolyte and electrode materials. In light of these advances we identify new directions for supercapacitor research. Further experimental and computational work is needed to explain the factors that control supercapacitor charging mechanisms, and to establish the links between mechanisms and performance. Increased understanding and control of charging mechanisms should lead to new strategies for developing next-generation supercapacitors with improved performances. PMID:27031622

Molecular Modeling of Lipid Aggregates: Theory and Application

NASA Astrophysics Data System (ADS)

Fenner, Joel Stewart

The ability of cell membranes to perform a wide variety of biological functions stems from the organization and composition of its molecular constituents. There are many engineering applications, such as liposome drug delivery carriers, whose functionality takes advantage of the structure to function relationship of lipid membranes. The fundamental understanding of the relationship between the thermodynamic behavior and structure of lipid membranes and the molecular properties of their lipid constituents is crucial to the successful design of lipid related applications. However, information about how the local microscopic composition of lipid membranes responds to the presence of proteins and nanomaterials is challenging given the intrinsic experimental and theoretical difficulties of studying such small-scale systems. The present work generalizes a self consistent mean field theory for the study of the thermodynamic and structural behavior of lipid bilayers as a function of its molecular composition and physicochemical environments. This novel molecular theory provides with the ability of performing systematic thermodynamic calculations at relatively low computational costs while considering a detailed molecular description of the system under study. The competition of all relevant molecular interactions, such as electrostatics, vdW and chemical equilibria, in the membrane system is described. The developed molecular theory is applied to study how the protonation state of pH-sensitive amphiphiles in a membrane system affects the membrane's morphology. The molecular theory results demonstrate that the protonation state of ionizable groups within amphiphilic membranes shows a highly complex non-monotonic dependence on bulk salt concentration and pH strength. This result suggests that information about the pKa of the molecules is not sufficient to predict the protonation state of the ionizable groups in the membrane system. The molecular theory is also applied to study how the presence of proteins or functionalized nanoparticles near a multicomponent membrane surface leads to changes in its local membrane composition. The results support an electrostatic dependent recruitment mechanism of oncogenic RhoA proteins to the cell membrane. Finally, the molecular theory results describe how nanoparticle functionality and/or membrane molecular composition can be tuned to enhance or suppress nanoparticle adsorption on to phospholipid membranes.

CDAC Student Report: Summary of LLNL Internship

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

Herriman, Jane E.

Multiple objectives motivated me to apply for an internship at LLNL: I wanted to experience the work environment at a national lab, to learn about research and job opportunities at LLNL in particular, and to gain greater experience with code development, particularly within the realm of high performance computing (HPC). This summer I was selected to participate in LLNL's Computational Chemistry and Material Science Summer Institute (CCMS). CCMS is a 10 week program hosted by the Quantum Simulations group leader, Dr. Eric Schwegler. CCMS connects graduate students to mentors at LLNL involved in similar re- search and provides weekly seminarsmore » on a broad array of topics from within chemistry and materials science. Dr. Xavier Andrade and Dr. Erik Draeger served as my co-mentors over the summer, and Dr. Andrade continues to mentor me now that CCMS has concluded. Dr. Andrade is a member of the Quantum Simulations group within the Physical and Life Sciences at LLNL, and Dr. Draeger leads the HPC group within the Center for Applied Scientific Computing (CASC). The two have worked together to develop Qb@ll, an open-source first principles molecular dynamics code that was the platform for my summer research project.« less

Introducing Molecular Life Science Students to Model Building Using Computer Simulations

ERIC Educational Resources Information Center

Aegerter-Wilmsen, Tinri; Kettenis, Dik; Sessink, Olivier; Hartog, Rob; Bisseling, Ton; Janssen, Fred

2006-01-01

Computer simulations can facilitate the building of models of natural phenomena in research, such as in the molecular life sciences. In order to introduce molecular life science students to the use of computer simulations for model building, a digital case was developed in which students build a model of a pattern formation process in…

Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors

PubMed Central

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-01-01

Motivation Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. Results We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. Availability A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm. PMID:21234299

Analysis of ice-binding sites in fish type II antifreeze protein by quantum mechanics.

PubMed

Cheng, Yuhua; Yang, Zuoyin; Tan, Hongwei; Liu, Ruozhuang; Chen, Guangju; Jia, Zongchao

2002-10-01

Many organisms living in cold environments can survive subzero temperatures by producing antifreeze proteins (AFPs) or antifreeze glycoproteins. In this paper we investigate the ice-binding surface of type II AFP by quantum mechanical methods, which, to the best of our knowledge, represents the first time that molecular orbital computational approaches have been applied to AFPs. Molecular mechanical approaches, including molecular docking, energy minimization, and molecular dynamics simulation, were used to obtain optimal systems for subsequent quantum mechanical analysis. We selected 17 surface patches covering the entire surface of the type II AFP and evaluated the interaction energy between each of these patches and two different ice planes using semi-empirical quantum mechanical methods. We have demonstrated the weak orbital overlay phenomenon and the change of bond orders in ice. These results consistently indicate that a surface patch containing 19 residues (K37, L38, Y20, E22, Y21, I19, L57, T56, F53, M127, T128, F129, R17, C7, N6, P5, G10, Q1, and W11) is the most favorable ice-binding site for both a regular ice plane and an ice plane where water O atoms are randomly positioned. Furthermore, for the first time the computation results provide new insights into the weakening of the ice lattice upon AFP binding, which may well be a primary factor leading to AFP-induced ice growth inhibition.

Analysis of ice-binding sites in fish type II antifreeze protein by quantum mechanics.

PubMed Central

Cheng, Yuhua; Yang, Zuoyin; Tan, Hongwei; Liu, Ruozhuang; Chen, Guangju; Jia, Zongchao

2002-01-01

Many organisms living in cold environments can survive subzero temperatures by producing antifreeze proteins (AFPs) or antifreeze glycoproteins. In this paper we investigate the ice-binding surface of type II AFP by quantum mechanical methods, which, to the best of our knowledge, represents the first time that molecular orbital computational approaches have been applied to AFPs. Molecular mechanical approaches, including molecular docking, energy minimization, and molecular dynamics simulation, were used to obtain optimal systems for subsequent quantum mechanical analysis. We selected 17 surface patches covering the entire surface of the type II AFP and evaluated the interaction energy between each of these patches and two different ice planes using semi-empirical quantum mechanical methods. We have demonstrated the weak orbital overlay phenomenon and the change of bond orders in ice. These results consistently indicate that a surface patch containing 19 residues (K37, L38, Y20, E22, Y21, I19, L57, T56, F53, M127, T128, F129, R17, C7, N6, P5, G10, Q1, and W11) is the most favorable ice-binding site for both a regular ice plane and an ice plane where water O atoms are randomly positioned. Furthermore, for the first time the computation results provide new insights into the weakening of the ice lattice upon AFP binding, which may well be a primary factor leading to AFP-induced ice growth inhibition. PMID:12324437

Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors.

PubMed

Kierczak, Marcin; Dramiński, Michał; Koronacki, Jacek; Komorowski, Jan

2010-12-12

Despite more than two decades of research, HIV resistance to drugs remains a serious obstacle in developing efficient AIDS treatments. Several computational methods have been developed to predict resistance level from the sequence of viral proteins such as reverse transcriptase (RT) or protease. These methods, while powerful and accurate, give very little insight into the molecular interactions that underly acquisition of drug resistance/hypersusceptibility. Here, we attempt at filling this gap by using our Monte Carlo feature selection and interdependency discovery method (MCFS-ID) to elucidate molecular interaction networks that characterize viral strains with altered drug resistance levels. We analyzed a number of HIV-1 RT sequences annotated with drug resistance level using the MCFS-ID method. This let us expound interdependency networks that characterize change of drug resistance to six selected RT inhibitors: Abacavir, Lamivudine, Stavudine, Zidovudine, Tenofovir and Nevirapine. The networks consider interdependencies at the level of physicochemical properties of mutating amino acids, eg,: polarity. We mapped each network on the 3D structure of RT in attempt to understand the molecular meaning of interacting pairs. The discovered interactions describe several known drug resistance mechanisms and, importantly, some previously unidentified ones. Our approach can be easily applied to a whole range of problems from the domain of protein engineering. A portable Java implementation of our MCFS-ID method is freely available for academic users and can be obtained at: http://www.ipipan.eu/staff/m.draminski/software.htm.

Systems Biology Methods for Alzheimer's Disease Research Toward Molecular Signatures, Subtypes, and Stages and Precision Medicine: Application in Cohort Studies and Trials.

PubMed

Castrillo, Juan I; Lista, Simone; Hampel, Harald; Ritchie, Craig W

2018-01-01

Alzheimer's disease (AD) is a complex multifactorial disease, involving a combination of genomic, interactome, and environmental factors, with essential participation of (a) intrinsic genomic susceptibility and (b) a constant dynamic interplay between impaired pathways and central homeostatic networks of nerve cells. The proper investigation of the complexity of AD requires new holistic systems-level approaches, at both the experimental and computational level. Systems biology methods offer the potential to unveil new fundamental insights, basic mechanisms, and networks and their interplay. These may lead to the characterization of mechanism-based molecular signatures, and AD hallmarks at the earliest molecular and cellular levels (and beyond), for characterization of AD subtypes and stages, toward targeted interventions according to the evolving precision medicine paradigm. In this work, an update on advanced systems biology methods and strategies for holistic studies of multifactorial diseases-particularly AD-is presented. This includes next-generation genomics, neuroimaging and multi-omics methods, experimental and computational approaches, relevant disease models, and latest genome editing and single-cell technologies. Their progressive incorporation into basic research, cohort studies, and trials is beginning to provide novel insights into AD essential mechanisms, molecular signatures, and markers toward mechanism-based classification and staging, and tailored interventions. Selected methods which can be applied in cohort studies and trials, with the European Prevention of Alzheimer's Dementia (EPAD) project as a reference example, are presented and discussed.

DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.

PubMed

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-08-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/.

AWE-WQ: fast-forwarding molecular dynamics using the accelerated weighted ensemble.

PubMed

Abdul-Wahid, Badi'; Feng, Haoyun; Rajan, Dinesh; Costaouec, Ronan; Darve, Eric; Thain, Douglas; Izaguirre, Jesús A

2014-10-27

A limitation of traditional molecular dynamics (MD) is that reaction rates are difficult to compute. This is due to the rarity of observing transitions between metastable states since high energy barriers trap the system in these states. Recently the weighted ensemble (WE) family of methods have emerged which can flexibly and efficiently sample conformational space without being trapped and allow calculation of unbiased rates. However, while WE can sample correctly and efficiently, a scalable implementation applicable to interesting biomolecular systems is not available. We provide here a GPLv2 implementation called AWE-WQ of a WE algorithm using the master/worker distributed computing WorkQueue (WQ) framework. AWE-WQ is scalable to thousands of nodes and supports dynamic allocation of computer resources, heterogeneous resource usage (such as central processing units (CPU) and graphical processing units (GPUs) concurrently), seamless heterogeneous cluster usage (i.e., campus grids and cloud providers), and support for arbitrary MD codes such as GROMACS, while ensuring that all statistics are unbiased. We applied AWE-WQ to a 34 residue protein which simulated 1.5 ms over 8 months with peak aggregate performance of 1000 ns/h. Comparison was done with a 200 μs simulation collected on a GPU over a similar timespan. The folding and unfolded rates were of comparable accuracy.

Incorporating modeling and simulations in undergraduate biophysical chemistry course to promote understanding of structure-dynamics-function relationships in proteins.

PubMed

Hati, Sanchita; Bhattacharyya, Sudeep

2016-01-01

A project-based biophysical chemistry laboratory course, which is offered to the biochemistry and molecular biology majors in their senior year, is described. In this course, the classroom study of the structure-function of biomolecules is integrated with the discovery-guided laboratory study of these molecules using computer modeling and simulations. In particular, modern computational tools are employed to elucidate the relationship between structure, dynamics, and function in proteins. Computer-based laboratory protocols that we introduced in three modules allow students to visualize the secondary, super-secondary, and tertiary structures of proteins, analyze non-covalent interactions in protein-ligand complexes, develop three-dimensional structural models (homology model) for new protein sequences and evaluate their structural qualities, and study proteins' intrinsic dynamics to understand their functions. In the fourth module, students are assigned to an authentic research problem, where they apply their laboratory skills (acquired in modules 1-3) to answer conceptual biophysical questions. Through this process, students gain in-depth understanding of protein dynamics-the missing link between structure and function. Additionally, the requirement of term papers sharpens students' writing and communication skills. Finally, these projects result in new findings that are communicated in peer-reviewed journals. © 2016 The International Union of Biochemistry and Molecular Biology.

DDBJ Read Annotation Pipeline: A Cloud Computing-Based Pipeline for High-Throughput Analysis of Next-Generation Sequencing Data

PubMed Central

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-01-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/. PMID:23657089

Computing UV/vis spectra using a combined molecular dynamics and quantum chemistry approach: bis-triazin-pyridine (BTP) ligands studied in solution.

PubMed

Höfener, Sebastian; Trumm, Michael; Koke, Carsten; Heuser, Johannes; Ekström, Ulf; Skerencak-Frech, Andrej; Schimmelpfennig, Bernd; Panak, Petra J

2016-03-21

We report a combined computational and experimental study to investigate the UV/vis spectra of 2,6-bis(5,6-dialkyl-1,2,4-triazin-3-yl)pyridine (BTP) ligands in solution. In order to study molecules in solution using theoretical methods, force-field parameters for the ligand-water interaction are adjusted to ab initio quantum chemical calculations. Based on these parameters, molecular dynamics (MD) simulations are carried out from which snapshots are extracted as input to quantum chemical excitation-energy calculations to obtain UV/vis spectra of BTP ligands in solution using time-dependent density functional theory (TDDFT) employing the Tamm-Dancoff approximation (TDA). The range-separated CAM-B3LYP functional is used to avoid large errors for charge-transfer states occurring in the electronic spectra. In order to study environment effects with theoretical methods, the frozen-density embedding scheme is applied. This computational procedure allows to obtain electronic spectra calculated at the (range-separated) DFT level of theory in solution, revealing solvatochromic shifts upon solvation of up to about 0.6 eV. Comparison to experimental data shows a significantly improved agreement compared to vacuum calculations and enables the analysis of relevant excitations for the line shape in solution.

Joint density-functional theory for energetics and spectroscopy in complex aqueous and nonaqueous solvents

NASA Astrophysics Data System (ADS)

Gunceler, Deniz

Solvents are of great importance in many technological applications, but are difficult to study using standard, off-the-shelf ab initio electronic structure methods. This is because a single configuration of molecular positions in the solvent (a "snapshot" of the fluid) is not necessarily representative of the thermodynamic average. To obtain any thermodynamic averages (e.g. free energies), the phase space of the solvent must be sampled, typically using molecular dynamics. This greatly increases the computational cost involved in studying solvated systems. Joint density-functional theory has made its mark by being a computationally efficient yet rigorous theory by which to study solvation. It replaces the need for thermodynamic sampling with an effective continuum description of the solvent environment that is in-principle exact, computationally efficient and intuitive (easier to interpret). It has been very successful in aqueous systems, with potential applications in (among others) energy materials discovery, catalysis and surface science. In this dissertation, we develop accurate and fast joint density functional theories for complex, non-aqueous solvent enviroments, including organic solvents and room temperature ionic liquids, as well as new methods for calculating electron excitation spectra in such systems. These theories are then applied to a range of physical problems, from dendrite formation in lithium-metal batteries to the optical spectra of solvated ions.

Computationally Guided Design of Polymer Electrolytes for Battery Applications

NASA Astrophysics Data System (ADS)

Wang, Zhen-Gang; Webb, Michael; Savoie, Brett; Miller, Thomas

We develop an efficient computational framework for guiding the design of polymer electrolytes for Li battery applications. Short-times molecular dynamics (MD) simulations are employed to identify key structural and dynamic features in the solvation and motion of Li ions, such as the structure of the solvation shells, the spatial distribution of solvation sites, and the polymer segmental mobility. Comparative studies on six polyester-based polymers and polyethylene oxide (PEO) yield good agreement with experimental data on the ion conductivities, and reveal significant differences in the ion diffusion mechanism between PEO and the polyesters. The molecular insights from the MD simulations are used to build a chemically specific coarse-grained model in the spirit of the dynamic bond percolation model of Druger, Ratner and Nitzan. We apply this coarse-grained model to characterize Li ion diffusion in several existing and yet-to-be synthesized polyethers that differ by oxygen content and backbone stiffness. Good agreement is obtained between the predictions of the coarse-grained model and long-timescale atomistic MD simulations, thus providing validation of the model. Our study predicts higher Li ion diffusivity in poly(trimethylene oxide-alt-ethylene oxide) than in PEO. These results demonstrate the potential of this computational framework for rapid screening of new polymer electrolytes based on ion diffusivity.

AWE-WQ: Fast-Forwarding Molecular Dynamics Using the Accelerated Weighted Ensemble

PubMed Central

2015-01-01

A limitation of traditional molecular dynamics (MD) is that reaction rates are difficult to compute. This is due to the rarity of observing transitions between metastable states since high energy barriers trap the system in these states. Recently the weighted ensemble (WE) family of methods have emerged which can flexibly and efficiently sample conformational space without being trapped and allow calculation of unbiased rates. However, while WE can sample correctly and efficiently, a scalable implementation applicable to interesting biomolecular systems is not available. We provide here a GPLv2 implementation called AWE-WQ of a WE algorithm using the master/worker distributed computing WorkQueue (WQ) framework. AWE-WQ is scalable to thousands of nodes and supports dynamic allocation of computer resources, heterogeneous resource usage (such as central processing units (CPU) and graphical processing units (GPUs) concurrently), seamless heterogeneous cluster usage (i.e., campus grids and cloud providers), and support for arbitrary MD codes such as GROMACS, while ensuring that all statistics are unbiased. We applied AWE-WQ to a 34 residue protein which simulated 1.5 ms over 8 months with peak aggregate performance of 1000 ns/h. Comparison was done with a 200 μs simulation collected on a GPU over a similar timespan. The folding and unfolded rates were of comparable accuracy. PMID:25207854

Identifying the Interaction of Vancomycin With Novel pH-Responsive Lipids as Antibacterial Biomaterials Via Accelerated Molecular Dynamics and Binding Free Energy Calculations.

PubMed

Ahmed, Shaimaa; Vepuri, Suresh B; Jadhav, Mahantesh; Kalhapure, Rahul S; Govender, Thirumala

2018-06-01

Nano-drug delivery systems have proven to be an efficient formulation tool to overcome the challenges with current antibiotics therapy and resistance. A series of pH-responsive lipid molecules were designed and synthesized for future liposomal formulation as a nano-drug delivery system for vancomycin at the infection site. The structures of these lipids differ from each other in respect of hydrocarbon tails: Lipid1, 2, 3 and 4 have stearic, oleic, linoleic, and linolenic acid hydrocarbon chains, respectively. The impact of variation in the hydrocarbon chain in the lipid structure on drug encapsulation and release profile, as well as mode of drug interaction, was investigated using molecular modeling analyses. A wide range of computational tools, including accelerated molecular dynamics, normal molecular dynamics, binding free energy calculations and principle component analysis, were applied to provide comprehensive insight into the interaction landscape between vancomycin and the designed lipid molecules. Interestingly, both MM-GBSA and MM-PBSA binding affinity calculations using normal molecular dynamics and accelerated molecular dynamics trajectories showed a very consistent trend, where the order of binding affinity towards vancomycin was lipid4 > lipid1 > lipid2 > lipid3. From both normal molecular dynamics and accelerated molecular dynamics, the interaction of lipid3 with vancomycin is demonstrated to be the weakest (∆G binding  = -2.17 and -11.57, for normal molecular dynamics and accelerated molecular dynamics, respectively) when compared to other complexes. We believe that the degree of unsaturation of the hydrocarbon chain in the lipid molecules may impact on the overall conformational behavior, interaction mode and encapsulation (wrapping) of the lipid molecules around the vancomycin molecule. This thorough computational analysis prior to the experimental investigation is a valuable approach to guide for predicting the encapsulation ability, drug release and further development of novel liposome-based pH-responsive nano-drug delivery system with refined structural and chemical features of potential lipid molecule for formulation development.

Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data.

PubMed

Narimani, Zahra; Beigy, Hamid; Ahmad, Ashar; Masoudi-Nejad, Ali; Fröhlich, Holger

2017-01-01

Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. We devise a novel Bayesian network reverse engineering approach using ordinary differential equations with the ability to include non-linearity. Besides modeling arbitrary, possibly combinatorial and time dependent perturbations with unknown targets, one of our main contributions is the use of Expectation Propagation, an algorithm for approximate Bayesian inference over large scale network structures in short computation time. We further explore the possibility of integrating prior knowledge into network inference. We evaluate the proposed model on DREAM4 and DREAM8 data and find it competitive against several state-of-the-art existing network inference methods.

A substrate selectivity and inhibitor design lesson from the PDE10-cAMP crystal structure: a computational study.

PubMed

Lau, Justin Kai-Chi; Li, Xiao-Bo; Cheng, Yuen-Kit

2010-04-22

Phosphodiesterases (PDEs) catalyze the hydrolysis of second messengers cAMP and cGMP in regulating many important cellular signals and have been recognized as important drug targets. Experimentally, a range of specificity/selectivity toward cAMP and cGMP is well-known for the individual PDE families. The study reported here reveals that PDEs might also exhibit selectivity toward conformations of the endogenous substrates cAMP and cGMP. Molecular dynamics simulations and free energy study have been applied to study the binding of the cAMP torsional conformers about the glycosyl bond in PDE10A2. The computational results elucidated that PDE10A2 is energetically more favorable in complex with the syn cAMP conformer (as reported in the crystal structure) and the binding of anti cAMP to PDE10A2 would lead to either a nonreactive configuration or significant perturbation on the catalytic pocket of the enzyme. This experimentally inaccessible information provides important molecular insights for the development of effective PDE10 ligands.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

PubMed

Kalantzis, Georgios

2009-06-01

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

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

PubMed

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

2016-02-18

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

Enhanced conformational sampling of carbohydrates by Hamiltonian replica-exchange simulation.

PubMed

Mishra, Sushil Kumar; Kara, Mahmut; Zacharias, Martin; Koca, Jaroslav

2014-01-01

Knowledge of the structure and conformational flexibility of carbohydrates in an aqueous solvent is important to improving our understanding of how carbohydrates function in biological systems. In this study, we extend a variant of the Hamiltonian replica-exchange molecular dynamics (MD) simulation to improve the conformational sampling of saccharides in an explicit solvent. During the simulations, a biasing potential along the glycosidic-dihedral linkage between the saccharide monomer units in an oligomer is applied at various levels along the replica runs to enable effective transitions between various conformations. One reference replica runs under the control of the original force field. The method was tested on disaccharide structures and further validated on biologically relevant blood group B, Lewis X and Lewis A trisaccharides. The biasing potential-based replica-exchange molecular dynamics (BP-REMD) method provided a significantly improved sampling of relevant conformational states compared with standard continuous MD simulations, with modest computational costs. Thus, the proposed BP-REMD approach adds a new dimension to existing carbohydrate conformational sampling approaches by enhancing conformational sampling in the presence of solvent molecules explicitly at relatively low computational cost.

