Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment.

PubMed

Minovski, Nikola; Perdih, Andrej; Solmajer, Tom

2012-05-01

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.

Using next generation transcriptome sequencing to predict an ectomycorrhizal metablome.

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

Larsen, P. E.; Sreedasyam, A.; Trivedi, G

Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models usingmore » a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. The generated model of mycorrhizal metabolome predicts that the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose. The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems.« less

Coarse-Grained Structural Modeling of Molecular Motors Using Multibody Dynamics

PubMed Central

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

2010-01-01

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

Coarse-Grained Lattice Model Simulations of Sequence-Structure Fitness of a Ribosome-Inactivating Protein

DTIC Science & Technology

2007-11-05

limits of what is considered practical when applying all-atom molecular - dynamics simulation methods. Lattice models provide computationally robust...of expectation values from the density of states. All-atom molecular - dynamics simulations provide the most rigorous sampling method to generate con... molecular - dynamics simulations of protein folding,6–9 reported studies of computing a heat capacity or other calorimetric observables have been limited to

Introductory Biology Students' Conceptual Models and Explanations of the Origin of Variation

ERIC Educational Resources Information Center

Bray Speth, Elena; Shaw, Neil; Momsen, Jennifer; Reinagel, Adam; Le, Paul; Taqieddin, Ranya; Long, Tammy

2014-01-01

Mutation is the key molecular mechanism generating phenotypic variation, which is the basis for evolution. In an introductory biology course, we used a model-based pedagogy that enabled students to integrate their understanding of genetics and evolution within multiple case studies. We used student-generated conceptual models to assess…

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

PubMed

Pothoczki, Szilvia; Temleitner, László; Pusztai, László

2014-02-07

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

Applying Contamination Modelling to Spacecraft Propulsion Systems Designs and Operations

NASA Technical Reports Server (NTRS)

Chen, Philip T.; Thomson, Shaun; Woronowicz, Michael S.

2000-01-01

Molecular and particulate contaminants generated from the operations of a propulsion system may impinge on spacecraft critical surfaces. Plume depositions or clouds may hinder the spacecraft and instruments from performing normal operations. Firing thrusters will generate both molecular and particulate contaminants. How to minimize the contamination impact from the plume becomes very critical for a successful mission. The resulting effect from either molecular or particulate contamination of the thruster firing is very distinct. This paper will discuss the interconnection between the functions of spacecraft contamination modeling and propulsion system implementation. The paper will address an innovative contamination engineering approach implemented from the spacecraft concept design, manufacturing, integration and test (I&T), launch, to on- orbit operations. This paper will also summarize the implementation on several successful missions. Despite other contamination sources, only molecular contamination will be considered here.

Nanoscale inhomogeneity and photoacid generation dynamics in extreme ultraviolet resist materials

NASA Astrophysics Data System (ADS)

Wu, Ping-Jui; Wang, Yu-Fu; Chen, Wei-Chi; Wang, Chien-Wei; Cheng, Joy; Chang, Vencent; Chang, Ching-Yu; Lin, John; Cheng, Yuan-Chung

2018-03-01

The development of extreme ultraviolet (EUV) lithography towards the 22 nm node and beyond depends critically on the availability of resist materials that meet stringent control requirements in resolution, line edge roughness, and sensitivity. However, the molecular mechanisms that govern the structure-function relationships in current EUV resist systems are not well understood. In particular, the nanoscale structures of the polymer base and the distributions of photoacid generators (PAGs) should play a critical roles in the performance of a resist system, yet currently available models for photochemical reactions in EUV resist systems are exclusively based on homogeneous bulk models that ignore molecular-level details of solid resist films. In this work, we investigate how microscopic molecular organizations in EUV resist affect photoacid generations in a bottom-up approach that describes structure-dependent electron-transfer dynamics in a solid film model. To this end, molecular dynamics simulations and stimulated annealing are used to obtain structures of a large simulation box containing poly(4-hydroxystyrene) (PHS) base polymers and triphenylsulfonium based PAGs. Our calculations reveal that ion-pair interactions govern the microscopic distributions of the polymer base and PAG molecules, resulting in a highly inhomogeneous system with nonuniform nanoscale chemical domains. Furthermore, the theoretical structures were used in combination of quantum chemical calculations and the Marcus theory to evaluate electron transfer rates between molecular sites, and then kinetic Monte Carlo simulations were carried out to model electron transfer dynamics with molecular structure details taken into consideration. As a result, the portion of thermalized electrons that are absorbed by the PAGs and the nanoscale spatial distribution of generated acids can be estimated. Our data reveal that the nanoscale inhomogeneous distributions of base polymers and PAGs strongly affect the electron transfer and the performance of the resist system. The implications to the performances of EUV resists and key engineering requirements for improved resist systems will also be discussed in this work. Our results shed light on the fundamental structure dependence of photoacid generation and the control of the nanoscale structures as well as base polymer-PAG interactions in EVU resist systems, and we expect these knowledge will be useful for the future development of improved EUV resist systems.

Of truth and pathways: chasing bits of information through myriads of articles.

PubMed

Krauthammer, Michael; Kra, Pauline; Iossifov, Ivan; Gomez, Shawn M; Hripcsak, George; Hatzivassiloglou, Vasileios; Friedman, Carol; Rzhetsky, Andrey

2002-01-01

Knowledge on interactions between molecules in living cells is indispensable for theoretical analysis and practical applications in modern genomics and molecular biology. Building such networks relies on the assumption that the correct molecular interactions are known or can be identified by reading a few research articles. However, this assumption does not necessarily hold, as truth is rather an emerging property based on many potentially conflicting facts. This paper explores the processes of knowledge generation and publishing in the molecular biology literature using modelling and analysis of real molecular interaction data. The data analysed in this article were automatically extracted from 50000 research articles in molecular biology using a computer system called GeneWays containing a natural language processing module. The paper indicates that truthfulness of statements is associated in the minds of scientists with the relative importance (connectedness) of substances under study, revealing a potential selection bias in the reporting of research results. Aiming at understanding the statistical properties of the life cycle of biological facts reported in research articles, we formulate a stochastic model describing generation and propagation of knowledge about molecular interactions through scientific publications. We hope that in the future such a model can be useful for automatically producing consensus views of molecular interaction data.

De Novo Design of Bioactive Small Molecules by Artificial Intelligence

PubMed Central

Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca

2018-01-01

Abstract Generative artificial intelligence offers a fresh view on molecular design. We present the first‐time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine‐tuned on recognizing retinoid X and peroxisome proliferator‐activated receptor agonists. We synthesized five top‐ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low‐micromolar receptor modulatory activity in cell‐based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. PMID:29319225

Small business development for molecular diagnostics.

PubMed

Anagostou, Anthanasia; Liotta, Lance A

2012-01-01

Molecular profiling, which is the application of molecular diagnostics technology to tissue and blood -specimens, is an integral element in the new era of molecular medicine and individualized therapy. Molecular diagnostics is a fertile ground for small business development because it can generate products that meet immediate demands in the health-care sector: (a) Detection of disease risk, or early-stage disease, with a higher specificity and sensitivity compared to previous testing methods, and (b) "Companion diagnostics" for stratifying patients to receive a treatment choice optimized to their individual disease. This chapter reviews the promise and challenges of business development in this field. Guidelines are provided for the creation of a business model and the generation of a marketing plan around a candidate molecular diagnostic product. Steps to commercialization are outlined using existing molecular diagnostics companies as learning examples.

Evaluation of reduced point charge models of proteins through Molecular Dynamics simulations: application to the Vps27 UIM-1-Ubiquitin complex.

PubMed

Leherte, Laurence; Vercauteren, Daniel P

2014-02-01

Reduced point charge models of amino acids are designed, (i) from local extrema positions in charge density distribution functions built from the Poisson equation applied to smoothed molecular electrostatic potential (MEP) functions, and (ii) from local maxima positions in promolecular electron density distribution functions. Corresponding charge values are fitted versus all-atom Amber99 MEPs. To easily generate reduced point charge models for protein structures, libraries of amino acid templates are built. The program GROMACS is used to generate stable Molecular Dynamics trajectories of an Ubiquitin-ligand complex (PDB: 1Q0W), under various implementation schemes, solvation, and temperature conditions. Point charges that are not located on atoms are considered as virtual sites with a nul mass and radius. The results illustrate how the intra- and inter-molecular H-bond interactions are affected by the degree of reduction of the point charge models and give directions for their implementation; a special attention to the atoms selected to locate the virtual sites and to the Coulomb-14 interactions is needed. Results obtained at various temperatures suggest that the use of reduced point charge models allows to probe local potential hyper-surface minima that are similar to the all-atom ones, but are characterized by lower energy barriers. It enables to generate various conformations of the protein complex more rapidly than the all-atom point charge representation. Copyright © 2013 Elsevier Inc. All rights reserved.

Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore-based virtual screening, molecular docking and molecular dynamics studies.

PubMed

Islam, Md Ataul; Pillay, Tahir S

2017-08-01

In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB. © 2017 John Wiley & Sons A/S.

Generation of Well-Relaxed All-Atom Models of Large Molecular Weight Polymer Melts: A Hybrid Particle-Continuum Approach Based on Particle-Field Molecular Dynamics Simulations.

PubMed

De Nicola, Antonio; Kawakatsu, Toshihiro; Milano, Giuseppe

2014-12-09

A procedure based on Molecular Dynamics (MD) simulations employing soft potentials derived from self-consistent field (SCF) theory (named MD-SCF) able to generate well-relaxed all-atom structures of polymer melts is proposed. All-atom structures having structural correlations indistinguishable from ones obtained by long MD relaxations have been obtained for poly(methyl methacrylate) (PMMA) and poly(ethylene oxide) (PEO) melts. The proposed procedure leads to computational costs mainly related on system size rather than to the chain length. Several advantages of the proposed procedure over current coarse-graining/reverse mapping strategies are apparent. No parametrization is needed to generate relaxed structures of different polymers at different scales or resolutions. There is no need for special algorithms or back-mapping schemes to change the resolution of the models. This characteristic makes the procedure general and its extension to other polymer architectures straightforward. A similar procedure can be easily extended to the generation of all-atom structures of block copolymer melts and polymer nanocomposites.

Comparing Classical Water Models Using Molecular Dynamics to Find Bulk Properties

ERIC Educational Resources Information Center

Kinnaman, Laura J.; Roller, Rachel M.; Miller, Carrie S.

2018-01-01

A computational chemistry exercise for the undergraduate physical chemistry laboratory is described. In this exercise, students use the molecular dynamics package Amber to generate trajectories of bulk liquid water for 4 different water models (TIP3P, OPC, SPC/E, and TIP4Pew). Students then process the trajectory to calculate structural (radial…

Molecular description of α-keto-based inhibitors of cruzain with activity against Chagas disease combining 3D-QSAR studies and molecular dynamics.

PubMed

Saraiva, Ádria P B; Miranda, Ricardo M; Valente, Renan P P; Araújo, Jéssica O; Souza, Rutelene N B; Costa, Clauber H S; Oliveira, Amanda R S; Almeida, Michell O; Figueiredo, Antonio F; Ferreira, João E V; Alves, Cláudio Nahum; Honorio, Kathia M

2018-04-22

In this work, a group of α-keto-based inhibitors of the cruzain enzyme with anti-chagas activity was selected for a three-dimensional quantitative structure-activity relationship study (3D-QSAR) combined with molecular dynamics (MD). Firstly, statistical models based on Partial Least Square (PLS) regression were developed employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) descriptors. Validation parameters (q 2 and r 2 )for the models were, respectively, 0.910 and 0.997 (CoMFA) and 0.913 and 0.992 (CoMSIA). In addition, external validation for the models using a test group revealed r 2 pred  = 0.728 (CoMFA) and 0.971 (CoMSIA). The most relevant aspect in this study was the generation of molecular fields in both favorable and unfavorable regions based on the models developed. These fields are important to interpret modifications necessary to enhance the biological activities of the inhibitors. This analysis was restricted considering the inhibitors in a fixed conformation, not interacting with their target, the cruzain enzyme. Then, MD was employed taking into account important variables such as time and temperature. MD helped describe the behavior of the inhibitors and their properties showed similar results as those generated by QSAR-3D study. © 2018 John Wiley & Sons A/S.

Molecular-Level Simulations of Shock Generation and Propagation in Soda-Lime Glass

DTIC Science & Technology

2012-08-01

Molecular-Level Simulations of Shock Generation and Propagation in Soda-Lime Glass M. Grujicic, W.C. Bell, B. Pandurangan, B.A. Cheeseman, C ...transparent structures with thickness approaching several inches; (b) relatively low material and manufacturing costs; and ( c ) compositional modifications... c ) models based on explicit crack representation (Ref 15, 16). Since a M. Grujicic, W.C. Bell, and B. Pandurangan, Department of Mec- hanical

Designing an educative curriculum unit for teaching molecular geometry in high school chemistry

NASA Astrophysics Data System (ADS)

Makarious, Nader N.

Chemistry is a highly abstract discipline that is taught and learned with the aid of various models. Among the most challenging, yet a fundamental topic in general chemistry at the high school level, is molecular geometry. This study focused on developing exemplary educative curriculum materials pertaining to the topic of molecular geometry. The methodology used in this study consisted of several steps. First, a diverse set of models were analyzed to determine to what extent each model serves its purpose in teaching molecular geometry. Second, a number of high school teachers and college chemistry professors were asked to share their experiences on using models in teaching molecular geometry through an online questionnaire. Third, findings from the comparative analysis of models, teachers’ experiences, literature review on models and students’ misconceptions, the curriculum expectations of the Next Generation Science Standards and their emphasis on three-dimensional learning and nature of science (NOS) contributed to the development of the molecular geometry unit. Fourth, the developed unit was reviewed by fellow teachers and doctoral-level science education experts and was revised to further improve its coherence and clarity in support of teaching and learning of the molecular geometry concepts. The produced educative curriculum materials focus on the scientific practice of developing and using models as promoted in the Next Generations Science Standards (NGSS) while also addressing nature of science (NOS) goals. The educative features of the newly developed unit support teachers’ pedagogical knowledge (PK) and pedagogical content knowledge (PCK). The unit includes an overview, teacher’s guide, and eight detailed lesson plans with inquiry oriented modeling activities replete with models and suggestions for teachers, as well as formative and summative assessment tasks. The unit design process serves as a model for redesigning other instructional units in science disciplines in general and chemistry courses in particular.

Potential human cholesterol esterase inhibitor design: benefits from the molecular dynamics simulations and pharmacophore modeling studies.

PubMed

John, Shalini; Thangapandian, Sundarapandian; Lee, Keun Woo

2012-01-01

Human pancreatic cholesterol esterase (hCEase) is one of the lipases found to involve in the digestion of large and broad spectrum of substrates including triglycerides, phospholipids, cholesteryl esters, etc. The presence of bile salts is found to be very important for the activation of hCEase. Molecular dynamic simulations were performed for the apoform and bile salt complexed form of hCEase using the co-ordinates of two bile salts from bovine CEase. The stability of the systems throughout the simulation time was checked and two representative structures from the highly populated regions were selected using cluster analysis. These two representative structures were used in pharmacophore model generation. The generated pharmacophore models were validated and used in database screening. The screened hits were refined for their drug-like properties based on Lipinski's rule of five and ADMET properties. The drug-like compounds were further refined by molecular docking simulation using GOLD program based on the GOLD fitness score, mode of binding, and molecular interactions with the active site amino acids. Finally, three hits of novel scaffolds were selected as potential leads to be used in novel and potent hCEase inhibitor design. The stability of binding modes and molecular interactions of these final hits were re-assured by molecular dynamics simulations.

Multiscale geometric modeling of macromolecules II: Lagrangian representation

PubMed Central

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

2013-01-01

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

Quantitative structure-retention relationships for gas chromatographic retention indices of alkylbenzenes with molecular graph descriptors.

PubMed

Ivanciuc, O; Ivanciuc, T; Klein, D J; Seitz, W A; Balaban, A T

2001-02-01

Quantitative structure-retention relationships (QSRR) represent statistical models that quantify the connection between the molecular structure and the chromatographic retention indices of organic compounds, allowing the prediction of retention indices of novel, not yet synthesized compounds, solely from their structural descriptors. Using multiple linear regression, QSRR models for the gas chromatographic Kováts retention indices of 129 alkylbenzenes are generated using molecular graph descriptors. The correlational ability of structural descriptors computed from 10 molecular matrices is investigated, showing that the novel reciprocal matrices give numerical indices with improved correlational ability. A QSRR equation with 5 graph descriptors gives the best calibration and prediction results, demonstrating the usefulness of the molecular graph descriptors in modeling chromatographic retention parameters. The sequential orthogonalization of descriptors suggests simpler QSRR models by eliminating redundant structural information.

DemQSAR: predicting human volume of distribution and clearance of drugs

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

PubMed

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

2011-12-01

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

Phase Structure of Strong-Field Tunneling Wave Packets from Molecules.

PubMed

Liu, Ming-Ming; Li, Min; Wu, Chengyin; Gong, Qihuang; Staudte, André; Liu, Yunquan

2016-04-22

We study the phase structure of the tunneling wave packets from strong-field ionization of molecules and present a molecular quantum-trajectory Monte Carlo model to describe the laser-driven dynamics of photoelectron momentum distributions of molecules. Using our model, we reproduce and explain the alignment-dependent molecular frame photoelectron spectra of strong-field tunneling ionization of N_{2} reported by M. Meckel et al. [Nat. Phys. 10, 594 (2014)]. In addition to modeling the low-energy photoelectron angular distributions quantitatively, we extract the phase structure of strong-field molecular tunneling wave packets, shedding light on its physical origin. The initial phase of the tunneling wave packets at the tunnel exit depends on both the initial transverse momentum distribution and the molecular internuclear distance. We further show that the ionizing molecular orbital has a critical effect on the initial phase of the tunneling wave packets. The phase structure of the photoelectron wave packet is a key ingredient for modeling strong-field molecular photoelectron holography, high-harmonic generation, and molecular orbital imaging.

3D-Lab: a collaborative web-based platform for molecular modeling.

PubMed

Grebner, Christoph; Norrby, Magnus; Enström, Jonatan; Nilsson, Ingemar; Hogner, Anders; Henriksson, Jonas; Westin, Johan; Faramarzi, Farzad; Werner, Philip; Boström, Jonas

2016-09-01

The use of 3D information has shown impact in numerous applications in drug design. However, it is often under-utilized and traditionally limited to specialists. We want to change that, and present an approach making 3D information and molecular modeling accessible and easy-to-use 'for the people'. A user-friendly and collaborative web-based platform (3D-Lab) for 3D modeling, including a blazingly fast virtual screening capability, was developed. 3D-Lab provides an interface to automatic molecular modeling, like conformer generation, ligand alignments, molecular dockings and simple quantum chemistry protocols. 3D-Lab is designed to be modular, and to facilitate sharing of 3D-information to promote interactions between drug designers. Recent enhancements to our open-source virtual reality tool Molecular Rift are described. The integrated drug-design platform allows drug designers to instantaneously access 3D information and readily apply advanced and automated 3D molecular modeling tasks, with the aim to improve decision-making in drug design projects.

Molecular pathophysiology of cerebral edema

PubMed Central

Gerzanich, Volodymyr; Simard, J Marc

2015-01-01

Advancements in molecular biology have led to a greater understanding of the individual proteins responsible for generating cerebral edema. In large part, the study of cerebral edema is the study of maladaptive ion transport. Following acute CNS injury, cells of the neurovascular unit, particularly brain endothelial cells and astrocytes, undergo a program of pre- and post-transcriptional changes in the activity of ion channels and transporters. These changes can result in maladaptive ion transport and the generation of abnormal osmotic forces that, ultimately, manifest as cerebral edema. This review discusses past models and current knowledge regarding the molecular and cellular pathophysiology of cerebral edema. PMID:26661240

Perspective: Markov models for long-timescale biomolecular dynamics.

PubMed

Schwantes, C R; McGibbon, R T; Pande, V S

2014-09-07

Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics.

TMOD-05. MOLECULAR CHARACTERIZATION OF ORTHOTOPIC PATIENT-DERIVED XENOGRAFT MODELS OF PEDIATRIC BRAIN TUMORS AND THEIR USE IN PRECLINICAL EXPERIMENTS

PubMed Central

Brabetz, Sebastian; Schmidt, Christin; Groebner, Susanne N.; Mack, Norman; Seker-Cin, Huriye; Jones, David T.W.; Chavez, Lukas; Milde, Till; Witt, Olaf; Leary, Sarah E.; Li, Xiao-Nan; Wechsler-Reya, Robert J.; Olson, James M.; Pfister, Stefan M.; Kool, Marcel

2017-01-01

Abstract Genomic studies have shown that multiple molecular subtypes of pediatric brain tumors exist that are biologically and clinically highly distinct. These findings ask for novel subtype specific treatments. To develop these we need more and better preclinical models that correctly reflect the proper tumor (sub)type. Orthotopic patient-derived xenograft (PDX) models generated by intracranial injection of primary patient material into the brain of NSG mice offer the unique possibility to test novel substances in primary patient tissue in an in vivo environment. Prior to drug selection and testing, extensive molecular characterizations of PDX and matching primary tumor/blood (DNA methylation, DNA sequencing, and gene expression) are needed to see how the PDX represents the original disease and to learn about targetable oncogenic drivers in each model. In collaboration with several groups around the world we have generated and fully characterized thus far 75 PDX models reflecting 15 distinct subtypes of pediatric brain cancer. PDX models always retain their molecular subtype and in the vast majority of cases also mutations and copy number alterations compared to matching primary tumors. Most aggressive tumors, harboring MYC(N) amplifications, are overrepresented in the cohort, but also subtypes which have not been available for preclinical testing before due to lack of genetically engineered mouse models or suitable cell lines, such as Group 4 medulloblastoma, are included. All models and corresponding molecular data will become available for the community for preclinical research. Examples of such preclinical experiments will be presented. PDX models of pediatric brain tumors are still quite rare. Our repertoire of PDX models and corresponding molecular characterizations allow researchers all over the world to find the right models for their specific scientific questions. It will provide an unprecedented resource to study tumor biology and pave the way for improving treatment strategies for children with malignant brain tumors.

De Novo Design of Bioactive Small Molecules by Artificial Intelligence.

PubMed

Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca; Schneider, Gisbert

2018-01-01

Generative artificial intelligence offers a fresh view on molecular design. We present the first-time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine-tuned on recognizing retinoid X and peroxisome proliferator-activated receptor agonists. We synthesized five top-ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low-micromolar receptor modulatory activity in cell-based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Ergodicity and model quality in template-restrained canonical and temperature/Hamiltonian replica exchange coarse-grained molecular dynamics simulations of proteins.

PubMed

Karczyńska, Agnieszka S; Czaplewski, Cezary; Krupa, Paweł; Mozolewska, Magdalena A; Joo, Keehyoung; Lee, Jooyoung; Liwo, Adam

2017-12-05

Molecular simulations restrained to single or multiple templates are commonly used in protein-structure modeling. However, the restraints introduce additional barriers, thus impairing the ergodicity of simulations, which can affect the quality of the resulting models. In this work, the effect of restraint types and simulation schemes on ergodicity and model quality was investigated by performing template-restrained canonical molecular dynamics (MD), multiplexed replica-exchange molecular dynamics, and Hamiltonian replica exchange molecular dynamics (HREMD) simulations with the coarse-grained UNRES force field on nine selected proteins, with pseudo-harmonic log-Gaussian (unbounded) or Lorentzian (bounded) restraint functions. The best ergodicity was exhibited by HREMD. It has been found that non-ergodicity does not affect model quality if good templates are used to generate restraints. However, when poor-quality restraints not covering the entire protein are used, the improved ergodicity of HREMD can lead to significantly improved protein models. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Applications of next generation sequencing in molecular ecology of non-model organisms.

PubMed

Ekblom, R; Galindo, J

2011-07-01

As most biologists are probably aware, technological advances in molecular biology during the last few years have opened up possibilities to rapidly generate large-scale sequencing data from non-model organisms at a reasonable cost. In an era when virtually any study organism can 'go genomic', it is worthwhile to review how this may impact molecular ecology. The first studies to put the next generation sequencing (NGS) to the test in ecologically well-characterized species without previous genome information were published in 2007 and the beginning of 2008. Since then several studies have followed in their footsteps, and a large number are undoubtedly under way. This review focuses on how NGS has been, and can be, applied to ecological, population genetic and conservation genetic studies of non-model species, in which there is no (or very limited) genomic resources. Our aim is to draw attention to the various possibilities that are opening up using the new technologies, but we also highlight some of the pitfalls and drawbacks with these methods. We will try to provide a snapshot of the current state of the art for this rapidly advancing and expanding field of research and give some likely directions for future developments.

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.

[Vitamin K3-induced activation of molecular oxygen in glioma cells].

PubMed

Krylova, N G; Kulagova, T A; Semenkova, G N; Cherenkevich, S N

2009-01-01

It has been shown by the method of fluorescent analysis that the rate of hydrogen peroxide generation in human U251 glioma cells under the effect of lipophilic (menadione) or hydrophilic (vikasol) analogues of vitamin K3 was different. Analyzing experimental data we can conclude that menadione underwent one- and two-electron reduction by intracellular reductases in glioma cells. Reduced forms of menadione interact with molecular oxygen leading to reactive oxygen species (ROS) generation. The theoretical model of ROS generation including two competitive processes of one- and two-electron reduction of menadione has been proposed. Rate constants of ROS generation mediated by one-electron reduction process have been estimated.

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

Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes andmore » fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.« less

Weighted Watson-Crick automata

NASA Astrophysics Data System (ADS)

Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

2014-07-01

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.

Compartmental and Spatial Rule-Based Modeling with Virtual Cell.

PubMed

Blinov, Michael L; Schaff, James C; Vasilescu, Dan; Moraru, Ion I; Bloom, Judy E; Loew, Leslie M

2017-10-03

In rule-based modeling, molecular interactions are systematically specified in the form of reaction rules that serve as generators of reactions. This provides a way to account for all the potential molecular complexes and interactions among multivalent or multistate molecules. Recently, we introduced rule-based modeling into the Virtual Cell (VCell) modeling framework, permitting graphical specification of rules and merger of networks generated automatically (using the BioNetGen modeling engine) with hand-specified reaction networks. VCell provides a number of ordinary differential equation and stochastic numerical solvers for single-compartment simulations of the kinetic systems derived from these networks, and agent-based network-free simulation of the rules. In this work, compartmental and spatial modeling of rule-based models has been implemented within VCell. To enable rule-based deterministic and stochastic spatial simulations and network-free agent-based compartmental simulations, the BioNetGen and NFSim engines were each modified to support compartments. In the new rule-based formalism, every reactant and product pattern and every reaction rule are assigned locations. We also introduce the rule-based concept of molecular anchors. This assures that any species that has a molecule anchored to a predefined compartment will remain in this compartment. Importantly, in addition to formulation of compartmental models, this now permits VCell users to seamlessly connect reaction networks derived from rules to explicit geometries to automatically generate a system of reaction-diffusion equations. These may then be simulated using either the VCell partial differential equations deterministic solvers or the Smoldyn stochastic simulator. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

3D-QSAR (CoMFA, CoMSIA), molecular docking and molecular dynamics simulations study of 6-aryl-5-cyano-pyrimidine derivatives to explore the structure requirements of LSD1 inhibitors.

PubMed

Ding, Lina; Wang, Zhi-Zheng; Sun, Xu-Dong; Yang, Jing; Ma, Chao-Ya; Li, Wen; Liu, Hong-Min

2017-08-01

Recently, Histone Lysine Specific Demethylase 1 (LSD1) was regarded as a promising anticancer target for the novel drug discovery. And several small molecules as LSD1 inhibitors in different structures have been reported. In this work, we carried out a molecular modeling study on the 6-aryl-5-cyano-pyrimidine fragment LSD1 inhibitors using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models. The results show that the best CoMFA model has q 2 =0.802, r 2 ncv =0.979, and the best CoMSIA model has q 2 =0.799, r 2 ncv =0.982. The electrostatic, hydrophobic and H-bond donor fields play important roles in the models. Molecular docking studies predict the binding mode and the interactions between the ligand and the receptor protein. Molecular dynamics simulations results reveal that the complex of the ligand and the receptor protein are stable at 300K. All the results can provide us more useful information for our further drug design. Copyright © 2017. Published by Elsevier Ltd.

Transitioning NWChem to the Next Generation of Manycore Machines

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

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

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

SynBioSS designer: a web-based tool for the automated generation of kinetic models for synthetic biological constructs

PubMed Central

Weeding, Emma; Houle, Jason

2010-01-01

Modeling tools can play an important role in synthetic biology the same way modeling helps in other engineering disciplines: simulations can quickly probe mechanisms and provide a clear picture of how different components influence the behavior of the whole. We present a brief review of available tools and present SynBioSS Designer. The Synthetic Biology Software Suite (SynBioSS) is used for the generation, storing, retrieval and quantitative simulation of synthetic biological networks. SynBioSS consists of three distinct components: the Desktop Simulator, the Wiki, and the Designer. SynBioSS Designer takes as input molecular parts involved in gene expression and regulation (e.g. promoters, transcription factors, ribosome binding sites, etc.), and automatically generates complete networks of reactions that represent transcription, translation, regulation, induction and degradation of those parts. Effectively, Designer uses DNA sequences as input and generates networks of biomolecular reactions as output. In this paper we describe how Designer uses universal principles of molecular biology to generate models of any arbitrary synthetic biological system. These models are useful as they explain biological phenotypic complexity in mechanistic terms. In turn, such mechanistic explanations can assist in designing synthetic biological systems. We also discuss, giving practical guidance to users, how Designer interfaces with the Registry of Standard Biological Parts, the de facto compendium of parts used in synthetic biology applications. PMID:20639523

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

NASA Astrophysics Data System (ADS)

Pan, Tongyan; Cheng, Cheng

2016-06-01

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

INVESTIGATIONS INTO MOLECULAR PATHWAYS IN THE POST GENOME ERA: CROSS SPECIES COMPARATIVE GENOMICS APPROACH

EPA Science Inventory

Genome sequencing efforts in the past decade were aimed at generating draft sequences of many prokaryotic and eukaryotic model organisms. Successful completion of unicellular eukaryotes, worm, fly and human genome have opened up the new field of molecular biology and function...

Modeling Cell Size Regulation: From Single-Cell-Level Statistics to Molecular Mechanisms and Population-Level Effects.

PubMed

Ho, Po-Yi; Lin, Jie; Amir, Ariel

2018-05-20

Most microorganisms regulate their cell size. In this article, we review some of the mathematical formulations of the problem of cell size regulation. We focus on coarse-grained stochastic models and the statistics that they generate. We review the biologically relevant insights obtained from these models. We then describe cell cycle regulation and its molecular implementations, protein number regulation, and population growth, all in relation to size regulation. Finally, we discuss several future directions for developing understanding beyond phenomenological models of cell size regulation.

SYVA: A program to analyze symmetry of molecules based on vector algebra

NASA Astrophysics Data System (ADS)

Gyevi-Nagy, László; Tasi, Gyula

2017-06-01

Symmetry is a useful concept in physics and chemistry. It can be used to find out some simple properties of a molecule or simplify complex calculations. In this paper a simple vector algebraic method is described to determine all symmetry elements of an arbitrary molecule. To carry out the symmetry analysis, a program has been written, which is also capable of generating the framework group of the molecule, revealing the symmetry properties of normal modes of vibration and symmetrizing the structure. To demonstrate the capabilities of the program, it is compared to other common widely used stand-alone symmetry analyzer (SYMMOL, Symmetrizer) and molecular modeling (NWChem, ORCA, MRCC) software. SYVA can generate input files for molecular modeling programs, e.g. Gaussian, using precisely symmetrized molecular structures. Possible applications are also demonstrated by integrating SYVA with the GAMESS and MRCC software.

Biomedical hypothesis generation by text mining and gene prioritization.

PubMed

Petric, Ingrid; Ligeti, Balazs; Gyorffy, Balazs; Pongor, Sandor

2014-01-01

Text mining methods can facilitate the generation of biomedical hypotheses by suggesting novel associations between diseases and genes. Previously, we developed a rare-term model called RaJoLink (Petric et al, J. Biomed. Inform. 42(2): 219-227, 2009) in which hypotheses are formulated on the basis of terms rarely associated with a target domain. Since many current medical hypotheses are formulated in terms of molecular entities and molecular mechanisms, here we extend the methodology to proteins and genes, using a standardized vocabulary as well as a gene/protein network model. The proposed enhanced RaJoLink rare-term model combines text mining and gene prioritization approaches. Its utility is illustrated by finding known as well as potential gene-disease associations in ovarian cancer using MEDLINE abstracts and the STRING database.

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

The Scientist as Illustrator.

PubMed

Iwasa, Janet H

2016-04-01

Proficiency in art and illustration was once considered an essential skill for biologists, because text alone often could not suffice to describe observations of biological systems. With modern imaging technology, it is no longer necessary to illustrate what we can see by eye. However, in molecular and cellular biology, our understanding of biological processes is dependent on our ability to synthesize diverse data to generate a hypothesis. Creating visual models of these hypotheses is important for generating new ideas and for communicating to our peers and to the public. Here, I discuss the benefits of creating visual models in molecular and cellular biology and consider steps to enable researchers to become more effective visual communicators. Copyright © 2016 Elsevier Ltd. All rights reserved.

Wavelength and intensity dependence of recollision-enhanced multielectron effects in high-order harmonic generation

NASA Astrophysics Data System (ADS)

Abanador, Paul M.; Mauger, François; Lopata, Kenneth; Gaarde, Mette B.; Schafer, Kenneth J.

2018-04-01

Using a model molecular system (A2) with two active electrons restricted to one dimension, we examine high-order harmonic generation (HHG) enhanced by rescattering. Our results show that even at intensities well below the single ionization saturation, harmonics generated from the cation (A2+ ) can be significantly enhanced due to the rescattering of the electron that is initially ionized. This two-electron effect is manifested by the appearance of a secondary plateau and cutoff in the HHG spectrum, extending beyond the predicted cutoff in the single active electron approximation. We use our molecular model to investigate the wavelength dependence of rescattering enhanced HHG, which was first reported in a model atomic system [I. Tikhomirov, T. Sato, and K. L. Ishikawa, Phys. Rev. Lett. 118, 203202 (2017), 10.1103/PhysRevLett.118.203202]. We demonstrate that the HHG yield in the secondary cutoff is highly sensitive to the available electron rescattering energies as indicated by a dramatic scaling with respect to driving wavelength.

Cross-Link Guided Molecular Modeling with ROSETTA

PubMed Central

Leitner, Alexander; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2013-01-01

Chemical cross-links identified by mass spectrometry generate distance restraints that reveal low-resolution structural information on proteins and protein complexes. The technology to reliably generate such data has become mature and robust enough to shift the focus to the question of how these distance restraints can be best integrated into molecular modeling calculations. Here, we introduce three workflows for incorporating distance restraints generated by chemical cross-linking and mass spectrometry into ROSETTA protocols for comparative and de novo modeling and protein-protein docking. We demonstrate that the cross-link validation and visualization software Xwalk facilitates successful cross-link data integration. Besides the protocols we introduce XLdb, a database of chemical cross-links from 14 different publications with 506 intra-protein and 62 inter-protein cross-links, where each cross-link can be mapped on an experimental structure from the Protein Data Bank. Finally, we demonstrate on a protein-protein docking reference data set the impact of virtual cross-links on protein docking calculations and show that an inter-protein cross-link can reduce on average the RMSD of a docking prediction by 5.0 Å. The methods and results presented here provide guidelines for the effective integration of chemical cross-link data in molecular modeling calculations and should advance the structural analysis of particularly large and transient protein complexes via hybrid structural biology methods. PMID:24069194

Mixing of gaseous reactants in chemical generation of atomic iodine for COIL: two-dimensional study

NASA Astrophysics Data System (ADS)

Jirasek, Vit; Spalek, Otomar; Kodymova, Jarmila; Censky, Miroslav

2003-11-01

Two-dimensional CFD model was applied for the study of mixing and reaction between gaseous chlorine dioxide and nitrogen monoxide diluted with nitrogen during atomic iodine generation. The influence of molecular diffusion on the production of atomic chlorine as a precursor of atomic iodine was predominantly studied. The results were compared with one-dimensional modeling of the system.

Hierarchical modeling of molecular energies using a deep neural network

NASA Astrophysics Data System (ADS)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

Computer display and manipulation of biological molecules

NASA Technical Reports Server (NTRS)

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

1978-01-01

This paper describes a computer model that was designed to investigate the conformation of molecules, macromolecules and subsequent complexes. Utilizing an advanced 3-D dynamic computer display system, the model is sufficiently versatile to accommodate a large variety of molecular input and to generate data for multiple purposes such as visual representation of conformational changes, and calculation of conformation and interaction energy. Molecules can be built on the basis of several levels of information. These include the specification of atomic coordinates and connectivities and the grouping of building blocks and duplicated substructures using symmetry rules found in crystals and polymers such as proteins and nucleic acids. Called AIMS (Ames Interactive Molecular modeling System), the model is now being used to study pre-biotic molecular evolution toward life.

Modeling molecular hydrogen emission in M dwarf exoplanetary systems

NASA Astrophysics Data System (ADS)

Evonosky, William; France, Kevin; Kruczek, Nick E.; Youngblood, Allison; Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanet host Stars (MUSCLES)

2017-01-01

Exoplanets orbiting low-mass stars are prime candidates for atmospheric characterization due to their astronomical abundance and short orbital periods. These planets orbit stars that are often more active than main sequence solar-type stars. They are exposed to differing levels of ultraviolet radiation which can cause traditional “biosignature” gases to be generated abiotically, potentially causing false-positive identifications of life. We modeled the recently discovered molecular hydrogen emission in the ultraviolet spectra (1350 - 1650 Å) as arising from the stellar surface, excited by radiation generated in the upper chromosphere. The model was compared with observed hydrogen emission from the “Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanet host Stars” (MUSCLES) survey by conducting a grid search and implementing a chi-squared minimization routine. We considered only progressions from the [1, 4] and [1, 7] first excited electronic levels. Our modeling procedure varied the atomic hydrogen column density (in the chromosphere) as well as the photospheric molecular hydrogen column density and temperature. The model required as an input a reconstructed intrinsic Lyman α profile which served as the pumping radiation for the molecular hydrogen. We found that an atomic hydrogen column density of log10N(H I) = 14.13 ± 0.16 cm-2 represents a breaking point above which there is not enough Lyman α flux available to excite a significant molecular hydrogen population into the [1, 7] state. We also present H2 temperatures which may suggest that star spots on low mass stars persist longer, and encompass more area than star spots on solar-type stars.

Modeling Molecular Hydrogen Emission in M-Dwarf Exoplanetary Systems

NASA Astrophysics Data System (ADS)

Evonosky, W. R.; France, K.; Kruczek, N.; Youngblood, A.

2016-12-01

Exoplanets orbiting low-mass stars are prime candidates for atmospheric characterization due to their astronomical abundance and short orbital periods. These planets orbit stars that are often more active than main sequence solar-type stars. They are exposed to differing levels of ultraviolet radiation which can cause traditional "biosignature" gases to be generated abiotically, potentially causing false-positive identifications of life. We modeled the recently discovered molecular hydrogen emission in the ultraviolet spectra (1350 - 1650 Å) as arising from the stellar surface, excited by radiation generated in the upper chromosphere. The model was compared with observed hydrogen emission from the "Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanet host Stars" (MUSCLES) survey by conducting a grid search and implementing a chi-squared minimization routine. We considered only progressions from the [1, 4] and [1, 7] first excited electronic levels. Our modeling procedure varied the atomic hydrogen column density (in the chromosphere) as well as the photospheric molecular hydrogen column density and temperature. The model required as an input a reconstructed intrinsic Lyman α profile which served as the pumping radiation for the molecular hydrogen. We found that an atomic hydrogen column density of log10N(H I) = 14.13 ± 0.16 cm-2 represents a breaking point above which there is not enough Lyman α flux available to excite a significant molecular hydrogen population into the [1, 7] state. We also present H2 temperatures which may suggest that star spots on low mass stars persist longer, and encompass more area than star spots on solar-type stars.

Gas solubility in dilute solutions: A novel molecular thermodynamic perspective

NASA Astrophysics Data System (ADS)

Chialvo, Ariel A.

2018-05-01

We present an explicit molecular-based interpretation of the thermodynamic phase equilibrium underlying gas solubility in liquids, through rigorous links between the microstructure of the dilute systems and the relevant macroscopic quantities that characterize their solution thermodynamics. We apply the formal analysis to unravel and highlight the molecular-level nature of the approximations behind the widely used Krichevsky-Kasarnovsky [J. Am. Chem. Soc. 57, 2168 (1935)] and Krichevsky-Ilinskaya [Acta Physicochim. 20, 327 (1945)] equations for the modeling of gas solubility. Then, we implement a general molecular-based approach to gas solubility and illustrate it by studying Lennard-Jones binary systems whose microstructure and thermodynamic properties were consistently generated via integral equation calculations. Furthermore, guided by the molecular-based analysis, we propose a novel macroscopic modeling approach to gas solubility, emphasize some usually overlook modeling subtleties, and identify novel interdependences among relevant solubility quantities that can be used as either handy modeling constraints or tools for consistency tests.

Gas solubility in dilute solutions: A novel molecular thermodynamic perspective.

PubMed

Chialvo, Ariel A

2018-05-07

We present an explicit molecular-based interpretation of the thermodynamic phase equilibrium underlying gas solubility in liquids, through rigorous links between the microstructure of the dilute systems and the relevant macroscopic quantities that characterize their solution thermodynamics. We apply the formal analysis to unravel and highlight the molecular-level nature of the approximations behind the widely used Krichevsky-Kasarnovsky [J. Am. Chem. Soc. 57, 2168 (1935)] and Krichevsky-Ilinskaya [Acta Physicochim. 20, 327 (1945)] equations for the modeling of gas solubility. Then, we implement a general molecular-based approach to gas solubility and illustrate it by studying Lennard-Jones binary systems whose microstructure and thermodynamic properties were consistently generated via integral equation calculations. Furthermore, guided by the molecular-based analysis, we propose a novel macroscopic modeling approach to gas solubility, emphasize some usually overlook modeling subtleties, and identify novel interdependences among relevant solubility quantities that can be used as either handy modeling constraints or tools for consistency tests.

GPCR-ModSim: A comprehensive web based solution for modeling G-protein coupled receptors

PubMed Central

Esguerra, Mauricio; Siretskiy, Alexey; Bello, Xabier; Sallander, Jessica; Gutiérrez-de-Terán, Hugo

2016-01-01

GPCR-ModSim (http://open.gpcr-modsim.org) is a centralized and easy to use service dedicated to the structural modeling of G-protein Coupled Receptors (GPCRs). 3D molecular models can be generated from amino acid sequence by homology-modeling techniques, considering different receptor conformations. GPCR-ModSim includes a membrane insertion and molecular dynamics (MD) equilibration protocol, which can be used to refine the generated model or any GPCR structure uploaded to the server, including if desired non-protein elements such as orthosteric or allosteric ligands, structural waters or ions. We herein revise the main characteristics of GPCR-ModSim and present new functionalities. The templates used for homology modeling have been updated considering the latest structural data, with separate profile structural alignments built for inactive, partially-active and active groups of templates. We have also added the possibility to perform multiple-template homology modeling in a unique and flexible way. Finally, our new MD protocol considers a series of distance restraints derived from a recently identified conserved network of helical contacts, allowing for a smoother refinement of the generated models which is particularly advised when there is low homology to the available templates. GPCR- ModSim has been tested on the GPCR Dock 2013 competition with satisfactory results. PMID:27166369

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Pharmacophore generation, atom-based 3D-QSAR, molecular docking and molecular dynamics simulation studies on benzamide analogues as FtsZ inhibitors.

PubMed

Tripathy, Swayansiddha; Azam, Mohammed Afzal; Jupudi, Srikanth; Sahu, Susanta Kumar

2017-10-11

FtsZ is an appealing target for the design of antimicrobial agent that can be used to defeat the multidrug-resistant bacterial pathogens. Pharmacophore modelling, molecular docking and molecular dynamics (MD) simulation studies were performed on a series of three-substituted benzamide derivatives. In the present study a five-featured pharmacophore model with one hydrogen bond acceptors, one hydrogen bond donors, one hydrophobic and two aromatic rings was developed using 97 molecules having MIC values ranging from .07 to 957 μM. A statistically significant 3D-QSAR model was obtained using this pharmacophore hypothesis with a good correlation coefficient (R 2  = .8319), cross validated coefficient (Q 2  = .6213) and a high Fisher ratio (F = 103.9) with three component PLS factor. A good correlation between experimental and predicted activity of the training (R 2  = .83) and test set (R 2  = .67) molecules were displayed by ADHRR.1682 model. The generated model was further validated by enrichment studies using the decoy test and MAE-based criteria to measure the efficiency of the model. The docking studies of all selected inhibitors in the active site of FtsZ protein showed crucial hydrogen bond interactions with Val 207, Asn 263, Leu 209, Gly 205 and Asn-299 residues. The binding free energies of these inhibitors were calculated by the molecular mechanics/generalized born surface area VSGB 2.0 method. Finally, a 15 ns MD simulation was done to confirm the stability of the 4DXD-ligand complex. On a wider scope, the prospect of present work provides insight in designing molecules with better selective FtsZ inhibitory potential.

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.

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

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

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

2016-07-28

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

Neurobiological Mechanisms for the Regulation of Mammalian Sleep-Wake Behavior: Reinterpretation of Historical Evidence and Inclusion of Contemporary Cellular and Molecular Evidence

PubMed Central

Datta, Subimal; MacLean, Robert Ross

2007-01-01

At its most basic level, the function of mammalian sleep can be described as a restorative process of the brain and body; recently, however, progressive research has revealed a host of vital functions to which sleep is essential. Although many excellent reviews on sleep behavior have been published, none have incorporated contemporary studies examining the molecular mechanisms that govern the various stages of sleep. Utilizing a holistic approach, this review is focused on the basic mechanisms involved in the transition from wakefulness, initiation of sleep and the subsequent generation of slow-wave sleep and rapid eye movement (REM) sleep. Additionally, using recent molecular studies and experimental evidence that provides a direct link to sleep as a behavior, we have developed a new model, the Cellular-Molecular-Network model, explaining the mechanisms responsible for regulating REM sleep. By analyzing the fundamental neurobiological mechanisms responsible for the generation and maintenance of sleep-wake behavior in mammals, we intend to provide a broader understanding of our present knowledge in the field of sleep research. PMID:17445891

Insights into the Molecular Mechanism of Rotation in the Fo Sector of ATP Synthase

PubMed Central

Aksimentiev, Aleksij; Balabin, Ilya A.; Fillingame, Robert H.; Schulten, Klaus

2004-01-01

F1Fo-ATP synthase is a ubiquitous membrane protein complex that efficiently converts a cell's transmembrane proton gradient into chemical energy stored as ATP. The protein is made of two molecular motors, Fo and F1, which are coupled by a central stalk. The membrane unit, Fo, converts the transmembrane electrochemical potential into mechanical rotation of a rotor in Fo and the physically connected central stalk. Based on available data of individual components, we have built an all-atom model of Fo and investigated through molecular dynamics simulations and mathematical modeling the mechanism of torque generation in Fo. The mechanism that emerged generates the torque at the interface of the a- and c-subunits of Fo through side groups aSer-206, aArg-210, and aAsn-214 of the a-subunit and side groups cAsp-61 of the c-subunits. The mechanism couples protonation/deprotonation of two cAsp-61 side groups, juxtaposed to the a-subunit at any moment in time, to rotations of individual c-subunit helices as well as rotation of the entire c-subunit. The aArg-210 side group orients the cAsp-61 side groups and, thereby, establishes proton transfer via aSer-206 and aAsn-214 to proton half-channels, while preventing direct proton transfer between the half-channels. A mathematical model proves the feasibility of torque generation by the stated mechanism against loads typical during ATP synthesis; the essential model characteristics, e.g., helix and subunit rotation and associated friction constants, have been tested and furnished by steered molecular dynamics simulations. PMID:14990464

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

PubMed

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

2017-11-29

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

Comparative Analyses of the β-Tubulin Gene and Molecular Modeling Reveal Molecular Insight into the Colchicine Resistance in Kinetoplastids Organisms

PubMed Central

Luis, Luis; Serrano, María Luisa; Hidalgo, Mariana; Mendoza-León, Alexis

2013-01-01

Differential susceptibility to microtubule agents has been demonstrated between mammalian cells and kinetoplastid organisms such as Leishmania spp. and Trypanosoma spp. The aims of this study were to identify and characterize the architecture of the putative colchicine binding site of Leishmania spp. and investigate the molecular basis of colchicine resistance. We cloned and sequenced the β-tubulin gene of Leishmania (Viannia) guyanensis and established the theoretical 3D model of the protein, using the crystallographic structure of the bovine protein as template. We identified mutations on the Leishmania   β-tubulin gene sequences on regions related to the putative colchicine-binding pocket, which generate amino acid substitutions and changes in the topology of this region, blocking the access of colchicine. The same mutations were found in the β-tubulin sequence of kinetoplastid organisms such as Trypanosoma cruzi, T. brucei, and T. evansi. Using molecular modelling approaches, we demonstrated that conformational changes include an elongation and torsion of an α-helix structure and displacement to the inside of the pocket of one β-sheet that hinders access of colchicine. We propose that kinetoplastid organisms show resistance to colchicine due to amino acids substitutions that generate structural changes in the putative colchicine-binding domain, which prevent colchicine access. PMID:24083244

The MOLGENIS toolkit: rapid prototyping of biosoftware at the push of a button.

PubMed

Swertz, Morris A; Dijkstra, Martijn; Adamusiak, Tomasz; van der Velde, Joeri K; Kanterakis, Alexandros; Roos, Erik T; Lops, Joris; Thorisson, Gudmundur A; Arends, Danny; Byelas, George; Muilu, Juha; Brookes, Anthony J; de Brock, Engbert O; Jansen, Ritsert C; Parkinson, Helen

2010-12-21

There is a huge demand on bioinformaticians to provide their biologists with user friendly and scalable software infrastructures to capture, exchange, and exploit the unprecedented amounts of new *omics data. We here present MOLGENIS, a generic, open source, software toolkit to quickly produce the bespoke MOLecular GENetics Information Systems needed. The MOLGENIS toolkit provides bioinformaticians with a simple language to model biological data structures and user interfaces. At the push of a button, MOLGENIS' generator suite automatically translates these models into a feature-rich, ready-to-use web application including database, user interfaces, exchange formats, and scriptable interfaces. Each generator is a template of SQL, JAVA, R, or HTML code that would require much effort to write by hand. This 'model-driven' method ensures reuse of best practices and improves quality because the modeling language and generators are shared between all MOLGENIS applications, so that errors are found quickly and improvements are shared easily by a re-generation. A plug-in mechanism ensures that both the generator suite and generated product can be customized just as much as hand-written software. In recent years we have successfully evaluated the MOLGENIS toolkit for the rapid prototyping of many types of biomedical applications, including next-generation sequencing, GWAS, QTL, proteomics and biobanking. Writing 500 lines of model XML typically replaces 15,000 lines of hand-written programming code, which allows for quick adaptation if the information system is not yet to the biologist's satisfaction. Each application generated with MOLGENIS comes with an optimized database back-end, user interfaces for biologists to manage and exploit their data, programming interfaces for bioinformaticians to script analysis tools in R, Java, SOAP, REST/JSON and RDF, a tab-delimited file format to ease upload and exchange of data, and detailed technical documentation. Existing databases can be quickly enhanced with MOLGENIS generated interfaces using the 'ExtractModel' procedure. The MOLGENIS toolkit provides bioinformaticians with a simple model to quickly generate flexible web platforms for all possible genomic, molecular and phenotypic experiments with a richness of interfaces not provided by other tools. All the software and manuals are available free as LGPLv3 open source at http://www.molgenis.org.

Penetration of Cosmic Rays into Dense Molecular Clouds: Role of Diffuse Envelopes

NASA Astrophysics Data System (ADS)

Ivlev, A. V.; Dogiel, V. A.; Chernyshov, D. O.; Caselli, P.; Ko, C.-M.; Cheng, K. S.

2018-03-01

A flux of cosmic rays (CRs) propagating through a diffuse ionized gas can excite MHD waves, thus generating magnetic disturbances. We propose a generic model of CR penetration into molecular clouds through their diffuse envelopes, and identify the leading physical processes controlling their transport on the way from a highly ionized interstellar medium to the dense interior of the cloud. The model allows us to describe a transition between a free streaming of CRs and their diffusive propagation, determined by the scattering on the self-generated disturbances. A self-consistent set of equations, governing the diffusive transport regime in an envelope and the MHD turbulence generated by the modulated CR flux, is characterized by two dimensionless numbers. We demonstrate a remarkable mutual complementarity of different mechanisms leading to the onset of the diffusive regime, which results in a universal energy spectrum of the modulated CRs. In conclusion, we briefly discuss implications of our results for several fundamental astrophysical problems, such as the spatial distribution of CRs in the Galaxy as well as the ionization, heating, and chemistry in dense molecular clouds. This paper is dedicated to the memory of Prof. Vadim Tsytovich.

Phaser.MRage: automated molecular replacement

PubMed Central

Bunkóczi, Gábor; Echols, Nathaniel; McCoy, Airlie J.; Oeffner, Robert D.; Adams, Paul D.; Read, Randy J.

2013-01-01

Phaser.MRage is a molecular-replacement automation framework that implements a full model-generation workflow and provides several layers of model exploration to the user. It is designed to handle a large number of models and can distribute calculations efficiently onto parallel hardware. In addition, phaser.MRage can identify correct solutions and use this information to accelerate the search. Firstly, it can quickly score all alternative models of a component once a correct solution has been found. Secondly, it can perform extensive analysis of identified solutions to find protein assemblies and can employ assembled models for subsequent searches. Thirdly, it is able to use a priori assembly information (derived from, for example, homologues) to speculatively place and score molecules, thereby customizing the search procedure to a certain class of protein molecule (for example, antibodies) and incorporating additional biological information into molecular replacement. PMID:24189240

Phaser.MRage: automated molecular replacement.

PubMed

Bunkóczi, Gábor; Echols, Nathaniel; McCoy, Airlie J; Oeffner, Robert D; Adams, Paul D; Read, Randy J

2013-11-01

Phaser.MRage is a molecular-replacement automation framework that implements a full model-generation workflow and provides several layers of model exploration to the user. It is designed to handle a large number of models and can distribute calculations efficiently onto parallel hardware. In addition, phaser.MRage can identify correct solutions and use this information to accelerate the search. Firstly, it can quickly score all alternative models of a component once a correct solution has been found. Secondly, it can perform extensive analysis of identified solutions to find protein assemblies and can employ assembled models for subsequent searches. Thirdly, it is able to use a priori assembly information (derived from, for example, homologues) to speculatively place and score molecules, thereby customizing the search procedure to a certain class of protein molecule (for example, antibodies) and incorporating additional biological information into molecular replacement.

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.

In silico models for development of insect repellents

USDA-ARS?s Scientific Manuscript database

In silico modeling a common term to describe computer-assisted molecular modeling has been used to make remarkable advances in mechanistic drug design and in the discovery of new potential bioactive chemical entities in recent years. The goal of this chapter will be to focus on new, next-generation ...

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Simulation of dense amorphous polymers by generating representative atomistic models

NASA Astrophysics Data System (ADS)

Curcó, David; Alemán, Carlos

2003-08-01

A method for generating atomistic models of dense amorphous polymers is presented. The generated models can be used as starting structures of Monte Carlo and molecular dynamics simulations, but also are suitable for the direct evaluation physical properties. The method is organized in a two-step procedure. First, structures are generated using an algorithm that minimizes the torsional strain. After this, an iterative algorithm is applied to relax the nonbonding interactions. In order to check the performance of the method we examined structure-dependent properties for three polymeric systems: polyethyelene (ρ=0.85 g/cm3), poly(L,D-lactic) acid (ρ=1.25 g/cm3), and polyglycolic acid (ρ=1.50 g/cm3). The method successfully generated representative packings for such dense systems using minimum computational resources.

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

PubMed

Ragan, Mark A; Chan, Cheong Xin

2013-08-01

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

Combined Molecular Algorithms for the Generation, Equilibration and Topological Analysis of Entangled Polymers: Methodology and Performance

PubMed Central

Karayiannis, Nikos Ch.; Kröger, Martin

2009-01-01

We review the methodology, algorithmic implementation and performance characteristics of a hierarchical modeling scheme for the generation, equilibration and topological analysis of polymer systems at various levels of molecular description: from atomistic polyethylene samples to random packings of freely-jointed chains of tangent hard spheres of uniform size. Our analysis focuses on hitherto less discussed algorithmic details of the implementation of both, the Monte Carlo (MC) procedure for the system generation and equilibration, and a postprocessing step, where we identify the underlying topological structure of the simulated systems in the form of primitive paths. In order to demonstrate our arguments, we study how molecular length and packing density (volume fraction) affect the performance of the MC scheme built around chain-connectivity altering moves. In parallel, we quantify the effect of finite system size, of polydispersity, and of the definition of the number of entanglements (and related entanglement molecular weight) on the results about the primitive path network. Along these lines we approve main concepts which had been previously proposed in the literature. PMID:20087477

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

PubMed Central

2017-01-01

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

Scaffolding Students' Online Critiquing of Expert- and Peer-generated Molecular Models of Chemical Reactions

NASA Astrophysics Data System (ADS)

Chang, Hsin-Yi; Chang, Hsiang-Chi

2013-08-01

In this study, we developed online critiquing activities using an open-source computer learning environment. We investigated how well the activities scaffolded students to critique molecular models of chemical reactions made by scientists, peers, and a fictitious peer, and whether the activities enhanced the students' understanding of science models and chemical reactions. The activities were implemented in an eighth-grade class with 28 students in a public junior high school in southern Taiwan. The study employed mixed research methods. Data collected included pre- and post-instructional assessments, post-instructional interviews, and students' electronic written responses and oral discussions during the critiquing activities. The results indicated that these activities guided the students to produce overall quality critiques. Also, the students developed a more sophisticated understanding of chemical reactions and scientific models as a result of the intervention. Design considerations for effective model critiquing activities are discussed based on observational results, including the use of peer-generated artefacts for critiquing to promote motivation and collaboration, coupled with critiques of scientific models to enhance students' epistemological understanding of model purpose and communication.

PRO_LIGAND: an approach to de novo molecular design. 2. Design of novel molecules from molecular field analysis (MFA) models and pharmacophores.

