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Sample records for molecular structure descriptors

  1. Molecular Descriptors

    NASA Astrophysics Data System (ADS)

    Consonni, Viviana; Todeschini, Roberto

    In the last decades, several scientific researches have been focused on studying how to encompass and convert - by a theoretical pathway - the information encoded in the molecular structure into one or more numbers used to establish quantitative relationships between structures and properties, biological activities, or other experimental properties. Molecular descriptors are formally mathematical representations of a molecule obtained by a well-specified algorithm applied to a defined molecular representation or a well-specified experimental procedure. They play a fundamental role in chemistry, pharmaceutical sciences, environmental protection policy, toxicology, ecotoxicology, health research, and quality control. Evidence of the interest of the scientific community in the molecular descriptors is provided by the huge number of descriptors proposed up today: more than 5000 descriptors derived from different theories and approaches are defined in the literature and most of them can be calculated by means of dedicated software applications. Molecular descriptors are of outstanding importance in the research fields of quantitative structure-activity relationships (QSARs) and quantitative structure-property relationships (QSPRs), where they are the independent chemical information used to predict the properties of interest. Along with the definition of appropriate molecular descriptors, the molecular structure representation and the mathematical tools for deriving and assessing models are other fundamental components of the QSAR/QSPR approach. The remarkable progress during the last few years in chemometrics and chemoinformatics has led to new strategies for finding mathematical meaningful relationships between the molecular structure and biological activities, physico-chemical, toxicological, and environmental properties of chemicals. Different approaches for deriving molecular descriptors here reviewed and some of the most relevant descriptors are presented in

  2. Reverse engineering chemical structures from molecular descriptors : how many solutions?

    SciTech Connect

    Brown, William Michael; Martin, Shawn Bryan; Faulon, Jean-Loup Michel

    2005-06-01

    Physical, chemical and biological properties are the ultimate information of interest for chemical compounds. Molecular descriptors that map structural information to activities and properties are obvious candidates for information sharing. In this paper, we consider the feasibility of using molecular descriptors to safely exchange chemical information in such a way that the original chemical structures cannot be reverse engineered. To investigate the safety of sharing such descriptors, we compute the degeneracy (the number of structure matching a descriptor value) of several 2D descriptors, and use various methods to search for and reverse engineer structures. We examine degeneracy in the entire chemical space taking descriptors values from the alkane isomer series and the PubChem database. We further use a stochastic search to retrieve structures matching specific topological index values. Finally, we investigate the safety of exchanging of fragmental descriptors using deterministic enumeration.

  3. Structure/response correlations and similarity/diversity analysis by GETAWAY descriptors. 2. Application of the novel 3D molecular descriptors to QSAR/QSPR studies.

    PubMed

    Consonni, Viviana; Todeschini, Roberto; Pavan, Manuela; Gramatica, Paola

    2002-01-01

    In a previous paper the theory of the new molecular descriptors called GETAWAY (GEometry, Topology, and Atom-Weights AssemblY) was explained. These descriptors have been proposed with the aim of matching 3D-molecular geometry, atom relatedness, and chemical information. In this paper prediction ability in structure-property correlations of GETAWAY descriptors has been tested extensively by analyzing the regressions of these descriptors for selected properties of some reference compound classes. Moreover, the general performance of the new descriptors in QSAR/QSPR has been evaluated with respect to other well-known sets of molecular descriptors.

  4. Results from the Use of Molecular Descriptors Family on Structure Property/Activity Relationships

    PubMed Central

    Jäntschi, Lorentz; Bolboacǎ, Sorana-Daniela

    2007-01-01

    The aim of the paper is to present the results obtained by utilization of an original approach called Molecular Descriptors Family on Structure-Property (MDF-SPR) and Structure-Activity Relationships (MDF-SAR) applied on classes of chemical compounds and its usefulness as precursors of models elaboration of new compounds with better properties and/or activities and low production costs. The MDF-SPR/MDF-SAR methodology integrates the complex information obtained from compound’s structure in unitary efficient models in order to explain properties/activities. The methodology has been applied on a number of thirty sets of chemical compounds. The best subsets of molecular descriptors family members able to estimate and predict property/activity of interest were identified and were statistically and visually analyzed. The MDF-SPR/MDF-SAR models were validated through internal and/or external validation methods. The estimation and prediction abilities of the MDF-SPR/MDF-SAR models were compared with previous reported models by applying of correlated correlation analysis, which revealed that the MDF-SPR/MDF-SAR methodology is reliable. The MDF-SPR/MDF-SAR methodology opens a new pathway in understanding the relationships between compound’s structure and property/activity, in property/activity prediction, and in discovery, investigation and characterization of new chemical compounds, more competitive as costs and property/activity, being a method less expensive comparative with experimental methods.

  5. Quantitative structure-activity relationship of organophosphate compounds based on molecular interaction fields descriptors.

    PubMed

    Zhao, Jinsong; Yu, Shuxia

    2013-03-01

    By using multi-block partial least-squares (MBPLS) method, quantitative structure-activity relationship (QSAR) between 35 organophosphate compounds (OP) and their 24h acute toxicities towards the housefly (Musca nebulo L.) was built on the molecular interaction fields (MIF) descriptors, which were obtained with O, N and DRY as probes, and then normalised with block unscaled weights (BUW) technique. The best QSAR model had 8 principal components, with the coefficient of determination R(2)=0.995 and that of leave-one-out cross-validation Q(2)=0.865, and the corresponding standard deviation of error 0.076 and 0.361, respectively. Block importance in the prediction (BIP) for O, N and DRY probe were 1.030, 0.962 and 1.007, respectively. Contour map of variable coefficients showed that hydrogen bonding between the O atom in PO and the NH groups in acetylcholinesterase (AChE) played an important role in the interaction between OP and AChE. Meanwhile, the hydrophobicity of OP also had significant contribution. QSAR based on the MIF descriptors could be a potential means to interpret the mechanisms of ligand-receptor interaction when the receptor was well known.

  6. Quantitative structure-activity relationship modeling of polycyclic aromatic hydrocarbon mutagenicity by classification methods based on holistic theoretical molecular descriptors.

    PubMed

    Gramatica, Paola; Papa, Ester; Marrocchi, Assunta; Minuti, Lucio; Taticchi, Aldo

    2007-03-01

    Various polycyclic aromatic hydrocarbons (PAHs), ubiquitous environmental pollutants, are recognized mutagens and carcinogens. A homogeneous set of mutagenicity data (TA98 and TA100,+S9) for 32 benzocyclopentaphenanthrenes/chrysenes was modeled by the quantitative structure-activity relationship classification methods k-nearest neighbor and classification and regression tree, using theoretical holistic molecular descriptors. Genetic algorithm provided the selection of the best subset of variables for modeling mutagenicity. The models were validated by leave-one-out and leave-50%-out approaches and have good performance, with sensitivity and specificity ranges of 90-100%. Mutagenicity assessment for these PAHs requires only a few theoretical descriptors of their molecular structure.

  7. PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints.

    PubMed

    Yap, Chun Wei

    2011-05-01

    PaDEL-Descriptor is a software for calculating molecular descriptors and fingerprints. The software currently calculates 797 descriptors (663 1D, 2D descriptors, and 134 3D descriptors) and 10 types of fingerprints. These descriptors and fingerprints are calculated mainly using The Chemistry Development Kit. Some additional descriptors and fingerprints were added, which include atom type electrotopological state descriptors, McGowan volume, molecular linear free energy relation descriptors, ring counts, count of chemical substructures identified by Laggner, and binary fingerprints and count of chemical substructures identified by Klekota and Roth. PaDEL-Descriptor was developed using the Java language and consists of a library component and an interface component. The library component allows it to be easily integrated into quantitative structure activity relationship software to provide the descriptor calculation feature while the interface component allows it to be used as a standalone software. The software uses a Master/Worker pattern to take advantage of the multiple CPU cores that are present in most modern computers to speed up calculations of molecular descriptors. The software has several advantages over existing standalone molecular descriptor calculation software. It is free and open source, has both graphical user interface and command line interfaces, can work on all major platforms (Windows, Linux, MacOS), supports more than 90 different molecular file formats, and is multithreaded. PaDEL-Descriptor is a useful addition to the currently available molecular descriptor calculation software. The software can be downloaded at http://padel.nus.edu.sg/software/padeldescriptor. Copyright © 2010 Wiley Periodicals, Inc.

  8. Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

    PubMed

    Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

    2015-10-06

    In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

  9. Signature molecular descriptor : advanced applications.

    SciTech Connect

    Visco, Donald Patrick, Jr.

    2010-04-01

    In this work we report on the development of the Signature Molecular Descriptor (or Signature) for use in the solution of inverse design problems as well as in highthroughput screening applications. The ultimate goal of using Signature is to identify novel and non-intuitive chemical structures with optimal predicted properties for a given application. We demonstrate this in three studies: green solvent design, glucocorticoid receptor ligand design and the design of inhibitors for Factor XIa. In many areas of engineering, compounds are designed and/or modified in incremental ways which rely upon heuristics or institutional knowledge. Often multiple experiments are performed and the optimal compound is identified in this brute-force fashion. Perhaps a traditional chemical scaffold is identified and movement of a substituent group around a ring constitutes the whole of the design process. Also notably, a chemical being evaluated in one area might demonstrate properties very attractive in another area and serendipity was the mechanism for solution. In contrast to such approaches, computer-aided molecular design (CAMD) looks to encompass both experimental and heuristic-based knowledge into a strategy that will design a molecule on a computer to meet a given target. Depending on the algorithm employed, the molecule which is designed might be quite novel (re: no CAS registration number) and/or non-intuitive relative to what is known about the problem at hand. While CAMD is a fairly recent strategy (dating to the early 1980s), it contains a variety of bottlenecks and limitations which have prevented the technique from garnering more attention in the academic, governmental and industrial institutions. A main reason for this is how the molecules are described in the computer. This step can control how models are developed for the properties of interest on a given problem as well as how to go from an output of the algorithm to an actual chemical structure. This report

  10. Relationships between structure and binding affinity of humic substances for polycyclic aromatic hydrocarbons: Relevance of molecular descriptors

    SciTech Connect

    Perminova, I.V.; Grechishcheva, N.Y.; Petrosyan, V.S.

    1999-11-01

    Partition coefficients for the binding affinities of pyrene, fluoranthene, and anthracene to 26 different humic materials were determined by fluorescence quenching. Sources included isolated humic acids, fulvic acids, and combined humic and fulvic fractions from soil, peat, and freshwater as well as Aldrich humic acid. Each of the humic materials was characterized by elemental composition, ultraviolet absorbance at 280 nm, molecular weight, and for 19 samples, composition of main structural fragments determined by {sup 13}C solution-state NMR. The magnitude of the K{sub oc} values correlated strongly with the independent descriptors of aromaticity of humic materials, including atomic H/C ratio, absorptivity at 280 nm, and three interdependent {sup 13}C NMR descriptors (C{sub Ar{minus}H,R}, {summation}C{sub Ar}, {summation}C{sub Ar}/{summation}C{sub Alk}). Statistical comparison of humic sources grouped by the origin revealed that binding affinities were best predicted by the {sup 13}C NMR descriptors. with a slight prevalence of {summation}C{sub Ar}/{summation}C{sub Alk} ration, while molecular weight was the poorest predictor. The latter produced either direct or inverse significant correlation with the K{sub oc} values depending upon the origin and/or fractional composition of the grouped humic materials.

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

    PubMed

    Basak, Subhash C; Majumdar, Subhabrata

    2015-01-01

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

  12. ANN expert system screening for illicit amphetamines using molecular descriptors

    NASA Astrophysics Data System (ADS)

    Gosav, S.; Praisler, M.; Dorohoi, D. O.

    2007-05-01

    The goal of this study was to develop and an artificial neural network (ANN) based on computed descriptors, which would be able to classify the molecular structures of potential illicit amphetamines and to derive their biological activity according to the similarity of their molecular structure with amphetamines of known toxicity. The system is necessary for testing new molecular structures for epidemiological, clinical, and forensic purposes. It was built using a database formed by 146 compounds representing drugs of abuse (mainly central stimulants, hallucinogens, sympathomimetic amines, narcotics and other potent analgesics), precursors, or derivatized counterparts. Their molecular structures were characterized by computing three types of descriptors: 38 constitutional descriptors (CDs), 69 topological descriptors (TDs) and 160 3D-MoRSE descriptors (3DDs). An ANN system was built for each category of variables. All three networks (CD-NN, TD-NN and 3DD-NN) were trained to distinguish between stimulant amphetamines, hallucinogenic amphetamines, and nonamphetamines. A selection of variables was performed when necessary. The efficiency with which each network identifies the class identity of an unknown sample was evaluated by calculating several figures of merit. The results of the comparative analysis are presented.

  13. Synthesis of novel anthraquinones: Molecular structure, molecular chemical reactivity descriptors and interactions with DNA as antibiotic and anti-cancer drugs

    NASA Astrophysics Data System (ADS)

    Al-Otaibi, Jamelah S.; EL Gogary, Tarek M.

    2017-02-01

    Anthraquinones are well-known anticancer drugs. Anthraquinones anticancer drugs carry out their cytotoxic activities through their interaction with DNA, and inhibition of topoisomerase II activity. Anthraquinones (AQ5 and AQ5H) were synthesized and studied with 1,5-DAAQ by computational and experimental tools. The purpose of this study is to shade more light on mechanism of interaction between anthraquinone DNA affinic agents and different types of DNA. This study will lead to gain of information useful for drug design and development. Molecular structures were optimized using DFT B3LYP/6-31 + G(d). Depending on intramolecular hydrogen bonding interactions four conformers of AQ5 were detected within the range of about 42 kcal/mol. Molecular reactivity of the anthraquinone compounds was explored using global and condensed descriptors (electrophilicity and Fukui functions). NMR and UV-VIS electronic absorption spectra of anthraquinones/DNA were investigated at the physiological pH. The interaction of the anthraquinones (AQ5 and AQ5H) were studied with different DNA namely, calf thymus DNA, (Poly[dA].Poly[dT]) and (Poly[dG].Poly[dC]). UV-VIS electronic absorption spectral data were employed to measure the affinity constants of drug/DNA binding using Scatchard analysis. NMR study confirms qualitatively the drug/DNA interaction in terms of peak shift and broadening.

  14. Molecular design and QSARs/QSPRs with molecular descriptors family.

    PubMed

    Bolboacă, Sorana D; Jäntschi, Lorentz; Diudea, Mircea V

    2013-06-01

    The aim of the present paper is to present the methodology of the molecular descriptors family (MDF) as an integrative tool in molecular modeling and its abilities as a multivariate QSAR/QSPR modeling tool. An algorithm for extracting useful information from the topological and geometrical representation of chemical compounds was developed and integrated to calculate MDF members. The MDF methodology was implemented and the software is available online (http://l.academicdirect.org/Chemistry/SARs/MDF_SARs/). This integrative tool was developed in order to maximize performance, functionality, efficiency and portability. The MDF methodology is able to provide reliable and valid multiple linear regression models. Furthermore, in many cases, the MDF models were better than the published results in the literature in terms of correlation coefficients (statistically significant Steiger's Z test at a significance level of 5%) and/or in terms of values of information criteria and Kubinyi function. The MDF methodology developed and implemented as a platform for investigating and characterizing quantitative relationships between the chemical structure and the activity/property of active compounds was used on more than 50 study cases. In almost all cases, the methodology allowed obtaining of QSAR/QSPR models improved in explanatory power of structure-activity and structure-property relationships. The algorithms applied in the computation of geometric and topological descriptors (useful in modeling physicochemical or biological properties of molecules) and those used in searching for reliable and valid multiple linear regression models certain enrich the pool of low-cost low-time drug design tools.

  15. COMPARATIVE STUDY OF THREE FUNDAMENTAL ORGANIC COMPOUNDS OF CHAIN STRUCTURE OF THREE RINGS An approach based in the molecular descriptors of the DFT (Density Functional Theory)

    NASA Astrophysics Data System (ADS)

    Leon, Neira B. Oscar; Fabio, Mejía Elio; Elizabeth, y. Rincón B.

    2008-04-01

    The organic molecules of a chain structure containing phenyl, oxazole and oxadiazole rings are used in different combinations as active media for tunable lasers. From this viewpoint, we focused in the theoretical study of organic compounds of three rings, which have similar optical properties (fluorescence and laser properties). The main goal of this study is to compare the electronic structure through the analysis of molecular global descriptors defined in the DFT framework of2-[2-X-phenyl]-5-phenyl-1,3-Oxazole, 2-[2-X-phenyl]-5-phenyl-1,3,4-Oxadiazole, and 2-[2-X-phenyl]-5-phenyl-furane with X = H, F and Cl. The basis set used was 6-31G+(d).

  16. Classification of some active compounds and their inactive analogues using two three-dimensional molecular descriptors derived from computation of three-dimensional convex hulls for structures theoretically generated for them.

    PubMed

    Lin, T H; Yu, Y S; Chen, H J

    2000-01-01

    Two three-dimensional (3D) molecular descriptors are used to classify 73 protease inhibitors against the human immunodeficiency virus type 1 (HIV-1). X-ray structures of these HIV-1 protease bound inhibitors are used as templates to generate the most probable bioactive conformations of the inhibitors. A convex hull computation algorithm is applied to each structure generated. The frequency of atoms lying on the vertexes of each hull is counted. Vertexes of the same atomic charge state are then gathered together as a set of commonly exposed groups for all the structures generated. The first 3D descriptor is computed as the maximum molecular path length among any three distinct commonly exposed groups, while the second 3D one is computed as the maximum molecular path length among any three atoms of nonconvex hull vertexes. We find that the 73 HIV-1 protease inhibitors can be classified by the first 3D descriptor into two groups, which agrees with the result of visual classification using the activity data as a criterion for these compounds. The classification scheme is then used to classify a database of 427 active trypsin inhibitors and their inactive analogues. The structures of these compounds are generated theoretically from steps of energy minimization and molecular dynamics. Classification for all these compounds is performed using the SYBYL hierarchical clustering method on the first 3D descriptor and then the second 3D one computed. It is found that some inactive analogues are completely separated from the active inhibitors at the first stage of classification using the first 3D descriptor. Most of the highly active inhibitors are classified into a cluster at the second stage of classification using the second 3D descriptor. Finally, most of these highly active inhibitors are separated from all the accompanying inactive analogues in the cluster through a structural alignment process using a set of commonly exposed groups determined for them.

  17. Compound-class specific estimation of solid organic compound vapour pressure and aqueous solubility from simple molecular structure descriptors and the temperature of melting.

    PubMed

    van Noort, Paul C M

    2009-10-01

    For many solid organic compounds, experimental data for their aqueous solubility and vapour pressure are lacking. Therefore, estimation procedures for these compound properties are needed. On theoretical grounds, this study derives a general compound-class specific estimation procedure for solid organic compound aqueous solubility and vapour pressure. The estimation procedure uses a linear combination of simple molecular descriptors for the molecular structure variation within the compound class and a polynomial for the temperature of melting. This procedure is applied to the vapour pressure of polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, polychlorinated dibenzo-p-dioxins and biphenyls and to the aqueous solubility of PAHs, methylated PAHs, chlorinated benzenes, polychlorinated and polybrominated biphenyls, chlorinated phenols, cresols, and chlorinated 2-methoxyphenols. The standard error of the solid vapour pressure or aqueous solubility estimates from the various compound-class specific regression equations was about 0.2 log units. For PAHs, chlorobenzenes, and PCBs used in the present study, aqueous solubility estimated from the regression equations taking the temperature of melting equal to 298 K, i.e. assuming that the compounds are in a hypothetical liquid state, was equal, within 0.1-0.3 log units to the subcooled liquid solubility estimated from literature regression equations.

  18. A structure-odour relationship study using EVA descriptors and hierarchical clustering.

    PubMed

    Takane, Shin-ya; Mitchell, John B O

    2004-11-21

    Structure-odour relationship analyses using hierarchical clustering were carried out on a diverse dataset of 47 molecules. These molecules were divided into seven odour categories: ambergris, bitter almond, camphoraceous, rose, jasmine, muguet, and musk. The alignment-independent descriptor EVA (EigenVAlue) was used as the molecular descriptor. The results were compared with those of another kind of descriptor, the UNITY 2D fingerprint. The dendrograms obtained with these descriptors were compared with the seven odour categories using the adjusted Rand index. The dendrograms produced by EVA consistently outperformed those from UNITY 2D in reproducing the experimental odour classifications of these 47 molecules.

  19. A new graph-based molecular descriptor using the canonical representation of the molecule.

    PubMed

    Hentabli, Hamza; Saeed, Faisal; Abdo, Ammar; Salim, Naomie

    2014-01-01

    Molecular similarity is a pervasive concept in drug design. The basic idea underlying molecular similarity is the similar property principle, which states that structurally similar molecules will exhibit similar physicochemical and biological properties. In this paper, a new graph-based molecular descriptor (GBMD) is introduced. The GBMD is a new method of obtaining a rough description of 2D molecular structure in textual form based on the canonical representations of the molecule outline shape and it allows rigorous structure specification using small and natural grammars. Simulated virtual screening experiments with the MDDR database show clearly the superiority of the graph-based descriptor compared to many standard descriptors (ALOGP, MACCS, EPFP4, CDKFP, PCFP, and SMILE) using the Tanimoto coefficient (TAN) and the basic local alignment search tool (BLAST) when searches were carried.

  20. How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space.

    PubMed

    Koutsoukas, Alexios; Paricharak, Shardul; Galloway, Warren R J D; Spring, David R; Ijzerman, Adriaan P; Glen, Robert C; Marcus, David; Bender, Andreas

    2014-01-27

    Chemical diversity is a widely applied approach to select structurally diverse subsets of molecules, often with the objective of maximizing the number of hits in biological screening. While many methods exist in the area, few systematic comparisons using current descriptors in particular with the objective of assessing diversity in bioactivity space have been published, and this shortage is what the current study is aiming to address. In this work, 13 widely used molecular descriptors were compared, including fingerprint-based descriptors (ECFP4, FCFP4, MACCS keys), pharmacophore-based descriptors (TAT, TAD, TGT, TGD, GpiDAPH3), shape-based descriptors (rapid overlay of chemical structures (ROCS) and principal moments of inertia (PMI)), a connectivity-matrix-based descriptor (BCUT), physicochemical-property-based descriptors (prop2D), and a more recently introduced molecular descriptor type (namely, "Bayes Affinity Fingerprints"). We assessed both the similar behavior of the descriptors in assessing the diversity of chemical libraries, and their ability to select compounds from libraries that are diverse in bioactivity space, which is a property of much practical relevance in screening library design. This is particularly evident, given that many future targets to be screened are not known in advance, but that the library should still maximize the likelihood of containing bioactive matter also for future screening campaigns. Overall, our results showed that descriptors based on atom topology (i.e., fingerprint-based descriptors and pharmacophore-based descriptors) correlate well in rank-ordering compounds, both within and between descriptor types. On the other hand, shape-based descriptors such as ROCS and PMI showed weak correlation with the other descriptors utilized in this study, demonstrating significantly different behavior. We then applied eight of the molecular descriptors compared in this study to sample a diverse subset of sample compounds (4%) from an

  1. Predictive toxicology: benchmarking molecular descriptors and statistical methods.

    PubMed

    Feng, Jun; Lurati, Laura; Ouyang, Haojun; Robinson, Tracy; Wang, Yuanyuan; Yuan, Shenglan; Young, S Stanley

    2003-01-01

    The development of drugs depends on finding compounds that have beneficial effects with a minimum of toxic effects. The measurement of toxic effects is typically time-consuming and expensive, so there is a need to be able to predict toxic effects from the compound structure. Predicting toxic effects is expected to be challenging because there are usually multiple toxic mechanisms involved. In this paper, combinations of different chemical descriptors and popular statistical methods were applied to the problem of predictive toxicology. Four data sets were collected and cleaned, and four different sets of chemical descriptors were calculated for the compounds in each of the four data sets. Three statistical methods (recursive partitioning, neural networks, and partial least squares) were used to attempt to link chemical descriptors to the response. Good predictions were achieved in the two smaller data sets; we found for large data sets that the results were less effective, indicating that new chemical descriptors or statistical methods are needed. All of the methods and descriptors worked to a degree, but our work hints that certain descriptors work better with specific statistical methods so there is a need for better understanding and for continued methods development.

  2. CBS-QB3 calculation of quantum chemical molecular descriptors of isomeric thiadiazoles.

    PubMed

    Glossman-Mitnik, Daniel

    2006-12-01

    The results of the calculation of several molecular descriptors of isomeric thiadiazoles through the CBS-QB3 model chemistry are presented in this work. The results could be useful in quantitative structure-activity relationship (QSAR) or quantitative structure-property relationship (QSPR) studies of derivatives of the nitrogen-containing analogs of thiophene.

  3. Prediction of pesticides chromatographic lipophilicity from the computational molecular descriptors.

    PubMed

    Casoni, Dorina; Petre, Jana; David, Victor; Sârbu, Costel

    2011-02-01

    Quantitative structure-property relationship models were developed for the prediction of pesticides and some PAH compounds lipophilicity based on a wide set of computational molecular descriptors and a set of experimental chromatographic data. The chromatographic lipophilicity of pesticides has been evaluated by high-performance liquid chromatography (HPLC) using different chemically bonded (C18, C8, CN and Phenyl HPLC columns) stationary phases and two different organic modifiers (methanol and acetonitrile, respectively) in the mobile phase composition. Through a systematic study, by using the classic multivariate analysis, several quantitative structure-property/lipophilicity multi-dimensional models were established. Multiple linear regression and genetic algorithm for the variable subset selection were used. The internal and external statistical evaluation procedures revealed some appropriate models for the chromatographic lipophilicity prediction of pesticides. Moreover, the statistical parameters of regression and those obtained by applying t-test for the intercept (a(0)) and for the slope (a(1)) in order to evaluate relationship between experimental and predicted octanol-water partition coefficients in case of the test set compounds, revealed two statistically valid models that can be successfully used in lipophilicity prediction of pesticides.

  4. Quantum vs. topological descriptors in the development of molecular models of groundwater pollution by pesticides.

    PubMed

    Worrall, Fred; Thomsen, Marianne

    2004-01-01

    Using monitoring observations from two, independent studies of US groundwater comprising a total of 61 pesticide compounds, this study has shown that those compounds found in groundwater can be distinguished from those that cannot be found in groundwater on the basis of semi-empirical, quantum chemical and empirical molecular descriptors. For the semi-empirical descriptors, logistic regression models have been developed and validated against the dataset based on the semi-empirical and quantum chemical descriptors. Logistic regression models, based on the Debye dipole moment (mu), the hydration energy (DeltaHhyd), and van der Waals volume (VvdW), resulted in a maximal explained variation in the data of 74%. When topological indices were also included the explained variance in data increased to 91%, with 86% of the variation being explained by the rule that a compound will be found in groundwater if: 0.28mu < 6chip(v) where 6chip(v) is the sixth-order molecular path connectivity and mu is the dipole moment of the compound. The significance of the dipole moment and hydration energy (or van der Waals volume) indicates that it is water solubility that controls mobility, with the inclusion of topological descriptors representing structural factors limiting the solubility. The dependence of leaching potential on the descriptors that control solubility indicates that predictions of environmental fate based on this approach may represent a strong alternative to the use of adsorption and degradation parameters.

  5. An Infrastructure to Mine Molecular Descriptors for Ligand Selection on Virtual Screening

    PubMed Central

    Seus, Vinicius Rosa; Perazzo, Giovanni Xavier; Winck, Ana T.; Werhli, Adriano V.; Machado, Karina S.

    2014-01-01

    The receptor-ligand interaction evaluation is one important step in rational drug design. The databases that provide the structures of the ligands are growing on a daily basis. This makes it impossible to test all the ligands for a target receptor. Hence, a ligand selection before testing the ligands is needed. One possible approach is to evaluate a set of molecular descriptors. With the aim of describing the characteristics of promising compounds for a specific receptor we introduce a data warehouse-based infrastructure to mine molecular descriptors for virtual screening (VS). We performed experiments that consider as target the receptor HIV-1 protease and different compounds for this protein. A set of 9 molecular descriptors are taken as the predictive attributes and the free energy of binding is taken as a target attribute. By applying the J48 algorithm over the data we obtain decision tree models that achieved up to 84% of accuracy. The models indicate which molecular descriptors and their respective values are relevant to influence good FEB results. Using their rules we performed ligand selection on ZINC database. Our results show important reduction in ligands selection to be applied in VS experiments; for instance, the best selection model picked only 0.21% of the total amount of drug-like ligands. PMID:24812613

  6. Correlation between calculated molecular descriptors of excipient amino acids and experimentally observed thermal stability of lysozyme.

    PubMed

    Meng-Lund, Helena; Friis, Natascha; van de Weert, Marco; Rantanen, Jukka; Poso, Antti; Grohganz, Holger; Jorgensen, Lene

    2017-05-15

    A quantitative structure-property relationship (QSPR) between protein stability and the physicochemical properties of excipients was investigated to enable a more rational choice of stabilizing excipients than prior knowledge. The thermal transition temperature and aggregation time were determined for lysozyme in combination with 13 different amino acids using high throughput fluorescence spectroscopy and kinetic static light scattering measurements. On the theoretical side, around 200 2D and 3D molecular descriptors were calculated based on the amino acids' chemical structure. Multivariate data analysis was applied to correlate the descriptors with the experimental results. It was possible to identify descriptors, i.e. amino acids properties, with a positive influence on either transition temperature or aggregation onset time, or both. A high number of hydrogen bond acceptor moieties was the most prominent stabilizing factor for both responses, whereas hydrophilic surface properties and high molecular mass density mostly had a positive influence on the unfolding temperature. A high partition coefficient (logP(o/w)) was identified as the most prominent destabilizing factor for both responses. The QSPR shows good correlation between calculated molecular descriptors and the measured stabilizing effect of amino acids on lysozyme. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Stabilizing factors of the molecular structure in silicon-based peptidomimetics in gas-phase and water solution. Assessment of the correlation between different descriptors of hydrogen bond strength.

    PubMed

    Rodríguez Ortega, María Pilar Gema; Montejo, Manuel; López González, Juan Jesús

    2013-10-01

    The use of DFT (B3LYP and M06L) and ab initio (MP2) computational methods allowed us to perform a thorough conformational study of N-[dihydroxy (methyl)silyl]methylformamide (DHSF) and 3-[dihydroxy (methyl) silyl] propanamide (DHSP), that could be considered simplified models of the environment of the silanediol group in silicon gem-diols that have proven efficiency as protease inhibitors. We have found a total of 13 molecular conformations that represent minima in the potential energy surfaces of DHSF (six conformers) and DHSP (seven conformers). The key feature in their molecular structure is the occurrence of intramolecular hydrogen bonding between the hydroxyl and aminocarbonyl groups. We have estimated the strength of each individual hydrogen bond in the mentioned species using the descriptors proposed by three different methodologies, i.e., the quantum theory of atoms in molecules (QTAIM), the natural bond orbitals population analysis (NBO), and the so-called empirical Rozenberg's enthalpy-distance relationship. We have found a good correlation among the calculated values for the different descriptors within the whole set of conformers in the molecular systems in this study. We have also discussed the predicted order of stabilities of the different conformers of each species in terms of the so-called ring anomeric effect (RAE) and generalized anomeric effect (GAE). Finally, we also analyzed the discrepancies found in the order of stability when going from the isolated molecule approximation to water solution (PCM).

  8. A local average distance descriptor for flexible protein structure comparison

    PubMed Central

    2014-01-01

    Background Protein structures are flexible and often show conformational changes upon binding to other molecules to exert biological functions. As protein structures correlate with characteristic functions, structure comparison allows classification and prediction of proteins of undefined functions. However, most comparison methods treat proteins as rigid bodies and cannot retrieve similarities of proteins with large conformational changes effectively. Results In this paper, we propose a novel descriptor, local average distance (LAD), based on either the geodesic distances (GDs) or Euclidean distances (EDs) for pairwise flexible protein structure comparison. The proposed method was compared with 7 structural alignment methods and 7 shape descriptors on two datasets comprising hinge bending motions from the MolMovDB, and the results have shown that our method outperformed all other methods regarding retrieving similar structures in terms of precision-recall curve, retrieval success rate, R-precision, mean average precision and F1-measure. Conclusions Both ED- and GD-based LAD descriptors are effective to search deformed structures and overcome the problems of self-connection caused by a large bending motion. We have also demonstrated that the ED-based LAD is more robust than the GD-based descriptor. The proposed algorithm provides an alternative approach for blasting structure database, discovering previously unknown conformational relationships, and reorganizing protein structure classification. PMID:24694083

  9. New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

    PubMed

    Ehresmann, Bernd; de Groot, Marcel J; Alex, Alexander; Clark, Timothy

    2004-01-01

    New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

  10. On an aspect of calculated molecular descriptors in QSAR studies of quinolone antibacterials.

    PubMed

    Ghosh, Payel; Thanadath, Megha; Bagchi, Manish C

    2006-08-01

    The re-emergence of tuberculosis infections, which are resistant to conventional drug therapy, has steadily risen in the last decade and as a result of that, fluoroquinolone drugs are being used as the second line of action. But there is hardly any study to examine specific structure activity relationships of quinolone antibacterials against mycobacteria. In this paper, an attempt has been made to establish a quantitative structure activity relationship modeling for a series of quinolone compounds against Mycobacterium fortuitum and Mycobacterium smegmatis. Due to lack of sufficient physicochemical data for the anti-mycobacterial compounds, it becomes very difficult to develop predictive methods based on experimental data. The present paper is an effort for the development of QSARs from the standpoint of physicochemical, constitutional, geometrical, electrostatic and topological indices. Molecular descriptors have been calculated solely from the chemical structure of N-1, C-7 and 8 substituted quinolone compounds and ridge regression models have been developed which can explain a better structure-activity relationship. Consideration of an intermolecular similarity analysis approach that led to a successful computer program development in PERL language has been used for comparing the influence of various molecular descriptors in different data subsets. The comparison of relative effectiveness of the calculated descriptors in our ridge regression model gives rise to some interesting results.

  11. Analysis of molecular and (di)atomic dual-descriptor functions and matrices.

    PubMed

    Alcoba, Diego R; Oña, Ofelia B; Torre, Alicia; Lain, Luis; Bultinck, Patrick

    2017-06-01

    In this work, the dual-descriptor is studied in matrix form [Formula: see text] and both coordinates condensed to atoms, resulting in atomic and diatomic (or where applicable, bond) condensed single values. This double partitioning method of the dual-descriptor matrix is proposed within the Hirshfeld-I atoms-in-molecule framework although it is easily extended to other atoms-in-molecules methods. Diagonalizing the resulting atomic and bond dual-descriptor matrices gives eigenvalues and eigenvectors describing the reactivity of atoms and bonds. The dual-descriptor function is the diagonal element of the underlying matrix. The extra information contained in the atom and bond resolution is highlighted and the effect of choosing either the fragment of molecular response or response of molecular fragment approach is quantified. Graphical Abstract Atom and bond condensed dual descriptor matrices and functions are derived from molecular ones using Hirshfeld-I atoms in molecules weight functions.

  12. Experimental (FT-IR, FT-Raman, UV and NMR) and quantum chemical studies on molecular structure, spectroscopic analysis, NLO, NBO and reactivity descriptors of 3,5-Difluoroaniline.

    PubMed

    Pathak, S K; Srivastava, R; Sachan, A K; Prasad, O; Sinha, L; Asiri, A M; Karabacak, M

    2015-01-25

    Comprehensive investigation of geometrical and electronic structure in ground as well as the first excited state of 3,5-Difluoroaniline (C6H5NF2) was carried out. The experimentally observed spectral data (FT-TR and FT-Raman) of the title compound was compared with the spectral data obtained by DFT/B3LYP method using 6-311++G(d,p) basis set. The molecular properties like dipole moment, polarizability, first static hyperpolarizability, molecular electrostatic potential surface (MEPs), and contour map were calculated to get a better insight of the properties of the title molecule. Natural bond orbital (NBO) analysis was applied to study stability of the molecule arising from charge delocalization. UV-Vis spectrum of the title compound was also recorded and the electronic properties, such as Frontier orbitals and band gap energies were measured by TD-DFT approach. Total and partial density of state (TDOS and PDOS) and also overlap population density of state (OPDOS) diagrams analysis were presented. Global and local reactivity descriptors were computed to predict reactivity and reactive sites on the molecule. (1)H and (13)C NMR spectra by using gauge including atomic orbital (GIAO) method of studied compound were compared with experimental data obtained. Moreover, the thermodynamic properties were evaluated.

  13. Dissecting molecular descriptors into atomic contributions in density functional reactivity theory.

    PubMed

    Rong, Chunying; Lu, Tian; Liu, Shubin

    2014-01-14

    Density functional reactivity theory (DFRT) employs the electron density of a molecule and its related quantities such as gradient and Laplacian to describe its structure and reactivity properties. Proper descriptions at both molecular (global) and atomic (local) levels are equally important and illuminating. In this work, we make use of Bader's zero-flux partition scheme and consider atomic contributions for a few global reactivity descriptors in DFRT, including the density-based quantification of steric effect and related indices. Earlier, we proved that these quantities are intrinsically correlated for atomic and molecular systems [S. B. Liu, J. Chem. Phys. 126, 191107 (2007); ibid. 126, 244103 (2007)]. In this work, a new basin-based integration algorithm has been implemented, whose reliability and effectiveness have been extensively examined. We also investigated a list of simple hydrocarbon systems and different scenarios of bonding processes, including stretching, bending, and rotating. Interesting changing patterns for the atomic and molecular values of these quantities have been revealed for different systems. This work not only confirms the strong correlation between these global reactivity descriptors for molecular systems, as theoretically proven earlier by us, it also provides new and unexpected changing patterns for their atomic values, which can be employed to understand the origin and nature of chemical phenomena.

  14. New Polynomial-Based Molecular Descriptors with Low Degeneracy

    PubMed Central

    Dehmer, Matthias; Mueller, Laurin A. J.; Graber, Armin

    2010-01-01

    In this paper, we introduce a novel graph polynomial called the ‘information polynomial’ of a graph. This graph polynomial can be derived by using a probability distribution of the vertex set. By using the zeros of the obtained polynomial, we additionally define some novel spectral descriptors. Compared with those based on computing the ordinary characteristic polynomial of a graph, we perform a numerical study using real chemical databases. We obtain that the novel descriptors do have a high discrimination power. PMID:20689599

  15. Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

    PubMed

    Liu, Zhi-Ping; Chen, Luonan

    2016-01-01

    Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

  16. Relationships between the antidotal efficacy and structure, PK/PD parameters and bio-relevant molecular descriptors of AChE reactivating oximes: inclusion and integration to biopharmaceutical classification systems.