Fabrication of an electrochemical sensor based on computationally designed molecularly imprinted polymer for the determination of mesalamine in real samples.

PubMed

Torkashvand, M; Gholivand, M B; Taherkhani, F

2015-10-01

A novel electrochemical sensor based on mesalamine molecularly imprinted polymer (MIP) film on a glassy carbon electrode was fabricated. Density functional theory (DFT) in gas and solution phases was developed to study the intermolecular interactions in the pre-polymerization mixture and to find the suitable functional monomers in MIP preparation. On the basis of computational results, o-phenylenediamine (OP), gallic acid (GA) and p-aminobenzoic acid (ABA) were selected as functional monomers. The MIP film was cast on glassy carbon electrode by electropolymerization of solution containing ternary monomers and then followed by Ag dendrites (AgDs) with nanobranch deposition. The surface feature of the modified electrode (AgDs/MIP/GCE) was characterized by scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). Under the optimal experimental conditions, the peak current was proportional to the concentration of mesalamine ranging from 0.05 to 100 μM, with the detection limit of 0.015 μM. The proposed sensor was applied successfully for mesalamine determination in real samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Fast recovery of free energy landscapes via diffusion-map-directed molecular dynamics.

PubMed

Preto, Jordane; Clementi, Cecilia

2014-09-28

The reaction pathways characterizing macromolecular systems of biological interest are associated with high free energy barriers. Resorting to the standard all-atom molecular dynamics (MD) to explore such critical regions may be inappropriate as the time needed to observe the relevant transitions can be remarkably long. In this paper, we present a new method called Extended Diffusion-Map-directed Molecular Dynamics (extended DM-d-MD) used to enhance the sampling of MD trajectories in such a way as to rapidly cover all important regions of the free energy landscape including deep metastable states and critical transition paths. Moreover, extended DM-d-MD was combined with a reweighting scheme enabling to save on-the-fly information about the Boltzmann distribution. Our algorithm was successfully applied to two systems, alanine dipeptide and alanine-12. Due to the enhanced sampling, the Boltzmann distribution is recovered much faster than in plain MD simulations. For alanine dipeptide, we report a speedup of one order of magnitude with respect to plain MD simulations. For alanine-12, our algorithm allows us to highlight all important unfolded basins in several days of computation when one single misfolded event is barely observable within the same amount of computational time by plain MD simulations. Our method is reaction coordinate free, shows little dependence on the a priori knowledge of the system, and can be implemented in such a way that the biased steps are not computationally expensive with respect to MD simulations thus making our approach well adapted for larger complex systems from which little information is known.

Quantum computing applied to calculations of molecular energies: CH2 benchmark.

PubMed

Veis, Libor; Pittner, Jiří

2010-11-21

Quantum computers are appealing for their ability to solve some tasks much faster than their classical counterparts. It was shown in [Aspuru-Guzik et al., Science 309, 1704 (2005)] that they, if available, would be able to perform the full configuration interaction (FCI) energy calculations with a polynomial scaling. This is in contrast to conventional computers where FCI scales exponentially. We have developed a code for simulation of quantum computers and implemented our version of the quantum FCI algorithm. We provide a detailed description of this algorithm and the results of the assessment of its performance on the four lowest lying electronic states of CH(2) molecule. This molecule was chosen as a benchmark, since its two lowest lying (1)A(1) states exhibit a multireference character at the equilibrium geometry. It has been shown that with a suitably chosen initial state of the quantum register, one is able to achieve the probability amplification regime of the iterative phase estimation algorithm even in this case.

Digital pathology in nephrology clinical trials, research, and pathology practice.

PubMed

Barisoni, Laura; Hodgin, Jeffrey B

2017-11-01

In this review, we will discuss (i) how the recent advancements in digital technology and computational engineering are currently applied to nephropathology in the setting of clinical research, trials, and practice; (ii) the benefits of the new digital environment; (iii) how recognizing its challenges provides opportunities for transformation; and (iv) nephropathology in the upcoming era of kidney precision and predictive medicine. Recent studies highlighted how new standardized protocols facilitate the harmonization of digital pathology database infrastructure and morphologic, morphometric, and computer-aided quantitative analyses. Digital pathology enables robust protocols for clinical trials and research, with the potential to identify previously underused or unrecognized clinically useful parameters. The integration of digital pathology with molecular signatures is leading the way to establishing clinically relevant morpho-omic taxonomies of renal diseases. The introduction of digital pathology in clinical research and trials, and the progressive implementation of the modern software ecosystem, opens opportunities for the development of new predictive diagnostic paradigms and computer-aided algorithms, transforming the practice of renal disease into a modern computational science.

Computational revelation of binding mechanisms of inhibitors to endocellular protein tyrosine phosphatase 1B using molecular dynamics simulations.

PubMed

Yan, Fangfang; Liu, Xinguo; Zhang, Shaolong; Su, Jing; Zhang, Qinggang; Chen, Jianzhong

2017-11-06

Endocellular protein tyrosine phosphatase 1B (PTP1B) is one of the most promising target for designing and developing drugs to cure type-II diabetes and obesity. Molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) and solvated interaction energy methods were applied to study binding differences of three inhibitors (ID: 901, 941, and 968) to PTP1B, the calculated results show that the inhibitor 901 has the strongest binding ability to PTP1B among the current inhibitors. Principal component (PC) analysis was also carried out to investigate the conformational change of PTP1B, and the results indicate that the associations of inhibitors with PTP1B generate a significant effect on the motion of the WPD-loop. Free energy decomposition method was applied to study the contributions of individual residues to inhibitor bindings, it is found that three inhibitors can generate hydrogen bonding interactions and hydrophobic interactions with different residues of PTP1B, which provide important forces for associations of inhibitors with PTP1B. This research is expected to give a meaningfully theoretical guidance to design and develop of effective drugs curing type-II diabetes and obesity.

Stochastic computing with biomolecular automata

PubMed Central

Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud

2004-01-01

Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure. PMID:15215499

Efficient approach to obtain free energy gradient using QM/MM MD simulation

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

Asada, Toshio; Koseki, Shiro; The Research Institute for Molecular Electronic Devices

2015-12-31

The efficient computational approach denoted as charge and atom dipole response kernel (CDRK) model to consider polarization effects of the quantum mechanical (QM) region is described using the charge response and the atom dipole response kernels for free energy gradient (FEG) calculations in the quantum mechanical/molecular mechanical (QM/MM) method. CDRK model can reasonably reproduce energies and also energy gradients of QM and MM atoms obtained by expensive QM/MM calculations in a drastically reduced computational time. This model is applied on the acylation reaction in hydrated trypsin-BPTI complex to optimize the reaction path on the free energy surface by means ofmore » FEG and the nudged elastic band (NEB) method.« less

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226

Molecular modeling of biomolecules by paramagnetic NMR and computational hybrid methods.

PubMed

Pilla, Kala Bharath; Gaalswyk, Kari; MacCallum, Justin L

2017-11-01

The 3D atomic structures of biomolecules and their complexes are key to our understanding of biomolecular function, recognition, and mechanism. However, it is often difficult to obtain structures, particularly for systems that are complex, dynamic, disordered, or exist in environments like cell membranes. In such cases sparse data from a variety of paramagnetic NMR experiments offers one possible source of structural information. These restraints can be incorporated in computer modeling algorithms that can accurately translate the sparse experimental data into full 3D atomic structures. In this review, we discuss various types of paramagnetic NMR/computational hybrid modeling techniques that can be applied to successful modeling of not only the atomic structure of proteins but also their interacting partners. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.

Second order Møller-Plesset and coupled cluster singles and doubles methods with complex basis functions for resonances in electron-molecule scattering

DOE PAGES

White, Alec F.; Epifanovsky, Evgeny; McCurdy, C. William; ...

2017-06-21

The method of complex basis functions is applied to molecular resonances at correlated levels of theory. Møller-Plesset perturbation theory at second order and equation-of-motion electron attachment coupled-cluster singles and doubles (EOM-EA-CCSD) methods based on a non-Hermitian self-consistent-field reference are used to compute accurate Siegert energies for shape resonances in small molecules including N 2 - , CO - , CO 2 - , and CH 2 O - . Analytic continuation of complex θ-trajectories is used to compute Siegert energies, and the θ-trajectories of energy differences are found to yield more consistent results than those of total energies.more » Furthermore, the ability of such methods to accurately compute complex potential energy surfaces is investigated, and the possibility of using EOM-EA-CCSD for Feshbach resonances is explored in the context of e-helium scattering.« less

Modeling molecule-plasmon interactions using quantized radiation fields within time-dependent electronic structure theory

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

Nascimento, Daniel R.; DePrince, A. Eugene, E-mail: deprince@chem.fsu.edu

2015-12-07

We present a combined cavity quantum electrodynamics/ab initio electronic structure approach for simulating plasmon-molecule interactions in the time domain. The simple Jaynes-Cummings-type model Hamiltonian typically utilized in such simulations is replaced with one in which the molecular component of the coupled system is treated in a fully ab initio way, resulting in a computationally efficient description of general plasmon-molecule interactions. Mutual polarization effects are easily incorporated within a standard ground-state Hartree-Fock computation, and time-dependent simulations carry the same formal computational scaling as real-time time-dependent Hartree-Fock theory. As a proof of principle, we apply this generalized method to the emergence ofmore » a Fano-like resonance in coupled molecule-plasmon systems; this feature is quite sensitive to the nanoparticle-molecule separation and the orientation of the molecule relative to the polarization of the external electric field.« less

Second order Møller-Plesset and coupled cluster singles and doubles methods with complex basis functions for resonances in electron-molecule scattering

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

White, Alec F.; Epifanovsky, Evgeny; McCurdy, C. William

The method of complex basis functions is applied to molecular resonances at correlated levels of theory. Møller-Plesset perturbation theory at second order and equation-of-motion electron attachment coupled-cluster singles and doubles (EOM-EA-CCSD) methods based on a non-Hermitian self-consistent-field reference are used to compute accurate Siegert energies for shape resonances in small molecules including N 2 - , CO - , CO 2 - , and CH 2 O - . Analytic continuation of complex θ-trajectories is used to compute Siegert energies, and the θ-trajectories of energy differences are found to yield more consistent results than those of total energies.more » Furthermore, the ability of such methods to accurately compute complex potential energy surfaces is investigated, and the possibility of using EOM-EA-CCSD for Feshbach resonances is explored in the context of e-helium scattering.« less

Perspective: Ring-polymer instanton theory

NASA Astrophysics Data System (ADS)

Richardson, Jeremy O.

2018-05-01

Since the earliest explorations of quantum mechanics, it has been a topic of great interest that quantum tunneling allows particles to penetrate classically insurmountable barriers. Instanton theory provides a simple description of these processes in terms of dominant tunneling pathways. Using a ring-polymer discretization, an efficient computational method is obtained for applying this theory to compute reaction rates and tunneling splittings in molecular systems. Unlike other quantum-dynamics approaches, the method scales well with the number of degrees of freedom, and for many polyatomic systems, the method may provide the most accurate predictions which can be practically computed. Instanton theory thus has the capability to produce useful data for many fields of low-temperature chemistry including spectroscopy, atmospheric and astrochemistry, as well as surface science. There is however still room for improvement in the efficiency of the numerical algorithms, and new theories are under development for describing tunneling in nonadiabatic transitions.

A mechanical Turing machine: blueprint for a biomolecular computer

PubMed Central

Shapiro, Ehud

2012-01-01

We describe a working mechanical device that embodies the theoretical computing machine of Alan Turing, and as such is a universal programmable computer. The device operates on three-dimensional building blocks by applying mechanical analogues of polymer elongation, cleavage and ligation, movement along a polymer, and control by molecular recognition unleashing allosteric conformational changes. Logically, the device is not more complicated than biomolecular machines of the living cell, and all its operations are part of the standard repertoire of these machines; hence, a biomolecular embodiment of the device is not infeasible. If implemented, such a biomolecular device may operate in vivo, interacting with its biochemical environment in a program-controlled manner. In particular, it may ‘compute’ synthetic biopolymers and release them into its environment in response to input from the environment, a capability that may have broad pharmaceutical and biological applications. PMID:22649583

Boolean logic tree of graphene-based chemical system for molecular computation and intelligent molecular search query.

PubMed

Huang, Wei Tao; Luo, Hong Qun; Li, Nian Bing

2014-05-06

The most serious, and yet unsolved, problem of constructing molecular computing devices consists in connecting all of these molecular events into a usable device. This report demonstrates the use of Boolean logic tree for analyzing the chemical event network based on graphene, organic dye, thrombin aptamer, and Fenton reaction, organizing and connecting these basic chemical events. And this chemical event network can be utilized to implement fluorescent combinatorial logic (including basic logic gates and complex integrated logic circuits) and fuzzy logic computing. On the basis of the Boolean logic tree analysis and logic computing, these basic chemical events can be considered as programmable "words" and chemical interactions as "syntax" logic rules to construct molecular search engine for performing intelligent molecular search query. Our approach is helpful in developing the advanced logic program based on molecules for application in biosensing, nanotechnology, and drug delivery.

GPU-Accelerated Molecular Modeling Coming Of Age

PubMed Central

Stone, John E.; Hardy, David J.; Ufimtsev, Ivan S.

2010-01-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. PMID:20675161

GPU-accelerated molecular modeling coming of age.

PubMed

Stone, John E; Hardy, David J; Ufimtsev, Ivan S; Schulten, Klaus

2010-09-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. (c) 2010 Elsevier Inc. All rights reserved.

Teaching 1H NMR Spectrometry Using Computer Modeling.

ERIC Educational Resources Information Center

Habata, Yoichi; Akabori, Sadatoshi

2001-01-01

Molecular modeling by computer is used to display stereochemistry, molecular orbitals, structure of transition states, and progress of reactions. Describes new ideas for teaching 1H NMR spectroscopy using computer modeling. (Contains 12 references.) (ASK)

Informing Mechanistic Toxicology with Computational Molecular Models

EPA Science Inventory

Computational molecular models of chemicals interacting with biomolecular targets provides toxicologists a valuable, affordable, and sustainable source of in silico molecular level information that augments, enriches, and complements in vitro and in vivo effo...

Key issues in the computational simulation of GPCR function: representation of loop domains

NASA Astrophysics Data System (ADS)

Mehler, E. L.; Periole, X.; Hassan, S. A.; Weinstein, H.

2002-11-01

Some key concerns raised by molecular modeling and computational simulation of functional mechanisms for membrane proteins are discussed and illustrated for members of the family of G protein coupled receptors (GPCRs). Of particular importance are issues related to the modeling and computational treatment of loop regions. These are demonstrated here with results from different levels of computational simulations applied to the structures of rhodopsin and a model of the 5-HT2A serotonin receptor, 5-HT2AR. First, comparative Molecular Dynamics (MD) simulations are reported for rhodopsin in vacuum and embedded in an explicit representation of the membrane and water environment. It is shown that in spite of a partial accounting of solvent screening effects by neutralization of charged side chains, vacuum MD simulations can lead to severe distortions of the loop structures. The primary source of the distortion appears to be formation of artifactual H-bonds, as has been repeatedly observed in vacuum simulations. To address such shortcomings, a recently proposed approach that has been developed for calculating the structure of segments that connect elements of secondary structure with known coordinates, is applied to 5-HT2AR to obtain an initial representation of the loops connecting the transmembrane (TM) helices. The approach consists of a simulated annealing combined with biased scaled collective variables Monte Carlo technique, and is applied to loops connecting the TM segments on both the extra-cellular and the cytoplasmic sides of the receptor. Although this initial calculation treats the loops as independent structural entities, the final structure exhibits a number of interloop interactions that may have functional significance. Finally, it is shown here that in the case where a given loop from two different GPCRs (here rhodopsin and 5-HT2AR) has approximately the same length and some degree of sequence identity, the fold adopted by the loops can be similar. Thus, in such special cases homology modeling might be used to obtain initial structures of these loops. Notably, however, all other loops in these two receptors appear to be very different in sequence and structure, so that their conformations can be found reliably only by ab initio, energy based methods and not by homology modeling.

A generalized crystal-cutting method for modeling arbitrarily oriented crystals in 3D periodic simulation cells with applications to crystal-crystal interfaces

NASA Astrophysics Data System (ADS)

Kroonblawd, Matthew P.; Mathew, Nithin; Jiang, Shan; Sewell, Thomas D.

2016-10-01

A Generalized Crystal-Cutting Method (GCCM) is developed that automates construction of three-dimensionally periodic simulation cells containing arbitrarily oriented single crystals and thin films, two-dimensionally (2D) infinite crystal-crystal homophase and heterophase interfaces, and nanostructures with intrinsic N-fold interfaces. The GCCM is based on a simple mathematical formalism that facilitates easy definition of constraints on cut crystal geometries. The method preserves the translational symmetry of all Bravais lattices and thus can be applied to any crystal described by such a lattice including complicated, low-symmetry molecular crystals. Implementations are presented with carefully articulated combinations of loop searches and constraints that drastically reduce computational complexity compared to simple loop searches. Orthorhombic representations of monoclinic and triclinic crystals found using the GCCM overcome some limitations in standard distributions of popular molecular dynamics software packages. Stability of grain boundaries in β-HMX was investigated using molecular dynamics and molecular statics simulations with 2D infinite crystal-crystal homophase interfaces created using the GCCM. The order of stabilities for the four grain boundaries studied is predicted to correlate with the relative prominence of particular crystal faces in lab-grown β-HMX crystals. We demonstrate how nanostructures can be constructed through simple constraints applied in the GCCM framework. Example GCCM constructions are shown that are relevant to some current problems in materials science, including shock sensitivity of explosives, layered electronic devices, and pharmaceuticals.

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP), Basic Science Program, HLA Immunogenetics Section, under the leadership of Dr. Mary Carrington, studies the influence of human leukocyte antigens (HLA) and specific KIR/HLA genotypes on risk of and outcomes to infection, cancer, autoimmune disease, and maternal-fetal disease. Recent studies have focused on the impact of HLA gene expression in disease, the molecular mechanism regulating expression levels, and the functional basis for the effect of differential expression on disease outcome. The lab’s further focus is on the genetic basis for resistance/susceptibility to disease conferred by immunogenetic variation. KEY ROLES/RESPONSIBILITIES The Senior Computational Scientist will provide research support to the CIP-BSP-HLA Immunogenetics Section performing bio-statistical design, analysis and reporting of research projects conducted in the lab. This individual will be involved in the implementation of statistical models and data preparation. Successful candidate should have 5 or more years of competent, innovative biostatistics/bioinformatics research experience, beyond doctoral training Considerable experience with statistical software, such as SAS, R and S-Plus Sound knowledge, and demonstrated experience of theoretical and applied statistics Write program code to analyze data using statistical analysis software Contribute to the interpretation and publication of research results

Effect of elastic constants of liquid crystals in their electro-optical properties

NASA Astrophysics Data System (ADS)

Parang, Z.; Ghaffary, T.; Gharahbeigi, M. M.

Recently following the success of the density functional theory (DFT) in obtaining the structure and thermodynamics of homogeneous and inhomogeneous classical systems such as simple fluids, dipolar fluid and binary hard spheres, this theory was also applied to obtain the density profile of a molecular fluid in between hard planar walls by Kalpaxis and Rickayzen. In the theory of molecular fluids, the direct correlation function (DCF) can be used to calculate the equation of state, free energy, phase transition, elastic constants, etc. It is well known that the hard core molecular models play an important role in understanding complex liquids such as liquid crystals. In this paper, a classical fluid of nonspherical molecules is studied. The required homogeneous (DCF) is obtained by solving Orenstein-Zernike (OZ) integral equation numerically. Some of the molecules in the liquid crystals have a sphere shape and this kind of molecular fluid is considered here. The DCF sphere of the molecular fluid is calculated and it will be shown that the results are in good agreement with the pervious works and the results of computer simulation. Finally the electro-optical properties of ellipsoid liquid crystal using DCF of these molecules are calculated.

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

PubMed Central

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J. P.; Chen, Yu-Ching

2016-01-01

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes. PMID:27304951

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation.

PubMed

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J P; Chen, Yu-Ching

2016-06-13

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Molecular structure, vibrational spectra, NLO and MEP analysis of bis[2-hydroxy-кO-N-(2-pyridyl)-1-naphthaldiminato-кN]zinc(II)

NASA Astrophysics Data System (ADS)

Tanak, Hasan; Toy, Mehmet

2013-11-01

The molecular geometry and vibrational frequencies of bis[2-hydroxy-кO-N-(2-pyridyl)-1-naphthaldiminato-кN]zinc(II) in the ground state have been calculated by using the Hartree-Fock (HF) and density functional method (B3LYP) with 6-311G(d,p) basis set. The results of the optimized molecular structure are presented and compared with the experimental X-ray diffraction. The energetic and atomic charge behavior of the title compound in solvent media has been examined by applying the Onsager and the polarizable continuum model. To investigate second order nonlinear optical properties of the title compound, the electric dipole (μ), linear polarizability (α) and first-order hyperpolarizability (β) were computed using the density functional B3LYP and CAM-B3LYP methods with the 6-31+G(d) basis set. According to our calculations, the title compound exhibits nonzero (β) value revealing second order NLO behavior. In addition, DFT calculations of the title compound, molecular electrostatic potential (MEP), frontier molecular orbitals, and thermodynamic properties were performed at B3LYP/6-311G(d,p) level of theory.

Intraoperative imaging-guided cancer surgery: from current fluorescence molecular imaging methods to future multi-modality imaging technology.

PubMed

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery.

Multiple time step integrators in ab initio molecular dynamics.

PubMed

Luehr, Nathan; Markland, Thomas E; Martínez, Todd J

2014-02-28

Multiple time-scale algorithms exploit the natural separation of time-scales in chemical systems to greatly accelerate the efficiency of molecular dynamics simulations. Although the utility of these methods in systems where the interactions are described by empirical potentials is now well established, their application to ab initio molecular dynamics calculations has been limited by difficulties associated with splitting the ab initio potential into fast and slowly varying components. Here we present two schemes that enable efficient time-scale separation in ab initio calculations: one based on fragment decomposition and the other on range separation of the Coulomb operator in the electronic Hamiltonian. We demonstrate for both water clusters and a solvated hydroxide ion that multiple time-scale molecular dynamics allows for outer time steps of 2.5 fs, which are as large as those obtained when such schemes are applied to empirical potentials, while still allowing for bonds to be broken and reformed throughout the dynamics. This permits computational speedups of up to 4.4x, compared to standard Born-Oppenheimer ab initio molecular dynamics with a 0.5 fs time step, while maintaining the same energy conservation and accuracy.