PubMed

Waszkowycz, B; Clark, D E; Frenkel, D; Li, J; Murray, C W; Robson, B; Westhead, D R

1994-11-11

A computational approach for molecular design, PRO_LIGAND, has been developed within the PROMETHEUS molecular design and simulation system in order to provide a unified framework for the de novo generation of diverse molecules which are either similar or complementary to a specified target. In this instance, the target is a pharmacophore derived from a series of active structures either by a novel interpretation of molecular field analysis data or by a pharmacophore-mapping procedure based on clique detection. After a brief introduction to PRO_LIGAND, a detailed description is given of the two pharmacophore generation procedures and their abilities are demonstrated by the elucidation of pharmacophores for steroid binding and ACE inhibition, respectively. As a further indication of its efficacy in aiding the rational drug design process, PRO_LIGAND is then employed to build novel organic molecules to satisfy the physicochemical constraints implied by the pharmacophores.

Combining configurational energies and forces for molecular force field optimization

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

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

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

Combining configurational energies and forces for molecular force field optimization

DOE PAGES

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

2017-07-21

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

Stacking the odds for Golgi cisternal maturation

PubMed Central

Mani, Somya; Thattai, Mukund

2016-01-01

What is the minimal set of cell-biological ingredients needed to generate a Golgi apparatus? The compositions of eukaryotic organelles arise through a process of molecular exchange via vesicle traffic. Here we statistically sample tens of thousands of homeostatic vesicle traffic networks generated by realistic molecular rules governing vesicle budding and fusion. Remarkably, the plurality of these networks contain chains of compartments that undergo creation, compositional maturation, and dissipation, coupled by molecular recycling along retrograde vesicles. This motif precisely matches the cisternal maturation model of the Golgi, which was developed to explain many observed aspects of the eukaryotic secretory pathway. In our analysis cisternal maturation is a robust consequence of vesicle traffic homeostasis, independent of the underlying details of molecular interactions or spatial stacking. This architecture may have been exapted rather than selected for its role in the secretion of large cargo. DOI: http://dx.doi.org/10.7554/eLife.16231.001 PMID:27542195

Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks

PubMed Central

2017-01-01

In de novo drug design, computational strategies are used to generate novel molecules with good affinity to the desired biological target. In this work, we show that recurrent neural networks can be trained as generative models for molecular structures, similar to statistical language models in natural language processing. We demonstrate that the properties of the generated molecules correlate very well with the properties of the molecules used to train the model. In order to enrich libraries with molecules active toward a given biological target, we propose to fine-tune the model with small sets of molecules, which are known to be active against that target. Against Staphylococcus aureus, the model reproduced 14% of 6051 hold-out test molecules that medicinal chemists designed, whereas against Plasmodium falciparum (Malaria), it reproduced 28% of 1240 test molecules. When coupled with a scoring function, our model can perform the complete de novo drug design cycle to generate large sets of novel molecules for drug discovery. PMID:29392184

The Molecular Underpinnings of Centromere Identity and Maintenance

PubMed Central

Sekulic, Nikolina; Black, Ben E.

2012-01-01

Centromeres direct faithful chromosome inheritance at cell division but are not defined by a conserved DNA sequence. Instead, a specialized form of chromatin containing the histone H3 variant, CENP-A, epigenetically specifies centromere location. We discuss current models where CENP-A serves as the marker for the centromere during the entire cell cycle in addition to generating the foundational chromatin for the kinetochore in mitosis. Recent elegant experiments indicate that engineered arrays of CENP-A-containing nucleosomes are sufficient to serve as the site of kinetochore formation and for seeding centromeric chromatin that self-propagates through cell generations. Finally, recent structural and dynamic studies of CENP-A-containing histone complexes—before and after assembly into nucleosomes—provide models to explain underlying molecular mechanisms at the centromere. PMID:22410197

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

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

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

2012-07-03

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

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

PubMed

Panda, Subhamay; Kumari, Leena; Panda, Santamay

2017-11-17

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

Girsanov reweighting for path ensembles and Markov state models

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors

PubMed Central

Schütte, Moritz; Risch, Thomas; Abdavi-Azar, Nilofar; Boehnke, Karsten; Schumacher, Dirk; Keil, Marlen; Yildiriman, Reha; Jandrasits, Christine; Borodina, Tatiana; Amstislavskiy, Vyacheslav; Worth, Catherine L.; Schweiger, Caroline; Liebs, Sandra; Lange, Martin; Warnatz, Hans- Jörg; Butcher, Lee M.; Barrett, James E.; Sultan, Marc; Wierling, Christoph; Golob-Schwarzl, Nicole; Lax, Sigurd; Uranitsch, Stefan; Becker, Michael; Welte, Yvonne; Regan, Joseph Lewis; Silvestrov, Maxine; Kehler, Inge; Fusi, Alberto; Kessler, Thomas; Herwig, Ralf; Landegren, Ulf; Wienke, Dirk; Nilsson, Mats; Velasco, Juan A.; Garin-Chesa, Pilar; Reinhard, Christoph; Beck, Stephan; Schäfer, Reinhold; Regenbrecht, Christian R. A.; Henderson, David; Lange, Bodo; Haybaeck, Johannes; Keilholz, Ulrich; Hoffmann, Jens; Lehrach, Hans; Yaspo, Marie-Laure

2017-01-01

Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I–IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming RAS/RAF mutations in predicting sensitivity to the EGFR inhibitor cetuximab. PMID:28186126

Next generation patient-derived prostate cancer xenograft models

PubMed Central

Lin, Dong; Xue, Hui; Wang, Yuwei; Wu, Rebecca; Watahiki, Akira; Dong, Xin; Cheng, Hongwei; Wyatt, Alexander W; Collins, Colin C; Gout, Peter W; Wang, Yuzhuo

2014-01-01

There is a critical need for more effective therapeutic approaches for prostate cancer. Research in this area, however, has been seriously hampered by a lack of clinically relevant, experimental in vivo models of the disease. This review particularly focuses on the development of prostate cancer xenograft models based on subrenal capsule grafting of patients’ tumor tissue into nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice. This technique allows successful development of transplantable, patient-derived cancer tissue xenograft lines not only from aggressive metastatic, but also from localized prostate cancer tissues. The xenografts have been found to retain key biological properties of the original malignancies, including histopathological and molecular characteristics, tumor heterogeneity, response to androgen ablation and metastatic ability. As such, they are highly clinically relevant and provide valuable tools for studies of prostate cancer progression at cellular and molecular levels, drug screening for personalized cancer therapy and preclinical drug efficacy testing; especially when a panel of models is used to cover a broader spectrum of the disease. These xenograft models could therefore be viewed as next-generation models of prostate cancer. PMID:24589467

Uncertainty in a Markov state model with missing states and rates: Application to a room temperature kinetic model obtained using high temperature molecular dynamics.

PubMed

Chatterjee, Abhijit; Bhattacharya, Swati

2015-09-21

Several studies in the past have generated Markov State Models (MSMs), i.e., kinetic models, of biomolecular systems by post-analyzing long standard molecular dynamics (MD) calculations at the temperature of interest and focusing on the maximally ergodic subset of states. Questions related to goodness of these models, namely, importance of the missing states and kinetic pathways, and the time for which the kinetic model is valid, are generally left unanswered. We show that similar questions arise when we generate a room-temperature MSM (denoted MSM-A) for solvated alanine dipeptide using state-constrained MD calculations at higher temperatures and Arrhenius relation — the main advantage of such a procedure being a speed-up of several thousand times over standard MD-based MSM building procedures. Bounds for rate constants calculated using probability theory from state-constrained MD at room temperature help validate MSM-A. However, bounds for pathways possibly missing in MSM-A show that alternate kinetic models exist that produce the same dynamical behaviour at short time scales as MSM-A but diverge later. Even in the worst case scenario, MSM-A is found to be valid longer than the time required to generate it. Concepts introduced here can be straightforwardly extended to other MSM building techniques.

Computational modeling of epidermal cell fate determination systems.

PubMed

Ryu, Kook Hui; Zheng, Xiaohua; Huang, Ling; Schiefelbein, John

2013-02-01

Cell fate decisions are of primary importance for plant development. Their simple 'either-or' outcome and dynamic nature has attracted the attention of computational modelers. Recent efforts have focused on modeling the determination of several epidermal cell types in the root and shoot of Arabidopsis where many molecular components have been defined. Results of integrated modeling and molecular biology experimentation in these systems have highlighted the importance of competitive positive and negative factors and interconnected feedback loops in generating flexible yet robust mechanisms for establishing distinct gene expression programs in neighboring cells. These models have proven useful in judging hypotheses and guiding future research. Copyright © 2012 Elsevier Ltd. All rights reserved.

Characterizing Human Stem Cell–derived Sensory Neurons at the Single-cell Level Reveals Their Ion Channel Expression and Utility in Pain Research

PubMed Central

Young, Gareth T; Gutteridge, Alex; Fox, Heather DE; Wilbrey, Anna L; Cao, Lishuang; Cho, Lily T; Brown, Adam R; Benn, Caroline L; Kammonen, Laura R; Friedman, Julia H; Bictash, Magda; Whiting, Paul; Bilsland, James G; Stevens, Edward B

2014-01-01

The generation of human sensory neurons by directed differentiation of pluripotent stem cells opens new opportunities for investigating the biology of pain. The inability to generate this cell type has meant that up until now their study has been reliant on the use of rodent models. Here, we use a combination of population and single-cell techniques to perform a detailed molecular, electrophysiological, and pharmacological phenotyping of sensory neurons derived from human embryonic stem cells. We describe the evolution of cell populations over 6 weeks of directed differentiation; a process that results in the generation of a largely homogeneous population of neurons that are both molecularly and functionally comparable to human sensory neurons derived from mature dorsal root ganglia. This work opens the prospect of using pluripotent stem-cell–derived sensory neurons to study human neuronal physiology and as in vitro models for drug discovery in pain and sensory disorders. PMID:24832007

Characterizing human stem cell-derived sensory neurons at the single-cell level reveals their ion channel expression and utility in pain research.

PubMed

Young, Gareth T; Gutteridge, Alex; Fox, Heather DE; Wilbrey, Anna L; Cao, Lishuang; Cho, Lily T; Brown, Adam R; Benn, Caroline L; Kammonen, Laura R; Friedman, Julia H; Bictash, Magda; Whiting, Paul; Bilsland, James G; Stevens, Edward B

2014-08-01

The generation of human sensory neurons by directed differentiation of pluripotent stem cells opens new opportunities for investigating the biology of pain. The inability to generate this cell type has meant that up until now their study has been reliant on the use of rodent models. Here, we use a combination of population and single-cell techniques to perform a detailed molecular, electrophysiological, and pharmacological phenotyping of sensory neurons derived from human embryonic stem cells. We describe the evolution of cell populations over 6 weeks of directed differentiation; a process that results in the generation of a largely homogeneous population of neurons that are both molecularly and functionally comparable to human sensory neurons derived from mature dorsal root ganglia. This work opens the prospect of using pluripotent stem-cell-derived sensory neurons to study human neuronal physiology and as in vitro models for drug discovery in pain and sensory disorders.

H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations.

PubMed

Anandakrishnan, Ramu; Aguilar, Boris; Onufriev, Alexey V

2012-07-01

The accuracy of atomistic biomolecular modeling and simulation studies depend on the accuracy of the input structures. Preparing these structures for an atomistic modeling task, such as molecular dynamics (MD) simulation, can involve the use of a variety of different tools for: correcting errors, adding missing atoms, filling valences with hydrogens, predicting pK values for titratable amino acids, assigning predefined partial charges and radii to all atoms, and generating force field parameter/topology files for MD. Identifying, installing and effectively using the appropriate tools for each of these tasks can be difficult for novice and time-consuming for experienced users. H++ (http://biophysics.cs.vt.edu/) is a free open-source web server that automates the above key steps in the preparation of biomolecular structures for molecular modeling and simulations. H++ also performs extensive error and consistency checking, providing error/warning messages together with the suggested corrections. In addition to numerous minor improvements, the latest version of H++ includes several new capabilities and options: fix erroneous (flipped) side chain conformations for HIS, GLN and ASN, include a ligand in the input structure, process nucleic acid structures and generate a solvent box with specified number of common ions for explicit solvent MD.

Molecular docking, molecular modeling, and molecular dynamics studies of azaisoflavone as dual COX-2 inhibitors and TP receptor antagonists.

PubMed

Hadianawala, Murtuza; Mahapatra, Amarjyoti Das; Yadav, Jitender K; Datta, Bhaskar

2018-02-26

Designed multi-target ligand (DML) is an emerging strategy for the development of new drugs and involves the engagement of multiple targets with the same moiety. In the context of NSAIDs it has been suggested that targeting the thromboxane prostanoid (TP) receptor along with cyclooxygenase-2 (COX-2) may help to overcome cardiovascular (CVS) complications associated with COXIBs. In the present work, azaisoflavones were studied for their COX-2 and TP receptor binding activities using structure based drug design (SBDD) techniques. Flavonoids were selected as a starting point based on their known COX-2 inhibitory and TP receptor antagonist activity. Iterative design and docking studies resulted in the evolution of a new class scaffold replacing the benzopyran-4-one ring of flavonoids with quinolin-4-one. The docking and binding parameters of these new compounds are found to be promising in comparison to those of selective COX-2 inhibitors, such as SC-558 and celecoxib. Owing to the lack of structural information, a model for the TP receptor was generated using a threading base alignment method with loop optimization performed using an ab initio method. The model generated was validated against known antagonists for TP receptor using docking/MMGBSA. Finally, the molecules that were designed for selective COX-2 inhibition were docked into the active site of the TP receptor. Iterative structural modifications and docking on these molecules generated a series which displays optimum docking scores and binding interaction for both targets. Molecular dynamics studies on a known TP receptor antagonist and a designed molecule show that both molecules remain in contact with protein throughout the simulation and interact in similar binding modes. Graphical abstract ᅟ.

Mechanism of the free charge carrier generation in the dielectric breakdown

NASA Astrophysics Data System (ADS)

Rahim, N. A. A.; Ranom, R.; Zainuddin, H.

2017-12-01

Many studies have been conducted to investigate the effect of environmental, mechanical and electrical stresses on insulator. However, studies on physical process of discharge phenomenon, leading to the breakdown of the insulator surface are lacking and difficult to comprehend. Therefore, this paper analysed charge carrier generation mechanism that can cause free charge carrier generation, leading toward surface discharge development. Besides, this paper developed a model of surface discharge based on the charge generation mechanism on the outdoor insulator. Nernst’s Planck theory was used in order to model the behaviour of the charge carriers while Poisson’s equation was used to determine the distribution of electric field on insulator surface. In the modelling of surface discharge on the outdoor insulator, electric field dependent molecular ionization was used as the charge generation mechanism. A mathematical model of the surface discharge was solved using method of line technique (MOL). The result from the mathematical model showed that the behaviour of net space charge density was correlated with the electric field distribution.

A Quantitative Structure-Property Relationship (QSPR) Study of Aliphatic Alcohols by the Method of Dividing the Molecular Structure into Substructure

PubMed Central

Liu, Fengping; Cao, Chenzhong; Cheng, Bin

2011-01-01

A quantitative structure–property relationship (QSPR) analysis of aliphatic alcohols is presented. Four physicochemical properties were studied: boiling point (BP), n-octanol–water partition coefficient (lg POW), water solubility (lg W) and the chromatographic retention indices (RI) on different polar stationary phases. In order to investigate the quantitative structure–property relationship of aliphatic alcohols, the molecular structure ROH is divided into two parts, R and OH to generate structural parameter. It was proposed that the property is affected by three main factors for aliphatic alcohols, alkyl group R, substituted group OH, and interaction between R and OH. On the basis of the polarizability effect index (PEI), previously developed by Cao, the novel molecular polarizability effect index (MPEI) combined with odd-even index (OEI), the sum eigenvalues of bond-connecting matrix (SX1CH) previously developed in our team, were used to predict the property of aliphatic alcohols. The sets of molecular descriptors were derived directly from the structure of the compounds based on graph theory. QSPR models were generated using only calculated descriptors and multiple linear regression techniques. These QSPR models showed high values of multiple correlation coefficient (R > 0.99) and Fisher-ratio statistics. The leave-one-out cross-validation demonstrated the final models to be statistically significant and reliable. PMID:21731451

Molecular dynamics simulations of theoretical cellulose nanotube models.

PubMed

Uto, Takuya; Kodama, Yuta; Miyata, Tatsuhiko; Yui, Toshifumi

2018-06-15

Nanotubes are remarkable nanoscale architectures for a wide range of potential applications. In the present paper, we report a molecular dynamics (MD) study of the theoretical cellulose nanotube (CelNT) models to evaluate their dynamic behavior in solution (either chloroform or benzene). Based on the one-quarter chain staggering relationship, we constructed six CelNT models by combining the two chain polarities (parallel (P) and antiparallel (AP)) and three symmetry operations (helical right (H R ), helical left (H L ), and rotation (R)) to generate a circular arrangement of molecular chains. Among the four models that retained the tubular form (P-H R , P-H L , P-R, and AP-R), the P-R and AP-R models have the lowest steric energies in benzene and chloroform, respectively. The structural features of the CelNT models were characterized in terms of the hydroxymethyl group conformation and intermolecular hydrogen bonds. Solvent structuring more clearly occurred with benzene than chloroform, suggesting that the CelNT models may disperse in benzene. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-07-01

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

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

PubMed Central

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

2014-01-01

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

High-fertility phenotypes: two outbred mouse models exhibit substantially different molecular and physiological strategies warranting improved fertility.

PubMed

Langhammer, Martina; Michaelis, Marten; Hoeflich, Andreas; Sobczak, Alexander; Schoen, Jennifer; Weitzel, Joachim M

2014-01-01

Animal models are valuable tools in fertility research. Worldwide, there are more than 400 transgenic or knockout mouse models available showing a reproductive phenotype; almost all of them exhibit an infertile or at least subfertile phenotype. By contrast, animal models revealing an improved fertility phenotype are barely described. This article summarizes data on two outbred mouse models exhibiting a 'high-fertility' phenotype. These mouse lines were generated via selection over a time period of more than 40 years and 161 generations. During this selection period, the number of offspring per litter and the total birth weight of the entire litter nearly doubled. Concomitantly with the increased fertility phenotype, several endocrine parameters (e.g. serum testosterone concentrations in male animals), physiological parameters (e.g. body weight, accelerated puberty, and life expectancy), and behavioral parameters (e.g. behavior in an open field and endurance fitness on a treadmill) were altered. We demonstrate that the two independently bred high-fertility mouse lines warranted their improved fertility phenotype using different molecular and physiological strategies. The fertility lines display female- as well as male-specific characteristics. These genetically heterogeneous mouse models provide new insights into molecular and cellular mechanisms that enhance fertility. In view of decreasing fertility in men, these models will therefore be a precious information source for human reproductive medicine. Translated abstract A German translation of abstract is freely available at http://www.reproduction-online.org/content/147/4/427/suppl/DC1.

Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

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

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion–ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Lastly, another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.« less

Molecular Modeling of Thermodynamic and Transport Properties for CO2 and Aqueous Brines.

PubMed

Jiang, Hao; Economou, Ioannis G; Panagiotopoulos, Athanassios Z

2017-04-18

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models for water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2 , and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2 -rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion-ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.

Molecular Modeling of Thermodynamic and Transport Properties for CO 2 and Aqueous Brines

DOE PAGES

Jiang, Hao; Economou, Ioannis G.; Panagiotopoulos, Athanassios Z.

2017-02-24

Molecular simulation techniques using classical force-fields occupy the space between ab initio quantum mechanical methods and phenomenological correlations. In particular, Monte Carlo and molecular dynamics algorithms can be used to provide quantitative predictions of thermodynamic and transport properties of fluids relevant for geologic carbon sequestration at conditions for which experimental data are uncertain or not available. These methods can cover time and length scales far exceeding those of quantum chemical methods, while maintaining transferability and predictive power lacking from phenomenological correlations. The accuracy of predictions depends sensitively on the quality of the molecular models used. Many existing fixed-point-charge models formore » water and aqueous mixtures fail to represent accurately these fluid properties, especially when descriptions covering broad ranges of thermodynamic conditions are needed. Recent work on development of accurate models for water, CO 2, and dissolved salts, as well as their mixtures, is summarized in this Account. Polarizable models that can respond to the different dielectric environments in aqueous versus nonaqueous phases are necessary for predictions of properties over extended ranges of temperatures and pressures. Phase compositions and densities, activity coefficients of the dissolved salts, interfacial tensions, viscosities and diffusivities can be obtained in near-quantitative agreement to available experimental data, using relatively modest computational resources. In some cases, for example, for the composition of the CO 2-rich phase in coexistence with an aqueous phase, recent results from molecular simulations have helped discriminate among conflicting experimental data sets. The sensitivity of properties on the quality of the intermolecular interaction model varies significantly. Properties such as the phase compositions or electrolyte activity coefficients are much more sensitive than phase densities, viscosities, or component diffusivities. Strong confinement effects on physical properties in nanoscale media can also be directly obtained from molecular simulations. Future work on molecular modeling for CO 2 and aqueous brines is likely to be focused on more systematic generation of interaction models by utilizing quantum chemical as well as direct experimental measurements. New ion models need to be developed for use with the current generation of polarizable water models, including ion–ion interactions that will allow for accurate description of dense, mixed brines. Methods will need to be devised that go beyond the use of effective potentials for incorporation of quantum effects known to be important for water, and reactive force fields developed that can handle bond creation and breaking in systems with carbonate and silicate minerals. Lastly, another area of potential future work is the integration of molecular simulation methods in multiscale models for the chemical reactions leading to mineral dissolution and flow within the porous media in underground formations.« less

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

PubMed

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

2017-06-28

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

Mapping biological process relationships and disease perturbations within a pathway network.

PubMed

Stoney, Ruth; Robertson, David L; Nenadic, Goran; Schwartz, Jean-Marc

2018-01-01

Molecular interaction networks are routinely used to map the organization of cellular function. Edges represent interactions between genes, proteins, or metabolites. However, in living cells, molecular interactions are dynamic, necessitating context-dependent models. Contextual information can be integrated into molecular interaction networks through the inclusion of additional molecular data, but there are concerns about completeness and relevance of this data. We developed an approach for representing the organization of human cellular processes using pathways as the nodes in a network. Pathways represent spatial and temporal sets of context-dependent interactions, generating a high-level network when linked together, which incorporates contextual information without the need for molecular interaction data. Analysis of the pathway network revealed linked communities representing functional relationships, comparable to those found in molecular networks, including metabolism, signaling, immunity, and the cell cycle. We mapped a range of diseases onto this network and find that pathways associated with diseases tend to be functionally connected, highlighting the perturbed functions that result in disease phenotypes. We demonstrated that disease pathways cluster within the network. We then examined the distribution of cancer pathways and showed that cancer pathways tend to localize within the signaling, DNA processes and immune modules, although some cancer-associated nodes are found in other network regions. Altogether, we generated a high-confidence functional network, which avoids some of the shortcomings faced by conventional molecular models. Our representation provides an intuitive functional interpretation of cellular organization, which relies only on high-quality pathway and Gene Ontology data. The network is available at https://data.mendeley.com/datasets/3pbwkxjxg9/1.

Modelface: an Application Programming Interface (API) for Homology Modeling Studies Using Modeller Software

PubMed Central

Sakhteman, Amirhossein; Zare, Bijan

2016-01-01

An interactive application, Modelface, was presented for Modeller software based on windows platform. The application is able to run all steps of homology modeling including pdb to fasta generation, running clustal, model building and loop refinement. Other modules of modeler including energy calculation, energy minimization and the ability to make single point mutations in the PDB structures are also implemented inside Modelface. The API is a simple batch based application with no memory occupation and is free of charge for academic use. The application is also able to repair missing atom types in the PDB structures making it suitable for many molecular modeling studies such as docking and molecular dynamic simulation. Some successful instances of modeling studies using Modelface are also reported. PMID:28243276

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

Cancer.gov

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

3D Printing of Protein Models in an Undergraduate Laboratory: Leucine Zippers

ERIC Educational Resources Information Center

Meyer, Scott C.

2015-01-01

An upper-division undergraduate laboratory experiment is described that explores the structure/function relationship of protein domains, namely leucine zippers, through a molecular graphics computer program and physical models fabricated by 3D printing. By generating solvent accessible surfaces and color-coding hydrophobic, basic, and acidic amino…

Animation Model to Conceptualize ATP Generation: A Mitochondrial Oxidative Phosphorylation

ERIC Educational Resources Information Center

Jena, Ananta Kumar

2015-01-01

Adenosine triphosphate (ATP) is the molecular unit of intracellular energy and it is the product of oxidative phosphorylation of cellular respiration uses in cellular processes. The study explores the growth of the misconception levels amongst the learners and evaluates the effectiveness of animation model over traditional methods. The data…

Cardiac myosin missense mutations cause dilated cardiomyopathy in mouse models and depress molecular motor function.

PubMed

Schmitt, Joachim P; Debold, Edward P; Ahmad, Ferhaan; Armstrong, Amy; Frederico, Andrea; Conner, David A; Mende, Ulrike; Lohse, Martin J; Warshaw, David; Seidman, Christine E; Seidman, J G

2006-09-26

Dilated cardiomyopathy (DCM) leads to heart failure, a leading cause of death in industrialized nations. Approximately 30% of DCM cases are genetic in origin, with some resulting from point mutations in cardiac myosin, the molecular motor of the heart. The effects of these mutations on myosin's molecular mechanics have not been determined. We have engineered two murine models characterizing the physiological, cellular, and molecular effects of DCM-causing missense mutations (S532P and F764L) in the alpha-cardiac myosin heavy chain and compared them with WT mice. Mutant mice developed morphological and functional characteristics of DCM consistent with the human phenotypes. Contractile function of isolated myocytes was depressed and preceded left ventricular dilation and reduced fractional shortening. In an in vitro motility assay, both mutant cardiac myosins exhibited a reduced ability to translocate actin (V(actin)) but had similar force-generating capacities. Actin-activated ATPase activities were also reduced. Single-molecule laser trap experiments revealed that the lower V(actin) in the S532P mutant was due to a reduced ability of the motor to generate a step displacement and an alteration of the kinetics of its chemomechanical cycle. These results suggest that the depressed molecular function in cardiac myosin may initiate the events that cause the heart to remodel and become pathologically dilated.

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

PubMed

Panda, Subhamay; Kumari, Leena

2017-01-01

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

Ames Culture Chamber System: Enabling Model Organism Research Aboard the international Space Station

NASA Technical Reports Server (NTRS)

Steele, Marianne

2014-01-01

Understanding the genetic, physiological, and behavioral effects of spaceflight on living organisms and elucidating the molecular mechanisms that underlie these effects are high priorities for NASA. Certain organisms, known as model organisms, are widely studied to help researchers better understand how all biological systems function. Small model organisms such as nem-atodes, slime mold, bacteria, green algae, yeast, and moss can be used to study the effects of micro- and reduced gravity at both the cellular and systems level over multiple generations. Many model organisms have sequenced genomes and published data sets on their transcriptomes and proteomes that enable scientific investigations of the molecular mechanisms underlying the adaptations of these organisms to space flight.

Approaches to ab initio molecular replacement of α-helical transmembrane proteins.

PubMed

Thomas, Jens M H; Simkovic, Felix; Keegan, Ronan; Mayans, Olga; Zhang, Chengxin; Zhang, Yang; Rigden, Daniel J

2017-12-01

α-Helical transmembrane proteins are a ubiquitous and important class of proteins, but present difficulties for crystallographic structure solution. Here, the effectiveness of the AMPLE molecular replacement pipeline in solving α-helical transmembrane-protein structures is assessed using a small library of eight ideal helices, as well as search models derived from ab initio models generated both with and without evolutionary contact information. The ideal helices prove to be surprisingly effective at solving higher resolution structures, but ab initio-derived search models are able to solve structures that could not be solved with the ideal helices. The addition of evolutionary contact information results in a marked improvement in the modelling and makes additional solutions possible.

Generation of a foveomacular transcriptome

PubMed Central

Bernstein, Steven; Wong, Paul W.

2014-01-01

Purpose Organizing molecular biologic data is a growing challenge since the rate of data accumulation is steadily increasing. Information relevant to a particular biologic query can be difficult to extract from the comprehensive databases currently available. We present a data collection and organization model designed to ameliorate these problems and applied it to generate an expressed sequence tag (EST)–based foveomacular transcriptome. Methods Using Perl, MySQL, EST libraries, screening, and human foveomacular gene expression as a model system, we generated a foveomacular transcriptome database enriched for molecularly relevant data. Results Using foveomacula as a gene expression model tissue, we identified and organized 6,056 genes expressed in that tissue. Of those identified genes, 3,480 had not been previously described as expressed in the foveomacula. Internal experimental controls as well as comparison of our data set to published data sets suggest we do not yet have a complete description of the foveomacula transcriptome. Conclusions We present an organizational method designed to amplify the utility of data pertinent to a specific research interest. Our method is generic enough to be applicable to a variety of conditions yet focused enough to allow for specialized study. PMID:24991187

Anticipatory dynamics of biological systems: from molecular quantum states to evolution

NASA Astrophysics Data System (ADS)

Igamberdiev, Abir U.

2015-08-01

Living systems possess anticipatory behaviour that is based on the flexibility of internal models generated by the system's embedded description. The idea was suggested by Aristotle and is explicitly introduced to theoretical biology by Rosen. The possibility of holding the embedded internal model is grounded in the principle of stable non-equilibrium (Bauer). From the quantum mechanical view, this principle aims to minimize energy dissipation in expense of long relaxation times. The ideas of stable non-equilibrium were developed by Liberman who viewed living systems as subdivided into the quantum regulator and the molecular computer supporting coherence of the regulator's internal quantum state. The computational power of the cell molecular computer is based on the possibility of molecular rearrangements according to molecular addresses. In evolution, the anticipatory strategies are realized both as a precession of phylogenesis by ontogenesis (Berg) and as the anticipatory search of genetic fixation of adaptive changes that incorporates them into the internal model of genetic system. We discuss how the fundamental ideas of anticipation can be introduced into the basic foundations of theoretical biology.

Towards a covariance matrix of CAB model parameters for H(H2O)

NASA Astrophysics Data System (ADS)

Scotta, Juan Pablo; Noguere, Gilles; Damian, José Ignacio Marquez

2017-09-01

Preliminary results on the uncertainties of hydrogen into light water thermal scattering law of the CAB model are presented. It was done through a coupling between the nuclear data code CONRAD and the molecular dynamic simulations code GROMACS. The Generalized Least Square method was used to adjust the model parameters on evaluated data and generate covariance matrices between the CAB model parameters.

Photodynamic therapy: computer modeling of diffusion and reaction phenomena

NASA Astrophysics Data System (ADS)

Hampton, James A.; Mahama, Patricia A.; Fournier, Ronald L.; Henning, Jeffery P.

1996-04-01

We have developed a transient, one-dimensional mathematical model for the reaction and diffusion phenomena that occurs during photodynamic therapy (PDT). This model is referred to as the PDTmodem program. The model is solved by the Crank-Nicholson finite difference technique and can be used to predict the fates of important molecular species within the intercapillary tissue undergoing PDT. The following factors govern molecular oxygen consumption and singlet oxygen generation within a tumor: (1) photosensitizer concentration; (2) fluence rate; and (3) intercapillary spacing. In an effort to maximize direct tumor cell killing, the model allows educated decisions to be made to insure the uniform generation and exposure of singlet oxygen to tumor cells across the intercapillary space. Based on predictions made by the model, we have determined that the singlet oxygen concentration profile within the intercapillary space is controlled by the product of the drug concentration, and light fluence rate. The model predicts that at high levels of this product, within seconds singlet oxygen generation is limited to a small core of cells immediately surrounding the capillary. The remainder of the tumor tissue in the intercapillary space is anoxic and protected from the generation and toxic effects of singlet oxygen. However, at lower values of this product, the PDT-induced anoxic regions are not observed. An important finding is that an optimal value of this product can be defined that maintains the singlet oxygen concentration throughout the intercapillary space at a near constant level. Direct tumor cell killing is therefore postulated to depend on the singlet oxygen exposure, defined as the product of the uniform singlet oxygen concentration and the time of exposure, and not on the total light dose.

Solvation Structure and Thermodynamic Mapping (SSTMap): An Open-Source, Flexible Package for the Analysis of Water in Molecular Dynamics Trajectories.

PubMed

Haider, Kamran; Cruz, Anthony; Ramsey, Steven; Gilson, Michael K; Kurtzman, Tom

2018-01-09

We have developed SSTMap, a software package for mapping structural and thermodynamic water properties in molecular dynamics trajectories. The package introduces automated analysis and mapping of local measures of frustration and enhancement of water structure. The thermodynamic calculations are based on Inhomogeneous Fluid Solvation Theory (IST), which is implemented using both site-based and grid-based approaches. The package also extends the applicability of solvation analysis calculations to multiple molecular dynamics (MD) simulation programs by using existing cross-platform tools for parsing MD parameter and trajectory files. SSTMap is implemented in Python and contains both command-line tools and a Python module to facilitate flexibility in setting up calculations and for automated generation of large data sets involving analysis of multiple solutes. Output is generated in formats compatible with popular Python data science packages. This tool will be used by the molecular modeling community for computational analysis of water in problems of biophysical interest such as ligand binding and protein function.

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.

Massively Parallel Simulations of Diffusion in Dense Polymeric Structures

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

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

1997-11-01

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

Complex molecular assemblies at hand via interactive simulations.

PubMed

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

2009-11-30

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

A DICOM-based 2nd generation Molecular Imaging Data Grid implementing the IHE XDS-i integration profile.

PubMed

Lee, Jasper; Zhang, Jianguo; Park, Ryan; Dagliyan, Grant; Liu, Brent; Huang, H K

2012-07-01

A Molecular Imaging Data Grid (MIDG) was developed to address current informatics challenges in archival, sharing, search, and distribution of preclinical imaging studies between animal imaging facilities and investigator sites. This manuscript presents a 2nd generation MIDG replacing the Globus Toolkit with a new system architecture that implements the IHE XDS-i integration profile. Implementation and evaluation were conducted using a 3-site interdisciplinary test-bed at the University of Southern California. The 2nd generation MIDG design architecture replaces the initial design's Globus Toolkit with dedicated web services and XML-based messaging for dedicated management and delivery of multi-modality DICOM imaging datasets. The Cross-enterprise Document Sharing for Imaging (XDS-i) integration profile from the field of enterprise radiology informatics was adopted into the MIDG design because streamlined image registration, management, and distribution dataflow are likewise needed in preclinical imaging informatics systems as in enterprise PACS application. Implementation of the MIDG is demonstrated at the University of Southern California Molecular Imaging Center (MIC) and two other sites with specified hardware, software, and network bandwidth. Evaluation of the MIDG involves data upload, download, and fault-tolerance testing scenarios using multi-modality animal imaging datasets collected at the USC Molecular Imaging Center. The upload, download, and fault-tolerance tests of the MIDG were performed multiple times using 12 collected animal study datasets. Upload and download times demonstrated reproducibility and improved real-world performance. Fault-tolerance tests showed that automated failover between Grid Node Servers has minimal impact on normal download times. Building upon the 1st generation concepts and experiences, the 2nd generation MIDG system improves accessibility of disparate animal-model molecular imaging datasets to users outside a molecular imaging facility's LAN using a new architecture, dataflow, and dedicated DICOM-based management web services. Productivity and efficiency of preclinical research for translational sciences investigators has been further streamlined for multi-center study data registration, management, and distribution.

The MOLGENIS toolkit: rapid prototyping of biosoftware at the push of a button

PubMed Central

2010-01-01

Background There is a huge demand on bioinformaticians to provide their biologists with user friendly and scalable software infrastructures to capture, exchange, and exploit the unprecedented amounts of new *omics data. We here present MOLGENIS, a generic, open source, software toolkit to quickly produce the bespoke MOLecular GENetics Information Systems needed. Methods The MOLGENIS toolkit provides bioinformaticians with a simple language to model biological data structures and user interfaces. At the push of a button, MOLGENIS’ generator suite automatically translates these models into a feature-rich, ready-to-use web application including database, user interfaces, exchange formats, and scriptable interfaces. Each generator is a template of SQL, JAVA, R, or HTML code that would require much effort to write by hand. This ‘model-driven’ method ensures reuse of best practices and improves quality because the modeling language and generators are shared between all MOLGENIS applications, so that errors are found quickly and improvements are shared easily by a re-generation. A plug-in mechanism ensures that both the generator suite and generated product can be customized just as much as hand-written software. Results In recent years we have successfully evaluated the MOLGENIS toolkit for the rapid prototyping of many types of biomedical applications, including next-generation sequencing, GWAS, QTL, proteomics and biobanking. Writing 500 lines of model XML typically replaces 15,000 lines of hand-written programming code, which allows for quick adaptation if the information system is not yet to the biologist’s satisfaction. Each application generated with MOLGENIS comes with an optimized database back-end, user interfaces for biologists to manage and exploit their data, programming interfaces for bioinformaticians to script analysis tools in R, Java, SOAP, REST/JSON and RDF, a tab-delimited file format to ease upload and exchange of data, and detailed technical documentation. Existing databases can be quickly enhanced with MOLGENIS generated interfaces using the ‘ExtractModel’ procedure. Conclusions The MOLGENIS toolkit provides bioinformaticians with a simple model to quickly generate flexible web platforms for all possible genomic, molecular and phenotypic experiments with a richness of interfaces not provided by other tools. All the software and manuals are available free as LGPLv3 open source at http://www.molgenis.org. PMID:21210979

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

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

Fidiani, Elok

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

Molecular Dynamics Visualization (MDV): Stereoscopic 3D Display of Biomolecular Structure and Interactions Using the Unity Game Engine.

PubMed

Wiebrands, Michael; Malajczuk, Chris J; Woods, Andrew J; Rohl, Andrew L; Mancera, Ricardo L

2018-06-21

Molecular graphics systems are visualization tools which, upon integration into a 3D immersive environment, provide a unique virtual reality experience for research and teaching of biomolecular structure, function and interactions. We have developed a molecular structure and dynamics application, the Molecular Dynamics Visualization tool, that uses the Unity game engine combined with large scale, multi-user, stereoscopic visualization systems to deliver an immersive display experience, particularly with a large cylindrical projection display. The application is structured to separate the biomolecular modeling and visualization systems. The biomolecular model loading and analysis system was developed as a stand-alone C# library and provides the foundation for the custom visualization system built in Unity. All visual models displayed within the tool are generated using Unity-based procedural mesh building routines. A 3D user interface was built to allow seamless dynamic interaction with the model while being viewed in 3D space. Biomolecular structure analysis and display capabilities are exemplified with a range of complex systems involving cell membranes, protein folding and lipid droplets.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

Use of molecular modeling to determine the interaction and competition of gases within coal for carbon dioxide sequestration

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

Jeffrey D. Evanseck; Jeffry D. Madura; Jonathan P. Mathews

2006-04-21

Molecular modeling was employed to both visualize and probe our understanding of carbon dioxide sequestration within a bituminous coal. A large-scale (>20,000 atoms) 3D molecular representation of Pocahontas No. 3 coal was generated. This model was constructed based on a the review data of Stock and Muntean, oxidation and decarboxylation data for aromatic clustersize frequency of Stock and Obeng, and the combination of Laser Desorption Mass Spectrometry data with HRTEM, enabled the inclusion of a molecular weight distribution. The model contains 21,931 atoms, with a molecular mass of 174,873 amu, and an average molecular weight of 714 amu, with 201more » structural components. The structure was evaluated based on several characteristics to ensure a reasonable constitution (chemical and physical representation). The helium density of Pocahontas No. 3 coal is 1.34 g/cm{sup 3} (dmmf) and the model was 1.27 g/cm{sup 3}. The structure is microporous, with a pore volume comprising 34% of the volume as expected for a coal of this rank. The representation was used to visualize CO{sub 2}, and CH{sub 4} capacity, and the role of moisture in swelling and CO{sub 2}, and CH{sub 4} capacity reduction. Inclusion of 0.68% moisture by mass (ash-free) enabled the model to swell by 1.2% (volume). Inclusion of CO{sub 2} enabled volumetric swelling of 4%.« less

Molecular Modeling of Nucleic Acid Structure: Electrostatics and Solvation

PubMed Central

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

2014-01-01

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

Molecular modeling of nucleic Acid structure: electrostatics and solvation.

PubMed

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

2014-12-19

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

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

PubMed

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

Modeling molecular mechanisms in the axon

NASA Astrophysics Data System (ADS)

de Rooij, R.; Miller, K. E.; Kuhl, E.

2017-03-01

Axons are living systems that display highly dynamic changes in stiffness, viscosity, and internal stress. However, the mechanistic origin of these phenomenological properties remains elusive. Here we establish a computational mechanics model that interprets cellular-level characteristics as emergent properties from molecular-level events. We create an axon model of discrete microtubules, which are connected to neighboring microtubules via discrete crosslinking mechanisms that obey a set of simple rules. We explore two types of mechanisms: passive and active crosslinking. Our passive and active simulations suggest that the stiffness and viscosity of the axon increase linearly with the crosslink density, and that both are highly sensitive to the crosslink detachment and reattachment times. Our model explains how active crosslinking with dynein motors generates internal stresses and actively drives axon elongation. We anticipate that our model will allow us to probe a wide variety of molecular phenomena—both in isolation and in interaction—to explore emergent cellular-level features under physiological and pathological conditions.

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

ERIC Educational Resources Information Center

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

2009-01-01

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

Young’s modulus calculations for cellulose Iß by MM3 and quantum mechanics

USDA-ARS?s Scientific Manuscript database

Quantum mechanics (QM) and molecular mechanics (MM) calculations were performed to elucidate Young’s moduli for a series of cellulose Iß models. Computations using the second generation empirical force field MM3 with a disaccharide cellulose model, 1,4'-O-dimethyl-ß-cellobioside (DMCB), and an analo...

Low-Volatility Model Demonstrates Humidity Affects Environmental Toxin Deposition on Plastics at a Molecular Level.

PubMed

Hankett, Jeanne M; Collin, William R; Yang, Pei; Chen, Zhan; Duhaime, Melissa

2016-02-02

Despite the ever-increasing prevalence of plastic debris and endocrine disrupting toxins in aquatic ecosystems, few studies describe their interactions in freshwater environments. We present a model system to investigate the deposition/desorption behaviors of low-volatility lake ecosystem toxins on microplastics in situ and in real time. Molecular interactions of gas-phase nonylphenols (NPs) with the surfaces of two common plastics, poly(styrene) and poly(ethylene terephthalate), were studied using quartz crystal microbalance and sum frequency generation vibrational spectroscopy. NP point sources were generated under two model environments: plastic on land and plastic on a freshwater surface. We found the headspace above calm water provides an excellent environment for NP deposition and demonstrate significant NP deposition on plastic within minutes at relevant concentrations. Further, NP deposits and orders differently on both plastics under humid versus dry environments. We attributed the unique deposition behaviors to surface energy changes from increased water content during the humid deposition. Lastly, nanograms of NP remained on microplastic surfaces hours after initial NP introduction and agitating conditions, illustrating feasibility for plastic-bound NPs to interact with biota and surrounding matter. Our model studies reveal important interactions between low-volatility environmental toxins and microplastics and hold potential to correlate the environmental fate of endocrine disrupting toxins in the Great Lakes with molecular behaviors.

In situ sum-frequency generation spectroscopy of ethylene-glycol and poly-N-isopropylacrylamide films

NASA Astrophysics Data System (ADS)

Kurz, Volker; Koelsch, Patrick

2009-03-01

Ethylene-glycol(EG)-based self-assembled monolayers (SAMs) are often used as a model systems for thin liquid films. Temperature series in heavy water were measured using a unique sample cell developed for in situ sum-frequency generation (SFG) spectroscopy experiments. Results obtained from model EG-SAMs with different lengths and terminating groups in various ionic solutions showed temperature-dependent changes in the molecular order. Films of poly-N-isopropylacrylamide(pNIPAM) were also characterized by in situ SFG spectroscopy in the CH, OH, OD and amide spectral regions under different polarization combinations. These systems have many applications as thermo-responsive polymers due to their ability to change solubility in water at the biologically relevant temperature of 32 C. This so-called lower critical solution temperature (LCST) phase transition was characterized in depth, allowing for the identification of the molecular groups involved in this process.

Classical Molecular Dynamics Simulation of Nuclear Fuel

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

Devanathan, Ram; Krack, Matthias; Bertolus, Marjorie

2015-10-10

Molecular dynamics simulation is well suited to study primary damage production by irradiation, defect interactions with fission gas atoms, gas bubble nucleation, grain boundary effects on defect and gas bubble evolution in nuclear fuel, and the resulting changes in thermo-mechanical properties. In these simulations, the forces on the ions are dictated by interaction potentials generated by fitting properties of interest to experimental data. The results obtained from the present generation of potentials are qualitatively similar, but quantitatively different. There is a need to refine existing potentials to provide a better representation of the performance of polycrystalline fuel under a varietymore » of operating conditions, and to develop models that are equipped to handle deviations from stoichiometry. In addition to providing insights into fundamental mechanisms governing the behaviour of nuclear fuel, MD simulations can also provide parameters that can be used as inputs for mesoscale models.« less

Macro and micro analysis of small molecule diffusion in amorphous polymers

NASA Astrophysics Data System (ADS)

Putta, Santosh Krishna

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

Molecular and functional assessment of multicellular cancer spheroids produced in double emulsions enabled by efficient airway resistance based selective surface treatment

NASA Astrophysics Data System (ADS)

Ma, Xiao; Leth Jepsen, Morten; Ivarsen, Anne Kathrine R.; Knudsen, Birgitta R.; Ho, Yi-Ping

2017-09-01

Multicellular spheroids have garnered significant attention as an in vitro three-dimensional cancer model which can mimick the in vivo microenvironmental features. While microfluidics generated double emulsions have become a potential method to generate spheroids, challenges remain on the tedious procedures. Enabled by a novel ‘airway resistance’ based selective surface treatment, this study presents an easy and facile generation of double emulsions for the initiation and cultivation of multicellular spheroids in a scaffold-free format. Combining with our previously developed DNA nanosensors, intestinal spheroids produced in the double emulsions have shown an elevated activities of an essential DNA modifying enzyme, the topoisomerase I. The observed molecular and functional characteristics of spheroids produced in double emulsions are similar to the counterparts produced by the commercially available ultra-low attachment plates. However, the double emulsions excel for their improved uniformity, and the consistency of the results obtained by subsequent analysis of the spheroids. The presented technique is expected to ease the burden of producing spheroids and to promote the spheroids model for cancer or stem cell study.

Numerical studies from quantum to macroscopic scales of carbon nanoparticules in hydrogen plasma

NASA Astrophysics Data System (ADS)

Lombardi, Guillaume; Ngandjong, Alain; Mezei, Zsolt; Mougenot, Jonathan; Michau, Armelle; Hassouni, Khaled; Seydou, Mahamadou; Maurel, François

2016-09-01

Dusty plasmas take part in large scientific domains from Universe Science to nanomaterial synthesis processes. They are often generated by growth from molecular precursor. This growth leads to the formation of larger clusters which induce solid germs nucleation. Particle formed are described by an aerosol dynamic taking into account coagulation, molecular deposition and transport processes. These processes are controlled by the elementary particle. So there is a strong coupling between particle dynamics and plasma discharge equilibrium. This study is focused on the development of a multiscale physic and numeric model of hydrogen plasmas and carbon particles around three essential coupled axes to describe the various physical phenomena: (i) Macro/mesoscopic fluid modeling describing in an auto-coherent way, characteristics of the plasma, molecular clusters and aerosol behavior; (ii) the classic molecular dynamics offering a description to the scale molecular of the chains of chemical reactions and the phenomena of aggregation; (iii) the quantum chemistry to establish the activation barriers of the different processes driving the nanopoarticule formation.

Transitioning NWChem to the Next Generation of Manycore Machines

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

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

The NorthWest Chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers[6, 28, 49]. It contains an umbrella of modules that today includes Self Consistent Field (SCF), second order Mller-Plesset perturbation theory (MP2), Coupled Cluster, multi-conguration selfconsistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics, Car-Parrinello molecular dynamics, classical molecular dynamics (MD), QM/MM,more » AIMD/MM, GIAO NMR, COSMO, COSMO-SMD, and RISM solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities[ 22]. Moreover new capabilities continue to be added with each new release.« less

Multiple templates-based homology modeling enhances structure quality of AT1 receptor: validation by molecular dynamics and antagonist docking.

PubMed

Sokkar, Pandian; Mohandass, Shylajanaciyar; Ramachandran, Murugesan

2011-07-01

We present a comparative account on 3D-structures of human type-1 receptor (AT1) for angiotensin II (AngII), modeled using three different methodologies. AngII activates a wide spectrum of signaling responses via the AT1 receptor that mediates physiological control of blood pressure and diverse pathological actions in cardiovascular, renal, and other cell types. Availability of 3D-model of AT1 receptor would significantly enhance the development of new drugs for cardiovascular diseases. However, templates of AT1 receptor with low sequence similarity increase the complexity in straightforward homology modeling, and hence there is a need to evaluate different modeling methodologies in order to use the models for sensitive applications such as rational drug design. Three models were generated for AT1 receptor by, (1) homology modeling with bovine rhodopsin as template, (2) homology modeling with multiple templates and (3) threading using I-TASSER web server. Molecular dynamics (MD) simulation (15 ns) of models in explicit membrane-water system, Ramachandran plot analysis and molecular docking with antagonists led to the conclusion that multiple template-based homology modeling outweighs other methodologies for AT1 modeling.

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

DOEpatents

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

2013-02-05

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

The Hydra model - a model for what?

PubMed

Gierer, Alfred

2012-01-01

The introductory personal remarks refer to my motivations for choosing research projects, and for moving from physics to molecular biology and then to development, with Hydra as a model system. Historically, Trembley's discovery of Hydra regeneration in 1744 was the beginning of developmental biology as we understand it, with passionate debates about preformation versus de novo generation, mechanisms versus organisms. In fact, seemingly conflicting bottom-up and top-down concepts are both required in combination to understand development. In modern terms, this means analysing the molecules involved, as well as searching for physical principles underlying development within systems of molecules, cells and tissues. During the last decade, molecular biology has provided surprising and impressive evidence that the same types of molecules and molecular systems are involved in pattern formation in a wide range of organisms, including coelenterates like Hydra, and thus appear to have been "invented" early in evolution. Likewise, the features of certain systems, especially those of developmental regulation, are found in many different organisms. This includes the generation of spatial structures by the interplay of self-enhancing activation and "lateral" inhibitory effects of wider range, which is a main topic of my essay. Hydra regeneration is a particularly clear model for the formation of defined patterns within initially near-uniform tissues. In conclusion, this essay emphasizes the analysis of development in terms of physical laws, including the application of mathematics, and insists that Hydra was, and will continue to be, a rewarding model for understanding general features of embryogenesis and regeneration.

Structure–property reduced order model for viscosity prediction in single-component CO 2 -binding organic liquids

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

Cantu, David C.; Malhotra, Deepika; Koech, Phillip K.

2016-01-01

CO2 capture from power generation with aqueous solvents remains energy intensive due to the high water content of the current technology, or the high viscosity of non-aqueous alternatives. Quantitative reduced models, connecting molecular structure to bulk properties, are key for developing structure-property relationships that enable molecular design. In this work, we describe such a model that quantitatively predicts viscosities of CO2 binding organic liquids (CO2BOLs) based solely on molecular structure and the amount of bound CO2. The functional form of the model correlates the viscosity with the CO2 loading and an electrostatic term describing the charge distribution between the CO2-bearingmore » functional group and the proton-receiving amine. Molecular simulations identify the proton shuttle between these groups within the same molecule to be the critical indicator of low viscosity. The model, developed to allow for quick screening of solvent libraries, paves the way towards the rational design of low viscosity non-aqueous solvent systems for post-combustion CO2 capture. Following these theoretical recommendations, synthetic efforts of promising candidates and viscosity measurement provide experimental validation and verification.« less

Establishment of Patient-Derived Tumor Xenograft Models of Epithelial Ovarian Cancer for Preclinical Evaluation of Novel Therapeutics.

PubMed

Liu, Joyce F; Palakurthi, Sangeetha; Zeng, Qing; Zhou, Shan; Ivanova, Elena; Huang, Wei; Zervantonakis, Ioannis K; Selfors, Laura M; Shen, Yiping; Pritchard, Colin C; Zheng, Mei; Adleff, Vilmos; Papp, Eniko; Piao, Huiying; Novak, Marian; Fotheringham, Susan; Wulf, Gerburg M; English, Jessie; Kirschmeier, Paul T; Velculescu, Victor E; Paweletz, Cloud; Mills, Gordon B; Livingston, David M; Brugge, Joan S; Matulonis, Ursula A; Drapkin, Ronny

2017-03-01

Purpose: Ovarian cancer is the leading cause of death from gynecologic malignancy in the United States, with high rates of recurrence and eventual resistance to cytotoxic chemotherapy. Model systems that allow for accurate and reproducible target discovery and validation are needed to support further drug development in this disease. Experimental Design: Clinically annotated patient-derived xenograft (PDX) models were generated from tumor cells isolated from the ascites or pleural fluid of patients undergoing clinical procedures. Models were characterized by IHC and by molecular analyses. Each PDX was luciferized to allow for reproducible in vivo assessment of intraperitoneal tumor burden by bioluminescence imaging (BLI). Plasma assays for CA125 and human LINE-1 were developed as secondary tests of in vivo disease burden. Results: Fourteen clinically annotated and molecularly characterized luciferized ovarian PDX models were generated. Luciferized PDX models retain fidelity to both the nonluciferized PDX and the original patient tumor, as demonstrated by IHC, array CGH, and targeted and whole-exome sequencing analyses. Models demonstrated diversity in specific genetic alterations and activation of PI3K signaling pathway members. Response of luciferized PDX models to standard-of-care therapy could be reproducibly monitored by BLI or plasma markers. Conclusions: We describe the establishment of a collection of 14 clinically annotated and molecularly characterized luciferized ovarian PDX models in which orthotopic tumor burden in the intraperitoneal space can be followed by standard and reproducible methods. This collection is well suited as a platform for proof-of-concept efficacy and biomarker studies and for validation of novel therapeutic strategies in ovarian cancer. Clin Cancer Res; 23(5); 1263-73. ©2016 AACR . ©2016 American Association for Cancer Research.

Cumulative atomic multipole moments complement any atomic charge model to obtain more accurate electrostatic properties

NASA Technical Reports Server (NTRS)

Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.

1992-01-01

The quality of several atomic charge models based on different definitions has been analyzed using cumulative atomic multipole moments (CAMM). This formalism can generate higher atomic moments starting from any atomic charges, while preserving the corresponding molecular moments. The atomic charge contribution to the higher molecular moments, as well as to the electrostatic potentials, has been examined for CO and HCN molecules at several different levels of theory. The results clearly show that the electrostatic potential obtained from CAMM expansion is convergent up to R-5 term for all atomic charge models used. This illustrates that higher atomic moments can be used to supplement any atomic charge model to obtain more accurate description of electrostatic properties.

Neural network error correction for solving coupled ordinary differential equations

NASA Technical Reports Server (NTRS)

Shelton, R. O.; Darsey, J. A.; Sumpter, B. G.; Noid, D. W.

1992-01-01

A neural network is presented to learn errors generated by a numerical algorithm for solving coupled nonlinear differential equations. The method is based on using a neural network to correctly learn the error generated by, for example, Runge-Kutta on a model molecular dynamics (MD) problem. The neural network programs used in this study were developed by NASA. Comparisons are made for training the neural network using backpropagation and a new method which was found to converge with fewer iterations. The neural net programs, the MD model and the calculations are discussed.

Generation of Comprehensive Surrogate Kinetic Models and Validation Databases for Simulating Large Molecular Weight Hydrocarbon Fuels

DTIC Science & Technology

2012-10-25

of hydrogen/ carbon molar ratio (H/C), derived cetane number (DCN), threshold sooting index (TSI), and average mean molecular weight (MWave) of...diffusive soot extinction configurations. Matching the “real fuel combustion property targets” of hydrogen/ carbon molar ratio (H/C), derived cetane number...combustion property targets - hydrogen/ carbon molar ratio (H/C), derived cetane number (DCN), threshold sooting index (TSI), and average mean

Molecular-level Simulations of Shock Generation and Propagation in Polyurea

DTIC Science & Technology

2011-01-26

homepage: www.e lsev ier .com/ locate /msea Molecular-level simulations of shock generation and propagation in polyurea M. Grujicica,∗, B. Pandurangana... Polyurea Shock-wave generation and propagation Molecular-level calculations a b s t r a c t A non-equilibrium molecular dynamics method is employed in order...to study various phenomena accompanying the generation and propagation of shock waves in polyurea (a micro-phase segregated elastomer). Several

High-resolution modeling of antibody structures by a combination of bioinformatics, expert knowledge, and molecular simulations.

PubMed

Shirai, Hiroki; Ikeda, Kazuyoshi; Yamashita, Kazuo; Tsuchiya, Yuko; Sarmiento, Jamica; Liang, Shide; Morokata, Tatsuaki; Mizuguchi, Kenji; Higo, Junichi; Standley, Daron M; Nakamura, Haruki

2014-08-01

In the second antibody modeling assessment, we used a semiautomated template-based structure modeling approach for 11 blinded antibody variable region (Fv) targets. The structural modeling method involved several steps, including template selection for framework and canonical structures of complementary determining regions (CDRs), homology modeling, energy minimization, and expert inspection. The submitted models for Fv modeling in Stage 1 had the lowest average backbone root mean square deviation (RMSD) (1.06 Å). Comparison to crystal structures showed the most accurate Fv models were generated for 4 out of 11 targets. We found that the successful modeling in Stage 1 mainly was due to expert-guided template selection for CDRs, especially for CDR-H3, based on our previously proposed empirical method (H3-rules) and the use of position specific scoring matrix-based scoring. Loop refinement using fragment assembly and multicanonical molecular dynamics (McMD) was applied to CDR-H3 loop modeling in Stage 2. Fragment assembly and McMD produced putative structural ensembles with low free energy values that were scored based on the OSCAR all-atom force field and conformation density in principal component analysis space, respectively, as well as the degree of consensus between the two sampling methods. The quality of 8 out of 10 targets improved as compared with Stage 1. For 4 out of 10 Stage-2 targets, our method generated top-scoring models with RMSD values of less than 1 Å. In this article, we discuss the strengths and weaknesses of our approach as well as possible directions for improvement to generate better predictions in the future. © 2014 Wiley Periodicals, Inc.