    PubMed

    Voicu, Victor; Rădulescu, Flavian Ştefan; Medvedovici, Andrei

    2015-01-01

    The therapeutic outcome of oximes used as reactivators of phosphorylated human acetylcholinesterase (AChE) is influenced, among other factors, by their biological distribution, their in vivo ability to achieve the nucleophilic attack and their affinity for the anionic center of the intact/inhibited AChE. An in silico evaluation of the molecular descriptors and biopharmaceutical properties of 454 set of oximes has been achieved. The available pharmacokinetic (PK) data was analyzed, in an attempt to illustrate their common characteristics and particularities. Based on the observed high water solubility and low permeability across biological barriers, we applied the officially adopted classification systems based on biopharmaceutical properties to identify the existing biopharmaceutical differences between the various oxime entities and to predict their in vivo fate. The structural differences of the organophosphorus compounds (OP) and the available oximes reactivators of OP-inhibited AChE generate distinct toxicokinetic or PK profiles. The tissue compartment specific distribution is one of the key elements for assessment of reactivating efficiency. The distribution through highly specialized barriers, such as blood-brain barrier remains a considerable challenge. The high solubility - low permeability biopharmaceutical profile of oximes can be used to suggest the possible involvement of active transport systems.

  17. Bayesian screening for active compounds in high-dimensional chemical spaces combining property descriptors and molecular fingerprints.

    PubMed

    Vogt, Martin; Bajorath, Jürgen

    2008-01-01

    Bayesian classifiers are increasingly being used to distinguish active from inactive compounds and search large databases for novel active molecules. We introduce an approach to directly combine the contributions of property descriptors and molecular fingerprints in the search for active compounds that is based on a Bayesian framework. Conventionally, property descriptors and fingerprints are used as alternative features for virtual screening methods. Following the approach introduced here, probability distributions of descriptor values and fingerprint bit settings are calculated for active and database molecules and the divergence between the resulting combined distributions is determined as a measure of biological activity. In test calculations on a large number of compound activity classes, this methodology was found to consistently perform better than similarity searching using fingerprints and multiple reference compounds or Bayesian screening calculations using probability distributions calculated only from property descriptors. These findings demonstrate that there is considerable synergy between different types of property descriptors and fingerprints in recognizing diverse structure-activity relationships, at least in the context of Bayesian modeling.

  18. BCL::EMAS — Enantioselective Molecular Asymmetry Descriptor for 3D-QSAR

    PubMed Central

    Sliwoski, Gregory; Lowe, Edward W.; Butkiewicz, Mariusz; Meiler, Jens

    2013-01-01

    Stereochemistry is an important determinant of a molecule's biological activity. Stereoisomers can have different degrees of efficacy or even opposing effects when interacting with a target protein. Stereochemistry is a molecular property difficult to represent in 2D-QSAR as it is an inherently three-dimensional phenomenon. A major drawback of most proposed descriptors for 3D-QSAR that encode stereochemistry is that they require a heuristic for defining all stereocenters and rank-ordering its substituents. Here we propose a novel 3D-QSAR descriptor termed Enantioselective Molecular ASymmetry (EMAS) that is capable of distinguishing between enantiomers in the absence of such heuristics. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. A radial-distribution function (RDF) determines a signed volume of tetrahedrons of all triplets of atoms and the molecule center. The descriptor can be enriched with atom-centric properties such as partial charge. This descriptor showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r2 = 0.89, q2 = 0.78). Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS) for inhibitors and substrates of cytochrome P450 (PUBCHEM AID891). PMID:22907158

  19. Electron-density descriptors as predictors in quantitative structure--activity/property relationships and drug design.

    PubMed

    Matta, Chérif F; Arabi, Alya A

    2011-06-01

    The use of electron density-based molecular descriptors in drug research, particularly in quantitative structure--activity relationships/quantitative structure--property relationships studies, is reviewed. The exposition starts by a discussion of molecular similarity and transferability in terms of the underlying electron density, which leads to a qualitative introduction to the quantum theory of atoms in molecules (QTAIM). The starting point of QTAIM is the topological analysis of the molecular electron-density distributions to extract atomic and bond properties that characterize every atom and bond in the molecule. These atomic and bond properties have considerable potential as bases for the construction of robust quantitative structure--activity/property relationships models as shown by selected examples in this review. QTAIM is applicable to the electron density calculated from quantum-chemical calculations and/or that obtained from ultra-high resolution x-ray diffraction experiments followed by nonspherical refinement. Atomic and bond properties are introduced followed by examples of application of each of these two families of descriptors. The review ends with a study whereby the molecular electrostatic potential, uniquely determined by the density, is used in conjunction with atomic properties to elucidate the reasons for the biological similarity of bioisosteres.

  20. Theoretical molecular descriptors relevant to the uptake of persistent organic pollutants from soil by zucchini. A QSAR study.

    PubMed

    Bordás, Barna; Bélai, Iván; Koomíves, Tamás

    2011-04-13

    The uptake of persistent organic pollutants (POPs) from soil by plants allows the development of phytoremediation protocols to rehabilitate contaminated areas. The use of diverse theoretical descriptors has been reported in the literature for developing quantitative structure-activity relationship (QSAR) models for predicting the bioconcentration factors (BCFs) of POPs in different plants. In this paper an evaluation is given on the molecular properties of POPs in terms of theoretical molecular descriptors that are relevant to the uptake and accumulation of these persistent pollutants from soil by two zucchini varieties. Statistically significant and predictive linear regression models have been developed for the BCF values of 20 polychlorinated dibenzo-p-dioxins/dibenzofurans and 14 polyhalogenated biphenyls in two zucchini varieties based on retrospective data. The relevant parameters have been selected from a set of 1660 DRAGON, 150 VolSurf, and 11 quantum chemical descriptors. The two most significant regression models, containing VolSurf, DRAGON GETAWAY, and quantum chemical descriptors, displayed the following statistical parameters: (eq 3) n = 27, R(2) = 0.940, q(2) = 0.922, SE = 0.155, F = 392.1; (eq 4) n = 27, R(2) = 0.921, q(2) = 0.898, SE = 0.161, F = 140.4. Predictive capabilities of the equations have been validated by using external validation sets. The QSAR models proposed might contribute to the development of viable soil remediation strategies.

  1. Chemical and Molecular Descriptors for the Reactivity of Amines with CO{sub 2}

    SciTech Connect

    Lee, Anita S.; Kitchin, John R.

    2012-10-24

    Amine-based solvents are likely to play an important role in CO{sub 2} capture applications in the future, and the identification of amines with superior performance will facilitate their use in CO{sub 2} capture. While some improvements in performance will be achieved through process modifications, modifying the CO{sub 2} capture performance of an amine also implies in part an ability to modify the reactions between the amine and CO{sub 2} through development of new functionalized amines. We present a computational study of trends in the reactions between CO{sub 2} and functionalized amines with a focus on identifying molecular descriptors that determine trends in reactivity. We examine the formation of bicarbonate and carbamate species on three classes of functionalized amines: alkylamines, alkanolamines, and fluorinated alkylamines including primary, secondary and tertiary amines in each class. These functional groups span electron-withdrawing to donating behavior, hydrogen-bonding, extent of functionalization, and proximity effects of the functional groups. Electron withdrawing groups tend to destabilize CO{sub 2} reaction products, whereas electron-donating groups tend to stabilize CO{sub 2} reaction products. Hydrogen bonding stabilizes CO{sub 2} reaction products. Electronic structure descriptors based on electronegativity were found to describe trends in the bicarbonate formation energy. A chemical correlation was observed between the carbamate formation energy and the carbamic acid formation energy. The local softness on the reacting N in the amine was found to partially explain trends carbamic acid formation energy.

  2. Establishment of an in silico phospholipidosis prediction method using descriptors related to molecular interactions causing phospholipid-compound complex formation.

    PubMed

    Haranosono, Yu; Nemoto, Shingo; Kurata, Masaaki; Sakaki, Hideyuki

    2016-04-01

    Although phospholipidosis (PLD) often affects drug development, there is no convenient in vitro or in vivo test system for PLD detection. In this study, we developed an in silico PLD prediction method based on the PLD-inducing mechanism. We focused on phospholipid (PL)-compound complex formation, which inhibits PL degradation by phospholipase. Thus, we used some molecular interactions, such as electrostatic interactions, hydrophobic interactions, and intermolecular forces, between PL and compounds as descriptors. First, we performed descriptor screening for intermolecular force and then developed a new in silico PLD prediction using descriptors related to molecular interactions. Based on the screening, we identified molecular refraction (MR) as a descriptor of intermolecular force. It is known that ClogP and most-basic pKa can be used for PLD prediction. Thereby, we developed an in silico prediction method using ClogP, most-basic pKa, and MR, which were related to hydrophobic interactions, electrostatic interactions, and intermolecular forces. In addition, a resampling method was used to determine the cut-off values for each descriptor. We obtained good results for 77 compounds as follows: sensitivity = 95.8%, specificity = 75.9%, and concordance = 88.3%. Although there is a concern regarding false-negative compounds for pKa calculations, this predictive ability will be adequate for PLD screening. In conclusion, the mechanism-based in silico PLD prediction method provided good prediction ability, and this method will be useful for evaluating the potential of drugs to cause PLD, particularly in the early stage of drug development, because this method only requires knowledge of the chemical structure.

  3. EVA: A new theoretically based molecular descriptor for use in QSAR/QSPR analysis

    NASA Astrophysics Data System (ADS)

    Ferguson, A. M.; Heritage, T.; Jonathon, P.; Pack, S. E.; Phillips, L.; Rogan, J.; Snaith, P. J.

    1997-03-01

    A new descriptor of molecular structure, EVA, for use in the derivation of robustly predictive QSAR relationships is described. It is based on theoretically derived normal coordinate frequencies, and has been used extensively and successfully in proprietary chemical discovery programmes within Shell Research. As a result of informal dissemination of the methodology, it is now being used successfully in related areas such as pharmaceutical drug discovery. Much of the experimental data used in development remain proprietary, and are not available for publication. This paper describes the method and illustrates its application to the calculation of nonproprietary data, log Pow, in both explanatory and predictive modes. It will be followed by other publications illustrating its application to a range of data derived from biological systems.

  4. Improvement of Ensemble of Multi-Regression Structure-Toxicity Models by Clustering of Molecules in Descriptor Space

    NASA Astrophysics Data System (ADS)

    Bašic, Ivan; Lučié, Bono; Nikolić, Sonja; Papeš-Šokčević, Lidija; Nadramija, Damir

    2009-08-01

    For selected data set published by Russom et al. (Environ. Toxicol. Chem. 16, 948-967 (1997)) containing 704 organic molecules with measured acute aquatic toxicity data (96-h LC50 tests) we calculated data set of more than 1400 molecular descriptors by the Dragon 5.0 program. After we excluded descriptors that have almost constant values, and those having very low correlation with the logarithm of LC50 values on the training set, 623 descriptors remained and were used in the modeling process. Data set of molecules was randomly partitioned into the training and test set containing 560 and 144 molecules, respectively. We developed and compared two kinds of ensemble of both linear and nonlinear multi-regression models (1) normal ensembles and (2) ensembles obtained by the clustering of molecules according to their similarity (clustered ensembles). Clustering of molecules was performed by calculating their Euclidian distances in normalized descriptor space. In this method, the final model was developed only on those molecules from the training set that are close (measured using Euclidian distance in normalized descriptor space) to the selected molecule from the test set. Although results obtained by normal ensembles are very good (e.g. nonlinear ensemble of 8-descriptor models: r2 = 0.82, s = 0.54 (training set), stest = 0.80), significant improvement is obtained by taking into account clustering of molecules in development of ensembles of linear models (e.g. 200 10-descriptor models in ensemble: r2 = 0.87, strain = 0.45 (training set), stest = 0.76; or for 200 simpler models having 7-descriptor models in ensemble r2 = 0.83, Strain = 0.53 (training set), stest = 0.77). These results clearly indicate that the use of information about similarity between molecules can improve structure-toxicity models, and we also expect that this could be valid generally.

  5. Generalized Molecular Descriptors Derived From Event-Based Discrete Derivative.

    PubMed

    Martínez-Santiago, Oscar; Cabrera, Reisel Millán; Marrero-Ponce, Yovani; Barigye, Stephen J; Le-Thi-Thu, Huong; Torres, F Javier; Zambrano, Cesar H; Yaber-Goenaga, Ivan; Cruz-Monteagudo, Maykel; López, Yoan Martínez; Giménez, Facundo Pérez; Torrens, Francisco

    2016-01-01

    In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (atoms). In earlier publications (22- 24), an unique event, named connected subgraphs, (based on the Kier-Hall's subgraphs) was systematically employed for the computation of the matrix F. The present report is a generalization of this notion, in which eleven additional events are introduced, classified in three categories, namely, topological (terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach's subgraphs), fingerprints (MACCs, E-state and substructure fingerprints) and atomic contributions (Ghose and Crippen atom-types for hydrophobicity and refractivity) for F generation. The events are intended to capture diverse information by the generation or search of different kinds of substructures from the graph representation of a molecule. The discrete derivative over duplex atom relations are calculated for each event, and the resulting derivatives, local vertex invariants (LOVIs) are finally obtained. These LOVIs are subsequently employed as the basis for the calculation of global and local indices over groups of atoms (heteroatoms, halogens, methyl carbons, etc.), by using norms, means, statistics and classical algorithms as aggregator (fusion) operators. These indices were implemented in our house software DIVATI (Derivative Type Indices, a new module of TOMOCOMDCARDD system). DIVATI provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http: //www.tomocomd.com. Factor analysis shows that the presented events are rather orthogonal and collect diverse information about the chemical structure. Finally, QSPR models were built to describe the logP and logK of 34

  6. Relationship between molecular descriptors and the enthalpies of sublimation of natural amino acids

    NASA Astrophysics Data System (ADS)

    Badelin, V. G.; Tyunina, V. V.; Girichev, G. V.; Tyunina, E. Yu.

    2016-07-01

    A multiparameter correlation between the enthalpies of sublimation and molecular descriptors of natural amino acids is proposed, based on generalized experimental and literature data on the heat effects of sublimation. The contributions from Van der Waals interactions, hydrogen bond formation, and electrostatic effects into enthalpy of sublimation has been evaluated using regression coefficients.

  7. Total and local (atom and atom type) molecular quadratic indices: significance interpretation, comparison to other molecular descriptors, and QSPR/QSAR applications.

    PubMed

    Ponce, Yovani Marrero

    2004-12-15

    This paper describes the significance interpretation, comparison to other molecular descriptors, and QSPR/QSAR applications of a new set of molecular descriptors: atom, atom type, and total molecular quadratic indices. The features of the kth total and local quadratic indices are illustrated by examples of various types of molecular structures, including chain lengthening, branching, heteroatoms content, and multiple bonds. The linear independence of the local (atom type) quadratic indices to others 0D, 1D, 2D, and 3D molecular descriptors is demonstrated by using principal component analysis for 42 heterogeneous molecules. It is concluded that the local quadratic indices are independent indices containing important structural information to be used in QSPR/QSAR and drug design studies. In this sense, molecular quadratic indices were used to the description and prediction of the boiling point of 28 alkyl alcohols and to the modeling of the partition coefficient (logP), specific rate constant (logk), and antibacterial activity of 2-furylethylene derivatives. These models were statistically significant and showed very good stability to data variation in leave-one-out (LOO) cross-validation experiment. The comparison with the other approaches also revealed good behaviors of our method in this QSAR study.

  8. Classification of signaling proteins based on molecular star graph descriptors using Machine Learning models.

    PubMed

    Fernandez-Lozano, Carlos; Cuiñas, Rubén F; Seoane, José A; Fernández-Blanco, Enrique; Dorado, Julian; Munteanu, Cristian R

    2015-11-07

    Signaling proteins are an important topic in drug development due to the increased importance of finding fast, accurate and cheap methods to evaluate new molecular targets involved in specific diseases. The complexity of the protein structure hinders the direct association of the signaling activity with the molecular structure. Therefore, the proposed solution involves the use of protein star graphs for the peptide sequence information encoding into specific topological indices calculated with S2SNet tool. The Quantitative Structure-Activity Relationship classification model obtained with Machine Learning techniques is able to predict new signaling peptides. The best classification model is the first signaling prediction model, which is based on eleven descriptors and it was obtained using the Support Vector Machines-Recursive Feature Elimination (SVM-RFE) technique with the Laplacian kernel (RFE-LAP) and an AUROC of 0.961. Testing a set of 3114 proteins of unknown function from the PDB database assessed the prediction performance of the model. Important signaling pathways are presented for three UniprotIDs (34 PDBs) with a signaling prediction greater than 98.0%. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Quantifying the fingerprint descriptor dependence of structure-activity relationship information on a large scale.

    PubMed

    Dimova, Dilyana; Stumpfe, Dagmar; Bajorath, Jürgen

    2013-09-23

    It is well-known that different molecular representations, e.g., graphs, numerical descriptors, fingerprints, or 3D models, change the numerical results of molecular similarity calculations. Because the assessment of structure-activity relationships (SARs) requires similarity and potency comparisons of active compounds, this representation dependence inevitably also affects SAR analysis. But to what extent? How exactly does SAR information change when alternative fingerprints are used as descriptors? What is the proportion of active compounds with substantial changes in SAR information induced by different fingerprints? To provide answers to these questions, we have quantified changes in SAR information across many different compound classes using six different fingerprints. SAR profiling was carried out on 128 target-based data sets comprising more than 60,000 compounds with high-confidence activity annotations. A numerical measure of SAR discontinuity was applied to assess SAR information on a per compound basis. For ~70% of all test compounds, changes in SAR characteristics were detected when different fingerprints were used as molecular representations. Moreover, the SAR phenotype of ~30% of the compounds changed, and distinct fingerprint-dependent local SAR environments were detected. The fingerprints we compared were found to generate SAR models that were essentially not comparable. Atom environment and pharmacophore fingerprints produced the largest differences in compound-associated SAR information. Taken together, the results of our systematic analysis reveal larger fingerprint-dependent changes in compound-associated SAR information than would have been anticipated.

  10. Analysing molecular polar surface descriptors to predict blood-brain barrier permeation.

    PubMed

    Shityakov, Sergey; Neuhaus, Winfried; Dandekar, Thomas; Förster, Carola

    2013-01-01

    Molecular polar surface (PS) descriptors are very useful parameters in prediction of drug transport properties. They could be also used to investigate the blood-brain barrier (BBB) permeation rate for various chemical compounds. In this study, a dataset of drugs (n = 19) from various pharmacological groups was studied to estimate their potential properties to permeate across the BBB. Experimental logBB data were available as steady-state distribution values of the in vivo rat model for these molecules. Including accurate calculation of the electrostatic potential maps, polar surface descriptors, such as a two-dimensional polar surface area (2D-PSA), topological polar surface area (TPSA) and three-dimensional polar surface area or polar area (3D-PSA; PA) were measured and analysed. We report the strong correlation of these descriptors with logBB values for the prediction of BBB permeation using the linear partial least squares (PLS) fitting technique. The 3D-PSA descriptor showed the best fit to logBB values with R² = 0.92 and RMSD = 0.29 (p-value < 0.0001). The obtained results demonstrate that all descriptors bear high predictive powers and could provide an efficient strategy to envisage the pharmacokinetic properties of chemical compounds to permeate across the BBB at an early stage of the drug development process.

  11. 'Quasi-Mixture' Descriptors for QSPR Analysis of Molecular Macroscopic Properties. The Critical Properties of Organic Compounds.

    PubMed

    Mokshyna, E; Nedostup, V I; Polishchuk, P G; Kuzmin, V E

    2014-10-01

    Rational approach towards the QSAR/QSPR modeling requires the descriptors to be computationally efficient, yet physically and chemically meaningful. On the basis of existing simplex representation of molecular structure (SiRMS) the novel 'quasi-mixture' descriptors were developed in order to accomplish the goal of characterization molecules on 2D level (i.e. without explicit generation of 3D structure and exhaustive conformational search) with account for potential intermolecular interactions. The critical properties of organic compounds were chosen as target properties for the estimation of descriptors' efficacy because of their well-known physical nature, rigorously estimated experimental errors and large quantity of experimental data. Among described properties are critical temperature, pressure and volume. Obtained models have high statistical characteristics, therefore showing the efficacy of suggested 'quasi-mixture' approach. Moreover, 'quasi-mixture' approach, as a branch of the SiRMS, allows to interpret results in terms of simple basic molecular properties. The obtained picture of influences corresponds to the accepted theoretical views.

  12. Quantitative structure-activity relationships of selective antagonists of glucagon receptor using QuaSAR descriptors.

    PubMed

    Manoj Kumar, Palanivelu; Karthikeyan, Chandrabose; Hari Narayana Moorthy, Narayana Subbiah; Trivedi, Piyush

    2006-11-01

    In the present paper, quantitative structure activity relationship (QSAR) approach was applied to understand the affinity and selectivity of a novel series of triaryl imidazole derivatives towards glucagon receptor. Statistically significant and highly predictive QSARs were derived for glucagon receptor inhibition by triaryl imidazoles using QuaSAR descriptors of molecular operating environment (MOE) employing computer-assisted multiple regression procedure. The generated QSAR models revealed that factors related to hydrophobicity, molecular shape and geometry predominantly influences glucagon receptor binding affinity of the triaryl imidazoles indicating the relevance of shape specific steric interactions between the molecule and the receptor. Further, QSAR models formulated for selective inhibition of glucagon receptor over p38 mitogen activated protein (MAP) kinase of the compounds in the series highlights that the same structural features, which influence the glucagon receptor affinity, also contribute to their selective inhibition.

  13. Combined experimental (FT-IR, UV-visible spectra, NMR) and theoretical studies on the molecular structure, vibrational spectra, HOMO, LUMO, MESP surfaces, reactivity descriptor and molecular docking of Phomarin

    NASA Astrophysics Data System (ADS)

    Kumar, Abhishek; Srivastava, Ambrish Kumar; Gangwar, Shashi; Misra, Neeraj; Mondal, Avijit; Brahmachari, Goutam

    2015-09-01

    Phomarin is an important natural product belonging to anthraquinone series of compounds. The equilibrium geometry of phomarin has been determined and analyzed at DFT method employing B3LYP/6-311++G(d,p) level of computation. The reactivity of molecule using various descriptors such as Fukui functions, local softness, electrophilicity, electronegativity, Hardness, HOMO-LUMO gap are calculated and discussed. The infrared and UV-vis spectra of phomarin are calculated and compared with the experimentally observed ones. Moreover, 1H and 13C NMR spectra have been calculated by using the gauge independent atomic orbital method. We also notice that phomarin shows remarkable biological activities against malaria parasite. The study suggests further investigation on phomarin for their pharmacological importance.

  14. Anabolic and androgenic activities of 19-nor-testosterone steroids: QSAR study using quantum and physicochemical molecular descriptors.

    PubMed

    Alvarez-Ginarte, Yoanna María; Montero-Cabrera, Luis Alberto; de la Vega, José Manuel García; Noheda-Marín, Pedro; Marrero-Ponce, Yovani; Ruíz-García, José Alberto

    2011-08-01

    Quantitative structure-activity relationship (QSAR) study of 19-nor-testosterone steroids family was performed using quantum and physicochemical molecular descriptors. The quantum-chemical descriptors were calculated using semiempirical calculations. The descriptor values were statistically correlated using multi-linear regression analysis. The QSAR study indicated that the electronic properties of these derivatives have significant relationship with observed biological activities. The found QSAR equations explain that the energy difference between the LUMO and HOMO, the total dipole moment, the chemical potential and the value of the net charge of different carbon atoms in the steroid nucleus showed key interaction of these steroids with their anabolic-androgenic receptor binding site. The calculated values predict that the 17α-cyclopropyl-17β, 3β-hydroxy-4-estrene compound presents the highest anabolic-androgenic ratio (AAR) and the 7α-methyl-17β-acetoxy-estr-4-en-3-one compound the lowest AAR. This study might be helpful in the future successful identification of "real" or "virtual" anabolic-androgenic steroids.

  15. Aquifer vulnerability to pesticide pollution - Combining soil, land-use and aquifer properties with molecular descriptors

    USGS Publications Warehouse

    Worrall, F.; Kolpin, D.W.

    2004-01-01

    This study uses an extensive survey of herbicides in groundwater across the midwest United States to predict occurrences of a range of compounds across the region from a combination of their molecular properties and the properties of the catchment of a borehole. The study covers 100 boreholes and eight pesticides. For each of the boreholes its catchment the soil, land-use and aquifer properties were characterized. Discriminating boreholes where pollution occurred from those where no pollution occurred gave a model that was 74% correct with organic carbon content, percentage sand content and depth to the water table being significant properties of the borehole catchment. Molecular topological descriptors as well as Koc, solubility and half-life were used to characterize each compound included in the study. Inclusion of molecular properties makes it possible to discriminate between occurrence and non-occurrence of each compound in each well. The best-fit model combines: organic carbon content, percentage sand content and depth to the water table with molecular descriptors representing molecular size, molecular branching and functional group composition of the herbicides.

  16. Structure-activity correlations for illicit amphetamines using ANN and constitutional descriptors.

    PubMed

    Gosav, S; Praisler, M; Dorohoi, D O; Popa, G

    2006-12-15

    The goal of this study was to develop an expert system capable to identify the potential biological activity of new substances having a molecular structure similar to illicit amphetamines. For this purpose we have designed two types of artificial neural network (ANN) systems, which have been trained to classify amphetamines according to their toxicological activity (stimulant amphetamines or hallucinogenic amphetamines) and distinguish them from nonamphetamines. Such a system is essential for testing new molecular structures for epidemiological, clinical, and forensic purposes. The first type of artificial neural network is a "spectral" neural network, which has as input variables the most important 100 absorption intensities from a total of 260 measured for each normalized infrared spectrum 10cm(-1) apart. The spectral data consists of a database built with the GC-FT-IR spectra of the most popular drugs of abuse (mainly central stimulants, hallucinogens, sympathomimetic amines, narcotics and other potent analgesics), precursors and derivatized counterparts. All samples were also characterized by their constitutional descriptors (CDs). For each sample, a number of 45 CDs were computed and introduced as input variables for a second type of ANN, which uses a structural database. The efficiency of this "structural" artificial neural network (CD-ANN) has been improved by optimizing the training set and increasing the number of input variables (CDs). A comparative analysis of the spectral and the structural networks is presented.

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

    PubMed

    Senet, P; Aparicio, F

    2007-04-14

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

  18. OCWLGI descriptors: theory and praxis.

    PubMed

    Toropov, Andrey A; Toropova, Alla P; Benfenati, Emilio; Gini, Giuseppina

    2013-06-01

    The aim of this review is description of the logic and evolution of optimal descriptors OCWLGI calculated with the molecular graph and the demonstration of their ability as tools for the modeling of biological and physicochemical parameters of chemical compounds. The ability of optimal descriptors calculated with hydrogen suppressed graph (HSG), hydrogen filled graph (HFG) and graph of atomic orbitals (GAO) is demonstrated as a collection of quantitative structure-property relationships (QSPR) and quantitative structure-activity relationships (QSAR) for properties and endpoints available from the literature. The Monte Carlo method optimization of the correlation weights of local and global invariants (OCWLGI) of molecular graphs is used as the principle for building up descriptors which are discussed in this article. The statistical quality of the QSPR and QSAR models for physicochemical and biological properties which were obtained with the optimal descriptors are reasonably high.

  19. Effective structural descriptors for natural and engineered radioactive waste confinement barriers

    NASA Astrophysics Data System (ADS)

    Lemmens, Laurent; Rogiers, Bart; De Craen, Mieke; Laloy, Eric; Jacques, Diederik; Huysmans, Marijke; Swennen, Rudy; Urai, Janos L.; Desbois, Guillaume

    2017-04-01

    The microstructure of a radioactive waste confinement barrier strongly influences its flow and transport properties. Numerical flow and transport simulations for these porous media at the pore scale therefore require input data that describe the microstructure as accurately as possible. To date, no imaging method can resolve all heterogeneities within important radioactive waste confinement barrier materials as hardened cement paste and natural clays at the micro scale (nm-cm). Therefore, it is necessary to merge information from different 2D and 3D imaging methods using porous media reconstruction techniques. To qualitatively compare the results of different reconstruction techniques, visual inspection might suffice. To quantitatively compare training-image based algorithms, Tan et al. (2014) proposed an algorithm using an analysis of distance. However, the ranking of the algorithm depends on the choice of the structural descriptor, in their case multiple-point or cluster-based histograms. We present here preliminary work in which we will review different structural descriptors and test their effectiveness, for capturing the main structural characteristics of radioactive waste confinement barrier materials, to determine the descriptors to use in the analysis of distance. The investigated descriptors are particle size distributions, surface area distributions, two point probability functions, multiple point histograms, linear functions and two point cluster functions. The descriptor testing consists of stochastically generating realizations from a reference image using the simulated annealing optimization procedure introduced by Karsanina et al. (2015). This procedure basically minimizes the differences between pre-specified descriptor values associated with the training image and the image being produced. The most efficient descriptor set can therefore be identified by comparing the image generation quality among the tested descriptor combinations. The assessment

  20. Selection of molecular descriptors with artificial intelligence for the understanding of HIV-1 protease peptidomimetic inhibitors-activity.

    PubMed

    Sirois, S; Tsoukas, C M; Chou, Kuo-Chen; Wei, Dongqing; Boucher, C; Hatzakis, G E

    2005-03-01

    Quantitative Structure Activity Relationship (QSAR) techniques are used routinely by computational chemists in drug discovery and development to analyze datasets of compounds. Quantitative numerical methods like Partial Least Squares (PLS) and Artificial Neural Networks (ANN) have been used on QSAR to establish correlations between molecular properties and bioactivity. However, ANN may be advantageous over PLS because it considers the interrelations of the modeled variables. This study focused on the HIV-1 Protease (HIV-1 Pr) inhibitors belonging to the peptidomimetic class of compounds. The main objective was to select molecular descriptors with the best predictive value for antiviral potency (Ki). PLS and ANN were used to predict Ki activity of HIV-1 Pr inhibitors and the results were compared. To address the issue of dimensionality reduction, Genetic Algorithms (GA) were used for variable selection and their performance was compared against that of ANN. Finally, the structure of the optimum ANN achieving the highest Pearson's-R coefficient was determined. On the basis of Pearson's-R, PLS and ANN were compared to determine which exhibits maximum performance. Training and validation of models was performed on 15 random split sets of the master dataset consisted of 231 compounds. For each compound 192 molecular descriptors were considered. The molecular structure and constant of inhibition (Ki) were selected from the NIAID database. Study findings suggested that non-covalent interactions such as hydrophobicity, shape and hydrogen bonding describe well the antiviral activity of the HIV-1 Pr compounds. The significance of lipophilicity and relationship to HIV-1 associated hyperlipidemia and lipodystrophy syndrome warrant further investigation.

  1. A descriptor of amino acids: SVRG and its application to peptide quantitative structure-activity relationship.

    PubMed

    Tong, J; Che, T; Li, Y; Wang, P; Xu, X; Chen, Y

    2011-01-01

    In this work, a descriptor, SVRG (principal component scores vector of radial distribution function descriptors and geometrical descriptors), was derived from principal component analysis (PCA) of a matrix of two structural variables of coded amino acids, including radial distribution function index (RDF) and geometrical index. SVRG scales were then applied in three panels of peptide quantitative structure-activity relationships (QSARs) which were modelled by partial least squares regression (PLS). The obtained models with the correlation coefficient (R²(cum)), cross-validation correlation coefficient (Q²(LOO)) were 0.910 and 0.863 for 48 bitter-tasting dipeptides; 0.968 and 0.931 for 21 oxytocin analogues; and 0.992 and 0.954 for 20 thromboplastin inhibitors. Satisfactory results showed that SVRG contained much chemical information relating to bioactivities. The approach may be a useful structural expression methodology for studies on peptide QSAR.

  2. Quantitative structure-activity relationship study of antioxidative peptide by using different sets of amino acids descriptors

    NASA Astrophysics Data System (ADS)

    Li, Yao-Wang; Li, Bo; He, Jiguo; Qian, Ping

    2011-07-01

    A database consisting of 214 tripeptides which contain either His or Tyr residue was applied to study quantitative structure-activity relationships (QSAR) of antioxidative tripeptides. Partial Least-Squares Regression analysis (PLSR) was conducted using parameters individually of each amino acid descriptor, including Divided Physico-chemical Property Scores (DPPS), Hydrophobic, Electronic, Steric, and Hydrogen (HESH), Vectors of Hydrophobic, Steric, and Electronic properties (VHSE), Molecular Surface-Weighted Holistic Invariant Molecular (MS-WHIM), isotropic surface area-electronic charge index (ISA-ECI) and Z-scale, to describe antioxidative tripeptides as X-variables and antioxidant activities measured with ferric thiocyanate methods were as Y-variable. After elimination of outliers by Hotelling's T 2 method and residual analysis, six significant models were obtained describing the entire data set. According to cumulative squared multiple correlation coefficients ( R2), cumulative cross-validation coefficients ( Q2) and relative standard deviation for calibration set (RSD c), the qualities of models using DPPS, HESH, ISA-ECI, and VHSE descriptors are better ( R2 > 0.6, Q2 > 0.5, RSD c < 0.39) than that of models using MS-WHIM and Z-scale descriptors ( R2 < 0.6, Q2 < 0.5, RSD c > 0.44). Furthermore, the predictive ability of models using DPPS descriptor is best among the six descriptors systems (cumulative multiple correlation coefficient for predict set ( Rext2) > 0.7). It was concluded that the DPPS is better to describe the amino acid of antioxidative tripeptides. The results of DPPS descriptor reveal that the importance of the center amino acid and the N-terminal amino acid are far more than the importance of the C-terminal amino acid for antioxidative tripeptides. The hydrophobic (positively to activity) and electronic (negatively to activity) properties of the N-terminal amino acid are suggested to play the most important significance to activity, followed

  3. A Survey of Quantitative Descriptions of Molecular Structure

    PubMed Central

    Guha, Rajarshi; Willighagen, Egon

    2013-01-01

    Numerical characterization of molecular structure is a first step in many computational analysis of chemical structure data. These numerical representations, termed descriptors, come in many forms, ranging from simple atom counts and invariants of the molecular graph to distribution of properties, such as charge, across a molecular surface. In this article we first present a broad categorization of descriptors and then describe applications and toolkits that can be employed to evaluate them. We highlight a number of issues surrounding molecular descriptor calculations such as versioning and reproducibility and describe how some toolkits have attempted to address these problems. PMID:23110530

  4. A survey of quantitative descriptions of molecular structure.

    PubMed

    Guha, Rajarshi; Willighagen, Egon

    2012-01-01

    Numerical characterization of molecular structure is a first step in many computational analysis of chemical structure data. These numerical representations, termed descriptors, come in many forms, ranging from simple atom counts and invariants of the molecular graph to distribution of properties, such as charge, across a molecular surface. In this article we first present a broad categorization of descriptors and then describe applications and toolkits that can be employed to evaluate them. We highlight a number of issues surrounding molecular descriptor calculations such as versioning and reproducibility and describe how some toolkits have attempted to address these problems.

  5. Prediction of acetylcholinesterase inhibitors and characterization of correlative molecular descriptors by machine learning methods.

    PubMed

    Lv, Wei; Xue, Ying

    2010-03-01

    Acetylcholinesterase (AChE) has become an important drug target and its inhibitors have proved useful in the symptomatic treatment of Alzheimer's disease. This work explores several machine learning methods (support vector machine (SVM), k-nearest neighbor (k-NN), and C4.5 decision tree (C4.5 DT)) for predicting AChE inhibitors (AChEIs). A feature selection method is used for improving prediction accuracy and selecting molecular descriptors responsible for distinguishing AChEIs and non-AChEIs. The prediction accuracies are 76.3% approximately 88.0% for AChEIs and 74.3% approximately 79.6% for non-AChEIs based on the three kinds of machine learning methods. This work suggests that machine learning methods such as SVM are facilitating for predicting AChEIs potential of unknown sets of compounds and for exhibiting the molecular descriptors associated with AChEIs. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

  6. Mammary carcinogen-protein binding potentials: novel and biologically relevant structure-activity relationship model descriptors.

    PubMed

    Cunningham, A R; Qamar, S; Carrasquer, C A; Holt, P A; Maguire, J M; Cunningham, S L; Trent, J O

    2010-07-01

    Previously, SAR models for carcinogenesis used descriptors that are essentially chemical descriptors. Herein we report the development of models with the cat-SAR expert system using biological descriptors (i.e., ligand-receptor interactions) rat mammary carcinogens. These new descriptors are derived from the virtual screening for ligand-receptor interactions of carcinogens, non-carcinogens, and mammary carcinogens to a set of 5494 target proteins. Leave-one-out validations of the ligand mammary carcinogen-non-carcinogen model had a concordance between experimental and predicted results of 71%, and the mammary carcinogen-non-mammary carcinogen model was 72% concordant. The development of a hybrid fragment-ligand model improved the concordances to 85 and 83%, respectively. In a separate external validation exercise, hybrid fragment-ligand models had concordances of 81 and 76%. Analyses of example rat mammary carcinogens including the food mutagen and oestrogenic compound PhIP, the herbicide atrazine, and the drug indomethacin; the ligand model identified a number of proteins associated with each compound that had previously been referenced in Medline in conjunction with the test chemical and separately with association to breast cancer. This new modelling approach can enhance model predictivity and help bridge the gap between chemical structure and carcinogenic activity by descriptors that are related to biological targets.

  7. Mammary Carcinogen-Protein Binding Potentials: Novel and Biologically Relevant Structure-Activity Relationship Model Descriptors

    PubMed Central

    Cunningham, A.R.; Qamar, S.; Carrasquer, C.A.; Holt, P.A.; Maguire, J.M.; Cunningham, S.L.; Trent, J.O.

    2010-01-01

    Previously, SAR models for carcinogenesis used descriptors that are essentially chemical descriptors. Herein we report the development of models with the cat-SAR expert system using biological descriptors (i.e., ligand-receptor interactions) rat mammary carcinogens. These new descriptors are derived from the virtual screening for ligand-receptor interactions of carcinogens, non-carcinogens, and mammary carcinogens to a set of 5494 target proteins. Leave-one-out validations of the ligand mammary carcinogen non-carcinogen model had a concordance between experimental and predicted results of 71% and the mammary carcinogen non-mammary carcinogen model was 72% concordant. The development of a hybrid fragment-ligand model improved the concordances to 85 and 83%, respectively. In a separate external validation exercise, hybrid fragment-ligand models had concordances of 81 and 76%. Analyses of example rat mammary carcinogens including the food mutagen and estrogenic compound PhIP, the herbicide atrazine, and the drug indomethacin, the ligand model identified a number of proteins associated with each compound that had previously been referenced in Medline in conjunction with the test chemical and separately with association to breast cancer. This new modelling approach can enhance model predictivity and help bridge the gap between chemical structure and carcinogenic activity by descriptors that are related to biological targets. PMID:20818582

  8. Lagrangian Descriptors: A Method for Revealing Phase Space Structures of General Time Dependent Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Mancho, Ana M.; Wiggins, Stephen; Curbelo, Jezabel; Mendoza, Carolina

    2013-11-01

    Lagrangian descriptors are a recent technique which reveals geometrical structures in phase space and which are valid for aperiodically time dependent dynamical systems. We discuss a general methodology for constructing them and we discuss a ``heuristic argument'' that explains why this method is successful. We support this argument by explicit calculations on a benchmark problem. Several other benchmark examples are considered that allow us to assess the performance of Lagrangian descriptors with both finite time Lyapunov exponents (FTLEs) and finite time averages of certain components of the vector field (``time averages''). In all cases Lagrangian descriptors are shown to be both more accurate and computationally efficient than these methods. We thank CESGA for computing facilities. This research was supported by MINECO grants: MTM2011-26696, I-Math C3-0104, ICMAT Severo Ochoa project SEV-2011-0087, and CSIC grant OCEANTECH. SW acknowledges the support of the ONR (Grant No. N00014-01-1-0769).