Intraoperative Imaging-Guided Cancer Surgery: From Current Fluorescence Molecular Imaging Methods to Future Multi-Modality Imaging Technology

PubMed Central

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery. PMID:25250092

Density functional theory fragment descriptors to quantify the reactivity of a molecular family: application to amino acids.

PubMed

Senet, P; Aparicio, F

2007-04-14

By using the exact density functional theory, one demonstrates that the value of the local electronic softness of a molecular fragment is directly related to the polarization charge (Coulomb hole) induced by a test electron removed (or added) from (at) the fragment. Our finding generalizes to a chemical group a formal relation between these molecular descriptors recently obtained for an atom in a molecule using an approximate atomistic model [P. Senet and M. Yang, J. Chem. Sci. 117, 411 (2005)]. In addition, a practical ab initio computational scheme of the Coulomb hole and related local descriptors of reactivity of a molecular family having in common a similar fragment is presented. As a blind test, the method is applied to the lateral chains of the 20 isolated amino acids. One demonstrates that the local softness of the lateral chain is a quantitative measure of the similarity of the amino acids. It predicts the separation of amino acids in different biochemical groups (aliphatic, basic, acidic, sulfur contained, and aromatic). The present approach may find applications in quantitative structure activity relationship methodology.

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

Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations.

PubMed

Sinko, William; de Oliveira, César Augusto F; Pierce, Levi C T; McCammon, J Andrew

2012-01-10

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations.

Oligomerization of G protein-coupled receptors: computational methods.

PubMed

Selent, J; Kaczor, A A

2011-01-01

Recent research has unveiled the complexity of mechanisms involved in G protein-coupled receptor (GPCR) functioning in which receptor dimerization/oligomerization may play an important role. Although the first high-resolution X-ray structure for a likely functional chemokine receptor dimer has been deposited in the Protein Data Bank, the interactions and mechanisms of dimer formation are not yet fully understood. In this respect, computational methods play a key role for predicting accurate GPCR complexes. This review outlines computational approaches focusing on sequence- and structure-based methodologies as well as discusses their advantages and limitations. Sequence-based approaches that search for possible protein-protein interfaces in GPCR complexes have been applied with success in several studies, but did not yield always consistent results. Structure-based methodologies are a potent complement to sequence-based approaches. For instance, protein-protein docking is a valuable method especially when guided by experimental constraints. Some disadvantages like limited receptor flexibility and non-consideration of the membrane environment have to be taken into account. Molecular dynamics simulation can overcome these drawbacks giving a detailed description of conformational changes in a native-like membrane. Successful prediction of GPCR complexes using computational approaches combined with experimental efforts may help to understand the role of dimeric/oligomeric GPCR complexes for fine-tuning receptor signaling. Moreover, since such GPCR complexes have attracted interest as potential drug target for diverse diseases, unveiling molecular determinants of dimerization/oligomerization can provide important implications for drug discovery.

pKa values in proteins determined by electrostatics applied to molecular dynamics trajectories.

PubMed

Meyer, Tim; Knapp, Ernst-Walter

2015-06-09

For a benchmark set of 194 measured pKa values in 13 proteins, electrostatic energy computations are performed in which pKa values are computed by solving the Poisson-Boltzmann equation. In contrast to the previous approach of Karlsberg(+) (KB(+)) that essentially used protein crystal structures with variations in their side chain conformations, the present approach (KB2(+)MD) uses protein conformations from four molecular dynamics (MD) simulations of 10 ns each. These MD simulations are performed with different specific but fixed protonation patterns, selected to sample the conformational space for the different protonation patterns faithfully. The root-mean-square deviation between computed and measured pKa values (pKa RMSD) is shown to be reduced from 1.17 pH units using KB(+) to 0.96 pH units using KB2(+)MD. The pKa RMSD can be further reduced to 0.79 pH units, if each conformation is energy-minimized with a dielectric constant of εmin = 4 prior to calculating the electrostatic energy. The electrostatic energy expressions upon which the computations are based have been reformulated such that they do not involve terms that mix protein and solvent environment contributions and no thermodynamic cycle is needed. As a consequence, conformations of the titratable residues can be treated independently in the protein and solvent environments. In addition, the energy terms used here avoid the so-called intrinsic pKa and can therefore be interpreted without reference to arbitrary protonation states and conformations.

Fragment-based drug discovery and molecular docking in drug design.

PubMed

Wang, Tao; Wu, Mian-Bin; Chen, Zheng-Jie; Chen, Hua; Lin, Jian-Ping; Yang, Li-Rong

2015-01-01

Fragment-based drug discovery (FBDD) has caused a revolution in the process of drug discovery and design, with many FBDD leads being developed into clinical trials or approved in the past few years. Compared with traditional high-throughput screening, it displays obvious advantages such as efficiently covering chemical space, achieving higher hit rates, and so forth. In this review, we focus on the most recent developments of FBDD for improving drug discovery, illustrating the process and the importance of FBDD. In particular, the computational strategies applied in the process of FBDD and molecular-docking programs are highlighted elaborately. In most cases, docking is used for predicting the ligand-receptor interaction modes and hit identification by structurebased virtual screening. The successful cases of typical significance and the hits identified most recently are discussed.

Molecular computation: RNA solutions to chess problems

PubMed Central

Faulhammer, Dirk; Cukras, Anthony R.; Lipton, Richard J.; Landweber, Laura F.

2000-01-01

We have expanded the field of “DNA computers” to RNA and present a general approach for the solution of satisfiability problems. As an example, we consider a variant of the “Knight problem,” which asks generally what configurations of knights can one place on an n × n chess board such that no knight is attacking any other knight on the board. Using specific ribonuclease digestion to manipulate strands of a 10-bit binary RNA library, we developed a molecular algorithm and applied it to a 3 × 3 chessboard as a 9-bit instance of this problem. Here, the nine spaces on the board correspond to nine “bits” or placeholders in a combinatorial RNA library. We recovered a set of “winning” molecules that describe solutions to this problem. PMID:10677471

Projected quasiparticle theory for molecular electronic structure

NASA Astrophysics Data System (ADS)

Scuseria, Gustavo E.; Jiménez-Hoyos, Carlos A.; Henderson, Thomas M.; Samanta, Kousik; Ellis, Jason K.

2011-09-01

We derive and implement symmetry-projected Hartree-Fock-Bogoliubov (HFB) equations and apply them to the molecular electronic structure problem. All symmetries (particle number, spin, spatial, and complex conjugation) are deliberately broken and restored in a self-consistent variation-after-projection approach. We show that the resulting method yields a comprehensive black-box treatment of static correlations with effective one-electron (mean-field) computational cost. The ensuing wave function is of multireference character and permeates the entire Hilbert space of the problem. The energy expression is different from regular HFB theory but remains a functional of an independent quasiparticle density matrix. All reduced density matrices are expressible as an integration of transition density matrices over a gauge grid. We present several proof-of-principle examples demonstrating the compelling power of projected quasiparticle theory for quantum chemistry.

Ames interactive molecular model building system - A 3-D computer modelling system applied to the study of the origin of life

NASA Technical Reports Server (NTRS)

Coeckelenbergh, Y.; Macelroy, R. D.; Rein, R.

1978-01-01

The investigation of specific interactions among biological molecules must take into consideration the stereochemistry of the structures. Thus, models of the molecules are essential for describing the spatial organization of potentially interacting groups, and estimations of conformation are required for a description of spatial organization. Both the function of visualizing molecules, and that of estimating conformation through calculations of energy, are part of the molecular modeling system described in the present paper. The potential uses of the system in investigating some aspects of the origin of life rest on the assumption that translation of conformation from genetic elements to catalytic elements would have been required for the development of the first replicating systems subject to the process of biological evolution.

Exploring the free energy surface using ab initio molecular dynamics

DOE PAGES

Samanta, Amit; Morales, Miguel A.; Schwegler, Eric

2016-04-22

Efficient exploration of the configuration space and identification of metastable structures are challenging from both computational as well as algorithmic perspectives. Here, we extend the recently proposed orderparameter aided temperature accelerated sampling schemes to efficiently and systematically explore free energy surfaces, and search for metastable states and reaction pathways within the framework of density functional theory based molecular dynamics. The sampling method is applied to explore the relevant parts of the configuration space in prototypical materials SiO 2 and Ti to identify the different metastable structures corresponding to different phases in these materials. In addition, we use the string methodmore » in collective variables to study the melting pathways in the high pressure cotunnite phase of SiO 2 and the hcp to fcc phase transition in Ti.« less

Computer simulation studies of anisotropic systems. XXXII. Field-induction of a smectic A phase in a Gay-Berne mesogen

NASA Astrophysics Data System (ADS)

Luckhurst, G. R.; Saielli, G.

2000-03-01

Molecular field theory predicts the induction of a smectic A phase by the application of a field, either magnetic or electric, to a nematic phase. This intriguing behavior results from an enhancement of the orientational order which is coupled to the translational order and so shifts the smectic A-nematic transition. To test this prediction we have investigated a system of Gay-Berne mesogenic molecules subject to an applied field of second rank using isothermal-isobaric Monte Carlo simulations. The results of our calculations are compared with the Kventsel-Luckhurst-Zewdie molecular field theory of smectogens, modified to include the effect of an external field. We have also used the simulations to explore the possibility of inducing more ordered smectic phases with stronger fields.

Logic integration of mRNA signals by an RNAi-based molecular computer.

PubMed

Xie, Zhen; Liu, Siyuan John; Bleris, Leonidas; Benenson, Yaakov

2010-05-01

Synthetic in vivo molecular 'computers' could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that 'transduce' mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi 'computational' module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting.

Science | Argonne National Laboratory

Science.gov Websites

Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at Argonne Work with Scientific Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels

Argonne Research Library | Argonne National Laboratory

Science.gov Websites

Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at Argonne Work with Scientific Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at IMEInstitute for Molecular Engineering JCESRJoint Center for Energy Storage Research MCSGMidwest Center for

Linear Regression Links Transcriptomic Data and Cellular Raman Spectra.

PubMed

Kobayashi-Kirschvink, Koseki J; Nakaoka, Hidenori; Oda, Arisa; Kamei, Ken-Ichiro F; Nosho, Kazuki; Fukushima, Hiroko; Kanesaki, Yu; Yajima, Shunsuke; Masaki, Haruhiko; Ohta, Kunihiro; Wakamoto, Yuichi

2018-06-08

Raman microscopy is an imaging technique that has been applied to assess molecular compositions of living cells to characterize cell types and states. However, owing to the diverse molecular species in cells and challenges of assigning peaks to specific molecules, it has not been clear how to interpret cellular Raman spectra. Here, we provide firm evidence that cellular Raman spectra and transcriptomic profiles of Schizosaccharomyces pombe and Escherichia coli can be computationally connected and thus interpreted. We find that the dimensions of high-dimensional Raman spectra and transcriptomes measured by RNA sequencing can be reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to predict global gene expression profiles by applying the calculated transformation matrix to Raman spectra, and vice versa. Highly expressed non-coding RNAs contributed to the Raman-transcriptome linear correspondence more significantly than mRNAs in S. pombe. This demonstration of correspondence between cellular Raman spectra and transcriptomes is a promising step toward establishing spectroscopic live-cell omics studies. Copyright © 2018 Elsevier Inc. All rights reserved.

Molecular dynamics study of the structural and dynamic characteristics of the polyextremophilic short-chain dehydrogenase from the Thermococcus sibiricus archaeon and its homologues

NASA Astrophysics Data System (ADS)

Popinako, Anna V.; Antonov, Mikhail Yu.; Bezsudnova, Ekaterina Yu.; Prokopiev, Georgiy A.; Popov, Vladimir O.

2017-11-01

The study of structural adaptations of proteins from polyextremophilic organisms using computational molecular dynamics method is appealing because the obtained knowledge can be applied to construction of synthetic proteins with high activity and stability in polyextreme media which is useful for many industrial applications. To investigate molecular adaptations to high temperature, we have focused on a superthermostable short-chain dehydrogenase TsAdh319 from the Thermococcus sibiricus polyextremophilic archaeon and its closest structural homologues. Molecular dynamics method is widely used for molecular structure refinement, investigation of biological macromolecules motion, and, consequently, for interpreting the results of certain biophysical experiments. We performed molecular dynamics simulations of the proteins at different temperatures. Comparison of root mean square fluctuations (RMSF) of the atoms in thermophilic alcohol dehydrogenases (ADHs) at 300 K and 358 K revealed the existence of stable residues at 358 K. These residues surround the active site and form a "nucleus of rigidity" in thermophilic ADHs. The results of our studies suggest that the existence of the "nucleus of rigidity" is crucial for the stability of TsAdh319. Absence of the "nucleus of rigidity" in non-thermally stable proteins causes fluctuations throughout the protein, especially on the surface, triggering the process of denaturation at high temperatures.

Parallel, stochastic measurement of molecular surface area.

PubMed

Juba, Derek; Varshney, Amitabh

2008-08-01

Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited. We describe a parallel, stochastic algorithm for molecular surface area computation that maps well to the emerging multi-core architectures. Our algorithm is also progressive, providing a rough estimate of surface area immediately and refining this estimate as time goes on. Furthermore, the algorithm generates points on the molecular surface which can be used for point-based rendering. We demonstrate a GPU implementation of our algorithm and show that it compares favorably with several existing molecular surface computation programs, giving fast estimates of the molecular surface area with good accuracy.

Quantum mechanical free energy profiles with post-quantization restraints: Binding free energy of the water dimer over a broad range of temperatures

NASA Astrophysics Data System (ADS)

Bishop, Kevin P.; Roy, Pierre-Nicholas

2018-03-01

Free energy calculations are a crucial part of understanding chemical systems but are often computationally expensive for all but the simplest of systems. Various enhanced sampling techniques have been developed to improve the efficiency of these calculations in numerical simulations. However, the majority of these approaches have been applied using classical molecular dynamics. There are many situations where nuclear quantum effects impact the system of interest and a classical description fails to capture these details. In this work, path integral molecular dynamics has been used in conjunction with umbrella sampling, and it has been observed that correct results are only obtained when the umbrella sampling potential is applied to a single path integral bead post quantization. This method has been validated against a Lennard-Jones benchmark system before being applied to the more complicated water dimer system over a broad range of temperatures. Free energy profiles are obtained, and these are utilized in the calculation of the second virial coefficient as well as the change in free energy from the separated water monomers to the dimer. Comparisons to experimental and ground state calculation values from the literature are made for the second virial coefficient at higher temperature and the dissociation energy of the dimer in the ground state.

Quantum mechanical free energy profiles with post-quantization restraints: Binding free energy of the water dimer over a broad range of temperatures.

PubMed

Bishop, Kevin P; Roy, Pierre-Nicholas

2018-03-14

Free energy calculations are a crucial part of understanding chemical systems but are often computationally expensive for all but the simplest of systems. Various enhanced sampling techniques have been developed to improve the efficiency of these calculations in numerical simulations. However, the majority of these approaches have been applied using classical molecular dynamics. There are many situations where nuclear quantum effects impact the system of interest and a classical description fails to capture these details. In this work, path integral molecular dynamics has been used in conjunction with umbrella sampling, and it has been observed that correct results are only obtained when the umbrella sampling potential is applied to a single path integral bead post quantization. This method has been validated against a Lennard-Jones benchmark system before being applied to the more complicated water dimer system over a broad range of temperatures. Free energy profiles are obtained, and these are utilized in the calculation of the second virial coefficient as well as the change in free energy from the separated water monomers to the dimer. Comparisons to experimental and ground state calculation values from the literature are made for the second virial coefficient at higher temperature and the dissociation energy of the dimer in the ground state.

Workshop in computational molecular biology, April 15, 1991--April 14, 1994

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

Tavare, S.

Funds from this award were used to the Workshop in Computational Molecular Biology, `91 Symposium entitled Interface: Computing Science and Statistics, Seattle, Washington, April 21, 1991; the Workshop in Statistical Issues in Molecular Biology held at Stanford, California, August 8, 1993; and the Session on Population Genetics a part of the 56th Annual Meeting, Institute of Mathematical Statistics, San Francisco, California, August 9, 1993.

Elucidation of molecular kinetic schemes from macroscopic traces using system identification

PubMed Central

González-Maeso, Javier; Sealfon, Stuart C.; Galocha-Iragüen, Belén; Brezina, Vladimir

2017-01-01

Overall cellular responses to biologically-relevant stimuli are mediated by networks of simpler lower-level processes. Although information about some of these processes can now be obtained by visualizing and recording events at the molecular level, this is still possible only in especially favorable cases. Therefore the development of methods to extract the dynamics and relationships between the different lower-level (microscopic) processes from the overall (macroscopic) response remains a crucial challenge in the understanding of many aspects of physiology. Here we have devised a hybrid computational-analytical method to accomplish this task, the SYStems-based MOLecular kinetic scheme Extractor (SYSMOLE). SYSMOLE utilizes system-identification input-output analysis to obtain a transfer function between the stimulus and the overall cellular response in the Laplace-transformed domain. It then derives a Markov-chain state molecular kinetic scheme uniquely associated with the transfer function by means of a classification procedure and an analytical step that imposes general biological constraints. We first tested SYSMOLE with synthetic data and evaluated its performance in terms of its rate of convergence to the correct molecular kinetic scheme and its robustness to noise. We then examined its performance on real experimental traces by analyzing macroscopic calcium-current traces elicited by membrane depolarization. SYSMOLE derived the correct, previously known molecular kinetic scheme describing the activation and inactivation of the underlying calcium channels and correctly identified the accepted mechanism of action of nifedipine, a calcium-channel blocker clinically used in patients with cardiovascular disease. Finally, we applied SYSMOLE to study the pharmacology of a new class of glutamate antipsychotic drugs and their crosstalk mechanism through a heteromeric complex of G protein-coupled receptors. Our results indicate that our methodology can be successfully applied to accurately derive molecular kinetic schemes from experimental macroscopic traces, and we anticipate that it may be useful in the study of a wide variety of biological systems. PMID:28192423

Assessment of Molecular Modeling & Simulation

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

None

2002-01-03

This report reviews the development and applications of molecular and materials modeling in Europe and Japan in comparison to those in the United States. Topics covered include computational quantum chemistry, molecular simulations by molecular dynamics and Monte Carlo methods, mesoscale modeling of material domains, molecular-structure/macroscale property correlations like QSARs and QSPRs, and related information technologies like informatics and special-purpose molecular-modeling computers. The panel's findings include the following: The United States leads this field in many scientific areas. However, Canada has particular strengths in DFT methods and homogeneous catalysis; Europe in heterogeneous catalysis, mesoscale, and materials modeling; and Japan in materialsmore » modeling and special-purpose computing. Major government-industry initiatives are underway in Europe and Japan, notably in multi-scale materials modeling and in development of chemistry-capable ab-initio molecular dynamics codes.« less

High Performance Parallel Computational Nanotechnology

NASA Technical Reports Server (NTRS)

Saini, Subhash; Craw, James M. (Technical Monitor)

1995-01-01

At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to control mini robotic manipulators for positional control; scalable numerical algorithms for reliability, verifications and testability. There appears no fundamental obstacle to simulating molecular compilers and molecular computers on high performance parallel computers, just as the Boeing 777 was simulated on a computer before manufacturing it.

Symplectic molecular dynamics simulations on specially designed parallel computers.

PubMed

Borstnik, Urban; Janezic, Dusanka

2005-01-01

We have developed a computer program for molecular dynamics (MD) simulation that implements the Split Integration Symplectic Method (SISM) and is designed to run on specialized parallel computers. The MD integration is performed by the SISM, which analytically treats high-frequency vibrational motion and thus enables the use of longer simulation time steps. The low-frequency motion is treated numerically on specially designed parallel computers, which decreases the computational time of each simulation time step. The combination of these approaches means that less time is required and fewer steps are needed and so enables fast MD simulations. We study the computational performance of MD simulation of molecular systems on specialized computers and provide a comparison to standard personal computers. The combination of the SISM with two specialized parallel computers is an effective way to increase the speed of MD simulations up to 16-fold over a single PC processor.

Distribution of tunnelling times for quantum electron transport.

PubMed

Rudge, Samuel L; Kosov, Daniel S

2016-03-28

In electron transport, the tunnelling time is the time taken for an electron to tunnel out of a system after it has tunnelled in. We define the tunnelling time distribution for quantum processes in a dissipative environment and develop a practical approach for calculating it, where the environment is described by the general Markovian master equation. We illustrate the theory by using the rate equation to compute the tunnelling time distribution for electron transport through a molecular junction. The tunnelling time distribution is exponential, which indicates that Markovian quantum tunnelling is a Poissonian statistical process. The tunnelling time distribution is used not only to study the quantum statistics of tunnelling along the average electric current but also to analyse extreme quantum events where an electron jumps against the applied voltage bias. The average tunnelling time shows distinctly different temperature dependence for p- and n-type molecular junctions and therefore provides a sensitive tool to probe the alignment of molecular orbitals relative to the electrode Fermi energy.

Ultrafast spectroscopy reveals subnanosecond peptide conformational dynamics and validates molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Spörlein, Sebastian; Carstens, Heiko; Satzger, Helmut; Renner, Christian; Behrendt, Raymond; Moroder, Luis; Tavan, Paul; Zinth, Wolfgang; Wachtveitl, Josef

2002-06-01

Femtosecond time-resolved spectroscopy on model peptides with built-in light switches combined with computer simulation of light-triggered motions offers an attractive integrated approach toward the understanding of peptide conformational dynamics. It was applied to monitor the light-induced relaxation dynamics occurring on subnanosecond time scales in a peptide that was backbone-cyclized with an azobenzene derivative as optical switch and spectroscopic probe. The femtosecond spectra permit the clear distinguishing and characterization of the subpicosecond photoisomerization of the chromophore, the subsequent dissipation of vibrational energy, and the subnanosecond conformational relaxation of the peptide. The photochemical cis/trans-isomerization of the chromophore and the resulting peptide relaxations have been simulated with molecular dynamics calculations. The calculated reaction kinetics, as monitored by the energy content of the peptide, were found to match the spectroscopic data. Thus we verify that all-atom molecular dynamics simulations can quantitatively describe the subnanosecond conformational dynamics of peptides, strengthening confidence in corresponding predictions for longer time scales.

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.

Molecular polarizability of water from local dielectric response theory

DOE PAGES

Ge, Xiaochuan; Lu, Deyu

2017-08-08

Here, we propose a fully ab initio theory to compute the electron density response under the perturbation in the local field. This method is based on our recently developed local dielectric response theory [Phys. Rev. B 92, 241107(R), 2015], which provides a rigorous theoretical framework to treat local electronic excitations in both nite and extended systems beyond the commonly employed dipole approximation. We have applied this method to study the electronic part of the molecular polarizability of water in ice Ih and liquid water. Our results reveal that the crystal field of the hydrogen-bond network has strong anisotropic effects, whichmore » significantly enhance the out-of-plane component and suppress the in-plane component perpendicular to the bisector direction. The contribution from the charge transfer is equally important, which increases the isotropic molecular polarizability by 5-6%. Our study provides new insights into the dielectric properties of water, which form the basis to understand electronic excitations in water and to develop accurate polarizable force fields of water.« less

Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics

NASA Astrophysics Data System (ADS)

Puzyrkov, Dmitry; Polyakov, Sergey; Podryga, Viktoriia; Markizov, Sergey

2018-02-01

At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.