Assembly of bipolar microtubule structures by passive cross-linkers and molecular motors

NASA Astrophysics Data System (ADS)

Johann, D.; Goswami, D.; Kruse, K.

2016-06-01

During cell division, sister chromatids are segregated by the mitotic spindle, a bipolar assembly of interdigitating antiparallel polar filaments called microtubules. The spindle contains the midzone, a stable region of overlapping antiparallel microtubules, that is essential for maintaining bipolarity. Although a lot is known about the molecular players involved, the mechanism underlying midzone formation and maintenance is still poorly understood. We study the interaction of polar filaments that are cross-linked by molecular motors moving directionally and by passive cross-linkers diffusing along microtubules. Using a particle-based stochastic model, we find that the interplay of motors and passive cross-linkers can generate a stable finite overlap between a pair of antiparallel polar filaments. We develop a mean-field theory to study this mechanism in detail and investigate the influence of steric interactions between motors and passive cross-linkers on the overlap dynamics. In the presence of interspecies steric interactions, passive cross-linkers mimic the behavior of molecular motors and stable finite overlaps are generated even for non-cross-linking motors. Finally, we develop a mean-field theory for a bundle of aligned polar filaments and show that they can self-organize into a spindlelike pattern. Our work suggests possible ways as to how cells can generate spindle midzones and control their extensions.

Systematic Analysis of Challenge-Driven Improvements in Molecular Prognostic Models for Breast Cancer

PubMed Central

Margolin, Adam A.; Bilal, Erhan; Huang, Erich; Norman, Thea C.; Ottestad, Lars; Mecham, Brigham H.; Sauerwine, Ben; Kellen, Michael R.; Mangravite, Lara M.; Furia, Matthew D.; Vollan, Hans Kristian Moen; Rueda, Oscar M.; Guinney, Justin; Deflaux, Nicole A.; Hoff, Bruce; Schildwachter, Xavier; Russnes, Hege G.; Park, Daehoon; Vang, Veronica O.; Pirtle, Tyler; Youseff, Lamia; Citro, Craig; Curtis, Christina; Kristensen, Vessela N.; Hellerstein, Joseph; Friend, Stephen H.; Stolovitzky, Gustavo; Aparicio, Samuel; Caldas, Carlos; Børresen-Dale, Anne-Lise

2013-01-01

Although molecular prognostics in breast cancer are among the most successful examples of translating genomic analysis to clinical applications, optimal approaches to breast cancer clinical risk prediction remain controversial. The Sage Bionetworks–DREAM Breast Cancer Prognosis Challenge (BCC) is a crowdsourced research study for breast cancer prognostic modeling using genome-scale data. The BCC provided a community of data analysts with a common platform for data access and blinded evaluation of model accuracy in predicting breast cancer survival on the basis of gene expression data, copy number data, and clinical covariates. This approach offered the opportunity to assess whether a crowdsourced community Challenge would generate models of breast cancer prognosis commensurate with or exceeding current best-in-class approaches. The BCC comprised multiple rounds of blinded evaluations on held-out portions of data on 1981 patients, resulting in more than 1400 models submitted as open source code. Participants then retrained their models on the full data set of 1981 samples and submitted up to five models for validation in a newly generated data set of 184 breast cancer patients. Analysis of the BCC results suggests that the best-performing modeling strategy outperformed previously reported methods in blinded evaluations; model performance was consistent across several independent evaluations; and aggregating community-developed models achieved performance on par with the best-performing individual models. PMID:23596205

Molecular alignment and orientation with a hybrid Raman scattering technique

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

A Simple Computer-Aided Three-Dimensional Molecular Modeling for the Octant Rule

ERIC Educational Resources Information Center

Kang, Yinan; Kang, Fu-An

2011-01-01

The Moffitt-Woodward-Moscowitz-Klyne-Djerassi octant rule is one of the most successful empirical rules in organic chemistry. However, the lack of a simple effective modeling method for the octant rule in the past 50 years has posed constant difficulties for researchers, teachers, and students, particularly the young generations, to learn and…

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

PubMed

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

2017-10-01

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

Powering a burnt bridges Brownian ratchet: a model for an extracellular motor driven by proteolysis of collagen.

PubMed

Saffarian, Saveez; Qian, Hong; Collier, Ivan; Elson, Elliot; Goldberg, Gregory

2006-04-01

Biased diffusion of collagenase on collagen fibrils may represent the first observed adenosine triphosphate-independent extracellular molecular motor. The magnitude of force generated by the enzyme remains unclear. We propose a propulsion mechanism based on a burnt bridges Brownian ratchet model with a varying degree of coupling of the free energy from collagen proteolysis to the enzyme motion. When constrained by experimental observations, our model predicts 0.1 pN stall force for individual collagenase molecules. A dimer, surprisingly, can generate a force in the range of 5 pN, suggesting that the motor can be of biological significance.

Highly Efficient Computation of the Basal kon using Direct Simulation of Protein-Protein Association with Flexible Molecular Models.

PubMed

Saglam, Ali S; Chong, Lillian T

2016-01-14

An essential baseline for determining the extent to which electrostatic interactions enhance the kinetics of protein-protein association is the "basal" kon, which is the rate constant for association in the absence of electrostatic interactions. However, since such association events are beyond the milliseconds time scale, it has not been practical to compute the basal kon by directly simulating the association with flexible models. Here, we computed the basal kon for barnase and barstar, two of the most rapidly associating proteins, using highly efficient, flexible molecular simulations. These simulations involved (a) pseudoatomic protein models that reproduce the molecular shapes, electrostatic, and diffusion properties of all-atom models, and (b) application of the weighted ensemble path sampling strategy, which enhanced the efficiency of generating association events by >130-fold. We also examined the extent to which the computed basal kon is affected by inclusion of intermolecular hydrodynamic interactions in the simulations.

Prospective Molecular Profiling of Canine Cancers Provides a Clinically Relevant Comparative Model for Evaluating Personalized Medicine (PMed) Trials

PubMed Central

Mazcko, Christina; Cherba, David; Hendricks, William; Lana, Susan; Ehrhart, E. J.; Charles, Brad; Fehling, Heather; Kumar, Leena; Vail, David; Henson, Michael; Childress, Michael; Kitchell, Barbara; Kingsley, Christopher; Kim, Seungchan; Neff, Mark; Davis, Barbara

2014-01-01

Background Molecularly-guided trials (i.e. PMed) now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting. Methodology A proof-of-concept study was conducted by the Comparative Oncology Trials Consortium (COTC) to determine if tumor collection, prospective molecular profiling, and PMed report generation within 1 week was feasible in dogs. Thirty-one dogs with cancers of varying histologies were enrolled. Twenty-four of 31 samples (77%) successfully met all predefined QA/QC criteria and were analyzed via Affymetrix gene expression profiling. A subsequent bioinformatics workflow transformed genomic data into a personalized drug report. Average turnaround from biopsy to report generation was 116 hours (4.8 days). Unsupervised clustering of canine tumor expression data clustered by cancer type, but supervised clustering of tumors based on the personalized drug report clustered by drug class rather than cancer type. Conclusions Collection and turnaround of high quality canine tumor samples, centralized pathology, analyte generation, array hybridization, and bioinformatic analyses matching gene expression to therapeutic options is achievable in a practical clinical window (<1 week). Clustering data show robust signatures by cancer type but also showed patient-to-patient heterogeneity in drug predictions. This lends further support to the inclusion of a heterogeneous population of dogs with cancer into the preclinical modeling of personalized medicine. Future comparative oncology studies optimizing the delivery of PMed strategies may aid cancer drug development. PMID:24637659

Prospective molecular profiling of canine cancers provides a clinically relevant comparative model for evaluating personalized medicine (PMed) trials.

PubMed

Paoloni, Melissa; Webb, Craig; Mazcko, Christina; Cherba, David; Hendricks, William; Lana, Susan; Ehrhart, E J; Charles, Brad; Fehling, Heather; Kumar, Leena; Vail, David; Henson, Michael; Childress, Michael; Kitchell, Barbara; Kingsley, Christopher; Kim, Seungchan; Neff, Mark; Davis, Barbara; Khanna, Chand; Trent, Jeffrey

2014-01-01

Molecularly-guided trials (i.e. PMed) now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting. A proof-of-concept study was conducted by the Comparative Oncology Trials Consortium (COTC) to determine if tumor collection, prospective molecular profiling, and PMed report generation within 1 week was feasible in dogs. Thirty-one dogs with cancers of varying histologies were enrolled. Twenty-four of 31 samples (77%) successfully met all predefined QA/QC criteria and were analyzed via Affymetrix gene expression profiling. A subsequent bioinformatics workflow transformed genomic data into a personalized drug report. Average turnaround from biopsy to report generation was 116 hours (4.8 days). Unsupervised clustering of canine tumor expression data clustered by cancer type, but supervised clustering of tumors based on the personalized drug report clustered by drug class rather than cancer type. Collection and turnaround of high quality canine tumor samples, centralized pathology, analyte generation, array hybridization, and bioinformatic analyses matching gene expression to therapeutic options is achievable in a practical clinical window (<1 week). Clustering data show robust signatures by cancer type but also showed patient-to-patient heterogeneity in drug predictions. This lends further support to the inclusion of a heterogeneous population of dogs with cancer into the preclinical modeling of personalized medicine. Future comparative oncology studies optimizing the delivery of PMed strategies may aid cancer drug development.

Atomic-like high-harmonic generation from two-dimensional materials.

PubMed

Tancogne-Dejean, Nicolas; Rubio, Angel

2018-02-01

The generation of high-order harmonics from atomic and molecular gases enables the production of high-energy photons and ultrashort isolated pulses. Obtaining efficiently similar photon energy from solid-state systems could lead, for instance, to more compact extreme ultraviolet and soft x-ray sources. We demonstrate from ab initio simulations that it is possible to generate high-order harmonics from free-standing monolayer materials, with an energy cutoff similar to that of atomic and molecular gases. In the limit in which electrons are driven by the pump laser perpendicularly to the monolayer, they behave qualitatively the same as the electrons responsible for high-harmonic generation (HHG) in atoms, where their trajectories are described by the widely used semiclassical model, and exhibit real-space trajectories similar to those of the atomic case. Despite the similarities, the first and last steps of the well-established three-step model for atomic HHG are remarkably different in the two-dimensional materials from gases. Moreover, we show that the electron-electron interaction plays an important role in harmonic generation from monolayer materials because of strong local-field effects, which modify how the material is ionized. The recombination of the accelerated electron wave packet is also found to be modified because of the infinite extension of the material in the monolayer plane, thus leading to a more favorable wavelength scaling of the harmonic yield than in atomic HHG. Our results establish a novel and efficient way of generating high-order harmonics based on a solid-state device, with an energy cutoff and a more favorable wavelength scaling of the harmonic yield similar to those of atomic and molecular gases. Two-dimensional materials offer a unique platform where both bulk and atomic HHG can be investigated, depending on the angle of incidence. Devices based on two-dimensional materials can extend the limit of existing sources.

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

NASA Astrophysics Data System (ADS)

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

2010-09-01

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

QSRR modeling for the chromatographic retention behavior of some β-lactam antibiotics using forward and firefly variable selection algorithms coupled with multiple linear regression.

PubMed

Fouad, Marwa A; Tolba, Enas H; El-Shal, Manal A; El Kerdawy, Ahmed M

2018-05-11

The justified continuous emerging of new β-lactam antibiotics provokes the need for developing suitable analytical methods that accelerate and facilitate their analysis. A face central composite experimental design was adopted using different levels of phosphate buffer pH, acetonitrile percentage at zero time and after 15 min in a gradient program to obtain the optimum chromatographic conditions for the elution of 31 β-lactam antibiotics. Retention factors were used as the target property to build two QSRR models utilizing the conventional forward selection and the advanced nature-inspired firefly algorithm for descriptor selection, coupled with multiple linear regression. The obtained models showed high performance in both internal and external validation indicating their robustness and predictive ability. Williams-Hotelling test and student's t-test showed that there is no statistical significant difference between the models' results. Y-randomization validation showed that the obtained models are due to significant correlation between the selected molecular descriptors and the analytes' chromatographic retention. These results indicate that the generated FS-MLR and FFA-MLR models are showing comparable quality on both the training and validation levels. They also gave comparable information about the molecular features that influence the retention behavior of β-lactams under the current chromatographic conditions. We can conclude that in some cases simple conventional feature selection algorithm can be used to generate robust and predictive models comparable to that are generated using advanced ones. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification of the Molecular Clockwork of the Oyster Crassostrea gigas

PubMed Central

Perrigault, Mickael; Tran, Damien

2017-01-01

Molecular clock system constitutes the origin of biological rhythms that allow organisms to anticipate cyclic environmental changes and adapt their behavior and physiology. Components of the molecular clock are largely conserved across a broad range of species but appreciable diversity in clock structure and function is also present especially in invertebrates. The present work aimed at identify and characterize molecular clockwork components in relationship with the monitoring of valve activity behavior in the oyster Crassostrea gigas. Results provided the characterization of most of canonical clock gene including clock, bmal/cycle, period, timeless, vertebrate-type cry, rev-erb, ror as well as other members of the cryptochrome/photolyase family (plant-like cry, 6–4 photolyase). Analyses of transcriptional variations of clock candidates in oysters exposed to light / dark regime and to constant darkness led to the generation of a putative and original clockwork model in C. gigas, intermediate of described systems in vertebrates and insects. This study is the first characterization of a mollusk clockwork. It constitutes essential bases to understand interactions of the different components of the molecular clock in C. gigas as well as the global mechanisms associated to the generation and the synchronization of biological rhythms in oysters. PMID:28072861

Molecular shear heating and vortex dynamics in thermostatted two dimensional Yukawa liquids

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

Gupta, Akanksha; Ganesh, Rajaraman, E-mail: ganesh@ipr.res.in; Joy, Ashwin

2016-07-15

It is well known that two-dimensional macroscale shear flows are susceptible to instabilities leading to macroscale vortical structures. The linear and nonlinear fate of such a macroscale flow in a strongly coupled medium is a fundamental problem. A popular example of a strongly coupled medium is a dusty plasma, often modelled as a Yukawa liquid. Recently, laboratory experiments and molecular dynamics (MD) studies of shear flows in strongly coupled Yukawa liquids indicated the occurrence of strong molecular shear heating, which is found to reduce the coupling strength exponentially leading to the destruction of macroscale vorticity. To understand the vortex dynamicsmore » of strongly coupled molecular fluids undergoing macroscale shear flows and molecular shear heating, MD simulation has been performed, which allows the macroscopic vortex dynamics to evolve, while at the same time “removes” the microscopically generated heat without using the velocity degrees of freedom. We demonstrate that by using a configurational thermostat in a novel way, the microscale heat generated by shear flow can be thermostatted out efficiently without compromising the large scale vortex dynamics. In the present work, using MD simulations, a comparative study of shear flow evolution in Yukawa liquids in the presence and absence of molecular or microscopic heating is presented for a prototype shear flow, namely, Kolmogorov flow.« less

QSPR modeling: graph connectivity indices versus line graph connectivity indices

PubMed

Basak; Nikolic; Trinajstic; Amic; Beslo

2000-07-01

Five QSPR models of alkanes were reinvestigated. Properties considered were molecular surface-dependent properties (boiling points and gas chromatographic retention indices) and molecular volume-dependent properties (molar volumes and molar refractions). The vertex- and edge-connectivity indices were used as structural parameters. In each studied case we computed connectivity indices of alkane trees and alkane line graphs and searched for the optimum exponent. Models based on indices with an optimum exponent and on the standard value of the exponent were compared. Thus, for each property we generated six QSPR models (four for alkane trees and two for the corresponding line graphs). In all studied cases QSPR models based on connectivity indices with optimum exponents have better statistical characteristics than the models based on connectivity indices with the standard value of the exponent. The comparison between models based on vertex- and edge-connectivity indices gave in two cases (molar volumes and molar refractions) better models based on edge-connectivity indices and in three cases (boiling points for octanes and nonanes and gas chromatographic retention indices) better models based on vertex-connectivity indices. Thus, it appears that the edge-connectivity index is more appropriate to be used in the structure-molecular volume properties modeling and the vertex-connectivity index in the structure-molecular surface properties modeling. The use of line graphs did not improve the predictive power of the connectivity indices. Only in one case (boiling points of nonanes) a better model was obtained with the use of line graphs.

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations.

PubMed

Saxena, Shalini; Abdullah, Maaged; Sriram, Dharmarajan; Guruprasad, Lalitha

2017-10-17

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.

Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation.

PubMed

Liu, Xiaofeng; Bai, Fang; Ouyang, Sisheng; Wang, Xicheng; Li, Honglin; Jiang, Hualiang

2009-03-31

Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105-112). Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 A to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 +/- 0.18 seconds per molecule) renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of reproducing the bioactive conformations against 329 structures. The speed advantage indicates Cyndi is a powerful alternative method for extensive conformational sampling and large-scale conformer database preparation.

Current's Fluctuations through Molecular Wires Composed of Thiophene Rings.

PubMed

Ojeda Silva, Judith Helena; Cortés Peñaranda, Juan Camilo; Gómez Castaño, Jovanny A; Duque, Carlos Alberto

2018-04-11

We study theoretically the electronic transport and quantum fluctuations in single-molecule systems using thiophene rings as integrated elementary functions, as well as the dependence of these properties with the increase of the coupled rings, i.e., as a quantum wire. In order to analyze the current flow through these molecular systems, the thiophene rings are considered to be connected to metal contacts, which, in general terms, will be related to the application of voltages (bias voltages or gate voltages) to generate non-equilibrium behavior between the contacts. Due to the nonlinear behavior that is generated when said voltages are applied, it is possible to observe quantum fluctuations in the transport properties of these molecular wires. For the calculation of the transport properties, we applied a tight-binding approach using the Landauer-Büttiker formalism and the Fischer-Lee relationship, by means of a semi-analytic Green's function method within a real-space renormalization (decimation procedure). Our results showed an excellent agreement with results using a tight-binding model with a minimal number of parameters reported so far for these molecular systems.

Medulloblastoma: experimental models and reality.

PubMed

Neumann, Julia E; Swartling, Fredrik J; Schüller, Ulrich

2017-11-01

Medulloblastoma is the most frequent malignant brain tumor in childhood, but it may also affect infants, adolescents, and young adults. Recent advances in the understanding of the disease have shed light on molecular and clinical heterogeneity, which is now reflected in the updated WHO classification of brain tumors. At the same time, it is well accepted that preclinical research and clinical trials have to be subgroup-specific. Hence, valid models have to be generated specifically for every medulloblastoma subgroup to properly mimic molecular fingerprints, clinical features, and responsiveness to targeted therapies. This review summarizes the availability of experimental medulloblastoma models with a particular focus on how well these models reflect the actual disease subgroup. We further describe technical advantages and disadvantages of the models and finally point out how some models have successfully been used to introduce new drugs and why some medulloblastoma subgroups are extraordinary difficult to model.

MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

PubMed Central

2011-01-01

Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs), microRNAs (miRNAs) and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs). Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL). In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT), an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http://mironton.uni.lu which will be updated on a regular basis. PMID:21375730

Influence of orientation mismatch on charge transport across grain boundaries in tri-isopropylsilylethynyl (TIPS) pentacene thin films.

PubMed

Steiner, Florian; Poelking, Carl; Niedzialek, Dorota; Andrienko, Denis; Nelson, Jenny

2017-05-03

We present a multi-scale model for charge transport across grain boundaries in molecular electronic materials that incorporates packing disorder, electrostatic and polarisation effects. We choose quasi two-dimensional films of tri-isopropylsilylethynyl pentacene (TIPS-P) as a model system representative of technologically relevant crystalline organic semiconductors. We use atomistic molecular dynamics, with a force-field specific for TIPS-P, to generate and equilibrate polycrystalline two-dimensional thin films. The energy landscape is obtained by calculating contributions from electrostatic interactions and polarization. The variation in these contributions leads to energetic barriers between grains. Subsequently, charge transport is simulated using a kinetic Monte-Carlo algorithm. Two-grain systems with varied mutual orientation are studied. We find relatively little effect of long grain boundaries due to the presence of low impedance pathways. However, effects could be more pronounced for systems with limited inter-grain contact areas. Furthermore, we present a lattice model to generalize the model for small molecular systems. In the general case, depending on molecular architecture and packing, grain boundaries can result in interfacial energy barriers, traps or a combination of both with qualitatively different effects on charge transport.

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

DTIC Science & Technology

2014-04-01

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

From Reactor to Rheology in LDPE Modeling

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

Read, Daniel J.; Das, Chinmay; Auhl, Dietmar

2008-07-07

In recent years the association between molecular structure and linear rheology has been established and well-understood through the tube concept and its extensions for well-characterized materials (e.g. McLeish, Adv. Phys. 2002). However, for industrial branched polymeric material at processing conditions this piece of information is missing. A large number of phenomenological models have been developed to describe the nonlinear response of polymers. But none of these models takes into account the underlying molecular structure, leading to a fitting procedure with arbitrary fitting parameters. The goal of applied molecular rheology is a predictive scheme that runs in its entirety from themore » molecular structure from the reactor to the non-linear rheology of the resin. In our approach, we use a model for the industrial reactor to explicitly generate the molecular structure ensemble of LDPE's, (Tobita, J. Polym. Sci. B 2001), which are consistent with the analytical information. We calculate the linear rheology of the LDPE ensemble with the use of a tube model for branched polymers (Das et al., J. Rheol. 2006). We then, separate the contribution of the stress decay to a large number of pompom modes (McLeish et al., J. Rheol. 1998 and Inkson et al., J. Rheol. 1999) with the stretch time and the priority variables corresponding to the actual ensemble of molecules involved. This multimode pompom model allows us to predict the nonlinear properties without any fitting parameter. We present and analyze our results in comparison with experimental data on industrial materials.« less

Molecular Docking for Prediction and Interpretation of Adverse Drug Reactions.

PubMed

Luo, Heng; Fokoue-Nkoutche, Achille; Singh, Nalini; Yang, Lun; Hu, Jianying; Zhang, Ping

2018-05-23

Adverse drug reactions (ADRs) present a major burden for patients and the healthcare industry. Various computational methods have been developed to predict ADRs for drug molecules. However, many of these methods require experimental or surveillance data and cannot be used when only structural information is available. We collected 1,231 small molecule drugs and 600 human proteins and utilized molecular docking to generate binding features among them. We developed machine learning models that use these docking features to make predictions for 1,533 ADRs. These models obtain an overall area under the receiver operating characteristic curve (AUROC) of 0.843 and an overall area under the precision-recall curve (AUPR) of 0.395, outperforming seven structural fingerprint-based prediction models. Using the method, we predicted skin striae for fluticasone propionate, dermatitis acneiform for mometasone, and decreased libido for irinotecan, as demonstrations. Furthermore, we analyzed the top binding proteins associated with some of the ADRs, which can help to understand and/or generate hypotheses for underlying mechanisms of ADRs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

On the origin of the Orion and Monoceros molecular cloud complexes

NASA Technical Reports Server (NTRS)

Franco, J.; Tenorio-Tagle, G.; Bodenheimer, P.; Rozyczka, M.; Mirabel, I. F.

1988-01-01

A detailed model for the origin of the Orion and Monoceros cloud complexes is presented, showing that a single high-velocity H I cloud-galaxy collision can explain their main observed features. The collision generates massive shocked layers, and self-gravity can then provide the conditions for the transformation of these layers into molecular clouds. The clouds formed by the collision maintain the motion of their parental shocked gas and reach positions located far away from the plane. According to this model, both the Orion and Monoceros complexes were formed some 60 million yr ago, when the original shocked layer was fragmented by Galactic tidal forces.

Defect-induced solid state amorphization of molecular crystals

NASA Astrophysics Data System (ADS)

Lei, Lei; Carvajal, Teresa; Koslowski, Marisol

2012-04-01

We investigate the process of mechanically induced amorphization in small molecule organic crystals under extensive deformation. In this work, we develop a model that describes the amorphization of molecular crystals, in which the plastic response is calculated with a phase field dislocation dynamics theory in four materials: acetaminophen, sucrose, γ-indomethacin, and aspirin. The model is able to predict the fraction of amorphous material generated in single crystals for a given applied stress. Our results show that γ-indomethacin and sucrose demonstrate large volume fractions of amorphous material after sufficient plastic deformation, while smaller amorphous volume fractions are predicted in acetaminophen and aspirin, in agreement with experimental observation.

Molecular replacement: tricks and treats

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

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

2013-11-01

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

Mimicking the action of folding chaperones by Hamiltonian replica-exchange molecular dynamics simulations: application in the refinement of de novo models.

PubMed

Fan, Hao; Periole, Xavier; Mark, Alan E

2012-07-01

The efficiency of using a variant of Hamiltonian replica-exchange molecular dynamics (Chaperone H-replica-exchange molecular dynamics [CH-REMD]) for the refinement of protein structural models generated de novo is investigated. In CH-REMD, the interaction between the protein and its environment, specifically, the electrostatic interaction between the protein and the solvating water, is varied leading to cycles of partial unfolding and refolding mimicking some aspects of folding chaperones. In 10 of the 15 cases examined, the CH-REMD approach sampled structures in which the root-mean-square deviation (RMSD) of secondary structure elements (SSE-RMSD) with respect to the experimental structure was more than 1.0 Å lower than the initial de novo model. In 14 of the 15 cases, the improvement was more than 0.5 Å. The ability of three different statistical potentials to identify near-native conformations was also examined. Little correlation between the SSE-RMSD of the sampled structures with respect to the experimental structure and any of the scoring functions tested was found. The most effective scoring function tested was the DFIRE potential. Using the DFIRE potential, the SSE-RMSD of the best scoring structures was on average 0.3 Å lower than the initial model. Overall the work demonstrates that targeted enhanced-sampling techniques such as CH-REMD can lead to the systematic refinement of protein structural models generated de novo but that improved potentials for the identification of near-native structures are still needed. Copyright © 2012 Wiley Periodicals, Inc.

Tight junction protein expression and barrier properties of immortalized mouse brain microvessel endothelial cells.

PubMed

Brown, Rachel C; Morris, Andrew P; O'Neil, Roger G

2007-01-26

Understanding the molecular and biochemical mechanisms regulating the blood-brain barrier is aided by in vitro model systems. Many studies have used primary cultures of brain microvessel endothelial cells for this purpose. However, primary cultures limit the generation of material for molecular and biochemical assays since cells grow slowly, are prone to contamination by other neurovascular unit cells, and lose blood-brain barrier characteristics when passaged. To address these issues, immortalized cell lines have been generated. In these studies, we assessed the suitability of the immortalized mouse brain endothelial cell line, bEnd3, as a blood-brain barrier model. RT-PCR and immunofluorescence indicated expression of multiple tight junction proteins. bEnd3 cells formed barriers to radiolabeled sucrose, and responded like primary cultures to disrupting stimuli. Exposing cells to serum-free media on their basolateral side significantly decreased paracellular permeability; astrocyte-conditioned media did not enhance barrier properties. The serum-free media-induced decrease in permeability was correlated with an increase in claudin-5 and zonula occludens-1 immunofluorescence at cell-cell contracts. We conclude that bEnd3 cells are an attractive candidate as a model of the blood-brain barrier due to their rapid growth, maintenance of blood-brain barrier characteristics over repeated passages, formation of functional barriers and amenability to numerous molecular interventions.

TIGHT JUNCTION PROTEIN EXPRESSION AND BARRIER PROPERTIES OF IMMORTALIZED MOUSE BRAIN MICROVESSEL ENDOTHELIAL CELLS

PubMed Central

Brown, Rachel C.; Morris, Andrew P.; O’Neil, Roger G.

2007-01-01

Understanding the molecular and biochemical mechanisms regulating the blood-brain barrier is aided by in vitro model systems. Many studies have used primary cultures of brain microvessel endothelial cells for this purpose. However, primary cultures limit the generation of material for molecular and biochemical assays since cells grow slowly, are prone to contamination by other neurovascular unit cells, and lose blood-brain barrier characteristics when passaged. To address these issues, immortalized cell lines have been generated. In these studies, we assessed the suitability of the immortalized mouse brain endothelial cell line, bEnd3, as a blood-brain barrier model. RT-PCR and immunofluorescence indicated expression of multiple tight junction proteins. bEnd3 cells formed barriers to radiolabeled sucrose, and responded like primary cultures to disrupting stimuli. Exposing cells to serum-free media on their basolateral side significantly decreased paracellular permeability; astrocyte-conditioned media did not enhance barrier properties. The serum-free media-induced decrease in permeability was correlated with an increase in claudin-5 and zonula occludens-1 immunofluorescence at cell-cell contracts. We conclude that bEnd3 cells are an attractive candidate as a model of the blood-brain barrier due to their rapid growth, maintenance of blood-brain barrier characteristics over repeated passages, formation of functional barriers and amenability to numerous molecular interventions. PMID:17169347

Genomic Sequencing Procedure Microcosting Analysis and Health Economic Cost-Impact Analysis: A Report of the Association for Molecular Pathology.

PubMed

Sabatini, Linda M; Mathews, Charles; Ptak, Devon; Doshi, Shivang; Tynan, Katherine; Hegde, Madhuri R; Burke, Tara L; Bossler, Aaron D

2016-05-01

The increasing use of advanced nucleic acid sequencing technologies for clinical diagnostics and therapeutics has made vital understanding the costs of performing these procedures and their value to patients, providers, and payers. The Association for Molecular Pathology invested in a cost and value analysis of specific genomic sequencing procedures (GSPs) newly coded by the American Medical Association Current Procedural Terminology Editorial Panel. Cost data and work effort, including the development and use of data analysis pipelines, were gathered from representative laboratories currently performing these GSPs. Results were aggregated to generate representative cost ranges given the complexity and variability of performing the tests. Cost-impact models for three clinical scenarios were generated with assistance from key opinion leaders: impact of using a targeted gene panel in optimizing care for patients with advanced non-small-cell lung cancer, use of a targeted gene panel in the diagnosis and management of patients with sensorineural hearing loss, and exome sequencing in the diagnosis and management of children with neurodevelopmental disorders of unknown genetic etiology. Each model demonstrated value by either reducing health care costs or identifying appropriate care pathways. The templates generated will aid laboratories in assessing their individual costs, considering the value structure in their own patient populations, and contributing their data to the ongoing dialogue regarding the impact of GSPs on improving patient care. Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Use of Molecular Modeling to Determine the Interaction and Competition of Gases within Coal for Carbon Dioxide Sequestration

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

Jeffrey D. Evanseck; Jeffry D. Madura

A 3-dimensional coal structural model for the Argonne Premium Coal Pocahontas No. 3 has been generated. The model was constructed based on the wealth of structural information available in the literature with the enhancement that the structural diversity within the structure was represented implicitly (for the first time) based on image analysis of HRTEM in combination with LDMS data. The complex and large structural model (>10,000 carbon atoms) will serve as a basis for examining the interaction of gases within this low volatile bituminous coal. Simulations are of interest to permit reasonable simulations of the host-guest interactions with regard tomore » carbon dioxide sequestration within coal and methane displacement from coal. The molecular structure will also prove useful in examining other coal related behavior such as solvent swelling, liquefaction and other properties. Molecular models of CO{sub 2} have been evaluated with water to analyze which classical molecular force-field parameters are the most reasonable to predict the interactions of CO{sub 2} with water. The comparison of the molecular force field models was for a single CO{sub 2}-H{sub 2}O complex and was compared against first principles quantum mechanical calculations. The interaction energies and the electrostatic interaction distances were used as criteria in the comparison. The ab initio calculations included Hartree-Fock, B3LYP, and Moeller-Plesset 2nd, 3rd, and 4th order perturbation theories with basis sets up to the aug-cc-pvtz basis set. The Steele model was the best literature model, when compared to the ab initio data, however, our new CO{sub 2} model reproduces the QM data significantly better than the Steele force-field model.« less

Muonic molecular ions p p μ and p d μ driven by superintense VUV laser pulses: Postexcitation muonic and nuclear oscillations and high-order harmonic generation

NASA Astrophysics Data System (ADS)

Paramonov, Guennaddi K.; Saalfrank, Peter

2018-05-01

The non-Born-Oppenheimer quantum dynamics of p p μ and p d μ molecular ions excited by ultrashort, superintense VUV laser pulses polarized along the molecular axis (z ) is studied by the numerical solution of the time-dependent Schrödinger equation within a three-dimensional (3D) model, including the internuclear distance R and muon coordinates z and ρ , a transversal degree of freedom. It is shown that in both p p μ and p d μ , muons approximately follow the applied laser field out of phase. After the end of the laser pulse, expectation values , <ρ > , and demonstrate "post-laser-pulse" oscillations in both p p μ and p d μ . In the case of p d μ , the post-laser-pulse oscillations of and appear as shaped "echo pulses." Power spectra, which are related to high-order harmonic generation (HHG), generated due to muonic and nuclear motion are calculated in the acceleration form. For p d μ it is found that there exists a unique characteristic frequency ωoscp d μ representing both frequencies of post-laser-pulse muonic oscillations and the frequency of nuclear vibrations, which manifest themselves by very sharp maxima in the corresponding power spectra of p d μ . The homonuclear p p μ ion does not possess such a unique characteristic frequency. The "exact" dynamics and power, and HHG spectra of the 3D model are compared with a Born-Oppenheimer, fixed-nuclei model featuring interesting differences: postpulse oscillations are absent and HHG spectra are affected indirectly or directly by nuclear motion.

Conservative and dissipative force field for simulation of coarse-grained alkane molecules: A bottom-up approach

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

Trément, Sébastien; Rousseau, Bernard, E-mail: bernard.rousseau@u-psud.fr; Schnell, Benoît

2014-04-07

We apply operational procedures available in the literature to the construction of coarse-grained conservative and friction forces for use in dissipative particle dynamics (DPD) simulations. The full procedure rely on a bottom-up approach: large molecular dynamics trajectories of n-pentane and n-decane modeled with an anisotropic united atom model serve as input for the force field generation. As a consequence, the coarse-grained model is expected to reproduce at least semi-quantitatively structural and dynamical properties of the underlying atomistic model. Two different coarse-graining levels are studied, corresponding to five and ten carbon atoms per DPD bead. The influence of the coarse-graining levelmore » on the generated force fields contributions, namely, the conservative and the friction part, is discussed. It is shown that the coarse-grained model of n-pentane correctly reproduces self-diffusion and viscosity coefficients of real n-pentane, while the fully coarse-grained model for n-decane at ambient temperature over-predicts diffusion by a factor of 2. However, when the n-pentane coarse-grained model is used as a building block for larger molecule (e.g., n-decane as a two blobs model), a much better agreement with experimental data is obtained, suggesting that the force field constructed is transferable to large macro-molecular systems.« less

Singlet molecular oxygen generated by biological hydroperoxides.

PubMed

Miyamoto, Sayuri; Martinez, Glaucia R; Medeiros, Marisa H G; Di Mascio, Paolo

2014-10-05

The chemistry behind the phenomenon of ultra-weak photon emission has been subject of considerable interest for decades. Great progress has been made on the understanding of the chemical generation of electronically excited states that are involved in these processes. Proposed mechanisms implicated the production of excited carbonyl species and singlet molecular oxygen in the mechanism of generation of chemiluminescence in biological system. In particular, attention has been focused on the potential generation of singlet molecular oxygen in the recombination reaction of peroxyl radicals by the Russell mechanism. In the last ten years, our group has demonstrated the generation of singlet molecular oxygen from reactions involving the decomposition of biologically relevant hydroperoxides, especially from lipid hydroperoxides in the presence of metal ions, peroxynitrite, HOCl and cytochrome c. In this review we will discuss details on the chemical aspects related to the mechanism of singlet molecular oxygen generation from different biological hydroperoxides. Copyright © 2014 Elsevier B.V. All rights reserved.

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...

Multi-scale genetic dynamic modelling I : an algorithm to compute generators.

PubMed

Kirkilionis, Markus; Janus, Ulrich; Sbano, Luca

2011-09-01

We present a new approach or framework to model dynamic regulatory genetic activity. The framework is using a multi-scale analysis based upon generic assumptions on the relative time scales attached to the different transitions of molecular states defining the genetic system. At micro-level such systems are regulated by the interaction of two kinds of molecular players: macro-molecules like DNA or polymerases, and smaller molecules acting as transcription factors. The proposed genetic model then represents the larger less abundant molecules with a finite discrete state space, for example describing different conformations of these molecules. This is in contrast to the representations of the transcription factors which are-like in classical reaction kinetics-represented by their particle number only. We illustrate the method by considering the genetic activity associated to certain configurations of interacting genes that are fundamental to modelling (synthetic) genetic clocks. A largely unknown question is how different molecular details incorporated via this more realistic modelling approach lead to different macroscopic regulatory genetic models which dynamical behaviour might-in general-be different for different model choices. The theory will be applied to a real synthetic clock in a second accompanying article (Kirkilioniset al., Theory Biosci, 2011).

Targeted next generation sequencing for the detection of ciprofloxacin resistance markers using molecular inversion probes

DTIC Science & Technology

2016-07-06

1 Targeted next-generation sequencing for the detection of ciprofloxacin resistance markers using molecular inversion probes Christopher P...development and evaluation of a panel of 44 single-stranded molecular inversion probes (MIPs) coupled to next-generation sequencing (NGS) for the...padlock and molecular inversion probes as upfront enrichment steps for use with NGS showed the specificity and multiplexability of these techniques

Insight into the interaction mechanism of human SGLT2 with its inhibitors: 3D-QSAR studies, homology modeling, and molecular docking and molecular dynamics simulations.

PubMed

Dong, Lili; Feng, Ruirui; Bi, Jiawei; Shen, Shengqiang; Lu, Huizhe; Zhang, Jianjun

2018-03-06

Human sodium-dependent glucose co-transporter 2 (hSGLT2) is a crucial therapeutic target in the treatment of type 2 diabetes. In this study, both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied to generate three-dimensional quantitative structure-activity relationship (3D-QSAR) models. In the most accurate CoMFA-based and CoMSIA-based QSAR models, the cross-validated coefficients (r 2 cv ) were 0.646 and 0.577, respectively, while the non-cross-validated coefficients (r 2 ) were 0.997 and 0.991, respectively, indicating that both models were reliable. In addition, we constructed a homology model of hSGLT2 in the absence of a crystal structure. Molecular docking was performed to explore the bonding mode of inhibitors to the active site of hSGLT2. Molecular dynamics (MD) simulations and binding free energy calculations using MM-PBSA and MM-GBSA were carried out to further elucidate the interaction mechanism. With regards to binding affinity, we found that hydrogen-bond interactions of Asn51 and Glu75, located in the active site of hSGLT2, with compound 40 were critical. Hydrophobic and electrostatic interactions were shown to enhance activity, in agreement with the results obtained from docking and 3D-QSAR analysis. Our study results shed light on the interaction mode between inhibitors and hSGLT2 and may aid in the development of C-aryl glucoside SGLT2 inhibitors.

Molecular Modeling and Experimental Study of Nonlinear Optical Compounds: Mono-Substituted Derivatives of Dicyanovinylbenzene

NASA Technical Reports Server (NTRS)

Timofeeva, Tatyana V.; Nesterov, Vladimir N.; Antipin, Mikhael Y.; Clark, R. D.; Sanghadasa, M.; Cardelino, B. H.; Moore, C. E.; Frazier, Donald O.

2000-01-01

A search for potential nonlinear optical (NLO) compounds has been performed using the Cambridge Structural Database and molecular modeling. We have studied a series of mono-substituted derivatives of dicyanovinylbenzene as the NLO properties of one of its derivatives (o-methoxy-dicyanovinylbenzene, DIVA) were described earlier. The molecular geometry in the series of the compounds studied was investigated with an X- ray analysis and discussed along with results of molecular mechanics and ab initio quantum chemical calculations. The influence of crystal packing on the molecular planarity has been revealed. Two new compounds from the series studied were found to be active for second harmonic generation (SHG) in the powder. The measurements of SHG efficiency have shown that the o-F- and p-Cl-derivatives of dicyanovinylbenzene are about 10 and 20- times more active than urea, respectively. The peculiarities of crystal structure formation in the framework of balance between the van der Waals and electrostatic interactions have been discussed. The crystal morphology of DIVA and two new SHG-active compounds have been calculated on the basis of their known crystal structures.

Cluster model studies of anion and molecular specificities via electrospray ionization photoelectron spectroscopy

DOE PAGES

Wang, Xue -Bin

2017-01-06

Ion specificity, a widely observed macroscopic phenomenon in condensed phases and at interfaces, is essentially a fundamental chemical physical issue. We have been investigating such effects using cluster models in an “atom-by-atom” and “molecule-by-molecule” fashion not possible with condensed-phase methods. We use electrospray ionization (ESI) to generate molecular and ionic clusters to simulate key molecular entities involved in local binding regions, and characterize them employing negative ion photoelectron spectroscopy (NIPES). Inter- and intramolecular interactions and binding configurations are directly obtained as functions of cluster size and composition, providing insightful molecular-level description and characterization over the local active sites that playmore » crucial roles in determining solution chemistry and condensed phase phenomena. Finally, the topics covered in this article are relevant to a wide scope of research fields ranging from ion specific effects in electrolyte solutions, ion selectivity/recognition in normal functioning of life, to molecular specificity in aerosol particle formation, as well as in rational material design and synthesis.« less

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

PubMed

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

2013-11-01

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

Modeling Amorphous Microporous Polymers for CO2 Capture and Separations.

PubMed

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

2018-06-13

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

Molecular markers of neuropsychological functioning and Alzheimer's disease.

PubMed

Edwards, Melissa; Balldin, Valerie Hobson; Hall, James; O'Bryant, Sid

2015-03-01

The current project sought to examine molecular markers of neuropsychological functioning among elders with and without Alzheimer's disease (AD) and determine the predictive ability of combined molecular markers and select neuropsychological tests in detecting disease presence. Data were analyzed from 300 participants (n = 150, AD and n = 150, controls) enrolled in the Texas Alzheimer's Research and Care Consortium. Linear regression models were created to examine the link between the top five molecular markers from our AD blood profile and neuropsychological test scores. Logistical regressions were used to predict AD presence using serum biomarkers in combination with select neuropsychological measures. Using the neuropsychological test with the least amount of variance overlap with the molecular markers, the combined neuropsychological test and molecular markers was highly accurate in detecting AD presence. This work provides the foundation for the generation of a point-of-care device that can be used to screen for AD.

Structure of the torque ring of the flagellar motor and the molecular basis for rotational switching.

PubMed

Lee, Lawrence K; Ginsburg, Michael A; Crovace, Claudia; Donohoe, Mhairi; Stock, Daniela

2010-08-19

The flagellar motor drives the rotation of flagellar filaments at hundreds of revolutions per second, efficiently propelling bacteria through viscous media. The motor uses the potential energy from an electrochemical gradient of cations across the cytoplasmic membrane to generate torque. A rapid switch from anticlockwise to clockwise rotation determines whether a bacterium runs smoothly forward or tumbles to change its trajectory. A protein called FliG forms a ring in the rotor of the flagellar motor that is involved in the generation of torque through an interaction with the cation-channel-forming stator subunit MotA. FliG has been suggested to adopt distinct conformations that induce switching but these structural changes and the molecular mechanism of switching are unknown. Here we report the molecular structure of the full-length FliG protein, identify conformational changes that are involved in rotational switching and uncover the structural basis for the formation of the FliG torque ring. This allows us to propose a model of the complete ring and switching mechanism in which conformational changes in FliG reverse the electrostatic charges involved in torque generation.

CHARMM-GUI 10 Years for Biomolecular Modeling and Simulation

PubMed Central

Jo, Sunhwan; Cheng, Xi; Lee, Jumin; Kim, Seonghoon; Park, Sang-Jun; Patel, Dhilon S.; Beaven, Andrew H.; Lee, Kyu Il; Rui, Huan; Roux, Benoît; MacKerell, Alexander D.; Klauda, Jeffrey B.; Qi, Yifei

2017-01-01

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the molecular details of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. PMID:27862047

Molecular building blocks and their architecture in biologically/environmentally compatible soft matter chemical machinery.

PubMed

Toyota, Taro; Banno, Taisuke; Nitta, Sachiko; Takinoue, Masahiro; Nomoto, Tomonori; Natsume, Yuno; Matsumura, Shuichi; Fujinami, Masanori

2014-01-01

This review briefly summarizes recent developments in the construction of biologically/environmentally compatible chemical machinery composed of soft matter. Since environmental and living systems are open systems, chemical machinery must continuously fulfill its functions not only through the influx and generation of molecules but also via the degradation and dissipation of molecules. If the degradation or dissipation of soft matter molecular building blocks and biomaterial molecules/polymers can be achieved, soft matter particles composed of them can be used to realize chemical machinery such as selfpropelled droplets, drug delivery carriers, tissue regeneration scaffolds, protocell models, cell-/tissuemarkers, and molecular computing systems.

Mathematically guided approaches to distinguish models of periodic patterning

PubMed Central

Hiscock, Tom W.; Megason, Sean G.

2015-01-01

How periodic patterns are generated is an open question. A number of mechanisms have been proposed – most famously, Turing's reaction-diffusion model. However, many theoretical and experimental studies focus on the Turing mechanism while ignoring other possible mechanisms. Here, we use a general model of periodic patterning to show that different types of mechanism (molecular, cellular, mechanical) can generate qualitatively similar final patterns. Observation of final patterns is therefore not sufficient to favour one mechanism over others. However, we propose that a mathematical approach can help to guide the design of experiments that can distinguish between different mechanisms, and illustrate the potential value of this approach with specific biological examples. PMID:25605777

Three-dimensional quantitative structure-activity relationship CoMSIA/CoMFA and LeapFrog studies on novel series of bicyclo [4.1.0] heptanes derivatives as melanin-concentrating hormone receptor R1 antagonists.

PubMed

Morales-Bayuelo, Alejandro; Ayazo, Hernan; Vivas-Reyes, Ricardo

2010-10-01

Comparative molecular similarity indices analysis (CoMSIA) and comparative molecular field analysis (CoMFA) were performed on a series of bicyclo [4.1.0] heptanes derivatives as melanin-concentrating hormone receptor R1 antagonists (MCHR1 antagonists). Molecular superimposition of antagonists on the template structure was performed by database alignment method. The statistically significant model was established on sixty five molecules, which were validated by a test set of ten molecules. The CoMSIA model yielded the best predictive model with a q(2) = 0.639, non cross-validated R(2) of 0.953, F value of 92.802, bootstrapped R(2) of 0.971, standard error of prediction = 0.402, and standard error of estimate = 0.146 while the CoMFA model yielded a q(2) = 0.680, non cross-validated R(2) of 0.922, F value of 114.351, bootstrapped R(2) of 0.925, standard error of prediction = 0.364, and standard error of estimate = 0.180. CoMFA analysis maps were employed for generating a pseudo cavity for LeapFrog calculation. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. The results show the variability of steric and electrostatic contributions that determine the activity of the MCHR1 antagonist, with these results we proposed new antagonists that may be more potent than previously reported, these novel antagonists were designed from the addition of highly electronegative groups in the substituent di(i-C(3)H(7))N- of the bicycle [4.1.0] heptanes, using the model CoMFA which also was used for the molecular design using the technique LeapFrog. The data generated from the present study will further help to design novel, potent, and selective MCHR1 antagonists. Copyright (c) 2010 Elsevier Masson SAS. All rights reserved.

Combining partially ranked data in plant breeding and biology: II. Analysis with Rasch model.

USDA-ARS?s Scientific Manuscript database

Many years of breeding experiments, germplasm screening, and molecular biologic experimentation have generated volumes of sequence, genotype, and phenotype information that have been stored in public data repositories. These resources afford genetic and genomic researchers the opportunity to handle ...

A Systems Biology Approach to Toxicology Research with Small Fish Models

EPA Science Inventory

Increasing use of mechanistically-based molecular and biochemical endpoints and in vitro assays is being advocated as a more efficient and cost-effective approach for generating chemical hazard data. However, development of effective assays and application of the resulting data i...

Noninvasive probes of mitochondrial molecular motors

NASA Astrophysics Data System (ADS)

Nawarathna, Dharmakeerthna; Claycomb, James

2005-03-01

We report on a noninvasive method of probing mitochondrial molecular motors using nonlinear dielectric spectroscopy. It has been found previously that enzymes in the plasma membrane, particularly H+ ATPase, result in a strong low frequency (less than 100 Hz) nonlinear harmonic response. In this study, we find evidence that molecular motors located in the inner membranes of mitochondria cause the generation of harmonics at relatively high frequencies (1 - 30 kHz). In particular, we find that potassium cyanide (KCN), a respiratory inhibitor that binds to cytochrome c oxidase and thus prevents transport of protons across the mitochondrial inner membrane, suppresses the harmonic response. We observe this behavior in yeast (S. cerevisiae), a eucaryote that typically contains about 300 mitochondria, and B. indicas, a procaryote believed to be related to the ancient ancestor of mitochondria. Our current modeling efforts are focusing on a Brownian ratchet model of the F0 unit of ATP synthase, a remarkable molecular turbine driven by the proton gradient across the mitochondrial inner membrane.

Computational strategies for the automated design of RNA nanoscale structures from building blocks using NanoTiler.

PubMed

Bindewald, Eckart; Grunewald, Calvin; Boyle, Brett; O'Connor, Mary; Shapiro, Bruce A

2008-10-01

One approach to designing RNA nanoscale structures is to use known RNA structural motifs such as junctions, kissing loops or bulges and to construct a molecular model by connecting these building blocks with helical struts. We previously developed an algorithm for detecting internal loops, junctions and kissing loops in RNA structures. Here we present algorithms for automating or assisting many of the steps that are involved in creating RNA structures from building blocks: (1) assembling building blocks into nanostructures using either a combinatorial search or constraint satisfaction; (2) optimizing RNA 3D ring structures to improve ring closure; (3) sequence optimisation; (4) creating a unique non-degenerate RNA topology descriptor. This effectively creates a computational pipeline for generating molecular models of RNA nanostructures and more specifically RNA ring structures with optimized sequences from RNA building blocks. We show several examples of how the algorithms can be utilized to generate RNA tecto-shapes.

Angle-dependent quantum Otto heat engine based on coherent dipole-dipole coupling

NASA Astrophysics Data System (ADS)

Su, Shan-He; Luo, Xiao-Qing; Chen, Jin-Can; Sun, Chang-Pu

2016-08-01

Electromagnetic interactions between molecules or within a molecule have been widely observed in biological systems and exhibit broad application for molecular structural studies. Quantum delocalization of molecular dipole moments has inspired researchers to explore new avenues to utilize this physical effect for energy harvesting devices. Herein, we propose a simple model of the angle-dependent quantum Otto heat engine which seeks to facilitate the conversion of heat to work. Unlike previous studies, the adiabatic processes are accomplished by varying only the directions of the magnetic field. We show that the heat engine continues to generate power when the angle relative to the vector r joining the centres of coupled dipoles departs from the magic angle θm where the static coupling vanishes. A significant improvement in the device performance has to be attributed to the presence of the quantum delocalized levels associated with the coherent dipole-dipole coupling. These results obtained may provide a promising model for the biomimetic design and fabrication of quantum energy generators.

Computational strategies for the automated design of RNA nanoscale structures from building blocks using NanoTiler☆

PubMed Central

Bindewald, Eckart; Grunewald, Calvin; Boyle, Brett; O’Connor, Mary; Shapiro, Bruce A.

2013-01-01

One approach to designing RNA nanoscale structures is to use known RNA structural motifs such as junctions, kissing loops or bulges and to construct a molecular model by connecting these building blocks with helical struts. We previously developed an algorithm for detecting internal loops, junctions and kissing loops in RNA structures. Here we present algorithms for automating or assisting many of the steps that are involved in creating RNA structures from building blocks: (1) assembling building blocks into nanostructures using either a combinatorial search or constraint satisfaction; (2) optimizing RNA 3D ring structures to improve ring closure; (3) sequence optimisation; (4) creating a unique non-degenerate RNA topology descriptor. This effectively creates a computational pipeline for generating molecular models of RNA nanostructures and more specifically RNA ring structures with optimized sequences from RNA building blocks. We show several examples of how the algorithms can be utilized to generate RNA tecto-shapes. PMID:18838281

Immune Cell-Supplemented Human Skin Model for Studying Fungal Infections.

PubMed

Kühbacher, Andreas; Sohn, Kai; Burger-Kentischer, Anke; Rupp, Steffen

2017-01-01

Human skin is a niche for various fungal species which either colonize the surface of this tissue as commensals or, primarily under conditions of immunosuppression, invade the skin and cause infection. Here we present a method for generation of a human in vitro skin model supplemented with immune cells of choice. This model represents a complex yet amenable tool to study molecular mechanisms of host-fungi interactions at human skin.

pysimm: A Python Package for Simulation of Molecular Systems

NASA Astrophysics Data System (ADS)

Fortunato, Michael; Colina, Coray

pysimm, short for python simulation interface for molecular modeling, is a python package designed to facilitate the structure generation and simulation of molecular systems through convenient and programmatic access to object-oriented representations of molecular system data. This poster presents core features of pysimm and design philosophies that highlight a generalized methodology for incorporation of third-party software packages through API interfaces. The integration with the LAMMPS simulation package is explained to demonstrate this methodology. pysimm began as a back-end python library that powered a cloud-based application on nanohub.org for amorphous polymer simulation. The extension from a specific application library to general purpose simulation interface is explained. Additionally, this poster highlights the rapid development of new applications to construct polymer chains capable of controlling chain morphology such as molecular weight distribution and monomer composition.

Analysis of conjugation of chloramphenicol and hemoglobin by fluorescence, circular dichroism and molecular modeling

NASA Astrophysics Data System (ADS)

Ding, Fei; Liu, Wei; Sun, Ye; Yang, Xin-Ling; Sun, Ying; Zhang, Li

2012-01-01

Chloramphenicol is a low cost, broad spectrum, highly active antibiotic, and widely used in the treatment of serious infections, including typhoid fever and other life-threatening infections of the central nervous system and respiratory tract. The purpose of the present study was to examine the conjugation of chloramphenicol with hemoglobin (Hb) and compared with albumin at molecular level, utilizing fluorescence, UV/vis absorption, circular dichroism (CD) as well as molecular modeling. Fluorescence data indicate that drug bind Hb generate quenching via static mechanism, this corroborates UV/vis absorption measurements that the ground state complex formation with an affinity of 10 4 M -1, and the driving forces in the Hb-drug complex are hydrophilic interactions and hydrogen bonds, as derived from computational model. The accurate binding site of drug has been identified from the analysis of fluorescence and molecular modeling, α1β2 interface of Hb was assigned to possess high-affinity for drug, which located at the β-37 Trp nearby. The structural investigation of the complexed Hb by synchronous fluorescence, UV/vis absorption, and CD observations revealed some degree of Hb structure unfolding upon complexation. Based on molecular modeling, we can draw the conclusion that the binding affinity of drug with albumin is superior, compared with Hb. These phenomena can provide salient information on the absorption, distribution, pharmacology, and toxicity of chloramphenicol and other drugs which have analogous configuration with chloramphenicol.

Genetic identification and molecular modeling characterization reveal a novel PROM1 mutation in Stargardt4-like macular dystrophy

PubMed Central

Imani, Saber; Cheng, Jingliang; Shasaltaneh, Marzieh Dehghan; Wei, Chunli; Yang, Lisha; Fu, Shangyi; Zou, Hui; Khan, Md. Asaduzzaman; Zhang, Xianqin; Chen, Hanchun; Zhang, Dianzheng; Duan, Chengxia; Lv, Hongbin; Li, Yumei; Chen, Rui; Fu, Junjiang

2018-01-01

Stargardt disease-4 (STGD4) is an autosomal dominant complex, genetically heterogeneous macular degeneration/dystrophy (MD) disorder. In this paper, we used targeted next generation sequencing and multiple molecular dynamics analyses to identify and characterize a disease-causing genetic variant in four generations of a Chinese family with STGD4-like MD. We found a novel heterozygous missense mutation, c.734T>C (p.L245P) in the PROM1 gene. Structurally, this mutation most likely impairs PROM1 protein stability, flexibility, and amino acid interaction network after changing the amino acid residue Leucine into Proline in the basic helix-loop-helix leucine zipper domain. Molecular dynamic simulation and principal component analysis provide compelling evidence that this PROM1 mutation contributes to disease causativeness or susceptibility variants in patients with STGD4-like MD. Thus, this finding defines new approaches in genetic characterization, accurate diagnosis, and prevention of STGD4-like MD. PMID:29416601

Angular and Intensity Dependent Spectral Modulations in High Harmonics from N2

NASA Astrophysics Data System (ADS)

McFarland, Brian; Farrell, Joseph; Bucksbaum, Philip; Guehr, Markus

2009-05-01

The spectral amplitude and phase modulation of high harmonics (HHG) in molecules provides important clues to molecular structure and dynamics in strong laser fields. We have studied these effects in aligned N2. Earlier results of HHG experiments claimed that the spectral amplitude modulation was predominantly due to geometrical interference between the recombining electron and the highest occupied molecular orbital (HOMO) [1]. We report evidence that contradicts this simple view. We observe a phase jump accompanied by a spectral minimum for HHG in aligned N2. The minimum shifts to lower harmonics as the angle between the molecular axis and harmonic generation polarization increases, and shifts to higher harmonics with increasing harmonic generation intensity. The features observed cannot be fully explained by a geometrical model. We discuss alternative explanations involving multi orbital effects [2]. [0pt] [1] Lein et al., Phys. Rev. A, 66, 023805 (2002) [2] B. K. McFarland, J. P. Farrell, P. H. Bucksbaum and M. Gühr, Science 322, 1232 (2008)

Pharmacophore modeling, virtual screening and molecular docking of ATPase inhibitors of HSP70.

PubMed

Sangeetha, K; Sasikala, R P; Meena, K S

2017-10-01

Heat shock protein 70 is an effective anticancer target as it influences many signaling pathways. Hence the study investigated the important pharmacophore feature required for ATPase inhibitors of HSP70 by generating a ligand based pharmacophore model followed by virtual based screening and subsequent validation by molecular docking in Discovery studio V4.0. The most extrapolative pharmacophore model (hypotheses 8) consisted of four hydrogen bond acceptors. Further validation by external test set prediction identified 200 hits from Mini Maybridge, Drug Diverse, SCPDB compounds and Phytochemicals. Consequently, the screened compounds were refined by rule of five, ADMET and molecular docking to retain the best competitive hits. Finally Phytochemical compounds Muricatetrocin B, Diacetylphiladelphicalactone C, Eleutheroside B and 5-(3-{[1-(benzylsulfonyl)piperidin-4-yl]amino}phenyl)- 4-bromo-3-(carboxymethoxy)thiophene-2-carboxylic acid were obtained as leads to inhibit the ATPase activity of HSP70 in our findings and thus can be proposed for further in vitro and in vivo evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Beyond precision surgery: Molecularly motivated precision care for gastric cancer.