  9. Binary classification of chalcone derivatives with LDA or KNN based on their antileishmanial activity and molecular descriptors selected using the Successive Projections Algorithm feature-selection technique.

    PubMed

    Goodarzi, Mohammad; Saeys, Wouter; de Araujo, Mario Cesar Ugulino; Galvão, Roberto Kawakami Harrop; Vander Heyden, Yvan

    2014-01-23

    Chalcones are naturally occurring aromatic ketones, which consist of an α-, β-unsaturated carbonyl system joining two aryl rings. These compounds are reported to exhibit several pharmacological activities, including antiparasitic, antibacterial, antifungal, anticancer, immunomodulatory, nitric oxide inhibition and anti-inflammatory effects. In the present work, a Quantitative Structure-Activity Relationship (QSAR) study is carried out to classify chalcone derivatives with respect to their antileishmanial activity (active/inactive) on the basis of molecular descriptors. For this purpose, two techniques to select descriptors are employed, the Successive Projections Algorithm (SPA) and the Genetic Algorithm (GA). The selected descriptors are initially employed to build Linear Discriminant Analysis (LDA) models. An additional investigation is then carried out to determine whether the results can be improved by using a non-parametric classification technique (One Nearest Neighbour, 1NN). In a case study involving 100 chalcone derivatives, the 1NN models were found to provide better rates of correct classification than LDA, both in the training and test sets. The best result was achieved by a SPA-1NN model with six molecular descriptors, which provided correct classification rates of 97% and 84% for the training and test sets, respectively.

  10. Multi-Server Approach for High-Throughput Molecular Descriptors Calculation based on Multi-Linear Algebraic Maps.

    PubMed

    García-Jacas, César R; Aguilera-Mendoza, Longendri; González-Pérez, Reisel; Marrero-Ponce, Yovani; Acevedo-Martínez, Liesner; Barigye, Stephen J; Avdeenko, Tatiana

    2015-01-01

    The present report introduces a novel module of the QuBiLS-MIDAS software for the distributed computation of the 3D Multi-Linear algebraic molecular indices. The main motivation for developing this module is to deal with the computational complexity experienced during the calculation of the descriptors over large datasets. To accomplish this task, a multi-server computing platform named T-arenal was developed, which is suited for institutions with many workstations interconnected through a local network and without resources particularly destined for computation tasks. This new system was deployed in 337 workstations and it was perfectly integrated with the QuBiLS-MIDAS software. To illustrate the usability of the T-arenal platform, performance tests over a dataset comprised of 15 000 compounds are carried out, yielding a 52 and 60 fold reduction in the sequential processing time for the 2-Linear and 3-Linear indices, respectively. Therefore, it can be stated that the T-arenal based distribution of computation tasks constitutes a suitable strategy for performing high-throughput calculations of 3D Multi-Linear descriptors over thousands of chemical structures for posterior QSAR and/or ADME-Tox studies.

  11. Reactivity Descriptors for the Activity of Molecular MN4 Catalysts for the Oxygen Reduction Reaction.

    PubMed

    Zagal, José H; Koper, Marc T M

    2016-11-14

    Similarities are established between well-known reactivity descriptors of metal electrodes for their activity in the oxygen reduction reaction (ORR) and the reactivity of molecular catalysts, in particular macrocyclic MN4 metal complexes confined to electrode surfaces. We show that there is a correlation between the M(III) /M(II) redox potential of MN4 chelates and the M-O2 binding energies. Specifically, the binding energy of O2 (and other O species) follows the M(III) -OH/M(II) redox transition for MnN4 and FeN4 chelates. The ORR volcano plot for MN4 catalysts is similar to that for metal catalysts: catalysts on the weak binding side (mostly CoN4 chelates) yield mainly H2 O2 as the product, with an ORR onset potential independent of the pH value on the NHE scale (and therefore pH-dependent on the RHE scale); catalysts on the stronger binding side yield H2 O as the product with the expected pH-dependence on the NHE scale. The suggested descriptors also apply to heat-treated pyrolyzed MN4 catalysts. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. QuBiLS-MIDAS: a parallel free-software for molecular descriptors computation based on multilinear algebraic maps.

    PubMed

    García-Jacas, César R; Marrero-Ponce, Yovani; Acevedo-Martínez, Liesner; Barigye, Stephen J; Valdés-Martiní, José R; Contreras-Torres, Ernesto

    2014-07-05

    The present report introduces the QuBiLS-MIDAS software belonging to the ToMoCoMD-CARDD suite for the calculation of three-dimensional molecular descriptors (MDs) based on the two-linear (bilinear), three-linear, and four-linear (multilinear or N-linear) algebraic forms. Thus, it is unique software that computes these tensor-based indices. These descriptors, establish relations for two, three, and four atoms by using several (dis-)similarity metrics or multimetrics, matrix transformations, cutoffs, local calculations and aggregation operators. The theoretical background of these N-linear indices is also presented. The QuBiLS-MIDAS software was developed in the Java programming language and employs the Chemical Development Kit library for the manipulation of the chemical structures and the calculation of the atomic properties. This software is composed by a desktop user-friendly interface and an Abstract Programming Interface library. The former was created to simplify the configuration of the different options of the MDs, whereas the library was designed to allow its easy integration to other software for chemoinformatics applications. This program provides functionalities for data cleaning tasks and for batch processing of the molecular indices. In addition, it offers parallel calculation of the MDs through the use of all available processors in current computers. The studies of complexity of the main algorithms demonstrate that these were efficiently implemented with respect to their trivial implementation. Lastly, the performance tests reveal that this software has a suitable behavior when the amount of processors is increased. Therefore, the QuBiLS-MIDAS software constitutes a useful application for the computation of the molecular indices based on N-linear algebraic maps and it can be used freely to perform chemoinformatics studies.

  13. Understanding the comparative molecular field analysis (CoMFA) in terms of molecular quantum similarity and DFT-based reactivity descriptors.

    PubMed

    Morales-Bayuelo, Alejandro; Matute, Ricardo A; Caballero, Julio

    2015-06-01

    The three-dimensional quantitative structure-activity relationship (3D QSAR) models have many applications, although the inherent complexity to understand the results coming from 3D-QSAR arises the necessity of new insights in the interpretation of them. Hence, the quantum similarity field as well as reactivity descriptors based on the density functional theory were used in this work as a consistent approach to better understand the 3D-QSAR studies in drug design. For this purpose, the quantification of steric and electrostatic effects on a series of bicycle [4.1.0] heptane derivatives as melanin-concentrating hormone receptor 1 antagonists were performed on the basis of molecular quantum similarity measures. The maximum similarity superposition and the topo-geometrical superposition algorithms were used as molecular alignment methods to deal with the problem of relative molecular orientation in quantum similarity. In addition, a chemical reactivity analysis using global and local descriptors such as chemical hardness, softness, electrophilicity, and Fukui functions, was developed. Overall, our results suggest that the application of this methodology in drug design can be useful when the receptor is known or even unknown.

  14. New quantum mechanics-based three-dimensional molecular descriptors for use in QSSR approaches: application to asymmetric catalysis.

    PubMed

    Urbano-Cuadrado, Manuel; Carbó, Jorge J; Maldonado, Ana G; Bo, Carles

    2007-01-01

    This paper presents a new protocol based on 3D molecular descriptors using QM calculations for use in CoMFA-like 3D-QSSR. The new method was developed and then applied to predict catalytic selectivity in the asymmetric alkylation of aldehydes catalyzed by Zn-aminoalcohols. The molecular descriptors are obtained straightforwardly from the electronic charge density function, rho(r), and the molecular electrostatic potential (MEP) distributions. The chemically meaningful Molecular Shape Field (MSF) descriptor that accounts for the shape properties of the catalyst is defined from rho(r). Alignment independence was achieved by computing the product of the MSF and MEP values of pairs of points over a given distance range on a molecular isosurface and then selecting the product with the highest value. The new QSSR method demonstrated good predictive ability (q2 = 0.79) when full cross-validation procedures were carried out. Accurate predictions were made for a larger data set, although some deviations occurred in the predictions for catalytic systems with low enantiodiscrimination. Analysis of this QSSR model allows for the following: (1) evaluation of the contribution of each functional group to enantioselectivity and (2) the molecular descriptors to be related to previously proposed stereochemical models for the reaction under study.

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

    PubMed

    Fernández, Alberto; Rallo, Robert; Giralt, Francesc

    2015-10-01

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

  16. Finding Chemical Structures Corresponding to a Set of Coordinates in Chemical Descriptor Space.

    PubMed

    Miyao, Tomoyuki; Funatsu, Kimito

    2017-08-01

    When chemical structures are searched based on descriptor values, or descriptors are interpreted based on values, it is important that corresponding chemical structures actually exist. In order to consider the existence of chemical structures located in a specific region in the chemical space, we propose to search them inside training data domains (TDDs), which are dense areas of a training dataset in the chemical space. We investigated TDDs' features using diverse and local datasets, assuming that GDB11 is the chemical universe. These two analyses showed that considering TDDs gives higher chance of finding chemical structures than a random search-based method, and that novel chemical structures actually exist inside TDDs. In addition to those findings, we tested the hypothesis that chemical structures were distributed on the limited areas of chemical space. This hypothesis was confirmed by the fact that distances among chemical structures in several descriptor spaces were much shorter than those among randomly generated coordinates in the training data range. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Molecular docking using the molecular lipophilicity potential as hydrophobic descriptor: impact on GOLD docking performance.

    PubMed

    Nurisso, Alessandra; Bravo, Juan; Carrupt, Pierre-Alain; Daina, Antoine

    2012-05-25

    GOLD is a molecular docking software widely used in drug design. In the initial steps of docking, it creates a list of hydrophobic fitting points inside protein cavities that steer the positioning of ligand hydrophobic moieties. These points are generated based on the Lennard-Jones potential between a carbon probe and each atom of the residues delimitating the binding site. To thoroughly describe hydrophobic regions in protein pockets and properly guide ligand hydrophobic moieties toward favorable areas, an in-house tool, the MLP filter, was developed and herein applied. This strategy only retains GOLD hydrophobic fitting points that match the rigorous definition of hydrophobicity given by the molecular lipophilicity potential (MLP), a molecular interaction field that relies on an atomic fragmental system based on 1-octanol/water experimental partition coefficients (log P(oct)). MLP computations in the binding sites of crystallographic protein structures revealed that a significant number of points considered hydrophobic by GOLD were actually polar according to the MLP definition of hydrophobicity. To examine the impact of this new tool, ligand-protein complexes from the Astex Diverse Set and the PDB bind core database were redocked with and without the use of the MLP filter. Reliable docking results were obtained by using the MLP filter that increased the quality of docking in nonpolar cavities and outperformed the standard GOLD docking approach.

  18. High-throughput screening for thermoelectric sulphides by using crystal structure features as descriptors

    NASA Astrophysics Data System (ADS)

    Zhang, Ruizhi; Du, Baoli; Chen, Kan; Reece, Mike; Materials Research Insititute Team

    With the increasing computational power and reliable databases, high-throughput screening is playing a more and more important role in the search of new thermoelectric materials. Rather than the well established density functional theory (DFT) calculation based methods, we propose an alternative approach to screen for new TE materials: using crystal structural features as 'descriptors'. We show that a non-distorted transition metal sulphide polyhedral network can be a good descriptor for high power factor according to crystal filed theory. By using Cu/S containing compounds as an example, 1600+ Cu/S containing entries in the Inorganic Crystal Structure Database (ICSD) were screened, and of those 84 phases are identified as promising thermoelectric materials. The screening results are validated by both electronic structure calculations and experimental results from the literature. We also fabricated some new compounds to test our screening results. Another advantage of using crystal structure features as descriptors is that we can easily establish structural relationships between the identified phases. Based on this, two material design approaches are discussed: 1) High-pressure synthesis of metastable phase; 2) In-situ 2-phase composites with coherent interface. This work was supported by a Marie Curie International Incoming Fellowship of the European Community Human Potential Program.

  19. Quantitative structure-activity relationship analysis of acute toxicity of diverse chemicals to Daphnia magna with whole molecule descriptors.

    PubMed

    Moosus, M; Maran, U

    2011-10-01

    Quantitative structure-activity relationship analysis and estimation of toxicological effects at lower-mid trophic levels provide first aid means to understand the toxicity of chemicals. Daphnia magna serves as a good starting point for such toxicity studies and is also recognized for regulatory use in estimating the risk of chemicals. The ECOTOX database was queried and analysed for available data and a homogenous subset of 253 compounds for the endpoint LC50 48 h was established. A four-parameter quantitative structure-activity relationship was derived (coefficient of determination, r (2) = 0.740) for half of the compounds and internally validated (leave-one-out cross-validated coefficient of determination, [Formula: see text] = 0.714; leave-many-out coefficient of determination, [Formula: see text] = 0.738). External validation was carried out with the remaining half of the compounds (coefficient of determination for external validation, [Formula: see text] = 0.634). Two of the descriptors in the model (log P, average bonding information content) capture the structural characteristics describing penetration through bio-membranes. Another two descriptors (energy of highest occupied molecular orbital, weighted partial negative surface area) capture the electronic structural characteristics describing the interaction between the chemical and its hypothetic target in the cell. The applicability domain was subsequently analysed and discussed.

  20. Metal Oxide Nanomaterial QNAR Models: Available Structural Descriptors and Understanding of Toxicity Mechanisms

    PubMed Central

    Ying, Jiali; Zhang, Ting; Tang, Meng

    2015-01-01

    Metal oxide nanomaterials are widely used in various areas; however, the divergent published toxicology data makes it difficult to determine whether there is a risk associated with exposure to metal oxide nanomaterials. The application of quantitative structure activity relationship (QSAR) modeling in metal oxide nanomaterials toxicity studies can reduce the need for time-consuming and resource-intensive nanotoxicity tests. The nanostructure and inorganic composition of metal oxide nanomaterials makes this approach different from classical QSAR study; this review lists and classifies some structural descriptors, such as size, cation charge, and band gap energy, in recent metal oxide nanomaterials quantitative nanostructure activity relationship (QNAR) studies and discusses the mechanism of metal oxide nanomaterials toxicity based on these descriptors and traditional nanotoxicity tests. PMID:28347085

  1. A novel 3D shape descriptor for automatic retrieval of anatomical structures from medical images

    NASA Astrophysics Data System (ADS)

    Nunes, Fátima L. S.; Bergamasco, Leila C. C.; Delmondes, Pedro H.; Valverde, Miguel A. G.; Jackowski, Marcel P.

    2017-03-01

    Content-based image retrieval (CBIR) aims at retrieving from a database objects that are similar to an object provided by a query, by taking into consideration a set of extracted features. While CBIR has been widely applied in the two-dimensional image domain, the retrieval of3D objects from medical image datasets using CBIR remains to be explored. In this context, the development of descriptors that can capture information specific to organs or structures is desirable. In this work, we focus on the retrieval of two anatomical structures commonly imaged by Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) techniques, the left ventricle of the heart and blood vessels. Towards this aim, we developed the Area-Distance Local Descriptor (ADLD), a novel 3D local shape descriptor that employs mesh geometry information, namely facet area and distance from centroid to surface, to identify shape changes. Because ADLD only considers surface meshes extracted from volumetric medical images, it substantially diminishes the amount of data to be analyzed. A 90% precision rate was obtained when retrieving both convex (left ventricle) and non-convex structures (blood vessels), allowing for detection of abnormalities associated with changes in shape. Thus, ADLD has the potential to aid in the diagnosis of a wide range of vascular and cardiac diseases.

  2. Multiple structure single parameter: analysis of a single protein nano environment descriptor characterizing a shared loci on structurally aligned proteins.

    PubMed

    Salim, José Augusto; Borro, Luiz; Mazoni, Ivan; Yano, Inácio; Jardine, José G; Neshich, Goran

    2016-06-15

    A graphical representation of physicochemical and structural descriptors attributed to amino acid residues occupying the same topological position in different, structurally aligned proteins can provide a more intuitive way to associate possible functional implications to identified variations in structural characteristics. This could be achieved by observing selected characteristics of amino acids and of their corresponding nano environments, described by the numerical value of matching descriptor. For this purpose, a web-based tool called multiple structure single parameter (MSSP) was developed and here presented. MSSP produces a two-dimensional plot of a single protein descriptor for a number of structurally aligned protein chains. From a total of 150 protein descriptors available in MSSP, selected of >1500 parameters stored in the STING database, it is possible to create easily readable and highly informative XY-plots, where X-axis contains the amino acid position in the multiple structural alignment, and Y-axis contains the descriptor's numerical values for each aligned structure. To illustrate one of possible MSSP contributions to the investigation of changes in physicochemical and structural properties of mutants, comparing them with the cognate wild-type structure, the oncogenic mutation of M918T in RET kinase is presented. The comparative analysis of wild-type and mutant structures shows great changes in their electrostatic potential. These variations are easily depicted at the MSSP-generated XY-plot. The web server is freely available at http://www.cbi.cnptia.embrapa.br/SMS/STINGm/MPA/index.html Web server implemented in Perl, Java and JavaScript and JMol or Protein Viewer as structure visualizers. goran.neshich@embrapa.br or gneshich@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  3. The utilisation of structural descriptors to predict metabolic constants of xenobiotics in mammals.

    PubMed

    Pirovano, Alessandra; Brandmaier, Stefan; Huijbregts, Mark A J; Ragas, Ad M J; Veltman, Karin; Hendriks, A Jan

    2015-01-01

    Quantitative structure-activity relationships (QSARs) were developed to predict the Michaelis-Menten constant (Km) and the maximum reaction rate (Vmax) of xenobiotics metabolised by four enzyme classes in mammalian livers: alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO), and cytochrome P450 (CYP). Metabolic constants were gathered from the literature and a genetic algorithm was employed to select at most six predictors from a pool of over 2000 potential molecular descriptors using two-thirds of the xenobiotics in each enzyme class. The resulting multiple linear models were cross-validated using the remaining one-third of the compounds. The explained variances (R(2)adj) of the QSARs were between 50% and 80% and the predictive abilities (R(2)ext) between 50% and 60%, except for the Vmax QSAR of FMO with both R(2)adj and R(2)ext less than 30%. The Vmax values of FMO were independent of substrate chemical structure because the rate-limiting step of its catalytic cycle occurs before compound oxidation. For the other enzymes, Vmax was predominantly determined by functional groups or fragments and electronic properties because of the strong and chemical-specific interactions involved in the metabolic reactions. The most relevant predictors for Km were functional groups or fragments for the enzymes metabolising specific compounds (ADH, ALDH and FMO) and size and shape properties for CYP, likely because of the broad substrate specificity of CYP enzymes. The present study can be helpful to predict the Km and Vmax of four important oxidising enzymes in mammals and better understand the underlying principles of chemical transformation by liver enzymes. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. A Java chemical structure editor supporting the Modular Chemical Descriptor Language (MCDL).

    PubMed

    Trepalin, Sergei V; Yarkov, Alexander V; Pletnev, Igor V; Gakh, Andrei A

    2006-03-29

    A compact Modular Chemical Descriptor Language (MCDL) chemical structure editor (Java applet) is described. The small size (approximately 200 KB) of the applet allows its use to display and edit chemical structures in various Internet applications. The editor supports the MCDL format, in which structures are presented in compact canonical form and is capable of restoring bond orders as well as of managing atom and bond drawing overlap. A small database of cage and large cyclic fragment is used for optimal representation of difficult-to-draw molecules. The improved algorithm of the structure diagram generation can be used for other chemical notations that lack atomic coordinates (SMILES, InChI).

  5. Quantum descriptors for biological macromolecules from linear-scaling electronic structure methods.

    PubMed

    Khandogin, Jana; York, Darrin M

    2004-09-01

    The characterization of electrostatic and chemical properties at the surface of biological macromolecules is of interest in elucidating the fundamental biological structure-function relationships as well as in problems of rational drug design. This paper presents a set of macromolecular quantum descriptors for the characterization of biological macromolecules in solution that can be obtained with modest computational cost from linear-scaling semi-empirical quantum/solvation methods. The descriptors discussed include: solvent-polarized electrostatic surface potential maps, equilibrated atomic charges, Fukui reactivity indices, approximate local hardness maps, and relative proton potentials. These properties are applied to study the conformational dependence of the electrostatic surface potential of the solvated phosphate-binding protein mutant (T141D), the regioselectivity of the zinc finger domains of HIV-1 nucleocapsid (NC) protein, and the order of pKa values of acidic residues in turkey ovomucoid third domain (OMTKY3) and of the zinc-binding residues in the carboxyl terminal zinc finger of NC. In all cases, insight beyond that obtainable from purely classical models is gained and can be used to rationalize the experimental observations. The macromolecular quantum descriptors presented here greatly extend the arsenal of tools for macromolecular characterization and offer promise in applications to modern structure-based drug design.

  6. A rotation-translation invariant molecular descriptor of partial charges and its use in ligand-based virtual screening

    PubMed Central

    2014-01-01

    Background Measures of similarity for chemical molecules have been developed since the dawn of chemoinformatics. Molecular similarity has been measured by a variety of methods including molecular descriptor based similarity, common molecular fragments, graph matching and 3D methods such as shape matching. Similarity measures are widespread in practice and have proven to be useful in drug discovery. Because of our interest in electrostatics and high throughput ligand-based virtual screening, we sought to exploit the information contained in atomic coordinates and partial charges of a molecule. Results A new molecular descriptor based on partial charges is proposed. It uses the autocorrelation function and linear binning to encode all atoms of a molecule into two rotation-translation invariant vectors. Combined with a scoring function, the descriptor allows to rank-order a database of compounds versus a query molecule. The proposed implementation is called ACPC (AutoCorrelation of Partial Charges) and released in open source. Extensive retrospective ligand-based virtual screening experiments were performed and other methods were compared with in order to validate the method and associated protocol. Conclusions While it is a simple method, it performed remarkably well in experiments. At an average speed of 1649 molecules per second, it reached an average median area under the curve of 0.81 on 40 different targets; hence validating the proposed protocol and implementation. PMID:24887178

  7. A novel texture descriptor for detection of glandular structures in colon histology images

    NASA Astrophysics Data System (ADS)

    Sirinukunwattana, Korsuk; Snead, David R.; Rajpoot, Nasir M.

    2015-03-01

    The first step prior to most analyses on most histopathology images is the detection of area of interest. In this work, we present a superpixel-based approach for glandular structure detection in colon histology images. An image is first segmented into superpixels with the constraint on the presence of glandular boundaries. Texture and color information is then extracted from each superpixel to calculate the probability of that superpixel belonging to glandular regions, resulting in a glandular probability map. In addition, we present a novel texture descriptor derived from a region covariance matrix of scattering coefficients. Our approach shows encouraging results for the detection of glandular structures in colon tissue samples.

  8. Methanol Oxidative Dehydrogenation on Oxide Catalysts: Molecular and Dissociative Routes and Hydrogen Addition Energies as Descriptors of Reactivity

    SciTech Connect

    Deshlahra, Prashant; Iglesia, Enrique

    2014-11-13

    The oxidative dehydrogenation (ODH) of alkanols on oxide catalysts is generally described as involving H-abstraction from alkoxy species formed via O–H dissociation. Kinetic and isotopic data cannot discern between such routes and those involving kinetically-relevant H-abstraction from undissociated alkanols. Here, we combine such experiments with theoretical estimates of activation energies and entropies to show that the latter molecular routes prevail over dissociative routes for methanol reactions on polyoxometalate (POM) clusters at all practical reaction temperatures. The stability of the late transition states that mediate H-abstraction depend predominantly on the stability of the O–H bond formed, making H-addition energies (HAE) accurate and single-valued descriptors of reactivity. Density functional theory-derived activation energies depend linearly on HAE values at each O-atom location on clusters with a range of composition (H3PMo12, H4SiMo12, H3PW12, H4PV1Mo11, and H4PV1W11); both barriers and HAE values reflect the lowest unoccupied molecular orbital energy of metal centers that accept the electron and the protonation energy of O-atoms that accept the proton involved in the H-atom transfer. Bridging O-atoms form O–H bonds that are stronger than those of terminal atoms and therefore exhibit more negative HAE values and higher ODH reactivity on all POM clusters. For each cluster composition, ODH turnover rates reflect the reactivity-averaged HAE of all accessible O-atoms, which can be evaluated for each cluster composition to provide a rigorous and accurate predictor of ODH reactivity for catalysts with known structure. These relations together with oxidation reactivity measurements can then be used to estimate HAE values and to infer plausible structures for catalysts with uncertain active site structures.

  9. BioGPS descriptors for rational engineering of enzyme promiscuity and structure based bioinformatic analysis.

    PubMed

    Ferrario, Valerio; Siragusa, Lydia; Ebert, Cynthia; Baroni, Massimo; Foscato, Marco; Cruciani, Gabriele; Gardossi, Lucia

    2014-01-01

    A new bioinformatic methodology was developed founded on the Unsupervised Pattern Cognition Analysis of GRID-based BioGPS descriptors (Global Positioning System in Biological Space). The procedure relies entirely on three-dimensional structure analysis of enzymes and does not stem from sequence or structure alignment. The BioGPS descriptors account for chemical, geometrical and physical-chemical features of enzymes and are able to describe comprehensively the active site of enzymes in terms of "pre-organized environment" able to stabilize the transition state of a given reaction. The efficiency of this new bioinformatic strategy was demonstrated by the consistent clustering of four different Ser hydrolases classes, which are characterized by the same active site organization but able to catalyze different reactions. The method was validated by considering, as a case study, the engineering of amidase activity into the scaffold of a lipase. The BioGPS tool predicted correctly the properties of lipase variants, as demonstrated by the projection of mutants inside the BioGPS "roadmap".

  10. Advances in structural damage assessment using strain measurements and invariant shape descriptors

    NASA Astrophysics Data System (ADS)

    Patki, Amol Suhas

    to the area surrounding the damage, while damage in orthotropic materials tends to have more global repercussions. This calls for analysis of full-field strain distributions adding to the complexity of post-damage life estimation. This study explores shape descriptors used in the field of medical imagery, military targeting and biometric recognition for obtaining a qualitative and quantitative comparison between full-field strain data recorded from damaged composite panels using sophisticated experimental techniques. These descriptors are capable of decomposing images with 103 to 106 pixels into a feature vector with only a few hundred elements. This ability of shape descriptors to achieve enormous reduction in strain data, while providing unique representation, makes them a practical choice for the purpose of structural damage assessment. Consequently, it is relatively easy to statistically compare the shape descriptors of the full-field strain maps using similarity measures rather than the strain maps themselves. However, the wide range of geometric and design features in engineering components pose difficulties in the application of traditional shape description techniques. Thus a new shape descriptor is developed which is applicable to a wide range of specimen geometries. This work also illustrates how shape description techniques can be applied to full-field finite element model validations and updating.

  11. Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

    PubMed

    Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

    2013-10-30

    In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.

  12. Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors

    PubMed Central

    2013-01-01

    Background In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Results Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. Conclusions A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation. PMID:24171724

  13. Adaptive modelling of structured molecular representations for toxicity prediction

    NASA Astrophysics Data System (ADS)

    Bertinetto, Carlo; Duce, Celia; Micheli, Alessio; Solaro, Roberto; Tiné, Maria Rosaria

    2012-12-01

    We investigated the possibility of modelling structure-toxicity relationships by direct treatment of the molecular structure (without using descriptors) through an adaptive model able to retain the appropriate structural information. With respect to traditional descriptor-based approaches, this provides a more general and flexible way to tackle prediction problems that is particularly suitable when little or no background knowledge is available. Our method employs a tree-structured molecular representation, which is processed by a recursive neural network (RNN). To explore the realization of RNN modelling in toxicological problems, we employed a data set containing growth impairment concentrations (IGC50) for Tetrahymena pyriformis.

  14. Electronic structure descriptor for the discovery of narrow-band red-emitting phosphors

    DOE PAGES

    Wang, Zhenbin; Chu, Iek -Heng; Zhou, Fei; ...

    2016-05-09

    Narrow-band red-emitting phosphors are a critical component of phosphor-converted light-emitting diodes for highly efficient illumination-grade lighting. In this work, we report the discovery of a quantitative descriptor for narrow-band Eu2+-activated emission identified through a comparison of the electronic structures of known narrow-band and broad-band phosphors. We find that a narrow emission bandwidth is characterized by a large splitting of more than 0.1 eV between the two highest Eu2+ 4f7 bands. By incorporating this descriptor in a high-throughput first-principles screening of 2259 nitride compounds, we identify five promising new nitride hosts for Eu2+-activated red-emitting phosphors that are predicted to exhibit goodmore » chemical stability, thermal quenching resistance, and quantum efficiency, as well as narrow-band emission. Lastly, our findings provide important insights into the emission characteristics of rare-earth activators in phosphor hosts and a general strategy to the discovery of phosphors with a desired emission peak and bandwidth.« less

  15. Electronic structure descriptor for the discovery of narrow-band red-emitting phosphors

    SciTech Connect

    Wang, Zhenbin; Chu, Iek -Heng; Zhou, Fei; Ong, Shyue Ping

    2016-05-09

    Narrow-band red-emitting phosphors are a critical component of phosphor-converted light-emitting diodes for highly efficient illumination-grade lighting. In this work, we report the discovery of a quantitative descriptor for narrow-band Eu2+-activated emission identified through a comparison of the electronic structures of known narrow-band and broad-band phosphors. We find that a narrow emission bandwidth is characterized by a large splitting of more than 0.1 eV between the two highest Eu2+ 4f7 bands. By incorporating this descriptor in a high-throughput first-principles screening of 2259 nitride compounds, we identify five promising new nitride hosts for Eu2+-activated red-emitting phosphors that are predicted to exhibit good chemical stability, thermal quenching resistance, and quantum efficiency, as well as narrow-band emission. Lastly, our findings provide important insights into the emission characteristics of rare-earth activators in phosphor hosts and a general strategy to the discovery of phosphors with a desired emission peak and bandwidth.

  16. Electronic structure descriptor for the discovery of narrow-band red-emitting phosphors

    SciTech Connect

    Wang, Zhenbin; Chu, Iek -Heng; Zhou, Fei; Ong, Shyue Ping

    2016-05-09

    Narrow-band red-emitting phosphors are a critical component of phosphor-converted light-emitting diodes for highly efficient illumination-grade lighting. In this work, we report the discovery of a quantitative descriptor for narrow-band Eu2+-activated emission identified through a comparison of the electronic structures of known narrow-band and broad-band phosphors. We find that a narrow emission bandwidth is characterized by a large splitting of more than 0.1 eV between the two highest Eu2+ 4f7 bands. By incorporating this descriptor in a high-throughput first-principles screening of 2259 nitride compounds, we identify five promising new nitride hosts for Eu2+-activated red-emitting phosphors that are predicted to exhibit good chemical stability, thermal quenching resistance, and quantum efficiency, as well as narrow-band emission. Lastly, our findings provide important insights into the emission characteristics of rare-earth activators in phosphor hosts and a general strategy to the discovery of phosphors with a desired emission peak and bandwidth.

  17. Scene text recognition in mobile applications by character descriptor and structure configuration.

    PubMed

    Yi, Chucai; Tian, Yingli

    2014-07-01

    Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

  18. Molecular descriptor data explain market prices of a large commercial chemical compound library

    NASA Astrophysics Data System (ADS)

    Polanski, Jaroslaw; Kucia, Urszula; Duszkiewicz, Roksana; Kurczyk, Agata; Magdziarz, Tomasz; Gasteiger, Johann

    2016-06-01

    The relationship between the structure and a property of a chemical compound is an essential concept in chemistry guiding, for example, drug design. Actually, however, we need economic considerations to fully understand the fate of drugs on the market. We are performing here for the first time the exploration of quantitative structure-economy relationships (QSER) for a large dataset of a commercial building block library of over 2.2 million chemicals. This investigation provided molecular statistics that shows that on average what we are paying for is the quantity of matter. On the other side, the influence of synthetic availability scores is also revealed. Finally, we are buying substances by looking at the molecular graphs or molecular formulas. Thus, those molecules that have a higher number of atoms look more attractive and are, on average, also more expensive. Our study shows how data binning could be used as an informative method when analyzing big data in chemistry.

  19. Molecular descriptor data explain market prices of a large commercial chemical compound library.

    PubMed

    Polanski, Jaroslaw; Kucia, Urszula; Duszkiewicz, Roksana; Kurczyk, Agata; Magdziarz, Tomasz; Gasteiger, Johann

    2016-06-23

    The relationship between the structure and a property of a chemical compound is an essential concept in chemistry guiding, for example, drug design. Actually, however, we need economic considerations to fully understand the fate of drugs on the market. We are performing here for the first time the exploration of quantitative structure-economy relationships (QSER) for a large dataset of a commercial building block library of over 2.2 million chemicals. This investigation provided molecular statistics that shows that on average what we are paying for is the quantity of matter. On the other side, the influence of synthetic availability scores is also revealed. Finally, we are buying substances by looking at the molecular graphs or molecular formulas. Thus, those molecules that have a higher number of atoms look more attractive and are, on average, also more expensive. Our study shows how data binning could be used as an informative method when analyzing big data in chemistry.

  20. Molecular descriptor data explain market prices of a large commercial chemical compound library

    PubMed Central

    Polanski, Jaroslaw; Kucia, Urszula; Duszkiewicz, Roksana; Kurczyk, Agata; Magdziarz, Tomasz; Gasteiger, Johann

    2016-01-01

    The relationship between the structure and a property of a chemical compound is an essential concept in chemistry guiding, for example, drug design. Actually, however, we need economic considerations to fully understand the fate of drugs on the market. We are performing here for the first time the exploration of quantitative structure-economy relationships (QSER) for a large dataset of a commercial building block library of over 2.2 million chemicals. This investigation provided molecular statistics that shows that on average what we are paying for is the quantity of matter. On the other side, the influence of synthetic availability scores is also revealed. Finally, we are buying substances by looking at the molecular graphs or molecular formulas. Thus, those molecules that have a higher number of atoms look more attractive and are, on average, also more expensive. Our study shows how data binning could be used as an informative method when analyzing big data in chemistry. PMID:27334348

  1. a Robust Descriptor Based on Spatial and Frequency Structural Information for Visible and Thermal Infrared Image Matching

    NASA Astrophysics Data System (ADS)

    Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.

    2017-09-01

    Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.

  2. Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

    PubMed Central

    Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

    2012-01-01

    Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

  3. Dynamic molecular graphs: "hopping" structures.

    PubMed

    Cortés-Guzmán, Fernando; Rocha-Rinza, Tomas; Guevara-Vela, José Manuel; Cuevas, Gabriel; Gómez, Rosa María

    2014-05-05

    This work aims to contribute to the discussion about the suitability of bond paths and bond-critical points as indicators of chemical bonding defined within the theoretical framework of the quantum theory of atoms in molecules. For this purpose, we consider the temporal evolution of the molecular structure of [Fe{C(CH2 )3 }(CO)3 ] throughout Born-Oppenheimer molecular dynamics (BOMD), which illustrates the changing behaviour of the molecular graph (MG) of an electronic system. Several MGs with significant lifespans are observed across the BOMD simulations. The bond paths between the trimethylenemethane and the metallic core are uninterruptedly formed and broken. This situation is reminiscent of a "hopping" ligand over the iron atom. The molecular graph wherein the bonding between trimethylenemethane and the iron atom takes place only by means of the tertiary carbon atom has the longest lifespan of all the considered structures, which is consistent with the MG found by X-ray diffraction experiments and quantum chemical calculations. In contrast, the η(4) complex predicted by molecular-orbital theory has an extremely brief lifetime. The lifespan of different molecular structures is related to bond descriptors on the basis of the topology of the electron density such as the ellipticities at the FeCH2 bond-critical points and electron delocalisation indices. This work also proposes the concept of a dynamic molecular graph composed of the different structures found throughout the BOMD trajectories in analogy to a resonance hybrid of Lewis structures. It is our hope that the notion of dynamic molecular graphs will prove useful in the discussion of electronic systems, in particular for those in which analysis on the basis of static structures leads to controversial conclusions.

  4. In vitro modeling of angiotensin-converting enzyme inhibitor's absorption with chromatographic retention data and selected molecular descriptors.

    PubMed

    Odović, Jadranka; Marković, Bojan; Vladimirov, Sote; Karljiković-Rajić, Katarina

    2014-03-15

    Set of nine angiotensin-converting enzyme inhibitors (enalapril, quinapril, fosinopril, lisinopril, cilazapril, ramipril, benazepril, perindopril and moexipril) were studied to evaluate the correlation between their intestinal absorption and salting-out thin-layer chromatography hydrophobicity parameters (RM(0) or C0) obtained by ascending technique applying four different salts, (NH4)2SO4, NH4NO3, NH4Cl and NaCl as mobile phases. The best correlations between KOWWIN logP and both hydrophobicity parameters, RM(0) and C0, (R(2)>0.850) were observed for NaCl (1.0-3.0M) while the lowest R(2) was obtained for (NH4)2SO4 (0.649 and 0.427, respectively) due to highest salting-out effect of (NH4)2SO4. The effect of selected inorganic salts in the salting-out mobile phases, on the solutes solubility and retention was evaluated. The topological polar surface area should be selected as independent variable (only this molecular descriptor showed low correlation with chromatographic hydrophobicity parameters) for multiple linear regression analysis, to obtain reliable correlation between angiotensin-converting enzyme inhibitor's intestinal absorption data and salting-out thin-layer chromatograpic hydrophobicity parameters. These correlations provide R(2)=0.823 for RM(0) or R(2)=0.799 for C0 indicating good relationship between predicted and literature available intestinal absorption (ranged from 22% to 70%) of investigated angiotensin-converting enzyme inhibitors. The proposed in vitro model was checked with three in addition experimentally analyzed drugs, zofenopril, trandolapril and captoril. The satisfactory absorption prediction was obtained for zofenopril and trandolapril, while divergence established for captopril resulted from considerably different structure.