Length dependence of electron transport through molecular wires--a first principles perspective.

PubMed

Khoo, Khoong Hong; Chen, Yifeng; Li, Suchun; Quek, Su Ying

2015-01-07

One-dimensional wires constitute a fundamental building block in nanoscale electronics. However, truly one-dimensional metallic wires do not exist due to Peierls distortion. Molecular wires come close to being stable one-dimensional wires, but are typically semiconductors, with charge transport occurring via tunneling or thermally-activated hopping. In this review, we discuss electron transport through molecular wires, from a theoretical, quantum mechanical perspective based on first principles. We focus specifically on the off-resonant tunneling regime, applicable to shorter molecular wires (<∼4-5 nm) where quantum mechanics dictates electron transport. Here, conductance decays exponentially with the wire length, with an exponential decay constant, beta, that is independent of temperature. Different levels of first principles theory are discussed, starting with the computational workhorse - density functional theory (DFT), and moving on to many-electron GW methods as well as GW-inspired DFT + Sigma calculations. These different levels of theory are applied in two major computational frameworks - complex band structure (CBS) calculations to estimate the tunneling decay constant, beta, and Landauer-Buttiker transport calculations that consider explicitly the effects of contact geometry, and compute the transmission spectra directly. In general, for the same level of theory, the Landauer-Buttiker calculations give more quantitative values of beta than the CBS calculations. However, the CBS calculations have a long history and are particularly useful for quick estimates of beta. Comparing different levels of theory, it is clear that GW and DFT + Sigma calculations give significantly improved agreement with experiment compared to DFT, especially for the conductance values. Quantitative agreement can also be obtained for the Seebeck coefficient - another independent probe of electron transport. This excellent agreement provides confirmative evidence of off-resonant tunneling in the systems under investigation. Calculations show that the tunneling decay constant beta is a robust quantity that does not depend on details of the contact geometry, provided that the same contact geometry is used for all molecular lengths considered. However, because conductance is sensitive to contact geometry, values of beta obtained by considering conductance values where the contact geometry is changing with the molecular junction length can be quite different. Experimentally measured values of beta in general compare well with beta obtained using DFT + Sigma and GW transport calculations, while discrepancies can be attributed to changes in the experimental contact geometries with molecular length. This review also summarizes experimental and theoretical efforts towards finding perfect molecular wires with high conductance and small beta values.

Predicting Monoamine Oxidase Inhibitory Activity through Ligand-Based Models

PubMed Central

Vilar, Santiago; Ferino, Giulio; Quezada, Elias; Santana, Lourdes; Friedman, Carol

2013-01-01

The evolution of bio- and cheminformatics associated with the development of specialized software and increasing computer power has produced a great interest in theoretical in silico methods applied in drug rational design. These techniques apply the concept that “similar molecules have similar biological properties” that has been exploited in Medicinal Chemistry for years to design new molecules with desirable pharmacological profiles. Ligand-based methods are not dependent on receptor structural data and take into account two and three-dimensional molecular properties to assess similarity of new compounds in regards to the set of molecules with the biological property under study. Depending on the complexity of the calculation, there are different types of ligand-based methods, such as QSAR (Quantitative Structure-Activity Relationship) with 2D and 3D descriptors, CoMFA (Comparative Molecular Field Analysis) or pharmacophoric approaches. This work provides a description of a series of ligand-based models applied in the prediction of the inhibitory activity of monoamine oxidase (MAO) enzymes. The controlled regulation of the enzymes’ function through the use of MAO inhibitors is used as a treatment in many psychiatric and neurological disorders, such as depression, anxiety, Alzheimer’s and Parkinson’s disease. For this reason, multiple scaffolds, such as substituted coumarins, indolylmethylamine or pyridazine derivatives were synthesized and assayed toward MAO-A and MAO-B inhibition. Our intention is to focus on the description of ligand-based models to provide new insights in the relationship between the MAO inhibitory activity and the molecular structure of the different inhibitors, and further study enzyme selectivity and possible mechanisms of action. PMID:23231398

The Effect of Interactive, Three Dimensional, High Speed Simulations on High School Science Students' Conceptions of the Molecular Structure of Water.

ERIC Educational Resources Information Center

Hakerem, Gita; And Others

The Water and Molecular Networks (WAMNet) Project uses graduate student written Reduced Instruction Set Computing (RISC) computer simulations of the molecular structure of water to assist high school students learn about the nature of water. This study examined: (1) preconceptions concerning the molecular structure of water common among high…

Mapping the Transmission Functions of Single-Molecule Junctions

DOE PAGES

Capozzi, Brian; Low, Jonathan Z.; Xia, Jianlong; ...

2016-06-08

Charge transport characteristics of single-molecule junctions are often governed by a transmission function that dictates the probability of electrons or holes tunneling across the junction. Here, we present a new and simple technique for measuring the transmission function of molecular junctions in the coherent tunneling limit, over an energy range of 2 eV around the Fermi energy. We create molecular junctions in an ionic environment with electrodes having different areas exposed, which results in the formation of electric double layers of dissimilar density on the two electrodes. This allows us to electrostatically shift the molecular resonance relative to the junctionmore » Fermi levels in a manner that depends on the sign of the applied bias, enabling us to map out the junction’s transmission function and determine the dominant orbital for charge transport in the molecular junction. We demonstrate this technique using two groups of molecules: one group having molecular resonance energies relatively far from EF and one group having molecular resonance energies within the accessible bias window. Our results compare well with previous electrochemical gating data and with transmission functions computed ab initio. Furthermore, with the second group of molecules, we are able to examine the behavior of a molecular junction as a resonance shifts into the bias window. This work provides a new, experimentally simple route for exploring the fundamentals of charge transport at the nanoscale.« less

Mapping the Transmission Functions of Single-Molecule Junctions

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

Capozzi, Brian; Low, Jonathan Z.; Xia, Jianlong

Charge transport characteristics of single-molecule junctions are often governed by a transmission function that dictates the probability of electrons or holes tunneling across the junction. Here, we present a new and simple technique for measuring the transmission function of molecular junctions in the coherent tunneling limit, over an energy range of 2 eV around the Fermi energy. We create molecular junctions in an ionic environment with electrodes having different areas exposed, which results in the formation of electric double layers of dissimilar density on the two electrodes. This allows us to electrostatically shift the molecular resonance relative to the junctionmore » Fermi levels in a manner that depends on the sign of the applied bias, enabling us to map out the junction’s transmission function and determine the dominant orbital for charge transport in the molecular junction. We demonstrate this technique using two groups of molecules: one group having molecular resonance energies relatively far from EF and one group having molecular resonance energies within the accessible bias window. Our results compare well with previous electrochemical gating data and with transmission functions computed ab initio. Furthermore, with the second group of molecules, we are able to examine the behavior of a molecular junction as a resonance shifts into the bias window. This work provides a new, experimentally simple route for exploring the fundamentals of charge transport at the nanoscale.« less

Mapping the Transmission Functions of Single-Molecule Junctions.

PubMed

Capozzi, Brian; Low, Jonathan Z; Xia, Jianlong; Liu, Zhen-Fei; Neaton, Jeffrey B; Campos, Luis M; Venkataraman, Latha

2016-06-08

Charge transport phenomena in single-molecule junctions are often dominated by tunneling, with a transmission function dictating the probability that electrons or holes tunnel through the junction. Here, we present a new and simple technique for measuring the transmission functions of molecular junctions in the coherent tunneling limit, over an energy range of 1.5 eV around the Fermi energy. We create molecular junctions in an ionic environment with electrodes having different exposed areas, which results in the formation of electric double layers of dissimilar density on the two electrodes. This allows us to electrostatically shift the molecular resonance relative to the junction Fermi levels in a manner that depends on the sign of the applied bias, enabling us to map out the junction's transmission function and determine the dominant orbital for charge transport in the molecular junction. We demonstrate this technique using two groups of molecules: one group having molecular resonance energies relatively far from EF and one group having molecular resonance energies within the accessible bias window. Our results compare well with previous electrochemical gating data and with transmission functions computed from first principles. Furthermore, with the second group of molecules, we are able to examine the behavior of a molecular junction as a resonance shifts into the bias window. This work provides a new, experimentally simple route for exploring the fundamentals of charge transport at the nanoscale.

AN EFFICIENT HIGHER-ORDER FAST MULTIPOLE BOUNDARY ELEMENT SOLUTION FOR POISSON-BOLTZMANN BASED MOLECULAR ELECTROSTATICS

PubMed Central

Bajaj, Chandrajit; Chen, Shun-Chuan; Rand, Alexander

2011-01-01

In order to compute polarization energy of biomolecules, we describe a boundary element approach to solving the linearized Poisson-Boltzmann equation. Our approach combines several important features including the derivative boundary formulation of the problem and a smooth approximation of the molecular surface based on the algebraic spline molecular surface. State of the art software for numerical linear algebra and the kernel independent fast multipole method is used for both simplicity and efficiency of our implementation. We perform a variety of computational experiments, testing our method on a number of actual proteins involved in molecular docking and demonstrating the effectiveness of our solver for computing molecular polarization energy. PMID:21660123

A review of bioinformatics training applied to research in molecular medicine, agriculture and biodiversity in Costa Rica and Central America.

PubMed

Orozco, Allan; Morera, Jessica; Jiménez, Sergio; Boza, Ricardo

2013-09-01

Today, Bioinformatics has become a scientific discipline with great relevance for the Molecular Biosciences and for the Omics sciences in general. Although developed countries have progressed with large strides in Bioinformatics education and research, in other regions, such as Central America, the advances have occurred in a gradual way and with little support from the Academia, either at the undergraduate or graduate level. To address this problem, the University of Costa Rica's Medical School, a regional leader in Bioinformatics in Central America, has been conducting a series of Bioinformatics workshops, seminars and courses, leading to the creation of the region's first Bioinformatics Master's Degree. The recent creation of the Central American Bioinformatics Network (BioCANET), associated to the deployment of a supporting computational infrastructure (HPC Cluster) devoted to provide computing support for Molecular Biology in the region, is providing a foundational stone for the development of Bioinformatics in the area. Central American bioinformaticians have participated in the creation of as well as co-founded the Iberoamerican Bioinformatics Society (SOIBIO). In this article, we review the most recent activities in education and research in Bioinformatics from several regional institutions. These activities have resulted in further advances for Molecular Medicine, Agriculture and Biodiversity research in Costa Rica and the rest of the Central American countries. Finally, we provide summary information on the first Central America Bioinformatics International Congress, as well as the creation of the first Bioinformatics company (Indromics Bioinformatics), spin-off the Academy in Central America and the Caribbean.

Importance of Vibronic Effects in the UV-Vis Spectrum of the 7,7,8,8-Tetracyanoquinodimethane Anion.

PubMed

Tapavicza, Enrico; Furche, Filipp; Sundholm, Dage

2016-10-11

We present a computational method for simulating vibronic absorption spectra in the ultraviolet-visible (UV-vis) range and apply it to the 7,7,8,8-tetracyanoquinodimethane anion (TCNQ - ), which has been used as a ligand in black absorbers. Gaussian broadening of vertical electronic excitation energies of TCNQ - from linear-response time-dependent density functional theory produces only one band, which is qualitatively incorrect. Thus, the harmonic vibrational modes of the two lowest doublet states were computed, and the vibronic UV-vis spectrum was simulated using the displaced harmonic oscillator approximation, the frequency-shifted harmonic oscillator approximation, and the full Duschinsky formalism. An efficient real-time generating function method was implemented to avoid the exponential complexity of conventional Franck-Condon approaches to vibronic spectra. The obtained UV-vis spectra for TCNQ - agree well with experiment; the Duschinsky rotation is found to have only a minor effect on the spectrum. Born-Oppenheimer molecular dynamics simulations combined with calculations of the electronic excitation energies for a large number of molecular structures were also used for simulating the UV-vis spectrum. The Born-Oppenheimer molecular dynamics simulations yield a broadening of the energetically lowest peak in the absorption spectrum, but additional vibrational bands present in the experimental and simulated quantum harmonic oscillator spectra are not observed in the molecular dynamics simulations. Our results underline the importance of vibronic effects for the UV-vis spectrum of TCNQ - , and they establish an efficient method for obtaining vibronic spectra using a combination of linear-response time-dependent density functional theory and a real-time generating function approach.

Symmetry-Based Techniques for Qualitative Understanding of Rovibrational Effects in Spherical-Top Molecular Spectra and Dynamics

NASA Astrophysics Data System (ADS)

Mitchell, Justin Chadwick

2011-12-01

Using light to probe the structure of matter is as natural as opening our eyes. Modern physics and chemistry have turned this art into a rich science, measuring the delicate interactions possible at the molecular level. Perhaps the most commonly used tool in computational spectroscopy is that of matrix diagonalization. While this is invaluable for calculating everything from molecular structure and energy levels to dipole moments and dynamics, the process of numerical diagonalization is an opaque one. This work applies symmetry and semi-classical techniques to elucidate numerical spectral analysis for high-symmetry molecules. Semi-classical techniques, such as the Potential Energy Surfaces, have long been used to help understand molecular vibronic and rovibronic spectra and dynamics. This investigation focuses on newer semi-classical techniques that apply Rotational Energy Surfaces (RES) to rotational energy level clustering effects in high-symmetry molecules. Such clusters exist in rigid rotor molecules as well as deformable spherical tops. This study begins by using the simplicity of rigid symmetric top molecules to clarify the classical-quantum correspondence of RES semi-classical analysis and then extends it to a more precise and complete theory of modern high-resolution spectra. RES analysis is extended to molecules having more complex and higher rank tensorial rotational and rovibrational Hamiltonians than were possible to understand before. Such molecules are shown to produce an extraordinary range of rotational level clusters, corresponding to a panoply of symmetries ranging from C4v to C2 and C1 (no symmetry) with a corresponding range of new angular momentum localization and J-tunneling effects. Using RES topography analysis and the commutation duality relations between symmetry group operators in the lab-frame to those in the body-frame, it is shown how to better describe and catalog complex splittings found in rotational level clusters. Symmetry character analysis is generalized to give analytic eigensolutions. An appendix provides vibrational analogies. For the first time, interactions between molecular vibrations (polyads) are described semi-classically by multiple RES. This is done for the nu 3/2nu4 dyad of CF4. The nine-surface RES topology of the U(9)-dyad agrees with both computational and experimental work. A connection between this and a simpler U(2) example is detailed in an Appendix.

Logic circuits based on molecular spider systems.

PubMed

Mo, Dandan; Lakin, Matthew R; Stefanovic, Darko

2016-08-01

Spatial locality brings the advantages of computation speed-up and sequence reuse to molecular computing. In particular, molecular walkers that undergo localized reactions are of interest for implementing logic computations at the nanoscale. We use molecular spider walkers to implement logic circuits. We develop an extended multi-spider model with a dynamic environment wherein signal transmission is triggered via localized reactions, and use this model to implement three basic gates (AND, OR, NOT) and a cascading mechanism. We develop an algorithm to automatically generate the layout of the circuit. We use a kinetic Monte Carlo algorithm to simulate circuit computations, and we analyze circuit complexity: our design scales linearly with formula size and has a logarithmic time complexity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Temperature for a dynamic spin ensemble

NASA Astrophysics Data System (ADS)

Ma, Pui-Wai; Dudarev, S. L.; Semenov, A. A.; Woo, C. H.

2010-09-01

In molecular dynamics simulations, temperature is evaluated, via the equipartition principle, by computing the mean kinetic energy of atoms. There is no similar recipe yet for evaluating temperature of a dynamic system of interacting spins. By solving semiclassical Langevin spin-dynamics equations, and applying the fluctuation-dissipation theorem, we derive an equation for the temperature of a spin ensemble, expressed in terms of dynamic spin variables. The fact that definitions for the kinetic and spin temperatures are fully consistent is illustrated using large-scale spin dynamics and spin-lattice dynamics simulations.

Biodiversity research in the “big data” era: GigaScience and Pensoft work together to publish the most data-rich species description

PubMed Central

2013-01-01

With the publication of the first eukaryotic species description, combining transcriptomic, DNA barcoding, and micro-CT imaging data, GigaScience and Pensoft demonstrate how classical taxonomic description of a new species can be enhanced by applying new generation molecular methods, and novel computing and imaging technologies. This 'holistic’ approach in taxonomic description of a new species of cave-dwelling centipede is published in the Biodiversity Data Journal (BDJ), with coordinated data release in the GigaScience GigaDB database. PMID:24229463

Biodiversity research in the "big data" era: GigaScience and Pensoft work together to publish the most data-rich species description.

PubMed

Edmunds, Scott C; Hunter, Chris I; Smith, Vincent; Stoev, Pavel; Penev, Lyubomir

2013-10-28

With the publication of the first eukaryotic species description, combining transcriptomic, DNA barcoding, and micro-CT imaging data, GigaScience and Pensoft demonstrate how classical taxonomic description of a new species can be enhanced by applying new generation molecular methods, and novel computing and imaging technologies. This 'holistic' approach in taxonomic description of a new species of cave-dwelling centipede is published in the Biodiversity Data Journal (BDJ), with coordinated data release in the GigaScience GigaDB database.

ChemEngine: harvesting 3D chemical structures of supplementary data from PDF files.

PubMed

Karthikeyan, Muthukumarasamy; Vyas, Renu

2016-01-01

Digital access to chemical journals resulted in a vast array of molecular information that is now available in the supplementary material files in PDF format. However, extracting this molecular information, generally from a PDF document format is a daunting task. Here we present an approach to harvest 3D molecular data from the supporting information of scientific research articles that are normally available from publisher's resources. In order to demonstrate the feasibility of extracting truly computable molecules from PDF file formats in a fast and efficient manner, we have developed a Java based application, namely ChemEngine. This program recognizes textual patterns from the supplementary data and generates standard molecular structure data (bond matrix, atomic coordinates) that can be subjected to a multitude of computational processes automatically. The methodology has been demonstrated via several case studies on different formats of coordinates data stored in supplementary information files, wherein ChemEngine selectively harvested the atomic coordinates and interpreted them as molecules with high accuracy. The reusability of extracted molecular coordinate data was demonstrated by computing Single Point Energies that were in close agreement with the original computed data provided with the articles. It is envisaged that the methodology will enable large scale conversion of molecular information from supplementary files available in the PDF format into a collection of ready- to- compute molecular data to create an automated workflow for advanced computational processes. Software along with source codes and instructions available at https://sourceforge.net/projects/chemengine/files/?source=navbar.Graphical abstract.

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

Teaching Molecular Biology with Microcomputers.

ERIC Educational Resources Information Center

Reiss, Rebecca; Jameson, David

1984-01-01

Describes a series of computer programs that use simulation and gaming techniques to present the basic principles of the central dogma of molecular genetics, mutation, and the genetic code. A history of discoveries in molecular biology is presented and the evolution of these computer assisted instructional programs is described. (MBR)

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.

Mapping the Space of Genomic Signatures

PubMed Central

Kari, Lila; Hill, Kathleen A.; Sayem, Abu S.; Karamichalis, Rallis; Bryans, Nathaniel; Davis, Katelyn; Dattani, Nikesh S.

2015-01-01

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands of complete mitochondrial genomes. An "image distance" is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Molecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to k (herein k = 9) in DNA sequences. We computed DSSIM distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence alignment and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information. This method also correctly finds the mtDNA sequences most closely related to that of the anatomically modern human (the Neanderthal, the Denisovan, and the chimp), and that the sequence most different from it in this dataset belongs to a cucumber. PMID:26000734

Modeling of a carbon nanotube ultracapacitor.

PubMed

Orphanou, Antonis; Yamada, Toshishige; Yang, Cary Y

2012-03-09

The modeling of carbon nanotube ultracapacitor (CNU) performance based on the simulation of electrolyte ion motion between the cathode and the anode is described. Using a molecular dynamics (MD) approach, the equilibrium positions of the electrode charges interacting through the Coulomb potential are determined, which in turn yield the equipotential surface and electric field associated with the capacitor. With an applied ac voltage, the current is computed based on the nanotube and electrolyte particle distribution and interaction, resulting in the frequency-dependent impedance Z(ω). From the current and impedance profiles, the Nyquist and cyclic voltammetry (CV) plots are then extracted. The results of these calculations compare well with existing experimental data. A lumped-element equivalent circuit for the CNU is proposed and the impedance computed from this circuit correlates well with the simulated and measured impedances.

Computer modeling in developmental biology: growing today, essential tomorrow.

PubMed

Sharpe, James

2017-12-01

D'Arcy Thompson was a true pioneer, applying mathematical concepts and analyses to the question of morphogenesis over 100 years ago. The centenary of his famous book, On Growth and Form , is therefore a great occasion on which to review the types of computer modeling now being pursued to understand the development of organs and organisms. Here, I present some of the latest modeling projects in the field, covering a wide range of developmental biology concepts, from molecular patterning to tissue morphogenesis. Rather than classifying them according to scientific question, or scale of problem, I focus instead on the different ways that modeling contributes to the scientific process and discuss the likely future of modeling in developmental biology. © 2017. Published by The Company of Biologists Ltd.

BetaCavityWeb: a webserver for molecular voids and channels

PubMed Central

Kim, Jae-Kwan; Cho, Youngsong; Lee, Mokwon; Laskowski, Roman A.; Ryu, Seong Eon; Sugihara, Kokichi; Kim, Deok-Soo

2015-01-01

Molecular cavities, which include voids and channels, are critical for molecular function. We present a webserver, BetaCavityWeb, which computes these cavities for a given molecular structure and a given spherical probe, and reports their geometrical properties: volume, boundary area, buried area, etc. The server's algorithms are based on the Voronoi diagram of atoms and its derivative construct: the beta-complex. The correctness of the computed result and computational efficiency are both mathematically guaranteed. BetaCavityWeb is freely accessible at the Voronoi Diagram Research Center (VDRC) (http://voronoi.hanyang.ac.kr/betacavityweb). PMID:25904629

Computational Nanotechnology Molecular Electronics, Materials and Machines

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Biegel, Bryan A. (Technical Monitor)

2002-01-01

This presentation covers research being performed on computational nanotechnology, carbon nanotubes and fullerenes at the NASA Ames Research Center. Topics cover include: nanomechanics of nanomaterials, nanotubes and composite materials, molecular electronics with nanotube junctions, kinky chemistry, and nanotechnology for solid-state quantum computers using fullerenes.

A quantum-mechanics molecular-mechanics scheme for extended systems

NASA Astrophysics Data System (ADS)

Hunt, Diego; Sanchez, Veronica M.; Scherlis, Damián A.