PubMed

Choi, Y Y; Cheong, J-H

2017-05-01

Gastric cancer is one of the leading causes of cancer-related deaths worldwide. Despite the high disease prevalence, gastric cancer research has not gained much attention. Recently, genome-scale technology has made it possible to explore the characteristics of gastric cancer at the molecular level. Accordingly, gastric cancer can be classified into molecular subtypes that convey more detailed information of tumor than histopathological characteristics, and these subtypes are associated with clinical outcomes. Furthermore, this molecular knowledge helps to identify new actionable targets and develop novel therapeutic strategies. To advance the concept of precision patient care in the clinic, patient-derived xenograft (PDX) models have recently been developed. PDX models not only represent histology and genomic features, but also predict responsiveness to investigational drugs in patient tumors. Molecularly curated PDX cohorts will be instrumental in hypothesis generation, biomarker discovery, and drug screening and testing in proof-of-concept preclinical trials for precision therapy. In the era of precision medicine, molecularly tailored therapeutic strategies should be individualized for cancer patients. To improve the overall clinical outcome, a multimodal approach is indispensable for advanced cancer patients. Careful, oncological principle-based surgery, combined with a molecularly guided multidisciplinary approach, will open new horizons in surgical oncology. Copyright © 2017. Published by Elsevier Ltd.

Structural insights of Staphylococcus aureus FtsZ inhibitors through molecular docking, 3D-QSAR and molecular dynamics simulations.

PubMed

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

2018-02-01

Filamentous temperature-sensitive protein Z (FtsZ) is a protein encoded by the FtsZ gene that assembles into a Z-ring at the future site of the septum of bacterial cell division. Structurally, FtsZ is a homolog of eukaryotic tubulin but has low sequence similarity; this makes it possible to obtain FtsZ inhibitors without affecting the eukaryotic cell division. Computational studies were performed on a series of substituted 3-arylalkoxybenzamide derivatives reported as inhibitors of FtsZ activity in Staphylococcus aureus. Quantitative structure-activity relationship models (QSAR) models generated showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of these models was determined and an acceptable predictive correlation (r 2 Pred ) values were obtained. Finally, we performed molecular dynamics simulations in order to examine the stability of protein-ligand interactions. This facilitated us to compare free binding energies of cocrystal ligand and newly designed molecule B1. The good concordance between the docking results and comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) contour maps afforded obliging clues for the rational modification of molecules to design more potent FtsZ inhibitors.

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

PubMed

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

2017-07-01

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

Modeling of capacitively and inductively coupled plasma for molecular decontamination

NASA Astrophysics Data System (ADS)

Mihailova, Diana; Hagelaar, Gerjan; Belenguer, Philippe; Laurent, Christopher; Lo, Juslan; Caillier, Bruno; Therese, Laurent; Guillot, Philippe

2013-09-01

This project aims to study and to develop new technology bricks for next generation of molecular decontamination systems, including plasma solution, for various applications. The contamination control in the processing stages is a major issue for the industrial performance as well as for the development of new technologies in the surface treatment area. The main task is to create uniform low temperature plasma inside a reactor containing the object to be treated. Different plasma sources are modeled with the aim of finding the most efficient one for surface decontamination: inductively coupled plasma, capacitively coupled plasma and combination of both. The model used for testing the various plasma sources is a time dependent two-dimensional multi-fluid model. The model is applied to a simplified cylindrically symmetric geometry in pure argon gas. The modeling results are validated by comparison with experimental results and observations based on optical and physical diagnostic tools. The influence of various parameters (power, pressure, flow) is studied and the corresponding results are presented, compared and discussed. This work has been performed in the frame of the collaborative program PAUD (Plasma Airborne molecular contamination Ultra Desorption) funded by the French agency OSEO and certified by French global competitive clusters Minalogic and Trimatec.

Human pluripotent stem cell models of autism spectrum disorder: emerging frontiers, opportunities, and challenges towards neuronal networks in a dish.

PubMed

Aigner, Stefan; Heckel, Tobias; Zhang, Jitao D; Andreae, Laura C; Jagasia, Ravi

2014-03-01

Autism spectrum disorder (ASD) is characterized by deficits in language development and social cognition and the manifestation of repetitive and restrictive behaviors. Despite recent major advances, our understanding of the pathophysiological mechanisms leading to ASD is limited. Although most ASD cases have unknown genetic underpinnings, animal and human cellular models of several rare, genetically defined syndromic forms of ASD have provided evidence for shared pathophysiological mechanisms that may extend to idiopathic cases. Here, we review our current knowledge of the genetic basis and molecular etiology of ASD and highlight how human pluripotent stem cell-based disease models have the potential to advance our understanding of molecular dysfunction. We summarize landmark studies in which neuronal cell populations generated from human embryonic stem cells and patient-derived induced pluripotent stem cells have served to model disease mechanisms, and we discuss recent technological advances that may ultimately allow in vitro modeling of specific human neuronal circuitry dysfunction in ASD. We propose that these advances now offer an unprecedented opportunity to help better understand ASD pathophysiology. This should ultimately enable the development of cellular models for ASD, allowing drug screening and the identification of molecular biomarkers for patient stratification.

Can we better predict the biologic behavior of incidental IPMN? A comprehensive analysis of molecular diagnostics and biomarkers in intraductal papillary mucinous neoplasms of the pancreas.

PubMed

Tulla, Kiara A; Maker, Ajay V

2018-03-01

Predicting the biologic behavior of intraductal papillary mucinous neoplasm (IPMN) remains challenging. Current guidelines utilize patient symptoms and imaging characteristics to determine appropriate surgical candidates. However, the majority of resected cysts remain low-risk lesions, many of which may be feasible to have under surveillance. We herein characterize the most promising and up-to-date molecular diagnostics in order to identify optimal components of a molecular signature to distinguish levels of IPMN dysplasia. A comprehensive systematic review of pertinent literature, including our own experience, was conducted based on the PRISMA guidelines. Molecular diagnostics in IPMN patient tissue, duodenal secretions, cyst fluid, saliva, and serum were evaluated and organized into the following categories: oncogenes, tumor suppressor genes, glycoproteins, markers of the immune response, proteomics, DNA/RNA mutations, and next-generation sequencing/microRNA. Specific targets in each of these categories, and in aggregate, were identified by their ability to both characterize a cyst as an IPMN and determine the level of cyst dysplasia. Combining molecular signatures with clinical and imaging features in this era of next-generation sequencing and advanced computational analysis will enable enhanced sensitivity and specificity of current models to predict the biologic behavior of IPMN.

Optically degradable dendrons for temporary adhesion of proteins to DNA.

PubMed

Kostiainen, Mauri A; Kotimaa, Juha; Laukkanen, Marja-Leena; Pavan, Giovanni M

2010-06-18

Experimental studies and molecular dynamics modeling demonstrate that multivalent dendrons can be used to temporarily glue proteins and DNA together with high affinity. We describe N-maleimide-cored polyamine dendrons that can be conjugated with free cysteine residues on protein surfaces through 1,4-conjugate addition to give one-to-one protein-polymer conjugates. We used a genetically engineered cysteine mutant of class II hydrophobin (HFBI) and a single-chain Fragment variable (scFv) antibody as model proteins for the conjugation reactions. The binding affinity of the protein-dendron conjugates towards DNA was experimentally assessed by using the ethidium bromide displacement assay. The binding was found to depend on the generation of the dendron, with the second generation having a stronger affinity than the first generation. Thermodynamic parameters of the binding were obtained from molecular dynamics modeling, which showed that the high binding affinity for each system is almost completely driven by a strong favorable binding enthalpy that is opposed by unfavorable binding entropy. A short exposure to UV (lambda approximately 350 nm) can cleave the photolabile o-nitrobenzyl-linked binding ligands from the surface of the dendron, which results in loss of the multivalent binding interactions and triggers the release of the DNA and protein. The timescale of the release is very rapid and the binding partners can be efficiently released after 3 min of UV exposure.

Numerical evidence of liquid crystalline mesophases of a lollipop shaped model in two dimensions

NASA Astrophysics Data System (ADS)

Pérez-Lemus, G. R.; Armas-Pérez, J. C.; Chapela, G. A.; Quintana-H., J.

2017-12-01

Small alterations in the molecular details may produce noticeable changes in the symmetry of the resulting phase behavior. It is possible to produce morphologies having different n-fold symmetries by manipulating molecular features such as chirality, polarity or anisotropy. In this paper, a two dimensional hard molecular model is introduced to study the formation of liquid crystalline phases in low dimensionality. The model is similar to that reported by Julio C. Armas-Pérez and Jacqueline Quintana-H., Phys. Rev. E 83, 051709 (2011). The main difference is the lack of chirality in the model proposed, although they share some characteristics like the geometrical polarity. Our model is called a lollipop model, because its shape is constructed by a rounded section attached to the end of a stick. Contrary to what happens in three dimensions where chiral nematogens produce interesting and complex phases such as blue phases, the lack of molecular chirality of our model generates a richer phase diagram compared to the chiral system. We show numerical and some geometrical evidences that the lack of laterality of the non chiral model seems to provide more routes of molecular self-assembly, producing triatic, a random cluster and possibly a tetratic phase behavior which were not presented in the previous work. We support our conclusions using results obtained from isobaric and isochoric Monte Carlo simulations. Properties as the n-fold order parameters such as the nematic, tetratic and triatic as well as their correlation functions were used to characterize the phases. We also provide the Fourier transform of equilibrium configurations to analyze the n-fold symmetry characteristic of each phase.

Realistic simulations of the coupling between the protomotive force and the mechanical rotation of the F0-ATPase

PubMed Central

Mukherjee, Shayantani; Warshel, Arieh

2012-01-01

The molecular origin of the action of the F0 proton gradient-driven rotor presents a major puzzle despite significant structural advances. Although important conceptual models have provided guidelines of how such systems should work, it has been challenging to generate a structure-based molecular model using physical principles that will consistently lead to the unidirectional proton-driven rotational motion during ATP synthesis. This work uses a coarse-grained (CG) model to simulate the energetics of the F0-ATPase system in the combined space defined by the rotational coordinate and the proton transport (PTR) from the periplasmic side (P) to the cytoplasmic side (N). The model establishes the molecular origin of the rotation, showing that this effect is due to asymmetry in the energetics of the proton path rather than only the asymmetry of the interaction of the Asp on the c-ring helices and Arg on the subunit-a. The simulation provides a clear conceptual background for further exploration of the electrostatic basis of proton-driven mechanochemical systems. PMID:22927379

Practical computational toolkits for dendrimers and dendrons structure design.

PubMed

Martinho, Nuno; Silva, Liana C; Florindo, Helena F; Brocchini, Steve; Barata, Teresa; Zloh, Mire

2017-09-01

Dendrimers and dendrons offer an excellent platform for developing novel drug delivery systems and medicines. The rational design and further development of these repetitively branched systems are restricted by difficulties in scalable synthesis and structural determination, which can be overcome by judicious use of molecular modelling and molecular simulations. A major difficulty to utilise in silico studies to design dendrimers lies in the laborious generation of their structures. Current modelling tools utilise automated assembly of simpler dendrimers or the inefficient manual assembly of monomer precursors to generate more complicated dendrimer structures. Herein we describe two novel graphical user interface toolkits written in Python that provide an improved degree of automation for rapid assembly of dendrimers and generation of their 2D and 3D structures. Our first toolkit uses the RDkit library, SMILES nomenclature of monomers and SMARTS reaction nomenclature to generate SMILES and mol files of dendrimers without 3D coordinates. These files are used for simple graphical representations and storing their structures in databases. The second toolkit assembles complex topology dendrimers from monomers to construct 3D dendrimer structures to be used as starting points for simulation using existing and widely available software and force fields. Both tools were validated for ease-of-use to prototype dendrimer structure and the second toolkit was especially relevant for dendrimers of high complexity and size.

Practical computational toolkits for dendrimers and dendrons structure design

NASA Astrophysics Data System (ADS)

Martinho, Nuno; Silva, Liana C.; Florindo, Helena F.; Brocchini, Steve; Barata, Teresa; Zloh, Mire

2017-09-01

Dendrimers and dendrons offer an excellent platform for developing novel drug delivery systems and medicines. The rational design and further development of these repetitively branched systems are restricted by difficulties in scalable synthesis and structural determination, which can be overcome by judicious use of molecular modelling and molecular simulations. A major difficulty to utilise in silico studies to design dendrimers lies in the laborious generation of their structures. Current modelling tools utilise automated assembly of simpler dendrimers or the inefficient manual assembly of monomer precursors to generate more complicated dendrimer structures. Herein we describe two novel graphical user interface toolkits written in Python that provide an improved degree of automation for rapid assembly of dendrimers and generation of their 2D and 3D structures. Our first toolkit uses the RDkit library, SMILES nomenclature of monomers and SMARTS reaction nomenclature to generate SMILES and mol files of dendrimers without 3D coordinates. These files are used for simple graphical representations and storing their structures in databases. The second toolkit assembles complex topology dendrimers from monomers to construct 3D dendrimer structures to be used as starting points for simulation using existing and widely available software and force fields. Both tools were validated for ease-of-use to prototype dendrimer structure and the second toolkit was especially relevant for dendrimers of high complexity and size.

Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer-aquitard complexes

USGS Publications Warehouse

Zhang, Yong; Green, Christopher T.; Tick, Geoffrey R.

2015-01-01

This study evaluates the role of the Peclet number as affected by molecular diffusion in transient anomalous transport, which is one of the major knowledge gaps in anomalous transport, by combining Monte Carlo simulations and stochastic model analysis. Two alluvial settings containing either short- or long-connected hydrofacies are generated and used as media for flow and transport modeling. Numerical experiments show that 1) the Peclet number affects both the duration of the power-law segment of tracer breakthrough curves (BTCs) and the transition rate from anomalous to Fickian transport by determining the solute residence time for a given low-permeability layer, 2) mechanical dispersion has a limited contribution to the anomalous characteristics of late-time transport as compared to molecular diffusion due to an almost negligible velocity in floodplain deposits, and 3) the initial source dimensions only enhance the power-law tail of the BTCs at short travel distances. A tempered stable stochastic (TSS) model is then applied to analyze the modeled transport. Applications show that the time-nonlocal parameters in the TSS model relate to the Peclet number, Pe. In particular, the truncation parameter in the TSS model increases nonlinearly with a decrease in Pe due to the decrease of the mean residence time, and the capacity coefficient increases with an increase in molecular diffusion which is probably due to the increase in the number of immobile particles. The above numerical experiments and stochastic analysis therefore reveal that the Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer–aquitard complexes.

Formal linguistics as a cue to demographic history.

PubMed

Longobardi, Giuseppe; Ceolin, Andrea; Ecay, Aaron; Ghirotto, Silvia; Guardiano, Cristina; Irimia, Monica-Alexandrina; Michelioudakis, Dimitris; Radkevich, Nina; Pettener, Davide; Luiselli, Donata; Barbujani, Guido

2016-06-20

Beyond its theoretical success, the development of molecular genetics has brought about the possibility of extraordinary progress in the study of classification and in the inference of the evolutionary history of many species and populations. A major step forward was represented by the availability of extremely large sets of molecular data suited to quantitative and computational treatments. In this paper, we argue that even in cognitive sciences, purely theoretical progress in a discipline such as linguistics may have analogous impact. Thus, exactly on the model of molecular biology, we propose to unify two traditionally unrelated lines of linguistic investigation: 1) the formal study of syntactic variation (parameter theory) in the biolinguistic program; 2) the reconstruction of relatedness among languages (phylogenetic taxonomy). The results of our linguistic analysis have thus been plotted against data from population genetics and the correlations have turned out to be largely significant: given a non-trivial set of languages/populations, the description of their variation provided by the comparison of systematic parametric analysis and molecular anthropology informatively recapitulates their history and relationships. As a result, we can claim that the reality of some parametric model of the language faculty and language acquisition/transmission (more broadly of generative grammar) receives strong and original support from its historical heuristic power. Then, on these grounds, we can begin testing Darwin's prediction that, when properly generated, the trees of human populations and of their languages should eventually turn out to be significantly parallel.

Next Generation Molecular Histology Using Highly Multiplexed Ion Beam Imaging (MIBI) of Breast Cancer Tissue Specimens for Enhanced Clinical Guidance

DTIC Science & Technology

2016-07-01

AWARD NUMBER: W81XWH- 14-1-0192 TITLE: Next-Generation Molecular Histology Using Highly Multiplexed Ion Beam Imaging (MIBI) of Breast Cancer...DATES COVERED 4. TITLE AND SUBTITLE Next-Generation Molecular Histology Using Highly Multiplexed Ion Beam Imaging (MIBI) of Breast Cancer Tissue

Generation of Mouse Lung Epithelial Cells.

PubMed

Kasinski, Andrea L; Slack, Frank J

2013-08-05

Although in vivo models are excellent for assessing various facets of whole organism physiology, pathology, and overall response to treatments, evaluating basic cellular functions, and molecular events in mammalian model systems is challenging. It is therefore advantageous to perform these studies in a refined and less costly setting. One approach involves utilizing cells derived from the model under evaluation. The approach to generate such cells varies based on the cell of origin and often the genetics of the cell. Here we describe the steps involved in generating epithelial cells from the lungs of Kras LSL-G12D/+ ; p53 LSL-R172/+ mice (Kasinski and Slack, 2012). These mice develop aggressive lung adenocarcinoma following cre-recombinase dependent removal of a stop cassette in the transgenes and subsequent expression of Kra -G12D and p53 R172 . While this protocol may be useful for the generation of epithelial lines from other genetic backgrounds, it should be noted that the Kras; p53 cell line generated here is capable of proliferating in culture without any additional genetic manipulation that is often needed for less aggressive backgrounds.

A prototype of an electric-discharge gas flow oxygen-iodine laser: I. Modeling of the processes of singlet oxygen generation in a transverse cryogenic slab RF discharge

NASA Astrophysics Data System (ADS)

Vagin, N. P.; Ionin, A. A.; Kochetov, I. V.; Napartovich, A. P.; Sinitsyn, D. V.; Yuryshev, N. N.

2017-03-01

The existing kinetic model describing self-sustained and electroionization discharges in mixtures enriched with singlet oxygen has been modified to calculate the characteristics of a flow RF discharge in molecular oxygen and its mixtures with helium. The simulations were performed in the gas plug-flow approximation, i.e., the evolution of the plasma components during their motion along the channel was represented as their evolution in time. The calculations were carried out for the O2: He = 1: 0, 1: 1, 1: 2, and 1: 3 mixtures at an oxygen partial pressure of 7.5 Torr. It is shown that, under these conditions, volumetric gas heating in a discharge in pure molecular oxygen prevails over gas cooling via heat conduction even at an electrode temperature as low as 100 K. When molecular oxygen is diluted with helium, the behavior of the gas temperature changes substantially: heat removal begins to prevail over volumetric gas heating, and the gas temperature at the outlet of the discharge zone drops to 220-230 K at room gas temperature at the inlet, which is very important in the context of achieving the generation threshold in an electric-discharge oxygen-iodine laser based on a slab cryogenic RF discharge.

Human mitochondrial disease-like symptoms caused by a reduced tRNA aminoacylation activity in flies

PubMed Central

Guitart, Tanit; Picchioni, Daria; Piñeyro, David; Ribas de Pouplana, Lluís

2013-01-01

The translation of genes encoded in the mitochondrial genome requires specific machinery that functions in the organelle. Among the many mutations linked to human disease that affect mitochondrial translation, several are localized to nuclear genes coding for mitochondrial aminoacyl-transfer RNA synthetases. The molecular significance of these mutations is poorly understood, but it is expected to be similar to that of the mutations affecting mitochondrial transfer RNAs. To better understand the molecular features of diseases caused by these mutations, and to improve their diagnosis and therapeutics, we have constructed a Drosophila melanogaster model disrupting the mitochondrial seryl-tRNA synthetase by RNA interference. At the molecular level, the knockdown generates a reduction in transfer RNA serylation, which correlates with the severity of the phenotype observed. The silencing compromises viability, longevity, motility and tissue development. At the cellular level, the knockdown alters mitochondrial morphology, biogenesis and function, and induces lactic acidosis and reactive oxygen species accumulation. We report that administration of antioxidant compounds has a palliative effect of some of these phenotypes. In conclusion, the fly model generated in this work reproduces typical characteristics of pathologies caused by mutations in the mitochondrial aminoacylation system, and can be useful to assess therapeutic approaches. PMID:23677612

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

PubMed

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

2013-10-31

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

Spin Seebeck effect in a metal-single-molecule-magnet-metal junction

NASA Astrophysics Data System (ADS)

Niu, Pengbin; Liu, Lixiang; Su, Xiaoqiang; Dong, Lijuan; Luo, Hong-Gang

2018-01-01

We investigate the nonlinear regime of temperature-driven spin-related currents through a single molecular magnet (SMM), which is connected with two metal electrodes. Under a large spin approximation, the SMM is simplified to a natural two-channel model possessing spin-opposite configuration and Coulomb interaction. We find that in temperature-driven case the system can generate spin-polarized currents. More interestingly, at electron-hole symmetry point, the competition of the two channels induces a temperature-driven pure spin current. This device demonstrates that temperature-driven SMM junction shows some results different from the usual quantum dot model, which may be useful in the future design of thermal-based molecular spintronic devices.

Three-dimensional quantitative structure-activity relationship studies on novel series of benzotriazine based compounds acting as Src inhibitors using CoMFA and CoMSIA.

PubMed

Gueto, Carlos; Ruiz, José L; Torres, Juan E; Méndez, Jefferson; Vivas-Reyes, Ricardo

2008-03-01

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of benzotriazine derivatives, as Src inhibitors. Ligand molecular superimposition on the template structure was performed by database alignment method. The statistically significant model was established of 72 molecules, which were validated by a test set of six compounds. The CoMFA model yielded a q(2)=0.526, non cross-validated R(2) of 0.781, F value of 88.132, bootstrapped R(2) of 0.831, standard error of prediction=0.587, and standard error of estimate=0.351 while the CoMSIA model yielded the best predictive model with a q(2)=0.647, non cross-validated R(2) of 0.895, F value of 115.906, bootstrapped R(2) of 0.953, standard error of prediction=0.519, and standard error of estimate=0.178. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that small steric volumes in the hydrophobic region, electron-withdrawing groups next to the aryl linker region, and atoms close to the solvent accessible region increase the Src inhibitory activity of the compounds. In fact, adding substituents at positions 5, 6, and 8 of the benzotriazine nucleus were generated new compounds having a higher predicted activity. The data generated from the present study will further help to design novel, potent, and selective Src inhibitors as anticancer therapeutic agents.

Quantum mechanics/molecular mechanics modeling of photoelectron spectra: the carbon 1s core-electron binding energies of ethanol-water solutions.

PubMed

Löytynoja, T; Niskanen, J; Jänkälä, K; Vahtras, O; Rinkevicius, Z; Ågren, H

2014-11-20

Using ethanol-water solutions as illustration, we demonstrate the capability of the hybrid quantum mechanics/molecular mechanics (QM/MM) paradigm to simulate core photoelectron spectroscopy: the binding energies and the chemical shifts. An integrated approach with QM/MM binding energy calculations coupled to preceding molecular dynamics sampling is adopted to generate binding energies averaged over the solute-solvent configurations available at a particular temperature and pressure and thus allowing for a statistical assessment with confidence levels for the final binding energies. The results are analyzed in terms of the contributions in the molecular mechanics model-electrostatic, polarization, and van der Waals-with atom or bond granulation of the corresponding MM charge and polarizability force-fields. The role of extramolecular charge transfer screening of the core-hole and explicit hydrogen bonding is studied by extending the QM core to cover the first solvation shell. The results are compared to those obtained from pure electrostatic and polarizable continuum models. Particularly, the dependence of the carbon 1s binding energies with respect to the ethanol concentration is studied. Our results indicate that QM/MM can be used as an all-encompassing model to study photoelectron binding energies and chemical shifts in solvent environments.

Molecular structure and gas chromatographic retention behavior of the components of Ylang-Ylang oil.

PubMed

Olivero, J; Gracia, T; Payares, P; Vivas, R; Díaz, D; Daza, E; Geerlings, P

1997-05-01

Using quantitative structure-retention relationships (QSRR) methodologies the Kovats gas chromatographic retention indices for both apolar (DB-1) and polar (DB-Wax) columns for 48 compounds from Ylang-Ylang essential oil were empirically predicted from calculated and experimental data on molecular structure. Topological, geometric, and electronic descriptors were obtained for model generation. Relationships between descriptors and the retention data reported were established by linear multiple regression, giving equations that can be used to predict the Kovats indices for compounds present in essential oils, both in DB-1 and DB-Wax columns. Factor analysis was performed to interpret the meaning of the descriptors included in the models. The prediction model for the DB-1 column includes descriptors such as Randic's first-order connectivity index (1X), the molecular surface (MSA), the sum of the atomic charge on all the hydrogens (QH), Randic's third-order connectivity index (3X) and the molecular electronegativity (chi). The prediction model for the DB-Wax column includes the first three descriptors mentioned for the DB-1 column (1X, MSA and QH) and the most negative charge (MNC), the global softness (S), and the difference between Randic's and Kier and Hall's third-order connectivity indexes (3X-3XV).

Photochemistry of porphyrins: a model for the origin of photosynthesis

NASA Technical Reports Server (NTRS)

Mercer-Smith, J. A.; Mauzerall, D. C.

1984-01-01

A series of porphyrins and catalysts has been prepared as a model for the origin of photosynthesis on the primordial earth. These compounds have been used to test the hypotheses that (1) the biosynthetic pathway to chlorophyll recapitulates the evolutionary history of photosynthesis, and (2) the proto-photosythetic function of biogenetic porphyrins (biosynthetic chlorophyll precursors) was the oxidation of organic molecules by photoexcited porphyrins with the attendant emission of molecular hydrogen. This paper describes experiments in which photoexcited biogenetic porphyrins oxidize ethylenediamine tetraacetic acid (EDTA). The concomitant reduction of protons to hydrogen gas occurs in the presence of a colloidal platinum catalyst. The addition of methyl viologen, a one-electron shuttle, increases the amount of molecular hydrogen generated during long irradiations and the quantum yield of hydrogen production. When the porphyrin and catalyst are held in association by molecular complexes, the increased efficiency of electron transfer produces higher yields of hydrogen gas.

Creation of half-metallic f -orbital Dirac fermion with superlight elements in orbital-designed molecular lattice

NASA Astrophysics Data System (ADS)

Cui, Bin; Huang, Bing; Li, Chong; Zhang, Xiaoming; Jin, Kyung-Hwan; Zhang, Lizhi; Jiang, Wei; Liu, Desheng; Liu, Feng

2017-08-01

Magnetism in solids generally originates from the localized d or f orbitals that are hosted by heavy transition-metal elements. Here, we demonstrate a mechanism for designing a half-metallic f -orbital Dirac fermion from superlight s p elements. Combining first-principles and model calculations, we show that bare and flat-band-sandwiched (FBS) Dirac bands can be created when C20 molecules are deposited into a two-dimensional hexagonal lattice, which are composed of f -molecular orbitals (MOs) derived from s p -atomic orbitals (AOs). Furthermore, charge doping of the FBS Dirac bands induces spontaneous spin polarization, converting the system into a half-metallic Dirac state. Based on this discovery, a model of a spin field effect transistor is proposed to generate and transport 100% spin-polarized carriers. Our finding illustrates a concept to realize exotic quantum states by manipulating MOs, instead of AOs, in orbital-designed molecular crystal lattices.

Microscopic cascading of second-order molecular nonlinearity: New design principles for enhancing third-order nonlinearity.

PubMed

Baev, Alexander; Autschbach, Jochen; Boyd, Robert W; Prasad, Paras N

2010-04-12

Herein, we develop a phenomenological model for microscopic cascading and substantiate it with ab initio calculations. It is shown that the concept of local microscopic cascading of a second-order nonlinearity can lead to a third-order nonlinearity, without introducing any new loss mechanisms that could limit the usefulness of our approach. This approach provides a new molecular design protocol, in which the current great successes achieved in producing molecules with extremely large second-order nonlinearity can be used in a supra molecular organization in a preferred orientation to generate very large third-order response magnitudes. The results of density functional calculations for a well-known second-order molecule, (para)nitroaniline, show that a head-to-tail dimer configuration exhibits enhanced third-order nonlinearity, in agreement with the phenomenological model which suggests that such an arrangement will produce cascading due to local field effects.

CURVATURE-DRIVEN MOLECULAR FLOW ON MEMBRANE SURFACE*

PubMed Central

MIKUCKI, MICHAEL; ZHOU, Y. C.

2017-01-01

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

A combined computational and structural model of the full-length human prolactin receptor

PubMed Central

Bugge, Katrine; Papaleo, Elena; Haxholm, Gitte W.; Hopper, Jonathan T. S.; Robinson, Carol V.; Olsen, Johan G.; Lindorff-Larsen, Kresten; Kragelund, Birthe B.

2016-01-01

The prolactin receptor is an archetype member of the class I cytokine receptor family, comprising receptors with fundamental functions in biology as well as key drug targets. Structurally, each of these receptors represent an intriguing diversity, providing an exceptionally challenging target for structural biology. Here, we access the molecular architecture of the monomeric human prolactin receptor by combining experimental and computational efforts. We solve the NMR structure of its transmembrane domain in micelles and collect structural data on overlapping fragments of the receptor with small-angle X-ray scattering, native mass spectrometry and NMR spectroscopy. Along with previously published data, these are integrated by molecular modelling to generate a full receptor structure. The result provides the first full view of a class I cytokine receptor, exemplifying the architecture of more than 40 different receptor chains, and reveals that the extracellular domain is merely the tip of a molecular iceberg. PMID:27174498

RealityConvert: a tool for preparing 3D models of biochemical structures for augmented and virtual reality.

PubMed

Borrel, Alexandre; Fourches, Denis

2017-12-01

There is a growing interest for the broad use of Augmented Reality (AR) and Virtual Reality (VR) in the fields of bioinformatics and cheminformatics to visualize complex biological and chemical structures. AR and VR technologies allow for stunning and immersive experiences, offering untapped opportunities for both research and education purposes. However, preparing 3D models ready to use for AR and VR is time-consuming and requires a technical expertise that severely limits the development of new contents of potential interest for structural biologists, medicinal chemists, molecular modellers and teachers. Herein we present the RealityConvert software tool and associated website, which allow users to easily convert molecular objects to high quality 3D models directly compatible for AR and VR applications. For chemical structures, in addition to the 3D model generation, RealityConvert also generates image trackers, useful to universally call and anchor that particular 3D model when used in AR applications. The ultimate goal of RealityConvert is to facilitate and boost the development and accessibility of AR and VR contents for bioinformatics and cheminformatics applications. http://www.realityconvert.com. dfourch@ncsu.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Understanding Plasmas with a High Degree of Correlation Through Modeling: From Rydberg and Fermionic Plasmas to Penning Plasmas

NASA Astrophysics Data System (ADS)

Christlieb, Andrew

2015-09-01

Ultra cold neutral plasmas have gained attention over the past 15 years as being a unique environment for studying moderately to strongly coupled neutral systems. The first ultra cold neutral plasmas were generated by ionizing a Bose Einstein condensate, generating a plasma with .1K ions and 2-4K electrons. These neutral plasmas have the unique property that the ratio of their potential energy to their kinetic energy, (Γ = PE / KE), can greatly exceed 1, leading to a strongly correlated system. The high degree of correlation means that everything from wave propagation through collision dynamics behaves quite differently from their counterpart in traditional neutral plasmas. Currently, a range of gases and different methods for cooling have been used to generate these plasmas from supersonic expansion, through penning trap configurations (reference Tom, Jake and Ed). These systems have time scales form picoseconds to milliseconds have a particle numbers from 105 to 109. These systems present a unique environment for studying the physics of correlation due to their low particle number and small size. We start by reviewing ultra cold plasmas and the current sate of the art in generating these correlated systems. Then we introduce the methods we will use for exploring these systems through direct simulation of Molecular Dynamics models; Momentum Dependent Potentials, Treecodes and Particle-Particle Particle-Mesh methods. We use these tools to look at two key areas of ultra cold plasmas; development of methods to generate a plasma with a Γ >> 1 and the impact of correlation of collisional relaxation. Our eventual goal is to use what we learn to develop models that can simulate correlation in large plasma systems that are outside of the scope of Molecular Dynamics models. In collaboration with Gautham Dharmuman, Mayur Jain, Michael Murillo and John Verboncoeur. This work it supposed by Air Force Office of Scientific Research.

Frequency modulation spectroscopy with a THz quantum-cascade laser.

PubMed

Eichholz, R; Richter, H; Wienold, M; Schrottke, L; Hey, R; Grahn, H T; Hübers, H-W

2013-12-30

We report on a terahertz spectrometer for high-resolution molecular spectroscopy based on a quantum-cascade laser. High-frequency modulation (up to 50 MHz) of the laser driving current produces a simultaneous modulation of the frequency and amplitude of the laser output. The modulation generates sidebands, which are symmetrically positioned with respect to the laser carrier frequency. The molecular transition is probed by scanning the sidebands across it. In this way, the absorption and the dispersion caused by the molecular transition are measured. The signals are modeled by taking into account the simultaneous modulation of the frequency and amplitude of the laser emission. This allows for the determination of the strength of the frequency as well as amplitude modulation of the laser and of molecular parameters such as pressure broadening.

Constructing a molecular theory of self-assembly: Interplay of ideas from surfactants and block copolymers.

PubMed

Nagarajan, Ramanathan

2017-06-01

Low molecular weight surfactants and high molecular weight block copolymers display analogous self-assembly behavior in solutions and at interfaces, generating nanoscale structures of different shapes. Understanding the link between the molecular structure of these amphiphiles and their self-assembly behavior has been the goal of theoretical studies. Despite the analogies between surfactants and block copolymers, models predicting their self-assembly behavior have evolved independent of one another, each overlooking the molecular feature considered critical to the other. In this review, we focus on the interplay of ideas pertaining to surfactants and block copolymers in three areas of self-assembly. First, we show how improved free energy models have evolved by applying ideas from surfactants to block copolymers and vice versa, giving rise to a unitary theoretical framework and better predictive capabilities for both classes of amphiphiles. Second we show that even though molecular packing arguments are often used to explain aggregate shape transitions resulting from self-assembly, the molecular packing considerations are more relevant in the case of surfactants whereas free energy criteria are relevant for block copolymers. Third, we show that even though the surfactant and block copolymer aggregates are small nanostructures, the size differences between them is significant enough to make the interfacial effects control the solubilization of molecules in surfactant micelles while the bulk interactions control the solubilization in block copolymer micelles. Finally, we conclude by identifying recent theoretical progress in adapting the micelle model to a wide variety of self-assembly phenomena and the challenges to modeling posed by emerging novel classes of amphiphiles with complex biological, inorganic or nanoparticle moieties. Published by Elsevier B.V.

Chemical and radiation mutagenesis: Induction and detection by whole genome sequencing

USDA-ARS?s Scientific Manuscript database

Brachypodium distachyon has emerged as an effective model system to address fundamental questions in grass biology. With its small sequenced genome, short generation time and rapidly expanding array of genetic tools B. distachyon is an ideal system to elucidate the molecular basis of important trai...

Molecular Modeling of High-Temperature Oxidation of Refractory Borides

DTIC Science & Technology

2008-02-01

generate the classical potential, we adopt the van Beest , Kramer and van Santen (BKS) parameterization for Si-O interactions, but fit B-O and Si-B...seminar at Department of Aerospace and Mechanical Engineering, University of Notre Dame, March 20, 2007. 6 Los Alamos National Lab Physics & Theoretical

Development and transferability of black and red raspberry microsatellite markers from short-read sequences

USDA-ARS?s Scientific Manuscript database

The advent of next-generation sequencing technologies has been a boon to the cost-effective development of molecular markers, particularly in non-model species. Here, we demonstrate the efficiency of microsatellite or simple sequence repeat (SSR) marker development from short-read sequences using th...

Nonequilibrium Nonideal Nanoplasma Generated by a Fast Single Ion in Condensed Matter

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

Faenov, A. Ya.; Kansai Photon Science Institut, Japan Atomic Energy Agency; Lankin, A. V.

A plasma model of relaxation of a medium in heavy ion tracks in condensed matter is proposed. The model is based on three assumptions: the Maxwell distribution of plasma electrons, localization of plasma inside the track nanochannel and constant values of the plasma electron density and temperature during the X-ray irradiation. It is demonstrated that the plasma relaxation model adequately describes the X-ray spectra observed upon interaction of a fast ion with condensed target. Preassumptions of plasma relaxation model are validated by the molecular dynamics modeling and simulation.

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

PubMed

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

2017-03-14

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

Exploring potential Pluto-generated neutral tori

NASA Astrophysics Data System (ADS)

Smith, Howard T.; Hill, Matthew; KollMann, Peter; McHutt, Ralph

2015-11-01

The NASA New Horizons mission to Pluto is providing unprecedented insight into this mysterious outer solar system body. Escaping molecular nitrogen is of particular interest and possibly analogous to similar features observed at moons of Saturn and Jupiter. Such escaping N2 has the potential of creating molecular nitrogen and N (as a result of molecular dissociation) tori or partial toroidal extended particle distributions. The presence of these features would present the first confirmation of an extended toroidal neutral feature on a planetary scale in our solar system. While escape velocities are anticipated to be lower than those at Enceladus, Io or even Europa, particle lifetimes are much longer in Pluto’s orbit because as a result of much weaker solar interaction processes along Pluto’s orbit (on the order of tens of years). Thus, with a ~248 year orbit, Pluto may in fact be generating an extended toroidal feature along it orbit.For this work, we modify and apply our 3-D Monte Carlo neutral torus model (previously used at Saturn, Jupiter and Mercury) to study/analyze the theoretical possibility and scope of potential Pluto-generated neutral tori. Our model injects weighted particles and tracks their trajectories under the influence of all gravitational fields with interactions with other particles, solar photons and Pluto collisions. We present anticipated N2 and N tori based on current estimates of source characterization and environmental conditions. We also present an analysis of sensitivity to assumed initial conditions. Such results can provide insight into the Pluto system as well as valuable interpretation of New Horizon’s observational data.

Generation of a large volume of clinically relevant nanometre-sized ultra-high-molecular-weight polyethylene wear particles for cell culture studies

PubMed Central

Ingham, Eileen; Fisher, John; Tipper, Joanne L

2014-01-01

It has recently been shown that the wear of ultra-high-molecular-weight polyethylene in hip and knee prostheses leads to the generation of nanometre-sized particles, in addition to micron-sized particles. The biological activity of nanometre-sized ultra-high-molecular-weight polyethylene wear particles has not, however, previously been studied due to difficulties in generating sufficient volumes of nanometre-sized ultra-high-molecular-weight polyethylene wear particles suitable for cell culture studies. In this study, wear simulation methods were investigated to generate a large volume of endotoxin-free clinically relevant nanometre-sized ultra-high-molecular-weight polyethylene wear particles. Both single-station and six-station multidirectional pin-on-plate wear simulators were used to generate ultra-high-molecular-weight polyethylene wear particles under sterile and non-sterile conditions. Microbial contamination and endotoxin levels in the lubricants were determined. The results indicated that microbial contamination was absent and endotoxin levels were low and within acceptable limits for the pharmaceutical industry, when a six-station pin-on-plate wear simulator was used to generate ultra-high-molecular-weight polyethylene wear particles in a non-sterile environment. Different pore-sized polycarbonate filters were investigated to isolate nanometre-sized ultra-high-molecular-weight polyethylene wear particles from the wear test lubricants. The use of the filter sequence of 10, 1, 0.1, 0.1 and 0.015 µm pore sizes allowed successful isolation of ultra-high-molecular-weight polyethylene wear particles with a size range of < 100 nm, which was suitable for cell culture studies. PMID:24658586

Generation of a large volume of clinically relevant nanometre-sized ultra-high-molecular-weight polyethylene wear particles for cell culture studies.

PubMed

Liu, Aiqin; Ingham, Eileen; Fisher, John; Tipper, Joanne L

2014-04-01

It has recently been shown that the wear of ultra-high-molecular-weight polyethylene in hip and knee prostheses leads to the generation of nanometre-sized particles, in addition to micron-sized particles. The biological activity of nanometre-sized ultra-high-molecular-weight polyethylene wear particles has not, however, previously been studied due to difficulties in generating sufficient volumes of nanometre-sized ultra-high-molecular-weight polyethylene wear particles suitable for cell culture studies. In this study, wear simulation methods were investigated to generate a large volume of endotoxin-free clinically relevant nanometre-sized ultra-high-molecular-weight polyethylene wear particles. Both single-station and six-station multidirectional pin-on-plate wear simulators were used to generate ultra-high-molecular-weight polyethylene wear particles under sterile and non-sterile conditions. Microbial contamination and endotoxin levels in the lubricants were determined. The results indicated that microbial contamination was absent and endotoxin levels were low and within acceptable limits for the pharmaceutical industry, when a six-station pin-on-plate wear simulator was used to generate ultra-high-molecular-weight polyethylene wear particles in a non-sterile environment. Different pore-sized polycarbonate filters were investigated to isolate nanometre-sized ultra-high-molecular-weight polyethylene wear particles from the wear test lubricants. The use of the filter sequence of 10, 1, 0.1, 0.1 and 0.015 µm pore sizes allowed successful isolation of ultra-high-molecular-weight polyethylene wear particles with a size range of < 100 nm, which was suitable for cell culture studies.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Structure- and ligand-based structure-activity relationships for a series of inhibitors of aldolase.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2012-12-01

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r²=0.98 and q²=0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pKi values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.

Identifying Molecular Targets for Chemoprevention in a Rat Model

DTIC Science & Technology

2005-12-01

95616-8671 REPORT DATE: December 2005 TYPE OF REPORT: Annual PREPARED FOR: U.S. Army Medical Research and Materiel Command...California 95616-8671 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) U.S. Army Medical Research and...addition, it induces high levels of oxidative damage in the target tissues. The scope of this research includes: 1) Generation of a rat model, 2) Analysis

Beyond the Central Dogma: Model-Based Learning of How Genes Determine Phenotypes

PubMed Central

Reinagel, Adam; Bray Speth, Elena

2016-01-01

In an introductory biology course, we implemented a learner-centered, model-based pedagogy that frequently engaged students in building conceptual models to explain how genes determine phenotypes. Model-building tasks were incorporated within case studies and aimed at eliciting students’ understanding of 1) the origin of variation in a population and 2) how genes/alleles determine phenotypes. Guided by theory on hierarchical development of systems-thinking skills, we scaffolded instruction and assessment so that students would first focus on articulating isolated relationships between pairs of molecular genetics structures and then integrate these relationships into an explanatory network. We analyzed models students generated on two exams to assess whether students’ learning of molecular genetics progressed along the theoretical hierarchical sequence of systems-thinking skills acquisition. With repeated practice, peer discussion, and instructor feedback over the course of the semester, students’ models became more accurate, better contextualized, and more meaningful. At the end of the semester, however, more than 25% of students still struggled to describe phenotype as an output of protein function. We therefore recommend that 1) practices like modeling, which require connecting genes to phenotypes; and 2) well-developed case studies highlighting proteins and their functions, take center stage in molecular genetics instruction. PMID:26903496

Molecular dissection of Norrie disease.

PubMed

Berger, W

1998-01-01

Norrie disease (ND) is a severe form of congenital blindness accompanied by mental retardation and/or deafness in at least one third of the patients. This article summarizes advances in the molecular genetic analysis of this disease during the last 13 years, including mapping and cloning of the human gene and the generation and characterization of a mouse model. Genetic linkage studies and physical mapping strategies have assigned the ND locus to the proximal short arm of the human X chromosome. The identification of chromosomal rearrangements in several patients, such as microdeletions, enabled the isolation of the ND gene by a positional cloning approach. Numerous point mutations in this gene have been identified in three distinct clinical entities: (1) ND, (2) familial and sporadic exudative vitreoretinopathy, and (3) retinopathy of prematurity. The gene encodes a relatively small protein, consisting of 133 amino acids. The function of the gene product is yet unknown, although homologies with known proteins and molecular modelling data suggest a role in the regulation of cell interaction or differentiation processes. A mouse model has been generated to shed more light on early pathogenic events involved in ND and allelic disorders. The mouse homologous protein is highly identical (94%) to the human polypeptide. The gene is expressed in the neuronal layers of the mouse retina, the cerebellum and olfactory epithelium. Mutant mice show snowflake-like opacities within the vitreous, dysgenesis of the ganglion cell layer and occasionally degeneration of photoreceptor cells. The mouse phenotype does not include phthisis bulbi and, overall, resembles a mild form of ND. Electrophysiological studies revealed a severely altered electroretinogram b-wave. These results suggest a primary defect in the inner neuronal layers of the retina. Defects in the vitreous and photoreceptor cell layer are most likely secondary effects. Further histological, functional and molecular studies of the mouse model are needed to provide additional information on disease associated pathways.

Conformational and Structural Properties of High Functionality Dendrimer-like Star Polymers Synthesized from Living Polymerization Techniques

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

Pople, John A

2001-03-22

The design, synthesis and solution properties of dendritic-linear hybrid macromolecules is described. The synthetic strategy employs living ring-opening polymerization in combination with selective and quantitative organic transformations for the preparation of new molecular architectures similar to classical star polymers and dendrimers. The polymers were constructed from high molecular weight poly(e-caprolactone) initiated from the surface hydroxyl groups of dendrimers derived from bis(hydroxymethyl) propionic acid (bis-MPA) in the presence of stannous 2-ethyl hexanoate (Sn(Oct)2). In this way, star and hyperstar poly(e-caprolactones) were elaborated depending on the generation of dendrimer employed. The ROP from these hydroxy groups was found to be a facilemore » process leading to controlled molecular weight, low dispersity products (Mw/Mn) < 1.15. In addition to the use of dendrimers as building blocks to star polymers, functional dendrons derived from bis-MPA were attached to chain ends of the star polymers, yielding structures that closely resemble that of the most advanced dendrimers. Measurements of the solution properties (hydrodynamic volume vs. molecular weight) on the dendritic-linear hybrids show a deviation from linearity, with a lower than expected hydrodynamic volume, analogous to the solution properties of dendrimers of high generation number. The onset of the deviation begins with the polymers initiated from the second generation dendrimer of bis-MPA and becomes more exaggerated with the higher generations. It was found that polymerization amplifies the nonlinear solution behavior of dendrimers. Small angle neutron scattering (SANS) measurements revealed that the radius of gyration scaled with arm functionality (f) as f 2/3, in accordance with the Daoud-Cotton model for many arm star polymer.« less

The dynamical role of the central molecular ring within the framework of a seven-component Galaxy model

NASA Astrophysics Data System (ADS)

Simin, A. A.; Fridman, A. M.; Haud, U. A.

1991-09-01

A Galaxy model in which the surface density of the gas component has a sharp (two orders of magnitude) jump in the region of the outer radius of the molecular ring is constructed on the basis of observational data. This model is used to calculate the contributions of each population to the model curve of Galactic rotation. The value of the dimensionless increment of hydrodynamical instability for the gas component, being much less than 1, coincides with a similar magnitude for the same gas in the gravity field of the entire Galaxy. It is concluded that the unstable gas component of the Galaxy lies near the limit of the hydrodynamical instability, which is in accordance with the Le Chatelier principle. The stellar populations of the Galaxy probably do not affect the generation of the spiral structure in the gaseous component.

Quantitative Structure-Activity Relationship of Insecticidal Activity of Benzyl Ether Diamidine Derivatives

NASA Astrophysics Data System (ADS)

Zhai, Mengting; Chen, Yan; Li, Jing; Zhou, Jun

2017-12-01

The molecular electrongativity distance vector (MEDV-13) was used to describe the molecular structure of benzyl ether diamidine derivatives in this paper, Based on MEDV-13, The three-parameter (M 3, M 15, M 47) QSAR model of insecticidal activity (pIC 50) for 60 benzyl ether diamidine derivatives was constructed by leaps-and-bounds regression (LBR) . The traditional correlation coefficient (R) and the cross-validation correlation coefficient (R CV ) were 0.975 and 0.971, respectively. The robustness of the regression model was validated by Jackknife method, the correlation coefficient R were between 0.971 and 0.983. Meanwhile, the independent variables in the model were tested to be no autocorrelation. The regression results indicate that the model has good robust and predictive capabilities. The research would provide theoretical guidance for the development of new generation of anti African trypanosomiasis drugs with efficiency and low toxicity.

Computational approach on PEB process in EUV resist: multi-scale simulation

NASA Astrophysics Data System (ADS)

Kim, Muyoung; Moon, Junghwan; Choi, Joonmyung; Lee, Byunghoon; Jeong, Changyoung; Kim, Heebom; Cho, Maenghyo

2017-03-01

For decades, downsizing has been a key issue for high performance and low cost of semiconductor, and extreme ultraviolet lithography is one of the promising candidates to achieve the goal. As a predominant process in extreme ultraviolet lithography on determining resolution and sensitivity, post exposure bake has been mainly studied by experimental groups, but development of its photoresist is at the breaking point because of the lack of unveiled mechanism during the process. Herein, we provide theoretical approach to investigate underlying mechanism on the post exposure bake process in chemically amplified resist, and it covers three important reactions during the process: acid generation by photo-acid generator dissociation, acid diffusion, and deprotection. Density functional theory calculation (quantum mechanical simulation) was conducted to quantitatively predict activation energy and probability of the chemical reactions, and they were applied to molecular dynamics simulation for constructing reliable computational model. Then, overall chemical reactions were simulated in the molecular dynamics unit cell, and final configuration of the photoresist was used to predict the line edge roughness. The presented multiscale model unifies the phenomena of both quantum and atomic scales during the post exposure bake process, and it will be helpful to understand critical factors affecting the performance of the resulting photoresist and design the next-generation material.

NIF Discovery Science Eagle Nebula

NASA Astrophysics Data System (ADS)

Kane, Jave; Martinez, David; Pound, Marc; Heeter, Robert; Casner, Alexis; Villette, Bruno; Mancini, Roberto

2017-10-01

The University of Maryland and and LLNL are investigating the origin and dynamics of the famous Pillars of the Eagle Nebula and similar parsec-scale structures at the boundaries of HII regions in molecular hydrogen clouds. The National Ignition Facility (NIF) Discovery Science program Eagle Nebula has performed NIF shots to study models of pillar formation. The shots feature a new long-duration x-ray source, in which multiple hohlraums mimicking a cluster of stars are driven with UV light in series for 10 to 15 ns each to create a 30 to 60 ns output x-ray pulse. The source generates deeply nonlinear hydrodynamics in the Eagle science package, a structure of dense plastic and foam mocking up a molecular cloud containing a dense core. Omega EP and NIF shots have validated the source concept, showing that earlier hohlraums do not compromise later ones by preheat or by ejecting ablated plumes that deflect later beams. The NIF shots generated radiographs of shadowing-model pillars, and also showed evidence that cometary structures can be generated. The velocity and column density profiles of the NIF shadowing and cometary pillars have been compared with observations of the Eagle Pillars made at the millimeter-wave BIMA and CARMA observatories. Prepared by LLNL under Contract DE-AC52-07NA27344.

SHAPEMOL: Modelling molecular line emission in protoplanetary and planetary nebulae with SHAPE

NASA Astrophysics Data System (ADS)

Santander-García, M.; Bujarrabal, V.; Steffen, W.; Koning, N.

2014-04-01

Modern instrumentation in radioastronomy constitutes a valuable tool for studying the Universe: ALMA will reach unprecedented sensitivities and spatial resolution, while Herschel/HIFI has opened a new window for probing molecular warm gas (˜50-1000 K). On the other hand, the SHAPE software has emerged in the last few years as the standard tool for determining the morphology and velocity field of different kinds of gaseous emission nebulae via spatio-kinematical modelling. Standard SHAPE implements radiative transfer solving, but it is only available for atomic species and not for molecules. Being aware of the growing importance of the development of tools for easying the analyses of molecular data from new era observatories, we introduce the computer code shapemol, a plug-in for SHAPE v5.0 with which we intend to fill the so far empty molecular niche. Shapemol enables spatio-kinematic modeling with accurate non-LTE calculations of line excitation and radiative transfer in molecular species. This code has been succesfully tested in the study of the excitation conditions of the molecular envelope of the young planetary nebula NGC 7027 using data from Herschel/HIFI and IRAM 30m. Currently, it allows radiative transfer solving in the 12CO and 13CO J=1-0 to J=17-16 lines. Shapemol, used along SHAPE, allows to easily generate synthetic maps to test against interferometric observations, as well as synthetic line profiles to match single-dish observations.

Atomic Forces for Geometry-Dependent Point Multipole and Gaussian Multipole Models

PubMed Central

Elking, Dennis M.; Perera, Lalith; Duke, Robert; Darden, Thomas; Pedersen, Lee G.

2010-01-01

In standard treatments of atomic multipole models, interaction energies, total molecular forces, and total molecular torques are given for multipolar interactions between rigid molecules. However, if the molecules are assumed to be flexible, two additional multipolar atomic forces arise due to 1) the transfer of torque between neighboring atoms, and 2) the dependence of multipole moment on internal geometry (bond lengths, bond angles, etc.) for geometry-dependent multipole models. In the current study, atomic force expressions for geometry-dependent multipoles are presented for use in simulations of flexible molecules. The atomic forces are derived by first proposing a new general expression for Wigner function derivatives ∂Dlm′m/∂Ω. The force equations can be applied to electrostatic models based on atomic point multipoles or Gaussian multipole charge density. Hydrogen bonded dimers are used to test the inter-molecular electrostatic energies and atomic forces calculated by geometry-dependent multipoles fit to the ab initio electrostatic potential (ESP). The electrostatic energies and forces are compared to their reference ab initio values. It is shown that both static and geometry-dependent multipole models are able to reproduce total molecular forces and torques with respect to ab initio, while geometry-dependent multipoles are needed to reproduce ab initio atomic forces. The expressions for atomic force can be used in simulations of flexible molecules with atomic multipoles. In addition, the results presented in this work should lead to further development of next generation force fields composed of geometry-dependent multipole models. PMID:20839297

Building an International Initiative to Infuse Novel Cancer Models into the Research Community | Office of Cancer Genomics

Cancer.gov

My name is Caitlyn Barrett and I am the Scientific Program Manager for the Human Cancer Model Initiative (HCMI) in the Office of Cancer Genomics (OCG). In my role within the HCMI, I am helping to establish communication pathways and build the foundation for collaboration that will enable the completion of the Initiative’s aim to develop as many as 1000 next-generation cancer models, established from patient tumors and accompanied by clinical and molecular data.

Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors.

PubMed

Nargotra, Amit; Sharma, Sujata; Koul, Jawahir Lal; Sangwan, Pyare Lal; Khan, Inshad Ali; Kumar, Ashwani; Taneja, Subhash Chander; Koul, Surrinder

2009-10-01

Quantitative structure activity relationship (QSAR) analysis of piperine analogs as inhibitors of efflux pump NorA from Staphylococcus aureus has been performed in order to obtain a highly accurate model enabling prediction of inhibition of S. aureus NorA of new chemical entities from natural sources as well as synthetic ones. Algorithm based on genetic function approximation method of variable selection in Cerius2 was used to generate the model. Among several types of descriptors viz., topological, spatial, thermodynamic, information content and E-state indices that were considered in generating the QSAR model, three descriptors such as partial negative surface area of the compounds, area of the molecular shadow in the XZ plane and heat of formation of the molecules resulted in a statistically significant model with r(2)=0.962 and cross-validation parameter q(2)=0.917. The validation of the QSAR models was done by cross-validation, leave-25%-out and external test set prediction. The theoretical approach indicates that the increase in the exposed partial negative surface area increases the inhibitory activity of the compound against NorA whereas the area of the molecular shadow in the XZ plane is inversely proportional to the inhibitory activity. This model also explains the relationship of the heat of formation of the compound with the inhibitory activity. The model is not only able to predict the activity of new compounds but also explains the important regions in the molecules in quantitative manner.

Transcriptome analysis using next generation sequencing reveals molecular signatures of diabetic retinopathy and efficacy of candidate drugs.

PubMed

Kandpal, Raj P; Rajasimha, Harsha K; Brooks, Matthew J; Nellissery, Jacob; Wan, Jun; Qian, Jiang; Kern, Timothy S; Swaroop, Anand

2012-01-01

To define gene expression changes associated with diabetic retinopathy in a mouse model using next generation sequencing, and to utilize transcriptome signatures to assess molecular pathways by which pharmacological agents inhibit diabetic retinopathy. We applied a high throughput RNA sequencing (RNA-seq) strategy using Illumina GAIIx to characterize the entire retinal transcriptome from nondiabetic and from streptozotocin-treated mice 32 weeks after induction of diabetes. Some of the diabetic mice were treated with inhibitors of receptor for advanced glycation endproducts (RAGE) and p38 mitogen activated protein (MAP) kinase, which have previously been shown to inhibit diabetic retinopathy in rodent models. The transcripts and alternatively spliced variants were determined in all experimental groups. Next generation sequencing-based RNA-seq profiles provided comprehensive signatures of transcripts that are altered in early stages of diabetic retinopathy. These transcripts encoded proteins involved in distinct yet physiologically relevant disease-associated pathways such as inflammation, microvasculature formation, apoptosis, glucose metabolism, Wnt signaling, xenobiotic metabolism, and photoreceptor biology. Significant upregulation of crystallin transcripts was observed in diabetic animals, and the diabetes-induced upregulation of these transcripts was inhibited in diabetic animals treated with inhibitors of either RAGE or p38 MAP kinase. These two therapies also showed dissimilar regulation of some subsets of transcripts that included alternatively spliced versions of arrestin, neutral sphingomyelinase activation associated factor (Nsmaf), SH3-domain GRB2-like interacting protein 1 (Sgip1), and axin. Diabetes alters many transcripts in the retina, and two therapies that inhibit the vascular pathology similarly inhibit a portion of these changes, pointing to possible molecular mechanisms for their beneficial effects. These therapies also changed the abundance of various alternatively spliced versions of signaling transcripts, suggesting a possible role of alternative splicing in disease etiology. Our studies clearly demonstrate RNA-seq as a comprehensive strategy for identifying disease-specific transcripts, and for determining comparative profiles of molecular changes mediated by candidate drugs.