  5. Novel 3D bio-macromolecular bilinear descriptors for protein science: Predicting protein structural classes.

    PubMed

    Marrero-Ponce, Yovani; Contreras-Torres, Ernesto; García-Jacas, César R; Barigye, Stephen J; Cubillán, Néstor; Alvarado, Ysaías J

    2015-06-07

    In the present study, we introduce novel 3D protein descriptors based on the bilinear algebraic form in the ℝ(n) space on the coulombic matrix. For the calculation of these descriptors, macromolecular vectors belonging to ℝ(n) space, whose components represent certain amino acid side-chain properties, were used as weighting schemes. Generalization approaches for the calculation of inter-amino acidic residue spatial distances based on Minkowski metrics are proposed. The simple- and double-stochastic schemes were defined as approaches to normalize the coulombic matrix. The local-fragment indices for both amino acid-types and amino acid-groups are presented in order to permit characterizing fragments of interest in proteins. On the other hand, with the objective of taking into account specific interactions among amino acids in global or local indices, geometric and topological cut-offs are defined. To assess the utility of global and local indices a classification model for the prediction of the major four protein structural classes, was built with the Linear Discriminant Analysis (LDA) technique. The developed LDA-model correctly classifies the 92.6% and 92.7% of the proteins on the training and test sets, respectively. The obtained model showed high values of the generalized square correlation coefficient (GC(2)) on both the training and test series. The statistical parameters derived from the internal and external validation procedures demonstrate the robustness, stability and the high predictive power of the proposed model. The performance of the LDA-model demonstrates the capability of the proposed indices not only to codify relevant biochemical information related to the structural classes of proteins, but also to yield suitable interpretability. It is anticipated that the current method will benefit the prediction of other protein attributes or functions.

  6. Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

    NASA Astrophysics Data System (ADS)

    Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

    2008-06-01

    A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

  7. Predicting optimal finite field strengths for calculating the first and second hyperpolarizabilities using simple molecular descriptors

    NASA Astrophysics Data System (ADS)

    Mohammed, Ahmed A. K.; Limacher, Peter A.; Ayers, Paul W.

    2017-08-01

    The finite field method was used to calculate the static first and second hyperpolarizabilities (β and γ) for organic molecules. The dependence of β and γ on the applied electric field strength was investigated and used to determine the optimal field strength for each individual molecule. For γ, we designed a protocol that uses the maximum atomic distance within the molecule along the direction of the applied field to estimate optimal field strengths. However, β is nearly independent of the descriptors we considered, and largely depends on the composition (e.g., the presence of certain functional groups) of the molecule.

  8. Modular Chemical Descriptor Language (MCDL): Stereochemical modules

    SciTech Connect

    Gakh, Andrei A; Burnett, Michael N; Trepalin, Sergei V.; Yarkov, Alexander V

    2011-01-01

    In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL) for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures. In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDL processing module software packages. Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format.

  9. Modular Chemical Descriptor Language (MCDL): Stereochemical modules

    PubMed Central

    2011-01-01

    Background In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL) for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures. Results In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDL processing module software packages. Conclusions Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format. PMID:21276272

  10. Modular Chemical Descriptor Language (MCDL): Stereochemical modules.

    PubMed

    Gakh, Andrei A; Burnett, Michael N; Trepalin, Sergei V; Yarkov, Alexander V

    2011-01-31

    In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL) for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures. In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDL processing module software packages. Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format.

  11. Stargate GTM: Bridging Descriptor and Activity Spaces.

    PubMed

    Gaspar, Héléna A; Baskin, Igor I; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

    2015-11-23

    Predicting the activity profile of a molecule or discovering structures possessing a specific activity profile are two important goals in chemoinformatics, which could be achieved by bridging activity and molecular descriptor spaces. In this paper, we introduce the "Stargate" version of the Generative Topographic Mapping approach (S-GTM) in which two different multidimensional spaces (e.g., structural descriptor space and activity space) are linked through a common 2D latent space. In the S-GTM algorithm, the manifolds are trained simultaneously in two initial spaces using the probabilities in the 2D latent space calculated as a weighted geometric mean of probability distributions in both spaces. S-GTM has the following interesting features: (1) activities are involved during the training procedure; therefore, the method is supervised, unlike conventional GTM; (2) using molecular descriptors of a given compound as input, the model predicts a whole activity profile, and (3) using an activity profile as input, areas populated by relevant chemical structures can be detected. To assess the performance of S-GTM prediction models, a descriptor space (ISIDA descriptors) of a set of 1325 GPCR ligands was related to a B-dimensional (B = 1 or 8) activity space corresponding to pKi values for eight different targets. S-GTM outperforms conventional GTM for individual activities and performs similarly to the Lasso multitask learning algorithm, although it is still slightly less accurate than the Random Forest method.

  12. Spherical harmonics based descriptor for neural network potentials: Structure and dynamics of Au147 nanocluster

    NASA Astrophysics Data System (ADS)

    Jindal, Shweta; Chiriki, Siva; Bulusu, Satya S.

    2017-05-01

    We propose a highly efficient method for fitting the potential energy surface of a nanocluster using a spherical harmonics based descriptor integrated with an artificial neural network. Our method achieves the accuracy of quantum mechanics and speed of empirical potentials. For large sized gold clusters (Au147), the computational time for accurate calculation of energy and forces is about 1.7 s, which is faster by several orders of magnitude compared to density functional theory (DFT). This method is used to perform the global minimum optimizations and molecular dynamics simulations for Au147, and it is found that its global minimum is not an icosahedron. The isomer that can be regarded as the global minimum is found to be 4 eV lower in energy than the icosahedron and is confirmed from DFT. The geometry of the obtained global minimum contains 105 atoms on the surface and 42 atoms in the core. A brief study on the fluxionality in Au147 is performed, and it is concluded that Au147 has a dynamic surface, thus opening a new window for studying its reaction dynamics.

  13. A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors.

    PubMed

    Carriger, John F; Martin, Todd M; Barron, Mace G

    2016-11-01

    The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the dataset of 1098 chemicals with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2%. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally complex dataset can simplify analysis and interpretation by identifying a subset of the key chemical descriptors associated with broad aquatic toxicity MoAs, and by providing a computational chemistry-based network classification model with reasonable prediction accuracy.

  14. [A new SVRDF 3D-descriptor of amino acids and its application to peptide quantitative structure activity relationship].

    PubMed

    Tong, Jian-Bo; Zhang, Sheng-Wan; Cheng, Su-Li; Li, Gai-Xian

    2007-01-01

    To establish a new amino acid structure descriptor that can be applied to polypeptide quantitative structure activity relationship (QSAR) studies, a new descriptor, SVRDF, was derived from a principal components analysis of a matrix of 150 radial distribution function index of amino acids. The scale was then applied in three panels of peptide QSAR that were molded by partial least squares regression. The obtained models with the correlation coefficients (R2(cum)), cross-validation correlation coefficients (Q2(cum)) were 0.766 and 0.724 for 48 bitter tasting dipeptides; 0.941 and 0.811 for 21 oxytocin analogues; 0.996 and 0.919 for 20 thromboplastin inhibitors. Satisfactory results showed that information related to biological activity can be systemically expressed by SVRDF scales, which may be an useful structural expression methodology for the study of peptides QSAR.

  15. Combining and comparing morphometric shape descriptors with a molecular phylogeny: the case of fruit type evolution in Bornean Lithocarpus (Fagaceae).

    PubMed

    Cannon, C H; Manos, P S

    2001-01-01

    Fruit type in the genus Lithocarpus (Fagaceae) includes both classic oak acorns and novel modifications. Bornean taxa with modified fruits can be separated into two sections (Synaedrys and Lithocarpus) based on subtle shape differences. By following strict criteria for homology and representation, this variation in shape can be captured and the sections distinguished by using elliptic Fourier or eigenshape analysis. Phenograms of fruit shape, constructed by using restricted maximum likelihood techniques and these morphometric descriptors, were incorporated into combined and comparative analyses with molecular sequence data from the internal transcribed spacer (ITS) region of the nuclear rDNA, using branch-weighted matrix representation. The combined analysis strongly suggested independent derivation of the novel fruit type in the two sections from different acornlike ancestors, while the comparative analysis indicated frequent decoupling between the molecular and morphological changes as inferred at well-supported nodes. The acorn fruit type has undergone little modification between ingroup and outgroup, despite large molecular distance. Greater morphological than molecular change was inferred at critical transitions between acorn and novel fruit types, particularly for section Lithocarpus. The combination of these two different types of data improved our understanding of the macroevolution of fruit type in this difficult group, and the comparative analysis highlighted the significant incongruities in evolutionary pattern between the two datasets.

  16. Electrospray Ionization Efficiency Is Dependent on Different Molecular Descriptors with Respect to Solvent pH and Instrumental Configuration

    PubMed Central

    Kiontke, Andreas; Oliveira-Birkmeier, Ariana; Opitz, Andreas

    2016-01-01

    Over the past decades, electrospray ionization for mass spectrometry (ESI-MS) has become one of the most commonly employed techniques in analytical chemistry, mainly due to its broad applicability to polar and semipolar compounds and the superior selectivity which is achieved in combination with high resolution separation techniques. However, responsiveness of an analytical method also determines its suitability for the quantitation of chemical compounds; and in electrospray ionization for mass spectrometry, it can vary significantly among different analytes with identical solution concentrations. Therefore, we investigated the ESI-response behavior of 56 nitrogen-containing compounds including aromatic amines and pyridines, two compound classes of high importance to both, synthetic organic chemistry as well as to pharmaceutical sciences. These compounds are increasingly analyzed employing ESI mass spectrometry detection due to their polar, basic character. Signal intensities of the peaks from the protonated molecular ion (MH+) were acquired under different conditions and related to compound properties such as basicity, polarity, volatility and molecular size exploring their quantitative impact on ionization efficiency. As a result, we found that though solution basicity of a compound is the main factor initially determining the ESI response of the protonated molecular ion, other factors such as polarity and vaporability become more important under acidic solvent conditions and may nearly outweigh the importance of basicity under these conditions. Moreover, we show that different molecular descriptors may become important when using different types of instruments for such investigations, a fact not detailed so far in the available literature. PMID:27907110

  17. Convergent study of Ru-ligand interactions through QTAIM, ELF, NBO molecular descriptors and TDDFT analysis of organometallic dyes

    NASA Astrophysics Data System (ADS)

    Sánchez-Coronilla, Antonio; Sánchez-Márquez, Jesús; Zorrilla, David; Martín, Elisa I.; de los Santos, Desireé M.; Navas, Javier; Fernández-Lorenzo, Concha; Alcántara, Rodrigo; Martín-Calleja, Joaquín

    2014-08-01

    We report a theoretical study of a series of Ru complexes of interest in dye-sensitised solar cells, in organic light-emitting diodes, and in the war against cancer. Other metal centres, such as Cr, Co, Ni, Rh, Pd, and Pt, have been included for comparison purposes. The metal-ligand trends in organometallic chemistry for those compounds are shown synergistically by using three molecular descriptors: quantum theory of atoms in molecules (QTAIM), electron localisation function (ELF) and second-order perturbation theory analysis of the natural bond orbital (NBO). The metal-ligand bond order is addressed through both delocalisation index (DI) of QTAIM and fluctuation index (λ) of ELF. Correlation between DI and λ for Ru-N bond in those complexes is introduced for the first time. Electron transfer and stability was also assessed by the second-order perturbation theory analysis of the NBO. Electron transfer from the lone pair NBO of the ligands toward the antibonding lone pair NBO of the metal plays a relevant role in stabilising the complexes, providing useful insights into understanding the effect of the 'expanded ligand' principle in supramolecular chemistry. Finally, absorption wavelengths associated to the metal-to-ligand charge transfer transitions and the highest occupied molecular orbital (HOMO)--lowest unoccupied molecular orbital (LUMO) characteristics were studied by time-dependent density functional theory.

  18. Free radical reactions of isoxazole and pyrazole derivatives of hispolon: kinetics correlated with molecular descriptors.

    PubMed

    Shaikh, Shaukat Ali M; Barik, Atanu; Singh, Beena G; Modukuri, Ramani V; Balaji, Neduri V; Subbaraju, Gottumukkala V; Naik, Devidas B; Priyadarsini, K Indira

    2016-12-01

    Hispolon (HS), a natural polyphenol found in medicinal mushrooms, and its isoxazole (HI) and pyrazole (HP) derivatives have been examined for free radical reactions and in vitro antioxidant activity. Reaction of these compounds with one-electron oxidant, azide radicals ([Formula: see text]) and trichloromethyl peroxyl radicals ([Formula: see text]), model peroxyl radicals, studied by nanosecond pulse radiolysis technique, indicated formation of phenoxyl radicals absorbing at 420 nm with half life of few hundred microseconds (μs). The formation of phenoxyl radicals confirmed that the phenolic OH is the active centre for free radical reactions. Rate constant for the reaction of these radicals with these compounds were in the order kHI ≅ kHP > kHS. Further the compounds were examined for their ability to inhibit lipid peroxidation in model membranes and also for the scavenging of 2,2'-diphenyl-1-picrylhydrazyl (DPPH) radical and superoxide ([Formula: see text]) radicals. The results suggested that HP and HI are less efficient than HS towards these radical reactions. Quantum chemical calculations were performed on these compounds to understand the mechanism of reaction with different radicals. Lower values of adiabatic ionization potential (AIP) and elevated highest occupied molecular orbital (HOMO) for HI and HP compared with HS controlled their activity towards [Formula: see text] and [Formula: see text] radicals, whereas the contribution of overall anion concentration was responsible for higher activity of HS for DPPH, [Formula: see text], and lipid peroxyl radical. The results confirm the role of different structural moieties on the antioxidant activity of hispolon derivatives.

  19. On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors Towards Materials Quantitative Structure Property Relationships

    NASA Astrophysics Data System (ADS)

    Krein, Michael

    After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright cheating in the form of explicitly removing data to fit models. These actions do not serve the community well, nor are they beneficial to future predictions based on established models. In practice, in order to select combinations of descriptors and machine learning methods that might work best, one must consider the nature and size of the training and test datasets, be aware of existing hypotheses about the data, and resist the temptation to bias structure representation and modeling to explicitly fit the hypotheses. The definition and application of these best practices is important for obtaining actionable modeling outcomes, and for setting user expectations of modeling accuracy when predicting the endpoint values of unknowns. A wide variety of statistical learning approaches, descriptor types, and model validation strategies are explored herein, with the goals of helping end users understand the factors involved in creating and using QSPR models effectively, and to better understand relationships within the data, especially by looking at the problem space from multiple perspectives. Molecular relationships are commonly envisioned in a continuous high-dimensional space of numerical descriptors, referred to as chemistry space. Descriptor and similarity metric choice influence the partitioning of this space into regions corresponding to local structural similarity. These regions, known as domains of applicability, are most likely to be successfully modeled by a QSPR. In Chapter 2, the network topology and scaling relationships of several chemistry spaces are thoroughly investigated. Chemistry spaces studied include the

  20. Pattern searching/alignment with RNA primary and secondary structures: an effective descriptor for tRNA.

    PubMed

    Gautheret, D; Major, F; Cedergren, R

    1990-10-01

    A convenient pattern-matching program using primary and higher-order structural features has been developed based on a 'backtracking' algorithm. A second implementation of the algorithm uses descriptors of structural features (including primary sequences) to align a list of homologous or highly similar sequences. An application of the pattern matcher to the search for tRNA and group I intron structural motifs in sequence data banks is presented. The design of a highly discriminate tRNA motif, common to all cellular tRNAs and not found in a control sequence bank, was accomplished using the pattern matcher in conjunction with the alignment program.

  1. Relationship between antimold activity and molecular structure of cinnamaldehyde analogues.

    PubMed

    Zhang, Yuanyuan; Li, Shujun; Kong, Xianchao

    2013-03-01

    A quantitative structure-activity relationship (QSAR) modeling of the antimold activity of cinnamaldehyde analogues against of Aspergillus niger and Paecilomyces variotii was presented. The molecular descriptors of cinnamaldehyde analogues were calculated by the CODESSA program, and these descriptors were selected by best multi-linear regression method (BMLR). Satisfactory multilinear regression models of Aspergillus niger and Paecilomyces variotii were obtained with R(2)=0.9099 and 0.9444, respectively. The models were also satisfactorily validated using internal validation and leave one out validation. The QSAR models provide the guidance for further synthetic work. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. A novel and robust rotation and scale invariant structuring elements based descriptor for pedestrian classification in infrared images

    NASA Astrophysics Data System (ADS)

    Soundrapandiyan, Rajkumar; Chandra Mouli, P. V. S. S. R.

    2016-09-01

    In this paper, a novel and robust rotation and scale invariant structuring elements based descriptor (RSSED) for pedestrian classification in infrared (IR) images is proposed. In addition, a segmentation method using difference of Gaussian (DoG) and horizontal intensity projection is proposed. The three major steps are moving object segmentation, feature extraction and classification of objects as pedestrian or non-pedestrian. The segmentation result is used to extract the RSSED feature descriptor. To extract features, the segmentation result is encoded using local directional pattern (LDP). This helps in the identification of local textural patterns. The LDP encoded image is further quantized adaptively to four levels. Finally the proposed RSSED is used to formalize the descriptor from the quantized image. Support vector machine is employed for classification of the moving objects in a given IR image into pedestrian and non-pedestrian classes. The segmentation results shows the robustness in extracting the moving objects. The classification results obtained from SVM classifier shows the efficacy of the proposed method.

  3. Essential Set of Molecular Descriptors for ADME Prediction in Drug and Environmental Chemical Space

    EPA Science Inventory

    Historically, the disciplines of pharmacology and toxicology have embraced quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR) to predict ADME properties or biological activities of untested chemicals. The question arises ...

  4. Essential Set of Molecular Descriptors for ADME Prediction in Drug and Environmental Chemical Space

    EPA Science Inventory

    Historically, the disciplines of pharmacology and toxicology have embraced quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR) to predict ADME properties or biological activities of untested chemicals. The question arises ...

  5. Characterization of structural vibration: Field descriptors based on energy density and intensity

    NASA Astrophysics Data System (ADS)

    Linjama, Jukka

    Measurement of energy flow in acoustical and vibrational fields is usually based on the detection of one linear field quantity (e.g. sound pressure) and its spatial gradient, two transducers being used for the measurement. This report first reviews the quantities which can be obtained from the measurement of acoustical intensity with a two-microphone probe: intensity and the energy densities. A set of 'field descriptors', relative quantities giving a measure of propagating (active) character of the waves in the sound field, is proposed. These energetic quantities are based entirely on the transversal velocity measured and the gradient of that velocity, and are available when the two-transducer method of bending wave intensity is used. Examples of the energy densities and field descriptors measured in an aluminum plate are presented, and proposals for further work are given.

  6. Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

    PubMed Central

    Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

    2017-01-01

    Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

  7. Partition Coefficients of Organics between Water and Carbon Dioxide Revisited: Correlation with Solute Molecular Descriptors and Solvent Cohesive Properties.

    PubMed

    Roth, Michal

    2016-12-06

    High-pressure phase behavior of systems containing water, carbon dioxide and organics has been important in several environment- and energy-related fields including carbon capture and storage, CO2 sequestration and CO2-assisted enhanced oil recovery. Here, partition coefficients (K-factors) of organic solutes between water and supercritical carbon dioxide have been correlated with extended linear solvation energy relationships (LSERs). In addition to the Abraham molecular descriptors of the solutes, the explanatory variables also include the logarithm of solute vapor pressure, the solubility parameters of carbon dioxide and water, and the internal pressure of water. This is the first attempt to include also the properties of water as explanatory variables in LSER correlations of K-factor data in CO2-water-organic systems. Increasing values of the solute hydrogen bond acidity, the solute hydrogen bond basicity, the solute dipolarity/polarizability, the internal pressure of water and the solubility parameter of water all tend to reduce the K-factor, that is, to favor the solute partitioning to the water-rich phase. On the contrary, increasing values of the solute characteristic volume, the solute vapor pressure and the solubility parameter of CO2 tend to raise the K-factor, that is, to favor the solute partitioning to the CO2-rich phase.

  8. Chemometric Methods and Theoretical Molecular Descriptors in Predictive QSAR Modeling of the Environmental Behavior of Organic Pollutants

    NASA Astrophysics Data System (ADS)

    Gramatica, Paola

    This chapter surveys the QSAR modeling approaches (developed by the author's research group) for the validated prediction of environmental properties of organic pollutants. Various chemometric methods, based on different theoretical molecular descriptors, have been applied: explorative techniques (such as PCA for ranking, SOM for similarity analysis), modeling approaches by multiple-linear regression (MLR, in particular OLS), and classification methods (mainly k-NN, CART, CP-ANN). The focus of this review is on the main topics of environmental chemistry and ecotoxicology, related to the physico-chemical properties, the reactivity, and biological activity of chemicals of high environmental concern. Thus, the review deals with atmospheric degradation reactions of VOCs by tropospheric oxidants, persistence and long-range transport of POPs, sorption behavior of pesticides (Koc and leaching), bioconcentration, toxicity (acute aquatic toxicity, mutagenicity of PAHs, estrogen binding activity for endocrine disruptors compounds (EDCs)), and finally persistent bioaccumulative and toxic (PBT) behavior for the screening and prioritization of organic pollutants. Common to all the proposed models is the attention paid to model validation for predictive ability (not only internal, but also external for chemicals not participating in the model development) and checking of the chemical domain of applicability. Adherence to such a policy, requested also by the OECD principles, ensures the production of reliable predicted data, useful also in the new European regulation of chemicals, REACH.

  9. Physicochemical vs. Vibrational Descriptors for Prediction of Odor Receptor Responses.

    PubMed

    Gabler, Stephan; Soelter, Jan; Hussain, Taufia; Sachse, Silke; Schmuker, Michael

    2013-10-01

    Responses of olfactory receptors (ORs) can be predicted by applying machine learning methods on a multivariate encoding of an odorant's chemical structure. Physicochemical descriptors that encode features of the molecular graph are a popular choice for such an encoding. Here, we explore the EVA descriptor set, which encodes features derived from the vibrational spectrum of a molecule. We assessed the performance of Support Vector Regression (SVR) and Random Forest Regression (RFR) to predict the gradual response of Drosophila ORs. We compared a 27-dimensional variant of the EVA descriptor against a set of 1467 descriptors provided by the eDragon software package, and against a 32-dimensional subset thereof that has been proposed as the basis for an odor metric consisting of 32 descriptors (HADDAD). The best prediction performance was reproducibly achieved using SVR on the highest-dimensional feature set. The low-dimensional EVA and HADDAD feature sets predicted odor-OR interactions with similar accuracy. Adding charge and polarizability information to the EVA descriptor did not improve the results but rather decreased predictive power. Post-hoc in vivo measurements confirmed these results. Our findings indicate that EVA provides a meaningful low-dimensional representation of odor space, although EVA hardly outperformed "classical" descriptor sets.

  10. Large-scale structure-activity relationship study of hepatitis C virus NS5B polymerase inhibition using SMILES-based descriptors.

    PubMed

    Worachartcheewan, Apilak; Prachayasittikul, Virapong; Toropova, Alla P; Toropov, Andrey A; Nantasenamat, Chanin

    2015-11-01

    Hepatitis C virus (HCV) is composed of structural and non-structural proteins involved in viral transcription and propagation. In particular, NS5B is an RNA-dependent RNA polymerase for viral transcription and genome replication and is a target for designing anti-viral agents. In this study, classification and quantitative structure-activity relationship (QSAR) models of HCV NS5B inhibitors were constructed using the Correlation and Logic software. Molecular descriptors for a set of 970 HCV NS5B inhibitors were encoded using the simplified molecular input line entry system notation, and predictive models were built via the Monte Carlo method. The QSAR models provided acceptable correlation coefficients of [Formula: see text] and [Formula: see text] in the ranges of 0.6038-0.7344 and 0.6171-0.7294, respectively, while the classification models displayed sensitivity, specificity, and accuracy in ranges of 88.24-98.84, 83.87-93.94, and 86.50-94.41 %, respectively. Furthermore, molecular fragments as substructures involved in increased and decreased inhibitory activities were explored. The results provide information on QSAR and classification models for high-throughput screening and mechanistic insights into the inhibitory activity of HCV NS5B polymerase.

  11. Relationship between reaction rate constants of organic pollutants and their molecular descriptors during Fenton oxidation and in situ formed ferric-oxyhydroxides.

    PubMed

    Jia, Lijuan; Shen, Zhemin; Su, Pingru

    2016-05-01

    Fenton oxidation is a promising water treatment method to degrade organic pollutants. In this study, 30 different organic compounds were selected and their reaction rate constants (k) were determined for the Fenton oxidation process. Gaussian09 and Material Studio software sets were used to carry out calculations and obtain values of 10 different molecular descriptors for each studied compound. Ferric-oxyhydroxide coagulation experiments were conducted to determine the coagulation percentage. Based upon the adsorption capacity, all of the investigated organic compounds were divided into two groups (Group A and Group B). The percentage adsorption of organic compounds in Group A was less than 15% (wt./wt.) and that in the Group B was higher than 15% (wt./wt.). For Group A, removal of the compounds by oxidation was the dominant process while for Group B, removal by both oxidation and coagulation (as a synergistic process) took place. Results showed that the relationship between the rate constants (k values) and the molecular descriptors of Group A was more pronounced than for Group B compounds. For the oxidation-dominated process, EHOMO and Fukui indices (f(0)x, f(-)x, f(+)x) were the most significant factors. The influence of bond order was more significant for the synergistic process of oxidation and coagulation than for the oxidation-dominated process. The influences of all other molecular descriptors on the synergistic process were weaker than on the oxidation-dominated process.

  12. Modelling of retention of pesticides in reversed-phase high-performance liquid chromatography: quantitative structure-retention relationships based on solute quantum-chemical descriptors and experimental (solvatochromic and spin-probe) mobile phase descriptors.

    PubMed

    D'Archivio, Angelo Antonio; Ruggieri, Fabrizio; Mazzeo, Pietro; Tettamanti, Enzo

    2007-06-19

    A quantitative structure-retention relationship (QSRR) analysis based on multilinear regression (MLR) and artificial neural networks (ANNs) is carried out to model the combined effect of solute structure and eluent composition on the retention behaviour of pesticides in isocratic reversed-phase high-performance liquid chromatography (RP-HPLC). The octanol-water partition coefficient and four quantum chemical descriptors (the total dipole moment, the mean polarizability, the anisotropy of the polarizability and a descriptor of hydrogen-bonding based on the atomic charges on acidic and basic chemical functionalities) are considered as solute descriptors. In order to identify suitable mobile phase descriptors, encoding composition-dependent properties of both methanol- and acetonitrile-containing mobile phases, the Kamlet-Taft solvatochromic parameters (polarity-dipolarity, hydrogen-bond acidity and hydrogen-bond basicity, pi*, alpha and beta, respectively) and the 14N hyperfine-splitting constant (aN) of a spin-probe dissolved in the eluent are examined. A satisfactory description of mobile phase properties influencing the solute retention is provided by aN and beta or alternatively pi* and beta. The two seven-parameter models resulting from combination of aN and beta, or pi* and beta, with the solute descriptors were tested on a set of 26 pesticides representative of 10 different chemical classes in a wide range of mobile phase composition (30-60% (v/v) water-methanol and 30-70% (v/v) water-acetonitrile). Within the explored experimental range, the acidity of the eluent, as quantified by alpha, is almost constant, and this parameter is in fact irrelevant. The results reveal that aN and pi*, that can be considered as interchangeable mobile phase descriptors, are the most influent variables in the respective models. The predictive ability of the proposed models, as tested on an external data set, is quite good (Q2 close to 0.94) when a MLR approach is used, but the

  13. Local descriptors of protein structure: a systematic analysis of the sequence-structure relationship in proteins using short- and long-range interactions.

    PubMed

    Hvidsten, Torgeir R; Kryshtafovych, Andriy; Fidelis, Krzysztof

    2009-06-01

    Local protein structure representations that incorporate long-range contacts between residues are often considered in protein structure comparison but have found relatively little use in structure prediction where assembly from single backbone fragments dominates. Here, we introduce the concept of local descriptors of protein structure to characterize local neighborhoods of amino acids including short- and long-range interactions. We build a library of recurring local descriptors and show that this library is general enough to allow assembly of unseen protein structures. The library could on average re-assemble 83% of 119 unseen structures, and showed little or no performance decrease between homologous targets and targets with folds not represented among domains used to build it. We then systematically evaluate the descriptor library to establish the level of the sequence signal in sets of protein fragments of similar geometrical conformation. In particular, we test whether that signal is strong enough to facilitate correct assignment and alignment of these local geometries to new sequences. We use the signal to assign descriptors to a test set of 479 sequences with less than 40% sequence identity to any domain used to build the library, and show that on average more than 50% of the backbone fragments constituting descriptors can be correctly aligned. We also use the assigned descriptors to infer SCOP folds, and show that correct predictions can be made in many of the 151 cases where PSI-BLAST was unable to detect significant sequence similarity to proteins in the library. Although the combinatorial problem of simultaneously aligning several fragments to sequence is a major bottleneck compared with single fragment methods, the advantage of the current approach is that correct alignments imply correct long range distance constraints. The lack of these constraints is most likely the major reason why structure prediction methods fail to consistently produce adequate

  14. Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

    PubMed Central

    de Moraes, Fábio R.; Neshich, Izabella A. P.; Mazoni, Ivan; Yano, Inácio H.; Pereira, José G. C.; Salim, José A.; Jardine, José G.; Neshich, Goran

    2014-01-01

    Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now

  15. Improving predictions of protein-protein interfaces by combining amino acid-specific classifiers based on structural and physicochemical descriptors with their weighted neighbor averages.

    PubMed

    de Moraes, Fábio R; Neshich, Izabella A P; Mazoni, Ivan; Yano, Inácio H; Pereira, José G C; Salim, José A; Jardine, José G; Neshich, Goran

    2014-01-01

    Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now

  16. Predicting the auto-ignition temperatures of organic compounds from molecular structure using support vector machine.

    PubMed

    Pan, Yong; Jiang, Juncheng; Wang, Rui; Cao, Hongyin; Cui, Yi

    2009-05-30

    A quantitative structure-property relationship (QSPR) study is suggested for the prediction of auto-ignition temperatures (AIT) of organic compounds. Various kinds of molecular descriptors were calculated to represent the molecular structures of compounds, such as topological, charge, and geometric descriptors. The variable selection method of genetic algorithm (GA) was employed to select optimal subset of descriptors that have significant contribution to the overall AIT property from the large pool of calculated descriptors. The novel modeling method of support vector machine (SVM) was then employed to model the possible quantitative relationship existed between these selected descriptors and AIT property. The resulted model showed high prediction ability with the average absolute error being 28.88 degrees C, and the root mean square error being 36.86 for the prediction set, which are within the range of the experimental error of AIT measurements. The proposed method can be successfully used to predict the auto-ignition temperatures of organic compounds with only nine pre-selected theoretical descriptors which can be calculated directly from molecular structure alone.

  17. Structural classification of proteins using texture descriptors extracted from the cellular automata image.

    PubMed

    Kavianpour, Hamidreza; Vasighi, Mahdi

    2017-02-01

    Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

  18. Molecular interaction fields vs. quantum-mechanical-based descriptors in the modelling of lipophilicity of platinum(IV) complexes.

    PubMed

    Ermondi, Giuseppe; Caron, Giulia; Ravera, Mauro; Gabano, Elisabetta; Bianco, Sabrina; Platts, James A; Osella, Domenico

    2013-03-14

    We report QSAR calculations using VolSurf descriptors to model the lipophilicity of 53 Pt(iv) complexes with a diverse range of axial and equatorial ligands. Lipophilicity is measured using an efficient HPLC method. Previous models based on a subset of these data are shown to be inadequate, due to incompatibility of whole molecule descriptors between carboxylato and hydroxido ligands. Instead, the interaction surfaces of complexes with various probes are used as independent descriptors. Partial least squares modelling using three latent variables results in an accurate (R(2) = 0.92) and robust model (Q(2) = 0.87) of lipophilicity, that moreover highlights the importance of size and hydrophobicity terms and the modest relevance of hydrogen bonding.

  19. Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.

    PubMed

    Ivanciuc, Ovidiu

    2013-06-01

    Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.

  20. Topological and quantum molecular descriptors as effective tools for analyzing cytotoxic activity achieved by a series of (diselanediyldibenzene-4,1-diylnide)biscarbamate derivatives.

    PubMed

    Font, María; Plano, Daniel; Sanmartín, Carmen; Palop, Juan Antonio

    2017-05-01

    A molecular modeling study has been carried out on a previously reported series of (diselanediyldibenzene-4,1-diylnide)biscarbamate derivatives that show cytotoxic and antiproliferative in vitro activity against MCF-7 human cell line; radical scavenging properties were also confirmed when these compounds were tested for their ability to scavenge DPPH and ABTS radicals. The data obtained allowed us to classify the compounds into two different groups: (a) aliphatic carbamates for which the activity could be related with a first nucleophilic attack (mediated by H2O, for example) on the selenium atoms of the central scaffold, followed by the release of the alkyl N-(4-selanylphenyl) and N-(4-selenenophenyl)carbamate moieties. Then, a second nucleophilic attack on the carbamate moiety, to yield 4-aminobenzeneselenol and 4-selenenoaniline respectively, which can ultimately be responsible for the activity of the compounds; (b) aromatic carbamates, for which we propose a preferred nucleophilic attack on the carbamate moiety, yielding 4-[(4-aminophenyl)diselanyl]aniline, the common structural fragment for this series, for which we have previously demonstrated its cytotoxic profile. Then, selenium atoms of the central fragment may later undergo a new nucleophilic attack, to yield 4-selenenoaniline and 4-aminobenzeneselenol. The phenolic moieties released in this process may also have a synergistic cytotoxic and redox activity. The data that support this connection include the conformational behavior and the molecular topography of the derivatives which can influence the accessibility of the hydrolysis points, and some quantum descriptors (bond order, atomic charges, total valences, ionization potential, electron affinity, HOMO 0 and LUMO 0 location, etc.) that have been related to the biological activity of the compounds.

  1. Calculation of aqueous solubility of crystalline un-ionized organic chemicals and drugs based on structural similarity and physicochemical descriptors.

    PubMed

    Raevsky, Oleg A; Grigor'ev, Veniamin Yu; Polianczyk, Daniel E; Raevskaja, Olga E; Dearden, John C

    2014-02-24

    Solubilities of crystalline organic compounds calculated according to AMP (arithmetic mean property) and LoReP (local one-parameter regression) models based on structural and physicochemical similarities are presented. We used data on water solubility of 2615 compounds in un-ionized form measured at 25±5 °C. The calculation results were compared with the equation based on the experimental data for lipophilicity and melting point. According to statistical criteria, the model based on structural and physicochemical similarities showed a better fit with the experimental data. An additional advantage of this model is that it uses only theoretical descriptors, and this provides means for calculating water solubility for both existing and not yet synthesized compounds.

  2. Between Descriptors and Properties: Understanding the Ligand Efficiency Trends for G Protein-Coupled Receptor and Kinase Structure-Activity Data Sets.

    PubMed

    Polanski, Jaroslaw; Tkocz, Aleksandra

    2017-06-26

    The chemical meaning of the ligand efficiency (LE) metrics is explained in this paper using a large G protein-coupled receptor (GPCR) and kinase structure-activity (IC50, Ki) data set. Although there is a controversy in the literature regarding both the mathematical validity and the performance of LE, it is in common use as an early estimator for drug optimization. Apparently, the numerous con arguments are not convincing enough. We show here for the first time that the main misunderstanding of the chemical meaning of LE is its interpretation as a molecular descriptor connected with a single molecule. Instead, LE should be interpreted as a statistical property. We show that the LE, which is designed as a regression of a binding property on the heavy atom count (HAC), is correlated to the reciprocal of the molecular weight because of Avogadro statistics. This indicates that the hyperbolic model of LE is basically a consequence of a nonbinding effect, an increase in the number of ligands that are available to a receptor for smaller molecules, and not a real increase in the binding potency for a single HAC as interpreted in the literature. Accordingly, we need to revisit and carefully reevaluate LE-based molecular comparisons.

  3. Relationships Between MRI Breast Imaging-Reporting and Data System (BI-RADS) Lexicon Descriptors and Breast Cancer Molecular Subtypes: Internal Enhancement is Associated with Luminal B Subtype.

    PubMed

    Grimm, Lars J; Zhang, Jing; Baker, Jay A; Soo, Mary S; Johnson, Karen S; Mazurowski, Maciej A

    2017-03-13

    The aim of this study was to determine the associations between breast MRI findings using the Breast Imaging-Reporting and Data System (BI-RADS) lexicon descriptors and breast cancer molecular subtypes. In this retrospective, IRB-approved, single institution study MRIs from 278 women with breast cancer were reviewed by one of six fellowship-trained breast imagers. Readers reported BI-RADS descriptors for breast masses (shape, margin, internal enhancement) and non-mass enhancement (distribution, internal enhancement). Pathology reports were reviewed for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2). Surrogates were used to categorize tumors by molecular subtype: ER/PR+, HER2- (luminal A); ER/PR+, HER2+ (luminal B); ER/PR-, HER2+ (HER2); ER/PR/HER2- (basal). A univariate logistic regression model was developed to identify associations between BI-RADS descriptors and molecular subtypes. Internal enhancement for mass and non-mass enhancement was combined for analysis. There was an association between mass shape and basal subtype (p = 0.039), which was more frequently round (17.1%) than other subtypes (range: 0-8.3%). In addition, there was an association between mass margin and HER2 subtype (p = 0.040), as HER2 cancers more frequently had a smooth margin (33.3%) than other subtypes (range: 4.2-17.1%). Finally, there was an association between internal enhancement and luminal B subtype (p = 0.003), with no cases of luminal B cancer demonstrating homogeneous internal enhancement versus a range of 10.9-23.5% for other subtypes. There are associations between breast cancer molecular subtypes and lesion appearance on MRI using the BI-RADS lexicon.

  4. Alternative methods for estimating common descriptors for QSAR studies of dyes and fluorescent probes using molecular modeling software. 2. Correlations between log P and the hydrophilic/lipophilic index, and new methods for estimating degrees of amphiphilicity.

    PubMed

    Dapson, Richard W; Horobin, Richard W

    2013-11-01

    The log P descriptor, despite its usefulness, can be difficult to use, especially for researchers lacking skills in physical chemistry. Moreover this classic measure has been determined in numerous ways, which can result in inconsistant estimates of log P values, especially for relatively complex molecules such as fluorescent probes. Novel measures of hydrophilicity/lipophilicity (the Hydrophilic/Lipophilic Index, HLI) and amphiphilicity (hydrophilic/lipophilic indices for the head group and tail, HLIT and HLIHG, respectively) therefore have been devised. We compare these descriptors with measures based on log P, the standard method for quantitative structure activity relationships (QSAR) studies. HLI can be determined using widely available molecular modeling software, coupled with simple arithmetic calculations. It is based on partial atomic charges and is intended to be a stand-alone measure of hydrophilicity/lipophilicity. Given the wide application of log P, however, we investigated the correlation between HLI and log P using a test set of 56 fluorescent probes of widely different physicochemical character. Overall correlation was poor; however, correlation of HLI and log P for probes of narrowly specified charge types, i.e., non-ionic compounds, anions, conjugated cations, or zwitterions, was excellent. Values for probes with additional nonconjugated quaternary cations, however, were less well correlated. The newly devised HLI can be divided into domain-specific descriptors, HLIT and HLIHG in amphiphilic probes. Determinations of amphiphilicity, made independently by the authors using their respective methods, showed excellent agreement. Quantifying amphiphilicity from partial log P values of the head group (head group hydrophilicity; HGH) and tail (amphiphilicity index; AI) has proved useful for understanding fluorescent probe action. The same limitations of log P apply to HGH and AI, however. The novel descriptors, HLIT and HLIHG, offer analogous advantages

  5. Computational nanochemistry study of the molecular structure and properties of ethambutol.

    PubMed

    Salgado-Morán, Guillermo; Ruiz-Nieto, Samuel; Gerli-Candia, Lorena; Flores-Holguín, Norma; Favila-Pérez, Alejandra; Glossman-Mitnik, Daniel

    2013-09-01

    The M06 family of density functionals was employed to calculate the molecular structure and properties of the ethambutol molecule. Besides determination of molecular structures, UV-vis spectra were computed using TD-DFT in the presence of a solvent and the results compared with available experimental data. The chemical reactivity descriptors were calculated through conceptual DFT. The active sites for nucleophilic and electrophilic attacks have been chosen by relating them to Fukui function indices. A comparison between the descriptors calculated through vertical energy values and those arising from Koopmans' theorem approximation were performed in order to check the validity of the latter procedure.