2016-08-01

We introduce and discuss a hybrid quantum-mechanics molecular-mechanics (QM-MM) approach for Car-Parrinello DFT simulations with pseudopotentials and planewaves basis, designed for the treatment of periodic systems. In this implementation the MM atoms are considered as additional QM ions having fractional charges of either sign, which provides conceptual and computational simplicity by exploiting the machinery already existing in planewave codes to deal with electrostatics in periodic boundary conditions. With this strategy, both the QM and MM regions are contained in the same supercell, which determines the periodicity for the whole system. Thus, while this method is not meant to compete with non-periodic QM-MM schemes able to handle extremely large but finite MM regions, it is shown that for periodic systems of a few hundred atoms, our approach provides substantial savings in computational times by treating classically a fraction of the particles. The performance and accuracy of the method is assessed through the study of energetic, structural, and dynamical aspects of the water dimer and of the aqueous bulk phase. Finally, the QM-MM scheme is applied to the computation of the vibrational spectra of water layers adsorbed at the TiO2 anatase (1 0 1) solid-liquid interface. This investigation suggests that the inclusion of a second monolayer of H2O molecules is sufficient to induce on the first adsorbed layer, a vibrational dynamics similar to that taking place in the presence of an aqueous environment. The present QM-MM scheme appears as a very interesting tool to efficiently perform molecular dynamics simulations of complex condensed matter systems, from solutions to nanoconfined fluids to different kind of interfaces.

A quantum-mechanics molecular-mechanics scheme for extended systems.

PubMed

Hunt, Diego; Sanchez, Veronica M; Scherlis, Damián A

2016-08-24

We introduce and discuss a hybrid quantum-mechanics molecular-mechanics (QM-MM) approach for Car-Parrinello DFT simulations with pseudopotentials and planewaves basis, designed for the treatment of periodic systems. In this implementation the MM atoms are considered as additional QM ions having fractional charges of either sign, which provides conceptual and computational simplicity by exploiting the machinery already existing in planewave codes to deal with electrostatics in periodic boundary conditions. With this strategy, both the QM and MM regions are contained in the same supercell, which determines the periodicity for the whole system. Thus, while this method is not meant to compete with non-periodic QM-MM schemes able to handle extremely large but finite MM regions, it is shown that for periodic systems of a few hundred atoms, our approach provides substantial savings in computational times by treating classically a fraction of the particles. The performance and accuracy of the method is assessed through the study of energetic, structural, and dynamical aspects of the water dimer and of the aqueous bulk phase. Finally, the QM-MM scheme is applied to the computation of the vibrational spectra of water layers adsorbed at the TiO2 anatase (1 0 1) solid-liquid interface. This investigation suggests that the inclusion of a second monolayer of H2O molecules is sufficient to induce on the first adsorbed layer, a vibrational dynamics similar to that taking place in the presence of an aqueous environment. The present QM-MM scheme appears as a very interesting tool to efficiently perform molecular dynamics simulations of complex condensed matter systems, from solutions to nanoconfined fluids to different kind of interfaces.

Computational study of the activity, dynamics, energetics and conformations of insulin analogues using molecular dynamics simulations: Application to hyperinsulinemia and the critical residue B26.

PubMed

Papaioannou, Anastasios; Kuyucak, Serdar; Kuncic, Zdenka

2017-09-01

Due to the increasing prevalence of diabetes, finding therapeutic analogues for insulin has become an urgent issue. While many experimental studies have been performed towards this end, they have limited scope to examine all aspects of the effect of a mutation. Computational studies can help to overcome these limitations, however, relatively few studies that focus on insulin analogues have been performed to date. Here, we present a comprehensive computational study of insulin analogues-three mutant insulins that have been identified with hyperinsulinemia and three mutations on the critical B26 residue that exhibit similar binding affinity to the insulin receptor-using molecular dynamics simulations with the aim of predicting how mutations of insulin affect its activity, dynamics, energetics and conformations. The time evolution of the conformers is studied in long simulations. The probability density function and potential of mean force calculations are performed on each insulin analogue to unravel the effect of mutations on the dynamics and energetics of insulin activation. Our conformational study can decrypt the key features and molecular mechanisms that are responsible for an enhanced or reduced activity of an insulin analogue. We find two key results: 1) hyperinsulinemia may be due to the drastically reduced activity (and binding affinity) of the mutant insulins. 2) Y26 B S and Y26 B E are promising therapeutic candidates for insulin as they are more active than WT-insulin. The analysis in this work can be readily applied to any set of mutations on insulin to guide development of more effective therapeutic analogues.

First principles calculations for liquids and solids using maximally localized Wannier functions

NASA Astrophysics Data System (ADS)

Swartz, Charles W., VI

The field of condensed matter computational physics has seen an explosion of applicability over the last 50+ years. Since the very first calculations with ENIAC and MANIAC the field has continued to pushed the boundaries of what is possible; from the first large-scale molecular dynamics simulation, to the implementation of Density Functional Theory and large scale Car-Parrinello molecular dynamics, to million-core turbulence calculations by Standford. These milestones represent not only technological advances but theoretical breakthroughs and algorithmic improvements as well. The work in this thesis was completed in the hopes of furthering such advancement, even by a small fraction. Here we will focus mainly on the calculation of electronic and structural properties of solids and liquids, where we shall implement a wide range of novel approaches that are both computational efficient and physically enlightening. To this end we routinely will work with maximally localized Wannier functions (MLWFs) which have recently seen a revival in mainstream scientific literature. MLWFs present us with interesting opportunity to calculate a localized orbital within the planewave formalism of atomistic simulations. Such a localization will prove to be invaluable in the construction of layer-based superlattice models, linear scaling hybrid functional schemes and model quasiparticle calculations. In the first application of MLWF we will look at modeling functional piezoelectricity in superlattices. Based on the locality principle of insulating superlattices, we apply the method of Wu et al to the piezoelectric strains of individual layers under iifixed displacement field. For a superlattice of arbitrary stacking sequence an accurate model is acquired for predicting piezoelectricity. By applying the model in the superlattices where ferroelectric and antiferrodistortive modes are in competition, functional piezoelectricity can be achieved. A strong nonlinear effect is observed and can be further engineered in the PbTiO3 /SrTiO3 superlattice and an interface enhancement of piezoelectricity is found in the BaTiO3 /CaTiO3 superlattice. The second project will look at The ionization potential distributions of hydrated hydroxide and hydronium which are computed within a many-body approach for electron excitations using configurations generated by ab initio molecular dynamics. The experimental features are well reproduced and found to be closely related to the molecular excitations. In the stable configurations, the ionization potential is mainly perturbed by solvent water molecules within the first solvation shell. On the other hand, electron excitation is delocalized on both proton receiving and donating complex during proton transfer, which shifts the excitation energies and broadens the spectra for both hydrated ions. The third project represents a work in progress, where we also make use of the previous electron excitation theory applied to ab initio x-ray emission spectroscopy. In this case we make use of a novel method to include the ultrafast core-hole electron dynamics present in such situations. At present we have shown only strong qualitative agreement with experiment.

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent.

PubMed

Peter, Emanuel K; Shea, Joan-Emma; Pivkin, Igor V

2016-05-14

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC). The new development significantly can reduce the amount of replicas and the computational cost needed to enhance sampling in protein simulations. We introduce 2 different methods which primarily differ in the exchange scheme between the parallel ensembles. We apply this approach on folding of 2 different β-stranded peptides: the C-terminal β-hairpin fragment of GB1 and TrpZip4. Additionally, we use the new simulation technique to study the folding of TrpCage, a small fast folding α-helical peptide. Subsequently, we apply the new methodology on conformation changes in signaling of the light-oxygen voltage (LOV) sensitive domain from Avena sativa (AsLOV2). Our results agree well with data reported in the literature. In simulations of dialanine, we compare the statistical sampling of the 2 techniques with conventional REMD and analyze their performance. The new techniques can reduce the computational cost of REMD significantly and can be used in enhanced sampling simulations of biomolecules.

Toward ab initio molecular dynamics modeling for sum-frequency generation spectra; an efficient algorithm based on surface-specific velocity-velocity correlation function.

PubMed

Ohto, Tatsuhiko; Usui, Kota; Hasegawa, Taisuke; Bonn, Mischa; Nagata, Yuki

2015-09-28

Interfacial water structures have been studied intensively by probing the O-H stretch mode of water molecules using sum-frequency generation (SFG) spectroscopy. This surface-specific technique is finding increasingly widespread use, and accordingly, computational approaches to calculate SFG spectra using molecular dynamics (MD) trajectories of interfacial water molecules have been developed and employed to correlate specific spectral signatures with distinct interfacial water structures. Such simulations typically require relatively long (several nanoseconds) MD trajectories to allow reliable calculation of the SFG response functions through the dipole moment-polarizability time correlation function. These long trajectories limit the use of computationally expensive MD techniques such as ab initio MD and centroid MD simulations. Here, we present an efficient algorithm determining the SFG response from the surface-specific velocity-velocity correlation function (ssVVCF). This ssVVCF formalism allows us to calculate SFG spectra using a MD trajectory of only ∼100 ps, resulting in the substantial reduction of the computational costs, by almost an order of magnitude. We demonstrate that the O-H stretch SFG spectra at the water-air interface calculated by using the ssVVCF formalism well reproduce those calculated by using the dipole moment-polarizability time correlation function. Furthermore, we applied this ssVVCF technique for computing the SFG spectra from the ab initio MD trajectories with various density functionals. We report that the SFG responses computed from both ab initio MD simulations and MD simulations with an ab initio based force field model do not show a positive feature in its imaginary component at 3100 cm(-1).

Molecular Modeling and Computational Chemistry at Humboldt State University.

ERIC Educational Resources Information Center

Paselk, Richard A.; Zoellner, Robert W.

2002-01-01

Describes a molecular modeling and computational chemistry (MM&CC) facility for undergraduate instruction and research at Humboldt State University. This facility complex allows the introduction of MM&CC throughout the chemistry curriculum with tailored experiments in general, organic, and inorganic courses as well as a new molecular modeling…

Computational approach to integrate 3D X-ray microtomography and NMR data

NASA Astrophysics Data System (ADS)

Lucas-Oliveira, Everton; Araujo-Ferreira, Arthur G.; Trevizan, Willian A.; Fortulan, Carlos A.; Bonagamba, Tito J.

2018-07-01

Nowadays, most of the efforts in NMR applied to porous media are dedicated to studying the molecular fluid dynamics within and among the pores. These analyses have a higher complexity due to morphology and chemical composition of rocks, besides dynamic effects as restricted diffusion, diffusional coupling, and exchange processes. Since the translational nuclear spin diffusion in a confined geometry (e.g. pores and fractures) requires specific boundary conditions, the theoretical solutions are restricted to some special problems and, in many cases, computational methods are required. The Random Walk Method is a classic way to simulate self-diffusion along a Digital Porous Medium. Bergman model considers the magnetic relaxation process of the fluid molecules by including a probability rate of magnetization survival under surface interactions. Here we propose a statistical approach to correlate surface magnetic relaxivity with the computational method applied to the NMR relaxation in order to elucidate the relationship between simulated relaxation time and pore size of the Digital Porous Medium. The proposed computational method simulates one- and two-dimensional NMR techniques reproducing, for example, longitudinal and transverse relaxation times (T1 and T2, respectively), diffusion coefficients (D), as well as their correlations. For a good approximation between the numerical and experimental results, it is necessary to preserve the complexity of translational diffusion through the microstructures in the digital rocks. Therefore, we use Digital Porous Media obtained by 3D X-ray microtomography. To validate the method, relaxation times of ideal spherical pores were obtained and compared with the previous determinations by the Brownstein-Tarr model, as well as the computational approach proposed by Bergman. Furthermore, simulated and experimental results of synthetic porous media are compared. These results make evident the potential of computational physics in the analysis of the NMR data for complex porous materials.

Molecular dynamic simulation of Ar-Kr mixture across a rough walled nanochannel: Velocity and temperature profiles

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

Pooja,, E-mail: pupooja16@gmail.com; Ahluwalia, P. K., E-mail: pk-ahluwalia7@yahoo.com; Pathania, Y.

2015-05-15

This paper presents the results from a molecular dynamics simulation of mixture of argon and krypton in the Poiseuille flow across a rough walled nanochannel. The roughness effect on liquid nanoflows has recently drawn attention The computational software used for carrying out the molecular dynamics simulations is LAMMPS. The fluid flow takes place between two parallel plates and is bounded by horizontal rough walls in one direction and periodic boundary conditions are imposed in the other two directions. Each fluid atom interacts with other fluid atoms and wall atoms through Leenard-Jones (LJ) potential with a cut off distance of 5.0.more » To derive the flow a constant force is applied whose value is varied from 0.1 to 0.3 and velocity profiles and temperature profiles are noted for these values of forces. The velocity profile and temperature profiles are also looked at different channel widths of nanochannel and at different densities of mixture. The velocity profile and temperature profile of rough walled nanochannel are compared with that of smooth walled nanochannel and it is concluded that mean velocity increases with increase in channel width, force applied and decrease in density also with introduction of roughness in the walls of nanochannel mean velocity again increases and results also agree with the analytical solution of a Poiseuille flow.« less

Faster protein folding using enhanced conformational sampling of molecular dynamics simulation.

PubMed

Kamberaj, Hiqmet

2018-05-01

In this study, we applied swarm particle-like molecular dynamics (SPMD) approach to enhance conformational sampling of replica exchange simulations. In particular, the approach showed significant improvement in sampling efficiency of conformational phase space when combined with replica exchange method (REM) in computer simulation of peptide/protein folding. First we introduce the augmented dynamical system of equations, and demonstrate the stability of the algorithm. Then, we illustrate the approach by using different fully atomistic and coarse-grained model systems, comparing them with the standard replica exchange method. In addition, we applied SPMD simulation to calculate the time correlation functions of the transitions in a two dimensional surface to demonstrate the enhancement of transition path sampling. Our results showed that folded structure can be obtained in a shorter simulation time using the new method when compared with non-augmented dynamical system. Typically, in less than 0.5 ns using replica exchange runs assuming that native folded structure is known and within simulation time scale of 40 ns in the case of blind structure prediction. Furthermore, the root mean square deviations from the reference structures were less than 2Å. To demonstrate the performance of new method, we also implemented three simulation protocols using CHARMM software. Comparisons are also performed with standard targeted molecular dynamics simulation method. Copyright © 2018 Elsevier Inc. All rights reserved.

Molecular dynamic simulation of Ar-Kr mixture across a rough walled nanochannel: Velocity & temperature profiles

NASA Astrophysics Data System (ADS)

Pooja, Pathania, Y.; Ahluwalia, P. K.

2015-05-01

This paper presents the results from a molecular dynamics simulation of mixture of argon and krypton in the Poiseuille flow across a rough walled nanochannel. The roughness effect on liquid nanoflows has recently drawn attention The computational software used for carrying out the molecular dynamics simulations is LAMMPS. The fluid flow takes place between two parallel plates and is bounded by horizontal rough walls in one direction and periodic boundary conditions are imposed in the other two directions. Each fluid atom interacts with other fluid atoms and wall atoms through Leenard-Jones (LJ) potential with a cut off distance of 5.0. To derive the flow a constant force is applied whose value is varied from 0.1 to 0.3 and velocity profiles and temperature profiles are noted for these values of forces. The velocity profile and temperature profiles are also looked at different channel widths of nanochannel and at different densities of mixture. The velocity profile and temperature profile of rough walled nanochannel are compared with that of smooth walled nanochannel and it is concluded that mean velocity increases with increase in channel width, force applied and decrease in density also with introduction of roughness in the walls of nanochannel mean velocity again increases and results also agree with the analytical solution of a Poiseuille flow.

Enhancing Next-Generation Sequencing-Guided Cancer Care Through Cognitive Computing.

PubMed

Patel, Nirali M; Michelini, Vanessa V; Snell, Jeff M; Balu, Saianand; Hoyle, Alan P; Parker, Joel S; Hayward, Michele C; Eberhard, David A; Salazar, Ashley H; McNeillie, Patrick; Xu, Jia; Huettner, Claudia S; Koyama, Takahiko; Utro, Filippo; Rhrissorrakrai, Kahn; Norel, Raquel; Bilal, Erhan; Royyuru, Ajay; Parida, Laxmi; Earp, H Shelton; Grilley-Olson, Juneko E; Hayes, D Neil; Harvey, Stephen J; Sharpless, Norman E; Kim, William Y

2018-02-01

Using next-generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human "molecular tumor boards" (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB. One thousand eighteen patient cases that previously underwent targeted exon sequencing at the University of North Carolina (UNC) and subsequent analysis by the UNCseq informatics pipeline and the UNC MTB between November 7, 2011, and May 12, 2015, were analyzed with WfG, a cognitive computing technology for genomic analysis. Using a WfG-curated actionable gene list, we identified additional genomic events of potential significance (not discovered by traditional MTB curation) in 323 (32%) patients. The majority of these additional genomic events were considered actionable based upon their ability to qualify patients for biomarker-selected clinical trials. Indeed, the opening of a relevant clinical trial within 1 month prior to WfG analysis provided the rationale for identification of a new actionable event in nearly a quarter of the 323 patients. This automated analysis took <3 minutes per case. These results demonstrate that the interpretation and actionability of somatic NGS results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing could potentially improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of up-to-date availability of clinical trials. The results of this study demonstrate that the interpretation and actionability of somatic next-generation sequencing results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing can significantly improve patient care by providing a fast, cost-effective, and comprehensive approach for data analysis in the delivery of precision medicine. Patients and physicians who are considering enrollment in clinical trials may benefit from the support of such tools applied to genomic data. © AlphaMed Press 2017.

Effect of sesamin against cytokine production from influenza type A H1N1-induced peripheral blood mononuclear cells: computational and experimental studies.

PubMed

Fanhchaksai, Kanda; Kodchakorn, Kanchanok; Pothacharoen, Peraphan; Kongtawelert, Prachya

2016-01-01

In 2009, swine flu (H1N1) had spread significantly to levels that threatened pandemic influenza. There have been many treatments that have arisen for patients since the WHO first reported the disease. Although some progress in controlling influenza has taken place during the last few years, the disease is not yet under control. The development of new and less expensive anti-influenza drugs is still needed. Here, we show that sesamin from the seeds of the Thai medicinal plant Sesamum indicum has anti-inflammatory cytokines in human peripheral blood mononuclear cells (PBMCs) induced by 2009 influenza virus type A H1N1. In this study, the combinatorial screening method combined with the computational approach was applied to investigate the new molecular binding structures of sesamin against the 2009 influenza virus type A H1N1 (p09N1) crystallized structure. Experimental methods were applied to propose the mechanisms of sesamin against cytokine production from H1N1-induced human PBMC model. The molecular dynamics simulation of sesamin binding with the p09N1 crystallized structure showed new molecular binding structures at ARG118, ILE222, ARG224, and TYR406, and it has been proposed that sesamin could potentially be used to produce anti-H1N1 compounds. Furthermore, the mechanisms of sesamin against cytokine production from influenza type A H1N1-induced PBMCs by ELISA and signaling transduction showed that sesamin exhibits the ability to inhibit proinflammatory cytokines, IL-1β and TNF-α, and to enhance the activity of the immune cell cytokine IL-2 via downregulating the phosphorylated JNK, p38, and ERK1/2 MAPK signaling pathways. This information might very well be useful in the prevention and treatment of immune-induced inflammatory disorders.

Comparison of molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) and molecular mechanics-three-dimensional reference interaction site model (MM-3D-RISM) method to calculate the binding free energy of protein-ligand complexes: Effect of metal ion and advance statistical test

NASA Astrophysics Data System (ADS)

Pandey, Preeti; Srivastava, Rakesh; Bandyopadhyay, Pradipta

2018-03-01

The relative performance of MM-PBSA and MM-3D-RISM methods to estimate the binding free energy of protein-ligand complexes is investigated by applying these to three proteins (Dihydrofolate Reductase, Catechol-O-methyltransferase, and Stromelysin-1) differing in the number of metal ions they contain. None of the computational methods could distinguish all the ligands based on their calculated binding free energies (as compared to experimental values). The difference between the two comes from both polar and non-polar part of solvation. For charged ligand case, MM-PBSA and MM-3D-RISM give a qualitatively different result for the polar part of solvation.

The torsional barriers of two equivalent methyl internal rotations in 2,5-dimethylfuran investigated by microwave spectroscopy

NASA Astrophysics Data System (ADS)

Van, Vinh; Bruckhuisen, Jonas; Stahl, Wolfgang; Ilyushin, Vadim; Nguyen, Ha Vinh Lam

2018-01-01

The microwave spectrum of 2,5-dimethylfuran was recorded using two pulsed molecular jet Fourier transform microwave spectrometers which cover the frequency range from 2 to 40 GHz. The internal rotations of two equivalent methyl tops with a barrier height of approximately 439.15 cm-1 introduce torsional splittings of all rotational transitions in the spectrum. For the spectral analysis, two different computer programs were applied and compared, the PAM-C2v-2tops code based on the principal axis method which treats several torsional states simultaneously, and the XIAM code based on the combined axis method, yielding accurate molecular parameters. The experimental work was supplemented by quantum chemical calculations. Two-dimensional potential energy surfaces depending on the torsional angles of both methyl groups were calculated and parametrized.

Voltage-Driven Conformational Switching with Distinct Raman Signature in a Single-Molecule Junction.

PubMed

Bi, Hai; Palma, Carlos-Andres; Gong, Yuxiang; Hasch, Peter; Elbing, Mark; Mayor, Marcel; Reichert, Joachim; Barth, Johannes V

2018-04-11

Precisely controlling well-defined, stable single-molecule junctions represents a pillar of single-molecule electronics. Early attempts to establish computing with molecular switching arrays were partly challenged by limitations in the direct chemical characterization of metal-molecule-metal junctions. While cryogenic scanning probe studies have advanced the mechanistic understanding of current- and voltage-induced conformational switching, metal-molecule-metal conformations are still largely inferred from indirect evidence. Hence, the development of robust, chemically sensitive techniques is instrumental for advancement in the field. Here we probe the conformation of a two-state molecular switch with vibrational spectroscopy, while simultaneously operating it by means of the applied voltage. Our study emphasizes measurements of single-molecule Raman spectra in a room-temperature stable single-molecule switch presenting a signal modulation of nearly 2 orders of magnitude.

Quasi-particle energy spectra in local reduced density matrix functional theory.

PubMed

Lathiotakis, Nektarios N; Helbig, Nicole; Rubio, Angel; Gidopoulos, Nikitas I

2014-10-28

Recently, we introduced [N. N. Lathiotakis, N. Helbig, A. Rubio, and N. I. Gidopoulos, Phys. Rev. A 90, 032511 (2014)] local reduced density matrix functional theory (local RDMFT), a theoretical scheme capable of incorporating static correlation effects in Kohn-Sham equations. Here, we apply local RDMFT to molecular systems of relatively large size, as a demonstration of its computational efficiency and its accuracy in predicting single-electron properties from the eigenvalue spectrum of the single-particle Hamiltonian with a local effective potential. We present encouraging results on the photoelectron spectrum of molecular systems and the relative stability of C20 isotopes. In addition, we propose a modelling of the fractional occupancies as functions of the orbital energies that further improves the efficiency of the method useful in applications to large systems and solids.