Human gastric cancer modelling using organoids.

PubMed

Seidlitz, Therese; Merker, Sebastian R; Rothe, Alexander; Zakrzewski, Falk; von Neubeck, Cläre; Grützmann, Konrad; Sommer, Ulrich; Schweitzer, Christine; Schölch, Sebastian; Uhlemann, Heike; Gaebler, Anne-Marlene; Werner, Kristin; Krause, Mechthild; Baretton, Gustavo B; Welsch, Thilo; Koo, Bon-Kyoung; Aust, Daniela E; Klink, Barbara; Weitz, Jürgen; Stange, Daniel E

2018-04-27

Gastric cancer is the second leading cause of cancer-related deaths and the fifth most common malignancy worldwide. In this study, human and mouse gastric cancer organoids were generated to model the disease and perform drug testing to delineate treatment strategies. Human gastric cancer organoid cultures were established, samples classified according to their molecular profile and their response to conventional chemotherapeutics tested. Targeted treatment was performed according to specific druggable mutations. Mouse gastric cancer organoid cultures were generated carrying molecular subtype-specific alterations. Twenty human gastric cancer organoid cultures were established and four selected for a comprehensive in-depth analysis. Organoids demonstrated divergent growth characteristics and morphologies. Immunohistochemistry showed similar characteristics to the corresponding primary tissue. A divergent response to 5-fluoruracil, oxaliplatin, irinotecan, epirubicin and docetaxel treatment was observed. Whole genome sequencing revealed a mutational spectrum that corresponded to the previously identified microsatellite instable, genomic stable and chromosomal instable subtypes of gastric cancer. The mutational landscape allowed targeted therapy with trastuzumab for ERBB2 alterations and palbociclib for CDKN2A loss. Mouse cancer organoids carrying Kras and Tp53 or Apc and Cdh1 mutations were characterised and serve as model system to study the signalling of induced pathways. We generated human and mouse gastric cancer organoids modelling typical characteristics and altered pathways of human gastric cancer. Successful interference with activated pathways demonstrates their potential usefulness as living biomarkers for therapy response testing. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Rational chemical design of the next generation of molecular imaging probes based on physics and biology: mixing modalities, colors and signals

PubMed Central

Longmire, Michelle R.; Ogawa, Mikako; Choyke, Peter L.

2012-01-01

In recent years, numerous in vivo molecular imaging probes have been developed. As a consequence, much has been published on the design and synthesis of molecular imaging probes focusing on each modality, each type of material, or each target disease. More recently, second generation molecular imaging probes with unique, multi-functional, or multiplexed characteristics have been designed. This critical review focuses on (i) molecular imaging using combinations of modalities and signals that employ the full range of the electromagnetic spectra, (ii) optimized chemical design of molecular imaging probes for in vivo kinetics based on biology and physiology across a range of physical sizes, (iii) practical examples of second generation molecular imaging probes designed to extract complementary data from targets using multiple modalities, color, and comprehensive signals (277 references). PMID:21607237

Strategy to discover diverse optimal molecules in the small molecule universe.

PubMed

Rupakheti, Chetan; Virshup, Aaron; Yang, Weitao; Beratan, David N

2015-03-23

The small molecule universe (SMU) is defined as a set of over 10(60) synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We take a stochastic approach and extend the ACSESS framework ( Virshup et al. J. Am. Chem. Soc. 2013 , 135 , 7296 - 7303 ) to develop diversity oriented molecular libraries that can generate a set of compounds that is representative of the small molecule universe and that also biases the library toward favorable physical property values. We show that the approach is efficient compared to exhaustive enumeration and to existing evolutionary algorithms for generating such libraries by testing in the NKp fitness landscape model and in the fully enumerated GDB-9 chemical universe containing 3 × 10(5) molecules.

Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe

PubMed Central

2015-01-01

The small molecule universe (SMU) is defined as a set of over 1060 synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We take a stochastic approach and extend the ACSESS framework (Virshup et al. J. Am. Chem. Soc.2013, 135, 7296–730323548177) to develop diversity oriented molecular libraries that can generate a set of compounds that is representative of the small molecule universe and that also biases the library toward favorable physical property values. We show that the approach is efficient compared to exhaustive enumeration and to existing evolutionary algorithms for generating such libraries by testing in the NKp fitness landscape model and in the fully enumerated GDB-9 chemical universe containing 3 × 105 molecules. PMID:25594586

A review of the evolution of viviparity in squamate reptiles: the past, present and future role of molecular biology and genomics.

PubMed

Murphy, Bridget F; Thompson, Michael B

2011-07-01

Squamate reptiles (lizards and snakes) offer a unique model system for testing hypotheses about the evolutionary transition from oviparity (egg-laying) to viviparity (live-bearing) in amniote vertebrates. The evolution of squamate viviparity has occurred remarkably frequently (>108 times) and has resulted in major changes in reproductive physiology. Such frequent changes in reproductive strategy pose two questions: (1) what are the molecular mechanisms responsible for the evolution of squamate viviparity? (2) Are these molecular mechanisms the same for separate origins of viviparity? Molecular approaches, such as RT-PCR, in situ hybridisation, Western blotting and immunofluorescence, have been invaluable for identifying genes and proteins that are involved in squamate placental development, materno-foetal immunotolerance, placental transport, placental angiogenesis, hormone synthesis and hormone receptor expression. However, the candidate-gene or -protein approach that has been used until now does not allow for de novo gene/protein discovery; results to date suggest that the reproductive physiologies of mammals and squamate reptiles are very similar, but this conclusion may simply be due to a limited capacity to study the subset of genes and proteins that are unique to reptiles. Progress has also been slowed by the lack of appropriate molecular and genomic resources for squamate reptiles. The advent of next-generation sequencing provides a relatively inexpensive way to conduct rapid high-throughput sequencing of genomes and transcriptomes. We discuss the potential use of next-generation sequencing technologies to analyse differences in gene expression between oviparous and viviparous squamates, provide important sequence information for reptiles, and generate testable hypotheses for the evolution of viviparity.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

PubMed

Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

2017-08-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

PubMed Central

Sing-Long, Carlos A.

2017-01-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates. PMID:28989618

Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer-aquitard complexes.

PubMed

Zhang, Yong; Green, Christopher T; Tick, Geoffrey R

2015-01-01

This study evaluates the role of the Peclet number as affected by molecular diffusion in transient anomalous transport, which is one of the major knowledge gaps in anomalous transport, by combining Monte Carlo simulations and stochastic model analysis. Two alluvial settings containing either short- or long-connected hydrofacies are generated and used as media for flow and transport modeling. Numerical experiments show that 1) the Peclet number affects both the duration of the power-law segment of tracer breakthrough curves (BTCs) and the transition rate from anomalous to Fickian transport by determining the solute residence time for a given low-permeability layer, 2) mechanical dispersion has a limited contribution to the anomalous characteristics of late-time transport as compared to molecular diffusion due to an almost negligible velocity in floodplain deposits, and 3) the initial source dimensions only enhance the power-law tail of the BTCs at short travel distances. A tempered stable stochastic (TSS) model is then applied to analyze the modeled transport. Applications show that the time-nonlocal parameters in the TSS model relate to the Peclet number, Pe. In particular, the truncation parameter in the TSS model increases nonlinearly with a decrease in Pe due to the decrease of the mean residence time, and the capacity coefficient increases with an increase in molecular diffusion which is probably due to the increase in the number of immobile particles. The above numerical experiments and stochastic analysis therefore reveal that the Peclet number as affected by molecular diffusion controls transient anomalous transport in alluvial aquifer-aquitard complexes. Copyright © 2015 Elsevier B.V. All rights reserved.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

DOE PAGES

Yang, Qian; Sing-Long, Carlos A.; Reed, Evan J.

2017-06-19

Here, we propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. Conversely, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our methodmore » on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. Furthermore, we describe a framework in this work that paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.« less

Structural Changes in Lipid Vesicles Generated by the Shock Blast Waves: Coarse-Grained Molecular Dynamics Simulation

DTIC Science & Technology

2013-11-01

duration, or shock-pulse shape. Used in this computational study is a coarse-grained model of the lipid vesicle as a simplified model of a cell...Figures iv List of Tables iv 1. Introduction 1 2. Model and Methods 3 3. Results and Discussion 6 3.1 Simulation of the Blast Waves with Low Peak...realistic detail but to focus on a simple model of the major constituent of a cell membrane, the phospholipid bilayer. In this work, we studied the

Pericentrin in cellular function and disease

PubMed Central

Delaval, Benedicte

2010-01-01

Pericentrin is an integral component of the centrosome that serves as a multifunctional scaffold for anchoring numerous proteins and protein complexes. Through these interactions, pericentrin contributes to a diversity of fundamental cellular processes. Recent studies link pericentrin to a growing list of human disorders. Studies on pericentrin at the cellular, molecular, and, more recently, organismal level, provide a platform for generating models to elucidate the etiology of these disorders. Although the complexity of phenotypes associated with pericentrin-mediated disorders is somewhat daunting, insights into the cellular basis of disease are beginning to come into focus. In this review, we focus on human conditions associated with loss or elevation of pericentrin and propose cellular and molecular models that might explain them. PMID:19951897

Nonlinear optics of astaxanthin thin films

NASA Astrophysics Data System (ADS)

Esser, A.; Fisch, Herbert; Haas, Karl-Heinz; Haedicke, E.; Paust, J.; Schrof, Wolfgang; Ticktin, Anton

1993-02-01

Carotinoids exhibit large nonlinear optical properties due to their extended (pi) -electron system. Compared to other polyenes which show a broad distribution of conjugation lengths, carotinoids exhibit a well defined molecular structure, i.e. a well defined conjugation length. Therefore the carotinoid molecules can serve as model compounds to study the relationship between structure and nonlinear optical properties. In this paper the synthesis of four astaxanthins with C-numbers ranging from 30 to 60, their preparation into thin films, wavelength dispersive Third Harmonic Generation (THG) measurements and some molecular modelling calculations will be presented. Resonant (chi) (3) values reach 1.2(DOT)10-10 esu for C60 astaxanthin. In the nonresonant regime a figure of merit (chi) (3)/(alpha) of several 10-13 esu-cm is demonstrated.

Reduced Order Models for Reactions of Energetic Materials

NASA Astrophysics Data System (ADS)

Kober, Edward

The formulation of reduced order models for the reaction chemistry of energetic materials under high pressures is needed for the development of mesoscale models in the areas of initiation, deflagration and detonation. Phenomenologically, 4-8 step models have been formulated from the analysis of cook-off data by analyzing the temperature rise of heated samples. Reactive molecular dynamics simulations have been used to simulate many of these processes, but reducing the results of those simulations to simple models has not been achieved. Typically, these efforts have focused on identifying molecular species and detailing specific chemical reactions. An alternative approach is presented here that is based on identifying the coordination geometries of each atom in the simulation and tracking classes of reactions by correlated changes in these geometries. Here, every atom and type of reaction is documented for every time step; no information is lost from unsuccessful molecular identification. Principal Component Analysis methods can then be used to map out the effective chemical reaction steps. For HMX and TATB decompositions simulated with ReaxFF, 90% of the data can be explained by 4-6 steps, generating models similar to those from the cook-off analysis. By performing these simulations at a variety of temperatures and pressures, both the activation and reaction energies and volumes can then be extracted.

Independent saturation of three TrpRS subsites generates a partially assembled state similar to those observed in molecular simulations

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

Laowanapiban, Poramaet; Kapustina, Maryna; Vonrhein, Clemens

2009-03-05

Two new crystal structures of Bacillus stearothermophilus tryptophanyl-tRNA synthetase (TrpRS) afford evidence that a closed interdomain hinge angle requires a covalent bond between AMP and an occupant of either pyrophosphate or tryptophan subsite. They also are within experimental error of a cluster of structures observed in a nonequilibrium molecular dynamics simulation showing partial active-site assembly. Further, the highest energy structure in a minimum action pathway computed by using elastic network models for Open and Pretransition state (PreTS) conformations for the fully liganded TrpRS monomer is intermediate between that simulated structure and a partially disassembled structure from a nonequilibrium molecular dynamicsmore » trajectory for the unliganded PreTS. These mutual consistencies provide unexpected validation of inferences drawn from molecular simulations.« less

Estimation of the Young’s modulus of cellulose Iß by MM3 and quantum mechanics

USDA-ARS?s Scientific Manuscript database

Young’s modulus provides a measure of the resistance to deformation of an elastic material. In this study, modulus estimations for models of cellulose Iß relied on calculations performed with molecular mechanics (MM) and quantum mechanics (QM) programs. MM computations used the second generation emp...

Virtual Environments Supporting Learning and Communication in Special Needs Education

ERIC Educational Resources Information Center

Cobb, Sue V. G.

2007-01-01

Virtual reality (VR) describes a set of technologies that allow users to explore and experience 3-dimensional computer-generated "worlds" or "environments." These virtual environments can contain representations of real or imaginary objects on a small or large scale (from modeling of molecular structures to buildings, streets, and scenery of a…

mrtailor: a tool for PDB-file preparation for the generation of external restraints.

PubMed

Gruene, Tim

2013-09-01

Model building starting from, for example, a molecular-replacement solution with low sequence similarity introduces model bias, which can be difficult to detect, especially at low resolution. The program mrtailor removes low-similarity regions from a template PDB file according to sequence similarity between the target sequence and the template sequence and maps the target sequence onto the PDB file. The modified PDB file can be used to generate external restraints for low-resolution refinement with reduced model bias and can be used as a starting point for model building and refinement. The program can call ProSMART [Nicholls et al. (2012), Acta Cryst. D68, 404-417] directly in order to create external restraints suitable for REFMAC5 [Murshudov et al. (2011), Acta Cryst. D67, 355-367]. Both a command-line version and a GUI exist.

A distance-limited sample of massive molecular outflows

NASA Astrophysics Data System (ADS)

Maud, L. T.; Moore, T. J. T.; Lumsden, S. L.; Mottram, J. C.; Urquhart, J. S.; Hoare, M. G.

2015-10-01

We have observed 99 mid-infrared-bright, massive young stellar objects and compact H II regions drawn from the Red MSX source survey in the J = 3-2 transition of 12CO and 13CO, using the James Clerk Maxwell Telescope. 89 targets are within 6 kpc of the Sun, covering a representative range of luminosities and core masses. These constitute a relatively unbiased sample of bipolar molecular outflows associated with massive star formation. Of these, 59, 17 and 13 sources (66, 19 and 15 per cent) are found to have outflows, show some evidence of outflow, and have no evidence of outflow, respectively. The time-dependent parameters of the high-velocity molecular flows are calculated using a spatially variable dynamic time-scale. The canonical correlations between the outflow parameters and source luminosity are recovered and shown to scale with those of low-mass sources. For coeval star formation, we find the scaling is consistent with all the protostars in an embedded cluster providing the outflow force, with massive stars up to ˜30 M⊙ generating outflows. Taken at face value, the results support the model of a scaled-up version of the accretion-related outflow-generation mechanism associated with discs and jets in low-mass objects with time-averaged accretion rates of ˜10-3 M⊙ yr-1 on to the cores. However, we also suggest an alternative model, in which the molecular outflow dynamics are dominated by the entrained mass and are unrelated to the details of the acceleration mechanism. We find no evidence that outflows contribute significantly to the turbulent kinetic energy of the surrounding dense cores.

Molecular dynamics simulations and docking studies on 3D models of the heterodimeric and homodimeric 5-HT(2A) receptor subtype.

PubMed

Bruno, Agostino; Beato, Claudia; Costantino, Gabriele

2011-04-01

G-protein coupled receptors may exist as functional homodimers, heterodimers and even as higher aggregates. In this work, we investigate the 5-HT(2A) receptor, which is a known target for antipsychotic drugs. Recently, 5-HT(2A) has been shown to form functional homodimers and heterodimers with the mGluR2 receptor. The objective of this study is to build up 3D models of the 5-HT(2A)/mGluR2 heterodimer and of the 5-HT(2A)-5-HT(2A) homodimer, and to evaluate the impact of the dimerization interface on the shape of the 5-HT(2A) binding pocket by using molecular dynamics simulations and docking studies. The heterodimer, homodimer and monomeric 5-HT(2A) receptors were simulated by molecular dynamics for 40 ns each. The trajectories were clustered and representative structures of six clusters for each system were generated. Inspection of the these representative structures clearly indicate an effect of the dimerization interface on the topology of the binding pocket. Docking studies allowed to generate receiver operating characteristic curves for a set of 5-HT(2A) ligands, indicating that different complexes prefer different classes of 5-HT(2A) ligands. This study clearly indicates that the presence of a dimerization interface must explicitly be considered when studying G-protein coupled receptors known to exist as dimers. Molecular dynamics simulation and cluster analysis are appropriate tools to study the phenomenon.

Generation of Synthetic Copolymer Libraries by Combinatorial Assembly on Nucleic Acid Templates.

PubMed

Kong, Dehui; Yeung, Wayland; Hili, Ryan

2016-07-11

Recent advances in nucleic acid-templated copolymerization have expanded the scope of sequence-controlled synthetic copolymers beyond the molecular architectures witnessed in nature. This has enabled the power of molecular evolution to be applied to synthetic copolymer libraries to evolve molecular function ranging from molecular recognition to catalysis. This Review seeks to summarize different approaches available to generate sequence-defined monodispersed synthetic copolymer libraries using nucleic acid-templated polymerization. Key concepts and principles governing nucleic acid-templated polymerization, as well as the fidelity of various copolymerization technologies, will be described. The Review will focus on methods that enable the combinatorial generation of copolymer libraries and their molecular evolution for desired function.

Animal models of pituitary neoplasia

PubMed Central

Lines, K.E.; Stevenson, M.; Thakker, R.V.

2016-01-01

Pituitary neoplasias can occur as part of a complex inherited disorder, or more commonly as sporadic (non-familial) disease. Studies of the molecular and genetic mechanisms causing such pituitary tumours have identified dysregulation of >35 genes, with many revealed by studies in mice, rats and zebrafish. Strategies used to generate these animal models have included gene knockout, gene knockin and transgenic over-expression, as well as chemical mutagenesis and drug induction. These animal models provide an important resource for investigation of tissue-specific tumourigenic mechanisms, and evaluations of novel therapies, illustrated by studies into multiple endocrine neoplasia type 1 (MEN1), a hereditary syndrome in which ∼30% of patients develop pituitary adenomas. This review describes animal models of pituitary neoplasia that have been generated, together with some recent advances in gene editing technologies, and an illustration of the use of the Men1 mouse as a pre clinical model for evaluating novel therapies. PMID:26320859

Role of Nurr1 in the Generation and Differentiation of Dopaminergic Neurons from Stem Cells.

PubMed

Rodríguez-Traver, Eva; Solís, Oscar; Díaz-Guerra, Eva; Ortiz, Óscar; Vergaño-Vera, Eva; Méndez-Gómez, Héctor R; García-Sanz, Patricia; Moratalla, Rosario; Vicario-Abejón, Carlos

2016-07-01

NURR1 is an essential transcription factor for the differentiation, maturation, and maintenance of midbrain dopaminergic neurons (DA neurons) as it has been demonstrated using knock-out mice. DA neurons of the substantia nigra pars compacta degenerate in Parkinson's disease (PD) and mutations in the Nurr1 gene have been associated with this human disease. Thus, the study of NURR1 actions in vivo is fundamental to understand the mechanisms of neuron generation and degeneration in the dopaminergic system. Here, we present and discuss findings indicating that NURR1 is a valuable molecular tool for the in vitro generation of DA neurons which could be used for modeling and studying PD in cell culture and in transplantation approaches. Transduction of Nurr1 alone or in combination with other transcription factors such as Foxa2, Ngn2, Ascl1, and Pitx3, induces the generation of DA neurons, which upon transplantation have the capacity to survive and restore motor behavior in animal models of PD. We show that the survival of transplanted neurons is increased when the Nurr1-transduced olfactory bulb stem cells are treated with GDNF. The use of these and other factors with the induced pluripotent stem cell (iPSC)-based technology or the direct reprogramming of astrocytes or fibroblasts into human DA neurons has produced encouraging results for the study of the cellular and molecular mechanisms of neurodegeneration in PD and for the search of new treatments for this disease.

Acquired MET expression confers resistance to EGFR inhibition in a mouse model of glioblastoma multiforme.

PubMed

Jun, H J; Acquaviva, J; Chi, D; Lessard, J; Zhu, H; Woolfenden, S; Bronson, R T; Pfannl, R; White, F; Housman, D E; Iyer, L; Whittaker, C A; Boskovitz, A; Raval, A; Charest, A

2012-06-21

Glioblastoma multiforme (GBM) is an aggressive brain tumor for which there is no cure. Overexpression of wild-type epidermal growth factor receptor (EGFR) and loss of the tumor suppressor genes Ink4a/Arf and PTEN are salient features of this deadly cancer. Surprisingly, targeted inhibition of EGFR has been clinically disappointing, demonstrating an innate ability for GBM to develop resistance. Efforts at modeling GBM in mice using wild-type EGFR have proven unsuccessful to date, hampering endeavors at understanding molecular mechanisms of therapeutic resistance. Here, we describe a unique genetically engineered mouse model of EGFR-driven gliomagenesis that uses a somatic conditional overexpression and chronic activation of wild-type EGFR in cooperation with deletions in the Ink4a/Arf and PTEN genes in adult brains. Using this model, we establish that chronic activation of wild-type EGFR with a ligand is necessary for generating tumors with histopathological and molecular characteristics of GBMs. We show that these GBMs are resistant to EGFR kinase inhibition and we define this resistance molecularly. Inhibition of EGFR kinase activity using tyrosine kinase inhibitors in GBM tumor cells generates a cytostatic response characterized by a cell cycle arrest, which is accompanied by a substantial change in global gene expression levels. We demonstrate that an important component of this pattern is the transcriptional activation of the MET receptor tyrosine kinase and that pharmacological inhibition of MET overcomes the resistance to EGFR inhibition in these cells. These findings provide important new insights into mechanisms of resistance to EGFR inhibition and suggest that inhibition of multiple targets will be necessary to provide therapeutic benefit for GBM patients.

Molecular interactions and redox effects of carvacrol and thymol on myofibrillar proteins using a non-destructive and solvent-free methodological approach.

PubMed

Lahmar, Aida; Akcan, Tolga; Chekir-Ghedira, Leila; Estévez, Mario

2018-04-01

The present study provides molecular insight into the effect of thymol and carvacrol on the oxidative damage caused to myofibrillar proteins by a hydroxyl-radical generating system (HRGS). An innovative model system was designed, in which gels, prepared with increasing levels of myofibrillar proteins, were oxidized by a HRGS (Fe 3+ /H 2 O 2 , 60 °C and 7 days) in the presence of lipids. The molecular affinity between myofibrillar proteins and both terpenes, as well as their effect on the oxidative stability of the gel systems, were studied using a non-destructive and solvent-free procedure based on fluorescence spectroscopy. Carvacrol displayed more affinity than thymol for establishing chemical interactions with protein residues. Both terpenes exhibited a significant antioxidant potential against the generation of lipid-derived volatile carbonyls and against the formation of protein crosslinking. This procedure may be applied to meat products to assess the effectiveness of a given antioxidant additive without size reduction or sample processing. Copyright © 2018 Elsevier Ltd. All rights reserved.

The interface of protein structure, protein biophysics, and molecular evolution

PubMed Central

Liberles, David A; Teichmann, Sarah A; Bahar, Ivet; Bastolla, Ugo; Bloom, Jesse; Bornberg-Bauer, Erich; Colwell, Lucy J; de Koning, A P Jason; Dokholyan, Nikolay V; Echave, Julian; Elofsson, Arne; Gerloff, Dietlind L; Goldstein, Richard A; Grahnen, Johan A; Holder, Mark T; Lakner, Clemens; Lartillot, Nicholas; Lovell, Simon C; Naylor, Gavin; Perica, Tina; Pollock, David D; Pupko, Tal; Regan, Lynne; Roger, Andrew; Rubinstein, Nimrod; Shakhnovich, Eugene; Sjölander, Kimmen; Sunyaev, Shamil; Teufel, Ashley I; Thorne, Jeffrey L; Thornton, Joseph W; Weinreich, Daniel M; Whelan, Simon

2012-01-01

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction. PMID:22528593

A prototype of an electric-discharge gas flow oxygen−iodine laser: I. Modeling of the processes of singlet oxygen generation in a transverse cryogenic slab RF discharge

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

Vagin, N. P.; Ionin, A. A., E-mail: aion@sci.lebedev.ru; Kochetov, I. V.

The existing kinetic model describing self-sustained and electroionization discharges in mixtures enriched with singlet oxygen has been modified to calculate the characteristics of a flow RF discharge in molecular oxygen and its mixtures with helium. The simulations were performed in the gas plug-flow approximation, i.e., the evolution of the plasma components during their motion along the channel was represented as their evolution in time. The calculations were carried out for the O{sub 2}: He = 1: 0, 1: 1, 1: 2, and 1: 3 mixtures at an oxygen partial pressure of 7.5 Torr. It is shown that, under these conditions,more » volumetric gas heating in a discharge in pure molecular oxygen prevails over gas cooling via heat conduction even at an electrode temperature as low as ~100 K. When molecular oxygen is diluted with helium, the behavior of the gas temperature changes substantially: heat removal begins to prevail over volumetric gas heating, and the gas temperature at the outlet of the discharge zone drops to ~220–230 K at room gas temperature at the inlet, which is very important in the context of achieving the generation threshold in an electric-discharge oxygen−iodine laser based on a slab cryogenic RF discharge.« less

Molecular Genetics Information System (MOLGENIS): alternatives in developing local experimental genomics databases.

PubMed

Swertz, Morris A; De Brock, E O; Van Hijum, Sacha A F T; De Jong, Anne; Buist, Girbe; Baerends, Richard J S; Kok, Jan; Kuipers, Oscar P; Jansen, Ritsert C

2004-09-01

Genomic research laboratories need adequate infrastructure to support management of their data production and research workflow. But what makes infrastructure adequate? A lack of appropriate criteria makes any decision on buying or developing a system difficult. Here, we report on the decision process for the case of a molecular genetics group establishing a microarray laboratory. Five typical requirements for experimental genomics database systems were identified: (i) evolution ability to keep up with the fast developing genomics field; (ii) a suitable data model to deal with local diversity; (iii) suitable storage of data files in the system; (iv) easy exchange with other software; and (v) low maintenance costs. The computer scientists and the researchers of the local microarray laboratory considered alternative solutions for these five requirements and chose the following options: (i) use of automatic code generation; (ii) a customized data model based on standards; (iii) storage of datasets as black boxes instead of decomposing them in database tables; (iv) loosely linking to other programs for improved flexibility; and (v) a low-maintenance web-based user interface. Our team evaluated existing microarray databases and then decided to build a new system, Molecular Genetics Information System (MOLGENIS), implemented using code generation in a period of three months. This case can provide valuable insights and lessons to both software developers and a user community embarking on large-scale genomic projects. http://www.molgenis.nl

Diamondoid hydrocarbons as a molecular proxy for thermal maturity and oil cracking: Geochemical models from hydrous pyrolysis

USGS Publications Warehouse

Wei, Z.; Moldowan, J.M.; Zhang, S.; Hill, R.; Jarvie, D.M.; Wang, Hongfang; Song, F.; Fago, F.

2007-01-01

A series of isothermal hydrous pyrolysis experiments was performed on immature sedimentary rocks and peats of different lithology and organic source input to explore the generation of diamondoids during the thermal maturation of sediments. Oil generation curves indicate that peak oil yields occur between 340 and 360 ??C, followed by intense oil cracking in different samples. The biomarker maturity parameters appear to be insensitive to thermal maturation as most of the isomerization ratios of molecular biomarkers in the pyrolysates have reached their equilibrium values. Diamondoids are absent from immature peat extracts, but exist in immature sedimentary rocks in various amounts. This implies that they are not products of biosynthesis and that they may be generated during diagenesis, not just catagenesis and cracking. Most importantly, the concentrations of diamondoids are observed to increase with thermal stress, suggesting that they can be used as a molecular proxy for thermal maturity of source rocks and crude oils. Their abundance is most sensitive to thermal exposure above temperatures of 360-370 ??C (R0 = 1.3-1.5%) for the studied samples, which corresponds to the onset of intense cracking of other less stable components. Below these temperatures, diamondoids increase gradually due to competing processes of generation and dilution. Calibrations were developed between their concentrations and measured vitrinite reflectance through hydrous pyrolysis maturation of different types of rocks and peats. The geochemical models obtained from these methods may provide an alterative approach for determining thermal maturity of source rocks and crude oils, particularly in mature to highly mature Paleozoic carbonates. In addition, the extent of oil cracking was quantified using the concentrations of diamondoids in hydrous pyrolysates of rocks and peats, verifying that these hydrocarbons are valuable indicators of oil cracking in nature. ?? 2006 Elsevier Ltd. All rights reserved.

Ten years of progress and promise of induced pluripotent stem cells: historical origins, characteristics, mechanisms, limitations, and potential applications.

PubMed

Omole, Adekunle Ebenezer; Fakoya, Adegbenro Omotuyi John

2018-01-01

The discovery of induced pluripotent stem cells (iPSCs) by Shinya Yamanaka in 2006 was heralded as a major breakthrough of the decade in stem cell research. The ability to reprogram human somatic cells to a pluripotent embryonic stem cell-like state through the ectopic expression of a combination of embryonic transcription factors was greeted with great excitement by scientists and bioethicists. The reprogramming technology offers the opportunity to generate patient-specific stem cells for modeling human diseases, drug development and screening, and individualized regenerative cell therapy. However, fundamental questions have been raised regarding the molecular mechanism of iPSCs generation, a process still poorly understood by scientists. The efficiency of reprogramming of iPSCs remains low due to the effect of various barriers to reprogramming. There is also the risk of chromosomal instability and oncogenic transformation associated with the use of viral vectors, such as retrovirus and lentivirus, which deliver the reprogramming transcription factors by integration in the host cell genome. These challenges can hinder the therapeutic prospects and promise of iPSCs and their clinical applications. Consequently, extensive studies have been done to elucidate the molecular mechanism of reprogramming and novel strategies have been identified which help to improve the efficiency of reprogramming methods and overcome the safety concerns linked with iPSC generation. Distinct barriers and enhancers of reprogramming have been elucidated, and non-integrating reprogramming methods have been reported. Here, we summarize the progress and the recent advances that have been made over the last 10 years in the iPSC field, with emphasis on the molecular mechanism of reprogramming, strategies to improve the efficiency of reprogramming, characteristics and limitations of iPSCs, and the progress made in the applications of iPSCs in the field of disease modelling, drug discovery and regenerative medicine. Additionally, this study appraises the role of genomic editing technology in the generation of healthy iPSCs.

Ten years of progress and promise of induced pluripotent stem cells: historical origins, characteristics, mechanisms, limitations, and potential applications

PubMed Central

2018-01-01

The discovery of induced pluripotent stem cells (iPSCs) by Shinya Yamanaka in 2006 was heralded as a major breakthrough of the decade in stem cell research. The ability to reprogram human somatic cells to a pluripotent embryonic stem cell-like state through the ectopic expression of a combination of embryonic transcription factors was greeted with great excitement by scientists and bioethicists. The reprogramming technology offers the opportunity to generate patient-specific stem cells for modeling human diseases, drug development and screening, and individualized regenerative cell therapy. However, fundamental questions have been raised regarding the molecular mechanism of iPSCs generation, a process still poorly understood by scientists. The efficiency of reprogramming of iPSCs remains low due to the effect of various barriers to reprogramming. There is also the risk of chromosomal instability and oncogenic transformation associated with the use of viral vectors, such as retrovirus and lentivirus, which deliver the reprogramming transcription factors by integration in the host cell genome. These challenges can hinder the therapeutic prospects and promise of iPSCs and their clinical applications. Consequently, extensive studies have been done to elucidate the molecular mechanism of reprogramming and novel strategies have been identified which help to improve the efficiency of reprogramming methods and overcome the safety concerns linked with iPSC generation. Distinct barriers and enhancers of reprogramming have been elucidated, and non-integrating reprogramming methods have been reported. Here, we summarize the progress and the recent advances that have been made over the last 10 years in the iPSC field, with emphasis on the molecular mechanism of reprogramming, strategies to improve the efficiency of reprogramming, characteristics and limitations of iPSCs, and the progress made in the applications of iPSCs in the field of disease modelling, drug discovery and regenerative medicine. Additionally, this study appraises the role of genomic editing technology in the generation of healthy iPSCs. PMID:29770269

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

PubMed

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

NASA Astrophysics Data System (ADS)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.

PubMed

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T; McDougal, Owen M; Andersen, Timothy L

2013-08-26

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.

Utilizing high throughput screening data for predictive toxicology models: protocols and application to MLSCN assays

NASA Astrophysics Data System (ADS)

Guha, Rajarshi; Schürer, Stephan C.

2008-06-01

Computational toxicology is emerging as an encouraging alternative to experimental testing. The Molecular Libraries Screening Center Network (MLSCN) as part of the NIH Molecular Libraries Roadmap has recently started generating large and diverse screening datasets, which are publicly available in PubChem. In this report, we investigate various aspects of developing computational models to predict cell toxicity based on cell proliferation screening data generated in the MLSCN. By capturing feature-based information in those datasets, such predictive models would be useful in evaluating cell-based screening results in general (for example from reporter assays) and could be used as an aid to identify and eliminate potentially undesired compounds. Specifically we present the results of random forest ensemble models developed using different cell proliferation datasets and highlight protocols to take into account their extremely imbalanced nature. Depending on the nature of the datasets and the descriptors employed we were able to achieve percentage correct classification rates between 70% and 85% on the prediction set, though the accuracy rate dropped significantly when the models were applied to in vivo data. In this context we also compare the MLSCN cell proliferation results with animal acute toxicity data to investigate to what extent animal toxicity can be correlated and potentially predicted by proliferation results. Finally, we present a visualization technique that allows one to compare a new dataset to the training set of the models to decide whether the new dataset may be reliably predicted.

The Molecular Revolution in Cutaneous Biology: Era of Molecular Diagnostics for Inherited Skin Diseases.

PubMed

McGrath, John A

2017-05-01

The discovery of pathogenic mutations in inherited skin diseases represents one of the major landmarks of late 20th century molecular genetics. Mutation data can provide accurate diagnoses, improve genetic counseling, help define disease mechanisms, establish disease models, and provide a basis for translational research and testing of novel therapeutics. The process of detecting disease mutations, however, has not always been straightforward. Traditional approaches using genetic linkage or candidate gene analysis have often been limited, costly, and slow to yield new insights, but the advent of next-generation sequencing (NGS) technologies has altered the landscape of current gene discovery and mutation detection approaches. Copyright © 2017 The Author. Published by Elsevier Inc. All rights reserved.

Synthesizing and databasing fossil calibrations: divergence dating and beyond

PubMed Central

Ksepka, Daniel T.; Benton, Michael J.; Carrano, Matthew T.; Gandolfo, Maria A.; Head, Jason J.; Hermsen, Elizabeth J.; Joyce, Walter G.; Lamm, Kristin S.; Patané, José S. L.; Phillips, Matthew J.; Polly, P. David; Van Tuinen, Marcel; Ware, Jessica L.; Warnock, Rachel C. M.; Parham, James F.

2011-01-01

Divergence dating studies, which combine temporal data from the fossil record with branch length data from molecular phylogenetic trees, represent a rapidly expanding approach to understanding the history of life. National Evolutionary Synthesis Center hosted the first Fossil Calibrations Working Group (3–6 March, 2011, Durham, NC, USA), bringing together palaeontologists, molecular evolutionists and bioinformatics experts to present perspectives from disciplines that generate, model and use fossil calibration data. Presentations and discussions focused on channels for interdisciplinary collaboration, best practices for justifying, reporting and using fossil calibrations and roadblocks to synthesis of palaeontological and molecular data. Bioinformatics solutions were proposed, with the primary objective being a new database for vetted fossil calibrations with linkages to existing resources, targeted for a 2012 launch. PMID:21525049

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.

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

NASA Astrophysics Data System (ADS)

Mehta, Neil A.; Levin, Deborah A.

2018-03-01

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

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

PubMed

Mehta, Neil A; Levin, Deborah A

2018-03-01

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

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

PubMed

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

2013-04-01

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

Cross-generational trans fat intake facilitates mania-like behavior: oxidative and molecular markers in brain cortex.

PubMed

Trevizol, F; Roversi, Kr; Dias, V T; Roversi, K; Barcelos, R C S; Kuhn, F T; Pase, C S; Golombieski, R; Veit, J C; Piccolo, J; Pochmann, D; Porciúncula, L O; Emanuelli, T; Rocha, J B T; Bürger, M E

2015-02-12

Since that fast food consumption have raised concerns about people's health, we evaluated the influence of trans fat consumption on behavioral, biochemical and molecular changes in the brain-cortex of second generation rats exposed to a model of mania. Two successive generations of female rats were supplemented with soybean oil (SO, rich in n-6 FA, control group), fish oil (FO, rich in n-3 FA) and hydrogenated vegetable fat (HVF, rich in trans FA) from pregnancy, lactation to adulthood, when male rats from 2nd generation received amphetamine (AMPH-4 mg/kg-i.p., once a day, for 14 days) treatment. AMPH increased locomotor index in all animals, which was higher in the HVF group. While the FO group showed increased n-3 polyunsaturated fatty acid (PUFA) incorporation and reduced n-6/n-3 PUFA ratio, HVF allowed trans fatty acid (TFA) incorporation and increased n-6/n-3 PUFA ratio in the brain-cortex. In fact, the FO group showed minor AMPH-induced hyperactivity, decreased reactive species (RS) generation per se, causing no changes in protein carbonyl (PC) levels and dopamine transporter (DAT). FO supplementation showed molecular changes, since proBDNF was increased per se and reduced by AMPH, decreasing the brain-derived neurotrophic factor (BDNF) level following drug treatment. Conversely, HVF was related to increased hyperactivity, higher PC level per se and higher AMPH-induced PC level, reflecting on DAT, whose levels were decreased per se as well as in AMPH-treated groups. In addition, while HVF increased BDNF-mRNA per se, AMPH reduced this value, acting on BDNF, whose level was lower in the same AMPH-treated experimental group. ProBDNF level was influenced by HVF supplementation, but it was not sufficient to modify BDNF level. These findings reinforce that prolonged consumption of trans fat allows TFA incorporation in the cortex, facilitating hyperactive behavior, oxidative damages and molecular changes. Our study is a warning about cross-generational consumption of processed food, since high trans fat may facilitate the development of neuropsychiatric conditions, including bipolar disorder (BD). Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

The discovery of novel histone lysine methyltransferase G9a inhibitors (part 1): molecular design based on a series of substituted 2,4-diamino-7- aminoalkoxyquinazoline by molecular-docking-guided 3D quantitative structure-activity relationship studies.

PubMed

Feng, Taotao; Wang, Hai; Zhang, Xiaojin; Sun, Haopeng; You, Qidong

2014-06-01

Protein lysine methyltransferase G9a, which catalyzes methylation of lysine 9 of histone H3 (H3K9) and lysine 373 (K373) of p53, is overexpressed in human cancers. This suggests that small molecular inhibitors of G9a might be attractive antitumor agents. Herein we report our efforts on the design of novel G9a inhibitor based on the 3D quantitative structure-activity relationship (3D-QSAR) analysis of a series of 2,4-diamino-7-aminoalkoxyquinazolineas G9a inhibitors. The 3D-QSAR model was generated from 47 compounds using docking based molecular alignment. The best predictions were obtained with CoMFA standard model (q2 =0.700, r2 = 0.952) and CoMSIA model combined with steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields (q2 = 0.724, r2 =0.960). The structural requirements for substituted 2,4-diamino-7-aminoalkoxyquinazoline for G9a inhibitory activity can be obtained by analysing the COMSIA plots. Based on the information, six novel follow-up analogs were designed.

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

NASA Astrophysics Data System (ADS)

Cao, Shandong

2012-08-01

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

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

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...

Standardized Profiling of The Membrane-Enriched Proteome of Mouse Dorsal Root Ganglia (DRG) Provides Novel Insights Into Chronic Pain.

PubMed

Rouwette, Tom; Sondermann, Julia; Avenali, Luca; Gomez-Varela, David; Schmidt, Manuela

2016-06-01

Chronic pain is a complex disease with limited treatment options. Several profiling efforts have been employed with the aim to dissect its molecular underpinnings. However, generated results are often inconsistent and nonoverlapping, which is largely because of inherent technical constraints. Emerging data-independent acquisition (DIA)-mass spectrometry (MS) has the potential to provide unbiased, reproducible and quantitative proteome maps - a prerequisite for standardization among experiments. Here, we designed a DIA-based proteomics workflow to profile changes in the abundance of dorsal root ganglia (DRG) proteins in two mouse models of chronic pain, inflammatory and neuropathic. We generated a DRG-specific spectral library containing 3067 DRG proteins, which enables their standardized quantification by means of DIA-MS in any laboratory. Using this resource, we profiled 2526 DRG proteins in each biological replicate of both chronic pain models and respective controls with unprecedented reproducibility. We detected numerous differentially regulated proteins, the majority of which exhibited pain model-specificity. Our approach recapitulates known biology and discovers dozens of proteins that have not been characterized in the somatosensory system before. Functional validation experiments and analysis of mouse pain behaviors demonstrate that indeed meaningful protein alterations were discovered. These results illustrate how the application of DIA-MS can open new avenues to achieve the long-awaited standardization in the molecular dissection of pathologies of the somatosensory system. Therefore, our findings provide a valuable framework to qualitatively extend our understanding of chronic pain and somatosensation. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Visually impaired researchers get their hands on quantum chemistry: application to a computational study on the isomerization of a sterol.

PubMed

Lounnas, Valère; Wedler, Henry B; Newman, Timothy; Schaftenaar, Gijs; Harrison, Jason G; Nepomuceno, Gabriella; Pemberton, Ryan; Tantillo, Dean J; Vriend, Gert

2014-11-01

In molecular sciences, articles tend to revolve around 2D representations of 3D molecules, and sighted scientists often resort to 3D virtual reality software to study these molecules in detail. Blind and visually impaired (BVI) molecular scientists have access to a series of audio devices that can help them read the text in articles and work with computers. Reading articles published in this journal, though, is nearly impossible for them because they need to generate mental 3D images of molecules, but the article-reading software cannot do that for them. We have previously designed AsteriX, a web server that fully automatically decomposes articles, detects 2D plots of low molecular weight molecules, removes meta data and annotations from these plots, and converts them into 3D atomic coordinates. AsteriX-BVI goes one step further and converts the 3D representation into a 3D printable, haptic-enhanced format that includes Braille annotations. These Braille-annotated physical 3D models allow BVI scientists to generate a complete mental model of the molecule. AsteriX-BVI uses Molden to convert the meta data of quantum chemistry experiments into BVI friendly formats so that the entire line of scientific information that sighted people take for granted-from published articles, via printed results of computational chemistry experiments, to 3D models-is now available to BVI scientists too. The possibilities offered by AsteriX-BVI are illustrated by a project on the isomerization of a sterol, executed by the blind co-author of this article (HBW).

Importance of Kier-Hall topological indices in the QSAR of anticancer drug design.

PubMed

Nandi, Sisir; Bagchi, Manish C

2012-06-01

An important area of theoretical drug design research is quantitative structure activity relationship (QSAR) using structural invariants. The impetus for this research trend comes from various directions. Researchers in chemical documentation have searched for a set of invariants which will be more convenient than the adjacency matrix (or connection table) for the storage and comparison of chemical structures. Molecular structure can be looked upon as the representation of the relationship among its various constituents. The term molecular structure represents a set of nonequivalent and probably disjoint concepts. There is no reason to believe that when we discuss diverse topics (e.g. chemical synthesis, reaction rates, spectroscopic transitions, reaction mechanisms, and ab initio calculations) using the notion of molecular structure, the different meanings we attach to the single term molecular structure originate from the same fundamental concept. On the contrary, there is a theoretical and philosophical basis for the non-homogeneity of concepts covered by the term molecular structure. In the context of molecular science, the various concepts of molecular structure (e.g. classical valence bond representations, various chemical graph-theoretic representations, ball and spoke model of a molecule, representation of a molecule by minimum energy conformation, semi symbolic contour map of a molecule, or symbolic representation of chemical species by Hamiltonian operators) are model objects derived through different abstractions of the same chemical reality. In each instance, the equivalence class (concept or model of molecular structure) is generated by selecting certain aspects while ignoring some unique properties of those actual events. This explains the plurality of the concept of molecular structure and their autonomous nature, the word autonomous being used in the same sense that one concept is not logically derived from the other. At the most fundamental level, the structural model of an assembled entity (e.g. a molecule consisting of atoms) may be defined as the pattern of relationship among its parts as distinct from the values associated with them. Constitutional formulae of molecules are graphs where vertices represent the set of atoms and edges represent chemical bonds. The pattern of connectedness of atoms in a molecule is preserved by constitutional graphs. A graph (more correctly a non-directed graph) G = [V, E] consists of a finite non-empty set V of points together with a prescribed set E of unordered pairs of distinct points of V. Thus the mathematical characterization of structures represents structural invariants having successful applications in chemical documentation, characterization of molecular branching, enumeration of molecular constitutional associated with a particular empirical formula, calculation of quantum chemical parameters for the generation of quantitative structure-property-activity correlations. Kier developed a number of structural invariants which are now-a-days called as topological indices with wide range of practical applications for QSAR and drug design. The present paper is restricted to the review of Kier-Hall topological indices for QSAR and anticancer drug design for 2,5-bis(1-aziridinyl) 1,4-benzoquinone (BABQ), pyridopyrimidine, 4-anilinoquinazoline and 2-Phenylindoles compounds utilizing various statistical multivariate regression analyses.

Diapause in a tropical oil-collecting bee: molecular basis unveiled by RNA-Seq.

PubMed

Santos, Priscila Karla F; de Souza Araujo, Natalia; Françoso, Elaine; Zuntini, Alexandre Rizzo; Arias, Maria Cristina

2018-04-27

Diapause is a natural phenomenon characterized by an arrest in development that ensures the survival of organisms under extreme environmental conditions. The process has been well documented in arthropods. However, its molecular basis has been mainly studied in species from temperate zones, leaving a knowledge gap of this phenomenon in tropical species. In the present study, the Neotropical and solitary bee Tetrapedia diversipes was employed as a model for investigating diapause in species from tropical zones. Being a bivoltine insect, Tetrapedia diversipes produce two generations of offspring per year. The first generation, normally born during the wet season, develops faster than individuals from the second generation, born after the dry season. Furthermore, it has been shown that the development of the progeny, of the second generation, is halted at the 5th larval instar, and remains in larval diapause during the dry season. Towards the goal of gaining a better understanding of the diapause phenomenon we compared the global gene expression pattern, in larvae, from both reproductive generations and during diapause. The results demonstrate that there are similarities in the observed gene expression patterns to those already described for temperate climate models, and also identify diapause-related genes that have not been previously reported in the literature. The RNA-Seq analysis identified 2275 differentially expressed transcripts, of which 1167 were annotated. Of these genes, during diapause, 352 were upregulated and 815 were downregulated. According to their biological functions, these genes were categorized into the following groups: cellular detoxification, cytoskeleton, cuticle, sterol and lipid metabolism, cell cycle, heat shock proteins, immune response, circadian clock, and epigenetic control. Many of the identified genes have already been described as being related to diapause; however, new genes were discovered, for the first time, in this study. Among those, we highlight: Niemann-Pick type C1, NPC2 and Acyl-CoA binding protein homolog (all involved in ecdysteroid synthesis); RhoBTB2 and SASH1 (associated with cell cycle regulation) and Histone acetyltransferase KAT7 (related to epigenetic transcriptional regulation). The results presented here add important findings to the understanding of diapause in tropical species, thus increasing the comprehension of diapause-related molecular mechanisms.

The molecular orientation of CO on Pd(1 1 1): a polarization-dependent SFG study

NASA Astrophysics Data System (ADS)

Galletto, Paolo; Unterhalt, Holger; Rupprechter, Günther

2003-01-01

The molecular orientation of carbon monoxide adsorbed on Pd(1 1 1) was examined by sum frequency generation (SFG) vibrational spectroscopy utilizing different polarization combinations of the visible and SFG light. This allows to determine the CO tilt angle with respect to the substrate, provided that a proper optical model for the interface can be defined. It is demonstrated that it is essential to invoke the βaac hyperpolarizability into the analysis and that polarization-dependent SFG of CO/Pd(1 1 1) yields information on βaac/ βccc rather than the tilt angle.

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.

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

PubMed

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

2015-10-28

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

Linking molecular models with ion mobility experiments. Illustration with a rigid nucleic acid structure

PubMed Central

D'Atri, Valentina; Porrini, Massimiliano; Rosu, Frédéric; Gabelica, Valérie

2015-01-01

Ion mobility spectrometry experiments allow the mass spectrometrist to determine an ion's rotationally averaged collision cross section ΩEXP. Molecular modelling is used to visualize what ion three-dimensional structure(s) is(are) compatible with the experiment. The collision cross sections of candidate molecular models have to be calculated, and the resulting ΩCALC are compared with the experimental data. Researchers who want to apply this strategy to a new type of molecule face many questions: (1) What experimental error is associated with ΩEXP determination, and how to estimate it (in particular when using a calibration for traveling wave ion guides)? (2) How to generate plausible 3D models in the gas phase? (3) Different collision cross section calculation models exist, which have been developed for other analytes than mine. Which one(s) can I apply to my systems? To apply ion mobility spectrometry to nucleic acid structural characterization, we explored each of these questions using a rigid structure which we know is preserved in the gas phase: the tetramolecular G-quadruplex [dTGGGGT]4, and we will present these detailed investigation in this tutorial. © 2015 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd. PMID:26259654

Statistical inference of the generation probability of T-cell receptors from sequence repertoires.

PubMed

Murugan, Anand; Mora, Thierry; Walczak, Aleksandra M; Callan, Curtis G

2012-10-02

Stochastic rearrangement of germline V-, D-, and J-genes to create variable coding sequence for certain cell surface receptors is at the origin of immune system diversity. This process, known as "VDJ recombination", is implemented via a series of stochastic molecular events involving gene choices and random nucleotide insertions between, and deletions from, genes. We use large sequence repertoires of the variable CDR3 region of human CD4+ T-cell receptor beta chains to infer the statistical properties of these basic biochemical events. Because any given CDR3 sequence can be produced in multiple ways, the probability distribution of hidden recombination events cannot be inferred directly from the observed sequences; we therefore develop a maximum likelihood inference method to achieve this end. To separate the properties of the molecular rearrangement mechanism from the effects of selection, we focus on nonproductive CDR3 sequences in T-cell DNA. We infer the joint distribution of the various generative events that occur when a new T-cell receptor gene is created. We find a rich picture of correlation (and absence thereof), providing insight into the molecular mechanisms involved. The generative event statistics are consistent between individuals, suggesting a universal biochemical process. Our probabilistic model predicts the generation probability of any specific CDR3 sequence by the primitive recombination process, allowing us to quantify the potential diversity of the T-cell repertoire and to understand why some sequences are shared between individuals. We argue that the use of formal statistical inference methods, of the kind presented in this paper, will be essential for quantitative understanding of the generation and evolution of diversity in the adaptive immune system.

Generation of Functional Thyroid Tissue Using 3D-Based Culture of Embryonic Stem Cells.

PubMed

Antonica, Francesco; Kasprzyk, Dominika Figini; Schiavo, Andrea Alex; Romitti, Mírian; Costagliola, Sabine

2017-01-01

During the last decade three-dimensional (3D) cultures of pluripotent stem cells have been intensively used to understand morphogenesis and molecular signaling important for the embryonic development of many tissues. In addition, pluripotent stem cells have been shown to be a valid tool for the in vitro modeling of several congenital or chronic human diseases, opening new possibilities to study their physiopathology without using animal models. Even more interestingly, 3D culture has proved to be a powerful and versatile tool to successfully generate functional tissues ex vivo. Using similar approaches, we here describe a protocol for the generation of functional thyroid tissue using mouse embryonic stem cells and give all the details and references for its characterization and analysis both in vitro and in vivo. This model is a valid approach to study the expression and the function of genes involved in the correct morphogenesis of thyroid gland, to elucidate the mechanisms of production and secretion of thyroid hormones and to test anti-thyroid drugs.

Strong-field control and enhancement of chiral response in bi-elliptical high-order harmonic generation: an analytical model

NASA Astrophysics Data System (ADS)

Ayuso, David; Decleva, Piero; Patchkovskii, Serguei; Smirnova, Olga

2018-06-01

The generation of high-order harmonics in a medium of chiral molecules driven by intense bi-elliptical laser fields can lead to strong chiroptical response in a broad range of harmonic numbers and ellipticities (Ayuso et al 2018 J. Phys. B: At. Mol. Opt. Phys. 51 06LT01). Here we present a comprehensive analytical model that can describe the most relevant features arising in the high-order harmonic spectra of chiral molecules driven by strong bi-elliptical fields. Our model recovers the physical picture underlying chiral high-order harmonic generation (HHG) based on ultrafast chiral hole motion and identifies the rotationally invariant molecular pseudoscalars responsible for chiral dynamics. Using the chiral molecule propylene oxide as an example, we show that one can control and enhance the chiral response in bi-elliptical HHG by tailoring the driving field, in particular by tuning its frequency, intensity and ellipticity, exploiting a suppression mechanism of achiral background based on the linear Stark effect.

Self-assembly Controls Self-cleavage of HHR from ASBVd (-): a Combined SANS and Modeling Study

NASA Astrophysics Data System (ADS)

Leclerc, Fabrice; Zaccai, Giuseppe; Vergne, Jacques; Řìhovà, Martina; Martel, Anne; Maurel, Marie-Christine

2016-07-01

In the Avocado Sunblotch Viroid (ASBVd: 249-nt) from the Avsunviroidae family, a symmetric rolling-circle replication operates through an autocatalytic mechanism mediated by hammerhead ribozymes (HHR) embedded in both polarity strands. The concatenated multimeric ASBVd (+) and ASBVd (-) RNAs thus generated are processed by cleavage to unit-length where ASBVd (-) self-cleaves with more efficiency. Absolute scale small angle neutron scattering (SANS) revealed a temperature-dependent dimer association in both ASBVd (-) and its derived 79-nt HHR (-). A joint thermodynamic analysis of SANS and catalytic data indicates the rate-determining step corresponds to the dimer/monomer transition. 2D and 3D models of monomeric and dimeric HHR (-) suggest that the inter-molecular contacts stabilizing the dimer (between HI and HII domains) compete with the intra-molecular ones stabilizing the active conformation of the full-length HHR required for an efficient self-cleavage. Similar competing intra- and inter-molecular contacts are proposed in ASBVd (-) though with a remoter region from an extension of the HI domain.

Modeling human infertility with pluripotent stem cells.

PubMed

Chen, Di; Gell, Joanna J; Tao, Yu; Sosa, Enrique; Clark, Amander T

2017-05-01

Human fertility is dependent upon the correct establishment and differentiation of the germline. This is because no other cell type in the body is capable of passing a genome and epigenome from parent to child. Terminally differentiated germline cells in the adult testis and ovary are called gametes. However, the initial specification of germline cells occurs in the embryo around the time of gastrulation. Most of our knowledge regarding the cell and molecular events that govern human germline specification involves extrapolating scientific principles from model organisms, most notably the mouse. However, recent work using next generation sequencing, gene editing and differentiation of germline cells from pluripotent stem cells has revealed that the core molecular mechanisms that regulate human germline development are different from rodents. Here, we will discuss the major molecular pathways required for human germline differentiation and how pluripotent stem cells have revolutionized our ability to study the earliest steps in human embryonic lineage specification in order to understand human fertility. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Watson-Crick Base Pair Radical Cation as a Model for Oxidative Damage in DNA.

PubMed

Feketeová, Linda; Chan, Bun; Khairallah, George N; Steinmetz, Vincent; Maitre, Philippe; Radom, Leo; O'Hair, Richard A J

2017-07-06

The deleterious cellular effects of ionizing radiation are well-known, but the mechanisms causing DNA damage are poorly understood. The accepted molecular events involve initial oxidation and deprotonation at guanine sites, triggering hydrogen atom abstraction reactions from the sugar moieties, causing DNA strand breaks. Probing the chemistry of the initially formed radical cation has been challenging. Here, we generate, spectroscopically characterize, and examine the reactivity of the Watson-Crick nucleobase pair radical cation in the gas phase. We observe rich chemistry, including proton transfer between the bases and propagation of the radical site in deoxyguanosine from the base to the sugar, thus rupturing the sugar. This first example of a gas-phase model system providing molecular-level details on the chemistry of an ionized DNA base pair paves the way toward a more complete understanding of molecular processes induced by radiation. It also highlights the role of radical propagation in chemistry, biology, and nanotechnology.

Decipher the Molecular Response of Plant Single Cell Types to Environmental Stresses

DOE PAGES

Nourbakhsh-Rey, Mehrnoush; Libault, Marc

2016-01-01

The analysis of the molecular response of entire plants or organs to environmental stresses suffers from the cellular complexity of the samples used. Specifically, this cellular complexity masks cell-specific responses to environmental stresses and logically leads to the dilution of the molecular changes occurring in each cell type composing the tissue/organ/plant in response to the stress. Therefore, to generate a more accurate picture of these responses, scientists are focusing on plant single cell type approaches. Several cell types are now considered as models such as the pollen, the trichomes, the cotton fiber, various root cell types including the root hairmore » cell, and the guard cell of stomata. Among them, several have been used to characterize plant response to abiotic and biotic stresses. Lastly, in this review, we are describing the various -omic studies performed on these different plant single cell type models to better understand plant cell response to biotic and abiotic stresses.« less

Decipher the Molecular Response of Plant Single Cell Types to Environmental Stresses

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

Nourbakhsh-Rey, Mehrnoush; Libault, Marc

The analysis of the molecular response of entire plants or organs to environmental stresses suffers from the cellular complexity of the samples used. Specifically, this cellular complexity masks cell-specific responses to environmental stresses and logically leads to the dilution of the molecular changes occurring in each cell type composing the tissue/organ/plant in response to the stress. Therefore, to generate a more accurate picture of these responses, scientists are focusing on plant single cell type approaches. Several cell types are now considered as models such as the pollen, the trichomes, the cotton fiber, various root cell types including the root hairmore » cell, and the guard cell of stomata. Among them, several have been used to characterize plant response to abiotic and biotic stresses. Lastly, in this review, we are describing the various -omic studies performed on these different plant single cell type models to better understand plant cell response to biotic and abiotic stresses.« less

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

PubMed

Radosinski, Lukasz; Labus, Karolina

2017-10-05

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

The oldest platypus and its bearing on divergence timing of the platypus and echidna clades

PubMed Central

Rowe, Timothy; Rich, Thomas H.; Vickers-Rich, Patricia; Springer, Mark; Woodburne, Michael O.