  6. Mathematical descriptors for the prediction of property, bioactivity, and toxicity of chemicals from their structure: a chemical-cum-biochemical approach.

    PubMed

    Basak, Subhash C

    2013-12-01

    This review article covers major aspects of mathematical chemistry, QSAR, chemoinformatics, bioinformatics, and molecular modeling research carried out by Subhash C. Basak and coworkers during 1968 to the present time in three distinct phases: 1) Department of Biochemistry, University of Calcutta and Charuchandra College, India (1968-1981); 2) Department of Chemistry & Biochemistry, University of Minnesota, Duluth, USA (1982-1987), and 3) Natural Resources Research Institute, University of Minnesota, Duluth, UMD-NRRI (1988-date). Topics discussed include development of novel mathematical descriptors of molecules and biomolecules; QSAR, HiQSAR, DiffQSAR and I-QSAR studies using chemodescriptors and biodescriptors; formulation of arbitrary quantitative molecular similarity analysis (QMSA) and tailored QMSA methods and their applications. The role of proper statistical methods in QSAR formulation and validation as well as the critical role of such methods in the molecular descriptor landscape of the twenty first century are also addressed.

  7. The Development of Quantitative Structure-Binding Affinity Relationship (QSBR) Models Based on Novel Geometrical Chemical Descriptors of the Protein-Ligand Interfaces

    PubMed Central

    Zhang, Shuxing; Golbraikh, Alexander; Tropsha, Alexander

    2009-01-01

    Novel geometrical chemical descriptors have been derived based on the computational geometry of protein-ligand interfaces and Pauling atomic electronegativities (EN). Delaunay tessellation has been applied to a diverse set of 517 X-ray characterized protein-ligand complexes yielding a unique collection of interfacial nearest neighbor atomic quadruplets for each complex. Each quadruplet composition was characterized by a single descriptor calculated as the sum of the EN values for the four participating atom types. We termed these simple descriptors generated from atomic EN values and derived with the Delaunay Tessellation the ENTess descriptors and used them in the variable selection k-Nearest Neighbor quantitative structure-binding affinity relationship (QSBR) studies of 264 diverse protein-ligand complexes with known binding constants. 24 complexes with chemically dissimilar ligands were set aside as an independent validation set, and the remaining dataset of 240 complexes was divided into multiple training and test sets. The best models were characterized by the leave-one-out cross-validated correlation coefficient q2 as high as 0.66 for the training set and the correlation coefficient R2 as high as 0.83 for the test set. High predictive power of these models was confirmed independently by applying them to the validation set of 24 complexes yielding R2 as high as 0.85. We conclude that QSBR models built with the ENTess descriptors can be instrumental for predicting the binding affinity of receptor-ligand complexes. PMID:16640331

  8. Novel use of chemical shift in NMR as molecular descriptor: a first report on modeling carbonic anhydrase inhibitory activity and related parameters.

    PubMed

    Khadikar, Padmakar V; Sharma, Vimukta; Karmarkar, Sneha; Supuran, Claudiu T

    2005-02-15

    A novel use of NMR chemical shift of the SO(2)NH(2) protons (in dioxane as solvent) as a molecular descriptor is described for modeling the inhibition constant for benzene sulfonamides against the zinc enzyme carbonic anhydrase (CA, EC 4.2.1.1). The methodology is extended to model diuretic activity and lipophilicity of benzene sulfonamide derivatives. The regression analysis of the data has shown that the NMR chemical shift is incapable of modeling lipophilicity. However, it is quite useful for modeling the diuretic activity of these derivatives. The results are compared with those obtained using distance-based topological indices: Wiener (W)-, Szeged (Sz)-, and PI (Padmakar-Ivan) indices.

  9. Understanding molecular structure from molecular mechanics.

    PubMed

    Allinger, Norman L

    2011-04-01

    Molecular mechanics gives us a well known model of molecular structure. It is less widely recognized that valence bond theory gives us structures which offer a direct interpretation of molecular mechanics formulations and parameters. The electronic effects well-known in physical organic chemistry can be directly interpreted in terms of valence bond structures, and hence quantitatively calculated and understood. The basic theory is outlined in this paper, and examples of the effects, and their interpretation in illustrative examples is presented.

  10. On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors towards Materials Quantitative Structure Property Relationships

    ERIC Educational Resources Information Center

    Krein, Michael

    2011-01-01

    After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright…

  11. On the Development and Use of Large Chemical Similarity Networks, Informatics Best Practices and Novel Chemical Descriptors towards Materials Quantitative Structure Property Relationships

    ERIC Educational Resources Information Center

    Krein, Michael

    2011-01-01

    After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright…

  12. A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

    PubMed

    Randhawa, Vinay; Kumar Singh, Anil; Acharya, Vishal

    2015-12-01

    Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize the effectiveness of such pipelines, we first analyzed the dysregulated gene pairs between control and tumor samples and then implemented an ensemble-based feature selection approach to prioritize targets in oral squamous cell carcinoma (OSCC) for therapeutic exploration. Based on the structural information of known inhibitors of CXCR4-one of the best targets identified in this study-a feature selection was implemented for the identification of optimal structural features (molecular descriptor) based on which a classification model was generated. Furthermore, the CXCR4-centered descriptor-based classification model was finally utilized to screen a repository of plant derived small-molecules to obtain potential inhibitors. The application of our methodology may assist effective selection of the best targets which may have previously been overlooked, that in turn will lead to the development of new oral cancer medications. The small molecules identified in this study can be ideal candidates for trials as potential novel anti-oral cancer agents. Importantly, distinct steps of this whole study may provide reference for the analysis of other complex human diseases.

  13. Derivatives in discrete mathematics: a novel graph-theoretical invariant for generating new 2/3D molecular descriptors. I. Theory and QSPR application.

    PubMed

    Marrero-Ponce, Yovani; Santiago, Oscar Martínez; López, Yoan Martínez; Barigye, Stephen J; Torrens, Francisco

    2012-11-01

    In this report, we present a new mathematical approach for describing chemical structures of organic molecules at atomic-molecular level, proposing for the first time the use of the concept of the derivative ([Formula: see text]) of a molecular graph (MG) with respect to a given event (E), to obtain a new family of molecular descriptors (MDs). With this purpose, a new matrix representation of the MG, which generalizes graph's theory's traditional incidence matrix, is introduced. This matrix, denominated the generalized incidence matrix, Q, arises from the Boolean representation of molecular sub-graphs that participate in the formation of the graph molecular skeleton MG and could be complete (representing all possible connected sub-graphs) or constitute sub-graphs of determined orders or types as well as a combination of these. The Q matrix is a non-quadratic and unsymmetrical in nature, its columns (n) and rows (m) are conditions (letters) and collection of conditions (words) with which the event occurs. This non-quadratic and unsymmetrical matrix is transformed, by algebraic manipulation, to a quadratic and symmetric matrix known as relations frequency matrix, F, which characterizes the participation intensity of the conditions (letters) in the events (words). With F, we calculate the derivative over a pair of atomic nuclei. The local index for the atomic nuclei i, Δ(i), can therefore be obtained as a linear combination of all the pair derivatives of the atomic nuclei i with all the rest of the j's atomic nuclei. Here, we also define new strategies that generalize the present form of obtaining global or local (group or atom-type) invariants from atomic contributions (local vertex invariants, LOVIs). In respect to this, metric (norms), means and statistical invariants are introduced. These invariants are applied to a vector whose components are the values Δ(i) for the atomic nuclei of the molecule or its fragments. Moreover, with the purpose of differentiating

  14. Using Theoretical Descriptors in Structural Activity Relationships. 5. A Review of the Theoretical Parameters

    DTIC Science & Technology

    1989-07-01

    10 3.1.1 Molecular Volume ........ ..................... ... 10 3.1.2 Polarizability Index ................... .... 11...3.2.2 Konneman’s Fish Toxicity ...... ... ................ 16 3.2.3 Microtox Toxicity Test . . . . . . ............ 17 3.2.4 UV-Visible (UV-Vis...Used ...... ..... .......................... . ... 9 2. Representative Polarizability Index Values ...... ........... 12 3. Representative Values of

  15. Quantitative structure-activity relationship modeling of antioxidant activities of hydroxybenzalacetones using quantum chemical, physicochemical and spatial descriptors.

    PubMed

    Mitra, Indrani; Saha, Achintya; Roy, Kunal

    2009-05-01

    We have modeled antioxidant activities of hydroxybenzalacetones against lipid peroxidation induced by t-butyl hydroperoxide (pC1), gamma-irradiation (pC2) and also their 1,1-diphenyl-2-picryl hydrazyl (DPPH) free radical scavenging activity (pC3) using quantitative structure-activity relationship technique. The quantitative structure-activity relationship models were developed using different statistical methods like stepwise multiple linear regression, genetic function approximation and genetic partial least squares with descriptors of different categories (quantum chemical, physicochemical, spatial and substituent constants). The models were validated by internal validation and randomization techniques. The model predictivity was judged on the basis of their cross-validated squared correlation coefficient (Q2) and modified r2 (r m 2) values. The best models for the two responses, pC1 and pC2, were obtained by genetic partial least squares technique while the best model for the third response, pC3, was obtained by genetic function approximation technique. The developed models suggest that the distribution of charges on the phenolic nucleus and the phenolic oxygen as well as the charged surface areas of the molecules together with the geometry and orientation of the substituents significantly influence all the three types of responses (pC1, pC2 and pC3). The developed models may be used to design hydroxybenzalacetones with better antioxidant activities.

  16. ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins.

    PubMed

    Ruiz-Blanco, Yasser B; Paz, Waldo; Green, James; Marrero-Ponce, Yovani

    2015-05-16

    The exponential growth of protein structural and sequence databases is enabling multifaceted approaches to understanding the long sought sequence-structure-function relationship. Advances in computation now make it possible to apply well-established data mining and pattern recognition techniques to these data to learn models that effectively relate structure and function. However, extracting meaningful numerical descriptors of protein sequence and structure is a key issue that requires an efficient and widely available solution. We here introduce ProtDCal, a new computational software suite capable of generating tens of thousands of features considering both sequence-based and 3D-structural descriptors. We demonstrate, by means of principle component analysis and Shannon entropy tests, how ProtDCal's sequence-based descriptors provide new and more relevant information not encoded by currently available servers for sequence-based protein feature generation. The wide diversity of the 3D-structure-based features generated by ProtDCal is shown to provide additional complementary information and effectively completes its general protein encoding capability. As demonstration of the utility of ProtDCal's features, prediction models of N-linked glycosylation sites are trained and evaluated. Classification performance compares favourably with that of contemporary predictors of N-linked glycosylation sites, in spite of not using domain-specific features as input information. ProtDCal provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http://bioinf.sce.carleton.ca/ProtDCal/ . ProtDCal introduces local and group-based encoding which enhances the diversity of the information captured by the computed features. Furthermore, we have shown that adding structure-based descriptors contributes non-redundant additional information to the features-based characterization of polypeptide systems. This

  17. Euclidian embeddings of periodic nets: definition of a topologically induced complete set of geometric descriptors for crystal structures.

    PubMed

    Eon, Jean-Guillaume

    2011-01-01

    Crystal-structure topologies, represented by periodic nets, are described by labelled quotient graphs (or voltage graphs). Because the edge space of a finite graph is the direct sum of its cycle and co-cycle spaces, a Euclidian representation of the derived periodic net is provided by mapping a basis of the cycle and co-cycle spaces to a set of real vectors. The mapping is consistent if every cycle of the basis is mapped on its own net voltage. The sum of all outgoing edges at every vertex may be chosen as a generating set of the co-cycle space. The embedding maps the cycle space onto the lattice L. By analogy, the concept of the co-lattice L* is defined as the image of the generators of the co-cycle space; a co-lattice vector is proportional to the distance vector between an atom and the centre of gravity of its neighbours. The pair (L, L*) forms a complete geometric descriptor of the embedding, generalizing the concept of barycentric embedding. An algebraic expression permits the direct calculation of fractional coordinates. Non-zero co-lattice vectors allow nets with collisions, displacive transitions etc. to be dealt with. The method applies to nets of any periodicity and dimension, be they crystallographic nets or not. Examples are analyzed: α-cristobalite, the seven unstable 3-periodic minimal nets etc.

  18. Prediction of deleterious functional effects of amino acid mutations using a library of structure-based function descriptors.

    PubMed

    Herrgard, Sanna; Cammer, Stephen A; Hoffman, Brian T; Knutson, Stacy; Gallina, Marijo; Speir, Jeffrey A; Fetrow, Jacquelyn S; Baxter, Susan M

    2003-12-01

    An automated, active site-focused, computational method is described for use in predicting the effects of engineered amino acid mutations on enzyme catalytic activity. The method uses structure-based function descriptors (Fuzzy Functional Forms trade mark or FFFs trade mark ) to automatically identify enzyme functional sites in proteins. Three-dimensional sequence profiles are created from the surrounding active site structure. The computationally derived active site profile is used to analyze the effect of each amino acid change by defining three key features: proximity of the change to the active site, degree of amino acid conservation at the position in related proteins, and compatibility of the change with residues observed at that position in similar proteins. The features were analyzed using a data set of individual amino acid mutations occurring at 128 residue positions in 14 different enzymes. The results show that changes at key active site residues and at highly conserved positions are likely to have deleterious effects on the catalytic activity, and that non-conservative mutations at highly conserved residues are even more likely to be deleterious. Interestingly, the study revealed that amino acid substitutions at residues in close contact with the key active site residues are not more likely to have deleterious effects than mutations more distant from the active site. Utilization of the FFF-derived structural information yields a prediction method that is accurate in 79-83% of the test cases. The success of this method across all six EC classes suggests that it can be used generally to predict the effects of mutations and nsSNPs for enzymes. Future applications of the approach include automated, large-scale identification of deleterious nsSNPs in clinical populations and in large sets of disease-associated nsSNPs, and identification of deleterious nsSNPs in drug targets and drug metabolizing enzymes. Copyright 2003 Wiley-Liss, Inc.

  19. Improved nucleic acid descriptors for siRNA efficacy prediction

    PubMed Central

    Sciabola, Simone; Cao, Qing; Orozco, Modesto; Faustino, Ignacio; Stanton, Robert V.

    2013-01-01

    Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies. PMID:23241392

  20. In silico prediction of spleen tyrosine kinase inhibitors using machine learning approaches and an optimized molecular descriptor subset generated by recursive feature elimination method.

    PubMed

    Li, Bing-Ke; Cong, Yong; Yang, Xue-Gang; Xue, Ying; Chen, Yi-Zong

    2013-05-01

    We tested four machine learning methods, support vector machine (SVM), k-nearest neighbor, back-propagation neural network and C4.5 decision tree for their capability in predicting spleen tyrosine kinase (Syk) inhibitors by using 2592 compounds which are more diverse than those in other studies. The recursive feature elimination method was used for improving prediction performance and selecting molecular descriptors responsible for distinguishing Syk inhibitors and non-inhibitors. Among four machine learning models, SVM produces the best performance at 99.18% for inhibitors and 98.82% for non-inhibitors, respectively, indicating that the SVM is potentially useful for facilitating the discovery of Syk inhibitors. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. A Structural Equation Model Analysis of Relationships among ENSO, Seasonal Descriptors and Wildfires

    PubMed Central

    Slocum, Matthew G.; Orzell, Steve L.

    2013-01-01

    Seasonality drives ecological processes through networks of forcings, and the resultant complexity requires creative approaches for modeling to be successful. Recently ecologists and climatologists have developed sophisticated methods for fully describing seasons. However, to date the relationships among the variables produced by these methods have not been analyzed as networks, but rather with simple univariate statistics. In this manuscript we used structural equation modeling (SEM) to analyze a proposed causal network describing seasonality of rainfall for a site in south-central Florida. We also described how this network was influenced by the El Niño-Southern Oscillation (ENSO), and how the network in turn affected the site’s wildfire regime. Our models indicated that wet and dry seasons starting later in the year (or ending earlier) were shorter and had less rainfall. El Niño conditions increased dry season rainfall, and via this effect decreased the consistency of that season’s drying trend. El Niño conditions also negatively influenced how consistent the moistening trend was during the wet season, but in this case the effect was direct and did not route through rainfall. In modeling wildfires, our models showed that area burned was indirectly influenced by ENSO via its effect on dry season rainfall. Area burned was also indirectly reduced when the wet season had consistent rainfall, as such wet seasons allowed fewer wildfires in subsequent fire seasons. Overall area burned at the study site was estimated with high accuracy (R2 score = 0.63). In summary, we found that by using SEMs, we were able to clearly describe causal patterns involving seasonal climate, ENSO and wildfire. We propose that similar approaches could be effectively applied to other sites where seasonality exerts strong and complex forcings on ecological processes. PMID:24086670

  2. A structural equation model analysis of relationships among ENSO, seasonal descriptors and wildfires.

    PubMed

    Slocum, Matthew G; Orzell, Steve L

    2013-01-01

    Seasonality drives ecological processes through networks of forcings, and the resultant complexity requires creative approaches for modeling to be successful. Recently ecologists and climatologists have developed sophisticated methods for fully describing seasons. However, to date the relationships among the variables produced by these methods have not been analyzed as networks, but rather with simple univariate statistics. In this manuscript we used structural equation modeling (SEM) to analyze a proposed causal network describing seasonality of rainfall for a site in south-central Florida. We also described how this network was influenced by the El Niño-Southern Oscillation (ENSO), and how the network in turn affected the site's wildfire regime. Our models indicated that wet and dry seasons starting later in the year (or ending earlier) were shorter and had less rainfall. El Niño conditions increased dry season rainfall, and via this effect decreased the consistency of that season's drying trend. El Niño conditions also negatively influenced how consistent the moistening trend was during the wet season, but in this case the effect was direct and did not route through rainfall. In modeling wildfires, our models showed that area burned was indirectly influenced by ENSO via its effect on dry season rainfall. Area burned was also indirectly reduced when the wet season had consistent rainfall, as such wet seasons allowed fewer wildfires in subsequent fire seasons. Overall area burned at the study site was estimated with high accuracy (R (2) score = 0.63). In summary, we found that by using SEMs, we were able to clearly describe causal patterns involving seasonal climate, ENSO and wildfire. We propose that similar approaches could be effectively applied to other sites where seasonality exerts strong and complex forcings on ecological processes.

  3. Comparison of coefficients and distance measurements in passion fruit plants based on molecular markers and physicochemical descriptors.

    PubMed

    Cerqueira-Silva, C B M; Cardoso-Silva, C B; Conceição, L D H C S; Nonato, J V A; Oliveira, A C; Corrêa, R X

    2009-07-28

    We investigated seven distance measures and 14 similarity coefficients in a set of observations of variables of the 'yellow' passion fruit plant (Passiflora edulis Sims), submitted to multivariate analyses (distance, projection and grouping). Fourteen genotypes were characterized, based on DNA amplification with 16 random amplified polymorphic DNA primers and the assessment of nine fruit physical-chemical descriptors. The distance measurements and the similarity coefficients were compared by the Spearman correlation test, projection in two-dimensional space and grouping efficiency, using five grouping methods; the genotype ranking varied with the different techniques. Coler-Rodger distance measures, Euclidean distance square measures and Yule similarity coefficients proved to be inadequate for projection in two-dimensional space or for grouping matrices. Regardless of the origin of the distance matrix, the unweighted pair group method with arithmetic mean grouping method proved to be the most adequate. The various distance measurements, similarity coefficients and grouping methods gave different values of distortion, cophenetic correlation and stress; they influence the characterization of genetic variability and this should be taken into account for studies of yellow passion fruit plants.

  4. Exploring the role of quantum chemical descriptors in modeling acute toxicity of diverse chemicals to Daphnia magna.

    PubMed

    Reenu; Vikas

    2015-09-01

    Various quantum-mechanically computed molecular and thermodynamic descriptors along with physico-chemical, electrostatic and topological descriptors are compared while developing quantitative structure-activity relationships (QSARs) for the acute toxicity of 252 diverse organic chemicals towards Daphnia magna. QSAR models based on the quantum-chemical descriptors, computed with routinely employed advanced semi-empirical and ab-initio methods, along with the electron-correlation contribution (CORR) of the descriptors, are analyzed for the external predictivity of the acute toxicity. The models with reliable internal stability and external predictivity are found to be based on the HOMO energy along with the physico-chemical, electrostatic and topological descriptors. Besides this, the total energy and electron-correlation energy are also observed as highly reliable descriptors, suggesting that the intra-molecular interactions between the electrons play an important role in the origin of the acute toxicity, which is in fact an unexplored phenomenon. The models based on quantum-chemical descriptors such as chemical hardness, absolute electronegativity, standard Gibbs free energy and enthalpy are also observed to be reliable. A comparison of the robust models based on the quantum-chemical descriptors computed with various quantum-mechanical methods suggests that the advanced semi-empirical methods such as PM7 can be more reliable than the ab-initio methods which are computationally more expensive. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Quantum descriptors for predictive toxicology of halogenated aliphatic hydrocarbons.

    PubMed

    Trohalaki, S; Pachter, R

    2003-04-01

    In order to improve Quantitative Structure-Activity Relationships (QSARs) for halogenated aliphatics (HA) and to better understand the biophysical mechanism of toxic response to these ubiquitous chemicals, we employ improved quantum-mechanical descriptors to account for HA electrophilicity. We demonstrate that, unlike the lowest unoccupied molecular orbital energy, ELUMO, which was previously used as a descriptor, the electron affinity can be systematically improved by application of higher levels of theory. We also show that employing the reciprocal of ELUMO, which is more consistent with frontier molecular orbital (FMO) theory, improves the correlations with in vitro toxicity data. We offer explanations based on FMO theory for a result from our previous work, in which the LUMO energies of HA anions correlated surprisingly well with in vitro toxicity data. Additional descriptors are also suggested and interpreted in terms of the accepted biophysical mechanism of toxic response to HAs and new QSARs are derived for various chemical categories that compose the data set employed. These alternate descriptors provide important insight and could benefit other classes of compounds where the biophysical mechanism of toxic response involves dissociative attachment.

  6. Six global and local QSPR models of aqueous solubility at pH = 7.4 based on structural similarity and physicochemical descriptors.

    PubMed

    Raevsky, O A; Grigorev, V Y; Polianczyk, D E; Raevskaja, O E; Dearden, J C

    2017-08-01

    Aqueous solubility at pH = 7.4 is a very important property for medicinal chemists because this is the pH value of physiological media. The present work describes the application of three different methods (support vector machine (SVM), random forest (RF) and multiple linear regression (MLR)) and three local quantitative structure-property relationship (QSPR) models (regression corrected by nearest neighbours (RCNN), arithmetic mean property (AMP) and local regression property (LoReP)) to construct stable QSPRs with clear mechanistic interpretation. Our data set contained experimental values of aqueous solubility at pH = 7.4 of 387 chemicals (349 in the training set and 38 in the test set including 16 own measurements). The initial descriptor pool contained 210 physicochemical descriptors, calculated from the HYBOT, DRAGON, SYBYL and VolSurf+ programs. Six QSPRs with good statistics based on fundamentals of aqueous solubility and optimization of descriptor space were obtained. Those models have an RMSE close to experimental error (0.70), and are amenable to physical interpretation. The QSPR models developed in this study may be useful for medicinal chemists. Global MLR, RF and SVM models may be valuable for consideration of common factors that influence solubility. The RCNN, AMP and LoReP local models may be helpful for the optimization of aqueous solubility in small sets of related chemicals.

  7. The electronic density obtained from a QTAIM analysis used as molecular descriptor. A study performed in a new series of DHFR inhibitors

    NASA Astrophysics Data System (ADS)

    Tosso, Rodrigo D.; Vettorazzi, Marcela; Andujar, Sebastian A.; Gutierrez, Lucas J.; Garro, Juan C.; Angelina, Emilio; Rodríguez, Ricaurte; Suvire, Fernando D.; Nogueras, Manuel; Cobo, Justo; Enriz, Ricardo D.

    2017-04-01

    The results reported here indicate that the electron density obtained from a QTAIM analysis is an excellent descriptor of molecular interactions that stabilize and destabilize the formation of the ligand-receptor (L-R) complex. The study was conducted on a series of 25 compounds that have inhibitory effects on DHFR. Besides the synthesis and bioassays performed for some of these compounds, various types of molecular calculations were performed. Thus, we performed MD simulations, computations at different levels of theory (ab initio and DFT) using reduced models and a QTAIM study on the different complexes. The resulting model has allowed us to differentiate not only highly active compounds with respect to compounds weakly active, but also among compounds that have similar affinities in this series. The model also showed a high degree of predictability which allows predicting the affinity of non-synthesized compounds. Very important additional information can be obtained through this type of study, it is possible to visualize which amino acids are involved in the interactions determining the different affinities of the ligands.

  8. Modeling and predicting pKa values of mono-hydroxylated polychlorinated biphenyls (HO-PCBs) and polybrominated diphenyl ethers (HO-PBDEs) by local molecular descriptors.

    PubMed

    Yu, Haiying; Wondrousch, Dominik; Yuan, Quan; Lin, Hongjun; Chen, Jianrong; Hong, Huachang; Schüürmann, Gerrit

    2015-11-01

    Hydroxylated polychlorinated biphenyls (HO-PCBs) and polybrominated diphenyl ethers (HO-PBDEs) are attracting considerable concerns because of their multiple endocrine-disrupting effects and wide existence in environment and organisms. The hydroxyl groups enable these chemicals to be ionizable, and dissociation constant, pKa, becomes an important parameter for investigating their environmental behavior and biological activities. In this study, a new pKa prediction model was developed using local molecular descriptors. The dataset contains 21 experimental pKa values of HO-PCBs and HO-PBDEs. The optimized geometries by ab initio HF/6-31G(∗∗) algorithm were used to calculate the site-specific molecular readiness to accept or donate electron charges. The developed model obtained good statistical performance, which significantly outperformed commercial software ACD and SPARC. Mechanism analysis indicates that pKa values increase with the charge-limited donor energy EQocc on hydroxyl oxygen atom and decrease with the energy-limited acceptor charge QEvac on hydroxyl hydrogen atom. The regression model was also applied to calculate pKa values for all 837 mono-hydroxylated PCBs and PBDEs in each class, aiming to provide basic data for the ecological risk assessment of these chemicals.

  9. DDC Descriptor Frequencies.

    ERIC Educational Resources Information Center

    Klingbiel, Paul H.; Jacobs, Charles R.

    This report summarizes the frequency of use of the 7144 descriptors used for indexing technical reports in the Defense Documentation Center (DDC) collection. The descriptors are arranged alphabetically in the first section and by frequency in the second section. The frequency data cover about 427,000 AD documents spanning the interval from March…

  10. Structure-activity correlation study of HIV-1 inhibitors: Electronic and molecular parameters

    NASA Astrophysics Data System (ADS)

    Hannongbua, Supa; Lawtrakul, Luckhana; Limtrakul, Jumras

    1996-04-01

    Quantitative structure-activity relationships (QSARs) for 40 HIV-1 inhibitors, 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine and its derivatives, were studied. Fully optimized geometries, based on the semiempirical AM1 method, were used to calculate electronic and molecular properties of all compounds. In order to examine the relation between biological activities and structural properties, multiple linear regression models were employed. A suitable QSAR model was obtained, showing not only statistical significance, but also predictive ability. The significant molecular descriptors used were atomic charges of two substituted carbon atoms in the thymine ring, hydration energies and molar refractivities of the molecules. These descriptors allowed a physical explanation of electronic and molecular properties contributing to HIV-1 inhibitory potency.

  11. Externally predictive quantitative modeling of supercooled liquid vapor pressure of polychlorinated-naphthalenes through electron-correlation based quantum-mechanical descriptors.

    PubMed

    Vikas; Chayawan

    2014-01-01

    For predicting physico-chemical properties related to environmental fate of molecules, quantitative structure-property relationships (QSPRs) are valuable tools in environmental chemistry. For developing a QSPR, molecular descriptors computed through quantum-mechanical methods are generally employed. The accuracy of a quantum-mechanical method, however, rests on the amount of electron-correlation estimated by the method. In this work, single-descriptor QSPRs for supercooled liquid vapor pressure of chloronaphthalenes and polychlorinated-naphthalenes are developed using molecular descriptors based on the electron-correlation contribution of the quantum-mechanical descriptor. The quantum-mechanical descriptors for which the electron-correlation contribution is analyzed include total-energy, mean polarizability, dipole moment, frontier orbital (HOMO/LUMO) energy, and density-functional theory (DFT) based descriptors, namely, absolute electronegativity, chemical hardness, and electrophilicity index. A total of 40 single-descriptor QSPRs were developed using molecular descriptors computed with advanced semi-empirical (SE) methods, namely, RM1, PM7, and ab intio methods, namely, Hartree-Fock and DFT. The developed QSPRs are validated using state-of-the-art external validation procedures employing an external prediction set. From the comparison of external predictivity of the models, it is observed that the single-descriptor QSPRs developed using total energy and correlation energy are found to be far more robust and predictive than those developed using commonly employed descriptors such as HOMO/LUMO energy and dipole moment. The work proposes that if real external predictivity of a QSPR model is desired to be explored, particularly, in terms of intra-molecular interactions, correlation-energy serves as a more appropriate descriptor than the polarizability. However, for developing QSPRs, computationally inexpensive advanced SE methods such as PM7 can be more reliable than

  12. Relations between water physico-chemistry and benthic algal communities in a northern Canadian watershed: defining reference conditions using multiple descriptors of community structure.

    PubMed

    Thomas, Kathryn E; Hall, Roland I; Scrimgeour, Garry J

    2015-09-01

    Defining reference conditions is central to identifying environmental effects of anthropogenic activities. Using a watershed approach, we quantified reference conditions for benthic algal communities and their relations to physico-chemical conditions in rivers in the South Nahanni River watershed, NWT, Canada, in 2008 and 2009. We also compared the ability of three descriptors that vary in terms of analytical costs to define algal community structure based on relative abundances of (i) all algal taxa, (ii) only diatom taxa, and (iii) photosynthetic pigments. Ordination analyses showed that variance in algal community structure was strongly related to gradients in environmental variables describing water physico-chemistry, stream habitats, and sub-watershed structure. Water physico-chemistry and local watershed-scale descriptors differed significantly between algal communities from sites in the Selwyn Mountain ecoregion compared to sites in the Nahanni-Hyland ecoregions. Distinct differences in algal community types between ecoregions were apparent irrespective of whether algal community structure was defined using all algal taxa, diatom taxa, or photosynthetic pigments. Two algal community types were highly predictable using environmental variables, a core consideration in the development of Reference Condition Approach (RCA) models. These results suggest that assessments of environmental impacts could be completed using RCA models for each ecoregion. We suggest that use of algal pigments, a high through-put analysis, is a promising alternative compared to more labor-intensive and costly taxonomic approaches for defining algal community structure.

  13. Local functional descriptors for surface comparison based binding prediction

    PubMed Central

    2012-01-01

    Background Molecular recognition in proteins occurs due to appropriate arrangements of physical, chemical, and geometric properties of an atomic surface. Similar surface regions should create similar binding interfaces. Effective methods for comparing surface regions can be used in identifying similar regions, and to predict interactions without regard to the underlying structural scaffold that creates the surface. Results We present a new descriptor for protein functional surfaces and algorithms for using these descriptors to compare protein surface regions to identify ligand binding interfaces. Our approach uses descriptors of local regions of the surface, and assembles collections of matches to compare larger regions. Our approach uses a variety of physical, chemical, and geometric properties, adaptively weighting these properties as appropriate for different regions of the interface. Our approach builds a classifier based on a training corpus of examples of binding sites of the target ligand. The constructed classifiers can be applied to a query protein providing a probability for each position on the protein that the position is part of a binding interface. We demonstrate the effectiveness of the approach on a number of benchmarks, demonstrating performance that is comparable to the state-of-the-art, with an approach with more generality than these prior methods. Conclusions Local functional descriptors offer a new method for protein surface comparison that is sufficiently flexible to serve in a variety of applications. PMID:23176080

  14. Structural details (kinks and non-alpha conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors.

    PubMed

    Rigoutsos, Isidore; Riek, Peter; Graham, Robert M; Novotny, Jiri

    2003-08-01

    One of the promising methods of protein structure prediction involves the use of amino acid sequence-derived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular alpha-helical character (i.e. pi-helices, 3(10)-helices and kinks). A 'search engine' derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above 'non-canonical' helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from alpha-helicity are encoded locally in sequence patterns only about 7-9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure-function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html.

  15. Combined computational-experimental approach to predict blood-brain barrier (BBB) permeation based on "green" salting-out thin layer chromatography supported by simple molecular descriptors.

    PubMed

    Ciura, Krzesimir; Belka, Mariusz; Kawczak, Piotr; Bączek, Tomasz; Markuszewski, Michał J; Nowakowska, Joanna

    2017-09-05

    The objective of this paper is to build QSRR/QSAR model for predicting the blood-brain barrier (BBB) permeability. The obtained models are based on salting-out thin layer chromatography (SOTLC) constants and calculated molecular descriptors. Among chromatographic methods SOTLC was chosen, since the mobile phases are free of organic solvent. As consequences, there are less toxic, and have lower environmental impact compared to classical reserved phases liquid chromatography (RPLC). During the study three stationary phase silica gel, cellulose plates and neutral aluminum oxide were examined. The model set of solutes presents a wide range of log BB values, containing compounds which cross the BBB readily and molecules poorly distributed to the brain including drugs acting on the nervous system as well as peripheral acting drugs. Additionally, the comparison of three regression models: multiple linear regression (MLR), partial least-squares (PLS) and orthogonal partial least squares (OPLS) were performed. The designed QSRR/QSAR models could be useful to predict BBB of systematically synthesized newly compounds in the drug development pipeline and are attractive alternatives of time-consuming and demanding directed methods for log BB measurement. The study also shown that among several regression techniques, significant differences can be obtained in models performance, measured by R(2) and Q(2), hence it is strongly suggested to evaluate all available options as MLR, PLS and OPLS. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Prediction of water-phosphatidylcholine membrane partition coefficient of some drugs from their molecular structures.

    PubMed

    Fatemi, Mohammad Hossein; Moghaddam, Masoomeh Raei

    2012-10-01

    In this work, the phosphatidylcholine membrane-water partition coefficients (MA) of some drugs were estimated from their theoretical derived molecular descriptors by applying quantitative structure-activity relationship (QSAR) methodology. The data set consisted of 46 drugs where their log MA were determined experimentally. Descriptors used in this work were calculated by DRAGON (version 1) package, on the basis of optimized molecular structures, and the most relevant descriptors were selected by stepwise multilinear regressions (MLRs). These descriptors were used to developing linear and nonlinear models by using MLR and artificial neural networks (ANNs), respectively. During this investigation, the best QSAR model was identified when using the ANN model that produced a reasonable level of correlation coefficients (R(train) = 0.995, R(test) = 0.948) and low standard error (SE(train) = 0.099, SE(test) = 0.326). The built model was fully assessed by various validation methods, including internal and external validation test, Y-randomization test, and cross-validation (Q(2) = 0.805). The results of this investigation revealed the applicability of QSAR approaches in the estimation of phosphatidylcholine membrane-water partition coefficients.

  17. Structural details (kinks and non-α conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors

    PubMed Central

    Rigoutsos, Isidore; Riek, Peter; Graham, Robert M.; Novotny, Jiri

    2003-01-01

    One of the promising methods of protein structure prediction involves the use of amino acid sequence-derived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular α-helical character (i.e. π-helices, 310-helices and kinks). A ‘search engine’ derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above ‘non-canonical’ helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from α-helicity are encoded locally in sequence patterns only about 7–9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure–function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html. PMID:12888523

  18. Evaluation of structure-reactivity descriptors and biological activity spectra of 4-(6-methoxy-2-naphthyl)-2-butanone using spectroscopic techniques

    NASA Astrophysics Data System (ADS)

    Agrawal, Megha; Deval, Vipin; Gupta, Archana; Sangala, Bagvanth Reddy; Prabhu, S. S.

    2016-10-01

    The structure and several spectroscopic features along with reactivity parameters of the compound 4-(6-methoxy-2-naphthyl)-2-butanone (Nabumetone) have been studied using experimental techniques and tools derived from quantum chemical calculations. Structure optimization is followed by force field calculations based on density functional theory (DFT) at the B3LYP/6-311++G(d,p) level of theory. The vibrational spectra have been interpreted with the aid of normal coordinate analysis. UV-visible spectrum and the effect of solvent have been discussed. The electronic properties such as HOMO and LUMO energies have been determined by TD-DFT approach. In order to understand various aspects of pharmacological sciences several new chemical reactivity descriptors - chemical potential, global hardness and electrophilicity have been evaluated. Local reactivity descriptors - Fukui functions and local softnesses have also been calculated to find out the reactive sites within molecule. Aqueous solubility and lipophilicity have been calculated which are crucial for estimating transport properties of organic molecules in drug development. Estimation of biological effects, toxic/side effects has been made on the basis of prediction of activity spectra for substances (PASS) prediction results and their analysis by Pharma Expert software. Using the THz-TDS technique, the frequency-dependent absorptions of NBM have been measured in the frequency range up to 3 THz.

  19. Biological spectra analysis: Linking biological activity profiles to molecular structure

    PubMed Central

    Fliri, Anton F.; Loging, William T.; Thadeio, Peter F.; Volkmann, Robert A.