GTKDynamo: a PyMOL plug-in for QC/MM hybrid potential simulations

PubMed Central

Bachega, José Fernando R.; Timmers, Luís Fernando S.M.; Assirati, Lucas; Bachega, Leonardo R.; Field, Martin J.; Wymore, Troy

2014-01-01

Hybrid quantum chemical (QC)/molecular mechanical (MM) potentials are very powerful tools for molecular simulation. They are especially useful for studying processes in condensed phase systems, such as chemical reactions, that involve a relatively localized change in electronic structure and where the surrounding environment contributes to these changes but can be represented with more computationally efficient functional forms. Despite their utility, however, these potentials are not always straightforward to apply since the extent of significant electronic structure changes occurring in the condensed phase process may not be intuitively obvious. To facilitate their use we have developed an open-source graphical plug-in, GTKDynamo, that links the PyMOL visualization program and the pDynamo QC/MM simulation library. This article describes the implementation of GTKDynamo and its capabilities and illustrates its application to QC/MM simulations. PMID:24137667

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

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

PubChem3D: Shape compatibility filtering using molecular shape quadrupoles

PubMed Central

2011-01-01

Background PubChem provides a 3-D neighboring relationship, which involves finding the maximal shape overlap between two static compound 3-D conformations, a computationally intensive step. It is highly desirable to avoid this overlap computation, especially if it can be determined with certainty that a conformer pair cannot meet the criteria to be a 3-D neighbor. As such, PubChem employs a series of pre-filters, based on the concept of volume, to remove approximately 65% of all conformer neighbor pairs prior to shape overlap optimization. Given that molecular volume, a somewhat vague concept, is rather effective, it leads one to wonder: can the existing PubChem 3-D neighboring relationship, which consists of billions of shape similar conformer pairs from tens of millions of unique small molecules, be used to identify additional shape descriptor relationships? Or, put more specifically, can one place an upper bound on shape similarity using other "fuzzy" shape-like concepts like length, width, and height? Results Using a basis set of 4.18 billion 3-D neighbor pairs identified from single conformer per compound neighboring of 17.1 million molecules, shape descriptors were computed for all conformers. These steric shape descriptors included several forms of molecular volume and shape quadrupoles, which essentially embody the length, width, and height of a conformer. For a given 3-D neighbor conformer pair, the volume and each quadrupole component (Qx, Qy, and Qz) were binned and their frequency of occurrence was examined. Per molecular volume type, this effectively produced three different maps, one per quadrupole component (Qx, Qy, and Qz), of allowed values for the similarity metric, shape Tanimoto (ST) ≥ 0.8. The efficiency of these relationships (in terms of true positive, true negative, false positive and false negative) as a function of ST threshold was determined in a test run of 13.2 billion conformer pairs not previously considered by the 3-D neighbor set. At an ST ≥ 0.8, a filtering efficiency of 40.4% of true negatives was achieved with only 32 false negatives out of 24 million true positives, when applying the separate Qx, Qy, and Qz maps in a series (Qxyz). This efficiency increased linearly as a function of ST threshold in the range 0.8-0.99. The Qx filter was consistently the most efficient followed by Qy and then by Qz. Use of a monopole volume showed the best overall performance, followed by the self-overlap volume and then by the analytic volume. Application of the monopole-based Qxyz filter in a "real world" test of 3-D neighboring of 4,218 chemicals of biomedical interest against 26.1 million molecules in PubChem reduced the total CPU cost of neighboring by between 24-38% and, if used as the initial filter, removed from consideration 48.3% of all conformer pairs at almost negligible computational overhead. Conclusion Basic shape descriptors, such as those embodied by size, length, width, and height, can be highly effective in identifying shape incompatible compound conformer pairs. When performing a 3-D search using a shape similarity cut-off, computation can be avoided by identifying conformer pairs that cannot meet the result criteria. Applying this methodology as a filter for PubChem 3-D neighboring computation, an improvement of 31% was realized, increasing the average conformer pair throughput from 154,000 to 202,000 per second per CPU core. PMID:21774809

Design Principles of Nanoparticles as Contrast Agents for Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Shan, Liang; Gu, Xinbin; Wang, Paul

2013-09-01

Molecular imaging is an emerging field that introduces molecular agents into traditional imaging techniques, enabling visualization, characterization and measurement of biological processes at the molecular and cellular levels in humans and other living systems. The promise of molecular imaging lies in its potential for selective potency by targeting biomarkers or molecular targets and the imaging agents serve as reporters for the selectivity of targeting. Development of an efficient molecular imaging agent depends on well-controlled high-quality experiment design involving target selection, agent synthesis, in vitro characterization, and in vivo animal characterization before it is applied in humans. According to the analysis from the Molecular Imaging and Contrast Agent Database (MICAD, ), more than 6000 molecular imaging agents with sufficient preclinical evaluation have been reported to date in the literature and this number increases by 250-300 novel agents each year. The majority of these agents are radionuclides, which are developed for positron emission tomography (PET) and single photon emission computed tomography (SPECT). Contrast agents for magnetic resonance imaging (MRI) account for only a small part. This is largely due to the fact that MRI is currently not a fully quantitative imaging technique and is less sensitive than PET and SPECT. However, because of the superior ability to simultaneously extract molecular and anatomic information, molecular MRI is attracting significant interest and various targeted nanoparticle contrast agents have been synthesized for MRI. The first and one of the most critical steps in developing a targeted nanoparticle contrast agent is target selection, which plays the central role and forms the basis for success of molecular imaging. This chapter discusses the design principles of targeted contrast agents in the emerging frontiers of molecular MRI.

Computational evaluation of sub-nanometer cluster activity of singly exposed copper atom with various coordinative environment in catalytic CO2 transformation

NASA Astrophysics Data System (ADS)

Shanmugam, Ramasamy; Thamaraichelvan, Arunachalam; Ganesan, Tharumeya Kuppusamy; Viswanathan, Balasubramanian

2017-02-01

Metal cluster, at sub-nanometer level has a unique property in the activation of small molecules, in contrast to that of bulk surface. In the present work, singly exposed active site of copper metal cluster at sub-nanometer level was designed to arrive at the energy minimised configurations, binding energy, electrostatic potential map, frontier molecular orbitals and partial density of states. The ab initio molecular dynamics was carried out to probe the catalytic nature of the cluster. Further, the stability of the metal cluster and its catalytic activity in the electrochemical reduction of CO2 to CO were evaluated by means of computational hydrogen electrode via calculation of the free energy profile using DFT/B3LYP level of theory in vacuum. The activity of the cluster is ascertained from the fact that the copper atom, present in a two coordinative environment, performs a more selective conversion of CO2 to CO at an applied potential of -0.35 V which is comparatively lower than that of higher coordinative sites. The present study helps to design any sub-nano level metal catalyst for electrochemical reduction of CO2 to various value added chemicals.

A reactive, scalable, and transferable model for molecular energies from a neural network approach based on local information

NASA Astrophysics Data System (ADS)

Unke, Oliver T.; Meuwly, Markus

2018-06-01

Despite the ever-increasing computer power, accurate ab initio calculations for large systems (thousands to millions of atoms) remain infeasible. Instead, approximate empirical energy functions are used. Most current approaches are either transferable between different chemical systems, but not particularly accurate, or they are fine-tuned to a specific application. In this work, a data-driven method to construct a potential energy surface based on neural networks is presented. Since the total energy is decomposed into local atomic contributions, the evaluation is easily parallelizable and scales linearly with system size. With prediction errors below 0.5 kcal mol-1 for both unknown molecules and configurations, the method is accurate across chemical and configurational space, which is demonstrated by applying it to datasets from nonreactive and reactive molecular dynamics simulations and a diverse database of equilibrium structures. The possibility to use small molecules as reference data to predict larger structures is also explored. Since the descriptor only uses local information, high-level ab initio methods, which are computationally too expensive for large molecules, become feasible for generating the necessary reference data used to train the neural network.

Detecting vapour bubbles in simulations of metastable water

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

González, Miguel A.; Abascal, Jose L. F.; Valeriani, Chantal, E-mail: christoph.dellago@univie.ac.at, E-mail: cvaleriani@quim.ucm.es

2014-11-14

The investigation of cavitation in metastable liquids with molecular simulations requires an appropriate definition of the volume of the vapour bubble forming within the metastable liquid phase. Commonly used approaches for bubble detection exhibit two significant flaws: first, when applied to water they often identify the voids within the hydrogen bond network as bubbles thus masking the signature of emerging bubbles and, second, they lack thermodynamic consistency. Here, we present two grid-based methods, the M-method and the V-method, to detect bubbles in metastable water specifically designed to address these shortcomings. The M-method incorporates information about neighbouring grid cells to distinguishmore » between liquid- and vapour-like cells, which allows for a very sensitive detection of small bubbles and high spatial resolution of the detected bubbles. The V-method is calibrated such that its estimates for the bubble volume correspond to the average change in system volume and are thus thermodynamically consistent. Both methods are computationally inexpensive such that they can be used in molecular dynamics and Monte Carlo simulations of cavitation. We illustrate them by computing the free energy barrier and the size of the critical bubble for cavitation in water at negative pressure.« less

Investigation of effective impact parameters in electron-ion temperature relaxation via Particle-Particle Coulombic molecular dynamics

NASA Astrophysics Data System (ADS)

Zhao, Yinjian

2017-09-01

Aiming at a high simulation accuracy, a Particle-Particle (PP) Coulombic molecular dynamics model is implemented to study the electron-ion temperature relaxation. In this model, the Coulomb's law is directly applied in a bounded system with two cutoffs at both short and long length scales. By increasing the range between the two cutoffs, it is found that the relaxation rate deviates from the BPS theory and approaches the LS theory and the GMS theory. Also, the effective minimum and maximum impact parameters (bmin* and bmax*) are obtained. For the simulated plasma condition, bmin* is about 6.352 times smaller than the Landau length (bC), and bmax* is about 2 times larger than the Debye length (λD), where bC and λD are used in the LS theory. Surprisingly, the effective relaxation time obtained from the PP model is very close to the LS theory and the GMS theory, even though the effective Coulomb logarithm is two times greater than the one used in the LS theory. Besides, this work shows that the PP model (commonly known as computationally expensive) is becoming practicable via GPU parallel computing techniques.

Chemical fingerprints of cold physical plasmas - an experimental and computational study using cysteine as tracer compound.

PubMed

Lackmann, J-W; Wende, K; Verlackt, C; Golda, J; Volzke, J; Kogelheide, F; Held, J; Bekeschus, S; Bogaerts, A; Schulz-von der Gathen, V; Stapelmann, K

2018-05-16

Reactive oxygen and nitrogen species released by cold physical plasma are being proposed as effectors in various clinical conditions connected to inflammatory processes. As these plasmas can be tailored in a wide range, models to compare and control their biochemical footprint are desired to infer on the molecular mechanisms underlying the observed effects and to enable the discrimination between different plasma sources. Here, an improved model to trace short-lived reactive species is presented. Using FTIR, high-resolution mass spectrometry, and molecular dynamics computational simulation, covalent modifications of cysteine treated with different plasmas were deciphered and the respective product pattern used to generate a fingerprint of each plasma source. Such, our experimental model allows a fast and reliable grading of the chemical potential of plasmas used for medical purposes. Major reaction products were identified to be cysteine sulfonic acid, cystine, and cysteine fragments. Less-abundant products, such as oxidized cystine derivatives or S-nitrosylated cysteines, were unique to different plasma sources or operating conditions. The data collected point at hydroxyl radicals, atomic O, and singlet oxygen as major contributing species that enable an impact on cellular thiol groups when applying cold plasma in vitro or in vivo.

Folding Proteins at 500 ns/hour with Work Queue.

PubMed

Abdul-Wahid, Badi'; Yu, Li; Rajan, Dinesh; Feng, Haoyun; Darve, Eric; Thain, Douglas; Izaguirre, Jesús A

2012-10-01

Molecular modeling is a field that traditionally has large computational costs. Until recently, most simulation techniques relied on long trajectories, which inherently have poor scalability. A new class of methods is proposed that requires only a large number of short calculations, and for which minimal communication between computer nodes is required. We considered one of the more accurate variants called Accelerated Weighted Ensemble Dynamics (AWE) and for which distributed computing can be made efficient. We implemented AWE using the Work Queue framework for task management and applied it to an all atom protein model (Fip35 WW domain). We can run with excellent scalability by simultaneously utilizing heterogeneous resources from multiple computing platforms such as clouds (Amazon EC2, Microsoft Azure), dedicated clusters, grids, on multiple architectures (CPU/GPU, 32/64bit), and in a dynamic environment in which processes are regularly added or removed from the pool. This has allowed us to achieve an aggregate sampling rate of over 500 ns/hour. As a comparison, a single process typically achieves 0.1 ns/hour.

Folding Proteins at 500 ns/hour with Work Queue

PubMed Central

Abdul-Wahid, Badi’; Yu, Li; Rajan, Dinesh; Feng, Haoyun; Darve, Eric; Thain, Douglas; Izaguirre, Jesús A.

2014-01-01

Molecular modeling is a field that traditionally has large computational costs. Until recently, most simulation techniques relied on long trajectories, which inherently have poor scalability. A new class of methods is proposed that requires only a large number of short calculations, and for which minimal communication between computer nodes is required. We considered one of the more accurate variants called Accelerated Weighted Ensemble Dynamics (AWE) and for which distributed computing can be made efficient. We implemented AWE using the Work Queue framework for task management and applied it to an all atom protein model (Fip35 WW domain). We can run with excellent scalability by simultaneously utilizing heterogeneous resources from multiple computing platforms such as clouds (Amazon EC2, Microsoft Azure), dedicated clusters, grids, on multiple architectures (CPU/GPU, 32/64bit), and in a dynamic environment in which processes are regularly added or removed from the pool. This has allowed us to achieve an aggregate sampling rate of over 500 ns/hour. As a comparison, a single process typically achieves 0.1 ns/hour. PMID:25540799

Solution of the lossy nonlinear Tricomi equation with application to sonic boom focusing

NASA Astrophysics Data System (ADS)

Salamone, Joseph A., III

Sonic boom focusing theory has been augmented with new terms that account for mean flow effects in the direction of propagation and also for atmospheric absorption/dispersion due to molecular relaxation due to oxygen and nitrogen. The newly derived model equation was numerically implemented using a computer code. The computer code was numerically validated using a spectral solution for nonlinear propagation of a sinusoid through a lossy homogeneous medium. An additional numerical check was performed to verify the linear diffraction component of the code calculations. The computer code was experimentally validated using measured sonic boom focusing data from the NASA sponsored Superboom Caustic and Analysis Measurement Program (SCAMP) flight test. The computer code was in good agreement with both the numerical and experimental validation. The newly developed code was applied to examine the focusing of a NASA low-boom demonstration vehicle concept. The resulting pressure field was calculated for several supersonic climb profiles. The shaping efforts designed into the signatures were still somewhat evident despite the effects of sonic boom focusing.

Interaction entropy for protein-protein binding

NASA Astrophysics Data System (ADS)

Sun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.

2017-03-01

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.

Interaction entropy for protein-protein binding.

PubMed

Sun, Zhaoxi; Yan, Yu N; Yang, Maoyou; Zhang, John Z H

2017-03-28

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interactionentropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interactionentropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.

Proteinortho: detection of (co-)orthologs in large-scale analysis.

PubMed

Lechner, Marcus; Findeiss, Sven; Steiner, Lydia; Marz, Manja; Stadler, Peter F; Prohaska, Sonja J

2011-04-28

Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.

Computational biology and bioinformatics in Nigeria.

PubMed

Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

2014-04-01

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography

PubMed Central

Cong, Wenxiang; Shen, Haiou; Wang, Ge

2011-01-01

The nanophosphors, or other similar materials, emit near-infrared (NIR) light upon x-ray excitation. They were designed as optical probes for in vivo visualization and analysis of molecular and cellular targets, pathways, and responses. Based on the previous work on x-ray fluorescence computed tomography (XFCT) and x-ray luminescence computed tomography (XLCT), here we propose a spectrally-resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography (SXLCT or SXFCT) approach to quantify a spatial distribution of nanophosphors (other similar materials or chemical elements) within a biological object. In this paper, the x-ray scattering is taken into account in the reconstruction algorithm. The NIR scattering is described in the diffusion approximation model. Then, x-ray excitations are applied with different spectra, and NIR signals are measured in a spectrally resolving fashion. Finally, a linear relationship is established between the nanophosphor distribution and measured NIR data using the finite element method and inverted using the compressive sensing technique. The numerical simulation results demonstrate the feasibility and merits of the proposed approach. PMID:21721815

Computational Biology and Bioinformatics in Nigeria

PubMed Central

Fatumo, Segun A.; Adoga, Moses P.; Ojo, Opeolu O.; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

2014-01-01

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. PMID:24763310

Design principles for cancer therapy guided by changes in complexity of protein-protein interaction networks.

PubMed

Benzekry, Sebastian; Tuszynski, Jack A; Rietman, Edward A; Lakka Klement, Giannoula

2015-05-28

The ever-increasing expanse of online bioinformatics data is enabling new ways to, not only explore the visualization of these data, but also to apply novel mathematical methods to extract meaningful information for clinically relevant analysis of pathways and treatment decisions. One of the methods used for computing topological characteristics of a space at different spatial resolutions is persistent homology. This concept can also be applied to network theory, and more specifically to protein-protein interaction networks, where the number of rings in an individual cancer network represents a measure of complexity. We observed a linear correlation of R = -0.55 between persistent homology and 5-year survival of patients with a variety of cancers. This relationship was used to predict the proteins within a protein-protein interaction network with the most impact on cancer progression. By re-computing the persistent homology after computationally removing an individual node (protein) from the protein-protein interaction network, we were able to evaluate whether such an inhibition would lead to improvement in patient survival. The power of this approach lied in its ability to identify the effects of inhibition of multiple proteins and in the ability to expose whether the effect of a single inhibition may be amplified by inhibition of other proteins. More importantly, we illustrate specific examples of persistent homology calculations, which correctly predict the survival benefit observed effects in clinical trials using inhibitors of the identified molecular target. We propose that computational approaches such as persistent homology may be used in the future for selection of molecular therapies in clinic. The technique uses a mathematical algorithm to evaluate the node (protein) whose inhibition has the highest potential to reduce network complexity. The greater the drop in persistent homology, the greater reduction in network complexity, and thus a larger potential for survival benefit. We hope that the use of advanced mathematics in medicine will provide timely information about the best drug combination for patients, and avoid the expense associated with an unsuccessful clinical trial, where drug(s) did not show a survival benefit.

A label-free and enzyme-free system for operating various logic devices using poly(thymine)-templated CuNPs and SYBR Green I as signal transducers

NASA Astrophysics Data System (ADS)

Wu, Changtong; Zhou, Chunyang; Wang, Erkang; Dong, Shaojun

2016-07-01

For the first time by integrating fluorescent polyT-templated CuNPs and SYBR Green I, a basic INHIBIT gate and four advanced logic circuits (2-to-1 encoder, 4-to-2 encoder, 1-to-2 decoder and 1-to-2 demultiplexer) have been conceptually realized under label-free and enzyme-free conditions. Taking advantage of the selective formation of CuNPs on ss-DNA, the implementation of these advanced logic devices were achieved without any usage of dye quenching groups or other nanomaterials like graphene oxide or AuNPs since polyA strands not only worked as an input but also acted as effective inhibitors towards polyT templates, meeting the aim of developing bio-computing with cost-effective and operationally simple methods. In short, polyT-templated CuNPs, as promising fluorescent signal reporters, are successfully applied to fabricate advanced logic devices, which may present a potential path for future development of molecular computations.For the first time by integrating fluorescent polyT-templated CuNPs and SYBR Green I, a basic INHIBIT gate and four advanced logic circuits (2-to-1 encoder, 4-to-2 encoder, 1-to-2 decoder and 1-to-2 demultiplexer) have been conceptually realized under label-free and enzyme-free conditions. Taking advantage of the selective formation of CuNPs on ss-DNA, the implementation of these advanced logic devices were achieved without any usage of dye quenching groups or other nanomaterials like graphene oxide or AuNPs since polyA strands not only worked as an input but also acted as effective inhibitors towards polyT templates, meeting the aim of developing bio-computing with cost-effective and operationally simple methods. In short, polyT-templated CuNPs, as promising fluorescent signal reporters, are successfully applied to fabricate advanced logic devices, which may present a potential path for future development of molecular computations. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr04069a

Exploring Biomolecular Recognition by Modeling and Simulation

NASA Astrophysics Data System (ADS)

Wade, Rebecca

2007-12-01

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

What is bioinformatics? A proposed definition and overview of the field.

PubMed

Luscombe, N M; Greenbaum, D; Gerstein, M

2001-01-01

The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems. Our definition is as follows: Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Analyses in bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). Additional information includes the text of scientific papers and "relationship data" from metabolic pathways, taxonomy trees, and protein-protein interaction networks. Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. We survey some representative applications, such as finding homologues, designing drugs, and performing large-scale censuses. Additional information pertinent to the review is available over the web at http://bioinfo.mbb.yale.edu/what-is-it.

Avoiding Defect Nucleation during Equilibration in Molecular Dynamics Simulations with ReaxFF

DTIC Science & Technology

2015-04-01

respectively. All simulations are performed using the LAMMPS computer code.12 2 Fig. 1 a) Initial and b) final configurations of the molecular centers...Plimpton S. Fast parallel algorithms for short-range molecular dynamics. Comput J Phys. 1995;117:1–19. (Software available at http:// lammps .sandia.gov

Adiabatic quantum simulation of quantum chemistry.

PubMed

Babbush, Ryan; Love, Peter J; Aspuru-Guzik, Alán

2014-10-13

We show how to apply the quantum adiabatic algorithm directly to the quantum computation of molecular properties. We describe a procedure to map electronic structure Hamiltonians to 2-body qubit Hamiltonians with a small set of physically realizable couplings. By combining the Bravyi-Kitaev construction to map fermions to qubits with perturbative gadgets to reduce the Hamiltonian to 2-body, we obtain precision requirements on the coupling strengths and a number of ancilla qubits that scale polynomially in the problem size. Hence our mapping is efficient. The required set of controllable interactions includes only two types of interaction beyond the Ising interactions required to apply the quantum adiabatic algorithm to combinatorial optimization problems. Our mapping may also be of interest to chemists directly as it defines a dictionary from electronic structure to spin Hamiltonians with physical interactions.