2008-01-01

Monotremes have left a poor fossil record, and paleontology has been virtually mute during two decades of discussion about molecular clock estimates of the timing of divergence between the platypus and echidna clades. We describe evidence from high-resolution x-ray computed tomography indicating that Teinolophos, an Early Cretaceous fossil from Australia's Flat Rocks locality (121–112.5 Ma), lies within the crown clade Monotremata, as a basal platypus. Strict molecular clock estimates of the divergence between platypus and echidnas range from 17 to 80 Ma, but Teinolophos suggests that the two monotreme clades were already distinct in the Early Cretaceous, and that their divergence may predate even the oldest strict molecular estimates by at least 50%. We generated relaxed molecular clock models using three different data sets, but only one yielded a date overlapping with the age of Teinolophos. Morphology suggests that Teinolophos is a platypus in both phylogenetic and ecological aspects, and tends to contradict the popular view of rapid Cenozoic monotreme diversification. Whereas the monotreme fossil record is still sparse and open to interpretation, the new data are consistent with much slower ecological, morphological, and taxonomic diversification rates for monotremes than in their sister taxon, the therian mammals. This alternative view of a deep geological history for monotremes suggests that rate heterogeneities may have affected mammalian evolution in such a way as to defeat strict molecular clock models and to challenge even relaxed molecular clock models when applied to mammalian history at a deep temporal scale. PMID:18216270

The oldest platypus and its bearing on divergence timing of the platypus and echidna clades.

PubMed

Rowe, Timothy; Rich, Thomas H; Vickers-Rich, Patricia; Springer, Mark; Woodburne, Michael O

2008-01-29

Monotremes have left a poor fossil record, and paleontology has been virtually mute during two decades of discussion about molecular clock estimates of the timing of divergence between the platypus and echidna clades. We describe evidence from high-resolution x-ray computed tomography indicating that Teinolophos, an Early Cretaceous fossil from Australia's Flat Rocks locality (121-112.5 Ma), lies within the crown clade Monotremata, as a basal platypus. Strict molecular clock estimates of the divergence between platypus and echidnas range from 17 to 80 Ma, but Teinolophos suggests that the two monotreme clades were already distinct in the Early Cretaceous, and that their divergence may predate even the oldest strict molecular estimates by at least 50%. We generated relaxed molecular clock models using three different data sets, but only one yielded a date overlapping with the age of Teinolophos. Morphology suggests that Teinolophos is a platypus in both phylogenetic and ecological aspects, and tends to contradict the popular view of rapid Cenozoic monotreme diversification. Whereas the monotreme fossil record is still sparse and open to interpretation, the new data are consistent with much slower ecological, morphological, and taxonomic diversification rates for monotremes than in their sister taxon, the therian mammals. This alternative view of a deep geological history for monotremes suggests that rate heterogeneities may have affected mammalian evolution in such a way as to defeat strict molecular clock models and to challenge even relaxed molecular clock models when applied to mammalian history at a deep temporal scale.

Chemical & Biological Point Detection Decontamination

DTIC Science & Technology

2002-04-01

high priority in biological defense. Research on multivalent assays is also ongoing. Biased libraries, generated from immunized animals, or unbiased ...2003 TBD decontamination and modeling and simulation I I The Chem-Bio Point Detection Roadmap The summary level updated and expanded Bio Point... Molecular Imprinted Polymer Sensor, Dendrimer-based Antibody Assays, Pyrolysis-GC-ion mobility spectrometry, and surface enhanced Raman spectroscopy. Data

Insights about Striatal Circuit Function and Schizophrenia from a Mouse Model of D2 Receptor Upregulation

PubMed Central

Simpson, Eleanor H.; Kellendonk, Christoph

2016-01-01

The dopamine hypothesis of schizophrenia is supported by a large number of imaging studies that have identified an increase in dopamine binding at the D2 receptor selectively in the striatum. Here we review a decade of work using a regionally restricted and temporally regulated transgenic mouse model to investigate the behavioral, molecular, electrophysiological, and anatomical consequences of selective D2 receptor upregulation in the striatum. These studies have identified new and potentially important biomarkers at the circuit and molecular level that can now be explored in patients with schizophrenia. They provide an example of how animal models and their detailed level of neurobiological analysis allow a deepening of our understanding of the relationship between neuronal circuit function and symptoms of schizophrenia, and as a consequence generate new hypotheses that are testable in patients. PMID:27720388

Nanopyroxene Grafting with β-Cyclodextrin Monomer for Wastewater Applications.

PubMed

Nafie, Ghada; Vitale, Gerardo; Carbognani Ortega, Lante; Nassar, Nashaat N

2017-12-06

Emerging nanoparticle technology provides opportunities for environmentally friendly wastewater treatment applications, including those in the large liquid tailings containments in the Alberta oil sands. In this study, we synthesize β-cyclodextrin grafted nanopyroxenes to offer an ecofriendly platform for the selective removal of organic compounds typically present in these types of applications. We carry out computational modeling at the micro level through molecular mechanics and molecular dynamics simulations and laboratory experiments at the macro level to understand the interactions between the synthesized nanomaterials and two-model naphthenic acid molecules (cyclopentanecarboxylic and trans-4-pentylcyclohexanecarboxylic acids) typically existing in tailing ponds. The proof-of-concept computational modeling and experiments demonstrate that monomer grafted nanopyroxene  or nano-AE of the sodium iron-silicate aegirine are found to be promising candidates for the removal of polar organic compounds from wastewater, among other applications. These nano-AE offer new possibilities for treating tailing ponds generated by the oil sands industry.

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

PubMed

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

2013-11-13

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

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

PubMed

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

2015-01-01

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

Nonlinear Acoustic Waves Generated by Surface Disturbances and Their Effects on Lower Thermospheric Composition

NASA Astrophysics Data System (ADS)

Pineyro, B.; Snively, J. B.

2017-12-01

Recent 1D and 2D nonlinear atmospheric models have provided important insight into acoustic waves generated by seismic events, which may steepen into shocks or saw-tooth trains while also dissipating strongly in the thermosphere [e.g., Chum et al., JGR, 121, 2016; Zettergren et al., JGR, 122, 2017]. Although they have yield results that agree with with observations of ionospheric perturbations, dynamical models for the diffusive and stratified lower thermosphere [e.g., Snively and Pasko, JGR, 113, 2008] often use single gas approximations with height-dependent physical properties (e.g. mean molecular weight, specific heats) that do not vary with time (fixed composition). This approximation is simpler and less computationally expensive than a true multi-fluid model, yet captures the important physical transition between molecular and atomic gases in the lower thermosphere. Models with time-dependent composition and properties have been shown to outperform commonly used models with fixed properties; these time-dependent effects have been included in a one-gas model by adding an advection equation for the molecular weight, finding closer agreement to a true binary-gas model [Walterscheid and Hickey, JGR, 106, 2001 and JGR, 117, 2012]. Here, a one-dimensional nonlinear mass fraction approach to multi-constituent gas modeling, motivated by the results of Walterscheid and Hickey [2001, 2012], is presented. The finite volume method of Bale et al. [SIAM JSC, 24, 2002] is implemented in Clawpack [http://www.clawpack.org; LeVeque, 2002] with a Riemann Solver to solve the Euler Equations including multiple species, defined by their mass fractions, as they undergo advection. Viscous dissipation and thermal conduction are applied via a fractional step method. The model is validated with shock tube problems for two species, and then applied to investigate propagating nonlinear acoustic waves from ground to thermosphere, such as following the 2011 Tohoku Earthquake [e.g., Zettergren et al., 2017] and rocket launches [Mabie et al., GRL, 43, 2016]. The limits of applicability are investigated for vertically propagating acoustic waves near the cut-off frequency, and for simulations of steepening waves at finite spatial resolution [Sabatini et al., JASA, 140, 2016].

An Empirical Polarizable Force Field Based on the Classical Drude Oscillator Model: Development History and Recent Applications

PubMed Central

2016-01-01

Molecular mechanics force fields that explicitly account for induced polarization represent the next generation of physical models for molecular dynamics simulations. Several methods exist for modeling induced polarization, and here we review the classical Drude oscillator model, in which electronic degrees of freedom are modeled by charged particles attached to the nuclei of their core atoms by harmonic springs. We describe the latest developments in Drude force field parametrization and application, primarily in the last 15 years. Emphasis is placed on the Drude-2013 polarizable force field for proteins, DNA, lipids, and carbohydrates. We discuss its parametrization protocol, development history, and recent simulations of biologically interesting systems, highlighting specific studies in which induced polarization plays a critical role in reproducing experimental observables and understanding physical behavior. As the Drude oscillator model is computationally tractable and available in a wide range of simulation packages, it is anticipated that use of these more complex physical models will lead to new and important discoveries of the physical forces driving a range of chemical and biological phenomena. PMID:26815602

On models of the genetic code generated by binary dichotomic algorithms.

PubMed

Gumbel, Markus; Fimmel, Elena; Danielli, Alberto; Strüngmann, Lutz

2015-02-01

In this paper we introduce the concept of a BDA-generated model of the genetic code which is based on binary dichotomic algorithms (BDAs). A BDA-generated model is based on binary dichotomic algorithms (BDAs). Such a BDA partitions the set of 64 codons into two disjoint classes of size 32 each and provides a generalization of known partitions like the Rumer dichotomy. We investigate what partitions can be generated when a set of different BDAs is applied sequentially to the set of codons. The search revealed that these models are able to generate code tables with very different numbers of classes ranging from 2 to 64. We have analyzed whether there are models that map the codons to their amino acids. A perfect matching is not possible. However, we present models that describe the standard genetic code with only few errors. There are also models that map all 64 codons uniquely to 64 classes showing that BDAs can be used to identify codons precisely. This could serve as a basis for further mathematical analysis using coding theory, for example. The hypothesis that BDAs might reflect a molecular mechanism taking place in the decoding center of the ribosome is discussed. The scan demonstrated that binary dichotomic partitions are able to model different aspects of the genetic code very well. The search was performed with our tool Beady-A. This software is freely available at http://mi.informatik.hs-mannheim.de/beady-a. It requires a JVM version 6 or higher. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Effect of Molecular Rotation on Charge Transport Phenomena

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Molecular approaches to third generation photovoltaics: photochemical up-conversion

NASA Astrophysics Data System (ADS)

Cheng, Yuen Yap; Fückel, Burkhard; Roberts, Derrick A.; Khoury, Tony; Clady, Rapha"l. G. C. R.; Tayebjee, Murad J. Y.; Piper, Roland; Ekins-Daukes, N. J.; Crossley, Maxwell J.; Schmidt, Timothy W.

2010-08-01

We have investigated a photochemical up-conversion system comprising a molecular mixture of a palladium porphyrin to harvest light, and a polycyclic aromatic hydrocarbon to emit light. The energy of harvested photons is stored as molecular triplet states which then annihilate to bring about up-converted fluorescence. The limiting efficiency of such triplet-triplet annihilation up-conversion has been believed to be 11% for some time. However, by rigorously investigating the kinetics of delayed fluorescence following pulsed excitation, we demonstrate instantaneous annihilation efficiencies exceeding 40%, and limiting efficiencies for the current system of ~60%. We attribute the high efficiencies obtained to the electronic structure of the emitting molecule, which exhibits an exceptionally high T2 molecular state. We utilize the kinetic data obtained to model an up-converting layer irradiated with broadband sunlight, finding that ~3% efficiencies can be obtained with the current system, with this improving dramatically upon optimization of various parameters.

LAD Dissertation Prize Talk: Molecular Collisional Excitation in Astrophysical Environments

NASA Astrophysics Data System (ADS)

Walker, Kyle M.

2017-06-01

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

Theoretical predictor for candidate structure assignment from IMS data of biomolecule-related conformational space.

PubMed

Schenk, Emily R; Nau, Frederic; Fernandez-Lima, Francisco

2015-06-01

The ability to correlate experimental ion mobility data with candidate structures from theoretical modeling provides a powerful analytical and structural tool for the characterization of biomolecules. In the present paper, a theoretical workflow is described to generate and assign candidate structures for experimental trapped ion mobility and H/D exchange (HDX-TIMS-MS) data following molecular dynamics simulations and statistical filtering. The applicability of the theoretical predictor is illustrated for a peptide and protein example with multiple conformations and kinetic intermediates. The described methodology yields a low computational cost and a simple workflow by incorporating statistical filtering and molecular dynamics simulations. The workflow can be adapted to different IMS scenarios and CCS calculators for a more accurate description of the IMS experimental conditions. For the case of the HDX-TIMS-MS experiments, molecular dynamics in the "TIMS box" accounts for a better sampling of the molecular intermediates and local energy minima.

Faunus: An object oriented framework for molecular simulation

PubMed Central

Lund, Mikael; Trulsson, Martin; Persson, Björn

2008-01-01

Background We present a C++ class library for Monte Carlo simulation of molecular systems, including proteins in solution. The design is generic and highly modular, enabling multiple developers to easily implement additional features. The statistical mechanical methods are documented by extensive use of code comments that – subsequently – are collected to automatically build a web-based manual. Results We show how an object oriented design can be used to create an intuitively appealing coding framework for molecular simulation. This is exemplified in a minimalistic C++ program that can calculate protein protonation states. We further discuss performance issues related to high level coding abstraction. Conclusion C++ and the Standard Template Library (STL) provide a high-performance platform for generic molecular modeling. Automatic generation of code documentation from inline comments has proven particularly useful in that no separate manual needs to be maintained. PMID:18241331

Ultrafast electron transfer at organic semiconductor interfaces: Importance of molecular orientation

DOE PAGES

Ayzner, Alexander L.; Nordlund, Dennis; Kim, Do -Hwan; ...

2014-12-04

Much is known about the rate of photoexcited charge generation in at organic donor/acceptor (D/A) heterojunctions overaged over all relative arrangements. However, there has been very little experimental work investigating how the photoexcited electron transfer (ET) rate depends on the precise relative molecular orientation between D and A in thin solid films. This is the question that we address in this work. We find that the ET rate depends strongly on the relative molecular arrangement: The interface where the model donor compound copper phthalocyanine is oriented face-on with respect to the fullerene C 60 acceptor yields a rate that ismore » approximately 4 times faster than that of the edge-on oriented interface. Our results suggest that the D/A electronic coupling is significantly enhanced in the face-on case, which agrees well with theoretical predictions, underscoring the importance of controlling the relative interfacial molecular orientation.« less

Plant synthetic biology for molecular engineering of signalling and development.

PubMed

Nemhauser, Jennifer L; Torii, Keiko U

2016-03-02

Molecular genetic studies of model plants in the past few decades have identified many key genes and pathways controlling development, metabolism and environmental responses. Recent technological and informatics advances have led to unprecedented volumes of data that may uncover underlying principles of plants as biological systems. The newly emerged discipline of synthetic biology and related molecular engineering approaches is built on this strong foundation. Today, plant regulatory pathways can be reconstituted in heterologous organisms to identify and manipulate parameters influencing signalling outputs. Moreover, regulatory circuits that include receptors, ligands, signal transduction components, epigenetic machinery and molecular motors can be engineered and introduced into plants to create novel traits in a predictive manner. Here, we provide a brief history of plant synthetic biology and significant recent examples of this approach, focusing on how knowledge generated by the reference plant Arabidopsis thaliana has contributed to the rapid rise of this new discipline, and discuss potential future directions.

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.

Whole transcriptome analysis using next-generation sequencing of model species Setaria viridis to support C4 photosynthesis research.

PubMed

Xu, Jiajia; Li, Yuanyuan; Ma, Xiuling; Ding, Jianfeng; Wang, Kai; Wang, Sisi; Tian, Ye; Zhang, Hui; Zhu, Xin-Guang

2013-09-01

Setaria viridis is an emerging model species for genetic studies of C4 photosynthesis. Many basic molecular resources need to be developed to support for this species. In this paper, we performed a comprehensive transcriptome analysis from multiple developmental stages and tissues of S. viridis using next-generation sequencing technologies. Sequencing of the transcriptome from multiple tissues across three developmental stages (seed germination, vegetative growth, and reproduction) yielded a total of 71 million single end 100 bp long reads. Reference-based assembly using Setaria italica genome as a reference generated 42,754 transcripts. De novo assembly generated 60,751 transcripts. In addition, 9,576 and 7,056 potential simple sequence repeats (SSRs) covering S. viridis genome were identified when using the reference based assembled transcripts and the de novo assembled transcripts, respectively. This identified transcripts and SSR provided by this study can be used for both reverse and forward genetic studies based on S. viridis.

Vibrational molecular modulation in hydrogen

NASA Astrophysics Data System (ADS)

Huang, Shu Wei; Chen, Wei-Jan; Kung, A. H.

2006-12-01

Detailed numerical modeling of using the vibrational coherence of H2 for molecular modulation is presented. The focus of the calculation is on a strongly driven system aimed at producing many sidebands in the presence of Doppler broadening and the effects of collisions at room temperature. It is shown that Dicke narrowing that reduces the Doppler width plays a critical role in high order sideband generation in room temperature H2 . In addition, the calculation shows that generation of many sidebands favors the phased state as has been reported in all gas phase experiments and is primarily a consequence of the Stark shifts that result from the applied high intensities. The influence of self-focusing in the gas medium that has been conjectured in previous studies is only secondary. The numerical results agree with experimental data obtained in our laboratory, where we have succeeded in generating collinearly propagating Raman sidebands with wavelengths that range from 2216nm in the infrared to 133nm in the vacuum ultraviolet. The frequencies covered by these sidebands span over four octaves for a total of more than 70600cm-1 in the optical region of the spectrum.

Quantitative analysis of RNA-protein interactions on a massively parallel array for mapping biophysical and evolutionary landscapes

PubMed Central

Buenrostro, Jason D.; Chircus, Lauren M.; Araya, Carlos L.; Layton, Curtis J.; Chang, Howard Y.; Snyder, Michael P.; Greenleaf, William J.

2015-01-01

RNA-protein interactions drive fundamental biological processes and are targets for molecular engineering, yet quantitative and comprehensive understanding of the sequence determinants of affinity remains limited. Here we repurpose a high-throughput sequencing instrument to quantitatively measure binding and dissociation of MS2 coat protein to >107 RNA targets generated on a flow-cell surface by in situ transcription and inter-molecular tethering of RNA to DNA. We decompose the binding energy contributions from primary and secondary RNA structure, finding that differences in affinity are often driven by sequence-specific changes in association rates. By analyzing the biophysical constraints and modeling mutational paths describing the molecular evolution of MS2 from low- to high-affinity hairpins, we quantify widespread molecular epistasis, and a long-hypothesized structure-dependent preference for G:U base pairs over C:A intermediates in evolutionary trajectories. Our results suggest that quantitative analysis of RNA on a massively parallel array (RNAMaP) relationships across molecular variants. PMID:24727714

Strategic placement of stereogenic centers in molecular materials for second harmonic generation.

PubMed

Gangopadhyay, P; Rao, D Narayana; Agranat, Israel; Radhakrishnan, T P

2002-01-01

Basic aspects of the nonlinear optical phenomenon of second harmonic generation (SHG) and the assembly of molecular materials for SHG are reviewed. Extensive use of chirality as a convenient tool to generate noncentrosymmetricity in molecular lattices, an essential requirement for the development of quadratic nonlinear optical materials, is noted. An overview of our investigations of chiral diaminodicyanoquinodimethanes is presented, which provides insight into a systematic approach to the effective deployment of chirality to achieve optimal molecular orientations for enhanced solid state SHG. Extension of these ideas to the realization of strong SHG in materials based on helical superstructures is outlined.

Transcriptomic evidence for the evolution of shoot meristem function in sporophyte-dominant land plants through concerted selection of ancestral gametophytic and sporophytic genetic programs.

PubMed

Frank, Margaret H; Scanlon, Michael J

2015-02-01

Alternation of generations, in which the haploid and diploid stages of the life cycle are each represented by multicellular forms that differ in their morphology, is a defining feature of the land plants (embryophytes). Anciently derived lineages of embryophytes grow predominately in the haploid gametophytic generation from apical cells that give rise to the photosynthetic body of the plant. More recently evolved plant lineages have multicellular shoot apical meristems (SAMs), and photosynthetic shoot development is restricted to the sporophyte generation. The molecular genetic basis for this evolutionary shift from gametophyte-dominant to sporophyte-dominant life cycles remains a major question in the study of land plant evolution. We used laser microdissection and next generation RNA sequencing to address whether angiosperm meristem patterning genes expressed in the sporophytic SAM of Zea mays are expressed in the gametophytic apical cells, or in the determinate sporophytes, of the model bryophytes Marchantia polymorpha and Physcomitrella patens. A wealth of upregulated genes involved in stem cell maintenance and organogenesis are identified in the maize SAM and in both the gametophytic apical cell and sporophyte of moss, but not in Marchantia. Significantly, meiosis-specific genetic programs are expressed in bryophyte sporophytes, long before the onset of sporogenesis. Our data suggest that this upregulated accumulation of meiotic gene transcripts suppresses indeterminate cell fate in the Physcomitrella sporophyte, and overrides the observed accumulation of meristem patterning genes. A model for the evolution of indeterminate growth in the sporophytic generation through the concerted selection of ancestral meristem gene programs from gametophyte-dominant lineages is proposed. © The Author 2014. 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.

Protein Modeling and Molecular Dynamics Simulation of Cloned Regucalcin (RGN) Gene from Bubalus bubalis.

PubMed

Pillai, Harikrishna; Yadav, Brijesh Singh; Chaturvedi, Navaneet; Jan, Arif Tasleem; Gupta, Girish Kumar; Baig, Mohammad Hassan; Bhure, Sanjeev Kumar

2017-01-01

Regucalcin (RGN), a calcium regulating protein having anti-prolific, antiapoptotic functions, plays important part in the biosynthesis of ascorbic acid. It is a highly conserved protein that has been reported from many tissue types of various vertebrate species. Employing its effect of regulating enzyme activities through reaction with sulfhydryl group (-SH) and calcium, structural level study believed to offer a better understanding of binding properties and regulatory mechanisms of RGN, was performed. Using sample from testis of Bubalus bubalis, amplification of regucalcin (RGN) gene was subjected to characterization by performing digestion using different restriction endonucleases (RE). Alongside, cDNA was cloned into pPICZαC vector and transformed in DH5α host for custom sequencing. To get a better insight of its structural characteristics, three dimensional (3D) structure of protein sequence was generated using in silico molecular modelling approach. The full trajectory analysis of structure was achieved by the Molecular Dynamics (MD) that explains the stability, flexibility and robustness of protein during simulation in a time of 50ns. Molecular docking against 1,5-anhydrosorbitol was performed for functional characterization of RGN. Preliminary screening of amplified products on Agarose gel showed expected size of ~893 bp of PCR product corresponding to RGN. Following sequencing, BLASTp search of the target sequence revealed that it shares 91% similarity score with human senescence marker protein-30 (pdb id: 3G4E). Molecular docking of 1,5-anhydrosorbitol reveals information regarding important binding site residues of RGN. 1,5-anhydrosorbitol was found to interact with binding free energy of - 6.01 Kcal/mol. RMSD calculation of subunits A, B and D-F might be responsible for functional and conserved regions of modeled protein. Three dimensional structure of RGN was generated and its interactions with 1,5- anhydrosorbitol, demonstrates the role of key binding residues. Until now, no structural details were available for buffalo RGN proteins, hence this study will broaden the horizon towards understanding the structural and functional aspects of different proteins in cattle. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Establishment of a Zebrafish Infection Model for the Study of Wild-Type and Recombinant European Sheatfish Virus.

PubMed

Martín, Verónica; Mavian, Carla; López Bueno, Alberto; de Molina, Antonio; Díaz, Eduardo; Andrés, Germán; Alcami, Antonio; Alejo, Alí

2015-10-01

Amphibian-like ranaviruses include pathogens of fish, amphibians, and reptiles that have recently evolved from a fish-infecting ancestor. The molecular determinants of host range and virulence in this group are largely unknown, and currently fish infection models are lacking. We show that European sheatfish virus (ESV) can productively infect zebrafish, causing a lethal pathology, and describe a method for the generation of recombinant ESV, establishing a useful model for the study of fish ranavirus infections. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Using next-generation sequencing to develop molecular diagnostics for Pseudoperonospora cubensis, the cucurbit downy mildew pathogen

USDA-ARS?s Scientific Manuscript database

Advances in Next Generation Sequencing (NGS) allow for rapid development of genomics resources needed to generate molecular diagnostics assays for infectious agents. NGS approaches are particularly helpful for organisms that cannot be cultured, such as the downy mildew pathogens, a group of biotrop...

Spectral studies related to dissociation of HBr, HCl and BrO

NASA Technical Reports Server (NTRS)

Ginter, M. L.

1986-01-01

Concern over halogen catalyzed decomposition of O3 in the upper atmosphere has generated need for data on the atomic and molecular species X, HX and XO (where X is Cl and Br). Of special importance are Cl produced from freon decomposition and Cl and Br produced from natural processes and from other industrial and agricultural chemicals. Basic spectral data is provided on HCl, HBr, and BrO necessary to detect specific states and energy levels, to enable detailed modeling of the processes involving molecular dissociation, ionization, etc., and to help evaluate field experiments to check the validity of model calculations for these species in the upper atmosphere. Results contained in four published papers and two major spectral compilations are summarized together with other results obtained.

ATK-ForceField: a new generation molecular dynamics software package

NASA Astrophysics Data System (ADS)

Schneider, Julian; Hamaekers, Jan; Chill, Samuel T.; Smidstrup, Søren; Bulin, Johannes; Thesen, Ralph; Blom, Anders; Stokbro, Kurt

2017-12-01

ATK-ForceField is a software package for atomistic simulations using classical interatomic potentials. It is implemented as a part of the Atomistix ToolKit (ATK), which is a Python programming environment that makes it easy to create and analyze both standard and highly customized simulations. This paper will focus on the atomic interaction potentials, molecular dynamics, and geometry optimization features of the software, however, many more advanced modeling features are available. The implementation details of these algorithms and their computational performance will be shown. We present three illustrative examples of the types of calculations that are possible with ATK-ForceField: modeling thermal transport properties in a silicon germanium crystal, vapor deposition of selenium molecules on a selenium surface, and a simulation of creep in a copper polycrystal.

Drosophila: a model for studying genetic and molecular aspects of haematopoiesis and associated leukaemias

PubMed Central

Crozatier, Michèle; Vincent, Alain

2011-01-01

Vertebrate haematopoietic stem cells (HSCs) give rise to a hierarchically organised set of progenitors for erythroid, myeloid, lymphoid and megakaryocyte lineages, and are responsible for lifelong maintenance of the blood system. Dysregulation of the haematopoietic differentiation programme is at the origin of numerous pathologies, including leukaemias. With the discoveries that many transcriptional regulators and signalling pathways controlling blood cell development are conserved between humans and Drosophila melanogaster, the fruit fly has become a good model for investigating the mechanisms underlying the generation of blood cell lineages and blood cell homeostasis. In this review article, we discuss how genetic and molecular studies of Drosophila haematopoiesis can contribute to our understanding of the haematopoietic niche, as well as of the origin and/or progression of haematopoietic malignancies in humans. PMID:21669932

Hierarchical Self-Organization of Perylene Bisimides into Supramolecular Spheres and Periodic Arrays Thereof.

PubMed

Sahoo, Dipankar; Peterca, Mihai; Aqad, Emad; Partridge, Benjamin E; Heiney, Paul A; Graf, Robert; Spiess, Hans W; Zeng, Xiangbing; Percec, Virgil

2016-11-09

Perylene bisimide derivatives (PBIs) are known to form only columnar or lamellar assemblies. There is no known example of a PBI self-assembling into a supramolecular sphere. Therefore, periodic and quasiperiodic arrays generated from spherical assemblies produced from PBIs are also not known. Here, a PBI functionalized at its imide groups with a second generation self-assembling dendron is reported to self-assemble into supramolecular spheres. These spheres self-organize in a body-centered cubic (BCC) periodic array, rarely encountered for self-assembling dendrons but often encountered in block copolymers. These supramolecular spheres also assemble into a columnar hexagonal array in which the supramolecular columns are unexpectedly and unprecedentedly made from spheres. At lower temperature, two additional columnar hexagonal phases consisting of symmetric and asymmetric tetrameric crowns of PBI are observed. Structural and retrostructural analysis via X-ray diffraction (XRD), molecular modeling, molecular simulation, and solid state NMR suggests that inversion of the symmetric tetrameric crowns at high temperature mediates their transformation into supramolecular spheres. The tetrameric crowns of PBIs are able to form an isotropic sphere in the cubic phase due to rapid molecular motion at high temperature, unobservable by XRD but demonstrated by solid state NMR studies. This mechanism of hierarchical self-organization of PBI into supramolecular spheres is most probably general and can be applied to other related planar molecules to generate new functions.

β-secretase inhibitors for Alzheimer's disease: identification using pharmacoinformatics.

PubMed

Islam, Md Ataul; Pillay, Tahir S

2018-02-01

In this study we searched for potential β-site amyloid precursor protein cleaving enzyme1 (BACE1) inhibitors using pharmacoinformatics. A large dataset containing 7155 known BACE1 inhibitors was evaluated for pharmacophore model generation. The final model (R = 0.950, RMSD = 1.094, Q 2  = 0.901, se = 0.332, [Formula: see text] = 0.901, [Formula: see text] = 0.756, sp = 0.468, [Formula: see text] = 0.667) was revealed with the importance of spatial arrangement of hydrogen bond acceptor and donor, hydrophobicity and aromatic ring features. The validated model was then used to search NCI and InterBioscreen databases for promising BACE1 inhibitors. The initial hits from both databases were sorted using a number of criteria and finally three molecules from each database were considered for further validation using molecular docking and molecular dynamics studies. Different protonation states of Asp32 and Asp228 dyad were analysed and best protonated form used for molecular docking study. Observation of the number of binding interactions in the molecular docking study supported the potential of these molecules being promising inhibitors. Values of RMSD, RMSF, Rg in molecular dynamics study and binding energies unquestionably explained that final screened molecules formed stable complexes inside the receptor cavity of BACE1. Hence, it can be concluded that the final screened six compounds may be potential therapeutic agents for Alzheimer's disease.

A new PDAC mouse model originated from iPSCs-converted pancreatic cancer stem cells (CSCcm)

PubMed Central

Calle, Anna Sanchez; Nair, Neha; Oo, Aung KoKo; Prieto-Vila, Marta; Koga, Megumi; Khayrani, Apriliana Cahya; Hussein, Maram; Hurley, Laura; Vaidyanath, Arun; Seno, Akimasa; Iwasaki, Yoshiaki; Calle, Malu; Kasai, Tomonari; Seno, Masaharu

2016-01-01

Pancreatic ductal adenocarcinoma (PDAC) is the most representative form of pancreatic cancers. PDAC solid tumours are constituted of heterogeneous populations of cells including cancer stem cells (CSCs), differentiated cancer cells, desmoplastic stroma and immune cells. The identification and consequent isolation of pancreatic CSCs facilitated the generation of genetically engineered murine models. Nonetheless, the current models may not be representative for the spontaneous tumour occurrence. In the present study, we show the generation of a novel pancreatic iPSC-converted cancer stem cell lines (CSCcm) as a cutting-edge model for the study of PDAC. The CSCcm lines were achieved only by the influence of pancreatic cancer cell lines conditioned medium and were not subjected to any genetic manipulation. The xenografts tumours from CSCcm lines displayed histopathological features of ADM, PanIN and PDAC lesions. Further molecular characterization from RNA-sequencing analysis highlighted primary culture cell lines (1st CSCcm) as potential candidates to represent the pancreatic CSCs and indicated the establishment of the pancreatic cancer molecular pattern in their subsequent progenies 2nd CSCcm and 3rd CSCcm. In addition, preliminary RNA-seq SNPs analysis showed that the distinct CSCcm lines did not harbour single point mutations for the oncogene Kras codon 12 or 13. Therefore, PDAC-CSCcm model may provide new insights about the actual occurrence of the pancreatic cancer leading to develop different approaches to target CSCs and abrogate the progression of this fatidic disease. PMID:28042501

Template-free modeling by LEE and LEER in CASP11.

PubMed

Joung, InSuk; Lee, Sun Young; Cheng, Qianyi; Kim, Jong Yun; Joo, Keehyoung; Lee, Sung Jong; Lee, Jooyoung

2016-09-01

For the template-free modeling of human targets of CASP11, we utilized two of our modeling protocols, LEE and LEER. The LEE protocol took CASP11-released server models as the input and used some of them as templates for 3D (three-dimensional) modeling. The template selection procedure was based on the clustering of the server models aided by a community detection method of a server-model network. Restraining energy terms generated from the selected templates together with physical and statistical energy terms were used to build 3D models. Side-chains of the 3D models were rebuilt using target-specific consensus side-chain library along with the SCWRL4 rotamer library, which completed the LEE protocol. The first success factor of the LEE protocol was due to efficient server model screening. The average backbone accuracy of selected server models was similar to that of top 30% server models. The second factor was that a proper energy function along with our optimization method guided us, so that we successfully generated better quality models than the input template models. In 10 out of 24 cases, better backbone structures than the best of input template structures were generated. LEE models were further refined by performing restrained molecular dynamics simulations to generate LEER models. CASP11 results indicate that LEE models were better than the average template models in terms of both backbone structures and side-chain orientations. LEER models were of improved physical realism and stereo-chemistry compared to LEE models, and they were comparable to LEE models in the backbone accuracy. Proteins 2016; 84(Suppl 1):118-130. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Inferring Biological Structures from Super-Resolution Single Molecule Images Using Generative Models

PubMed Central

Maji, Suvrajit; Bruchez, Marcel P.

2012-01-01

Localization-based super resolution imaging is presently limited by sampling requirements for dynamic measurements of biological structures. Generating an image requires serial acquisition of individual molecular positions at sufficient density to define a biological structure, increasing the acquisition time. Efficient analysis of biological structures from sparse localization data could substantially improve the dynamic imaging capabilities of these methods. Using a feature extraction technique called the Hough Transform simple biological structures are identified from both simulated and real localization data. We demonstrate that these generative models can efficiently infer biological structures in the data from far fewer localizations than are required for complete spatial sampling. Analysis at partial data densities revealed efficient recovery of clathrin vesicle size distributions and microtubule orientation angles with as little as 10% of the localization data. This approach significantly increases the temporal resolution for dynamic imaging and provides quantitatively useful biological information. PMID:22629348

A Protein Chimera Strategy Supports Production of a Model "Difficult-to-Express" Recombinant Target.

PubMed

Hussain, Hirra; Fisher, David I; Roth, Robert G; Abbott, W Mark; Carballo-Amador, Manuel Alejandro; Warwicker, Jim; Dickson, Alan J

2018-06-22

Due in part to the needs of the biopharmaceutical industry, there has been an increased drive to generate high quality recombinant proteins in large amounts. However, achieving high yields can be a challenge as the novelty and increased complexity of new targets often makes them 'difficult-to-express'. This study aimed to define the molecular features that restrict the production of a model 'difficult-to-express' recombinant protein, Tissue Inhibitor Metalloproteinase-3 (TIMP-3). Building from experimental data, computational approaches were used to rationalise the re-design of this recombinant target to generate a chimera with enhanced secretion. The results highlight the importance of early identification of unfavourable sequence attributes, enabling the generation of engineered protein forms that bypass 'secretory' bottlenecks and result in efficient recombinant protein production. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A 99 percent purity molecular sieve oxygen generator

NASA Technical Reports Server (NTRS)

Miller, G. W.

1991-01-01

Molecular sieve oxygen generating systems (MSOGS) have become the accepted method for the production of breathable oxygen on military aircraft. These systems separate oxygen for aircraft engine bleed air by application of pressure swing adsorption (PSA) technology. Oxygen is concentrated by preferential adsorption in nitrogen in a zeolite molecular sieve. However, the inability of current zeolite molecular sieves to discriminate between oxygen and argon results in an oxygen purity limitations of 93-95 percent (both oxygen and argon concentrate). The goal was to develop a new PSA process capable of exceeding the present oxygen purity limitations. A novel molecular sieve oxygen concentrator was developed which is capable of generating oxygen concentrations of up to 99.7 percent directly from air. The process is comprised of four absorbent beds, two containing a zeolite molecular sieve and two containing a carbon molecular sieve. This new process may find use in aircraft and medical breathing systems, and industrial air separation systems. The commercial potential of the process is currently being evaluated.

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

Molecular dynamic simulations and structure-based pharmacophore development for farnesyltransferase inhibitors discovery.

PubMed

Moorthy, N S Hari Narayana; Sousa, Sergio F; Ramos, Maria J; Fernandes, Pedro A

2016-12-01

Farnesyltransferase is one of the enzyme targets for the development of drugs for diseases, including cancer, malaria, progeria, etc. In the present study, the structure-based pharmacophore models have been developed from five complex structures (1LD7, 1NI1, 2IEJ, 2ZIR and 2ZIS) obtained from the protein data bank. Initially, molecular dynamic (MD) simulations were performed for the complexes for 10 ns using AMBER 12 software. The conformers of the complexes (75) generated from the equilibrated protein were undergone protein-ligand interaction fingerprint (PLIF) analysis. The results showed that some important residues, such as LeuB96, TrpB102, TrpB106, ArgB202, TyrB300, AspB359 and TyrB361, are predominantly present in most of the complexes for interactions. These residues form side chain acceptor and surface (hydrophobic or π-π) kind of interactions with the ligands present in the complexes. The structure-based pharmacophore models were generated from the fingerprint bits obtained from PLIF analysis. The pharmacophore models have 3-4 pharmacophore contours consist of acceptor and metal ligation (Acc & ML), hydrophobic (HydA) and extended acceptor (Acc2) features with the radius ranging between 1-3 Å for Acc & ML and 1-2 Å for HydA. The excluded volumes of the pharmacophore contours radius are between 1-2 Å. Further, the distance between the interacting groups, root mean square deviation (RMSD), root mean square fluctuation (RMSF) and radial distribution function (RDF) analysis were performed for the MD-simulated proteins using PTRAJ module. The generated pharmacophore models were used to screen a set of natural compounds and database compounds to select significant HITs. We conclude that the developed pharmacophore model can be a significant model for the identification of HITs as FTase inhibitors.

Simultaneous optimization of biomolecular energy function on features from small molecules and macromolecules

PubMed Central

Park, Hahnbeom; Bradley, Philip; Greisen, Per; Liu, Yuan; Mulligan, Vikram Khipple; Kim, David E.; Baker, David; DiMaio, Frank

2017-01-01

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking, have been parameterized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data. The energy function improves performance in a wide range of protein structure prediction challenges, including monomeric structure prediction, protein-protein and protein-ligand docking, protein sequence design, and prediction of the free energy changes by mutation, while reasonably recapitulating small-molecule thermodynamic properties. PMID:27766851

Integral control of plant gravitropism through the interplay of hormone signaling and gene regulation.

PubMed

Rodrigo, Guillermo; Jaramillo, Alfonso; Blázquez, Miguel A

2011-08-17

The interplay between hormone signaling and gene regulatory networks is instrumental in promoting the development of living organisms. In particular, plants have evolved mechanisms to sense gravity and orient themselves accordingly. Here, we present a mathematical model that reproduces plant gravitropic responses based on known molecular genetic interactions for auxin signaling coupled with a physical description of plant reorientation. The model allows one to analyze the spatiotemporal dynamics of the system, triggered by an auxin gradient that induces differential growth of the plant with respect to the gravity vector. Our model predicts two important features with strong biological implications: 1), robustness of the regulatory circuit as a consequence of integral control; and 2), a higher degree of plasticity generated by the molecular interplay between two classes of hormones. Our model also predicts the ability of gibberellins to modulate the tropic response and supports the integration of the hormonal role at the level of gene regulation. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Markov-modulated Markov chains and the covarion process of molecular evolution.

PubMed

Galtier, N; Jean-Marie, A

2004-01-01

The covarion (or site specific rate variation, SSRV) process of biological sequence evolution is a process by which the evolutionary rate of a nucleotide/amino acid/codon position can change in time. In this paper, we introduce time-continuous, space-discrete, Markov-modulated Markov chains as a model for representing SSRV processes, generalizing existing theory to any model of rate change. We propose a fast algorithm for diagonalizing the generator matrix of relevant Markov-modulated Markov processes. This algorithm makes phylogeny likelihood calculation tractable even for a large number of rate classes and a large number of states, so that SSRV models become applicable to amino acid or codon sequence datasets. Using this algorithm, we investigate the accuracy of the discrete approximation to the Gamma distribution of evolutionary rates, widely used in molecular phylogeny. We show that a relatively large number of classes is required to achieve accurate approximation of the exact likelihood when the number of analyzed sequences exceeds 20, both under the SSRV and among site rate variation (ASRV) models.

Patient-derived Models of Human Breast Cancer: Protocols for In vitro and In vivo Applications in Tumor Biology and Translational Medicine

PubMed Central

DeRose, Yoko S.; Gligorich, Keith M.; Wang, Guoying; Georgelas, Ann; Bowman, Paulette; Courdy, Samir J.; Welm, Alana L.; Welm, Bryan E.

2013-01-01

Research models that replicate the diverse genetic and molecular landscape of breast cancer are critical for developing the next generation therapeutic entities that can target specific cancer subtypes. Patient-derived tumorgrafts, generated by transplanting primary human tumor samples into immune-compromised mice, are a valuable method to model the clinical diversity of breast cancer in mice, and are a potential resource in personalized medicine. Primary tumorgrafts also enable in vivo testing of therapeutics and make possible the use of patient cancer tissue for in vitro screens. Described in this unit are a variety of protocols including tissue collection, biospecimen tracking, tissue processing, transplantation, and 3-dimensional culturing of xenografted tissue, that enable use of bona fide uncultured human tissue in designing and validating cancer therapies. PMID:23456611

Next-Generation of Allergen-Specific Immunotherapies: Molecular Approaches.

PubMed

Curin, Mirela; Khaitov, Musa; Karaulov, Alexander; Namazova-Baranova, Leyla; Campana, Raffaela; Garib, Victoria; Valenta, Rudolf

2018-06-09

The aim of this article is to discuss how allergen-specific immunotherapy (AIT) can be improved through molecular approaches. We provide a summary of next-generation molecular AIT approaches and of their clinical evaluation. Furthermore, we discuss the potential of next generation molecular AIT forms for the treatment of severe manifestations of allergy and mention possible future molecular strategies for the secondary and primary prevention of allergy. AIT has important advantages over symptomatic forms of allergy treatment but its further development is limited by the quality of the therapeutic antigen preparations which are derived from natural allergen sources. The field of allergy diagnosis is currently undergoing a dramatic improvement through the use of molecular testing with defined, mainly recombinant allergens which allows high-resolution diagnosis. Several studies demonstrate that molecular testing in early childhood can predict the development of symptomatic allergy later on in life. Clinical studies indicate that molecular AIT approaches have the potential to improve therapy of allergic diseases and may be used as allergen-specific forms of secondary and eventually primary prevention for allergy.

Understanding phylogenetic incongruence: lessons from phyllostomid bats

PubMed Central

Dávalos, Liliana M; Cirranello, Andrea L; Geisler, Jonathan H; Simmons, Nancy B

2012-01-01

All characters and trait systems in an organism share a common evolutionary history that can be estimated using phylogenetic methods. However, differential rates of change and the evolutionary mechanisms driving those rates result in pervasive phylogenetic conflict. These drivers need to be uncovered because mismatches between evolutionary processes and phylogenetic models can lead to high confidence in incorrect hypotheses. Incongruence between phylogenies derived from morphological versus molecular analyses, and between trees based on different subsets of molecular sequences has become pervasive as datasets have expanded rapidly in both characters and species. For more than a decade, evolutionary relationships among members of the New World bat family Phyllostomidae inferred from morphological and molecular data have been in conflict. Here, we develop and apply methods to minimize systematic biases, uncover the biological mechanisms underlying phylogenetic conflict, and outline data requirements for future phylogenomic and morphological data collection. We introduce new morphological data for phyllostomids and outgroups and expand previous molecular analyses to eliminate methodological sources of phylogenetic conflict such as taxonomic sampling, sparse character sampling, or use of different algorithms to estimate the phylogeny. We also evaluate the impact of biological sources of conflict: saturation in morphological changes and molecular substitutions, and other processes that result in incongruent trees, including convergent morphological and molecular evolution. Methodological sources of incongruence play some role in generating phylogenetic conflict, and are relatively easy to eliminate by matching taxa, collecting more characters, and applying the same algorithms to optimize phylogeny. The evolutionary patterns uncovered are consistent with multiple biological sources of conflict, including saturation in morphological and molecular changes, adaptive morphological convergence among nectar-feeding lineages, and incongruent gene trees. Applying methods to account for nucleotide sequence saturation reduces, but does not completely eliminate, phylogenetic conflict. We ruled out paralogy, lateral gene transfer, and poor taxon sampling and outgroup choices among the processes leading to incongruent gene trees in phyllostomid bats. Uncovering and countering the possible effects of introgression and lineage sorting of ancestral polymorphism on gene trees will require great leaps in genomic and allelic sequencing in this species-rich mammalian family. We also found evidence for adaptive molecular evolution leading to convergence in mitochondrial proteins among nectar-feeding lineages. In conclusion, the biological processes that generate phylogenetic conflict are ubiquitous, and overcoming incongruence requires better models and more data than have been collected even in well-studied organisms such as phyllostomid bats. PMID:22891620

The phylogenomic roots of modern biochemistry: origins of proteins, cofactors and protein biosynthesis.

PubMed

Caetano-Anollés, Gustavo; Kim, Kyung Mo; Caetano-Anollés, Derek

2012-02-01

The complexity of modern biochemistry developed gradually on early Earth as new molecules and structures populated the emerging cellular systems. Here, we generate a historical account of the gradual discovery of primordial proteins, cofactors, and molecular functions using phylogenomic information in the sequence of 420 genomes. We focus on structural and functional annotations of the 54 most ancient protein domains. We show how primordial functions are linked to folded structures and how their interaction with cofactors expanded the functional repertoire. We also reveal protocell membranes played a crucial role in early protein evolution and show translation started with RNA and thioester cofactor-mediated aminoacylation. Our findings allow elaboration of an evolutionary model of early biochemistry that is firmly grounded in phylogenomic information and biochemical, biophysical, and structural knowledge. The model describes how primordial α-helical bundles stabilized membranes, how these were decorated by layered arrangements of β-sheets and α-helices, and how these arrangements became globular. Ancient forms of aminoacyl-tRNA synthetase (aaRS) catalytic domains and ancient non-ribosomal protein synthetase (NRPS) modules gave rise to primordial protein synthesis and the ability to generate a code for specificity in their active sites. These structures diversified producing cofactor-binding molecular switches and barrel structures. Accretion of domains and molecules gave rise to modern aaRSs, NRPS, and ribosomal ensembles, first organized around novel emerging cofactors (tRNA and carrier proteins) and then more complex cofactor structures (rRNA). The model explains how the generation of protein structures acted as scaffold for nucleic acids and resulted in crystallization of modern translation.

The use of many-body physics and thermodynamics to describe the dynamics of rhythmic generators in sensory cortices engaged in memory and learning.

PubMed

Vitiello, Giuseppe

2015-04-01

The problem of the transition from the molecular and cellular level to the macroscopic level of observed assemblies of myriads of neurons is the subject addressed in this report. The great amount of detailed information available at molecular and cellular level seems not sufficient to account for the high effectiveness and reliability observed in the brain macroscopic functioning. It is suggested that the dissipative many-body model and thermodynamics might offer the dynamical frame underlying the rich phenomenology observed at microscopic and macroscopic level and help in the understanding on how to fill the gap between the bio-molecular and cellular level and the one of brain macroscopic functioning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Opacity probability distribution functions for electronic systems of CN and C2 molecules including their stellar isotopic forms.

NASA Technical Reports Server (NTRS)

Querci, F.; Kunde, V. G.; Querci, M.

1971-01-01

The basis and techniques are presented for generating opacity probability distribution functions for the CN molecule (red and violet systems) and the C2 molecule (Swan, Phillips, Ballik-Ramsay systems), two of the more important diatomic molecules in the spectra of carbon stars, with a view to including these distribution functions in equilibrium model atmosphere calculations. Comparisons to the CO molecule are also shown. T he computation of the monochromatic absorption coefficient uses the most recent molecular data with revision of the oscillator strengths for some of the band systems. The total molecular stellar mass absorption coefficient is established through fifteen equations of molecular dissociation equilibrium to relate the distribution functions to each other on a per gram of stellar material basis.

Protein modeling and molecular dynamics simulation of the two novel surfactant proteins SP-G and SP-H.

PubMed

Rausch, Felix; Schicht, Martin; Bräuer, Lars; Paulsen, Friedrich; Brandt, Wolfgang

2014-11-01

Surfactant proteins are well known from the human lung where they are responsible for the stability and flexibility of the pulmonary surfactant system. They are able to influence the surface tension of the gas-liquid interface specifically by directly interacting with single lipids. This work describes the generation of reliable protein structure models to support the experimental characterization of two novel putative surfactant proteins called SP-G and SP-H. The obtained protein models were complemented by predicted posttranslational modifications and placed in a lipid model system mimicking the pulmonary surface. Molecular dynamics simulations of these protein-lipid systems showed the stability of the protein models and the formation of interactions between protein surface and lipid head groups on an atomic scale. Thereby, interaction interface and strength seem to be dependent on orientation and posttranslational modification of the protein. The here presented modeling was fundamental for experimental localization studies and the simulations showed that SP-G and SP-H are theoretically able to interact with lipid systems and thus are members of the surfactant protein family.

Multiscale modeling of dislocation-precipitate interactions in Fe: From molecular dynamics to discrete dislocations.

PubMed

Lehtinen, Arttu; Granberg, Fredric; Laurson, Lasse; Nordlund, Kai; Alava, Mikko J

2016-01-01

The stress-driven motion of dislocations in crystalline solids, and thus the ensuing plastic deformation process, is greatly influenced by the presence or absence of various pointlike defects such as precipitates or solute atoms. These defects act as obstacles for dislocation motion and hence affect the mechanical properties of the material. Here we combine molecular dynamics studies with three-dimensional discrete dislocation dynamics simulations in order to model the interaction between different kinds of precipitates and a 1/2〈111〉{110} edge dislocation in BCC iron. We have implemented immobile spherical precipitates into the ParaDis discrete dislocation dynamics code, with the dislocations interacting with the precipitates via a Gaussian potential, generating a normal force acting on the dislocation segments. The parameters used in the discrete dislocation dynamics simulations for the precipitate potential, the dislocation mobility, shear modulus, and dislocation core energy are obtained from molecular dynamics simulations. We compare the critical stresses needed to unpin the dislocation from the precipitate in molecular dynamics and discrete dislocation dynamics simulations in order to fit the two methods together and discuss the variety of the relevant pinning and depinning mechanisms.

Superchiral Light Generation on Degenerate Achiral Surfaces

NASA Astrophysics Data System (ADS)

Vázquez-Guardado, Abraham; Chanda, Debashis

2018-03-01

A novel route of superchiral near-field generation is demonstrated based on geometrically achiral systems supporting degenerate and spatially superimposed plasmonic modes. Such systems generate a single-handed chiral near field with simultaneous zero far-field circular dichroism. The phenomenon is theoretically elucidated with a rotating dipole model, which predicts a uniform single-handed chiral near field that flips handedness solely by reversing the handedness of the source. This property allows detection of pure background free molecular chirality through near-field light-matter interaction, which is experimentally demonstrated in the precise identification of both handedness of a chiral molecule on a single substrate with about four orders of magnitude enhancement in detection sensitivity compared to its conventional volumetric counterpart.

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

NASA Astrophysics Data System (ADS)

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

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

Molecular Dynamics-based Simulations of Bulk/Interfacial Structures and Diffusion Behaviors in Nuclear Waste Glasses

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

Du, Jincheng; Rimsza, Jessica; Deng, Lu

This NEUP Project aimed to generate accurate atomic structural models of nuclear waste glasses by using large-scale molecular dynamics-based computer simulations and to use these models to investigate self-diffusion behaviors, interfacial structures, and hydrated gel structures formed during dissolution of these glasses. The goal was to obtain realistic and accurate short and medium range structures of these complex oxide glasses, to provide a mechanistic understanding of the dissolution behaviors, and to generate reliable information with predictive power in designing nuclear waste glasses for long-term geological storage. Looking back of the research accomplishments of this project, most of the scientific goalsmore » initially proposed have been achieved through intensive research in the three and a half year period of the project. This project has also generated a wealth of scientific data and vibrant discussions with various groups through collaborations within and outside of this project. Throughout the project one book chapter and 14 peer reviewed journal publications have been generated (including one under review) and 16 presentations (including 8 invited talks) have been made to disseminate the results of this project in national and international conference. Furthermore, this project has trained several outstanding graduate students and young researchers for future workforce in nuclear related field, especially on nuclear waste immobilization. One postdoc and four PhD students have been fully or partially supported through the project with intensive training in the field material science and engineering with expertise on glass science and nuclear waste disposal« less

Intrinsic Resolution of Molecular Electronic Wave Functions and Energies in Terms of Quasi-atoms and Their Interactions.

PubMed

West, Aaron C; Schmidt, Michael W; Gordon, Mark S; Ruedenberg, Klaus

2017-02-09

A general intrinsic energy resolution has been formulated for strongly correlated wave functions in the full molecular valence space and its subspaces. The information regarding the quasi-atomic organization of the molecular electronic structure is extracted from the molecular wave function without introducing any additional postulated model state wave functions. To this end, the molecular wave function is expressed in terms of quasi-atomic molecular orbitals, which maximize the overlap between subspaces of the molecular orbital space and the free-atom orbital spaces. As a result, the molecular wave function becomes the superposition of a wave function representing the juxtaposed nonbonded quasi-atoms and a wave function describing the interatomic electron migrations that create bonds through electron sharing. The juxtaposed nonbonded quasi-atoms are shown to consist of entangled quasi-atomic states from different atoms. The binding energy is resolved as a sum of contributions that are due to quasi-atom formation, quasiclassical electrostatic interactions, and interatomic interferences caused by electron sharing. The contributions are further resolved according to orbital interactions. The various transformations that generate the analysis are determined by criteria that are independent of the working orbital basis used for calculating the molecular wave function. The theoretical formulation of the resolution is quantitatively validated by an application to the C 2 molecule.

SHAPEMOL: the companion to SHAPE in the molecular era of ALMA and HERSCHEL

NASA Astrophysics Data System (ADS)

Santander-García, M.; Bujarrabal, V.; Alcolea, J.

2013-05-01

Modern instrumentation in radioastronomy constitutes a valuable tool for studying the Universe: ALMA will reach unprecedented sensitivities and spatial resolution, while Herschel/HIFI has opened a new window (most of the sub-mm and far infrared ranges are only accessible from space) for probing molecular warm gas (˜50-1000 K), complementing ground-based telescopes, which are better suited to study molecular molecular gas with temperatures under ˜100 K. On the other hand, the SHAPE software has emerged in the last few years as the standard tool for determinging the morphology and velocity field of different kinds of gaseous nebulae (mainly planetary nebulae, protoplanetary nebulae and nebulae around massive stars, although it can also be applied to H II regions and molecular clouds) via spatio-kinematical modelling. Standard SHAPE implements radiative transfer solving, but it is only available for atomic species and not for molecules. Being aware of the growing importance of the development of tools for easying the analyses of molecular data from new era observatories, we introduce the computer code shapemol, a plug-in for SHAPE with which we intend to fill the so far empty molecular niche. shapemol enables spatio-kinematic modeling with accurate non-LTE calculations of line excitation and radiative transfer in molecular species. This code has been succesfully tested in the study of the excitation conditions of the molecular envelope of the planetary nebula NGC 7027 using data from Herschel/HIFI and IRAM 30m. Currently, it allows radiative transfer solving in the ^{12}CO and ^{13}CO J=1-0 to J=17-16 lines. shapemol, used along SHAPE, allows to easily generate synthetic maps to test against interferometric observations, as well as synthetic line profiles to match single-dish observations.

WDL-RF: Predicting Bioactivities of Ligand Molecules Acting with G Protein-coupled Receptors by Combining Weighted Deep Learning and Random Forest.

PubMed

Wu, Jiansheng; Zhang, Qiuming; Wu, Weijian; Pang, Tao; Hu, Haifeng; Chan, Wallace K B; Ke, Xiaoyan; Zhang, Yang; Wren, Jonathan

2018-02-08

Precise assessment of ligand bioactivities (including IC50, EC50, Ki, Kd, etc.) is essential for virtual screening and lead compound identification. However, not all ligands have experimentally-determined activities. In particular, many G protein-coupled receptors (GPCRs), which are the largest integral membrane protein family and represent targets of nearly 40% drugs on the market, lack published experimental data about ligand interactions. Computational methods with the ability to accurately predict the bioactivity of ligands can help efficiently address this problem. We proposed a new method, WDL-RF, using weighted deep learning and random forest, to model the bioactivity of GPCR-associated ligand molecules. The pipeline of our algorithm consists of two consecutive stages: 1) molecular fingerprint generation through a new weighted deep learning method, and 2) bioactivity calculations with a random forest model; where one uniqueness of the approach is that the model allows end-to-end learning of prediction pipelines with input ligands being of arbitrary size. The method was tested on a set of twenty-six non-redundant GPCRs that have a high number of active ligands, each with 200∼4000 ligand associations. The results from our benchmark show that WDL-RF can generate bioactivity predictions with an average root-mean square error 1.33 and correlation coefficient (r2) 0.80 compared to the experimental measurements, which are significantly more accurate than the control predictors with different molecular fingerprints and descriptors. In particular, data-driven molecular fingerprint features, as extracted from the weighted deep learning models, can help solve deficiencies stemming from the use of traditional hand-crafted features and significantly increase the efficiency of short molecular fingerprints in virtual screening. The WDL-RF web server, as well as source codes and datasets of WDL-RF, is freely available at https://zhanglab.ccmb.med.umich.edu/WDL-RF/ for academic purposes. Xiaoyan Ke (kexynj@hotmail.com); Yang Zhang (zhng@umich.edu). Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Density functional theory-based simulations of sum frequency generation spectra involving methyl stretching vibrations: effect of the molecular model on the deduced molecular orientation and comparison with an analytical approach.