    2005-01-01

    Establishing quantitative relationships between molecular structure and broad biological effects has been a longstanding challenge in science. Currently, no method exists for forecasting broad biological activity profiles of medicinal agents even within narrow boundaries of structurally similar molecules. Starting from the premise that biological activity results from the capacity of small organic molecules to modulate the activity of the proteome, we set out to investigate whether descriptor sets could be developed for measuring and quantifying this molecular property. Using a 1,567-compound database, we show that percent inhibition values, determined at single high drug concentration in a battery of in vitro assays representing a cross section of the proteome, provide precise molecular property descriptors that identify the structure of molecules. When broad biological activity of molecules is represented in spectra form, organic molecules can be sorted by quantifying differences between biological spectra. Unlike traditional structure–activity relationship methods, sorting of molecules by using biospectra comparisons does not require knowledge of a molecule's putative drug targets. To illustrate this finding, we selected as starting point the biological activity spectra of clotrimazole and tioconazole because their putative target, lanosterol demethylase (CYP51), was not included in the bioassay array. Spectra similarity obtained through profile similarity measurements and hierarchical clustering provided an unbiased means for establishing quantitative relationships between chemical structures and biological activity spectra. This methodology, which we have termed biological spectra analysis, provides the capability not only of sorting molecules on the basis of biospectra similarity but also of predicting simultaneous interactions of new molecules with multiple proteins. PMID:15625110

  20. Potential energy profile, structural, vibrational and reactivity descriptors of trans-2-methoxycinnamic acid by FTIR, FT-Raman and quantum chemical studies

    NASA Astrophysics Data System (ADS)

    Arjunan, V.; Anitha, R.; Thenmozhi, S.; Marchewka, M. K.; Mohan, S.

    2016-06-01

    The stable conformers of trans-2-methoxycinnamic acid (trans-2MCA) are determined by potential energy profile analysis. The energies of the s-cis and s-trans conformers of trans-2MCA determined by B3LYP/cc-pVTZ method are -612.9788331 Hartrees and -612.9780953 Hartrees, respectively. The vibrational and electronic investigations of the stable s-cis and s-trans conformers of trans-2-methoxycinnamic acid have been carried out extensively with FTIR and FT-Raman spectral techniques. The s-cis conformer (I) with a (C16-C17-C18-O19) dihedral angle equal to 0° is found to be more favoured relative to the one s-trans (II) with (C16-C17-C18-O19) = 180°, possibly due to delocalization, hydrogen bonding and steric repulsion effects between the methoxy and acrylic acid groups. The DFT studies are performed with B3LYP method by utilizing 6-311++G** and cc-pVTZ basis sets to determine the structure, thermodynamic properties, vibrational characteristics and chemical shifts of the compound. The total dipole moments of the conformers determined by B3LYP/cc-pVTZ method are 3.35 D and 4.87 D for s-cis and s-trans, respectively. It reveals the higher polarity of s-trans conformer of trans-2MCA molecule. The electronic and steric influence of the methoxy group on the skeletal frequencies has been analysed. The energies of the frontier molecular orbitals and the LUMO-HOMO energy gap have been determined. The MEP of s-cis conformer lie in the range +1.374e × 10-2 to -1.374e × 10-2 while for s-trans it is +1.591e × 10-2 to -1.591e × 10-2. The total electron density of s-cis conformer lie in the range +5.273e × 10-2 to -5.273e × 10-2 while for s-trans it is +5.403e × 10-2 to -5.403e × 10-2. The MEP and total electron density shows that the s-cis conformer is less polar, less reactive and more stable than the s-trans conformer. All the reactivity descriptors of the molecule have been discussed. Intramolecular electronic interactions and their stabilisation energies have analysed

  1. Effects of surface water on gas sorption capacities of gravimetric sensing layers analyzed by molecular descriptors of organic adsorbates.

    PubMed

    Sugimoto, Iwao; Mitsui, Kouta; Nakamura, Masayuki; Seyama, Michiko

    2011-02-01

    The gas sorption capacities of sputtered carbonaceous films are evaluated with quartz crystal resonators. These films are sensitive to 20 ppm organic vapors and exhibit structure-dependent responses. Films derived from synthetic polymers are hydrophobic, whereas films derived from biomaterials are amphiphilic or hydrophilic. Polyethylene (PE) film has an extremely high sorption capacity for a wide range of vapors. Transient sorption responses are investigated using a humidified carrier by employing carboxylic acid esters, whose aliphatic groups are systematically changed. Small esters with a higher affinity to water induce negative U-shaped responses from amphiphilic films derived from biomaterials. On the other hand, polymeric films exhibit positive exponential response curves. Even if the concentrations are decreased, the response intensities are enhanced with the incremental expansion of carbon chains of aliphatic groups. Only fluoropolymer film shows the opposite tendency. The modeling of quantitative structure property relationships has indicated that the sorption capacities of the PE film to the carboxylic acid esters are fundamentally governed by electrostatic interactions. The intermolecular attractive forces are basically attributable to interactions between the positively polarized sites in esters and the negatively polarized/charged sites in PE film.

  2. In silico prediction and screening of gamma-secretase inhibitors by molecular descriptors and machine learning methods.

    PubMed

    Yang, Xue-Gang; Lv, Wei; Chen, Yu-Zong; Xue, Ying

    2010-04-30

    Gamma-secretase inhibitors have been explored for the prevention and treatment of Alzheimer's disease (AD). Methods for prediction and screening of gamma-secretase inhibitors are highly desired for facilitating the design of novel therapeutic agents against AD, especially when incomplete knowledge about the mechanism and three-dimensional structure of gamma-secretase. We explored two machine learning methods, support vector machine (SVM) and random forest (RF), to develop models for predicting gamma-secretase inhibitors of diverse structures. Quantitative analysis of the receiver operating characteristic (ROC) curve was performed to further examine and optimize the models. Especially, the Youden index (YI) was initially introduced into the ROC curve of RF so as to obtain an optimal threshold of probability for prediction. The developed models were validated by an external testing set with the prediction accuracies of SVM and RF 96.48 and 98.83% for gamma-secretase inhibitors and 98.18 and 99.27% for noninhibitors, respectively. The different feature selection methods were used to extract the physicochemical features most relevant to gamma-secretase inhibition. To the best of our knowledge, the RF model developed in this work is the first model with a broad applicability domain, based on which the virtual screening of gamma-secretase inhibitors against the ZINC database was performed, resulting in 368 potential hit candidates. 2009 Wiley Periodicals, Inc.

  3. Logistic regression models to predict solvent accessible residues using sequence- and homology-based qualitative and quantitative descriptors applied to a domain-complete X-ray structure learning set

    PubMed Central

    Nepal, Reecha; Spencer, Joanna; Bhogal, Guneet; Nedunuri, Amulya; Poelman, Thomas; Kamath, Thejas; Chung, Edwin; Kantardjieff, Katherine; Gottlieb, Andrea; Lustig, Brooke

    2015-01-01

    A working example of relative solvent accessibility (RSA) prediction for proteins is presented. Novel logistic regression models with various qualitative descriptors that include amino acid type and quantitative descriptors that include 20- and six-term sequence entropy have been built and validated. A domain-complete learning set of over 1300 proteins is used to fit initial models with various sequence homology descriptors as well as query residue qualitative descriptors. Homology descriptors are derived from BLASTp sequence alignments, whereas the RSA values are determined directly from the crystal structure. The logistic regression models are fitted using dichotomous responses indicating buried or accessible solvent, with binary classifications obtained from the RSA values. The fitted models determine binary predictions of residue solvent accessibility with accuracies comparable to other less computationally intensive methods using the standard RSA threshold criteria 20 and 25% as solvent accessible. When an additional non-homology descriptor describing Lobanov–Galzitskaya residue disorder propensity is included, incremental improvements in accuracy are achieved with 25% threshold accuracies of 76.12 and 74.79% for the Manesh-215 and CASP(8+9) test sets, respectively. Moreover, the described software and the accompanying learning and validation sets allow students and researchers to explore the utility of RSA prediction with simple, physically intuitive models in any number of related applications. PMID:26664348

  4. Reversed-phase TLC and HPLC retention data in correlation studies with in silico molecular descriptors and druglikeness properties of newly synthesized anticonvulsant succinimide derivatives.

    PubMed

    Perisic-Janjic, Nada; Kaliszan, Roman; Wiczling, Paweł; Milosevic, Natasa; Uscumlic, Gordana; Banjac, Nebojsa

    2011-04-04

    The properties relevant to pharmacokinetics of two series of newly synthesized succinimide derivatives have been studied. The properties under consideration have been either determined empirically, by reversed-phase liquid chromatography (TLC and HPLC technique), or calculated with the use of established theoretical medicinal chemistry/drug design software. Chromatographic techniques allowed determination of the retention constants R(M)⁰ and log k(w), which characterize lipophilicity of compounds. Considering potential pharmaceutical importance of succinimide derivatives, we (i) examined the retention behavior in the reversed-phase liquid chromatographic (RP LC) systems, in both planar and column LC, and (ii) determined the relationships between chromatographic data and selected structural features of analytes that are believed to markedly affect their processes of absorption, distribution, metabolism, excretion and toxicity (ADMETox). Significant relationships were found between the retention constants, R(M)⁰ and log k(w), and the in silico calculated bioactivity descriptors, in particular HIA (human intestinal absorption) and PPB (plasma protein binding) parameters. The R(M)⁰ and log k(w) values of the investigated compounds have been recommended for description of their lipophilicity and evaluating pharmacokinetic properties. In view of results of this study the newly synthesized succinimide agents meet pharmacokinetic criteria of preselection of drug candidates and hence qualify for pharmacodynamic phase of antiepileptic drug development. Best compromising human intestinal absorption and plasma protein binding features appear to be compounds A4, A5, A10 and A11.

  5. Evaluation of angiotensin-converting enzyme inhibitor's absorption with retention data of micellar thin-layer chromatography and suitable molecular descriptor.

    PubMed

    Odovic, Jadranka; Markovic, Bojan; Vladimirov, Sote; Karljikovic-Rajic, Katarina

    2015-01-01

    Twelve angiotensin-converting enzyme (ACE) inhibitors were studied to evaluate correlation between their absorption (ABS) data available in the literature (22-96%) and hydrophobicity parameters (km and Pm/w) obtained in micellar thin-layer chromatography (MTLC) using Brij 35. The theoretical considerations showed that the geometric molecular descriptor-volume value (Vol) should be considered as an independent variable simultaneously with calculated hydrophobicity parameters in multiple linear regression analysis to obtain reliable correlation between ACE inhibitor's absorption and lipophilicity (calculated KOWWINlog P) and that captopril should be excluded from further correlations. The results of MTLC confirmed that between the two hydrophobicity parameters km and Pm/w, for absorption prediction of 11 ACE inhibitors, the micelle-water partition coefficient Pm/w provided higher correlation (R(2) = 0.756), while for the km parameter R(2) = 0.612 was obtained. The micelle-water partition coefficient Pm/w could be considered as analogous to hydrophobicity parameter C0 from reversed-phase thin-layer chromatography. Dissimilar retention behavior of lisinopril indicated its lowest non-polar interaction with micelle, because of its di-acid form. The proposed model which included ACE inhibitors on the opposite site of lipophilicity-lisinopril and fosinopril (KOWWINlog P = -0.96 and KOWWINlog P = 6.61, respectively), both with similar absorption values (25 and 36%, respectively), could indicate that absorption of investigated compounds occurs via two different mechanisms: active and passive transport. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. New quantitative structure-fragmentation relationship strategy for chemical structure identification using the calculated enthalpy of formation as a descriptor for the fragments produced in electron ionization mass spectrometry: a case study with tetrachlorinated biphenyls.

    PubMed

    Dinca, Nicolae; Dragan, Simona; Dinca, Mihael; Sisu, Eugen; Covaci, Adrian

    2014-05-20

    Differential mass spectrometry correlated with quantum chemical calculations (QCC-ΔMS) has been shown to be an efficient tool for the chemical structure identification (CSI) of isomers with similar mass spectra. For this type of analysis, we report here a new strategy based on ordering (ORD), linear correlation (LCOR) algorithms, and their coupling, to filter the most probable structures corresponding to similar mass spectra belonging to a group with dozens of isomers (e.g., tetrachlorinated biphenyls, TeCBs). This strategy quantifies and compares the values of enthalpies of formation (Δ(f)H) obtained by QCC for some isobaric ions from the electron ionization (EI)-MS mass spectra, to the corresponding relative intensities. The result of CSI is provided in the form of lists of decreasing probabilities calculated for all the position-isomeric structures using the specialized software package CSI-Diff-MS Analysis 3.1.1. The simulation of CSI with ORD, LCOR, and their coupling of six TeCBs (IUPAC no. 44, 46, 52, 66, 74, and 77) has allowed us to find the best semiempirical molecular-orbital methods for several of their common isobaric fragments. The study of algorithms and strategy for the entire group of TeCBs (42 isomers) was made with one of the optimal variants for the computation of Δ(f)H using semiempirical molecular orbital methods of HyperChem: AM1 for M(+•) and [M - 4Cl](+•) ions and RM1 for [M - Cl](+) and [M - 2Cl](+•). The analytical performance of ORD, LCOR, and their coupling resulted from the CSI simulation of an analyte of known structure, using a decreasing number of isomeric standards, s = 5, 4, 3, and 2. Compared with the results obtained by a classical library search for TeCB isomers, the novel strategies of assigning structures of isomers with very similar mass spectra based on ORD, LCOR, and their coupling were much more efficient, because they provide the correct structure at the top of the probability list. Databases used in these CSI

  7. Atom-type-based AI topological descriptors: application in structure-boiling point correlations of oxo organic compounds.

    PubMed

    Ren, Biye

    2003-01-01

    Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.

  8. Nanogap structures for molecular nanoelectronics.

    PubMed

    Motto, Paolo; Dimonte, Alice; Rattalino, Ismael; Demarchi, Danilo; Piccinini, Gianluca; Civera, Pierluigi

    2012-02-09

    This study is focused on the realization of nanodevices for nano and molecular electronics, based on molecular interactions in a metal-molecule-metal (M-M-M) structure. In an M-M-M system, the electronic function is a property of the structure and can be characterized through I/V measurements. The contact between the metals and the molecule was obtained by gold nanogaps (with a dimension of less than 10 nm), produced with the electromigration technique. The nanogap fabrication was controlled by a custom hardware and the related software system. The studies were carried out through experiments and simulations of organic molecules, in particular oligothiophenes.

  9. Nanogap structures for molecular nanoelectronics

    PubMed Central

    2012-01-01

    This study is focused on the realization of nanodevices for nano and molecular electronics, based on molecular interactions in a metal-molecule-metal (M-M-M) structure. In an M-M-M system, the electronic function is a property of the structure and can be characterized through I/V measurements. The contact between the metals and the molecule was obtained by gold nanogaps (with a dimension of less than 10 nm), produced with the electromigration technique. The nanogap fabrication was controlled by a custom hardware and the related software system. The studies were carried out through experiments and simulations of organic molecules, in particular oligothiophenes. PMID:22321736

  10. The recent progress in proteochemometric modelling: focusing on target descriptors, cross-term descriptors and application scope.

    PubMed

    Qiu, Tianyi; Qiu, Jingxuan; Feng, Jun; Wu, Dingfeng; Yang, Yiyan; Tang, Kailin; Cao, Zhiwei; Zhu, Ruixin

    2017-01-01

    As an extension of the conventional quantitative structure activity relationship models, proteochemometric (PCM) modelling is a computational method that can predict the bioactivity relations between multiple ligands and multiple targets. Traditional PCM modelling includes three essential elements: descriptors (including target descriptors, ligand descriptors and cross-term descriptors), bioactivity data and appropriate learning functions that link the descriptors to the bioactivity data. Since its appearance, PCM modelling has developed rapidly over the past decade by taking advantage of the progress of different descriptors and machine learning techniques, along with the increasing amounts of available bioactivity data. Specifically, the new emerging target descriptors and cross-term descriptors not only significantly increased the performance of PCM modelling but also expanded its application scope from traditional protein-ligand interaction to more abundant interactions, including protein-peptide, protein-DNA and even protein-protein interactions. In this review, target descriptors and cross-term descriptors, as well as the corresponding application scope, are intensively summarized. Additionally, we look forward to seeing PCM modelling extend into new application scopes, such as Target-Catalyst-Ligand systems, with the further development of descriptors, machine learning techniques and increasing amounts of available bioactivity data. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  11. Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG

    PubMed Central

    Bigdely-Shamlo, Nima; Cockfield, Jeremy; Makeig, Scott; Rognon, Thomas; La Valle, Chris; Miyakoshi, Makoto; Robbins, Kay A.

    2016-01-01

    Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies. PMID:27799907

  12. Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG.

    PubMed

    Bigdely-Shamlo, Nima; Cockfield, Jeremy; Makeig, Scott; Rognon, Thomas; La Valle, Chris; Miyakoshi, Makoto; Robbins, Kay A

    2016-01-01

    Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies.

  13. Student Descriptor Scale Manual.

    ERIC Educational Resources Information Center

    Goetz, Lori; And Others

    The Student Descriptor Scale (SDS) was developed as a validation measure to determine whether students described and counted by states as "severely handicapped" were, indeed, students with severe disabilities. The SDS addresses nine characteristics: intellectual disability, health impairment, need for toileting assistance, upper torso motor…

  14. Learning discriminant face descriptor.

    PubMed

    Lei, Zhen; Pietikäinen, Matti; Li, Stan Z

    2014-02-01

    Local feature descriptor is an important module for face recognition and those like Gabor and local binary patterns (LBP) have proven effective face descriptors. Traditionally, the form of such local descriptors is predefined in a handcrafted way. In this paper, we propose a method to learn a discriminant face descriptor (DFD) in a data-driven way. The idea is to learn the most discriminant local features that minimize the difference of the features between images of the same person and maximize that between images from different people. In particular, we propose to enhance the discriminative ability of face representation in three aspects. First, the discriminant image filters are learned. Second, the optimal neighborhood sampling strategy is soft determined. Third, the dominant patterns are statistically constructed. Discriminative learning is incorporated to extract effective and robust features. We further apply the proposed method to the heterogeneous (cross-modality) face recognition problem and learn DFD in a coupled way (coupled DFD or C-DFD) to reduce the gap between features of heterogeneous face images to improve the performance of this challenging problem. Extensive experiments on FERET, CAS-PEAL-R1, LFW, and HFB face databases validate the effectiveness of the proposed DFD learning on both homogeneous and heterogeneous face recognition problems. The DFD improves POEM and LQP by about 4.5 percent on LFW database and the C-DFD enhances the heterogeneous face recognition performance of LBP by over 25 percent.

  15. Molecular structure and elastic properties of thermotropic liquid crystals: integrated molecular dynamics--statistical mechanical theory vs molecular field approach.

    PubMed

    Ilk Capar, M; Nar, A; Ferrarini, A; Frezza, E; Greco, C; Zakharov, A V; Vakulenko, A A

    2013-03-21

    The connection between the molecular structure of liquid crystals and their elastic properties, which control the director deformations relevant for electro-optic applications, remains a challenging objective for theories and computations. Here, we compare two methods that have been proposed to this purpose, both characterized by a detailed molecular level description. One is an integrated molecular dynamics-statistical mechanical approach, where the bulk elastic constants of nematics are calculated from the direct correlation function (DCFs) and the single molecule orientational distribution function [D. A. McQuarrie, Statistical Mechanics (Harper & Row, New York, 1973)]. The latter is obtained from atomistic molecular dynamics trajectories, together with the radial distribution function, from which the DCF is then determined by solving the Ornstein-Zernike equation. The other approach is based on a molecular field theory, where the potential of mean torque experienced by a mesogen in the liquid crystal phase is parameterized according to its molecular surface. In this case, the calculation of elastic constants is combined with the Monte Carlo sampling of single molecule conformations. Using these different approaches, but the same description, at the level of molecular geometry and torsional potentials, we have investigated the elastic properties of the nematic phase of two typical mesogens, 4'-n-pentyloxy-4-cyanobiphenyl and 4'-n-heptyloxy-4-cyanobiphenyl. Both methods yield K3(bend) >K1 (splay) >K2 (twist), although there are some discrepancies in the average elastic constants and in their anisotropy. These are interpreted in terms of the different approximations and the different ways of accounting for the structural properties of molecules in the two approaches. In general, the results point to the role of the molecular shape, which is modulated by the conformational freedom and cannot be fully accounted for by a single descriptor such as the aspect ratio.

  16. Molecular structure and elastic properties of thermotropic liquid crystals: Integrated molecular dynamics—Statistical mechanical theory vs molecular field approach

    NASA Astrophysics Data System (ADS)

    Capar, M. Ilk; Nar, A.; Ferrarini, A.; Frezza, E.; Greco, C.; Zakharov, A. V.; Vakulenko, A. A.

    2013-03-01

    The connection between the molecular structure of liquid crystals and their elastic properties, which control the director deformations relevant for electro-optic applications, remains a challenging objective for theories and computations. Here, we compare two methods that have been proposed to this purpose, both characterized by a detailed molecular level description. One is an integrated molecular dynamics-statistical mechanical approach, where the bulk elastic constants of nematics are calculated from the direct correlation function (DCFs) and the single molecule orientational distribution function [D. A. McQuarrie, Statistical Mechanics (Harper & Row, New York, 1973)]. The latter is obtained from atomistic molecular dynamics trajectories, together with the radial distribution function, from which the DCF is then determined by solving the Ornstein-Zernike equation. The other approach is based on a molecular field theory, where the potential of mean torque experienced by a mesogen in the liquid crystal phase is parameterized according to its molecular surface. In this case, the calculation of elastic constants is combined with the Monte Carlo sampling of single molecule conformations. Using these different approaches, but the same description, at the level of molecular geometry and torsional potentials, we have investigated the elastic properties of the nematic phase of two typical mesogens, 4'-n-pentyloxy-4-cyanobiphenyl and 4'-n-heptyloxy-4-cyanobiphenyl. Both methods yield K3(bend) >K1 (splay) >K2 (twist), although there are some discrepancies in the average elastic constants and in their anisotropy. These are interpreted in terms of the different approximations and the different ways of accounting for the structural properties of molecules in the two approaches. In general, the results point to the role of the molecular shape, which is modulated by the conformational freedom and cannot be fully accounted for by a single descriptor such as the aspect ratio.

  17. Quantitative structure-property relationships for predicting Henry's law constant from molecular structure.

    PubMed

    Dearden, John C; Schüürmann, Gerrit

    2003-08-01

    Various models are available for the prediction of Henry's law constant (H) or the air-water partition coefficient (Kaw), its dimensionless counterpart. Incremental methods are based on structural features such as atom types, bond types, and local structural environments; other regression models employ physicochemical properties, structural descriptors such as connectivity indices, and descriptors reflecting the electronic structure. There are also methods to calculate H from the ratio of vapor pressure (p(v)) and water solubility (S(w)) that in turn can be estimated from molecular structure, and quantum chemical continuum-solvation models to predict H via the solvation-free energy (deltaG(s)). This review is confined to methods that calculate H from molecular structure without experimental information and covers more than 40 methods published in the last 26 years. For a subset of eight incremental methods and four continuum-solvation models, a comparative analysis of their prediction performance is made using a test set of 700 compounds that includes a significant number of more complex and drug-like chemical structures. The results reveal substantial differences in the application range as well as in the prediction capability, a general decrease in prediction performance with decreasing H, and surprisingly large individual prediction errors, which are particularly striking for some quantum chemical schemes. The overall best-performing method appears to be the bond contribution method as implemented in the HENRYWIN software package, yielding a predictive squared correlation coefficient (q2) of 0.87 and a standard error of 1.03 log units for the test set.

  18. QSPR modeling of thermal stability of nitroaromatic compounds: DFT vs. AM1 calculated descriptors.

    PubMed

    Fayet, Guillaume; Rotureau, Patricia; Joubert, Laurent; Adamo, Carlo

    2010-04-01

    The quantitative structure-property relationship (QSPR) methodology was applied to predict the decomposition enthalpies of 22 nitroaromatic compounds, used as indicators of thermal stability. An extended series of descriptors (constitutional, topological, geometrical charge related and quantum chemical) was calculated at two different levels of theory: density functional theory (DFT) and semi-empirical AM1 approaches. Reliable models have been developed for each level, leading to similar correlations between calculated and experimental data (R(2) > 0.98). Hence, both of them can be employed as screening tools for the prediction of thermal stability of nitroaromatic compounds. If using the AM1 model presents the advantage to be less time consuming, DFT allows the calculation of more accurate molecular quantum properties, e.g., conceptual DFT descriptors. In this study, our best QSPR model is based on such descriptors, providing more chemical comprehensive relationships with decomposition reactivity, a particularly complex property for the specific class of nitroaromatic compounds.

  19. Image Descriptors for Displays

    DTIC Science & Technology

    1977-02-01

    information. In Section V of the report, however, we have extended our descriptor for the total channel capacity of a display to include both chromi - nance and...frequency and for constant chromi - nance. The quantities nl(w) represent the number of perceivable colors for a given spatial frequancy and luminance value...the chromi - nance contribution to the total channel capacity, we shall utilize a linear model for thot distribution of perceived chrominance levels. We

  20. Admissible consensus for heterogeneous descriptor multi-agent systems

    NASA Astrophysics Data System (ADS)

    Yang, Xin-Rong; Liu, Guo-Ping

    2016-09-01

    This paper focuses on the admissible consensus problem for heterogeneous descriptor multi-agent systems. Based on algebra, graph and descriptor system theory, the necessary and sufficient conditions are proposed for heterogeneous descriptor multi-agent systems achieving admissible consensus. The provided conditions depend on not only the structure properties of each agent dynamics but also the topologies within the descriptor multi-agent systems. Moreover, an algorithm is given to design the novel consensus protocol. A numerical example demonstrates the effectiveness of the proposed design approach.

  1. STING Report: convenient web-based application for graphic and tabular presentations of protein sequence, structure and function descriptors from the STING database

    PubMed Central

    Neshich, Goran; Mancini, Adauto L.; Yamagishi, Michel E. B.; Kuser, Paula R.; Fileto, Renato; Pinto, Ivan P.; Palandrani, Juliana F.; Krauchenco, João N.; Baudet, Christian; Montagner, Arnaldo J.; Higa, Roberto H.

    2005-01-01

    The Sting Report is a versatile web-based application for extraction and presentation of detailed information about any individual amino acid of a protein structure stored in the STING Database. The extracted information is presented as a series of GIF images and tables, containing the values of up to 125 sequence/structure/function descriptors/parameters. The GIF images are generated by the Gold STING modules. The HTML page resulting from the STING Report query can be printed and, most importantly, it can be composed and visualized on a computer platform with an elementary configuration. Using the STING Report, a user can generate a collection of customized reports for amino acids of specific interest. Such a collection comes as an ideal match for a demand for the rapid and detailed consultation and documentation of data about structure/function. The inclusion of information generated with STING Report in a research report or even a textbook, allows for the increased density of its contents. STING Report is freely accessible within the Gold STING Suite at http://www.cbi.cnptia.embrapa.br, http://www.es.embnet.org/SMS/, http://gibk26.bse.kyutech.ac.jp/SMS/ and http://trantor.bioc.columbia.edu/SMS (option: STING Report). PMID:15608194

  2. STING Report: convenient web-based application for graphic and tabular presentations of protein sequence, structure and function descriptors from the STING database.

    PubMed

    Neshich, Goran; Mancini, Adauto L; Yamagishi, Michel E B; Kuser, Paula R; Fileto, Renato; Pinto, Ivan P; Palandrani, Juliana F; Krauchenco, João N; Baudet, Christian; Montagner, Arnaldo J; Higa, Roberto H

    2005-01-01

    The Sting Report is a versatile web-based application for extraction and presentation of detailed information about any individual amino acid of a protein structure stored in the STING Database. The extracted information is presented as a series of GIF images and tables, containing the values of up to 125 sequence/structure/function descriptors/parameters. The GIF images are generated by the Gold STING modules. The HTML page resulting from the STING Report query can be printed and, most importantly, it can be composed and visualized on a computer platform with an elementary configuration. Using the STING Report, a user can generate a collection of customized reports for amino acids of specific interest. Such a collection comes as an ideal match for a demand for the rapid and detailed consultation and documentation of data about structure/function. The inclusion of information generated with STING Report in a research report or even a textbook, allows for the increased density of its contents. STING Report is freely accessible within the Gold STING Suite at http://www.cbi.cnptia.embrapa.br, http://www.es.embnet.org/SMS/, http://gibk26.bse.kyutech.ac.jp/SMS/ and http://trantor.bioc.columbia.edu/SMS (option: STING Report).

  3. Local Descriptors of Dynamic and Nondynamic Correlation.

    PubMed

    Ramos-Cordoba, Eloy; Matito, Eduard

    2017-06-13

    Quantitatively accurate electronic structure calculations rely on the proper description of electron correlation. A judicious choice of the approximate quantum chemistry method depends upon the importance of dynamic and nondynamic correlation, which is usually assesed by scalar measures. Existing measures of electron correlation do not consider separately the regions of the Cartesian space where dynamic or nondynamic correlation are most important. We introduce real-space descriptors of dynamic and nondynamic electron correlation that admit orbital decomposition. Integration of the local descriptors yields global numbers that can be used to quantify dynamic and nondynamic correlation. Illustrative examples over different chemical systems with varying electron correlation regimes are used to demonstrate the capabilities of the local descriptors. Since the expressions only require orbitals and occupation numbers, they can be readily applied in the context of local correlation methods, hybrid methods, density matrix functional theory, and fractional-occupancy density functional theory.

  4. New developments in PEST shape/property hybrid descriptors

    NASA Astrophysics Data System (ADS)

    Breneman, Curt M.; Sundling, C. Matthew; Sukumar, N.; Shen, Lingling; Katt, William P.; Embrechts, Mark J.

    2003-02-01

    Recent investigations have shown that the inclusion of hybrid shape/property descriptors together with 2D topological descriptors increases the predictive capability of QSAR and QSPR models. Property-Encoded Surface Translator (PEST) descriptors may be computed using ab initio or semi-empirical electron density surfaces and/or electronic properties, as well as atomic fragment-based TAE/RECON property-encoded surface reconstructions. The RECON and PEST algorithms also include rapid fragment-based wavelet coefficient descriptor (WCD) computation. These descriptors enable a compact encoding of chemical information. We also briefly discuss the use of the RECON/PEST methodology in a virtual high-throughput mode, as well as the use of TAE properties for molecular surface autocorrelation analysis.

  5. Complementing ultrafast shape recognition with an optical isomerism descriptor.

    PubMed

    Zhou, Ting; Lafleur, Karine; Caflisch, Amedeo

    2010-11-01

    We introduce the mixed product of three vectors spanning four molecular locations as a descriptor of optical isomerism. This descriptor is very efficient as it does not require molecular superposition, and is very robust in discriminating between a given isomer and its mirror image. In particular, conformational isomers that are mirror images of each other, as well as optical isomers have opposite sign of the descriptor value. For efficient database searches, the optical isomerism descriptor can be used to complement an available ultrafast shape recognition (USR) method based solely on distances, which is not able to distinguish enantiomers. By an extensive comparison of the USR-based similarity score with an approach based on Gaussian molecular volume overlap, the accuracy and completeness of the former are discussed.

  6. Analysis of the antioxidant activity of 4-(5-chloro-2-hydroxyphenylamino)-4-oxobut-2-enoic acid derivatives using quantum-chemistry descriptors and molecular docking.

    PubMed

    Ardjani, Ahmed Taki Eddine; Mekelleche, Sidi Mohamed

    2016-12-01

    In the present work, the molecular structure and the antioxidant activity of 4-(5-chloro-2-hydroxyphenylamino)-4-oxobut-2-enoic acid (A) and its derivatives (B-E) have been studied at the B3LYP/6-31++G(2d,2p) computational level. The obtained results indicate that the hydrogen atom transfer (HAT mechanism) is thermodynamically more favored in gas phase; whereas, the sequential proton loss-electron transfer (SPLET mechanism) is more preferred in polar solvents. The antioxidant activity of compounds A-E is also analyzed by the calculation of atomic spin densities, chemical hardnesses, dipole moments, and lipophilicity indexes. It turns out that compound E (R = t-Bu) is predicted to be more antioxidant than ascorbic acid and other derivatives A-D in both gas phase and polar solvents. The high antioxidant activity of compound E compared to other derivatives A-D is also rationalized using the molecular docking technique.

  7. Application of the quantum mechanical IEF/PCM-MST hydrophobic descriptors to selectivity in ligand binding.

    PubMed

    Ginex, Tiziana; Muñoz-Muriedas, Jordi; Herrero, Enric; Gibert, Enric; Cozzini, Pietro; Luque, F Javier

    2016-06-01

    We have recently reported the development and validation of quantum mechanical (QM)-based hydrophobic descriptors derived from the parametrized IEF/PCM-MST continuum solvation model for 3D-QSAR studies within the framework of the Hydrophobic Pharmacophore (HyPhar) method. In this study we explore the applicability of these descriptors to the analysis of selectivity fields. To this end, we have examined a series of 88 compounds with inhibitory activities against thrombin, trypsin and factor Xa, and the HyPhar results have been compared with 3D-QSAR models reported in the literature. The quantitative models obtained by combining the electrostatic and non-electrostatic components of the octanol/water partition coefficient yield results that compare well with the predictive potential of standard CoMFA and CoMSIA techniques. The results also highlight the potential of HyPhar descriptors to discriminate the selectivity of the compounds against thrombin, trypsin, and factor Xa. Moreover, the graphical representation of the hydrophobic maps provides a direct linkage with the pattern of interactions found in crystallographic structures. Overall, the results support the usefulness of the QM/MST-based hydrophobic descriptors as a complementary approach for disclosing structure-activity relationships in drug design and for gaining insight into the molecular determinants of ligand selectivity. Graphical Abstract Quantum Mechanical continuum solvation calculations performed with the IEF/PCM-MST method are used to derived atomic hydrophobic descriptors, which are then used to discriminate the selectivity of ligands against thrombin, trypsin and factor Xa. The descriptors provide complementary view to standard 3D-QSAR analysis, leading to a more comprehensive understanding of ligand recognition.

  8. Multi-Scale Surface Descriptors

    PubMed Central

    Cipriano, Gregory; Phillips, George N.; Gleicher, Michael

    2010-01-01

    Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis. PMID:19834190

  9. Structural Descriptors of Zeolitic-Imidazolate Frameworks Are Keys to the Activity of Fe-N-C Catalysts.

    PubMed

    Armel, Vanessa; Hindocha, Sheena; Salles, Fabrice; Bennett, Stephen; Jones, Deborah; Jaouen, Frédéric

    2017-01-11

    Active and inexpensive catalysts for oxygen reduction are crucially needed for the widespread development of polymer electrolyte fuel cells and metal-air batteries. While iron-nitrogen-carbon materials pyrolytically prepared from ZIF-8, a specific zeolitic imidazolate framework (ZIF) with sodalite topology, have shown enhanced activities toward oxygen reduction in acidic electrolyte, the rational design of sacrificial metal-organic frameworks toward this application has hitherto remained elusive. Here, we report for the first time that the oxygen reduction activity of Fe-N-C catalysts positively correlates with the cavity size and mass-specific pore volume in pristine ZIFs. The high activity of Fe-N-C materials prepared from ZIF-8 could be rationalized, and another ZIF structure leading to even higher activity was identified. In contrast, the ORR activity is mostly unaffected by the ligand chemistry in pristine ZIFs. These structure-property relationships will help identifying novel sacrificial ZIF or porous metal-organic frameworks leading to even more active Fe-N-C catalysts. The findings are of great interest for a broader application of the class of inexpensive metal-nitrogen-carbon catalysts that have shown promising activity also for the hydrogen evolution (Co-N-C) and carbon dioxide reduction (Fe-N-C and Mn-N-C).

  10. Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex.

    PubMed

    Ben Ahmed, Olfa; Mizotin, Maxim; Benois-Pineau, Jenny; Allard, Michèle; Catheline, Gwénaëlle; Ben Amar, Chokri

    2015-09-01

    Recently, several pattern recognition methods have been proposed to automatically discriminate between patients with and without Alzheimer's disease using different imaging modalities: sMRI, fMRI, PET and SPECT. Classical approaches in visual information retrieval have been successfully used for analysis of structural MRI brain images. In this paper, we use the visual indexing framework and pattern recognition analysis based on structural MRI data to discriminate three classes of subjects: normal controls (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD). The approach uses the circular harmonic functions (CHFs) to extract local features from the most involved areas in the disease: hippocampus and posterior cingulate cortex (PCC) in each slice in all three brain projections. The features are quantized using the Bag-of-Visual-Words approach to build one signature by brain (subject). This yields a transformation of a full 3D image of brain ROIs into a 1D signature, a histogram of quantized features. To reduce the dimensionality of the signature, we use the PCA technique. Support vector machines classifiers are then applied to classify groups. The experiments were conducted on a subset of ADNI dataset and applied to the "Bordeaux-3City" dataset. The results showed that our approach achieves respectively for ADNI dataset and "Bordeaux-3City" dataset; for AD vs NC classification, an accuracy of 83.77% and 78%, a specificity of 88.2% and 80.4% and a sensitivity of 79.09% and 74.7%. For NC vs MCI classification we achieved for the ADNI datasets an accuracy of 69.45%, a specificity of 74.8% and a sensitivity of 62.52%. For the most challenging classification task (AD vs MCI), we reached an accuracy of 62.07%, a specificity of 75.15% and a sensitivity of 49.02%. The use of PCC visual features description improves classification results by more than 5% compared to the use of hippocampus features only. Our approach is automatic, less time-consuming and does

  11. Discrete Derivatives for Atom-Pairs as a Novel Graph-Theoretical Invariant for Generating New Molecular Descriptors: Orthogonality, Interpretation and QSARs/QSPRs on Benchmark Databases.

    PubMed

    Martínez-Santiago, Oscar; Millán-Cabrera, Reisel; Marrero-Ponce, Yovani; Barigye, Stephen J; Martínez-López, Yoan; Torrens, Francisco; Pérez-Giménez, Facundo

    2014-05-01

    This report presents a new mathematical method based on the concept of the derivative of a molecular graph (G) with respect to a given event (S) to codify chemical structure information. The derivate over each pair of atoms in the molecule is defined as ∂G/∂S(vi  , vj )=(fi -2fij +fj )/fij , where fi (or fj ) and fij are the individual frequency of atom i (or j) and the reciprocal frequency of the atoms i and j, respectively. These frequencies characterize the participation intensity of atom pairs in S. Here, the event space is composed of molecular sub-graphs which participate in the formation of the G skeleton that could be complete (representing all possible connected sub-graphs) or comprised of sub-graphs of certain orders or types or combinations of these. The atom level graph derivative index, Δi , is expressed as a linear combination of all atom pair derivatives that include the atomic nuclei i. Global [total or local (group or atom-type)] indices are obtained by applying the so called invariants over a vector of Δi values. The novel MDs are validated using a data set of 28 alkyl-alcohols and other benchmark data sets proposed by the International Academy of Mathematical Chemistry. Also, the boiling point for the alcohols, the adrenergic blocking activity of N,N-dimethyl-2-halo-phenethylamines and physicochemical properties of polychlorinated biphenyls and octanes are modeled. These models exhibit satisfactory predictive power compared with other 0-3D indices implemented successfully by other researchers. In addition, tendencies of the proposed indices are investigated using examples of various types of molecular structures, including chain-lengthening, branching, heteroatoms-content, and multiple bonds. On the other hand, the relation of atom-based derivative indices with (17) O NMR of a series of ethers and carbonyls reflects that the new MDs encode electronic, topological and steric information. Linear independence between the graph derivative

  12. Functional Constructivism: In Search of Formal Descriptors.

    PubMed

    Trofimova, Irina

    2017-10-01

    The Functional Constructivism (FC) paradigm is an alternative to behaviorism and considers behavior as being generated every time anew, based on an individual's capacities, environmental resources and demands. Walter Freeman's work provided us with evidence supporting the FC principles. In this paper we make parallels between gradual construction processes leading to the formation of individual behavior and habits, and evolutionary processes leading to the establishment of biological systems. Referencing evolutionary theory, several formal descriptors of such processes are proposed. These FC descriptors refer to the most universal aspects for constructing consistent structures: expansion of degrees of freedom, integration processes based on internal and external compatibility between systems and maintenance processes, all given in four different classes of systems: (a) Zone of Proximate Development (poorly defined) systems; (b) peer systems with emerging reproduction of multiple siblings; (c) systems with internalized integration of behavioral elements ('cruise controls'); and (d) systems capable of handling low-probability, not yet present events. The recursive dynamics within this set of descriptors acting on (traditional) downward, upward and horizontal directions of evolution, is conceptualized as diagonal evolution, or di-evolution. Two examples applying these FC descriptors to taxonomy are given: classification of the functionality of neuro-transmitters and temperament traits; classification of mental disorders. The paper is an early step towards finding a formal language describing universal tendencies in highly diverse, complex and multi-level transient systems known in ecology and biology as 'contingency cycles.'