The Distributed Diagonal Force Decomposition Method for Parallelizing Molecular Dynamics Simulations

PubMed Central

Boršnik, Urban; Miller, Benjamin T.; Brooks, Bernard R.; Janežič, Dušanka

2011-01-01

Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition methods, increasing the parallel efficiency. It also dynamically load-balances the processors' computational load throughout the simulation. The method is readily implemented in existing molecular dynamics codes and it has been incorporated into the CHARMM program, allowing its immediate use in conjunction with the many molecular dynamics simulation techniques that are already present in the program. We also present the design of the Force Decomposition Machine, a cluster of personal computers and networks that is tailored to running molecular dynamics simulations using the distributed diagonal force decomposition method. The design is expandable and provides various degrees of fault resilience. This approach is easily adaptable to computers with Graphics Processing Units because it is independent of the processor type being used. PMID:21793007

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

Computational Nanotechnology at NASA Ames Research Center, 1996

NASA Technical Reports Server (NTRS)

Globus, Al; Bailey, David; Langhoff, Steve; Pohorille, Andrew; Levit, Creon; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Some forms of nanotechnology appear to have enormous potential to improve aerospace and computer systems; computational nanotechnology, the design and simulation of programmable molecular machines, is crucial to progress. NASA Ames Research Center has begun a computational nanotechnology program including in-house work, external research grants, and grants of supercomputer time. Four goals have been established: (1) Simulate a hypothetical programmable molecular machine replicating itself and building other products. (2) Develop molecular manufacturing CAD (computer aided design) software and use it to design molecular manufacturing systems and products of aerospace interest, including computer components. (3) Characterize nanotechnologically accessible materials of aerospace interest. Such materials may have excellent strength and thermal properties. (4) Collaborate with experimentalists. Current in-house activities include: (1) Development of NanoDesign, software to design and simulate a nanotechnology based on functionalized fullerenes. Early work focuses on gears. (2) A design for high density atomically precise memory. (3) Design of nanotechnology systems based on biology. (4) Characterization of diamonoid mechanosynthetic pathways. (5) Studies of the laplacian of the electronic charge density to understand molecular structure and reactivity. (6) Studies of entropic effects during self-assembly. Characterization of properties of matter for clusters up to sizes exhibiting bulk properties. In addition, the NAS (NASA Advanced Supercomputing) supercomputer division sponsored a workshop on computational molecular nanotechnology on March 4-5, 1996 held at NASA Ames Research Center. Finally, collaborations with Bill Goddard at CalTech, Ralph Merkle at Xerox Parc, Don Brenner at NCSU (North Carolina State University), Tom McKendree at Hughes, and Todd Wipke at UCSC are underway.

Towards a molecular logic machine

NASA Astrophysics Data System (ADS)

Remacle, F.; Levine, R. D.

2001-06-01

Finite state logic machines can be realized by pump-probe spectroscopic experiments on an isolated molecule. The most elaborate setup, a Turing machine, can be programmed to carry out a specific computation. We argue that a molecule can be similarly programmed, and provide examples using two photon spectroscopies. The states of the molecule serve as the possible states of the head of the Turing machine and the physics of the problem determines the possible instructions of the program. The tape is written in an alphabet that allows the listing of the different pump and probe signals that are applied in a given experiment. Different experiments using the same set of molecular levels correspond to different tapes that can be read and processed by the same head and program. The analogy to a Turing machine is not a mechanical one and is not completely molecular because the tape is not part of the molecular machine. We therefore also discuss molecular finite state machines, such as sequential devices, for which the tape is not part of the machine. Nonmolecular tapes allow for quite long input sequences with a rich alphabet (at the level of 7 bits) and laser pulse shaping experiments provide concrete examples. Single molecule spectroscopies show that a single molecule can be repeatedly cycled through a logical operation.

Simple and exact approach to the electronic polarization effect on the solvation free energy: formulation for quantum-mechanical/molecular-mechanical system and its applications to aqueous solutions.

PubMed

Takahashi, Hideaki; Omi, Atsushi; Morita, Akihiro; Matubayasi, Nobuyuki

2012-06-07

We present a simple and exact numerical approach to compute the free energy contribution δμ in solvation due to the electron density polarization and fluctuation of a quantum-mechanical solute in the quantum-mechanical/molecular-mechanical (QM/MM) simulation combined with the theory of the energy representation (QM/MM-ER). Since the electron density fluctuation is responsible for the many-body QM-MM interactions, the standard version of the energy representation method cannot be applied directly. Instead of decomposing the QM-MM polarization energy into the pairwise additive and non-additive contributions, we take sum of the polarization energies in the QM-MM interaction and adopt it as a new energy coordinate for the method of energy representation. Then, it is demonstrated that the free energy δμ can be exactly formulated in terms of the energy distribution functions for the solution and reference systems with respect to this energy coordinate. The benchmark tests were performed to examine the numerical efficiency of the method with respect to the changes in the individual properties of the solvent and the solute. Explicitly, we computed the solvation free energy of a QM water molecule in ambient and supercritical water, and also the free-energy change associated with the isomerization reaction of glycine from neutral to zwitterionic structure in aqueous solution. In all the systems examined, it was demonstrated that the computed free energy δμ agrees with the experimental value, irrespective of the choice of the reference electron density of the QM solute. The present method was also applied to a prototype reaction of adenosine 5'-triphosphate hydrolysis where the effect of the electron density fluctuation is substantial due to the excess charge. It was demonstrated that the experimental free energy of the reaction has been accurately reproduced with the present approach.

Logic integration of mRNA signals by an RNAi-based molecular computer

PubMed Central

Xie, Zhen; Liu, Siyuan John; Bleris, Leonidas; Benenson, Yaakov

2010-01-01

Synthetic in vivo molecular ‘computers’ could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that ‘transduce’ mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi ‘computational’ module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting. PMID:20194121

Quantum ring-polymer contraction method: Including nuclear quantum effects at no additional computational cost in comparison to ab initio molecular dynamics

NASA Astrophysics Data System (ADS)

John, Christopher; Spura, Thomas; Habershon, Scott; Kühne, Thomas D.

2016-04-01

We present a simple and accurate computational method which facilitates ab initio path-integral molecular dynamics simulations, where the quantum-mechanical nature of the nuclei is explicitly taken into account, at essentially no additional computational cost in comparison to the corresponding calculation using classical nuclei. The predictive power of the proposed quantum ring-polymer contraction method is demonstrated by computing various static and dynamic properties of liquid water at ambient conditions using density functional theory. This development will enable routine inclusion of nuclear quantum effects in ab initio molecular dynamics simulations of condensed-phase systems.

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

PubMed

Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

2016-06-20

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field. Copyright © 2015 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

The activation strain model and molecular orbital theory

PubMed Central

Wolters, Lando P; Bickelhaupt, F Matthias

2015-01-01

The activation strain model is a powerful tool for understanding reactivity, or inertness, of molecular species. This is done by relating the relative energy of a molecular complex along the reaction energy profile to the structural rigidity of the reactants and the strength of their mutual interactions: ΔE(ζ) = ΔEstrain(ζ) + ΔEint(ζ). We provide a detailed discussion of the model, and elaborate on its strong connection with molecular orbital theory. Using these approaches, a causal relationship is revealed between the properties of the reactants and their reactivity, e.g., reaction barriers and plausible reaction mechanisms. This methodology may reveal intriguing parallels between completely different types of chemical transformations. Thus, the activation strain model constitutes a unifying framework that furthers the development of cross-disciplinary concepts throughout various fields of chemistry. We illustrate the activation strain model in action with selected examples from literature. These examples demonstrate how the methodology is applied to different research questions, how results are interpreted, and how insights into one chemical phenomenon can lead to an improved understanding of another, seemingly completely different chemical process. WIREs Comput Mol Sci 2015, 5:324–343. doi: 10.1002/wcms.1221 PMID:26753009

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

Computational study of molecular electrostatic potential, docking and dynamics simulations of gallic acid derivatives as ABL inhibitors.

PubMed

Raghi, K R; Sherin, D R; Saumya, M J; Arun, P S; Sobha, V N; Manojkumar, T K

2018-04-05

Chronic myeloid leukemia (CML), a hematological malignancy arises due to the spontaneous fusion of the BCR and ABL gene, resulting in a constitutively active tyrosine kinase (BCR-ABL). Pharmacological activity of Gallic acid and 1,3,4-Oxadiazole as potential inhibitors of ABL kinase has already been reported. Objective of this study is to evaluate the ABL kinase inhibitory activity of derivatives of Gallic acid fused with 1,3,4-Oxadiazole moieties. Attempts have been made to identify the key structural features responsible for drug likeness of the Gallic acid and the 1,3,4-Oxadiazole ring using molecular electrostatic potential maps (MESP). To investigate the inhibitory activity of Gallic acid derivatives towards the ABL receptor, we have applied molecular docking and molecular dynamics (MD) simulation approaches. A comparative study was performed using Bosutinib as the standard which is an approved CML drug acting on the same receptor. Furthermore, the novel compounds designed and reported here in were evaluated for ADME properties and the results indicate that they show acceptable pharmacokinetic properties. Accordingly these compounds are predicted to be drug like with low toxicity potential. Copyright © 2018 Elsevier Ltd. All rights reserved.

In vivo targeted peripheral nerve imaging with a nerve-specific nanoscale magnetic resonance probe.

PubMed

Zheng, Linfeng; Li, Kangan; Han, Yuedong; Wei, Wei; Zheng, Sujuan; Zhang, Guixiang

2014-11-01

Neuroimaging plays a pivotal role in clinical practice. Currently, computed tomography (CT), magnetic resonance imaging (MRI), ultrasonography, and positron emission tomography (PET) are applied in the clinical setting as neuroimaging modalities. There is no optimal imaging modality for clinical peripheral nerve imaging even though fluorescence/bioluminescence imaging has been used for preclinical studies on the nervous system. Some studies have shown that molecular and cellular MRI (MCMRI) can be used to visualize and image the cellular and molecular level of the nervous system. Other studies revealed that there are different pathological/molecular changes in the proximal and distal sites after peripheral nerve injury (PNI). Therefore, we hypothesized that in vivo peripheral nerve targets can be imaged using MCMRI with specific MRI probes. Specific probes should have higher penetrability for the blood-nerve barrier (BNB) in vivo. Here, a functional nanometre MRI probe that is based on nerve-specific proteins as targets, specifically, using a molecular antibody (mAb) fragment conjugated to iron nanoparticles as an MRI probe, was constructed for further study. The MRI probe allows for imaging the peripheral nerve targets in vivo. Copyright © 2014 Elsevier Ltd. All rights reserved.

QSAR Methods.

PubMed

Gini, Giuseppina

2016-01-01

In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

PubMed

Guerra, Concettina

2015-01-01

Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.

Molecular electronics: The technology of sixth generation computers

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

Jarvis, M.T.; Miller, R.K.

1987-01-01

In February 1986, Japan began the 6th Generation project. At the 1987 Economic Summit in Venice, Prime Minister Yashuhiro Makasone opened the project to world collaboration. A project director suggests that the 6th Generation ''may just be a turning point for human society.'' The major rationale for building molecular electronic devices is to achieve advances in computational densities and speeds. Proposed chromophore chains for molecular-scale chips, for example, could be spaced closer than today's silicone elements by a factor of almost 100. This book describes the research and proposed designs for molecular electronic devices and computers. It examines specific potentialmore » applications and the relationship to molecular electronics to silicon technology and presents the first published survey of experts on research issues, applications, and forecast of future developments and also includes market forecast. An interesting suggestion of the survey is that the chemical industry may become a significant factor in the computer industry as the sixth generation unfolds.« less

Structural biology computing: Lessons for the biomedical research sciences.

PubMed

Morin, Andrew; Sliz, Piotr

2013-11-01

The field of structural biology, whose aim is to elucidate the molecular and atomic structures of biological macromolecules, has long been at the forefront of biomedical sciences in adopting and developing computational research methods. Operating at the intersection between biophysics, biochemistry, and molecular biology, structural biology's growth into a foundational framework on which many concepts and findings of molecular biology are interpreted1 has depended largely on parallel advancements in computational tools and techniques. Without these computing advances, modern structural biology would likely have remained an exclusive pursuit practiced by few, and not become the widely practiced, foundational field it is today. As other areas of biomedical research increasingly embrace research computing techniques, the successes, failures and lessons of structural biology computing can serve as a useful guide to progress in other biomedically related research fields. Copyright © 2013 Wiley Periodicals, Inc.

Molecular Orbitals of NO, NO[superscript+], and NO[superscript-]: A Computational Quantum Chemistry Experiment

ERIC Educational Resources Information Center

Orenha, Renato P.; Galembeck, Sérgio E.

2014-01-01

This computational experiment presents qualitative molecular orbital (QMO) and computational quantum chemistry exercises of NO, NO[superscript+], and NO[superscript-]. Initially students explore several properties of the target molecules by Lewis diagrams and the QMO theory. Then, they compare qualitative conclusions with EHT and DFT calculations…

Computer-Based Semantic Network in Molecular Biology: A Demonstration.

ERIC Educational Resources Information Center

Callman, Joshua L.; And Others

This paper analyzes the hardware and software features that would be desirable in a computer-based semantic network system for representing biology knowledge. It then describes in detail a prototype network of molecular biology knowledge that has been developed using Filevision software and a Macintosh computer. The prototype contains about 100…

DNA-programmed dynamic assembly of quantum dots for molecular computation.

PubMed

He, Xuewen; Li, Zhi; Chen, Muzi; Ma, Nan

2014-12-22

Despite the widespread use of quantum dots (QDs) for biosensing and bioimaging, QD-based bio-interfaceable and reconfigurable molecular computing systems have not yet been realized. DNA-programmed dynamic assembly of multi-color QDs is presented for the construction of a new class of fluorescence resonance energy transfer (FRET)-based QD computing systems. A complete set of seven elementary logic gates (OR, AND, NOR, NAND, INH, XOR, XNOR) are realized using a series of binary and ternary QD complexes operated by strand displacement reactions. The integration of different logic gates into a half-adder circuit for molecular computation is also demonstrated. This strategy is quite versatile and straightforward for logical operations and would pave the way for QD-biocomputing-based intelligent molecular diagnostics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Adiabatic quantum computing with spin qubits hosted by molecules.

PubMed

Yamamoto, Satoru; Nakazawa, Shigeaki; Sugisaki, Kenji; Sato, Kazunobu; Toyota, Kazuo; Shiomi, Daisuke; Takui, Takeji

2015-01-28

A molecular spin quantum computer (MSQC) requires electron spin qubits, which pulse-based electron spin/magnetic resonance (ESR/MR) techniques can afford to manipulate for implementing quantum gate operations in open shell molecular entities. Importantly, nuclear spins, which are topologically connected, particularly in organic molecular spin systems, are client qubits, while electron spins play a role of bus qubits. Here, we introduce the implementation for an adiabatic quantum algorithm, suggesting the possible utilization of molecular spins with optimized spin structures for MSQCs. We exemplify the utilization of an adiabatic factorization problem of 21, compared with the corresponding nuclear magnetic resonance (NMR) case. Two molecular spins are selected: one is a molecular spin composed of three exchange-coupled electrons as electron-only qubits and the other an electron-bus qubit with two client nuclear spin qubits. Their electronic spin structures are well characterized in terms of the quantum mechanical behaviour in the spin Hamiltonian. The implementation of adiabatic quantum computing/computation (AQC) has, for the first time, been achieved by establishing ESR/MR pulse sequences for effective spin Hamiltonians in a fully controlled manner of spin manipulation. The conquered pulse sequences have been compared with the NMR experiments and shown much faster CPU times corresponding to the interaction strength between the spins. Significant differences are shown in rotational operations and pulse intervals for ESR/MR operations. As a result, we suggest the advantages and possible utilization of the time-evolution based AQC approach for molecular spin quantum computers and molecular spin quantum simulators underlain by sophisticated ESR/MR pulsed spin technology.

Introductory Molecular Orbital Theory: An Honors General Chemistry Computational Lab as Implemented Using Three-Dimensional Modeling Software

ERIC Educational Resources Information Center

Ruddick, Kristie R.; Parrill, Abby L.; Petersen, Richard L.

2012-01-01

In this study, a computational molecular orbital theory experiment was implemented in a first-semester honors general chemistry course. Students used the GAMESS (General Atomic and Molecular Electronic Structure System) quantum mechanical software (as implemented in ChemBio3D) to optimize the geometry for various small molecules. Extended Huckel…

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.

Femtosecond-laser induced dynamics of CO on Ru(0001): Deep insights from a hot-electron friction model including surface motion

NASA Astrophysics Data System (ADS)

Scholz, Robert; Floß, Gereon; Saalfrank, Peter; Füchsel, Gernot; Lončarić, Ivor; Juaristi, J. I.

2016-10-01

A Langevin model accounting for all six molecular degrees of freedom is applied to femtosecond-laser induced, hot-electron driven dynamics of Ru(0001)(2 ×2 ):CO. In our molecular dynamics with electronic friction approach, a recently developed potential energy surface based on gradient-corrected density functional theory accounting for van der Waals interactions is adopted. Electronic friction due to the coupling of molecular degrees of freedom to electron-hole pairs in the metal are included via a local density friction approximation, and surface phonons by a generalized Langevin oscillator model. The action of ultrashort laser pulses enters through a substrate-mediated, hot-electron mechanism via a time-dependent electronic temperature (derived from a two-temperature model), causing random forces acting on the molecule. The model is applied to laser induced lateral diffusion of CO on the surface, "hot adsorbate" formation, and laser induced desorption. Reaction probabilities are strongly enhanced compared to purely thermal processes, both for diffusion and desorption. Reaction yields depend in a characteristic (nonlinear) fashion on the applied laser fluence, as well as branching ratios for various reaction channels. Computed two-pulse correlation traces for desorption and other indicators suggest that aside from electron-hole pairs, phonons play a non-negligible role for laser induced dynamics in this system, acting on a surprisingly short time scale. Our simulations on precomputed potentials allow for good statistics and the treatment of long-time dynamics (300 ps), giving insight into this system which hitherto has not been reached. We find generally good agreement with experimental data where available and make predictions in addition. A recently proposed laser induced population of physisorbed precursor states could not be observed with the present low-coverage model.

RPYFMM: Parallel adaptive fast multipole method for Rotne-Prager-Yamakawa tensor in biomolecular hydrodynamics simulations

NASA Astrophysics Data System (ADS)

Guan, W.; Cheng, X.; Huang, J.; Huber, G.; Li, W.; McCammon, J. A.; Zhang, B.

2018-06-01

RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne-Prager-Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.

Yoink: An interaction-based partitioning API.

PubMed

Zheng, Min; Waller, Mark P

2018-05-15

Herein, we describe the implementation details of our interaction-based partitioning API (application programming interface) called Yoink for QM/MM modeling and fragment-based quantum chemistry studies. Interactions are detected by computing density descriptors such as reduced density gradient, density overlap regions indicator, and single exponential decay detector. Only molecules having an interaction with a user-definable QM core are added to the QM region of a hybrid QM/MM calculation. Moreover, a set of molecule pairs having density-based interactions within a molecular system can be computed in Yoink, and an interaction graph can then be constructed. Standard graph clustering methods can then be applied to construct fragments for further quantum chemical calculations. The Yoink API is licensed under Apache 2.0 and can be accessed via yoink.wallerlab.org. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

An omics perspective to the molecular mechanisms of anticancer metallo-drugs in the computational microscope era.

PubMed

Spinello, Angelo; Magistrato, Alessandra

2017-08-01

Metallo-drugs have attracted enormous interest for cancer treatment. The achievements of this drug-type are summarized by the success story of cisplatin. That being said, there have been many drawbacks with its clinical use, which prompted decades worth of research efforts to move towards safer and more effective agents, either containing platinum or different metals. Areas covered: In this review, the authors provide an atomistic picture of the molecular mechanisms involving selected metallo-drugs from structural and molecular simulation studies. They also provide an omics perspective, pointing out many unsettled aspects of the most relevant families of metallo-drugs at an epigenetic level. Expert opinion: Molecular simulations are able to provide detailed information at atomistic and temporal (ps) resolutions that are rarely accessible to experiments. The increasing accuracy of computational methods and the growing performance of computational platforms, allow us to mirror wet lab experiments in silico. Consequently, the molecular mechanisms of drugs action/failure can be directly viewed on a computer screen, like a 'computational microscope', allowing us to harness this knowledge for the design of the next-generation of metallo-drugs.

Molecular dynamics simulations of thermally activated edge dislocation unpinning from voids in α -Fe

NASA Astrophysics Data System (ADS)

Byggmästar, J.; Granberg, F.; Nordlund, K.

2017-10-01

In this study, thermal unpinning of edge dislocations from voids in α -Fe is investigated by means of molecular dynamics simulations. The activation energy as a function of shear stress and temperature is systematically determined. Simulations with a constant applied stress are compared with dynamic simulations with a constant strain rate. We found that a constant applied stress results in a temperature-dependent activation energy. The temperature dependence is attributed to the elastic softening of iron. If the stress is normalized with the softening of the specific shear modulus, the activation energy is shown to be temperature-independent. From the dynamic simulations, the activation energy as a function of critical shear stress was determined using previously developed methods. The results from the dynamic simulations are in good agreement with the constant stress simulations, after the normalization. This indicates that the computationally more efficient dynamic method can be used to obtain the activation energy as a function of stress and temperature. The obtained relation between stress, temperature, and activation energy can be used to introduce a stochastic unpinning event in larger-scale simulation methods, such as discrete dislocation dynamics.

Integrated Multiscale Modeling of Molecular Computing Devices

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

Gregory Beylkin

2012-03-23

Significant advances were made on all objectives of the research program. We have developed fast multiresolution methods for performing electronic structure calculations with emphasis on constructing efficient representations of functions and operators. We extended our approach to problems of scattering in solids, i.e. constructing fast algorithms for computing above the Fermi energy level. Part of the work was done in collaboration with Robert Harrison and George Fann at ORNL. Specific results (in part supported by this grant) are listed here and are described in greater detail. (1) We have implemented a fast algorithm to apply the Green's function for themore » free space (oscillatory) Helmholtz kernel. The algorithm maintains its speed and accuracy when the kernel is applied to functions with singularities. (2) We have developed a fast algorithm for applying periodic and quasi-periodic, oscillatory Green's functions and those with boundary conditions on simple domains. Importantly, the algorithm maintains its speed and accuracy when applied to functions with singularities. (3) We have developed a fast algorithm for obtaining and applying multiresolution representations of periodic and quasi-periodic Green's functions and Green's functions with boundary conditions on simple domains. (4) We have implemented modifications to improve the speed of adaptive multiresolution algorithms for applying operators which are represented via a Gaussian expansion. (5) We have constructed new nearly optimal quadratures for the sphere that are invariant under the icosahedral rotation group. (6) We obtained new results on approximation of functions by exponential sums and/or rational functions, one of the key methods that allows us to construct separated representations for Green's functions. (7) We developed a new fast and accurate reduction algorithm for obtaining optimal approximation of functions by exponential sums and/or their rational representations.« less

Mutual diffusion coefficients of heptane isomers in nitrogen: A molecular dynamics study

NASA Astrophysics Data System (ADS)

Chae, Kyungchan; Violi, Angela

2011-01-01

The accurate knowledge of transport properties of pure and mixture fluids is essential for the design of various chemical and mechanical systems that include fluxes of mass, momentum, and energy. In this study we determine the mutual diffusion coefficients of mixtures composed of heptane isomers and nitrogen using molecular dynamics (MD) simulations with fully atomistic intermolecular potential parameters, in conjunction with the Green-Kubo formula. The computed results were compared with the values obtained using the Chapman-Enskog (C-E) equation with Lennard-Jones (LJ) potential parameters derived from the correlations of state values: MD simulations predict a maximum difference of 6% among isomers while the C-E equation presents that of 3% in the mutual diffusion coefficients in the temperature range 500-1000 K. The comparison of two approaches implies that the corresponding state principle can be applied to the models, which are only weakly affected by the anisotropy of the interaction potentials and the large uncertainty will be included in its application for complex polyatomic molecules. The MD simulations successfully address the pure effects of molecular structure among isomers on mutual diffusion coefficients by revealing that the differences of the total mutual diffusion coefficients for the six mixtures are caused mainly by heptane isomers. The cross interaction potential parameters, collision diameter σ _{12}, and potential energy well depth \\varepsilon _{12} of heptane isomers and nitrogen mixtures were also computed from the mutual diffusion coefficients.