PubMed

Cecchet, F; Lis, D; Caudano, Y; Mani, A A; Peremans, A; Champagne, B; Guthmuller, J

2012-03-28

The knowledge of the first hyperpolarizability tensor elements of molecular groups is crucial for a quantitative interpretation of the sum frequency generation (SFG) activity of thin organic films at interfaces. Here, the SFG response of the terminal methyl group of a dodecanethiol (DDT) monolayer has been interpreted on the basis of calculations performed at the density functional theory (DFT) level of approximation. In particular, DFT calculations have been carried out on three classes of models for the aliphatic chains. The first class of models consists of aliphatic chains, containing from 3 to 12 carbon atoms, in which only one methyl group can freely vibrate, while the rest of the chain is frozen by a strong overweight of its C and H atoms. This enables us to localize the probed vibrational modes on the methyl group. In the second class, only one methyl group is frozen, while the entire remaining chain is allowed to vibrate. This enables us to analyse the influence of the aliphatic chain on the methyl stretching vibrations. Finally, the dodecanethiol (DDT) molecule is considered, for which the effects of two dielectrics, i.e. n-hexane and n-dodecane, are investigated. Moreover, DDT calculations are also carried out by using different exchange-correlation (XC) functionals in order to assess the DFT approximations. Using the DFT IR vectors and Raman tensors, the SFG spectrum of DDT has been simulated and the orientation of the methyl group has then been deduced and compared with that obtained using an analytical approach based on a bond additivity model. This analysis shows that when using DFT molecular properties, the predicted orientation of the terminal methyl group tends to converge as a function of the alkyl chain length and that the effects of the chain as well as of the dielectric environment are small. Instead, a more significant difference is observed when comparing the DFT-based results with those obtained from the analytical approach, thus indicating the importance of a quantum chemical description of the hyperpolarizability tensor elements of the methyl group. © 2012 IOP Publishing Ltd

Overview of Animal Models of Obesity

PubMed Central

Lutz, Thomas A.; Woods, Stephen C.

2012-01-01

This is a review of animal models of obesity currently used in research. We have focused upon more commonly utilized models since there are far too many newly created models to consider, especially those caused by selective molecular genetic approaches modifying one or more genes in specific populations of cells. Further, we will not discuss the generation and use of inducible transgenic animals (induced knock-out or knock-in) even though they often bear significant advantages compared to traditional transgenic animals; influences of the genetic modification during the development of the animals can be minimized. The number of these animal models is simply too large to be covered in this chapter. PMID:22948848

Application of Generative Autoencoder in De Novo Molecular Design.

PubMed

Blaschke, Thomas; Olivecrona, Marcus; Engkvist, Ola; Bajorath, Jürgen; Chen, Hongming

2018-01-01

A major challenge in computational chemistry is the generation of novel molecular structures with desirable pharmacological and physiochemical properties. In this work, we investigate the potential use of autoencoder, a deep learning methodology, for de novo molecular design. Various generative autoencoders were used to map molecule structures into a continuous latent space and vice versa and their performance as structure generator was assessed. Our results show that the latent space preserves chemical similarity principle and thus can be used for the generation of analogue structures. Furthermore, the latent space created by autoencoders were searched systematically to generate novel compounds with predicted activity against dopamine receptor type 2 and compounds similar to known active compounds not included in the trainings set were identified. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Draft genome assembly of the Bengalese finch, Lonchura striata domestica, a model for motor skill variability and learning

PubMed Central

Mets, David G; Brainard, Michael S

2018-01-01

Abstract Background Vocal learning in songbirds has emerged as a powerful model for sensorimotor learning. Neurobehavioral studies of Bengalese finch (Lonchura striata domestica) song, naturally more variable and plastic than songs of other finch species, have demonstrated the importance of behavioral variability for initial learning, maintenance, and plasticity of vocalizations. However, the molecular and genetic underpinnings of this variability and the learning it supports are poorly understood. Findings To establish a platform for the molecular analysis of behavioral variability and plasticity, we generated an initial draft assembly of the Bengalese finch genome from a single male animal to 151× coverage and an N50 of 3.0 MB. Furthermore, we developed an initial set of gene models using RNA-seq data from 8 samples that comprise liver, muscle, cerebellum, brainstem/midbrain, and forebrain tissue from juvenile and adult Bengalese finches of both sexes. Conclusions We provide a draft Bengalese finch genome and gene annotation to facilitate the study of the molecular-genetic influences on behavioral variability and the process of vocal learning. These data will directly support many avenues for the identification of genes involved in learning, including differential expression analysis, comparative genomic analysis (through comparison to existing avian genome assemblies), and derivation of genetic maps for linkage analysis. Bengalese finch gene models and sequences will be essential for subsequent manipulation (molecular or genetic) of genes and gene products, enabling novel mechanistic investigations into the role of variability in learned behavior. PMID:29618046

Design of novel quinazolinone derivatives as inhibitors for 5HT7 receptor.

PubMed

Chitta, Aparna; Jatavath, Mohan Babu; Fatima, Sabiha; Manga, Vijjulatha

2012-02-01

To study the pharmacophore properties of quinazolinone derivatives as 5HT(7) inhibitors, 3D QSAR methodologies, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied, partial least square (PLS) analysis was performed and QSAR models were generated. The derived model showed good statistical reliability in terms of predicting the 5HT(7) inhibitory activity of the quinazolione derivative, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like q(2) (cross validated correlation coefficient) of 0.642, 0.602 and r(2) (conventional correlation coefficient) of 0.937, 0.908 for CoMFA and CoMSIA respectively. The predictive ability of the models to determine 5HT(7) antagonistic activity is validated using a test set of 26 molecules that were not included in the training set and the predictive r(2) obtained for the test set was 0.512 & 0.541. Further, the results of the derived model are illustrated by means of contour maps, which give an insight into the interaction of the drug with the receptor. The molecular fields so obtained served as the basis for the design of twenty new ligands. In addition, ADME (Adsorption, Distribution, Metabolism and Elimination) have been calculated in order to predict the relevant pharmaceutical properties, and the results are in conformity with required drug like properties.

Draft genome assembly of the Bengalese finch, Lonchura striata domestica, a model for motor skill variability and learning.

PubMed

Colquitt, Bradley M; Mets, David G; Brainard, Michael S

2018-03-01

Vocal learning in songbirds has emerged as a powerful model for sensorimotor learning. Neurobehavioral studies of Bengalese finch (Lonchura striata domestica) song, naturally more variable and plastic than songs of other finch species, have demonstrated the importance of behavioral variability for initial learning, maintenance, and plasticity of vocalizations. However, the molecular and genetic underpinnings of this variability and the learning it supports are poorly understood. To establish a platform for the molecular analysis of behavioral variability and plasticity, we generated an initial draft assembly of the Bengalese finch genome from a single male animal to 151× coverage and an N50 of 3.0 MB. Furthermore, we developed an initial set of gene models using RNA-seq data from 8 samples that comprise liver, muscle, cerebellum, brainstem/midbrain, and forebrain tissue from juvenile and adult Bengalese finches of both sexes. We provide a draft Bengalese finch genome and gene annotation to facilitate the study of the molecular-genetic influences on behavioral variability and the process of vocal learning. These data will directly support many avenues for the identification of genes involved in learning, including differential expression analysis, comparative genomic analysis (through comparison to existing avian genome assemblies), and derivation of genetic maps for linkage analysis. Bengalese finch gene models and sequences will be essential for subsequent manipulation (molecular or genetic) of genes and gene products, enabling novel mechanistic investigations into the role of variability in learned behavior.

The effects of moisture on molecular sieve oxygen concentrators.

PubMed

Ikels, K G; Theis, C F

1985-01-01

Molecular sieve oxygen generating systems are receiving extensive laboratory and flight evaluation. Assessment of the molecular system has generally been conducted in the laboratory using clean dry air. In aircraft, however, the molecular sieve generator is supplied with engine bleed air which may not always be totally free of contaminants and water. Recent studies using bed washout technics have shown that the molecular sieve units, with 50% of the beds deactivated with water, still function normally with respect to product gas flow and O2 concentration. By utilizing the technics described in this paper, the moisture content or state of hydration of the molecular sieve can readily be determined.

DockoMatic 2.0: High Throughput Inverse Virtual Screening and Homology Modeling

PubMed Central

Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T.; McDougal, Owen M.; Andersen, Timothy L.

2013-01-01

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly Graphical User Interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to: (1) conduct high throughput Inverse Virtual Screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying a receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories, and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELLER programs, and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education. PMID:23808933

Binding Mode Analyses and Pharmacophore Model Development for Stilbene Derivatives as a Novel and Competitive Class of α-Glucosidase Inhibitors

PubMed Central

Kim, Jun Young; Arooj, Mahreen; Kim, Siu; Hwang, Swan; Kim, Byeong-Woo; Park, Ki Hun; Lee, Keun Woo

2014-01-01

Stilbene urea derivatives as a novel and competitive class of non-glycosidic α-glucosidase inhibitors are effective for the treatment of type II diabetes and obesity. The main purposes of our molecular modeling study are to explore the most suitable binding poses of stilbene derivatives with analyzing the binding affinity differences and finally to develop a pharmacophore model which would represents critical features responsible for α-glucosidase inhibitory activity. Three-dimensional structure of S. cerevisiae α-glucosidase was built by homology modeling method and the structure was used for the molecular docking study to find out the initial binding mode of compound 12, which is the most highly active one. The initial structure was subjected to molecular dynamics (MD) simulations for protein structure adjustment at compound 12-bound state. Based on the adjusted conformation, the more reasonable binding modes of the stilbene urea derivatives were obtained from molecular docking and MD simulations. The binding mode of the derivatives was validated by correlation analysis between experimental Ki value and interaction energy. Our results revealed that the binding modes of the potent inhibitors were engaged with important hydrogen bond, hydrophobic, and π-interactions. With the validated compound 12-bound structure obtained from combining approach of docking and MD simulation, a proper four featured pharmacophore model was generated. It was also validated by comparison of fit values with the Ki values. Thus, these results will be helpful for understanding the relationship between binding mode and bioactivity and for designing better inhibitors from stilbene derivatives. PMID:24465730

A perspective on laboratory utilization management from Canada.

PubMed

Naugler, Christopher

2014-01-01

Utilization, particularly in chemistry and molecular testing, is growing rapidly in Canada at a time when laboratory budgets are shrinking. Canadian laboratories face particular challenges as the prevailing funding model limits the scope for new revenue generation. Aggressive and coordinated interventions to reduce over-utilization will be necessary to ensure the long-term viability of the current system. © 2013.

Dissecting and Targeting Latent Metastasis

DTIC Science & Technology

2013-09-01

particular. Developing and using experimental models of LMBC to elucidate these survival mechanisms will provide a basis for therapeutically targeting...stochastic, low frequency generation of lethal macrometastatic lesion. Progress Item 1.1. Using this approach, we have successfully isolated latent...cells lines are being used to illuminate the molecular basis for the latent metastasis state. Progress Item 1.2. In parallel with the isolation of

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

Kadoura, Ahmad, E-mail: ahmad.kadoura@kaust.edu.sa, E-mail: adil.siripatana@kaust.edu.sa, E-mail: shuyu.sun@kaust.edu.sa, E-mail: omar.knio@kaust.edu.sa; Sun, Shuyu, E-mail: ahmad.kadoura@kaust.edu.sa, E-mail: adil.siripatana@kaust.edu.sa, E-mail: shuyu.sun@kaust.edu.sa, E-mail: omar.knio@kaust.edu.sa; Siripatana, Adil, E-mail: ahmad.kadoura@kaust.edu.sa, E-mail: adil.siripatana@kaust.edu.sa, E-mail: shuyu.sun@kaust.edu.sa, E-mail: omar.knio@kaust.edu.sa

In this work, two Polynomial Chaos (PC) surrogates were generated to reproduce Monte Carlo (MC) molecular simulation results of the canonical (single-phase) and the NVT-Gibbs (two-phase) ensembles for a system of normalized structureless Lennard-Jones (LJ) particles. The main advantage of such surrogates, once generated, is the capability of accurately computing the needed thermodynamic quantities in a few seconds, thus efficiently replacing the computationally expensive MC molecular simulations. Benefiting from the tremendous computational time reduction, the PC surrogates were used to conduct large-scale optimization in order to propose single-site LJ models for several simple molecules. Experimental data, a set of supercriticalmore » isotherms, and part of the two-phase envelope, of several pure components were used for tuning the LJ parameters (ε, σ). Based on the conducted optimization, excellent fit was obtained for different noble gases (Ar, Kr, and Xe) and other small molecules (CH{sub 4}, N{sub 2}, and CO). On the other hand, due to the simplicity of the LJ model used, dramatic deviations between simulation and experimental data were observed, especially in the two-phase region, for more complex molecules such as CO{sub 2} and C{sub 2} H{sub 6}.« less

Evaluation of Ochratoxin Recognition by Peptides Using Explicit Solvent Molecular Dynamics

PubMed Central

Thyparambil, Aby A.; Bazin, Ingrid; Guiseppi-Elie, Anthony

2017-01-01

Biosensing platforms based on peptide recognition provide a cost-effective and stable alternative to antibody-based capture and discrimination of ochratoxin-A (OTA) vs. ochratoxin-B (OTB) in monitoring bioassays. Attempts to engineer peptides with improved recognition efficacy require thorough structural and thermodynamic characterization of the binding-competent conformations. Classical molecular dynamics (MD) approaches alone do not provide a thorough assessment of a peptide’s recognition efficacy. In this study, in-solution binding properties of four different peptides, a hexamer (SNLHPK), an octamer (CSIVEDGK), NFO4 (VYMNRKYYKCCK), and a 13-mer (GPAGIDGPAGIRC), which were previously generated for OTA-specific recognition, were evaluated using an advanced MD simulation approach involving accelerated configurational search and predictive modeling. Peptide configurations relevant to ochratoxin binding were initially generated using biased exchange metadynamics and the dynamic properties associated with the in-solution peptide–ochratoxin binding were derived from Markov State Models. Among the various peptides, NFO4 shows superior in-solution OTA sensing and also shows superior selectivity for OTA vs. OTB due to the lower penalty associated with solvating its bound complex. Advanced MD approaches provide structural and energetic insights critical to the hapten-specific recognition to aid the engineering of peptides with better sensing efficacies. PMID:28505090

Modeling Complex Workflow in Molecular Diagnostics

PubMed Central

Gomah, Mohamed E.; Turley, James P.; Lu, Huimin; Jones, Dan

2010-01-01

One of the hurdles to achieving personalized medicine has been implementing the laboratory processes for performing and reporting complex molecular tests. The rapidly changing test rosters and complex analysis platforms in molecular diagnostics have meant that many clinical laboratories still use labor-intensive manual processing and testing without the level of automation seen in high-volume chemistry and hematology testing. We provide here a discussion of design requirements and the results of implementation of a suite of lab management tools that incorporate the many elements required for use of molecular diagnostics in personalized medicine, particularly in cancer. These applications provide the functionality required for sample accessioning and tracking, material generation, and testing that are particular to the evolving needs of individualized molecular diagnostics. On implementation, the applications described here resulted in improvements in the turn-around time for reporting of more complex molecular test sets, and significant changes in the workflow. Therefore, careful mapping of workflow can permit design of software applications that simplify even the complex demands of specialized molecular testing. By incorporating design features for order review, software tools can permit a more personalized approach to sample handling and test selection without compromising efficiency. PMID:20007844

Assessment of the Simulated Molecular Composition with the GECKO-A Modeling Tool Using Chamber Observations for α-Pinene.

NASA Astrophysics Data System (ADS)

Aumont, B.; Camredon, M.; Isaacman-VanWertz, G. A.; Karam, C.; Valorso, R.; Madronich, S.; Kroll, J. H.

2016-12-01

Gas phase oxidation of VOC is a gradual process leading to the formation of multifunctional organic compounds, i.e., typically species with higher oxidation state, high water solubility and low volatility. These species contribute to the formation of secondary organic aerosols (SOA) viamultiphase processes involving a myriad of organic species that evolve through thousands of reactions and gas/particle mass exchanges. Explicit chemical mechanisms reflect the understanding of these multigenerational oxidation steps. These mechanisms rely directly on elementary reactions to describe the chemical evolution and track the identity of organic carbon through various phases down to ultimate oxidation products. The development, assessment and improvement of such explicit schemes is a key issue, as major uncertainties remain on the chemical pathways involved during atmospheric oxidation of organic matter. An array of mass spectrometric techniques (CIMS, PTRMS, AMS) was recently used to track the composition of organic species during α-pinene oxidation in the MIT environmental chamber, providing an experimental database to evaluate and improve explicit mechanisms. In this study, the GECKO-A tool (Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere) is used to generate fully explicit oxidation schemes for α-pinene multiphase oxidation simulating the MIT experiment. The ability of the GECKO-A chemical scheme to explain the organic molecular composition in the gas and the condensed phases is explored. First results of this model/observation comparison at the molecular level will be presented.

Using open source computational tools for predicting human metabolic stability and additional absorption, distribution, metabolism, excretion, and toxicity properties.

PubMed

Gupta, Rishi R; Gifford, Eric M; Liston, Ted; Waller, Chris L; Hohman, Moses; Bunin, Barry A; Ekins, Sean

2010-11-01

Ligand-based computational models could be more readily shared between researchers and organizations if they were generated with open source molecular descriptors [e.g., chemistry development kit (CDK)] and modeling algorithms, because this would negate the requirement for proprietary commercial software. We initially evaluated open source descriptors and model building algorithms using a training set of approximately 50,000 molecules and a test set of approximately 25,000 molecules with human liver microsomal metabolic stability data. A C5.0 decision tree model demonstrated that CDK descriptors together with a set of Smiles Arbitrary Target Specification (SMARTS) keys had good statistics [κ = 0.43, sensitivity = 0.57, specificity = 0.91, and positive predicted value (PPV) = 0.64], equivalent to those of models built with commercial Molecular Operating Environment 2D (MOE2D) and the same set of SMARTS keys (κ = 0.43, sensitivity = 0.58, specificity = 0.91, and PPV = 0.63). Extending the dataset to ∼193,000 molecules and generating a continuous model using Cubist with a combination of CDK and SMARTS keys or MOE2D and SMARTS keys confirmed this observation. When the continuous predictions and actual values were binned to get a categorical score we observed a similar κ statistic (0.42). The same combination of descriptor set and modeling method was applied to passive permeability and P-glycoprotein efflux data with similar model testing statistics. In summary, open source tools demonstrated predictive results comparable to those of commercial software with attendant cost savings. We discuss the advantages and disadvantages of open source descriptors and the opportunity for their use as a tool for organizations to share data precompetitively, avoiding repetition and assisting drug discovery.

SMOG 2: A Versatile Software Package for Generating Structure-Based Models.

PubMed

Noel, Jeffrey K; Levi, Mariana; Raghunathan, Mohit; Lammert, Heiko; Hayes, Ryan L; Onuchic, José N; Whitford, Paul C

2016-03-01

Molecular dynamics simulations with coarse-grained or simplified Hamiltonians have proven to be an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Originally developed in the context of protein folding, structure-based models (SBMs) have since been extended to probe a diverse range of biomolecular processes, spanning from protein and RNA folding to functional transitions in molecular machines. The hallmark feature of a structure-based model is that part, or all, of the potential energy function is defined by a known structure. Within this general class of models, there exist many possible variations in resolution and energetic composition. SMOG 2 is a downloadable software package that reads user-designated structural information and user-defined energy definitions, in order to produce the files necessary to use SBMs with high performance molecular dynamics packages: GROMACS and NAMD. SMOG 2 is bundled with XML-formatted template files that define commonly used SBMs, and it can process template files that are altered according to the needs of each user. This computational infrastructure also allows for experimental or bioinformatics-derived restraints or novel structural features to be included, e.g. novel ligands, prosthetic groups and post-translational/transcriptional modifications. The code and user guide can be downloaded at http://smog-server.org/smog2.

Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation

PubMed Central

Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio

2012-01-01

Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurological, psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homology models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with molecular dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in molecular docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calculation. Robust correlation of computed and experimental Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands. PMID:22970199

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

PubMed

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

2016-01-01

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

Potential toxicity and affinity of triphenylmethane dye malachite green to lysozyme.

PubMed

Ding, Fei; Li, Xiu-Nan; Diao, Jian-Xiong; Sun, Ye; Zhang, Li; Ma, Lin; Yang, Xin-Ling; Zhang, Li; Sun, Ying

2012-04-01

Malachite green is a triphenylmethane dye that is used extensively in many industrial and aquacultural processes, generating environmental concerns and health problems to human being. In this contribution, the complexation between lysozyme and malachite green was verified by means of computer-aided molecular modeling, steady state and time-resolved fluorescence, and circular dichroism (CD) approaches. The precise binding patch of malachite green in lysozyme has been identified from molecular modeling and ANS displacement, Trp-62, Trp-63, and Trp-108 residues of lysozyme were earmarked to possess high-affinity for this dye, the principal forces in the lysozyme-malachite green adduct are hydrophobic and π-π interactions. Steady state fluorescence proclaimed the complex of malachite green with lysozyme yields quenching through static type, which substantiates time-resolved fluorescence measurements that lysozyme-malachite green conjugation formation has an affinity of 10(3)M(-1). Moreover, via molecular modeling and also CD data, we can safely arrive at a conclusion that the polypeptide chain of lysozyme partially destabilized upon complexation with malachite green. The data emerged here will help to further understand the toxicological action of malachite green in human body. Copyright © 2012 Elsevier Inc. All rights reserved.

A 3D visualization system for molecular structures

NASA Technical Reports Server (NTRS)

Green, Terry J.

1989-01-01

The properties of molecules derive in part from their structures. Because of the importance of understanding molecular structures various methodologies, ranging from first principles to empirical technique, were developed for computing the structure of molecules. For large molecules such as polymer model compounds, the structural information is difficult to comprehend by examining tabulated data. Therefore, a molecular graphics display system, called MOLDS, was developed to help interpret the data. MOLDS is a menu-driven program developed to run on the LADC SNS computer systems. This program can read a data file generated by the modeling programs or data can be entered using the keyboard. MOLDS has the following capabilities: draws the 3-D representation of a molecule using stick, ball and ball, or space filled model from Cartesian coordinates, draws different perspective views of the molecule; rotates the molecule on the X, Y, Z axis or about some arbitrary line in space, zooms in on a small area of the molecule in order to obtain a better view of a specific region; and makes hard copy representation of molecules on a graphic printer. In addition, MOLDS can be easily updated and readily adapted to run on most computer systems.

Molecular docking, 3D QSAR and dynamics simulation studies of imidazo-pyrrolopyridines as janus kinase 1 (JAK 1) inhibitors.

PubMed

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

2016-10-01

Janus kinase 1 (JAK 1) plays a critical role in initiating responses to cytokines by the JAK-signal transducer and activator of transcription (JAK-STAT). This controls survival, proliferation and differentiation of a variety of cells. Docking, 3D quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) studies were performed on a series of Imidazo-pyrrolopyridine derivatives reported as JAK 1 inhibitors. QSAR model was generated using 30 molecules in the training set; developed model showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of this model was determined using a test set of 13 molecules that gave acceptable predictive correlation (r 2 Pred ) values. Finally, molecular dynamics simulation was performed to validate docking results and MM/GBSA calculations. This facilitated us to compare binding free energies of cocrystal ligand and newly designed molecule R1. The good concordance between the docking results and CoMFA/CoMSIA contour maps afforded obliging clues for the rational modification of molecules to design more potent JAK 1 inhibitors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular property diagnostic suite (MPDS): Development of disease-specific open source web portals for drug discovery.

PubMed

Nagamani, S; Gaur, A S; Tanneeru, K; Muneeswaran, G; Madugula, S S; Consortium, Mpds; Druzhilovskiy, D; Poroikov, V V; Sastry, G N

2017-11-01

Molecular property diagnostic suite (MPDS) is a Galaxy-based open source drug discovery and development platform. MPDS web portals are designed for several diseases, such as tuberculosis, diabetes mellitus, and other metabolic disorders, specifically aimed to evaluate and estimate the drug-likeness of a given molecule. MPDS consists of three modules, namely data libraries, data processing, and data analysis tools which are configured and interconnected to assist drug discovery for specific diseases. The data library module encompasses vast information on chemical space, wherein the MPDS compound library comprises 110.31 million unique molecules generated from public domain databases. Every molecule is assigned with a unique ID and card, which provides complete information for the molecule. Some of the modules in the MPDS are specific to the diseases, while others are non-specific. Importantly, a suitably altered protocol can be effectively generated for another disease-specific MPDS web portal by modifying some of the modules. Thus, the MPDS suite of web portals shows great promise to emerge as disease-specific portals of great value, integrating chemoinformatics, bioinformatics, molecular modelling, and structure- and analogue-based drug discovery approaches.

Multiple e-pharmacophore modelling pooled with high-throughput virtual screening, docking and molecular dynamics simulations to discover potential inhibitors of Plasmodium falciparum lactate dehydrogenase (PfLDH).

PubMed

Saxena, Shalini; Durgam, Laxman; Guruprasad, Lalitha

2018-05-14

Development of new antimalarial drugs continues to be of huge importance because of the resistance of malarial parasite towards currently used drugs. Due to the reliance of parasite on glycolysis for energy generation, glycolytic enzymes have played important role as potential targets for the development of new drugs. Plasmodium falciparum lactate dehydrogenase (PfLDH) is a key enzyme for energy generation of malarial parasites and is considered to be a potential antimalarial target. Presently, there are nearly 15 crystal structures bound with inhibitors and substrate that are available in the protein data bank (PDB). In the present work, we attempted to consider multiple crystal structures with bound inhibitors showing affinity in the range of 1.4 × 10 2 -1.3 × 10 6  nM efficacy and optimized the pharmacophore based on the energy involved in binding termed as e-pharmacophore mapping. A high throughput virtual screening (HTVS) combined with molecular docking, ADME predictions and molecular dynamics simulation led to the identification of 20 potential compounds which could be further developed as novel inhibitors for PfLDH.

Temperature-accelerated molecular dynamics gives insights into globular conformations sampled in the free state of the AC catalytic domain.

PubMed

Selwa, Edithe; Huynh, Tru; Ciccotti, Giovanni; Maragliano, Luca; Malliavin, Thérèse E

2014-10-01

The catalytic domain of the adenyl cyclase (AC) toxin from Bordetella pertussis is activated by interaction with calmodulin (CaM), resulting in cAMP overproduction in the infected cell. In the X-ray crystallographic structure of the complex between AC and the C terminal lobe of CaM, the toxin displays a markedly elongated shape. As for the structure of the isolated protein, experimental results support the hypothesis that more globular conformations are sampled, but information at atomic resolution is still lacking. Here, we use temperature-accelerated molecular dynamics (TAMD) simulations to generate putative all-atom models of globular conformations sampled by CaM-free AC. As collective variables, we use centers of mass coordinates of groups of residues selected from the analysis of standard molecular dynamics (MD) simulations. Results show that TAMD allows extended conformational sampling and generates AC conformations that are more globular than in the complexed state. These structures are then refined via energy minimization and further unrestrained MD simulations to optimize inter-domain packing interactions, thus resulting in the identification of a set of hydrogen bonds present in the globular conformations. © 2014 Wiley Periodicals, Inc.

STOCK: Structure mapper and online coarse-graining kit for molecular simulations

DOE PAGES

Bevc, Staš; Junghans, Christoph; Praprotnik, Matej

2015-03-15

We present a web toolkit STructure mapper and Online Coarse-graining Kit for setting up coarse-grained molecular simulations. The kit consists of two tools: structure mapping and Boltzmann inversion tools. The aim of the first tool is to define a molecular mapping from high, e.g. all-atom, to low, i.e. coarse-grained, resolution. Using a graphical user interface it generates input files, which are compatible with standard coarse-graining packages, e.g. VOTCA and DL_CGMAP. Our second tool generates effective potentials for coarse-grained simulations preserving the structural properties, e.g. radial distribution functions, of the underlying higher resolution model. The required distribution functions can be providedmore » by any simulation package. Simulations are performed on a local machine and only the distributions are uploaded to the server. The applicability of the toolkit is validated by mapping atomistic pentane and polyalanine molecules to a coarse-grained representation. Effective potentials are derived for systems of TIP3P (transferable intermolecular potential 3 point) water molecules and salt solution. The presented coarse-graining web toolkit is available at http://stock.cmm.ki.si.« less

Control of mobility in molecular organic semiconductors by dendrimer generation

NASA Astrophysics Data System (ADS)

Lupton, J. M.; Samuel, I. D.; Beavington, R.; Frampton, M. J.; Burn, P. L.; Bässler, H.

2001-04-01

Conjugated dendrimers are of interest as novel materials for light-emitting diodes. They consist of a luminescent chromophore at the core with highly branched conjugated dendron sidegroups. In these materials, light emission occurs from the core and is independent of generation. The dendron branching controls the separation between the chromophores. We present here a family of conjugated dendrimers and investigate the effect of dendron branching on light emission and charge transport. We apply a number of transport measurement techniques to thin films of a conjugated dendrimer in a light-emitting diode configuration to determine the effect of chromophore spacing on charge transport. We find that the mobility is reduced by two orders of magnitude as the size of the molecule doubles with increased branching or dendrimer generation. The degree of branching allows a unique control of mobility by molecular structure. An increase in chromophore separation also results in a reduction of intermolecular interactions, which reduces the red emission tail in film photoluminescence. We find that the steady-state charge transport is well described by a simple device model incorporating the effect of generation, and use the materials to shed light on the interpretation of transient electroluminescence data. We demonstrate the significance of the ability to tune the mobility in bilayer devices, where a more balanced charge transport can be achieved.

Self-interrupted synthesis of sterically hindered aliphatic polyamide dendrimers

PubMed Central

Jishkariani, Davit; Timsina, Yam N.; Grama, Silvia; Gillani, Syeda S.; Divar, Masoumeh; Yadavalli, Srujana S.; Moussodia, Ralph-Olivier; Leowanawat, Pawaret; Berrios Camacho, Angely M.; Walter, Ricardo; Goulian, Mark; Klein, Michael L.; Percec, Virgil

2017-01-01

2,2-Bis(azidomethyl)propionic acid was prepared in four steps and 85% yield from the commercially available 2,2-bis(hydroxymethyl)propionic acid and used as the starting building block for the divergent, convergent, and double-stage convergent–divergent iterative methods for the synthesis of dendrimers and dendrons containing ethylenediamine (EDA), piperazine (PPZ), and methyl 2,2-bis(aminomethyl)propionate (COOMe) cores. These cores have the same multiplicity but different conformations. A diversity of synthetic methods were used for the synthesis of dendrimers and dendrons. Regardless of the method used, a self-interruption of the synthesis was observed at generation 4 for the dendrimer with an EDA core and at generation 5 for the one with a PPZ core, whereas for the COOMe core, self-interruption was observed at generation 6 dendron, which is equivalent to generation 5 dendrimer. Molecular modeling and molecular-dynamics simulations demonstrated that the observed self-interruption is determined by the backfolding of the azide groups at the periphery of the dendrimer. The latter conformation inhibits completely the heterogeneous hydrogenation of the azide groups catalyzed by 10% Pd/carbon as well as homogeneous hydrogenation by the Staudinger method. These self-terminated polyamide dendrimers are enzymatically and hydrolytically stable and also exhibit antimicrobial activity. Thus, these nanoscale constructs open avenues for biomedical applications. PMID:28270599

Early induction of a prechondrogenic population allows efficient generation of stable chondrocytes from human induced pluripotent stem cells.

PubMed

Lee, Jieun; Taylor, Sarah E B; Smeriglio, Piera; Lai, Janice; Maloney, William J; Yang, Fan; Bhutani, Nidhi

2015-08-01

Regeneration of human cartilage is inherently inefficient; an abundant autologous source, such as human induced pluripotent stem cells (hiPSCs), is therefore attractive for engineering cartilage. We report a growth factor-based protocol for differentiating hiPSCs into articular-like chondrocytes (hiChondrocytes) within 2 weeks, with an overall efficiency >90%. The hiChondrocytes are stable and comparable to adult articular chondrocytes in global gene expression, extracellular matrix production, and ability to generate cartilage tissue in vitro and in immune-deficient mice. Molecular characterization identified an early SRY (sex-determining region Y) box (Sox)9(low) cluster of differentiation (CD)44(low)CD140(low) prechondrogenic population during hiPSC differentiation. In addition, 2 distinct Sox9-regulated gene networks were identified in the Sox9(low) and Sox9(high) populations providing novel molecular insights into chondrogenic fate commitment and differentiation. Our findings present a favorable method for generating hiPSC-derived articular-like chondrocytes. The hiChondrocytes are an attractive cell source for cartilage engineering because of their abundance, autologous nature, and potential to generate articular-like cartilage rather than fibrocartilage. In addition, hiChondrocytes can be excellent tools for modeling human musculoskeletal diseases in a dish and for rapid drug screening. © FASEB.

A hybrid model describing ion induced kinetic electron emission

NASA Astrophysics Data System (ADS)

Hanke, S.; Duvenbeck, A.; Heuser, C.; Weidtmann, B.; Wucher, A.

2015-06-01

We present a model to describe the kinetic internal and external electron emission from an ion bombarded metal target. The model is based upon a molecular dynamics treatment of the nuclear degree of freedom, the electronic system is assumed as a quasi-free electron gas characterized by its Fermi energy, electron temperature and a characteristic attenuation length. In a series of previous works we have employed this model, which includes the local kinetic excitation as well as the rapid spread of the generated excitation energy, in order to calculate internal and external electron emission yields within the framework of a Richardson-Dushman-like thermionic emission model. However, this kind of treatment turned out to fail in the realistic prediction of experimentally measured internal electron yields mainly due to the restriction of the treatment of electronic transport to a diffusive manner. Here, we propose a slightly modified approach additionally incorporating the contribution of hot electrons which are generated in the bulk material and undergo ballistic transport towards the emitting interface.

Mathematical modeling of tetrahydroimidazole benzodiazepine-1-one derivatives as an anti HIV agent

NASA Astrophysics Data System (ADS)

Ojha, Lokendra Kumar

2017-07-01

The goal of the present work is the study of drug receptor interaction via QSAR (Quantitative Structure-Activity Relationship) analysis for 89 set of TIBO (Tetrahydroimidazole Benzodiazepine-1-one) derivatives. MLR (Multiple Linear Regression) method is utilized to generate predictive models of quantitative structure-activity relationships between a set of molecular descriptors and biological activity (IC50). The best QSAR model was selected having a correlation coefficient (r) of 0.9299 and Standard Error of Estimation (SEE) of 0.5022, Fisher Ratio (F) of 159.822 and Quality factor (Q) of 1.852. This model is statistically significant and strongly favours the substitution of sulphur atom, IS i.e. indicator parameter for -Z position of the TIBO derivatives. Two other parameter logP (octanol-water partition coefficient) and SAG (Surface Area Grid) also played a vital role in the generation of best QSAR model. All three descriptor shows very good stability towards data variation in leave-one-out (LOO).

Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.

PubMed

Murrell, Daniel S; Cortes-Ciriano, Isidro; van Westen, Gerard J P; Stott, Ian P; Bender, Andreas; Malliavin, Thérèse E; Glen, Robert C

2015-01-01

In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2). Overall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.Graphical abstractFrom compounds and data to models: a complete model building workflow in one package.

Polydopamine and eumelanin molecular structures investigated with ab initio calculations† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6sc04692d Click here for additional data file.

PubMed Central

Chen, Chun-Teh; Martin-Martinez, Francisco J.; Jung, Gang Seob

2017-01-01

A set of computational methods that contains a brute-force algorithmic generation of chemical isomers, molecular dynamics (MD) simulations, and density functional theory (DFT) calculations is reported and applied to investigate nearly 3000 probable molecular structures of polydopamine (PDA) and eumelanin. All probable early-polymerized 5,6-dihydroxyindole (DHI) oligomers, ranging from dimers to tetramers, have been systematically analyzed to find the most stable geometry connections as well as to propose a set of molecular models that represents the chemically diverse nature of PDA and eumelanin. Our results indicate that more planar oligomers have a tendency to be more stable. This finding is in good agreement with recent experimental observations, which suggested that PDA and eumelanin are composed of nearly planar oligomers that appear to be stacked together via π–π interactions to form graphite-like layered aggregates. We also show that there is a group of tetramers notably more stable than the others, implying that even though there is an inherent chemical diversity in PDA and eumelanin, the molecular structures of the majority of the species are quite repetitive. Our results also suggest that larger oligomers are less likely to form. This observation is also consistent with experimental measurements, supporting the existence of small oligomers instead of large polymers as main components of PDA and eumelanin. In summary, this work brings an insight into the controversial structure of PDA and eumelanin, explaining some of the most important structural features, and providing a set of molecular models for more accurate modeling of eumelanin-like materials. PMID:28451292

Integrative analysis of genes and miRNA alterations in human embryonic stem cells-derived neural cells after exposure to silver nanoparticles

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

Oh, Jung-Hwa; Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113; Son, Mi-Young

Given the rapid growth of engineered and customer products made of silver nanoparticles (Ag NPs), understanding their biological and toxicological effects on humans is critically important. The molecular developmental neurotoxic effects associated with exposure to Ag NPs were analyzed at the physiological and molecular levels, using an alternative cell model: human embryonic stem cell (hESC)-derived neural stem/progenitor cells (NPCs). In this study, the cytotoxic effects of Ag NPs (10–200 μg/ml) were examined in these hESC-derived NPCs, which have a capacity for neurogenesis in vitro, at 6 and 24 h. The results showed that Ag NPs evoked significant toxicity in hESC-derivedmore » NPCs at 24 h in a dose-dependent manner. In addition, Ag NPs induced cell cycle arrest and apoptosis following a significant increase in oxidative stress in these cells. To further clarify the molecular mechanisms of the toxicological effects of Ag NPs at the transcriptional and post-transcriptional levels, the global expression profiles of genes and miRNAs were analyzed in hESC-derived NPCs after Ag NP exposure. The results showed that Ag NPs induced oxidative stress and dysfunctional neurogenesis at the molecular level in hESC-derived NPCs. Based on this hESC-derived neural cell model, these findings have increased our understanding of the molecular events underlying developmental neurotoxicity induced by Ag NPs in humans. - Highlights: • This system served as a suitable model for developmental neurotoxicity testing. • Ag NPs induce the apoptosis in human neural cells by ROS generation. • Genes for development of neurons were dysregulated in response to Ag NPs. • Molecular events during early developmental neurotoxicity were proposed.« less

Mathematical Description of Dendrimer Structure

NASA Technical Reports Server (NTRS)

Majoros, Istvan J.; Mehta, Chandan B.; Baker, James R., Jr.

2004-01-01

Characteristics of starburst dendrimers can be easily attributed to the multiplicity of the monomers used to synthesize them. The molecular weight, degree of polymerization, number of terminal groups and branch points for each generation of a dendrimer can be calculated using mathematical formulas incorporating these variables. Mathematical models for the calculation of degree of polymerization, molecular weight, and number of terminal groups and branching groups previously published were revised and elaborated on for poly(amidoamine) (PAMAM) dendrimers, and introduced for poly(propyleneimine) (POPAM) dendrimers and the novel POPAM-PAMAM hybrid, which we call the POMAM dendrimer. Experimental verification of the relationship between theoretical and actual structure for the PAMAM dendrimer was also established.

Molecular dynamics simulations revealed structural differences among WRKY domain-DNA interaction in barley (Hordeum vulgare).

PubMed

Pandey, Bharati; Grover, Abhinav; Sharma, Pradeep

2018-02-12

The WRKY transcription factors are a class of DNA-binding proteins involved in diverse plant processes play critical roles in response to abiotic and biotic stresses. Genome-wide divergence analysis of WRKY gene family in Hordeum vulgare provided a framework for molecular evolution and functional roles. So far, the crystal structure of WRKY from barley has not been resolved; moreover, knowledge of the three-dimensional structure of WRKY domain is pre-requisites for exploring the protein-DNA recognition mechanisms. Homology modelling based approach was used to generate structures for WRKY DNA binding domain (DBD) and its variants using AtWRKY1 as a template. Finally, the stability and conformational changes of the generated model in unbound and bound form was examined through atomistic molecular dynamics (MD) simulations for 100 ns time period. In this study, we investigated the comparative binding pattern of WRKY domain and its variants with W-box cis-regulatory element using molecular docking and dynamics (MD) simulations assays. The atomic insight into WRKY domain exhibited significant variation in the intermolecular hydrogen bonding pattern, leading to the structural anomalies in the variant type and differences in the DNA-binding specificities. Based on the MD analysis, residual contribution and interaction contour, wild-type WRKY (HvWRKY46) were found to interact with DNA through highly conserved heptapeptide in the pre- and post-MD simulated complexes, whereas heptapeptide interaction with DNA was missing in variants (I and II) in post-MD complexes. Consequently, through principal component analysis, wild-type WRKY was also found to be more stable by obscuring a reduced conformational space than the variant I (HvWRKY34). Lastly, high binding free energy for wild-type and variant II allowed us to conclude that wild-type WRKY-DNA complex was more stable relative to variants I. The results of our study revealed complete dynamic and structural information about WRKY domain-DNA interactions. However, no structure base information reported to date for WRKY variants and their mechanism of interaction with DNA. Our findings highlighted the importance of selecting a sequence to generate newer transgenic plants that would be increasingly tolerance to stress conditions.

Chlorite dismutases – a heme enzyme family for use in bioremediation and generation of molecular oxygen

PubMed Central

Hofbauer, Stefan; Schaffner, Irene; Furtmüller, Paul G; Obinger, Christian

2014-01-01

Chlorite is a serious environmental concern, as rising concentrations of this harmful anthropogenic compound have been detected in groundwater, drinking water, and soil. Chlorite dismutases (Clds) are therefore important molecules in bioremediation as Clds catalyze the degradation of chlorite to chloride and molecular oxygen. Clds are heme b-containing oxidoreductases present in numerous bacterial and archaeal phyla. This review presents the phylogeny of functional Clds and Cld-like proteins, and demonstrates the close relationship of this novel enzyme family to the recently discovered dye-decolorizing peroxidases. The available X-ray structures, biophysical and enzymatic properties, as well as a proposed reaction mechanism, are presented and critically discussed. Open questions about structure-function relationships are addressed, including the nature of the catalytically relevant redox and reaction intermediates and the mechanism of inactivation of Clds during turnover. Based on analysis of currently available data, chlorite dismutase from “Candidatus Nitrospira defluvii” is suggested as a model Cld for future application in biotechnology and bioremediation. Additionally, Clds can be used in various applications as local generators of molecular oxygen, a reactivity already exploited by microbes that must perform aerobic metabolic pathways in the absence of molecular oxygen. For biotechnologists in the field of chemical engineering and bioremediation, this review provides the biochemical and biophysical background of the Cld enzyme family as well as critically assesses Cld's technological potential. PMID:24519858

Molecular interactions and residues involved in force generation in the T4 viral DNA packaging motor.

PubMed

Migliori, Amy D; Smith, Douglas E; Arya, Gaurav

2014-12-12

Many viruses utilize molecular motors to package their genomes into preformed capsids. A striking feature of these motors is their ability to generate large forces to drive DNA translocation against entropic, electrostatic, and bending forces resisting DNA confinement. A model based on recently resolved structures of the bacteriophage T4 motor protein gp17 suggests that this motor generates large forces by undergoing a conformational change from an extended to a compact state. This transition is proposed to be driven by electrostatic interactions between complementarily charged residues across the interface between the N- and C-terminal domains of gp17. Here we use atomistic molecular dynamics simulations to investigate in detail the molecular interactions and residues involved in such a compaction transition of gp17. We find that although electrostatic interactions between charged residues contribute significantly to the overall free energy change of compaction, interactions mediated by the uncharged residues are equally if not more important. We identify five charged residues and six uncharged residues at the interface that play a dominant role in the compaction transition and also reveal salt bridging, van der Waals, and solvent hydrogen-bonding interactions mediated by these residues in stabilizing the compact form of gp17. The formation of a salt bridge between Glu309 and Arg494 is found to be particularly crucial, consistent with experiments showing complete abrogation in packaging upon Glu309Lys mutation. The computed contributions of several other residues are also found to correlate well with single-molecule measurements of impairments in DNA translocation activity caused by site-directed mutations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Full genome survey and dynamics of gene expression in the greater amberjack Seriola dumerili.

PubMed

Sarropoulou, Elena; Sundaram, Arvind Y M; Kaitetzidou, Elisavet; Kotoulas, Georgios; Gilfillan, Gregor D; Papandroulakis, Nikos; Mylonas, Constantinos C; Magoulas, Antonios

2017-12-01

Teleosts of the genus Seriola, commonly known as amberjacks, are of high commercial value in international markets due to their flesh quality and worldwide distribution. The Seriola species of interest to Mediterranean aquaculture is the greater amberjack (Seriola dumerili). This species holds great potential for the aquaculture industry, but in captivity, reproduction has proved to be challenging, and observed growth dysfunction hinders their domestication. Insights into molecular mechanisms may contribute to a better understanding of traits like growth and sex, but investigations to unravel the molecular background of amberjacks have begun only recently. Illumina HiSeq sequencing generated a high-coverage greater amberjack genome sequence comprising 45 909 scaffolds. Comparative mapping to the Japanese yellowtail (Seriola quinqueriadiata) and to the model species medaka (Oryzias latipes) allowed the generation of in silico groups. Additional gonad transcriptome sequencing identified sex-biased transcripts, including known sex-determining and differentiation genes. Investigation of the muscle transcriptome of slow-growing individuals showed that transcripts involved in oxygen and gas transport were differentially expressed compared with fast/normal-growing individuals. On the other hand, transcripts involved in muscle functions were found to be enriched in fast/normal-growing individuals. The present study provides the first insights into the molecular background of male and female amberjacks and of fast- and slow-growing fish. Therefore, valuable molecular resources have been generated in the form of a first draft genome and a reference transcriptome. Sex-biased genes, which may also have roles in sex determination or differentiation, and genes that may be responsible for slow growth are suggested. © The Authors 2017. Published by Oxford University Press.

A coupled two-dimensional main chain torsional potential for protein dynamics: generation and implementation.

PubMed

Li, Yongxiu; Gao, Ya; Zhang, Xuqiang; Wang, Xingyu; Mou, Lirong; Duan, Lili; He, Xiao; Mei, Ye; Zhang, John Z H

2013-09-01

Main chain torsions of alanine dipeptide are parameterized into coupled 2-dimensional Fourier expansions based on quantum mechanical (QM) calculations at M06 2X/aug-cc-pvtz//HF/6-31G** level. Solvation effect is considered by employing polarizable continuum model. Utilization of the M06 2X functional leads to precise potential energy surface that is comparable to or even better than MP2 level, but with much less computational demand. Parameterization of the 2D expansions is against the full main chain torsion space instead of just a few low energy conformations. This procedure is similar to that for the development of AMBER03 force field, except unique weighting factor was assigned to all the grid points. To avoid inconsistency between quantum mechanical calculations and molecular modeling, the model peptide is further optimized at molecular mechanics level with main chain dihedral angles fixed before the calculation of the conformational energy on molecular mechanical level at each grid point, during which generalized Born model is employed. Difference in solvation models at quantum mechanics and molecular mechanics levels makes this parameterization procedure less straightforward. All force field parameters other than main chain torsions are taken from existing AMBER force field. With this new main chain torsion terms, we have studied the main chain dihedral distributions of ALA dipeptide and pentapeptide in aqueous solution. The results demonstrate that 2D main chain torsion is effective in delineating the energy variation associated with rotations along main chain dihedrals. This work is an implication for the necessity of more accurate description of main chain torsions in the future development of ab initio force field and it also raises a challenge to the development of quantum mechanical methods, especially the quantum mechanical solvation models.

Effect of fuel concentration on cargo transport by a team of Kinesin motors

NASA Astrophysics Data System (ADS)

Takshak, Anjneya; Mishra, Nirvantosh; Kulkarni, Aditi; Kunwar, Ambarish

2017-02-01

Eukaryotic cells employ specialized proteins called molecular motors for transporting organelles and vesicles from one location to another in a regulated and directed manner. These molecular motors often work collectively in a team while transporting cargos. Molecular motors use cytoplasmic ATP as fuel, which is hydrolyzed to generate mechanical force. While the effect of ATP concentration on cargo transport by single Kinesin motor function is well understood, it is still unexplored, both theoretically and experimentally, how ATP concentration would affect cargo transport by a team of Kinesin motors. For instance, how does fuel concentration affect the travel distances and travel velocities of cargo? How cooperativity of Kinesin motors engaged on a cargo is affected by ATP concentration? To answer these questions, here we develop mechano-chemical models of cargo transport by a team of Kinesin motors. To develop these models we use experimentally-constrained mechano-chemical model of a single Kinesin motor as well as earlier developed mean-field and stochastic models of load sharing for cargo transport. Thus, our new models for cargo transport by a team of Kinesin motors include fuel concentration explicitly, which was not considered in earlier models. We make several interesting predictions which can be tested experimentally. For instance, the travel distances of cargos are very large at limited ATP concentrations in spite of very small travel velocity. Velocities of cargos driven by multiple Kinesin have a Michaelis-Menten dependence on ATP concentration. Similarly, cooperativity among the engaged Kinesin motors on the cargo shows a Michaelis-Menten type dependence, which attains a maximum value near physiological ATP concentrations. Our new results can be potentially useful in controlling artificial nano-molecular shuttles precisely for targeted delivery in various nano-technological applications.

Robust generation of Fourier-synthesized laser fields and their estimation of the optical phase by using quantum control of molecular tunneling ionization

NASA Astrophysics Data System (ADS)

Yoshida, Tsuyoshi; Saito, Naoaki; Ohmura, Hideki

2018-03-01

Intense (5.0 × 1012 W cm-2) nanosecond Fourier-synthesized laser fields consisting of fundamental, second-, third-, and fourth-harmonic light generated by an interferometer-free Fourier-synthesized laser field generator induce orientation-selective ionization based on directionally asymmetric molecular tunneling ionization (TI). The laser field generator ensures adjustment-free operation, high stability, and high reproducibility. Phase-sensitive, orientation-selective molecular TI provides a simple way to estimate the relative phase differences between the fundamental light and each harmonic by data-fitting analysis. This application of Fourier-synthesized laser fields will facilitate not only lightwave engineering but also the control of matter.

A comparative modeling and molecular docking study on Mycobacterium tuberculosis targets involved in peptidoglycan biosynthesis.

PubMed

Fakhar, Zeynab; Naiker, Suhashni; Alves, Claudio N; Govender, Thavendran; Maguire, Glenn E M; Lameira, Jeronimo; Lamichhane, Gyanu; Kruger, Hendrik G; Honarparvar, Bahareh

2016-11-01

An alarming rise of multidrug-resistant Mycobacterium tuberculosis strains and the continuous high global morbidity of tuberculosis have reinvigorated the need to identify novel targets to combat the disease. The enzymes that catalyze the biosynthesis of peptidoglycan in M. tuberculosis are essential and noteworthy therapeutic targets. In this study, the biochemical function and homology modeling of MurI, MurG, MraY, DapE, DapA, Alr, and Ddl enzymes of the CDC1551 M. tuberculosis strain involved in the biosynthesis of peptidoglycan cell wall are reported. Generation of the 3D structures was achieved with Modeller 9.13. To assess the structural quality of the obtained homology modeled targets, the models were validated using PROCHECK, PDBsum, QMEAN, and ERRAT scores. Molecular dynamics simulations were performed to calculate root mean square deviation (RMSD) and radius of gyration (Rg) of MurI and MurG target proteins and their corresponding templates. For further model validation, RMSD and Rg for selected targets/templates were investigated to compare the close proximity of their dynamic behavior in terms of protein stability and average distances. To identify the potential binding mode required for molecular docking, binding site information of all modeled targets was obtained using two prediction algorithms. A docking study was performed for MurI to determine the potential mode of interaction between the inhibitor and the active site residues. This study presents the first accounts of the 3D structural information for the selected M. tuberculosis targets involved in peptidoglycan biosynthesis.

Geometry-dependent distributed polarizability models for the water molecule

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

Loboda, Oleksandr; Ingrosso, Francesca; Ruiz-López, Manuel F.

2016-01-21

Geometry-dependent distributed polarizability models have been constructed by fits to ab initio calculations at the coupled cluster level of theory with up to noniterative triple excitations in an augmented triple-zeta quality basis set for the water molecule in the field of a point charge. The investigated models include (i) charge-flow polarizabilities between chemically bonded atoms, (ii) isotropic or anisotropic dipolar polarizabilities on oxygen atom or on all atoms, and (iii) combinations of models (i) and (ii). For each model, the polarizability parameters have been optimized to reproduce the induction energy of a water molecule polarized by a point charge successivelymore » occupying a grid of points surrounding the molecule. The quality of the models is ascertained by examining their ability to reproduce these induction energies as well as the molecular dipolar and quadrupolar polarizabilities. The geometry dependence of the distributed polarizability models has been explored by changing bond lengths and HOH angle to generate 125 molecular structures (reduced to 75 symmetry-unique ones). For each considered model, the distributed polarizability components have been fitted as a function of the geometry by a Taylor expansion in monomer coordinate displacements up to the sum of powers equal to 4.« less

Field-enhanced route to generating anti-Frenkel pairs in HfO2

NASA Astrophysics Data System (ADS)

Schie, Marcel; Menzel, Stephan; Robertson, John; Waser, Rainer; De Souza, Roger A.

2018-03-01

The generation of anti-Frenkel pairs (oxygen vacancies and oxygen interstitials) in monoclinic and cubic HfO2 under an applied electric field is examined. A thermodynamic model is used to derive an expression for the critical field strength required to generate an anti-Frenkel pair. The critical field strength of EaFcr˜101GVm-1 obtained for HfO2 exceeds substantially the field strengths routinely employed in the forming and switching operations of resistive switching HfO2 devices, suggesting that field-enhanced defect generation is negligible. Atomistic simulations with molecular static (MS) and molecular dynamic (MD) approaches support this finding. The MS calculations indicated a high formation energy of Δ EaF≈8 eV for the infinitely separated anti-Frenkel pair, and only a decrease to Δ EaF≈6 eV for the adjacent anti-Frenkel pair. The MD simulations showed no defect generation in either phase for E <3 GVm-1 , and only sporadic defect generation in the monoclinic phase (at E =3 GVm-1 ) with fast (trec<4 ps ) recombination. At even higher E but below EaFcr both monoclinic and cubic structures became unstable as a result of field-induced deformation of the ionic potential wells. Further MD investigations starting with preexisting anti-Frenkel pairs revealed recombination of all pairs within trec<1 ps , even for the case of neutral vacancies and charged interstitials, for which formally there is no electrostatic attraction between the defects. In conclusion, we find no physically reasonable route to generating point-defects in HfO2 by an applied field.

Femtosecond two-photon photoassociation of hot magnesium atoms: A quantum dynamical study using thermal random phase wavefunctions

NASA Astrophysics Data System (ADS)

Amaran, Saieswari; Kosloff, Ronnie; Tomza, Michał; Skomorowski, Wojciech; Pawłowski, Filip; Moszynski, Robert; Rybak, Leonid; Levin, Liat; Amitay, Zohar; Berglund, J. Martin; Reich, Daniel M.; Koch, Christiane P.

2013-10-01

Two-photon photoassociation of hot magnesium atoms by femtosecond laser pulses, creating electronically excited magnesium dimer molecules, is studied from first principles, combining ab initio quantum chemistry and molecular quantum dynamics. This theoretical framework allows for rationalizing the generation of molecular rovibrational coherence from thermally hot atoms [L. Rybak, S. Amaran, L. Levin, M. Tomza, R. Moszynski, R. Kosloff, C. P. Koch, and Z. Amitay, Phys. Rev. Lett. 107, 273001 (2011)]. Random phase thermal wavefunctions are employed to model the thermal ensemble of hot colliding atoms. Comparing two different choices of basis functions, random phase wavefunctions built from eigenstates are found to have the fastest convergence for the photoassociation yield. The interaction of the colliding atoms with a femtosecond laser pulse is modeled non-perturbatively to account for strong-field effects.

Unified model for singlet fission within a non-conjugated covalent pentacene dimer

NASA Astrophysics Data System (ADS)

Basel, Bettina S.; Zirzlmeier, Johannes; Hetzer, Constantin; Phelan, Brian T.; Krzyaniak, Matthew D.; Reddy, S. Rajagopala; Coto, Pedro B.; Horwitz, Noah E.; Young, Ryan M.; White, Fraser J.; Hampel, Frank; Clark, Timothy; Thoss, Michael; Tykwinski, Rik R.; Wasielewski, Michael R.; Guldi, Dirk M.

2017-05-01

When molecular dimers, crystalline films or molecular aggregates absorb a photon to produce a singlet exciton, spin-allowed singlet fission may produce two triplet excitons that can be used to generate two electron-hole pairs, leading to a predicted ~50% enhancement in maximum solar cell performance. The singlet fission mechanism is still not well understood. Here we report on the use of time-resolved optical and electron paramagnetic resonance spectroscopy to probe singlet fission in a pentacene dimer linked by a non-conjugated spacer. We observe the key intermediates in the singlet fission process, including the formation and decay of a quintet state that precedes formation of the pentacene triplet excitons. Using these combined data, we develop a single kinetic model that describes the data over seven temporal orders of magnitude both at room and cryogenic temperatures.

Unified model for singlet fission within a non-conjugated covalent pentacene dimer.

PubMed

Basel, Bettina S; Zirzlmeier, Johannes; Hetzer, Constantin; Phelan, Brian T; Krzyaniak, Matthew D; Reddy, S Rajagopala; Coto, Pedro B; Horwitz, Noah E; Young, Ryan M; White, Fraser J; Hampel, Frank; Clark, Timothy; Thoss, Michael; Tykwinski, Rik R; Wasielewski, Michael R; Guldi, Dirk M

2017-05-18

When molecular dimers, crystalline films or molecular aggregates absorb a photon to produce a singlet exciton, spin-allowed singlet fission may produce two triplet excitons that can be used to generate two electron-hole pairs, leading to a predicted ∼50% enhancement in maximum solar cell performance. The singlet fission mechanism is still not well understood. Here we report on the use of time-resolved optical and electron paramagnetic resonance spectroscopy to probe singlet fission in a pentacene dimer linked by a non-conjugated spacer. We observe the key intermediates in the singlet fission process, including the formation and decay of a quintet state that precedes formation of the pentacene triplet excitons. Using these combined data, we develop a single kinetic model that describes the data over seven temporal orders of magnitude both at room and cryogenic temperatures.