  13. Testing the ability of rhodanine and 2, 4-thiazolidinedione to interact with the human pancreatic alpha-amylase: electron-density descriptors complement molecular docking, QM, and QM/MM dynamics calculations.

    PubMed

    Devi, Rajendran Niranjana; Khrenova, Maria G; Israel, Samuel; Anzline, Chellam; Astakhov, Andrey A; Tsirelson, Vladimir G

    2017-09-01

    A combined molecular docking, QM, and QM/MM dynamics modeling complemented with electron-density based descriptors computed at the B3LYP/6-311G++(d,p) level of theory have been carried out in order to understand the ability of the drugs rhodanine (RD) and 2,4-thiazolidinedione (TZD) in the effective treatment of type 2 diabetes mellitus. The global HOMO/LUMO descriptors provided just a very rough estimate of the chemical reactivity of both molecules, while the features of electron density studied in terms of its Laplacian and electrostatic potential allowed identifying the local electron rich/poor sites which were associated with the regions of electrophilic/nucleophilic attacks in RD and TZD. These results were thoroughly checked using the novel physically-grounded functional descriptors such as the phase-space Fisher information density and the internal kinetic electronic pressure density, which confirmed the information on bonding and lone electron pair details. The molecular docking, QM, and QM/MM dynamics analyses revealed the detailed picture of interactions of the drugs with the amino acid residues of the active site of the human pancreatic alpha-amylase protein (hPAA). The main difference in behavior of RD and TZD molecules is related to the hydrogen bond between the NH group of the ligand and Asp197. In hPAA complex with RD the proton from the NH group, which carries large positive charge (~ +0.45 e), spontaneously transfers to the carboxyl group of Asp197 and stays there, while in complex with TZD this proton frequently changes its position with the more preferable formation of covalent bond with the N atom. Upon deprotonation of the ligand, its hydrogen bonds with Arg195 and His299 become stronger. This process influences the binding with the difference of the binding constants of RD and TZD about 200 times with the higher value corresponding to the RD molecule. Thus, the cumulative results lead to the conclusion that rhodanine would have a higher

  14. Quantitative structure-hydrophobicity relationships of molecular fragments and beyond.

    PubMed

    Zou, Jian-Wei; Huang, Meilan; Huang, Jian-Xiang; Hu, Gui-Xiang; Jiang, Yong-Jun

    2016-03-01

    Quantitative structure-property relationship (QSPR) models were firstly established for the hydrophobic substituent constant (πX) using the theoretical descriptors derived solely from electrostatic potentials (EPSs) at the substituent atoms. The descriptors introduced are found to be related to hydrogen-bond basicity, hydrogen-bond acidity, cavity, or dipolarity/polarizability terms in linear solvation energy relationship, which endows the models good interpretability. The predictive capabilities of the models constructed were also verified by rigorous Monte Carlo cross-validation. Then, eight groups of meta- or para-disubstituted benzenes and one group of substituted pyridines were investigated. QSPR models for individual systems were achieved with the ESP-derived descriptors. Additionally, two QSPR models were also established for Rekker's fragment constants (foct), which is a secondary-treatment quantity and reflects average contribution of the fragment to logP. It has been demonstrated that the descriptors derived from ESPs at the fragments, can be well used to quantitatively express the relationship between fragment structures and their hydrophobic properties, regardless of the attached parent structure or the valence state. Finally, the relations of Hammett σ constant and ESP quantities were explored. It implies that σ and π, which are essential in classic QSAR and represent different type of contributions to biological activities, are also complementary in interaction site.

  15. Application of topological descriptors in QSAR and drug design: history and new trends.

    PubMed

    Gozalbes, R; Doucet, J P; Derouin, F

    2002-03-01

    Powerful methodologies for drug design and drug database screening and selection are presently available. Studies relating the structure of molecules to a property or a biological activity by means of statistical tools (QSPR and QSAR studies, respectively) are particularly relevant. An important point for this methodology is the use of good structural descriptors that are representative of the molecular features responsible for the relevant activity. Topological indices (TIs) are two-dimensional descriptors which take into account the internal atomic arrangement of compounds, and which encode in numerical form information about molecular size, shape, branching, presence of heteroatoms and multiple bonds. The usefulness of TIs in QSPR and QSAR studies has been extensively demonstrated, and they have also been used as a measure of structural similarity or diversity by their application to databases virtually generated by computer. In this article we will briefly review the history of TIs, their advantages and limitations with respect to other descriptors, and their possibilities in drug design and database selection. These applications rely on new computational techniques such as virtual combinatorial synthesis, virtual computational screening or inverse QSAR.

  16. TOPS-MODE versus DRAGON descriptors to predict permeability coefficients through low-density polyethylene

    NASA Astrophysics Data System (ADS)

    González, Maykel Pérez; Helguera, Aliuska Morales

    2003-10-01

    The TOPological Sub-Structural MOlecular DEsign (TOPS-MODE) approach has been applied to the study of the permeability coefficient of various compounds through low-density polyethylene at 0 °C. A model able to describe more than 92% of the variance in the experimental permeability of 38 organic compounds was developed with the use of the mentioned approach. In contrast, none of eight different approaches, including the use of constitutional, topological, BCUT, 2D autocorrelations, geometrical, RDF, 3D Morse, and GETAWAY descriptors was able to explain more than 75% of the variance in the mentioned property with the same number of descriptors. In addition, the TOPS-MODE approach permitted to find the contribution of different fragments to the permeability coefficients, giving to the model a straightforward structural interpretability.

  17. QSAR without arbitrary descriptors: the electron-conformational method.

    PubMed

    Bersuker, Isaac B

    2008-01-01

    The electron-conformational (EC) method in QSAR problems employs a unique (based on first principles) descriptor of molecular properties that incorporates the electronic structure and topology of the molecule and is presented in a digital-matrix form suitable for computer processing, the EC matrix of congruity (ECMC). Its matrix elements have clear-cut physical meanings of interatomic distances, bond orders, and atomic reactivity (interaction indices). By comparing these matrices for several active compounds of the training set a group of matrix elements is revealed that are common for these compounds within a minimum tolerance, the EC submatrix of activity (ECSA). The latter is the numerical pharmacophore for the level of activity and diversity of the tried compounds. The EC method was described in detail and used for pharmacophore identification and quantitative bioactivity prediction elsewhere. In this paper we give further general considerations of its uniqueness and emphasize its advantages as compared with traditional QSAR methods, outlining the following three novel points: (1) The unique, non-arbitrary descriptor employed in the EC method avoids the shortcomings of the arbitrary chosen descriptors and statistical estimation of their weight in the evaluation of the pharmacophore used in traditional QSAR methods. Arbitrary descriptors may be interdependent ("non-orthogonal") and their sets are necessarily incomplete, hence they may lead to chance correlations and artifacts. The EC pharmacophore is void of these failures, thus deemed to be absolutely reliable within the accuracy of the experimental data and the diversity of the molecules used in its evaluation; (2) The tolerances in the matrix elements of the ECSA play a special role reflecting the flexibilities of the pharmacophore parameters and the dependence of the activity on the latter quantitatively; they are obtained in a minimization procedure; by increasing the tolerances one can get pharmacophores

  18. Periodic table-based descriptors to encode cytotoxicity profile of metal oxide nanoparticles: a mechanistic QSTR approach.

    PubMed

    Kar, Supratik; Gajewicz, Agnieszka; Puzyn, Tomasz; Roy, Kunal; Leszczynski, Jerzy

    2014-09-01

    Nanotechnology has evolved as a frontrunner in the development of modern science. Current studies have established toxicity of some nanoparticles to human and environment. Lack of sufficient data and low adequacy of experimental protocols hinder comprehensive risk assessment of nanoparticles (NPs). In the present work, metal electronegativity (χ), the charge of the metal cation corresponding to a given oxide (χox), atomic number and valence electron number of the metal have been used as simple molecular descriptors to build up quantitative structure-toxicity relationship (QSTR) models for prediction of cytotoxicity of metal oxide NPs to bacteria Escherichia coli. These descriptors can be easily obtained from molecular formula and information acquired from periodic table in no time. It has been shown that a simple molecular descriptor χox can efficiently encode cytotoxicity of metal oxides leading to models with high statistical quality as well as interpretability. Based on this model and previously published experimental results, we have hypothesized the most probable mechanism of the cytotoxicity of metal oxide nanoparticles to E. coli. Moreover, the required information for descriptor calculation is independent of size range of NPs, nullifying a significant problem that various physical properties of NPs change for different size ranges. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Molecular structural characteristics governing biocatalytic oxidation of PAHs with hemoglobin.

    PubMed

    Niu, Junfeng; Yu, Gang

    2004-09-01

    Based on some fundamental quantum chemical descriptors computed by PM3 hamiltonian, two quantitative structure-activity relationship (QSAR) models for biocatalytic oxidation specific activity of unmodified and chemically modified hemoglobin in the oxidation of different polycyclic aromatic hydrocarbons (PAHs) in 15% acetonitrile were developed, respectively, using partial least squares analysis (PLS). The cross-validated Q(cum)(2) values for the two optimal QSAR models are 0.785 and 0.747, respectively, indicating a good predictive ability for biocatalytic oxidation specific activity of PAHs. The main factors affecting specific activity of PAHs are most positive net atomic charges on a hydrogen atom (q(H)(+)), largest negative atomic charge on a carbon atom (q(C)(-)), dipole moment (μ), the energy of the highest occupied molecular orbital (E(HOMO)), and (E(LUMO) - E(HOMO))(2). The biocatalytic oxidation specific activity of PAHs with big q(C)(-) and (E(LUMO) - E(HOMO))(2) values tends to be slow. Increasing q(H)(+), μ, and E(HOMO) values of PAHs leads to increase of specific activity.

  20. The Timbre Toolbox: extracting audio descriptors from musical signals.

    PubMed

    Peeters, Geoffroy; Giordano, Bruno L; Susini, Patrick; Misdariis, Nicolas; McAdams, Stephen

    2011-11-01

    The analysis of musical signals to extract audio descriptors that can potentially characterize their timbre has been disparate and often too focused on a particular small set of sounds. The Timbre Toolbox provides a comprehensive set of descriptors that can be useful in perceptual research, as well as in music information retrieval and machine-learning approaches to content-based retrieval in large sound databases. Sound events are first analyzed in terms of various input representations (short-term Fourier transform, harmonic sinusoidal components, an auditory model based on the equivalent rectangular bandwidth concept, the energy envelope). A large number of audio descriptors are then derived from each of these representations to capture temporal, spectral, spectrotemporal, and energetic properties of the sound events. Some descriptors are global, providing a single value for the whole sound event, whereas others are time-varying. Robust descriptive statistics are used to characterize the time-varying descriptors. To examine the information redundancy across audio descriptors, correlational analysis followed by hierarchical clustering is performed. This analysis suggests ten classes of relatively independent audio descriptors, showing that the Timbre Toolbox is a multidimensional instrument for the measurement of the acoustical structure of complex sound signals.

  1. Structure parameters in molecular tunneling ionization theory

    NASA Astrophysics Data System (ADS)

    Wang, Jun-Ping; Li, Wei; Zhao, Song-Feng

    2014-04-01

    We extracted the accurate structure parameters in molecular tunneling ionization theory (so called MO-ADK theory) for 22 selected linear molecules including some inner orbitals. The molecular wave functions with the correct asymptotic behavior are obtained by solving the time-independent Schrödinger equation with B-spline functions and molecular potentials numerically constructed using the modified Leeuwen-Baerends (LBα) model.

  2. A Quantitative Structure-Property Relationship (QSPR) Study of aliphatic alcohols by the method of dividing the molecular structure into substructure.

    PubMed

    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 P(OW)), 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 (SX(1CH)) 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.

  3. Molecular modeling of nucleic acid structure

    PubMed Central

    Galindo-Murillo, Rodrigo; Bergonzo, Christina

    2013-01-01

    This unit is the first in a series of four units covering the analysis of nucleic acid structure by molecular modeling. This unit provides an overview of computer simulation of nucleic acids. Topics include the static structure model, computational graphics and energy models, generation of an initial model, and characterization of the overall three-dimensional structure. PMID:18428873

  4. The Molecular Structure of Penicillin

    NASA Astrophysics Data System (ADS)

    Bentley, Ronald

    2004-10-01

    The chemical structure of penicillin was determined between 1942 and 1945 under conditions of secrecy established by the U.S. and U.K. governments. The evidence was not published in the open literature but as a monograph. This complex volume does not present a structure proof that can be readily comprehended by a student. In this article, a basic structural proof for the penicillin molecule is provided, emphasizing the chemical work. The stereochemistry of penicillin is also described, and various rearrangements are considered on the basis of the accepted β-lactam structure.

  5. Prediction of chemical carcinogenicity from molecular structure.

    PubMed

    Sun, Hongmao

    2004-01-01

    Carcinogens represent a serious threat to human health. In vivo determination of carcinogenicity is time-consuming and expensive, thus in silico models to predict chemical carcinogenicity are highly desirable for virtual screening of compound libraries of both pharmaceutically and other commercially interesting molecules. In the present study, a PLS-DA (partial least squares discriminant analysis) model was developed to predict carcinogenicities in each of four rodent models: male mouse (MM), female mouse (FM), male rat (MR), and female rat (FR). The data set that was used contained over 520 compounds from both the NTP and the FDA databases. All the models were built from the same molecular descriptor system, which is based on atom typing [Sun, H. J. Chem. Inf. Comput. Sci. 2004, 44, 748-757], enabling the comparison of atomic contributions to carcinogenicity with respect to species and gender. Using four components, the models were able to achieve excellent fitting and prediction, with r(2) = 0.987 and q(2) = 0.944 for MM, r(2) = 0.985 and q(2) = 0.950 for FM, r(2) = 0.989 and q(2) = 0.962 for MR, and r(2) = 0.990 and q(2) = 0.965 for FR. The models were further validated by response permutation testing and external validation, and the results indicated that the models were both statistically significant and predictive. Variable influence on projection (VIP) analysis identified the key atom types and fragments that contributed to carcinogenicities and response differences across species and gender.

  6. The Molecular Structure of Penicillin

    ERIC Educational Resources Information Center

    Bentley, Ronald

    2004-01-01

    Overviews of the observations that constitute a structure proof for penicillin, specifically aimed at the general student population, are presented. Melting points and boiling points were criteria of purity and a crucial tool was microanalysis leading to empirical formulas.

  7. The Molecular Structure of Penicillin

    ERIC Educational Resources Information Center

    Bentley, Ronald

    2004-01-01

    Overviews of the observations that constitute a structure proof for penicillin, specifically aimed at the general student population, are presented. Melting points and boiling points were criteria of purity and a crucial tool was microanalysis leading to empirical formulas.

  8. Comparative performance of descriptors in a multiple linear and Kriging models: a case study on the acute toxicity of organic chemicals to algae.

    PubMed

    Tugcu, Gulcin; Yilmaz, H Birkan; Saçan, Melek Türker

    2014-10-01

    This study presents quantitative structure-toxicity relationship (QSTR) models on the toxicity of 91 organic compounds to Chlorella vulgaris using multiple linear regression (MLR) and Kriging techniques. The molecular descriptors were calculated using SPARTAN and DRAGON programs, and descriptor selection was made by "all subset" method available in the QSARINS software. MLR and Kriging models developed with the same descriptors were compared. In addition to these models, Kriging method was used for descriptor selection, and model development. The selected descriptors showed the importance of hydrophobicity, molecular weight and atomic ionization state in describing the toxicity of a diverse set of chemicals to C. vulgaris. A QSTR model should be associated with appropriate measures of goodness-of-fit, robustness, and predictivity in order to be used for regulatory purpose. Therefore, while the internal performances (goodness-of-fit and robustness) of the models were determined by using a training set, the predictive abilities of the models were determined by using a test set. The results of the study showed that while MLR method is easier to apply, the Kriging method was more successful in predicting toxicity.

  9. Structured Molecular Gas Reveals Galactic Spiral Arms

    NASA Astrophysics Data System (ADS)

    Sawada, Tsuyoshi; Hasegawa, Tetsuo; Koda, Jin

    2012-11-01

    We explore the development of structures in molecular gas in the Milky Way by applying the analysis of the brightness distribution function and the brightness distribution index (BDI) in the archival data from the Boston University-Five College Radio Astronomy Observatory 13CO J = 1-0 Galactic Ring Survey. The BDI measures the fractional contribution of spatially confined bright molecular emission over faint emission extended over large areas. This relative quantity is largely independent of the amount of molecular gas and of any conventional, pre-conceived structures, such as cores, clumps, or giant molecular clouds. The structured molecular gas traced by higher BDI is located continuously along the spiral arms in the Milky Way in the longitude-velocity diagram. This clearly indicates that molecular gas changes its structure as it flows through the spiral arms. Although the high-BDI gas generally coincides with H II regions, there is also some high-BDI gas with no/little signature of ongoing star formation. These results support a possible evolutionary sequence in which unstructured, diffuse gas transforms itself into a structured state on encountering the spiral arms, followed by star formation and an eventual return to the unstructured state after the spiral arm passage.

  10. STRUCTURED MOLECULAR GAS REVEALS GALACTIC SPIRAL ARMS

    SciTech Connect

    Sawada, Tsuyoshi; Hasegawa, Tetsuo; Koda, Jin

    2012-11-01

    We explore the development of structures in molecular gas in the Milky Way by applying the analysis of the brightness distribution function and the brightness distribution index (BDI) in the archival data from the Boston University-Five College Radio Astronomy Observatory {sup 13}CO J = 1-0 Galactic Ring Survey. The BDI measures the fractional contribution of spatially confined bright molecular emission over faint emission extended over large areas. This relative quantity is largely independent of the amount of molecular gas and of any conventional, pre-conceived structures, such as cores, clumps, or giant molecular clouds. The structured molecular gas traced by higher BDI is located continuously along the spiral arms in the Milky Way in the longitude-velocity diagram. This clearly indicates that molecular gas changes its structure as it flows through the spiral arms. Although the high-BDI gas generally coincides with H II regions, there is also some high-BDI gas with no/little signature of ongoing star formation. These results support a possible evolutionary sequence in which unstructured, diffuse gas transforms itself into a structured state on encountering the spiral arms, followed by star formation and an eventual return to the unstructured state after the spiral arm passage.

  11. QSAR of molecular structure and cytotoxic activity of vitamin K2 derivatives with concept of absolute hardness.

    PubMed

    Ishihara, Mariko; Sakagami, Hiroshi

    2007-01-01

    The correlation between the cytotoxicity of seven vitamin K2 (menaquinone) derivatives and thirteen chemical descriptors determined by CONFLEX5/CAChe Worksystem 4.9 (PM3) was investigated. After determination of the conformation of the seven vitamin K2 derivatives and approximation to the molecular form present in vivo (biomimetic) by CONFLEX5, the most stable structure was then determined by CAChe Worksystem 4.9 MOPAC (PM3). The vitamin K2 derivatives with one to three isoprenyl units [1-3] showed an extended form, whereas those with four to seven isoprenyl units [4-7] displayed a spherical form. The human hepatocellular carcinoma HepG2 cells displayed a good correlation between cytotoxicity and all the descriptors except for the electron affinity and lowest unoccupied molecular orbital energy (E(LUMO)). The absolute hardness (eta)--absolute electron negativity (chi) activity diagram determined by this calculation method may be useful for estimating the cytotoxic activity of vitamin K2 derivatives against HepG2 cells. The human squamous cell carcinoma HSC-2 and HSC-3 cells showed similar correlation. The human promyleocytic leukemia HL-60 cells showed the good correlation between cytotoxicity and molecular length. The present study demonstrates for the first time the best correlation between cytotoxic activity and molecular shape or molecular weight of vitamin K2 derivatives, regardless of the type of target cells.

  12. A novel method for protein-ligand binding affinity prediction and the related descriptors exploration.

    PubMed

    Li, Shuyan; Xi, Lili; Wang, Chengqi; Li, Jiazhong; Lei, Beilei; Liu, Huanxiang; Yao, Xiaojun

    2009-04-30

    In this study, a novel method was developed to predict the binding affinity of protein-ligand based on a comprehensive set of structurally diverse protein-ligand complexes (PLCs). The 1300 PLCs with binding affinity (493 complexes with K(d) and 807 complexes with K(i)) from the refined dataset of PDBbind Database (release 2007) were studied in the predictive model development. In this method, each complex was described using calculated descriptors from three blocks: protein sequence, ligand structure, and binding pocket. Thereafter, the PLCs data were rationally split into representative training and test sets by full consideration of the validation of the models. The molecular descriptors relevant to the binding affinity were selected using the ReliefF method combined with least squares support vector machines (LS-SVMs) modeling method based on the training data set. Two final optimized LS-SVMs models were developed using the selected descriptors to predict the binding affinities of K(d) and K(i). The correlation coefficients (R) of training set and test set for K(d) model were 0.890 and 0.833. The corresponding correlation coefficients for the K(i) model were 0.922 and 0.742, respectively. The prediction method proposed in this work can give better generalization ability than other recently published methods and can be used as an alternative fast filter in the virtual screening of large chemical database. (c) 2008 Wiley Periodicals, Inc.

  13. Thermodynamics of organic chemical hydration: QSPR models using physicochemical HYBOT descriptors.

    PubMed

    Raevsky, O A; Liplavskiy, Y V; Raevskaya, O E; Mannhold, R

    2009-07-01

    Stable and predictive quantitative structure-property relationship (QSPR) models of thermodynamics of chemical hydration (changes in Gibbs energy, DeltaG(air/water), enthalpy, DeltaH(air/water) and entropy DeltaS(air/water)) were obtained on the basis of physicochemical descriptors calculated by the HYBOT program. The structurally diverse training set (n = 151) and test set (n = 37) included 13 mono-functional chemical classes. The applied HYBOT descriptors comprise molecular polarizability alpha (as a volume-related term), the sum of partial negative charges on all atoms in a molecule SigmaQ(-) (as an electrostatic term) and the sum of H-bond acceptor and donor factors SigmaC(a) and SigmaC(d) (as H-bond terms). Final equations for changes in Gibbs energy and enthalpy provided good statistical criteria and standard deviations on the level of errors of experimental determinations. All four above-mentioned terms essentially contribute to hydration enthalpy and each of them increases negative values of enthalpy. Hydration Gibbs energy predominantly depends on hydrogen bonding between solute and water molecules. Steric and electrostatic terms act in opposite directions and partly compensate each other. Changes in entropy correlate with increasing H-bond acceptor ability, whereas the other three descriptors exhibit inverse correlations.

  14. Molecular structure, reactivity, and toxicity of the complete series of chlorinated benzenes.

    PubMed

    Padmanabhan, J; Parthasarathi, R; Subramanian, V; Chattaraj, P K

    2005-12-08

    The structure and chemical reactivity profiles of all 12 chlorobenzenes have been investigated using the density functional theory and ab initio molecular orbital calculations. Global and local reactivity descriptors such as electrophilicity index and local philicity, respectively, of the selected systems have been calculated in order to gain insights into the reactive nature and the reactive sites of these compounds. Also, the effects of chlorine substitution on the aromaticity of the compounds have been analyzed by calculating the nucleus-independent chemical shift. Interaction through charge transfer between chlorobenzenes and nucleic acid bases/selected base pairs are determined using Parr's formula. The results revealed that the chlorobenzenes act as electron acceptors in their interaction with biomolecules. Structure-toxicity analysis of this entire set of chlorobenzenes demonstrates the importance of the electrophilicity index in the prediction of reactivity/toxicity.

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

    PubMed

    Toropova, Alla P; Toropov, Andrey A

    2017-06-05

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

  16. Structures in Molecular Clouds: Modeling

    SciTech Connect

    Kane, J O; Mizuta, A; Pound, M W; Remington, B A; Ryutov, D D

    2006-04-20

    We attempt to predict the observed morphology, column density and velocity gradient of Pillar II of the Eagle Nebula, using Rayleigh Taylor (RT) models in which growth is seeded by an initial perturbation in density or in shape of the illuminated surface, and cometary models in which structure is arises from a initially spherical cloud with a dense core. Attempting to mitigate suppression of RT growth by recombination, we use a large cylindrical model volume containing the illuminating source and the self-consistently evolving ablated outflow and the photon flux field, and use initial clouds with finite lateral extent. An RT model shows no growth, while a cometary model appears to be more successful at reproducing observations.

  17. A Generally Applicable Computer Algorithm Based on the Group Additivity Method for the Calculation of Seven Molecular Descriptors: Heat of Combustion, LogPO/W, LogS, Refractivity, Polarizability, Toxicity and LogBB of Organic Compounds; Scope and Limits of Applicability.

    PubMed

    Naef, Rudolf

    2015-10-07

    A generally applicable computer algorithm for the calculation of the seven molecular descriptors heat of combustion, logPoctanol/water, logS (water solubility), molar refractivity, molecular polarizability, aqueous toxicity (protozoan growth inhibition) and logBB (log (cblood/cbrain)) is presented. The method, an extendable form of the group-additivity method, is based on the complete break-down of the molecules into their constituting atoms and their immediate neighbourhood. The contribution of the resulting atom groups to the descriptor values is calculated using the Gauss-Seidel fitting method, based on experimental data gathered from literature. The plausibility of the method was tested for each descriptor by means of a k-fold cross-validation procedure demonstrating good to excellent predictive power for the former six descriptors and low reliability of logBB predictions. The goodness of fit (Q²) and the standard deviation of the 10-fold cross-validation calculation was >0.9999 and 25.2 kJ/mol, respectively, (based on N = 1965 test compounds) for the heat of combustion, 0.9451 and 0.51 (N = 2640) for logP, 0.8838 and 0.74 (N = 1419) for logS, 0.9987 and 0.74 (N = 4045) for the molar refractivity, 0.9897 and 0.77 (N = 308) for the molecular polarizability, 0.8404 and 0.42 (N = 810) for the toxicity and 0.4709 and 0.53 (N = 383) for logBB. The latter descriptor revealing a very low Q² for the test molecules (R² was 0.7068 and standard deviation 0.38 for N = 413 training molecules) is included as an example to show the limits of the group-additivity method. An eighth molecular descriptor, the heat of formation, was indirectly calculated from the heat of combustion data and correlated with published experimental heat of formation data with a correlation coefficient R² of 0.9974 (N = 2031).

  18. Molecular descriptors calculation as a tool in the analysis of the antileishmanial activity achieved by two series of diselenide derivatives. An insight into its potential action mechanism.

    PubMed

    Font, María; Baquedano, Ylenia; Plano, Daniel; Moreno, Esther; Espuelas, Socorro; Sanmartín, Carmen; Palop, Juan Antonio

    2015-07-01

    A molecular modeling study has been carried out on two previously reported series of symmetric diselenide derivatives that show remarkable antileishmanial in vitro activity against Leishmania infantum intracellular amastigotes and in infected macrophages (THP-1 cells), in addition to showing favorable selectivity indices. Series 1 consists of compounds that can be considered as central scaffold constructed with a diaryl/dialkylaryl diselenide central nucleus, decorated with different substituents located on the aryl rings. Series 2 consists of compounds constructed over a diaryl diselenide central nucleus, decorated in 4 and 4' positions with an aryl or heteroaryl sulfonamide fragment, thus forming the diselenosulfonamide derivatives. With regard to the diselenosulfonamide derivatives (2 series), the activity can be related, as a first approximation, with (a) the ability to release bis(4-aminophenyl) diselenide, the common fragment which can be ultimately responsible for the activity of the compounds. (b) the anti-parasitic activity achieved by the sulfonamide pharmacophore present in the analyzed derivatives. The data that support this connection include the topography of the molecules, the conformational behavior of the compounds, which influences the bond order, as well as the accessibility of the hydrolysis point, and possibly the hydrophobicity and polarizability of the compounds. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. The Molecular Structure of Monofluorobenzaldehydes

    NASA Astrophysics Data System (ADS)

    Lozada, Issiah Byen; Sun, Wenhao; van Wijngaarden, Jennifer

    2017-06-01

    The pure rotational spectra of 2- and 3-fluorobenzaldehyde have been investigated using a chirped pulse Fourier transform microwave (FTMW) spectrometer in the range of 8-18 GHz and a Balle-Flygare FTMW spectrometer in the range of 4-26 GHz. As in a previous study of monofluorobenzaldehydes, only transitions due to a single planar conformer were observed for 2-fluorobenzaldehyde (O-trans) whereas two planar conformers (O-trans and O-cis) of 3-fluorobenzaldehydes were confirmed. Transitions due to the seven unique ^{13}C isotopologues of each of the three molecules have been observed for the first time. Their rotational constants were used to derive the effective ground state (r_{0}) and substitution (r_{s}) structures. The results compare favourably with the equilibrium (r_{e}) geometries which were determined following geometry optimization at the MP2/aug-cc-pVTZ level of theory. José L. Alonso and Rosa M. Villamañán, J. Chem. Soc., Faraday Trans. 2, 1989, 85(2), 137-149

  20. On the emergence of molecular structure

    SciTech Connect

    Matyus, Edit; Reiher, Markus; Hutter, Juerg; Mueller-Herold, Ulrich

    2011-05-15

    The structure of (a{sup {+-}},a{sup {+-}},b{sup {+-}})-type Coulombic systems is characterized by the effective ground-state density of the a-type particles, computed via nonrelativistic quantum mechanics without introduction of the Born-Oppenheimer approximation. A structural transition is observed when varying the relative mass of the a- and b-type particles, e.g., between atomic H{sup -} and molecular H{sub 2}{sup +}. The particle-density profile indicates a molecular-type behavior for the positronium ion, Ps{sup -}.

  1. Hierarchical QSAR technology based on the Simplex representation of molecular structure

    NASA Astrophysics Data System (ADS)

    Kuz'min, V. E.; Artemenko, A. G.; Muratov, E. N.

    2008-06-01

    This article is about the hierarchical quantitative structure-activity relationship technology (HiT QSAR) based on the Simplex representation of molecular structure (SiRMS) and its application for different QSAR/QSP(property)R tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) to the QSAR problem by the series of enhanced models of molecular structure description [from one dimensional (1D) to four dimensional (4D)]. It is a system of permanently improved solutions. In the SiRMS approach, every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality and symmetry). The level of simplex descriptors detailing increases consecutively from the 1D to 4D representation of the molecular structure. The advantages of the approach reported here are the absence of "molecular alignment" problems, consideration of different physical-chemical properties of atoms (e.g. charge, lipophilicity, etc.), the high adequacy and good interpretability of obtained models and clear ways for molecular design. The efficiency of the HiT QSAR approach is demonstrated by comparing it with the most popular modern QSAR approaches on two representative examination sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D-4D) of the molecular structure description are also highlighted. The reliability of developed QSAR models as predictive virtual screening tools and their ability to serve as the base of directed drug design was validated by subsequent synthetic and biological experiments, among others. The HiT QSAR is realized as a complex of computer programs known as HiT QSAR software that also includes a powerful statistical block and a number of useful utilities.

  2. Lagrangian descriptors of driven chemical reaction manifolds

    NASA Astrophysics Data System (ADS)

    Craven, Galen T.; Junginger, Andrej; Hernandez, Rigoberto

    2017-08-01

    The persistence of a transition state structure in systems driven by time-dependent environments allows the application of modern reaction rate theories to solution-phase and nonequilibrium chemical reactions. However, identifying this structure is problematic in driven systems and has been limited by theories built on series expansion about a saddle point. Recently, it has been shown that to obtain formally exact rates for reactions in thermal environments, a transition state trajectory must be constructed. Here, using optimized Lagrangian descriptors [G. T. Craven and R. Hernandez, Phys. Rev. Lett. 115, 148301 (2015), 10.1103/PhysRevLett.115.148301], we obtain this so-called distinguished trajectory and the associated moving reaction manifolds on model energy surfaces subject to various driving and dissipative conditions. In particular, we demonstrate that this is exact for harmonic barriers in one dimension and this verification gives impetus to the application of Lagrangian descriptor-based methods in diverse classes of chemical reactions. The development of these objects is paramount in the theory of reaction dynamics as the transition state structure and its underlying network of manifolds directly dictate reactivity and selectivity.

  3. Lagrangian descriptors of driven chemical reaction manifolds.

    PubMed

    Craven, Galen T; Junginger, Andrej; Hernandez, Rigoberto

    2017-08-01

    The persistence of a transition state structure in systems driven by time-dependent environments allows the application of modern reaction rate theories to solution-phase and nonequilibrium chemical reactions. However, identifying this structure is problematic in driven systems and has been limited by theories built on series expansion about a saddle point. Recently, it has been shown that to obtain formally exact rates for reactions in thermal environments, a transition state trajectory must be constructed. Here, using optimized Lagrangian descriptors [G. T. Craven and R. Hernandez, Phys. Rev. Lett. 115, 148301 (2015)PRLTAO0031-900710.1103/PhysRevLett.115.148301], we obtain this so-called distinguished trajectory and the associated moving reaction manifolds on model energy surfaces subject to various driving and dissipative conditions. In particular, we demonstrate that this is exact for harmonic barriers in one dimension and this verification gives impetus to the application of Lagrangian descriptor-based methods in diverse classes of chemical reactions. The development of these objects is paramount in the theory of reaction dynamics as the transition state structure and its underlying network of manifolds directly dictate reactivity and selectivity.

  4. Molecular docking to ensembles of protein structures.

    PubMed

    Knegtel, R M; Kuntz, I D; Oshiro, C M

    1997-02-21

    Until recently, applications of molecular docking assumed that the macromolecular receptor exists in a single, rigid conformation. However, structural studies involving different ligands bound to the same target biomolecule frequently reveal modest but significant conformational changes in the target. In this paper, two related methods for molecular docking are described that utilize information on conformational variability from ensembles of experimental receptor structures. One method combines the information into an "energy-weighted average" of the interaction energy between a ligand and each receptor structure. The other method performs the averaging on a structural level, producing a "geometry-weighted average" of the inter-molecular force field score used in DOCK 3.5. Both methods have been applied in docking small molecules to ensembles of crystal and solution structures, and we show that experimentally determined binding orientations and computed energies of known ligands can be reproduced accurately. The use of composite grids, when conformationally different protein structures are available, yields an improvement in computational speed for database searches in proportion to the number of structures.

  5. Learning surface molecular structures via machine vision

    NASA Astrophysics Data System (ADS)

    Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

    2017-08-01

    Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (`read out') all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds and thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. The method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.

  6. Learning surface molecular structures via machine vision

    DOE PAGES

    Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

    2017-08-10

    Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (‘read out’) all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds andmore » thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. Here, the method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.« less

  7. Molecular Association and Structure of Hydrogen Peroxide.

    ERIC Educational Resources Information Center

    Giguere, Paul A.

    1983-01-01

    The statement is sometimes made in textbooks that liquid hydrogen peroxide is more strongly associated than water, evidenced by its higher boiling point and greater heat of vaporization. Discusses these and an additional factor (the nearly double molecular mass of the peroxide), focusing on hydrogen bonds and structure of the molecule. (JN)

  8. Students' Understanding of Molecular Structure Representations

    ERIC Educational Resources Information Center

    Ferk, Vesna; Vrtacnik, Margareta; Blejec, Andrej; Gril, Alenka

    2003-01-01

    The purpose of the investigation was to determine the meanings attached by students to the different kinds of molecular structure representations used in chemistry teaching. The students (n = 124) were from primary (aged 13-14 years) and secondary (aged 17-18 years) schools and a university (aged 21-25 years). A computerised "Chemical…

  9. Molecular Association and Structure of Hydrogen Peroxide.

    ERIC Educational Resources Information Center

    Giguere, Paul A.

    1983-01-01

    The statement is sometimes made in textbooks that liquid hydrogen peroxide is more strongly associated than water, evidenced by its higher boiling point and greater heat of vaporization. Discusses these and an additional factor (the nearly double molecular mass of the peroxide), focusing on hydrogen bonds and structure of the molecule. (JN)

  10. Students' Understanding of Molecular Structure Representations

    ERIC Educational Resources Information Center

    Ferk, Vesna; Vrtacnik, Margareta; Blejec, Andrej; Gril, Alenka

    2003-01-01

    The purpose of the investigation was to determine the meanings attached by students to the different kinds of molecular structure representations used in chemistry teaching. The students (n = 124) were from primary (aged 13-14 years) and secondary (aged 17-18 years) schools and a university (aged 21-25 years). A computerised "Chemical…

  11. How We Teach Molecular Structure to Freshmen.

    ERIC Educational Resources Information Center

    Hurst, Michael O.

    2002-01-01

    Currently molecular structure is taught in general chemistry using three theories, this being based more on historical development rather than logical pedagogy. Electronegativity is taught with a confusing mixture of definitions that do not correspond to modern practice. Valence bond theory and VSEPR are used together in a way that often confuses…

  12. A 2D-QSAR and Grid-Independent Molecular Descriptor (GRIND) Analysis of Quinoline-Type Inhibitors of Akt2: Exploration of the Binding Mode in the Pleckstrin Homology (PH) Domain

    PubMed Central

    Akhtar, Noreen; Jabeen, Ishrat

    2016-01-01

    Protein kinase B-β (PKBβ/Akt2) is a serine/threonine-specific protein kinase that has emerged as one of the most important regulators of cell growth, differentiation, and division. Upregulation of Akt2 in various human carcinomas, including ovarian, breast, and pancreatic, is a well-known tumorigenesis phenomenon. Early on, the concept of the simultaneous administration of anticancer drugs with inhibitors of Akt2 was advocated to overcome cell proliferation in the chemotherapeutic treatment of cancer. However, clinical studies have not lived up to the high expectations, and several phase II and phase III clinical studies have been terminated prematurely because of severe side effects related to the non-selective isomeric inhibition of Akt2. The notion that the sequence identity of pleckstrin homology (PH) domains within Akt-isoforms is less than 30% might indicate the possibility of the development of selective antagonists against the Akt2 PH domain. Therefore, in this study, various in silico tools were utilized to explore the hypothesis that quinoline-type inhibitors bind in the Akt2 PH domain. A Grid-Independent Molecular Descriptor (GRIND) analysis indicated that two hydrogen bond acceptors, two hydrogen bond donors and one hydrophobic feature at a certain distance from each other were important for the selective inhibition of Akt2. Our docking results delineated the importance of Lys30 as an anchor point for mapping the distances of important amino acid residues in the binding pocket, including Lys14, Glu17, Arg25, Asn53, Asn54 and Arg86. The binding regions identified complement the GRIND-based pharmacophoric features. PMID:28036396

  13. Evaluation of descriptors and classification schemes to predict cytochrome substrates in terms of chemical information

    NASA Astrophysics Data System (ADS)

    Block, John H.; Henry, Douglas R.