Study of Li atom diffusion in amorphous Li3PO4 with neural network potential

NASA Astrophysics Data System (ADS)

Li, Wenwen; Ando, Yasunobu; Minamitani, Emi; Watanabe, Satoshi

2017-12-01

To clarify atomic diffusion in amorphous materials, which is important in novel information and energy devices, theoretical methods having both reliability and computational speed are eagerly anticipated. In the present study, we applied neural network (NN) potentials, a recently developed machine learning technique, to the study of atom diffusion in amorphous materials, using Li3PO4 as a benchmark material. The NN potential was used together with the nudged elastic band, kinetic Monte Carlo, and molecular dynamics methods to characterize Li vacancy diffusion behavior in the amorphous Li3PO4 model. By comparing these results with corresponding DFT calculations, we found that the average error of the NN potential is 0.048 eV in calculating energy barriers of diffusion paths, and 0.041 eV in diffusion activation energy. Moreover, the diffusion coefficients obtained from molecular dynamics are always consistent with those from ab initio molecular dynamics simulation, while the computation speed of the NN potential is 3-4 orders of magnitude faster than DFT. Lastly, the structure of amorphous Li3PO4 and the ion transport properties in it were studied with the NN potential using a large supercell model containing more than 1000 atoms. The formation of P2O7 units was observed, which is consistent with the experimental characterization. The Li diffusion activation energy was estimated to be 0.55 eV, which agrees well with the experimental measurements.

Molecular properties of excited electronic state: Formalism, implementation, and applications of analytical second energy derivatives within the framework of the time-dependent density functional theory/molecular mechanics

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

Zeng, Qiao; Liang, WanZhen, E-mail: liangwz@xmu.edu.cn; Liu, Jie

2014-05-14

This work extends our previous works [J. Liu and W. Z. Liang, J. Chem. Phys. 135, 014113 (2011); J. Liu and W. Z. Liang, J. Chem. Phys. 135, 184111 (2011)] on analytical excited-state energy Hessian within the framework of time-dependent density functional theory (TDDFT) to couple with molecular mechanics (MM). The formalism, implementation, and applications of analytical first and second energy derivatives of TDDFT/MM excited state with respect to the nuclear and electric perturbations are presented. Their performances are demonstrated by the calculations of adiabatic excitation energies, and excited-state geometries, harmonic vibrational frequencies, and infrared intensities for a number ofmore » benchmark systems. The consistent results with the full quantum mechanical method and other hybrid theoretical methods indicate the reliability of the current numerical implementation of developed algorithms. The computational accuracy and efficiency of the current analytical approach are also checked and the computational efficient strategies are suggested to speed up the calculations of complex systems with many MM degrees of freedom. Finally, we apply the current analytical approach in TDDFT/MM to a realistic system, a red fluorescent protein chromophore together with part of its nearby protein matrix. The calculated results indicate that the rearrangement of the hydrogen bond interactions between the chromophore and the protein matrix is responsible for the large Stokes shift.« less

Multiscale Quantum Mechanics/Molecular Mechanics Simulations with Neural Networks.

PubMed

Shen, Lin; Wu, Jingheng; Yang, Weitao

2016-10-11

Molecular dynamics simulation with multiscale quantum mechanics/molecular mechanics (QM/MM) methods is a very powerful tool for understanding the mechanism of chemical and biological processes in solution or enzymes. However, its computational cost can be too high for many biochemical systems because of the large number of ab initio QM calculations. Semiempirical QM/MM simulations have much higher efficiency. Its accuracy can be improved with a correction to reach the ab initio QM/MM level. The computational cost on the ab initio calculation for the correction determines the efficiency. In this paper we developed a neural network method for QM/MM calculation as an extension of the neural-network representation reported by Behler and Parrinello. With this approach, the potential energy of any configuration along the reaction path for a given QM/MM system can be predicted at the ab initio QM/MM level based on the semiempirical QM/MM simulations. We further applied this method to three reactions in water to calculate the free energy changes. The free-energy profile obtained from the semiempirical QM/MM simulation is corrected to the ab initio QM/MM level with the potential energies predicted with the constructed neural network. The results are in excellent accordance with the reference data that are obtained from the ab initio QM/MM molecular dynamics simulation or corrected with direct ab initio QM/MM potential energies. Compared with the correction using direct ab initio QM/MM potential energies, our method shows a speed-up of 1 or 2 orders of magnitude. It demonstrates that the neural network method combined with the semiempirical QM/MM calculation can be an efficient and reliable strategy for chemical reaction simulations.

Single-molecule force-conductance spectroscopy of hydrogen-bonded complexes

NASA Astrophysics Data System (ADS)

Pirrotta, Alessandro; De Vico, Luca; Solomon, Gemma C.; Franco, Ignacio

2017-03-01

The emerging ability to study physical properties at the single-molecule limit highlights the disparity between what is observable in an ensemble of molecules and the heterogeneous contributions of its constituent parts. A particularly convenient platform for single-molecule studies are molecular junctions where forces and voltages can be applied to individual molecules, giving access to a series of electromechanical observables that can form the basis of highly discriminating multidimensional single-molecule spectroscopies. Here, we computationally examine the ability of force and conductance to inform about molecular recognition events at the single-molecule limit. For this, we consider the force-conductance characteristics of a prototypical class of hydrogen bonded bimolecular complexes sandwiched between gold electrodes. The complexes consist of derivatives of a barbituric acid and a Hamilton receptor that can form up to six simultaneous hydrogen bonds. The simulations combine classical molecular dynamics of the mechanical deformation of the junction with non-equilibrium Green's function computations of the electronic transport. As shown, in these complexes hydrogen bonds mediate transport either by directly participating as a possible transport pathway or by stabilizing molecular conformations with enhanced conductance properties. Further, we observe that force-conductance correlations can be very sensitive to small changes in the chemical structure of the complexes and provide detailed information about the behavior of single molecules that cannot be gleaned from either measurement alone. In fact, there are regions during the elongation that are only mechanically active, others that are only conductance active, and regions where both force and conductance changes as the complex is mechanically manipulated. The implication is that force and conductance provide complementary information about the evolution of molecules in junctions that can be used to interrogate basic structure-transport relations at the single-molecule limit.

The appropriateness of density-functional theory for the calculation of molecular electronics properties.

PubMed

Reimers, Jeffrey R; Cai, Zheng-Li; Bilić, Ante; Hush, Noel S

2003-12-01

As molecular electronics advances, efficient and reliable computation procedures are required for the simulation of the atomic structures of actual devices, as well as for the prediction of their electronic properties. Density-functional theory (DFT) has had widespread success throughout chemistry and solid-state physics, and it offers the possibility of fulfilling these roles. In its modern form it is an empirically parameterized approach that cannot be extended toward exact solutions in a prescribed way, ab initio. Thus, it is essential that the weaknesses of the method be identified and likely shortcomings anticipated in advance. We consider four known systematic failures of modern DFT: dispersion, charge transfer, extended pi conjugation, and bond cleavage. Their ramifications for molecular electronics applications are outlined and we suggest that great care is required when using modern DFT to partition charge flow across electrode-molecule junctions, screen applied electric fields, position molecular orbitals with respect to electrode Fermi energies, and in evaluating the distance dependence of through-molecule conductivity. The causes of these difficulties are traced to errors inherent in the types of density functionals in common use, associated with their inability to treat very long-range electron correlation effects. Heuristic enhancements of modern DFT designed to eliminate individual problems are outlined, as are three new schemes that each represent significant departures from modern DFT implementations designed to provide a priori improvements in at least one and possible all problem areas. Finally, fully semiempirical schemes based on both Hartree-Fock and Kohn-Sham theory are described that, in the short term, offer the means to avoid the inherent problems of modern DFT and, in the long term, offer competitive accuracy at dramatically reduced computational costs.

Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data

PubMed Central

Wang, Yongcui; Chen, Shilong; Deng, Naiyang; Wang, Yong

2013-01-01

Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems. PMID:24244318

Students' use of atomic and molecular models in learning chemistry

NASA Astrophysics Data System (ADS)

O'Connor, Eileen Ann

1997-09-01

The objective of this study was to investigate the development of introductory college chemistry students' use of atomic and molecular models to explain physical and chemical phenomena. The study was conducted during the first semester of the course at a University and College II. Public institution (Carnegie Commission of Higher Education, 1973). Students' use of models was observed during one-on-one interviews conducted over the course of the semester. The approach to introductory chemistry emphasized models. Students were exposed to over two-hundred and fifty atomic and molecular models during lectures, were assigned text readings that used over a thousand models, and worked interactively with dozens of models on the computer. These models illustrated various features of the spatial organization of valence electrons and nuclei in atoms and molecules. Despite extensive exposure to models in lectures, in textbook, and in computer-based activities, the students in the study based their explanation in large part on a simple Bohr model (electrons arranged in concentric circles around the nuclei)--a model that had not been introduced in the course. Students used visual information from their models to construct their explanation, while overlooking inter-atomic and intra-molecular forces which are not represented explicitly in the models. In addition, students often explained phenomena by adding separate information about the topic without either integrating or logically relating this information into a cohesive explanation. The results of the study demonstrate that despite the extensive use of models in chemistry instruction, students do not necessarily apply them appropriately in explaining chemical and physical phenomena. The results of this study suggest that for the power of models as aids to learning to be more fully realized, chemistry professors must give more attention to the selection, use, integration, and limitations of models in their instruction.

Computational and Experimental Investigations of the Molecular Scale Structure and Dynamics of Gologically Important Fluids and Mineral-Fluid Interfaces

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

Bowers, Geoffrey

United States Department of Energy grant DE-FG02-10ER16128, “Computational and Spectroscopic Investigations of the Molecular Scale Structure and Dynamics of Geologically Important Fluids and Mineral-Fluid Interfaces” (Geoffrey M. Bowers, P.I.) focused on developing a molecular-scale understanding of processes that occur in fluids and at solid-fluid interfaces using the combination of spectroscopic, microscopic, and diffraction studies with molecular dynamics computer modeling. The work is intimately tied to the twin proposal at Michigan State University (DOE DE-FG02-08ER15929; same title: R. James Kirkpatrick, P.I. and A. Ozgur Yazaydin, co-P.I.).

Potent New Small-Molecule Inhibitor of Botulinum Neurotoxin Serotype A Endopeptidase Developed by Synthesis-Based Computer-Aided Molecular Design

DTIC Science & Technology

2009-11-01

dynamics of the complex predicted by multiple molecular dynamics simulations , and discuss further structural optimization to achieve better in vivo efficacy...complex with BoNTAe and the dynamics of the complex predicted by multiple molecular dynamics simulations (MMDSs). On the basis of the 3D model, we discuss...is unlimited whereas AHP exhibited 54% inhibition under the same conditions (Table 1). Computer Simulation Twenty different molecular dynamics

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.

Spintronics: The molecular way

NASA Astrophysics Data System (ADS)

Cornia, Andrea; Seneor, Pierre

2017-05-01

Molecular spintronics is an interdisciplinary field at the interface between organic spintronics, molecular magnetism, molecular electronics and quantum computing, which is advancing fast and promises large technological payoffs.

Application of the thermorheologically complex nonlinear Adam-Gibbs model for the glass transition to molecular motion in hydrated proteins.

PubMed

Hodge, Ian M

2006-08-01

The nonlinear thermorheologically complex Adam Gibbs (extended "Scherer-Hodge") model for the glass transition is applied to enthalpy relaxation data reported by Sartor, Mayer, and Johari for hydrated methemoglobin. A sensible range in values for the average localized activation energy is obtained (100-200 kJ mol(-1)). The standard deviation in the inferred Gaussian distribution of activation energies, computed from the reported KWW beta-parameter, is approximately 30% of the average, consistent with the suggestion that some relaxation processes in hydrated proteins have exceptionally low activation energies.

Linear and quadratic static response functions and structure functions in Yukawa liquids.

PubMed

Magyar, Péter; Donkó, Zoltán; Kalman, Gabor J; Golden, Kenneth I

2014-08-01

We compute linear and quadratic static density response functions of three-dimensional Yukawa liquids by applying an external perturbation potential in molecular dynamics simulations. The response functions are also obtained from the equilibrium fluctuations (static structure factors) in the system via the fluctuation-dissipation theorems. The good agreement of the quadratic response functions, obtained in the two different ways, confirms the quadratic fluctuation-dissipation theorem. We also find that the three-point structure function may be factorizable into two-point structure functions, leading to a cluster representation of the equilibrium triplet correlation function.

Precise calculation of the local pressure tensor in Cartesian and spherical coordinates in LAMMPS

NASA Astrophysics Data System (ADS)

Nakamura, Takenobu; Kawamoto, Shuhei; Shinoda, Wataru

2015-05-01

An accurate and efficient algorithm for calculating the 3D pressure field has been developed and implemented in the open-source molecular dynamics package, LAMMPS. Additionally, an algorithm to compute the pressure profile along the radial direction in spherical coordinates has also been implemented. The latter is particularly useful for systems showing a spherical symmetry such as micelles and vesicles. These methods yield precise pressure fields based on the Irving-Kirkwood contour integration and are particularly useful for biomolecular force fields. The present methods are applied to several systems including a buckled membrane and a vesicle.

Open Source Molecular Modeling

PubMed Central

Pirhadi, Somayeh; Sunseri, Jocelyn; Koes, David Ryan

2016-01-01

The success of molecular modeling and computational chemistry efforts are, by definition, dependent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. PMID:27631126

Accessible high-throughput virtual screening molecular docking software for students and educators.

PubMed

Jacob, Reed B; Andersen, Tim; McDougal, Owen M

2012-05-01

We survey low cost high-throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms.

Interactive Visualization of Infrared Spectral Data: Synergy of Computation, Visualization, and Experiment for Learning Spectroscopy

NASA Astrophysics Data System (ADS)

Lahti, Paul M.; Motyka, Eric J.; Lancashire, Robert J.

2000-05-01

A straightforward procedure is described to combine computation of molecular vibrational modes using commonly available molecular modeling programs with visualization of the modes using advanced features of the MDL Information Systems Inc. Chime World Wide Web browser plug-in. Minor editing of experimental spectra that are stored in the JCAMP-DX format allows linkage of IR spectral frequency ranges to Chime molecular display windows. The spectra and animation files can be combined by Hypertext Markup Language programming to allow interactive linkage between experimental spectra and computationally generated vibrational displays. Both the spectra and the molecular displays can be interactively manipulated to allow the user maximum control of the objects being viewed. This procedure should be very valuable not only for aiding students through visual linkage of spectra and various vibrational animations, but also by assisting them in learning the advantages and limitations of computational chemistry by comparison to experiment.

Nanoscale Bio-engineering Solutions for Space Exploration: The Nanopore Sequencer

NASA Technical Reports Server (NTRS)

Stolc, Viktor; Cozmuta, Ioana

2004-01-01

Characterization of biological systems at the molecular level and extraction of essential information for nano-engineering design to guide the nano-fabrication of solid-state sensors and molecular identification devices is a computational challenge. The alpha hemolysin protein ion channel is used as a model system for structural analysis of nucleic acids like DNA. Applied voltage draws a DNA strand and surrounding ionic solution through the biological nanopore. The subunits in the DNA strand block ion flow by differing amounts. Atomistic scale simulations are employed using NASA supercomputers to study DNA translocation, with the aim to enhance single DNA subunit identification. Compared to protein channels, solid-state nanopores offer a better temporal control of the translocation of DNA and the possibility to easily tune its chemistry to increase the signal resolution. Potential applications for NASA missions, besides real-time genome sequencing include astronaut health, life detection and decoding of various genomes.

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

Calculation and Visualization of Atomistic Mechanical Stresses in Nanomaterials and Biomolecules

PubMed Central

Gilson, Michael K.

2014-01-01

Many biomolecules have machine-like functions, and accordingly are discussed in terms of mechanical properties like force and motion. However, the concept of stress, a mechanical property that is of fundamental importance in the study of macroscopic mechanics, is not commonly applied in the biomolecular context. We anticipate that microscopical stress analyses of biomolecules and nanomaterials will provide useful mechanistic insights and help guide molecular design. To enable such applications, we have developed Calculator of Atomistic Mechanical Stress (CAMS), an open-source software package for computing atomic resolution stresses from molecular dynamics (MD) simulations. The software also enables decomposition of stress into contributions from bonded, nonbonded and Generalized Born potential terms. CAMS reads GROMACS topology and trajectory files, which are easily generated from AMBER files as well; and time-varying stresses may be animated and visualized in the VMD viewer. Here, we review relevant theory and present illustrative applications. PMID:25503996

Cine: Line excitation by infrared fluorescence in cometary atmospheres

NASA Astrophysics Data System (ADS)

de Val-Borro, Miguel; Cordiner, Martin A.; Milam, Stefanie N.; Charnley, Steven B.

2017-03-01

CINE is a Python module for calculating infrared pumping efficiencies that can be applied to the most common molecules found in cometary comae such as water, hydrogen cyanide or methanol. Excitation by solar radiation of vibrational bands followed by radiative decay to the ground vibrational state is one of the main mechanisms for molecular excitation in comets. This code calculates the effective pumping rates for rotational levels in the ground vibrational state scaled by the heliocentric distance of the comet. Line transitions are queried from the latest version of the HITRAN spectroscopic repository using the astroquery affiliated package of astropy. Molecular data are obtained from the LAMDA database. These coefficients are useful for modeling rotational emission lines observed in cometary spectra at sub-millimeter wavelengths. Combined with computational methods to solve the radiative transfer equations based, e.g., on the Monte Carlo algorithm, this model can retrieve production rates and rotational temperatures from the observed emission spectrum.

Nanoscale Bioengineering Solutions for Space Exploration the Nanopore Sequencer

NASA Technical Reports Server (NTRS)

Ioana, Cozmuta; Viktor, Stoic

2005-01-01

Characterization of biological systems at the molecular level and extraction of essential information for nano-engineering design to guide the nano-fabrication of solid-state sensors and molecular identification devices is a computational challenge. The alpha hemolysin protein ion channel is used as a model system for structural analysis of nucleic acids like DNA. Applied voltage draws a DNA strand and surrounding ionic solution through the biological nanopore. The subunits in the DNA strand block ion flow by differing amounts. Atomistic scale simulations are employed using NASA supercomputers to study DNA translocation. with the aim to enhance single DNA subunit identification. Compared to protein channels, solid-state nanopores offer a better temporal control of the translocation of DNA and the possibility to easily tune its chemistry to increase the signal resolution. Potential applications for NASA missions, besides real-time genome sequencing include astronaut health, life detection and decoding of various genomes. http://phenomrph.arc.nasa.gov/index.php

The solution of radiative transfer problems in molecular bands without the LTE assumption by accelerated lambda iteration methods

NASA Technical Reports Server (NTRS)

Kutepov, A. A.; Kunze, D.; Hummer, D. G.; Rybicki, G. B.

1991-01-01

An iterative method based on the use of approximate transfer operators, which was designed initially to solve multilevel NLTE line formation problems in stellar atmospheres, is adapted and applied to the solution of the NLTE molecular band radiative transfer in planetary atmospheres. The matrices to be constructed and inverted are much smaller than those used in the traditional Curtis matrix technique, which makes possible the treatment of more realistic problems using relatively small computers. This technique converges much more rapidly than straightforward iteration between the transfer equation and the equations of statistical equilibrium. A test application of this new technique to the solution of NLTE radiative transfer problems for optically thick and thin bands (the 4.3 micron CO2 band in the Venusian atmosphere and the 4.7 and 2.3 micron CO bands in the earth's atmosphere) is described.

Conception and development of the Second Life® Embryo Physics Course.

PubMed

Gordon, Richard

2013-06-01

The study of embryos with the tools and mindset of physics, started by Wilhelm His in the 1880s, has resumed after a hiatus of a century. The Embryo Physics Course convenes online allowing interested researchers and students, who are scattered around the world, to gather weekly in one place, the virtual world of Second Life®. It attracts people from a wide variety of disciplines and walks of life: applied mathematics, artificial life, bioengineering, biophysics, cancer biology, cellular automata, civil engineering, computer science, embryology, electrical engineering, evolution, finite element methods, history of biology, human genetics, mathematics, molecular developmental biology, molecular biology, nanotechnology, philosophy of biology, phycology, physics, self-reproducing systems, stem cells, tensegrity structures, theoretical biology, and tissue engineering. Now in its fifth year, the Embryo Physics Course provides a focus for research on the central question of how an embryo builds itself.

Quantitative structure-activity relationships of selective antagonists of glucagon receptor using QuaSAR descriptors.

PubMed

Manoj Kumar, Palanivelu; Karthikeyan, Chandrabose; Hari Narayana Moorthy, Narayana Subbiah; Trivedi, Piyush

2006-11-01

In the present paper, quantitative structure activity relationship (QSAR) approach was applied to understand the affinity and selectivity of a novel series of triaryl imidazole derivatives towards glucagon receptor. Statistically significant and highly predictive QSARs were derived for glucagon receptor inhibition by triaryl imidazoles using QuaSAR descriptors of molecular operating environment (MOE) employing computer-assisted multiple regression procedure. The generated QSAR models revealed that factors related to hydrophobicity, molecular shape and geometry predominantly influences glucagon receptor binding affinity of the triaryl imidazoles indicating the relevance of shape specific steric interactions between the molecule and the receptor. Further, QSAR models formulated for selective inhibition of glucagon receptor over p38 mitogen activated protein (MAP) kinase of the compounds in the series highlights that the same structural features, which influence the glucagon receptor affinity, also contribute to their selective inhibition.