Light-powered micromotor driven by geometry-assisted, asymmetric photon-heating and subsequent gas convection

NASA Astrophysics Data System (ADS)

Han, Li-Hsin; Wu, Shaomin; Condit, J. Christopher; Kemp, Nate J.; Milner, Thomas E.; Feldman, Marc D.; Chen, Shaochen

2010-05-01

We report on the design, fabrication, and analysis of a light-driven micromotor. The micromotor was created from a nanoporous polymer with close-packed gold nanoparticles which generate heat by absorbing light. The blades of the micromotor were curved, forming convex and concave sides. Upon lateral irradiation, by geometric effect the convex side transfers more photon-generated heat to the surrounding gas molecules, causing a convective motion of gas and leading to the rotation of the micromotor. The light-driven motions of gas molecules were analyzed using molecular dynamics modeling.

Alleles versus mutations: Understanding the evolution of genetic architecture requires a molecular perspective on allelic origins.

PubMed

Remington, David L

2015-12-01

Perspectives on the role of large-effect quantitative trait loci (QTL) in the evolution of complex traits have shifted back and forth over the past few decades. Different sets of studies have produced contradictory insights on the evolution of genetic architecture. I argue that much of the confusion results from a failure to distinguish mutational and allelic effects, a limitation of using the Fisherian model of adaptive evolution as the lens through which the evolution of adaptive variation is examined. A molecular-based perspective reveals that allelic differences can involve the cumulative effects of many mutations plus intragenic recombination, a model that is supported by extensive empirical evidence. I discuss how different selection regimes could produce very different architectures of allelic effects under a molecular-based model, which may explain conflicting insights on genetic architecture from studies of variation within populations versus between divergently selected populations. I address shortcomings of genome-wide association study (GWAS) practices in light of more suitable models of allelic evolution, and suggest alternate GWAS strategies to generate more valid inferences about genetic architecture. Finally, I discuss how adopting more suitable models of allelic evolution could help redirect research on complex trait evolution toward addressing more meaningful questions in evolutionary biology. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Molecular docking and 3D-QSAR studies on triazolinone and pyridazinone, non-nucleoside inhibitor of HIV-1 reverse transcriptase.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2010-06-01

Nonnucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors of the HIV-1 reverse transcriptase. Recently a series of Triazolinone and Pyridazinone were reported as potent inhibitors of HIV-1 wild type reverse transcriptase. In the present study, docking and 3D quantitative structure activity relationship (3D QSAR) studies involving comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 31 molecules. Ligands were built and minimized using Tripos force field and applying Gasteiger-Hückel charges. These ligands were docked into protein active site using GLIDE 4.0. The docked poses were analyzed; the best docked poses were selected and aligned. CoMFA and CoMSIA fields were calculated using SYBYL6.9. The molecules were divided into training set and test set, a PLS analysis was performed and QSAR models were generated. The model showed good statistical reliability which is evident from the r2 nv, q2 loo and r2 pred values. The CoMFA model provides the most significant correlation of steric and electrostatic fields with biological activities. The CoMSIA model provides a correlation of steric, electrostatic, acceptor and hydrophobic fields with biological activities. The information rendered by 3D QSAR model initiated us to optimize the lead and design new potential inhibitors.

A Multiscale Model for the Quasi-Static Thermo-Plastic Behavior of Highly Cross-Linked Glassy Polymers

DOE PAGES

Vu-Bac, N.; Bessa, M. A.; Rabczuk, Timon; ...

2015-09-10

In this paper, we present experimentally validated molecular dynamics predictions of the quasi- static yield and post-yield behavior for a highly cross-linked epoxy polymer under gen- eral stress states and for different temperatures. In addition, a hierarchical multiscale model is presented where the nano-scale simulations obtained from molecular dynamics were homogenized to a continuum thermoplastic constitutive model for the epoxy that can be used to describe the macroscopic behavior of the material. Three major conclusions were achieved: (1) the yield surfaces generated from the nano-scale model for different temperatures agree well with the paraboloid yield crite- rion, supporting previous macroscopicmore » experimental observations; (2) rescaling of the entire yield surfaces to the quasi-static case is possible by considering Argon’s theoretical predictions for pure compression of the polymer at absolute zero temperature; (3) nano- scale simulations can be used for an experimentally-free calibration of macroscopic con- tinuum models, opening new avenues for the design of materials and structures through multi-scale simulations that provide structure-property-performance relationships.« less

Modelling dynamics in protein crystal structures by ensemble refinement

PubMed Central

Burnley, B Tom; Afonine, Pavel V; Adams, Paul D; Gros, Piet

2012-01-01

Single-structure models derived from X-ray data do not adequately account for the inherent, functionally important dynamics of protein molecules. We generated ensembles of structures by time-averaged refinement, where local molecular vibrations were sampled by molecular-dynamics (MD) simulation whilst global disorder was partitioned into an underlying overall translation–libration–screw (TLS) model. Modeling of 20 protein datasets at 1.1–3.1 Å resolution reduced cross-validated Rfree values by 0.3–4.9%, indicating that ensemble models fit the X-ray data better than single structures. The ensembles revealed that, while most proteins display a well-ordered core, some proteins exhibit a ‘molten core’ likely supporting functionally important dynamics in ligand binding, enzyme activity and protomer assembly. Order–disorder changes in HIV protease indicate a mechanism of entropy compensation for ordering the catalytic residues upon ligand binding by disordering specific core residues. Thus, ensemble refinement extracts dynamical details from the X-ray data that allow a more comprehensive understanding of structure–dynamics–function relationships. DOI: http://dx.doi.org/10.7554/eLife.00311.001 PMID:23251785

Molecular approaches to solar energy conversion: the energetic cost of charge separation from molecular-excited states.

PubMed

Durrant, James R

2013-08-13

This review starts with a brief overview of the technological potential of molecular-based solar cell technologies. It then goes on to focus on the core scientific challenge associated with using molecular light-absorbing materials for solar energy conversion, namely the separation of short-lived, molecular-excited states into sufficiently long-lived, energetic, separated charges capable of generating an external photocurrent. Comparisons are made between different molecular-based solar cell technologies, with particular focus on the function of dye-sensitized photoelectrochemical solar cells as well as parallels with the function of photosynthetic reaction centres. The core theme of this review is that generating charge carriers with sufficient lifetime and a high quantum yield from molecular-excited states comes at a significant energetic cost-such that the energy stored in these charge-separated states is typically substantially less than the energy of the initially generated excited state. The role of this energetic loss in limiting the efficiency of solar energy conversion by such devices is emphasized, and strategies to minimize this energy loss are compared and contrasted.

A critique of the molecular target-based drug discovery paradigm based on principles of metabolic control: advantages of pathway-based discovery.

PubMed

Hellerstein, Marc K

2008-01-01

Contemporary drug discovery and development (DDD) is dominated by a molecular target-based paradigm. Molecular targets that are potentially important in disease are physically characterized; chemical entities that interact with these targets are identified by ex vivo high-throughput screening assays, and optimized lead compounds enter testing as drugs. Contrary to highly publicized claims, the ascendance of this approach has in fact resulted in the lowest rate of new drug approvals in a generation. The primary explanation for low rates of new drugs is attrition, or the failure of candidates identified by molecular target-based methods to advance successfully through the DDD process. In this essay, I advance the thesis that this failure was predictable, based on modern principles of metabolic control that have emerged and been applied most forcefully in the field of metabolic engineering. These principles, such as the robustness of flux distributions, address connectivity relationships in complex metabolic networks and make it unlikely a priori that modulating most molecular targets will have predictable, beneficial functional outcomes. These same principles also suggest, however, that unexpected therapeutic actions will be common for agents that have any effect (i.e., that complexity can be exploited therapeutically). A potential operational solution (pathway-based DDD), based on observability rather than predictability, is described, focusing on emergent properties of key metabolic pathways in vivo. Recent examples of pathway-based DDD are described. In summary, the molecular target-based DDD paradigm is built on a naïve and misleading model of biologic control and is not heuristically adequate for advancing the mission of modern therapeutics. New approaches that take account of and are built on principles described by metabolic engineers are needed for the next generation of DDD.

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

PubMed

Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, Jaques

2015-02-01

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Seismic generated infrasounds on Telluric Planets: Modeling and comparisons between Earth, Venus and Mars

NASA Astrophysics Data System (ADS)

Lognonne, P. H.; Rolland, L.; Karakostas, F. G.; Garcia, R.; Mimoun, D.; Banerdt, W. B.; Smrekar, S. E.

2015-12-01

Earth, Venus and Mars are all planets in which infrasounds can propagate and interact with the solid surface. This leads to infrasound generation for internal sources (e.g. quakes) and to seismic waves generations for atmospheric sources (e.g. meteor, impactor explosions, boundary layer turbulences). Both the atmospheric profile, surface density, atmospheric wind and viscous/attenuation processes are however greatly different, including major differences between Mars/Venus and Earth due to the CO2 molecular relaxation. We present modeling results and compare the seismic/acoustic coupling strength for Earth, Mars and Venus. This modeling is made through normal modes modelling for models integrating the interior, atmosphere, both with realistic attenuation (intrinsic Q for solid part, viscosity and molecular relaxation for the atmosphere). We complete these modeling, made for spherical structure, by integration of wind, assuming the later to be homogeneous at the scale of the infrasound wavelength. This allows us to compute either the Seismic normal modes (e.g. Rayleigh surface waves), or the acoustic or the atmospheric gravity modes. Comparisons are done, for either a seismic source or an atmospheric source, on the amplitude of expected signals as a function of distance and frequency. Effects of local time are integrated in the modeling. We illustrate the Rayleigh waves modelling by Earth data (for large quakes and volcanoes eruptions). For Venus, very large coupling can occur at resonance frequencies between the solid part and atmospheric part of the planet through infrasounds/Rayleigh waves coupling. If the atmosphere reduced the Q (quality coefficient) of Rayleigh waves in general, the atmosphere at these resonance soffers better propagation than Venus crust and increases their Q. For Mars, Rayleigh waves excitations by atmospheric burst is shown and discussed for the typical yield of impacts. The new data of the Nasa INSIGHT mission which carry both seismic and infrasound sensors will offer a unique confirmation in 2016-2017. We conclude with the seismic/infrasounds coupling on Venus which make the detection from space of seismic waves possible through the perturbation of the infrared airglow by infrassounds. Detection threshold as low as Magnitude 5.5 can be reached with existing technologies.

Generation of an allelic series of knock-in mice using recombinase-mediated cassette exchange (RMCE).

PubMed

Roebroek, Anton J M; Van Gool, Bart

2014-01-01

Molecular genetic strategies applying embryonic stem cell (ES cell) technologies to study the function of a gene in mice or to generate a mouse model for a human disease are continuously under development. Next to (conditional) inactivation of genes the application and importance of approaches to generate knock-in mutations are increasing. In this chapter the principle and application of recombinase-mediated cassette exchange (RMCE) are discussed as being a new emerging knock-in strategy, which enables easy generation of a series of different knock-in mutations within one gene. An RMCE protocol, which was used to generate a series of different knock-in mutations in the Lrp1 gene of ES cells, is described in detail as an example of how RMCE can be used to generate highly efficiently an allelic series of differently modified ES cell clones from a parental modified ES cell clone. Subsequently the differently modified ES cell clones can be used to generate an allelic series of mutant knock-in mice.

Information origins of the chemical bond: Bond descriptors from molecular communication channels in orbital resolution

NASA Astrophysics Data System (ADS)

Nalewajski, Roman F.

The flow of information in the molecular communication networks in the (condensed) atomic orbital (AO) resolution is investigated and the plane-wave (momentum-space) interpretation of the average Fisher information in the molecular information system is given. It is argued using the quantum-mechanical superposition principle that, in the LCAO MO theory the squares of corresponding elements of the Charge and Bond-Order (CBO) matrix determine the conditional probabilities between AO, which generate the molecular communication system of the Orbital Communication Theory (OCT) of the chemical bond. The conditional-entropy ("noise," information-theoretic "covalency") and the mutual-information (information flow, information-theoretic "ionicity") descriptors of these molecular channels are related to Wiberg's covalency indices of chemical bonds. The illustrative application of OCT to the three-orbital model of the chemical bond X-Y, which is capable of describing the forward- and back-donations as well as the atom promotion accompanying the bond formation, is reported. It is demonstrated that the entropy/information characteristics of these separate bond-effects can be extracted by an appropriate reduction of the output of the molecular information channel, carried out by combining several exits into a single (condensed) one. The molecular channels in both the AO and hybrid orbital representations are examined for both the molecular and representative promolecular input probabilities.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.

PubMed

Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

PubMed Central

Marshall-Colon, Amy; Long, Stephen P.; Allen, Douglas K.; Allen, Gabrielle; Beard, Daniel A.; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A. J.; Cox, Donna J.; Hart, John C.; Hirst, Peter M.; Kannan, Kavya; Katz, Daniel S.; Lynch, Jonathan P.; Millar, Andrew J.; Panneerselvam, Balaji; Price, Nathan D.; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G.; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J.; Voit, Eberhard O.; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop. PMID:28555150

Interpreting the Coulomb-field approximation for generalized-Born electrostatics using boundary-integral equation theory.

PubMed

Bardhan, Jaydeep P

2008-10-14

The importance of molecular electrostatic interactions in aqueous solution has motivated extensive research into physical models and numerical methods for their estimation. The computational costs associated with simulations that include many explicit water molecules have driven the development of implicit-solvent models, with generalized-Born (GB) models among the most popular of these. In this paper, we analyze a boundary-integral equation interpretation for the Coulomb-field approximation (CFA), which plays a central role in most GB models. This interpretation offers new insights into the nature of the CFA, which traditionally has been assessed using only a single point charge in the solute. The boundary-integral interpretation of the CFA allows the use of multiple point charges, or even continuous charge distributions, leading naturally to methods that eliminate the interpolation inaccuracies associated with the Still equation. This approach, which we call boundary-integral-based electrostatic estimation by the CFA (BIBEE/CFA), is most accurate when the molecular charge distribution generates a smooth normal displacement field at the solute-solvent boundary, and CFA-based GB methods perform similarly. Conversely, both methods are least accurate for charge distributions that give rise to rapidly varying or highly localized normal displacement fields. Supporting this analysis are comparisons of the reaction-potential matrices calculated using GB methods and boundary-element-method (BEM) simulations. An approximation similar to BIBEE/CFA exhibits complementary behavior, with superior accuracy for charge distributions that generate rapidly varying normal fields and poorer accuracy for distributions that produce smooth fields. This approximation, BIBEE by preconditioning (BIBEE/P), essentially generates initial guesses for preconditioned Krylov-subspace iterative BEMs. Thus, iterative refinement of the BIBEE/P results recovers the BEM solution; excellent agreement is obtained in only a few iterations. The boundary-integral-equation framework may also provide a means to derive rigorous results explaining how the empirical correction terms in many modern GB models significantly improve accuracy despite their simple analytical forms.

A Computational Framework for 3D Mechanical Modeling of Plant Morphogenesis with Cellular Resolution

PubMed Central

Gilles, Benjamin; Hamant, Olivier; Boudaoud, Arezki; Traas, Jan; Godin, Christophe

2015-01-01

The link between genetic regulation and the definition of form and size during morphogenesis remains largely an open question in both plant and animal biology. This is partially due to the complexity of the process, involving extensive molecular networks, multiple feedbacks between different scales of organization and physical forces operating at multiple levels. Here we present a conceptual and modeling framework aimed at generating an integrated understanding of morphogenesis in plants. This framework is based on the biophysical properties of plant cells, which are under high internal turgor pressure, and are prevented from bursting because of the presence of a rigid cell wall. To control cell growth, the underlying molecular networks must interfere locally with the elastic and/or plastic extensibility of this cell wall. We present a model in the form of a three dimensional (3D) virtual tissue, where growth depends on the local modulation of wall mechanical properties and turgor pressure. The model shows how forces generated by turgor-pressure can act both cell autonomously and non-cell autonomously to drive growth in different directions. We use simulations to explore lateral organ formation at the shoot apical meristem. Although different scenarios lead to similar shape changes, they are not equivalent and lead to different, testable predictions regarding the mechanical and geometrical properties of the growing lateral organs. Using flower development as an example, we further show how a limited number of gene activities can explain the complex shape changes that accompany organ outgrowth. PMID:25569615

Automated de novo phasing and model building of coiled-coil proteins.

PubMed

Rämisch, Sebastian; Lizatović, Robert; André, Ingemar

2015-03-01

Models generated by de novo structure prediction can be very useful starting points for molecular replacement for systems where suitable structural homologues cannot be readily identified. Protein-protein complexes and de novo-designed proteins are examples of systems that can be challenging to phase. In this study, the potential of de novo models of protein complexes for use as starting points for molecular replacement is investigated. The approach is demonstrated using homomeric coiled-coil proteins, which are excellent model systems for oligomeric systems. Despite the stereotypical fold of coiled coils, initial phase estimation can be difficult and many structures have to be solved with experimental phasing. A method was developed for automatic structure determination of homomeric coiled coils from X-ray diffraction data. In a benchmark set of 24 coiled coils, ranging from dimers to pentamers with resolutions down to 2.5 Å, 22 systems were automatically solved, 11 of which had previously been solved by experimental phasing. The generated models contained 71-103% of the residues present in the deposited structures, had the correct sequence and had free R values that deviated on average by 0.01 from those of the respective reference structures. The electron-density maps were of sufficient quality that only minor manual editing was necessary to produce final structures. The method, named CCsolve, combines methods for de novo structure prediction, initial phase estimation and automated model building into one pipeline. CCsolve is robust against errors in the initial models and can readily be modified to make use of alternative crystallographic software. The results demonstrate the feasibility of de novo phasing of protein-protein complexes, an approach that could also be employed for other small systems beyond coiled coils.

Density waves in granular flow

NASA Astrophysics Data System (ADS)

Herrmann, H. J.; Flekkøy, E.; Nagel, K.; Peng, G.; Ristow, G.

Ample experimental evidence has shown the existence of spontaneous density waves in granular material flowing through pipes or hoppers. Using Molecular Dynamics Simulations we show that several types of waves exist and find that these density fluctuations follow a 1/f spectrum. We compare this behaviour to deterministic one-dimensional traffic models. If positions and velocities are continuous variables the model shows self-organized criticality driven by the slowest car. We also present Lattice Gas and Boltzmann Lattice Models which reproduce the experimentally observed effects. Density waves are spontaneously generated when the viscosity has a nonlinear dependence on density which characterizes granular flow.

Materials learning from life: concepts for active, adaptive and autonomous molecular systems.

PubMed

Merindol, Rémi; Walther, Andreas

2017-09-18

Bioinspired out-of-equilibrium systems will set the scene for the next generation of molecular materials with active, adaptive, autonomous, emergent and intelligent behavior. Indeed life provides the best demonstrations of complex and functional out-of-equilibrium systems: cells keep track of time, communicate, move, adapt, evolve and replicate continuously. Stirred by the understanding of biological principles, artificial out-of-equilibrium systems are emerging in many fields of soft matter science. Here we put in perspective the molecular mechanisms driving biological functions with the ones driving synthetic molecular systems. Focusing on principles that enable new levels of functionalities (temporal control, autonomous structures, motion and work generation, information processing) rather than on specific material classes, we outline key cross-disciplinary concepts that emerge in this challenging field. Ultimately, the goal is to inspire and support new generations of autonomous and adaptive molecular devices fueled by self-regulating chemistry.

Morphological, molecular and phylogenetic analyses of Diplotriaena bargusinica Skrjabin, 1917 (Nematoda: Diplotriaenidae).

PubMed

Dutra Vieira, Thainá; Pegoraro de Macedo, Marcia Raquel; Fedatto Bernardon, Fabiana; Müller, Gertrud

2017-10-01

The nematode Diplotriaena bargusinica is a bird air sac parasite, and its taxonomy is based mainly on morphological and morphometric characteristics. Increasing knowledge of genetic information variability has spurred the use of DNA markers in conjunction with morphological data for inferring phylogenetic relationships in different taxa. Considering the potential of molecular biology in taxonomy, this study presents the morphological and molecular characterization of D. bargusinica, and establishes the phylogenetic position of the nematode in Spirurina. Twenty partial sequences of the 18S region of D. bargusinica rDNA were generated. Phylogenetic trees were obtained through the Maximum Likelihood and Bayesian Inference methods where both had similar topology. The group Diplotriaenoidea is monophyletic and the topologies generated corroborate the phylogenetic studies based on traditional and previously performed molecular taxonomy. This study is the first to generate molecular data associated with the morphology of the species. Copyright © 2017 Elsevier B.V. All rights reserved.

Novel ligands of Choline Acetyltransferase designed by in silico molecular docking, hologram QSAR and lead optimization

NASA Astrophysics Data System (ADS)

Kumar, Rajnish; Långström, Bengt; Darreh-Shori, Taher

2016-08-01

Recent reports have brought back the acetylcholine synthesizing enzyme, choline acetyltransferase in the mainstream research in dementia and the cholinergic anti-inflammatory pathway. Here we report, a specific strategy for the design of novel ChAT ligands based on molecular docking, Hologram Quantitative Structure Activity Relationship (HQSAR) and lead optimization. Molecular docking was performed on a series of ChAT inhibitors to decipher the molecular fingerprint of their interaction with the active site of ChAT. Then robust statistical fragment HQSAR models were developed. A library of novel ligands was generated based on the pharmacophoric and shape similarity scoring function, and evaluated in silico for their molecular interactions with ChAT. Ten of the top scoring invented compounds are reported here. We confirmed the activity of α-NETA, the only commercially available ChAT inhibitor, and one of the seed compounds in our model, using a new simple colorimetric ChAT assay (IC50 ~ 88 nM). In contrast, α-NETA exhibited an IC50 of ~30 μM for the ACh-degrading cholinesterases. In conclusion, the overall results may provide useful insight for discovering novel ChAT ligands and potential positron emission tomography tracers as in vivo functional biomarkers of the health of central cholinergic system in neurodegenerative disorders, such as Alzheimer’s disease.

Quantitative structure-retention relationships of flavonoids unraveled by immobilized artificial membrane chromatography.

PubMed

Santoro, Adriana Leandra; Carrilho, Emanuel; Lanças, Fernando Mauro; Montanari, Carlos Alberto

2016-06-10

The pharmacokinetic properties of flavonoids with differing degrees of lipophilicity were investigated using immobilized artificial membranes (IAMs) as the stationary phase in high performance liquid chromatography (HPLC). For each flavonoid compound, we investigated whether the type of column used affected the correlation between the retention factors and the calculated octanol/water partition (log Poct). Three-dimensional (3D) molecular descriptors were calculated from the molecular structure of each compound using i) VolSurf software, ii) the GRID method (computational procedure for determining energetically favorable binding sites in molecules of known structure using a probe for calculating the 3D molecular interaction fields, between the probe and the molecule), and iii) the relationship between partition and molecular structure, analyzed in terms of physicochemical descriptors. The VolSurf built-in Caco-2 model was used to estimate compound permeability. The extent to which the datasets obtained from different columns differ both from each other and from both the calculated log Poct and the predicted permeability in Caco-2 cells was examined by principal component analysis (PCA). The immobilized membrane partition coefficients (kIAM) were analyzed using molecular descriptors in partial least square regression (PLS) and a quantitative structure-retention relationship was generated for the chromatographic retention in the cholesterol column. The cholesterol column provided the best correlation with the permeability predicted by the Caco-2 cell model and a good fit model with great prediction power was obtained for its retention data (R(2)=0.96 and Q(2)=0.85 with four latent variables). Copyright © 2015 Elsevier B.V. All rights reserved.

Bioengineered silk scaffolds in 3D tissue modeling with focus on mammary tissues.

PubMed

Maghdouri-White, Yas; Bowlin, Gary L; Lemmon, Christopher A; Dréau, Didier

2016-02-01

In vitro generation of three-dimensional (3D) biological tissues and organ-like structures is a promising strategy to study and closely model complex aspects of the molecular, cellular, and physiological interactions of tissue. In particular, in vitro 3D tissue modeling holds promises to further our understanding of breast development. Indeed, biologically relevant 3D structures that combine mammary cells and engineered matrices have improved our knowledge of mammary tissue growth, organization, and differentiation. Several polymeric biomaterials have been used as scaffolds to engineer 3D mammary tissues. Among those, silk fibroin-based biomaterials have many biologically relevant properties and have been successfully used in multiple medical applications. Here, we review the recent advances in engineered scaffolds with an emphasis on breast-like tissue generation and the benefits of modified silk-based scaffolds. Copyright © 2015 Elsevier B.V. All rights reserved.

Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method

PubMed Central

Besalú, Emili

2016-01-01

The Superposing Significant Interaction Rules (SSIR) method is described. It is a general combinatorial and symbolic procedure able to rank compounds belonging to combinatorial analogue series. The procedure generates structure-activity relationship (SAR) models and also serves as an inverse SAR tool. The method is fast and can deal with large databases. SSIR operates from statistical significances calculated from the available library of compounds and according to the previously attached molecular labels of interest or non-interest. The required symbolic codification allows dealing with almost any combinatorial data set, even in a confidential manner, if desired. The application example categorizes molecules as binding or non-binding, and consensus ranking SAR models are generated from training and two distinct cross-validation methods: leave-one-out and balanced leave-two-out (BL2O), the latter being suited for the treatment of binary properties. PMID:27240346

Generative Topographic Mapping (GTM): Universal Tool for Data Visualization, Structure-Activity Modeling and Dataset Comparison.

PubMed

Kireeva, N; Baskin, I I; Gaspar, H A; Horvath, D; Marcou, G; Varnek, A

2012-04-01

Here, the utility of Generative Topographic Maps (GTM) for data visualization, structure-activity modeling and database comparison is evaluated, on hand of subsets of the Database of Useful Decoys (DUD). Unlike other popular dimensionality reduction approaches like Principal Component Analysis, Sammon Mapping or Self-Organizing Maps, the great advantage of GTMs is providing data probability distribution functions (PDF), both in the high-dimensional space defined by molecular descriptors and in 2D latent space. PDFs for the molecules of different activity classes were successfully used to build classification models in the framework of the Bayesian approach. Because PDFs are represented by a mixture of Gaussian functions, the Bhattacharyya kernel has been proposed as a measure of the overlap of datasets, which leads to an elegant method of global comparison of chemical libraries. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Consequences of Molecular-Scale Non-Equilibrium Activity on the Dynamics and Mechanics of Self-Assembled Actin-Based Structures and Materials

NASA Astrophysics Data System (ADS)

Marshall Mccall, Patrick

Living cells are hierarchically self-organized forms of active soft matter: molecules on the nanometer scale form functional structures and organelles on the micron scale, which then compose cells on the scale of 10s of microns. While the biological functions of intracellular organelles are defined by the composition and properties of the structures themselves, how those bulk properties emerge from the properties and interactions of individual molecules remains poorly understood. Actin, a globular protein which self-assembles into dynamic semi-flexible polymers, is the basic structural material of cells and the major component of many functional organelles. In this thesis, I have used purified actin as a model system to explore the interplay between molecular-scale dynamics and organelle-scale functionality, with particular focus on the role of molecular-scale non-equilibrium activity. One of the most canonical forms of molecular-scale non-equilibrium activity is that of mechanoenzymes, also called motor proteins. These proteins utilized the free energy liberated by hydrolysis of ATP to perform mechanical work, thereby introducing non-equilibrium "active" stresses on the molecular scale. Combining experiments with mathematical modeling, we demonstrate in this thesis that non-equilibrium motor activity is sufficient to drive self-organization and pattern formation of the multimeric actin-binding motor protein Myosin II on 1D reconstituted actomyosin bundles. Like myosin, actin is itself an ATPase. However, nono-equilibrium ATP hydrolysis on actin is known to regulate the stability and assembly kinetics of actin filaments rather than generate active stresses per se. At the level of single actin filaments, the inhomogeneous nucleotide composition generated along the filament length by hydrolysis directs binding of regulatory proteins like cofilin, which mediate filament disassembly and thereby accelerate actin filament turnover. The concequences of this non-equilibrium turnover on the steady-state properties of collections of filaments remained unclear. Here, I reconstituted tunable, non-equilibrium actin turnover dynamics in entangled solutions of actin filaments as a model of the actin cortex of living cells. We found that this non-equilibrium turnover decouples solution mechanics from microstructure, enabling structurally indistinguishable materials to behave effectively as either viscous fluids or elastic gels. Additionally, we employed computer simulations to identify the dynamical regime in which actin turnover controls the effective viscosity of 2D cross-linked actin networks in the presence of motors. Additionally, I examine in this thesis the localization and self-assembly of actin filaments in condensed liquid phases called polyelectrolyte coacervates as a model membrane-less organelle. We find that concentration of actin through spontaneous partitioning preferentially to the coacervate phase accelerates the assembly of filaments. These filaments then localize to the coacervate-bulk interface, generating particles with visco-elastic shells surrounding liquid cores. In this case, the properties of the condensed phase enable regulation of actin assembly dynamics.

Reading PDB: perception of molecules from 3D atomic coordinates.

PubMed

Urbaczek, Sascha; Kolodzik, Adrian; Groth, Inken; Heuser, Stefan; Rarey, Matthias

2013-01-28

The analysis of small molecule crystal structures is a common way to gather valuable information for drug development. The necessary structural data is usually provided in specific file formats containing only element identities and three-dimensional atomic coordinates as reliable chemical information. Consequently, the automated perception of molecular structures from atomic coordinates has become a standard task in cheminformatics. The molecules generated by such methods must be both chemically valid and reasonable to provide a reliable basis for subsequent calculations. This can be a difficult task since the provided coordinates may deviate from ideal molecular geometries due to experimental uncertainties or low resolution. Additionally, the quality of the input data often differs significantly thus making it difficult to distinguish between actual structural features and mere geometric distortions. We present a method for the generation of molecular structures from atomic coordinates based on the recently published NAOMI model. By making use of this consistent chemical description, our method is able to generate reliable results even with input data of low quality. Molecules from 363 Protein Data Bank (PDB) entries could be perceived with a success rate of 98%, a result which could not be achieved with previously described methods. The robustness of our approach has been assessed by processing all small molecules from the PDB and comparing them to reference structures. The complete data set can be processed in less than 3 min, thus showing that our approach is suitable for large scale applications.

Chapter 5 Multiple, Localized, and Delocalized/Conjugated Bonds in the Orbital Communication Theory of Molecular Systems

NASA Astrophysics Data System (ADS)

Nalewajski, Roman F.

Information theory (IT) probe of the molecular electronic structure, within the communication theory of chemical bonds (CTCB), uses the standard entropy/information descriptors of the Shannon theory of communication to characterize a scattering of the electronic probabilities and their information content throughout the system chemical bonds generated by the occupied molecular orbitals (MO). These "communications" between the basis-set orbitals are determined by the two-orbital conditional probabilities: one- and two-electron in character. They define the molecular information system, in which the electron-allocation "signals" are transmitted between various orbital "inputs" and "outputs". It is argued, using the quantum mechanical superposition principle, that the one-electron conditional probabilities are proportional to the squares of corresponding elements of the charge and bond-order (CBO) matrix of the standard LCAO MO theory. Therefore, the probability of the interorbital connections in the molecular communication system is directly related to Wiberg's quadratic covalency indices of chemical bonds. The conditional-entropy (communication "noise") and mutual-information (information capacity) descriptors of these molecular channels generate the IT-covalent and IT-ionic bond components, respectively. The former reflects the electron delocalization (indeterminacy) due to the orbital mixing, throughout all chemical bonds in the system under consideration. The latter characterizes the localization (determinacy) in the probability scattering in the molecule. These two IT indices, respectively, indicate a fraction of the input information lost in the channel output, due to the communication noise, and its surviving part, due to deterministic elements in probability scattering in the molecular network. Together, these two components generate the system overall bond index. By a straightforward output reduction (condensation) of the molecular channel, the IT indices of molecular fragments, for example, localized bonds, functional groups, and forward and back donations accompanying the bond formation, and so on, can be extracted. The flow of information in such molecular communication networks is investigated in several prototype molecules. These illustrative (model) applications of the orbital communication theory of chemical bonds (CTCB) deal with several classical issues in the electronic structure theory: atom hybridization/promotion, single and multiple chemical bonds, bond conjugation, and so on. The localized bonds in hydrides and delocalized [pi]-bonds in simple hydrocarbons, as well as the multiple bonds in CO and CO2, are diagnosed using the entropy/information descriptors of CTCB. The atom promotion in hydrides and bond conjugation in [pi]-electron systems are investigated in more detail. A major drawback of the previous two-electron approach to molecular channels, namely, two weak bond differentiation in aromatic systems, has been shown to be remedied in the one-electron approach.

A united event grand canonical Monte Carlo study of partially doped polyaniline

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

Byshkin, M. S., E-mail: mbyshkin@unisa.it, E-mail: gmilano@unisa.it; Correa, A.; Buonocore, F.

2013-12-28

A Grand Canonical Monte Carlo scheme, based on united events combining protonation/deprotonation and insertion/deletion of HCl molecules is proposed for the generation of polyaniline structures at intermediate doping levels between 0% (PANI EB) and 100% (PANI ES). A procedure based on this scheme and subsequent structure relaxations using molecular dynamics is described and validated. Using the proposed scheme and the corresponding procedure, atomistic models of amorphous PANI-HCl structures were generated and studied at different doping levels. Density, structure factors, and solubility parameters were calculated. Their values agree well with available experimental data. The interactions of HCl with PANI have beenmore » studied and distribution of their energies has been analyzed. The procedure has also been extended to the generation of PANI models including adsorbed water and the effect of inclusion of water molecules on PANI properties has also been modeled and discussed. The protocol described here is general and the proposed United Event Grand Canonical Monte Carlo scheme can be easily extended to similar polymeric materials used in gas sensing and to other systems involving adsorption and chemical reactions steps.« less

Disordered Actomyosin Is Sufficient to Promote Cooperative and Telescopic Contractility

NASA Astrophysics Data System (ADS)

Murrell, Michael; Linsmeier, Ian; Banerjee, Shiladitya; Kim, Tae Yoon; Jung, Wonyeong; Oakes, Patrick

While the molecular interactions between myosin motors and F-actin are well known, the relationship between F-actin organization and myosin-mediated force generation remains poorly understood. Here, we explore the accumulation of myosin-induced stresses within a 2D biomimetic model of the actomyosin cortex, where myosin activity is controlled spatially and temporally using light. By controlling the geometry and the duration of myosin activation, we show that contraction of disordered actomyosin is highly cooperative, telescopic with the activation area and generates a pattern of mechanical stresses consistent with those observed in contractile cells. We quantitatively reproduce these properties using an in vitro isotropic model of the actomyosin cytoskeleton, and explore the physical origins of telescopic contractility in disordered networks using agent-based simulations. NSF CMMI-1525316.

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

Du, Qiang

The rational design of materials, the development of accurate and efficient material simulation algorithms, and the determination of the response of materials to environments and loads occurring in practice all require an understanding of mechanics at disparate spatial and temporal scales. The project addresses mathematical and numerical analyses for material problems for which relevant scales range from those usually treated by molecular dynamics all the way up to those most often treated by classical elasticity. The prevalent approach towards developing a multiscale material model couples two or more well known models, e.g., molecular dynamics and classical elasticity, each of whichmore » is useful at a different scale, creating a multiscale multi-model. However, the challenges behind such a coupling are formidable and largely arise because the atomistic and continuum models employ nonlocal and local models of force, respectively. The project focuses on a multiscale analysis of the peridynamics materials model. Peridynamics can be used as a transition between molecular dynamics and classical elasticity so that the difficulties encountered when directly coupling those two models are mitigated. In addition, in some situations, peridynamics can be used all by itself as a material model that accurately and efficiently captures the behavior of materials over a wide range of spatial and temporal scales. Peridynamics is well suited to these purposes because it employs a nonlocal model of force, analogous to that of molecular dynamics; furthermore, at sufficiently large length scales and assuming smooth deformation, peridynamics can be approximated by classical elasticity. The project will extend the emerging mathematical and numerical analysis of peridynamics. One goal is to develop a peridynamics-enabled multiscale multi-model that potentially provides a new and more extensive mathematical basis for coupling classical elasticity and molecular dynamics, thus enabling next generation atomistic-to-continuum multiscale simulations. In addition, a rigorous studyof nite element discretizations of peridynamics will be considered. Using the fact that peridynamics is spatially derivative free, we will also characterize the space of admissible peridynamic solutions and carry out systematic analyses of the models, in particular rigorously showing how peridynamics encompasses fracture and other failure phenomena. Additional aspects of the project include the mathematical and numerical analysis of peridynamics applied to stochastic peridynamics models. In summary, the project will make feasible mathematically consistent multiscale models for the analysis and design of advanced materials.« less

Chemically Realistic Tetrahedral Lattice Models for Polymer Chains: Application to Polyethylene Oxide.

PubMed

Dietschreit, Johannes C B; Diestler, Dennis J; Knapp, Ernst W

2016-05-10

To speed up the generation of an ensemble of poly(ethylene oxide) (PEO) polymer chains in solution, a tetrahedral lattice model possessing the appropriate bond angles is used. The distance between noncovalently bonded atoms is maintained at realistic values by generating chains with an enhanced degree of self-avoidance by a very efficient Monte Carlo (MC) algorithm. Potential energy parameters characterizing this lattice model are adjusted so as to mimic realistic PEO polymer chains in water simulated by molecular dynamics (MD), which serves as a benchmark. The MD data show that PEO chains have a fractal dimension of about two, in contrast to self-avoiding walk lattice models, which exhibit the fractal dimension of 1.7. The potential energy accounts for a mild hydrophobic effect (HYEF) of PEO and for a proper setting of the distribution between trans and gauche conformers. The potential energy parameters are determined by matching the Flory radius, the radius of gyration, and the fraction of trans torsion angles in the chain. A gratifying result is the excellent agreement of the pair distribution function and the angular correlation for the lattice model with the benchmark distribution. The lattice model allows for the precise computation of the torsional entropy of the chain. The generation of polymer conformations of the adjusted lattice model is at least 2 orders of magnitude more efficient than MD simulations of the PEO chain in explicit water. This method of generating chain conformations on a tetrahedral lattice can also be applied to other types of polymers with appropriate adjustment of the potential energy function. The efficient MC algorithm for generating chain conformations on a tetrahedral lattice is available for download at https://github.com/Roulattice/Roulattice .

A molecular map of CQR in Mali

PubMed Central

Djimde, Abdoulaye A.; Barger, Breanna; Kone, Aminatou; Beavogui, Abdoul H.; Tekete, Mamadou; Fofana, Bakary; Dara, Antoine; Maiga, Hamma; Dembele, Demba; Toure, Sekou; Dama, Souleymane; Ouologuem, Dinkorma; Sangare, Cheick Papa Oumar; Dolo, Amagana; Sogoba, Nofomo; Nimaga, Karamoko; Kone, Yacouba; Doumbo, Ogobara K.

2009-01-01

Plasmodium falciparum CQR transporter point mutation (PfCRT76T) is known to be the key determinant of CQR. Molecular detection of PfCRT76T in field samples may be used for the surveillance of CQR in the malaria endemic countries. The genotype-resistance index (GRI) which is obtained as the ratio of the prevalence of PfCRT 76T to the incidence of CQR in a clinical trial was proposed as a simple andpractical molecular-based addition to the tools currently available for monitoring CQR in the field. In order to validate the GRI model across populations, time, and resistance patterns, we compiled data from the literature and generated new data from a dozen of sites across Mali. We found a mean PfCRT76T mutation prevalence of 84.5% (range 60.9%–95.1%) across all sites. CQR rates predicted from the GRI model was extrapolated onto a map of Mali to show the patterns of resistance throughout the participating regions. We present a comprehensive map of CQR in Mali, which strongly supports recent changes in drug policy away from chloroquine. PMID:20041947

A molecular map of chloroquine resistance in Mali.

PubMed

Djimde, Abdoulaye A; Barger, Breanna; Kone, Aminatou; Beavogui, Abdoul H; Tekete, Mamadou; Fofana, Bakary; Dara, Antoine; Maiga, Hamma; Dembele, Demba; Toure, Sekou; Dama, Souleymane; Ouologuem, Dinkorma; Sangare, Cheick Papa Oumar; Dolo, Amagana; Sogoba, Nofomo; Nimaga, Karamoko; Kone, Yacouba; Doumbo, Ogobara K

2010-02-01

Plasmodium falciparum chloroquine resistance (CQR) transporter point mutation (PfCRT 76T) is known to be the key determinant of CQR. Molecular detection of PfCRT 76T in field samples may be used for the surveillance of CQR in malaria-endemic countries. The genotype-resistance index (GRI), which is obtained as the ratio of the prevalence of PfCRT 76T to the incidence of CQR in a clinical trial, was proposed as a simple and practical molecular-based addition to the tools currently available for monitoring CQR in the field. In order to validate the GRI model across populations, time, and resistance patterns, we compiled data from the literature and generated new data from 12 sites across Mali. We found a mean PfCRT 76T mutation prevalence of 84.5% (range 60.9-95.1%) across all sites. CQR rates predicted from the GRI model were extrapolated onto a map of Mali to show the patterns of resistance throughout the participating regions. We present a comprehensive map of CQR in Mali, which strongly supports recent changes in drug policy away from chloroquine.

Multi-scale modeling to relate Be surface temperatures, concentrations and molecular sputtering yields

NASA Astrophysics Data System (ADS)

Lasa, Ane; Safi, Elnaz; Nordlund, Kai

2015-11-01

Recent experiments and Molecular Dynamics (MD) simulations show erosion rates of Be exposed to deuterium (D) plasma varying with surface temperature and the correlated D concentration. Little is understood how these three parameters relate for Be surfaces, despite being essential for reliable prediction of impurity transport and plasma facing material lifetime in current (JET) and future (ITER) devices. A multi-scale exercise is presented here to relate Be surface temperatures, concentrations and sputtering yields. Kinetic Monte Carlo (MC) code MMonCa is used to estimate equilibrium D concentrations in Be at different temperatures. Then, mixed Be-D surfaces - that correspond to the KMC profiles - are generated in MD, to calculate Be-D molecular erosion yields due to D irradiation. With this new database implemented in the 3D MC impurity transport code ERO, modeling scenarios studying wall erosion, such as RF-induced enhanced limiter erosion or main wall surface temperature scans run at JET, can be revisited with higher confidence. Work supported by U.S. DOE under Contract DE-AC05-00OR22725.

Layers: A molecular surface peeling algorithm and its applications to analyze protein structures

PubMed Central

Karampudi, Naga Bhushana Rao; Bahadur, Ranjit Prasad

2015-01-01

We present an algorithm ‘Layers’ to peel the atoms of proteins as layers. Using Layers we show an efficient way to transform protein structures into 2D pattern, named residue transition pattern (RTP), which is independent of molecular orientations. RTP explains the folding patterns of proteins and hence identification of similarity between proteins is simple and reliable using RTP than with the standard sequence or structure based methods. Moreover, Layers generates a fine-tunable coarse model for the molecular surface by using non-random sampling. The coarse model can be used for shape comparison, protein recognition and ligand design. Additionally, Layers can be used to develop biased initial configuration of molecules for protein folding simulations. We have developed a random forest classifier to predict the RTP of a given polypeptide sequence. Layers is a standalone application; however, it can be merged with other applications to reduce the computational load when working with large datasets of protein structures. Layers is available freely at http://www.csb.iitkgp.ernet.in/applications/mol_layers/main. PMID:26553411

Three Dimensional (3D) Printing: A Straightforward, User-Friendly Protocol to Convert Virtual Chemical Models to Real-Life Objects

ERIC Educational Resources Information Center

Rossi, Sergio; Benaglia, Maurizio; Brenna, Davide; Porta, Riccardo; Orlandi, Manuel

2015-01-01

A simple procedure to convert protein data bank files (.pdb) into a stereolithography file (.stl) using VMD software (Virtual Molecular Dynamic) is reported. This tutorial allows generating, with a very simple protocol, three-dimensional customized structures that can be printed by a low-cost 3D-printer, and used for teaching chemical education…

Three Dimensional Projection Environment for Molecular Design and Surgical Simulation

DTIC Science & Technology

2011-08-01

bypasses the cumbersome meshing process . The deformation model is only comprised of mass nodes, which are generated by sampling the object volume before...force should minimize the penetration volume, the haptic feedback force is derived directly. Additionally, a post- processing technique is developed to...render distinct physi-cal tissue properties across different interaction areas. The proposed approach does not require any pre- processing and is

Factors affecting interactions between sulphonate-terminated dendrimers and proteins: A three case study.

PubMed

González-García, Estefanía; Maly, Marek; de la Mata, Francisco Javier; Gómez, Rafael; Marina, María Luisa; García, María Concepción

2017-01-01

This work proposes a deep study on the interactions between sulphonate-terminated carbosilane dendrimers and proteins. Three different proteins with different molecular weights and isoelectric points were employed and different pHs, dendrimer concentrations and generations were tested. Variations in fluorescence intensity and emission wavelength were used as protein-dendrimer interaction probes. Interaction between dendrimers and proteins greatly depended on the protein itself and pH. Other important issues were the dendrimer concentration and generation. Protein-dendrimer interactions were favored under acidic working conditions when proteins were positively charged. Moreover, in general, high dendrimer generations promoted these interactions. Modeling of protein-dendrimer interactions allowed to understand the different behaviors observed for every protein. Copyright © 2016 Elsevier B.V. All rights reserved.

Evidence for anticipation in schizophrenia

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

Bassett, A.S.; Honer, W.G.

Anticipation, or increasing severity of a disorder across successive generations, is a genetic phenomenon with an identified molecular mechanism: expansion of unstable trinucleotide repeat sequences. This study examined anticipation in familial schizophrenia. Three generations of siblines from the affected side of families selected for unilineal, autosomal dominant-like inheritance of schizophrenia were studied (n = 186). Across generations more subjects were hospitalized with psychotic illness (P<.0001), at progressively earlier ages (P<.0001), and with increasing severity of illness (P<.0003). The results indicate that anticipation is present in familial schizophrenia. These findings support both an active search for unstable trinucleotide repeat sequences inmore » schizophrenia and reconsideration of the genetic model used for linkage studies in this disorder. 32 refs., 2 figs., 1 tab.« less

Kinesin spindle protein (KSP) inhibitors. Part 4: Structure-based design of 5-alkylamino-3,5-diaryl-4,5-dihydropyrazoles as potent, water-soluble inhibitors of the mitotic kinesin KSP.

PubMed

Cox, Christopher D; Torrent, Maricel; Breslin, Michael J; Mariano, Brenda J; Whitman, David B; Coleman, Paul J; Buser, Carolyn A; Walsh, Eileen S; Hamilton, Kelly; Schaber, Michael D; Lobell, Robert B; Tao, Weikang; South, Vicki J; Kohl, Nancy E; Yan, Youwei; Kuo, Lawrence C; Prueksaritanont, Thomayant; Slaughter, Donald E; Li, Chunze; Mahan, Elizabeth; Lu, Bing; Hartman, George D

2006-06-15

Molecular modeling in combination with X-ray crystallographic information was employed to identify a region of the kinesin spindle protein (KSP) binding site not fully utilized by our first generation inhibitors. We discovered that by appending a propylamine substituent at the C5 carbon of a dihydropyrazole core, we could effectively fill this unoccupied region of space and engage in a hydrogen-bonding interaction with the enzyme backbone. This change led to a second generation compound with increased potency, a 400-fold enhancement in aqueous solubility at pH 4, and improved dog pharmacokinetics relative to the first generation compound.

Direct observation of sequential oxidations of a titania-bound molecular proxy catalyst generated through illumination of molecular sensitizers

NASA Astrophysics Data System (ADS)

Chen, Hsiang-Yun; Ardo, Shane

2018-01-01

Natural photosynthesis uses the energy in sunlight to oxidize or reduce reaction centres multiple times, therefore preparing each reaction centre for a multiple-electron-transfer reaction that will ultimately generate stable reaction products. This process relies on multiple chromophores per reaction centre to quickly generate the active state of the reaction centre and to outcompete deleterious charge recombination. Using a similar design principle, we report spectroscopic evidence for the generation of a twice-oxidized TiO2-bound molecular proxy catalyst after low-intensity visible-light excitation of co-anchored molecular Ru(II)-polypyridyl dyes. Electron transfer from an excited dye to TiO2 generated a Ru(III) state that subsequently and repeatedly reacted with neighbouring Ru(II) dyes via self-exchange electron transfer to ultimately oxidize a distant co-anchored proxy catalyst before charge recombination. The largest yield for twice-oxidized proxy catalysts occurred when they were present at low coverage, suggesting that large dye/electrocatalyst ratios are also desired in dye-sensitized photoelectrochemical cells.

The top skin-associated genes: a comparative analysis of human and mouse skin transcriptomes.

PubMed

Gerber, Peter Arne; Buhren, Bettina Alexandra; Schrumpf, Holger; Homey, Bernhard; Zlotnik, Albert; Hevezi, Peter

2014-06-01

The mouse represents a key model system for the study of the physiology and biochemistry of skin. Comparison of skin between mouse and human is critical for interpretation and application of data from mouse experiments to human disease. Here, we review the current knowledge on structure and immunology of mouse and human skin. Moreover, we present a systematic comparison of human and mouse skin transcriptomes. To this end, we have recently used a genome-wide database of human gene expression to identify genes highly expressed in skin, with no, or limited expression elsewhere - human skin-associated genes (hSAGs). Analysis of our set of hSAGs allowed us to generate a comprehensive molecular characterization of healthy human skin. Here, we used a similar database to generate a list of mouse skin-associated genes (mSAGs). A comparative analysis between the top human (n=666) and mouse (n=873) skin-associated genes (SAGs) revealed a total of only 30.2% identity between the two lists. The majority of shared genes encode proteins that participate in structural and barrier functions. Analysis of the top functional annotation terms revealed an overlap for morphogenesis, cell adhesion, structure, and signal transduction. The results of this analysis, discussed in the context of published data, illustrate the diversity between the molecular make up of skin of both species and grants a probable explanation, why results generated in murine in vivo models often fail to translate into the human.

Particle-based simulations of polarity establishment reveal stochastic promotion of Turing pattern formation

PubMed Central

Ramirez, Samuel A.; Elston, Timothy C.

2018-01-01

Polarity establishment, the spontaneous generation of asymmetric molecular distributions, is a crucial component of many cellular functions. Saccharomyces cerevisiae (yeast) undergoes directed growth during budding and mating, and is an ideal model organism for studying polarization. In yeast and many other cell types, the Rho GTPase Cdc42 is the key molecular player in polarity establishment. During yeast polarization, multiple patches of Cdc42 initially form, then resolve into a single front. Because polarization relies on strong positive feedback, it is likely that the amplification of molecular-level fluctuations underlies the generation of multiple nascent patches. In the absence of spatial cues, these fluctuations may be key to driving polarization. Here we used particle-based simulations to investigate the role of stochastic effects in a Turing-type model of yeast polarity establishment. In the model, reactions take place either between two molecules on the membrane, or between a cytosolic and a membrane-bound molecule. Thus, we developed a computational platform that explicitly simulates molecules at and near the cell membrane, and implicitly handles molecules away from the membrane. To evaluate stochastic effects, we compared particle simulations to deterministic reaction-diffusion equation simulations. Defining macroscopic rate constants that are consistent with the microscopic parameters for this system is challenging, because diffusion occurs in two dimensions and particles exchange between the membrane and cytoplasm. We address this problem by empirically estimating macroscopic rate constants from appropriately designed particle-based simulations. Ultimately, we find that stochastic fluctuations speed polarity establishment and permit polarization in parameter regions predicted to be Turing stable. These effects can operate at Cdc42 abundances expected of yeast cells, and promote polarization on timescales consistent with experimental results. To our knowledge, our work represents the first particle-based simulations of a model for yeast polarization that is based on a Turing mechanism. PMID:29529021

Supramolecular Interactions in Secondary Plant Cell Walls: Effect of Lignin Chemical Composition Revealed with the Molecular Theory of Solvation.

PubMed

Silveira, Rodrigo L; Stoyanov, Stanislav R; Gusarov, Sergey; Skaf, Munir S; Kovalenko, Andriy

2015-01-02

Plant biomass recalcitrance, a major obstacle to achieving sustainable production of second generation biofuels, arises mainly from the amorphous cell-wall matrix containing lignin and hemicellulose assembled into a complex supramolecular network that coats the cellulose fibrils. We employed the statistical-mechanical, 3D reference interaction site model with the Kovalenko-Hirata closure approximation (or 3D-RISM-KH molecular theory of solvation) to reveal the supramolecular interactions in this network and provide molecular-level insight into the effective lignin-lignin and lignin-hemicellulose thermodynamic interactions. We found that such interactions are hydrophobic and entropy-driven, and arise from the expelling of water from the mutual interaction surfaces. The molecular origin of these interactions is carbohydrate-π and π-π stacking forces, whose strengths are dependent on the lignin chemical composition. Methoxy substituents in the phenyl groups of lignin promote substantial entropic stabilization of the ligno-hemicellulosic matrix. Our results provide a detailed molecular view of the fundamental interactions within the secondary plant cell walls that lead to recalcitrance.

On the Overdispersed Molecular Clock

PubMed Central

Takahata, Naoyuki

1987-01-01

Rates of molecular evolution at some loci are more irregular than described by simple Poisson processes. Three situations under which molecular evolution would not follow simple Poisson processes are reevaluated from the viewpoint of the neutrality hypothesis: (i) concomitant or multiple substitutions in a gene, (ii) fluctuating substitution rates in time caused by coupled effects of deleterious mutations and bottlenecks, and (iii) changes in the degree of selective constraints against a gene (neutral space) caused by successive substitutions. The common underlying assumption that these causes are lineage nonspecific excludes the case where mutation rates themselves change systematically among lineages or taxonomic groups, and severely limits the extent of variation in the number of substitutions among lineages. Even under this stringent condition, however, the third hypothesis, the fluctuating neutral space model, can generate fairly large variation. This is described by a time-dependent renewal process, which does not exhibit any episodic nature of molecular evolution. It is argued that the observed elevated variances in the number of nucleotide or amino acid substitutions do not immediately call for positive Darwinian selection in molecular evolution. PMID:3596230

Heuristic lipophilicity potential for computer-aided rational drug design

NASA Astrophysics Data System (ADS)

Du, Qishi; Arteca, Gustavo A.; Mezey, Paul G.

1997-09-01

In this contribution we suggest a heuristic molecular lipophilicitypotential (HMLP), which is a structure-based technique requiring noempirical indices of atomic lipophilicity. The input data used in thisapproach are molecular geometries and molecular surfaces. The HMLP is amodified electrostatic potential, combined with the averaged influences fromthe molecular environment. Quantum mechanics is used to calculate theelectron density function ρ(r) and the electrostatic potential V(r), andfrom this information a lipophilicity potential L(r) is generated. The HMLPis a unified lipophilicity and hydrophilicity potential. The interactions ofdipole and multipole moments, hydrogen bonds, and charged atoms in amolecule are included in the hydrophilic interactions in this model. TheHMLP is used to study hydrogen bonds and water-octanol partitioncoefficients in several examples. The calculated results show that the HMLPgives qualitatively and quantitatively correct, as well as chemicallyreasonable, results in cases where comparisons are available. Thesecomparisons indicate that the HMLP has advantages over the empiricallipophilicity potential in many aspects. The HMLP is a three-dimensional andeasily visualizable representation of molecular lipophilicity, suggested asa potential tool in computer-aided three-dimensional drug design.

Equilibrium Molecular Thermodynamics from Kirkwood Sampling

PubMed Central

2015-01-01

We present two methods for barrierless equilibrium sampling of molecular systems based on the recently proposed Kirkwood method (J. Chem. Phys.2009, 130, 134102). Kirkwood sampling employs low-order correlations among internal coordinates of a molecule for random (or non-Markovian) sampling of the high dimensional conformational space. This is a geometrical sampling method independent of the potential energy surface. The first method is a variant of biased Monte Carlo, where Kirkwood sampling is used for generating trial Monte Carlo moves. Using this method, equilibrium distributions corresponding to different temperatures and potential energy functions can be generated from a given set of low-order correlations. Since Kirkwood samples are generated independently, this method is ideally suited for massively parallel distributed computing. The second approach is a variant of reservoir replica exchange, where Kirkwood sampling is used to construct a reservoir of conformations, which exchanges conformations with the replicas performing equilibrium sampling corresponding to different thermodynamic states. Coupling with the Kirkwood reservoir enhances sampling by facilitating global jumps in the conformational space. The efficiency of both methods depends on the overlap of the Kirkwood distribution with the target equilibrium distribution. We present proof-of-concept results for a model nine-atom linear molecule and alanine dipeptide. PMID:25915525

POLYANA-A tool for the calculation of molecular radial distribution functions based on Molecular Dynamics trajectories

NASA Astrophysics Data System (ADS)

Dimitroulis, Christos; Raptis, Theophanes; Raptis, Vasilios

2015-12-01

We present an application for the calculation of radial distribution functions for molecular centres of mass, based on trajectories generated by molecular simulation methods (Molecular Dynamics, Monte Carlo). When designing this application, the emphasis was placed on ease of use as well as ease of further development. In its current version, the program can read trajectories generated by the well-known DL_POLY package, but it can be easily extended to handle other formats. It is also very easy to 'hack' the program so it can compute intermolecular radial distribution functions for groups of interaction sites rather than whole molecules.

Investigation of the possible effects of comet Encke's meteoroid stream on the Ca exosphere of Mercury

NASA Astrophysics Data System (ADS)

Plainaki, Christina; Mura, Alessandro; Milillo, Anna; Orsini, Stefano; Livi, Stefano; Mangano, Valeria; Massetti, Stefano; Rispoli, Rosanna; De Angelis, Elisabetta

2017-06-01

The MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) observations of the seasonal variability of Mercury's Ca exosphere are consistent with the general idea that the Ca atoms originate from the bombardment of the surface by particles from comet 2P/Encke. The generating mechanism is believed to be a combination of different processes including the release of atomic and molecular surface particles and the photodissociation of exospheric molecules. Considering different generation and loss mechanisms, we perform simulations with a 3-D Monte Carlo model based on the exosphere generation model by Mura et al. (2009). We present for the first time the 3-D spatial distribution of the CaO and Ca exospheres generated through the process of micrometeoroid impact vaporization, and we show that the morphology of the latter is consistent with the available MESSENGER/Mercury Atmospheric and Surface Composition Spectrometer observations. The results presented in this paper can be useful in the exosphere observations planning for BepiColombo, the upcoming European Space Agency-Japanese Aerospace Exploration Agency mission to Mercury.