    2008-06-01

    Using a small database of defined substrates in humans for cytochrome P450 mixed function oxidases, a series of descriptors and classification methods were evaluated with respect to how well they correctly classified substrates. The descriptors ranged from structural keys to topological to electronic. A variety of classification schemes were examined in terms of their ability to point out which descriptors are important for predicting the cytochrome P450 specificity for a substrate. Results illustrate the relative effectiveness of the various kinds of descriptors and classification methods, as well as the value of using as well-defined data set as possible.

  14. A superior descriptor of random textures and its predictive capacity

    PubMed Central

    Jiao, Y.; Stillinger, F. H.; Torquato, S.

    2009-01-01

    Two-phase random textures abound in a host of contexts, including porous and composite media, ecological structures, biological media, and astrophysical structures. Questions surrounding the spatial structure of such textures continue to pose many theoretical challenges. For example, can two-point correlation functions be identified that can be manageably measured and yet reflect nontrivial higher-order structural information about the textures? We present a solution to this question by probing the information content of the widest class of different types of two-point functions examined to date using inverse “reconstruction” techniques. This enables us to show that a superior descriptor is the two-point cluster function C2(r), which is sensitive to topological connectedness information. We demonstrate the utility of C2(r) by accurately reconstructing textures drawn from materials science, cosmology, and granular media, among other examples. Our work suggests a theoretical pathway to predict the bulk physical properties of random textures and that also has important ramifications for atomic and molecular systems. PMID:19805040

  15. Molecular clouds and galactic spiral structure

    NASA Technical Reports Server (NTRS)

    Cohen, R. S.; Cong, H.; Dame, T. M.; Thaddeus, P.

    1980-01-01

    Two large-scale 2.6 mm CO surveys of the galactic plane, one in the first quadrant (l = 12 to 60 deg, b = -1 to +1 deg), the other in the second (l = 105 to 139 deg, b = -3 to +3 deg), have provided evidence that, contrary to previous findings, molecular clouds constitute a highly specific tracer of spiral structure. Molecular counterparts of five of the classical 21-cm spiral arms have been identified: the Perseus arm, the local arm (including Lindblad's local expanding ring), the Sagittarius arm, the Scutum arm, and the 4-kpc arm. The region between the local arm and the Perseus arm is apparently devoid of molecular clouds, and the interarm regions of the inner Galaxy appear largely so. CO spiral structure implies that the mean lifetime of molecular clouds cannot be greater than 100 million years, the time required for interstellar matter to cross a spiral arm. Conservation of mass then sets a limit on the fraction of the interstellar medium in the form of molecular clouds: it cannot exceed one-half at any distance from the galactic center in the range 4-12 kpc.

  16. How We Teach Molecular Structure to Freshmen

    NASA Astrophysics Data System (ADS)

    Hurst, Michael O.

    2002-06-01

    Currently molecular structure is taught in general chemistry using three theories, this being based more on historical development rather than logical pedagogy. Electronegativity is taught with a confusing mixture of definitions that do not correspond to modern practice. Explaining bond type with electronegativity is also done poorly. Teaching of valence bond theory and molecular orbital theory should be left to upper-level classes where it will be used. Currently, valence bond theory and VSEPR are used together in a way that often confuses the students about the difference between the different theories.

  17. Structural effects in molecular metal halides.

    PubMed

    Hargittai, Magdolna

    2009-03-17

    Metal halides are a relatively large class of inorganic compounds that participate in many industrial processes, from halogen metallurgy to the production of semiconductors. Because most metal halides are ionic crystals at ambient conditions, the term "molecular metal halides" usually refers to vapor-phase species. These gas-phase molecules have a special place in basic research because they exhibit the widest range of chemical bonding from the purely ionic to mostly covalent bonding through to weakly interacting systems. Although our focus is basic research, knowledge of the structural and thermodynamic properties of gas-phase metal halides is also important in industrial processes. In this Account, we review our most recent work on metal halide molecular structures. Our studies are based on electron diffraction and vibrational spectroscopy, and increasingly, we have augmented our experimental work with quantum chemical computations. Using both experimental and computational techniques has enabled us to determine intriguing structural effects with better accuracy than using either technique alone. We loosely group our discussion based on structural effects including "floppiness", relativistic effects, vibronic interactions, and finally, undiscovered molecules with computational thermodynamic stability. Floppiness, or serious "nonrigidity", is a typical characteristic of metal halides and makes their study challenging for both experimentalists and theoreticians. Relativistic effects are mostly responsible for the unique structure of gold and mercury halides. These molecules have shorter-than-expected bonds and often have unusual geometrical configurations. The gold monohalide and mercury dihalide dimers and the molecular-type crystal structure of HgCl(2) are examples. We also examined spin-orbit coupling and the possible effect of the 4f electrons on the structure of lanthanide trihalides. Unexpectedly, we found that the geometry of their dimers depends on the f

  18. Gun bore flaw image matching based on improved SIFT descriptor

    NASA Astrophysics Data System (ADS)

    Zeng, Luan; Xiong, Wei; Zhai, You

    2013-01-01

    In order to increase the operation speed and matching ability of SIFT algorithm, the SIFT descriptor and matching strategy are improved. First, a method of constructing feature descriptor based on sector area is proposed. By computing the gradients histogram of location bins which are parted into 6 sector areas, a descriptor with 48 dimensions is constituted. It can reduce the dimension of feature vector and decrease the complexity of structuring descriptor. Second, it introduce a strategy that partitions the circular region into 6 identical sector areas starting from the dominate orientation. Consequently, the computational complexity is reduced due to cancellation of rotation operation for the area. The experimental results indicate that comparing with the OpenCV SIFT arithmetic, the average matching speed of the new method increase by about 55.86%. The matching veracity can be increased even under some variation of view point, illumination, rotation, scale and out of focus. The new method got satisfied results in gun bore flaw image matching. Keywords: Metrology, Flaw image matching, Gun bore, Feature descriptor

  19. Symmetric curvature descriptors for label-free analysis of DNA

    PubMed Central

    Buzio, Renato; Repetto, Luca; Giacopelli, Francesca; Ravazzolo, Roberto; Valbusa, Ugo

    2014-01-01

    High-resolution microscopy techniques such as electron microscopy, scanning tunnelling microscopy and atomic force microscopy represent well-established, powerful tools for the structural characterization of adsorbed DNA molecules at the nanoscale. Notably, the analysis of DNA contours allows mapping intrinsic curvature and flexibility along the molecular backbone. This is particularly suited to address the impact of the base-pairs sequence on the local conformation of the strands and plays a pivotal role for investigations relating the inherent DNA shape and flexibility to other functional properties. Here, we introduce novel chain descriptors aimed to characterize the local intrinsic curvature and flexibility of adsorbed DNA molecules with unknown orientation. They consist of stochastic functions that couple the curvatures of two nanosized segments, symmetrically placed on the DNA contour. We show that the fine mapping of the ensemble-averaged functions along the molecular backbone generates characteristic patterns of variation that highlight all pairs of tracts with large intrinsic curvature or enhanced flexibility. We demonstrate the practical applicability of the method for DNA chains imaged by atomic force microscopy. Our approach paves the way for the label-free comparative analysis of duplexes, aimed to detect nanoscale conformational changes of physical or biological relevance in large sample numbers. PMID:25248631

  20. A Theoretical Framework for Lagrangian Descriptors

    NASA Astrophysics Data System (ADS)

    Lopesino, C.; Balibrea-Iniesta, F.; García-Garrido, V. J.; Wiggins, S.; Mancho, A. M.

    This paper provides a theoretical background for Lagrangian Descriptors (LDs). The goal of achieving rigorous proofs that justify the ability of LDs to detect invariant manifolds is simplified by introducing an alternative definition for LDs. The definition is stated for n-dimensional systems with general time dependence, however we rigorously prove that this method reveals the stable and unstable manifolds of hyperbolic points in four particular 2D cases: a hyperbolic saddle point for linear autonomous systems, a hyperbolic saddle point for nonlinear autonomous systems, a hyperbolic saddle point for linear nonautonomous systems and a hyperbolic saddle point for nonlinear nonautonomous systems. We also discuss further rigorous results which show the ability of LDs to highlight additional invariants sets, such as n-tori. These results are just a simple extension of the ergodic partition theory which we illustrate by applying this methodology to well-known examples, such as the planar field of the harmonic oscillator and the 3D ABC flow. Finally, we provide a thorough discussion on the requirement of the objectivity (frame-invariance) property for tools designed to reveal phase space structures and their implications for Lagrangian descriptors.

  1. 2004 Reversible Associations in Structure & Molecular Biology

    SciTech Connect

    Edward Eisenstein Nancy Ryan Gray

    2005-03-23

    The Gordon Research Conference (GRC) on 2004 Gordon Research Conference on Reversible Associations in Structure & Molecular Biology was held at Four Points Sheraton, CA, 1/25-30/2004. The Conference was well attended with 82 participants (attendees list attached). The attendees represented the spectrum of endeavor in this field coming from academia, industry, and government laboratories, both U.S. and foreign scientists, senior researchers, young investigators, and students.

  2. 8B structure in Fermionic Molecular Dynamics

    NASA Astrophysics Data System (ADS)

    Henninger, K. R.; Neff, T.; Feldmeier, H.

    2015-04-01

    The structure of the light exotic nucleus 8B is investigated in the Fermionic Molecular Dynamics (FMD) model. The decay of 8B is responsible for almost the entire high- energy solar-neutrino flux, making structure calculations of 8B important for determining the solar core temperature. 8B is a proton halo candidate thought to exhibit clustering. FMD uses a wave-packet basis and is well-suited for modelling clustering and halos. For a multiconfiguration treatment we construct the many-body Hilbert space from antisymmetrised angular-momentum projected 8-particle states. First results show formation of a proton halo.

  3. QSPR modeling for enthalpies of formation of organometallic compounds by means of SMILES-based optimal descriptors

    NASA Astrophysics Data System (ADS)

    Toropov, A. A.; Toropova, A. P.; Benfenati, E.

    2008-08-01

    A quantitative structure-property relationship (QSPR) model for a predicting gas-phase enthalpy of formation have been developed, using as chemical information descriptors based on the simplified molecular input line entry system (SMILES). The model is one-variable equation. The SMILES-based descriptors calculated with correlation weights of SMILES attributes which are obtained by the Monte Carlo method. The model addressed organometallic compounds. Statistical characteristics of the model are the following: n = 104, R2 = 0.9943, Q2 = 0.9940, s = 19.9 (kJ/mol), F = 17701 (training set); n = 28, R2 = 0.9908, Q2 = 0.9892, s = 29.4 (kJ/mol), F = 2788 (test set).

  4. OSRI: a rotationally invariant binary descriptor.

    PubMed

    Xu, Xianwei; Tian, Lu; Feng, Jianjiang; Zhou, Jie

    2014-07-01

    Binary descriptors are becoming widely used in computer vision field because of their high matching efficiency and low memory requirements. Since conventional approaches, which first compute a floating-point descriptor then binarize it, are computationally expensive, some recent efforts have focused on directly computing binary descriptors from local image patches. Although these binary descriptors enable a significant speedup in processing time, their performances usually drop a lot due to orientation estimation errors and limited description abilities. To address these issues, we propose a novel binary descriptor based on the ordinal and spatial information of regional invariants (OSRIs) over a rotation invariant sampling pattern. Our main contributions are twofold: 1) each bit in OSRI is computed based on difference tests of regional invariants over pairwise sampling-regions instead of difference tests of pixel intensities commonly used in existing binary descriptors, which can significantly enhance the discriminative ability and 2) rotation and illumination changes are handled well by ordering pixels according to their intensities and gradient orientations, meanwhile, which is also more reliable than those methods that resort to a reference orientation for rotation invariance. Besides, a statistical analysis of discriminative abilities of different parts in the descriptor is conducted to design a cascade filter which can reject nonmatching descriptors at early stages by comparing just a small portion of the whole descriptor, further reducing the matching time. Extensive experiments on four challenging data sets (Oxford, 53 Objects, ZuBuD, and Kentucky) show that OSRI significantly outperforms two state-of-the-art binary descriptors (FREAK and ORB). The matching performance of OSRI with only 512 bits is also better than the well-known floating-point descriptor SIFT (4K bits) and is comparable with the state-of-the-art floating-point descriptor MROGH (6K bits

  5. Evaluation of the EVA descriptor for QSAR studies: 3. The use of a genetic algorithm to search for models with enhanced predictive properties (EVA_GA)

    NASA Astrophysics Data System (ADS)

    Turner, David B.; Willett, Peter

    2000-01-01

    The EVA structural descriptor, based upon calculated fundamental molecular vibrational frequencies, has proved to be an effective descriptor for both QSAR and database similarity calculations. The descriptor is sensitive to 3D structure but has an advantage over field-based 3D-QSAR methods inasmuch as structural superposition is not required. The original technique involves a standardisation method wherein uniform Gaussians of fixed standard deviation (σ) are used to smear out frequencies projected onto a linear scale. The smearing function permits the overlap of proximal frequencies and thence the extraction of a fixed dimensional descriptor regardless of the number and precise values of the frequencies. It is proposed here that there exist optimal localised values of σ in different spectral regions; that is, the overlap of frequencies using uniform Gaussians may, at certain points in the spectrum, either be insufficient to pick up relationships where they exist or mix up information to such an extent that significant correlations are obscured by noise. A genetic algorithm is used to search for optimal localised σ values using crossvalidated PLS regression scores as the fitness score to be optimised. The resultant models were then validated against a previously unseen test set of compounds and through data scrambling. The performance of EVA_GA is compared to that of EVA and analogous CoMFA studies; in the latter case a brief evaluation is made of the effect of grid resolution upon the stability of CoMFA PLS scores particularly in relation to test set predictions.

  6. Statistically validated QSARs, based on theoretical descriptors, for modeling aquatic toxicity of organic chemicals in Pimephales promelas (fathead minnow).

    PubMed

    Papa, Ester; Villa, Fulvio; Gramatica, Paola

    2005-01-01

    The use of Quantitative Structure-Activity Relationships in assessing the potential negative effects of chemicals plays an important role in ecotoxicology. (LC50)(96h) in Pimephales promelas (Duluth database) is widely modeled as an aquatic toxicity end-point. The object of this study was to compare different molecular descriptors in the development of new statistically validated QSAR models to predict the aquatic toxicity of chemicals classified according to their MOA and in a unique general model. The applied multiple linear regression approach (ordinary least squares) is based on theoretical molecular descriptor variety (1D, 2D, and 3D, from DRAGON package, and some calculated logP). The best combination of modeling descriptors was selected by the Genetic Algorithm-Variable Subset Selection procedure. The robustness and the predictive performance of the proposed models was verified using both internal (cross-validation by LOO, bootstrap, Y-scrambling) and external statistical validations (by splitting the original data set into training and validation sets by Kohonen-artificial neural networks (K-ANN)). The model applicability domain (AD) was checked by the leverage approach to verify prediction reliability.

  7. Molecular Structure of a Functional Drosophila Centromere

    PubMed Central

    Sun, Xiaoping; Wahlstrom, Janice

    2011-01-01

    Summary Centromeres play a critical role in chromosome inheritance but are among the most difficult genomic components to analyze in multicellular eukaryotes. Here, we present a highly detailed molecular structure of a functional centromere in a multicellular organism. The centromere of the Drosophila minichromosome Dp1187 is contained within a 420 kb region of centric heterochromatin. We have used a new approach to characterize the detailed structure of this centromere and found that it is primarily composed of satellites and single, complete transposable elements. In the rest of the Drosophila genome, these satellites and transposable elements are neither unique to the centromeres nor present at all centromeres. We discuss the impact of these results on our understanding of heterochromatin structure and on the determinants of centromere identity and function. PMID:9428523

  8. Molecular Dynamics Modeling of Hydrated Calcium-Silicate-Hydrate (CSH) Cement Molecular Structure

    DTIC Science & Technology

    2014-08-30

    properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown...public release; distribution is unlimited. Molecular Dynamics Modeling of Hydrated Calcium-Silicate- Hydrate (CSH) Cement Molecular Structure The views... Cement Molecular Structure Report Title Multi-scale modeling of complex material systems requires starting from fundamental building blocks to

  9. Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study

    PubMed Central

    Satpathy, Raghunath; Guru, R. K.; Behera, R.; Nayak, B.

    2015-01-01

    Context: Boswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here. Aims: To predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. Materials and Methods: In this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. Statistical Analysis Used: Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network. Results: From the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. Conclusions: Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound. PMID:25709332

  10. Unveiling descriptors for predicting the bulk modulus of amorphous carbon

    NASA Astrophysics Data System (ADS)

    Takahashi, Keisuke; Tanaka, Yuzuru

    2017-02-01

    Descriptors for the bulk modulus of amorphous carbon are investigated through the implementation of data mining where data sets are prepared using first-principles calculations. Data mining reveals that the number of bonds in each C atom and the density of amorphous carbon are found to be descriptors representing the bulk modulus. Support vector regression (SVR) within machine learning is implemented and descriptors are trained where trained SVR is able to predict the bulk modulus of amorphous carbon. An inverse problem, starting from the bulk modulus towards structural information of amorphous carbon, is performed and structural information of amorphous carbon is successfully predicted from the desired bulk modulus. Thus, treating several physics factors in multidimensional space allows for the prediction of physical phenomena. In addition, the reported approach proposes that "big data" can be generated from a small data set using machine learning if descriptors are well defined. This would greatly change how amorphous carbon would be treated and help accelerate further development of amorphous carbon materials.

  11. Molecular structure and QSAR study on antispasmodic activity of some xanthoxyline derivatives.

    PubMed

    dos Santos, Rodrigo; Kuhnen, Carlos Alberto; Yunes, Rosendo Augusto

    2006-05-01

    Semi-empirical molecular orbital calculations at AM1 level were done with the aim to investigate the structure-activity relationships of antispasmodic activities of ten 2-(X-benzyloxy)-4,6-dimethoxyacetophenones with X = H, 4'-F, 4'-NO2, 4'-CH3, 4'-Cl, 3',4'-(CH3)2, 4'-OCH3, 4'-Br, 4'-OCH2C6H5, and 4'-C(CH3)3, against acetylcholine-induced contraction of the guinea pig ileum. The most significant quantum chemical descriptors for this series of compounds were the net atomic charges, nucleophilic and electrophilic frontier electron density, HOMO and LUMO orbitals, and reactivity indices. While no significant correlations were found employing molecular parameters such as heat of formation, dipole moment, molecular polarizability, and so on, good correlations were obtained using the reactivity indices of HOMO and LUMO orbitals at specific atoms of the molecules. These results indicate that the spatial distribution of HOMO and LUMO orbitals over these specific atoms play an important role for an increase of biological activity.

  12. Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review

    PubMed Central

    Mamy, Laure; Patureau, Dominique; Barriuso, Enrique; Bedos, Carole; Bessac, Fabienne; Louchart, Xavier; Martin-laurent, Fabrice; Miege, Cecile; Benoit, Pierre

    2015-01-01

    A comprehensive review of quantitative structure-activity relationships (QSAR) allowing the prediction of the fate of organic compounds in the environment from their molecular properties was done. The considered processes were water dissolution, dissociation, volatilization, retention on soils and sediments (mainly adsorption and desorption), degradation (biotic and abiotic), and absorption by plants. A total of 790 equations involving 686 structural molecular descriptors are reported to estimate 90 environmental parameters related to these processes. A significant number of equations was found for dissociation process (pKa), water dissolution or hydrophobic behavior (especially through the KOW parameter), adsorption to soils and biodegradation. A lack of QSAR was observed to estimate desorption or potential of transfer to water. Among the 686 molecular descriptors, five were found to be dominant in the 790 collected equations and the most generic ones: four quantum-chemical descriptors, the energy of the highest occupied molecular orbital (EHOMO) and the energy of the lowest unoccupied molecular orbital (ELUMO), polarizability (α) and dipole moment (μ), and one constitutional descriptor, the molecular weight. Keeping in mind that the combination of descriptors belonging to different categories (constitutional, topological, quantum-chemical) led to improve QSAR performances, these descriptors should be considered for the development of new QSAR, for further predictions of environmental parameters. This review also allows finding of the relevant QSAR equations to predict the fate of a wide diversity of compounds in the environment. PMID:25866458

  13. The assess facility descriptor module

    SciTech Connect

    Jordan, S.E.; Winblad, A.; Key, B.; Walker, S.; Renis, T.; Saleh, R.

    1989-01-01

    The Facility Descriptor (Facility) module is part of the Analytic System and Software for Evaluating Safeguards and Security (ASSESS). Facility is the foundational software application in the ASSESS system for modelling a nuclear facility's safeguards and security system to determine the effectiveness against theft of special nuclear material. The Facility module provides the tools for an analyst to define a complete description of a facility's physical protection system which can then be used by other ASSESS software modules to determine vulnerability to a spectrum of insider and outsider threats. The analyst can enter a comprehensive description of the protection system layout including all secured areas, target locations, and detailed safeguards specifications. An extensive safeguard component catalog provides the reference data for calculating delay and detection performance. Multiple target locations within the same physical area may be specified, and the facility may be defined for two different operational states such as dayshift and nightshift. 6 refs., 5 figs.

  14. SMILES-based optimal descriptors: QSAR modeling of carcinogenicity by balance of correlations with ideal slopes.

    PubMed

    Toropov, A A; Toropova, A P; Benfenati, E

    2010-09-01

    Optimal descriptors which are calculated using the simplified molecular input line entry system (SMILES) were utilized to build quantitative structure-activity relationships (QSAR) of carcinogenicity (log TD50). Three schemes of the modeling have been examined: 1. The most traditional "classic" training-test system, i.e., models are built with training set and validated with external test set; 2. The correlation balance, i.e., models are built with preliminary estimation of the predictability of the model with the calibration set (this set plays a role of preliminary test set); and 3. The extended correlation balance that takes into account the slopes of regression lines in plots experimental versus predicted values of carcinogenicity (in ideal, these slopes should be similar). It has been shown that the extended correlation balance with the ideal slopes gives most robust prediction of carcinogenicity for external test set. These models have been built by Monte Carlo method for three splits into subtraining set, calibration set, and test set. The number of the N-nitroso groups (i.e., R1-N(R2)-N=O) in a molecular system has been examined as an additional descriptor. 2010 Elsevier Masson SAS. All rights reserved.

  15. Molecular structure, IR spectra, and chemical reactivity of cisplatin and transplatin: DFT studies, basis set effect and solvent effect.

    PubMed

    Wang, Yang; Liu, Qingzhu; Qiu, Ling; Wang, Tengfei; Yuan, Haoliang; Lin, Jianguo; Luo, Shineng

    2015-01-01

    Three different density functional theory (DFT) methods were employed to study the molecular structures of cis-diamminedichloroplatinum(II) (CDDP) and trans-diamminedichloroplatinum(II) (TDDP). The basis set effect on the structure was also investigated. By comparing the optimized structures with the experimental data, a relatively more accurate method was chosen for further study of the IR spectra and other properties as well as the solvent effect. Nineteen characteristic vibrational bands of the title compounds were assigned and compared with available experimental data. The number of characteristic peaks for the asymmetric stretching and deformation vibrations of N-H can serve as a judgment for the isomer between CDDP and TDDP. Significant solvent effect was observed on the molecular structures and IR spectra. The reduced density gradient analysis was performed to study the intramolecular interactions of CDDP and TDDP, and the nature of changes in the structures caused by the solvent was illustrated. Several descriptors determined from the energies of frontier molecular orbitals (HOMO and LUMO) were applied to describe the chemical reactivity of the title compounds. The molecular electrostatic potential (MESP) surfaces showed that the amino groups were the most favorable sites that nucleophilic reagents tend to attack, and CDDP was easier to be attacked by nucleophilic reagents than TDDP.

  16. Flexible 3D pharmacophores as descriptors of dynamic biological space.

    PubMed

    Nettles, James H; Jenkins, Jeremy L; Williams, Chris; Clark, Alex M; Bender, Andreas; Deng, Zhan; Davies, John W; Glick, Meir

    2007-10-01

    Development of a pharmacophore hypothesis related to small-molecule activity is pivotal to chemical optimization of a series, since it defines features beneficial or detrimental to activity. Although crystal structures may provide detailed 3D interaction information for one molecule with its receptor, docking a different ligand to that model often leads to unreliable results due to protein flexibility. Graham Richards' lab was one of the first groups to utilize "fuzzy" pattern recognition algorithms taken from the field of image processing to solve problems in protein modeling. Thus, descriptor "fuzziness" was partly able to emulate conformational flexibility of the target while simultaneously enhancing the speed of the search. In this work, we extend these developments to a ligand-based method for describing and aligning molecules in flexible chemical space termed FEature POint PharmacophoreS (FEPOPS), which allows exploration of dynamic biological space. We develop a novel, combinatorial algorithm for molecular comparisons and evaluate it using the WOMBAT dataset. The new approach shows superior retrospective virtual screening performance than earlier shape-based or charge-based algorithms. Additionally, we use target prediction to evaluate how FEPOPS alignments match the molecules biological activity by identifying the atoms and features that make the key contributions to overall chemical similarity. Overall, we find that FEPOPS are sufficiently fuzzy and flexible to find not only new ligand scaffolds, but also challenging molecules that occupy different conformational states of dynamic biological space as from induced fits.

  17. [Molecular structure and fractal analysis of oligosaccharide].

    PubMed

    Liu, Wen-long; Wang, Lu-man; He, Dong-qi; Zhang, Tian-lan; Gou, Bao-di; Li, Qing

    2014-10-18

    To propose a calculation method of oligosaccharides' fractal dimension, and to provide a new approach to studying the drug molecular design and activity. By using the principle of energy optimization and computer simulation technology, the steady structures of oligosaccharides were found, and an effective way of oligosaccharides fractal dimension's calculation was further established by applying the theory of box dimension to the chemical compounds. By using the proposed method, 22 oligosaccharides' fractal dimensions were calculated, with the mean 1.518 8 ± 0.107 2; in addition, the fractal dimensions of the two activity multivalent oligosaccharides which were confirmed by experiments, An-2 and Gu-4, were about 1.478 8 and 1.516 0 respectively, while C-type lectin-like receptor Dectin-1's fractal dimension was about 1.541 2. The experimental and computational results were expected to help to find a class of glycoside drugs whose target receptor was Dectin-1. Fractal dimension, differing from other known macro parameters, is a useful tool to characterize the compound molecules' microscopic structure and function, which may play an important role in the molecular design and biological activity study. In the process of oligosaccharides drug screening, the fractal dimension of receptor and designed oligosaccharides or glycoclusters can be calculated respectively. The oligosaccharides with fractal dimension close to that of target receptor should then take priority compared with others, to get the drug molecules with latent activity.

  18. Aircraft noise descriptor and its application

    NASA Astrophysics Data System (ADS)

    Igarashi, Juichi

    The methods and indices used in Japan to evaluate aircraft noise and the government-enforced countermeasures are discussed. The ECPNL descriptor was modified so as to make the new descriptor, WECPNL', approximately equivalent to Lden, and the noise contours were calculated for each airport in Japan. The government enforced the policy of land purchase within the WECPNL' of 85, and the houses within the value of 75 were declared as needing insulation. The noise descriptor Leq or Ldn has been used to describe human responses to various kinds of noises. However, a single value descriptor was found to have a limit of applicability, because the human response is not a linear function of a sound level. Another defect of the descriptor is a failure to represent the human response adequately for a small number of flights. It is noted that the house vibration caused by low-frequency components of aircraft noise cannot yet be evaluated.

  19. Hedonics of odors and odor descriptors

    SciTech Connect

    Dravnieks, A.; Masurat, T.; Lamm, R.A.

    1984-07-01

    The hedonic tone (pleasantness-unpleasantness) of an air pollution odor depends on its character and influences how annoying the odor may be. In the context of air pollution, both unpleasant and pleasant odors may become objectionable, while this is less likely for hedonically neutral odors. A profile of an odor consists of a list of odor descriptors and ratings of the applicabilities of each of the descriptors to the odor being characterized. The working hypothesis was that each of the descriptors can be assigned its own hedonic connotation (tone) from very pleasant, through neutral, to the very unpleasant. The hedonic tones of the descriptors could then be combined with the descriptor applicability percentages over the entire profile, producing a profile-derived hedonic index. The data that were used were profiles of odors and the hedonic ratings of the same odors made directly upon smelling these odors, obtained independently of the study.

  20. Chemical Descriptors Library (CDL): a generic, open source software library for chemical informatics.

    PubMed

    Sykora, Vladimir J; Leahy, David E

    2008-10-01

    In this article the Chemical Descriptors Library (CDL), a generic, open source software library for chemical informatics is introduced. The library is written using standard-compliant C++ programming language. The CDL provides a generic interface for traversing the structure of a molecular graph and accessing its properties. As a result, the software offers flexibility, reusability, and maintainability. This interface has been used to develop several chemical informatics algorithms, including molecular text format parsers and writers; substructure, pharmacophore, and atom type fingerprints; and both common substructure search and SMARTS search. The algorithms are described and evaluated on 3 data sets comprising 1000, 50000, and 100000 small molecules, respectively. The properties of the algorithms in terms of complexity analysis and processing times are presented and discussed.

  1. Is Electronegativity a Useful Descriptor for the "Pseudo-Alkali-Metal" NH4?

    SciTech Connect

    Whiteside, Alexander; Xantheas, Sotiris S.; Gutowski, Maciej S.

    2011-11-18

    Molecular ions in the form of "pseudo-atoms" are common structural motifs in chemistry, with properties that are transferrable between different compounds. We have determined the electronegativity of the "pseudo-alkali metal" ammonium (NH4) and evaluated its reliability as a descriptor in comparison to the electronegativities of the alkali metals. The computed properties of its binary complexes with astatine and of selected borohydrides confirm the similarity of NH4 to the alkali metal atoms, although the electronegativity of NH4 is relatively large in comparison to its cationic radius. We paid particular attention to the molecular properties of ammonium (angular anisotropy, geometric relaxation, and reactivity), which can cause deviations from the behaviour expected of a conceptual "true alkali metal" with this electronegativity. These deviations allow for the discrimination of effects associated with the polyatomic nature of NH4.

  2. Viewpoint 9--molecular structure of aqueous interfaces

    NASA Technical Reports Server (NTRS)

    Pohorille, A.; Wilson, M. A.

    1993-01-01

    In this review we summarize recent progress in our understanding of the structure of aqueous interfaces emerging from molecular level computer simulations. It is emphasized that the presence of the interface induces specific structural effects which, in turn, influence a wide variety of phenomena occurring near the phase boundaries. At the liquid-vapor interface, the most probable orientations of a water molecule is such that its dipole moment lies parallel to the interface, one O-H bond points toward the vapor and the other O-H bond is directed toward the liquid. The orientational distributions are broad and slightly asymmetric, resulting in an excess dipole moment pointing toward the liquid. These structural preferences persist at interfaces between water and nonpolar liquids, indicating that the interactions between the two liquids in contact are weak. It was found that liquid-liquid interfaces are locally sharp but broadened by capillary waves. One consequence of anisotropic orientations of interfacial water molecules is asymmetric interactions, with respect to the sign of the charge, of ions with the water surface. It was found that even very close to the surface ions retain their hydration shells. New features of aqueous interfaces have been revealed in studies of water-membrane and water-monolayer systems. In particular, water molecules are strongly oriented by the polar head groups of the amphiphilic phase, and they penetrate the hydrophilic head-group region, but not the hydrophobic core. At infinite dilution near interfaces, amphiphilic molecules exhibit behavior different from that in the gas phase or in bulk water. This result sheds new light on the nature of hydrophobic effect in the interfacial regions. The presence of interfaces was also shown to affect both equilibrium and dynamic components of rates of chemical reactions. Applications of continuum models to interfacial problems have been, so far, unsuccessful. This, again, underscores the

  3. Viewpoint 9--molecular structure of aqueous interfaces.

    PubMed

    Pohorille, A; Wilson, M A

    1993-01-01

    In this review we summarize recent progress in our understanding of the structure of aqueous interfaces emerging from molecular level computer simulations. It is emphasized that the presence of the interface induces specific structural effects which, in turn, influence a wide variety of phenomena occurring near the phase boundaries. At the liquid-vapor interface, the most probable orientations of a water molecule is such that its dipole moment lies parallel to the interface, one O-H bond points toward the vapor and the other O-H bond is directed toward the liquid. The orientational distributions are broad and slightly asymmetric, resulting in an excess dipole moment pointing toward the liquid. These structural preferences persist at interfaces between water and nonpolar liquids, indicating that the interactions between the two liquids in contact are weak. It was found that liquid-liquid interfaces are locally sharp but broadened by capillary waves. One consequence of anisotropic orientations of interfacial water molecules is asymmetric interactions, with respect to the sign of the charge, of ions with the water surface. It was found that even very close to the surface ions retain their hydration shells. New features of aqueous interfaces have been revealed in studies of water-membrane and water-monolayer systems. In particular, water molecules are strongly oriented by the polar head groups of the amphiphilic phase, and they penetrate the hydrophilic head-group region, but not the hydrophobic core. At infinite dilution near interfaces, amphiphilic molecules exhibit behavior different from that in the gas phase or in bulk water. This result sheds new light on the nature of hydrophobic effect in the interfacial regions. The presence of interfaces was also shown to affect both equilibrium and dynamic components of rates of chemical reactions. Applications of continuum models to interfacial problems have been, so far, unsuccessful. This, again, underscores the

  4. Analysis of peptide-protein binding using amino acid descriptors: prediction and experimental verification for human histocompatibility complex HLA-A0201.

    PubMed

    Guan, Pingping; Doytchinova, Irini A; Walshe, Valerie A; Borrow, Persephone; Flower, Darren R

    2005-11-17

    Amino acid descriptors are often used in quantitative structure-activity relationship (QSAR) analysis of proteins and peptides. In the present study, descriptors were used to characterize peptides binding to the human MHC allele HLA-A0201. Two sets of amino acid descriptors were chosen: 93 descriptors taken from the amino acid descriptor database AAindex and the z descriptors defined by Wold and Sandberg. Variable selection techniques (SIMCA, genetic algorithm, and GOLPE) were applied to remove redundant descriptors. Our results indicate that QSAR models generated using five z descriptors had the highest predictivity and explained variance (q2 between 0.6 and 0.7 and r2 between 0.6 and 0.9). Further to the QSAR analysis, 15 peptides were synthesized and tested using a T2 stabilization assay. All peptides bound to HLA-A0201 well, and four peptides were identified as high-affinity binders.

  5. Is conformation a fundamental descriptor in QSAR? A case for halogenated anesthetics

    PubMed Central

    Guimarães, Maria C; Duarte, Mariene H; Silla, Josué M

    2016-01-01

    Summary An intriguing question in 3D-QSAR lies on which conformation(s) to use when generating molecular descriptors (MD) for correlation with bioactivity values. This is not a simple task because the bioactive conformation in molecule data sets is usually unknown and, therefore, optimized structures in a receptor-free environment are often used to generate the MD´s. In this case, a wrong conformational choice can cause misinterpretation of the QSAR model. The present computational work reports the conformational analysis of the volatile anesthetic isoflurane (2-chloro-2-(difluoromethoxy)-1,1,1-trifluoroethane) in the gas phase and also in polar and nonpolar implicit and explicit solvents to show that stable minima (ruled by intramolecular interactions) do not necessarily coincide with the bioconformation (ruled by enzyme induced fit). Consequently, a QSAR model based on two-dimensional chemical structures was built and exhibited satisfactory modeling/prediction capability and interpretability, then suggesting that these 2D MD´s can be advantageous over some three-dimensional descriptors. PMID:27340468

  6. Molecular structure of the collagen triple helix.

    PubMed

    Brodsky, Barbara; Persikov, Anton V

    2005-01-01

    The molecular conformation of the collagen triple helix confers strict amino acid sequence constraints, requiring a (Gly-X-Y)(n) repeating pattern and a high content of imino acids. The increasing family of collagens and proteins with collagenous domains shows the collagen triple helix to be a basic motif adaptable to a range of proteins and functions. Its rodlike domain has the potential for various modes of self-association and the capacity to bind receptors, other proteins, GAGs, and nucleic acids. High-resolution crystal structures obtained for collagen model peptides confirm the supercoiled triple helix conformation, and provide new information on hydrogen bonding patterns, hydration, sidechain interactions, and ligand binding. For several peptides, the helix twist was found to be sequence dependent, and such variation in helix twist may serve as recognition features or to orient the triple helix for binding. Mutations in the collagen triple-helix domain lead to a variety of human disorders. The most common mutations are single-base substitutions that lead to the replacement of one Gly residue, breaking the Gly-X-Y repeating pattern. A single Gly substitution destabilizes the triple helix through a local disruption in hydrogen bonding and produces a discontinuity in the register of the helix. Molecular information about the collagen triple helix and the effect of mutations will lead to a better understanding of function and pathology.

  7. Algorithmic dimensionality reduction for molecular structure analysis.

    PubMed

    Brown, W Michael; Martin, Shawn; Pollock, Sara N; Coutsias, Evangelos A; Watson, Jean-Paul

    2008-08-14

    Dimensionality reduction approaches have been used to exploit the redundancy in a Cartesian coordinate representation of molecular motion by producing low-dimensional representations of molecular motion. This has been used to help visualize complex energy landscapes, to extend the time scales of simulation, and to improve the efficiency of optimization. Until recently, linear approaches for dimensionality reduction have been employed. Here, we investigate the efficacy of several automated algorithms for nonlinear dimensionality reduction for representation of trans, trans-1,2,4-trifluorocyclo-octane conformation--a molecule whose structure can be described on a 2-manifold in a Cartesian coordinate phase space. We describe an efficient approach for a deterministic enumeration of ring conformations. We demonstrate a drastic improvement in dimensionality reduction with the use of nonlinear methods. We discuss the use of dimensionality reduction algorithms for estimating intrinsic dimensionality and the relationship to the Whitney embedding theorem. Additionally, we investigate the influence of the choice of high-dimensional encoding on the reduction. We show for the case studied that, in terms of reconstruction error root mean square deviation, Cartesian coordinate representations and encodings based on interatom distances provide better performance than encodings based on a dihedral angle representation.

  8. Structure and Dynamics of Cellulose Molecular Solutions

    NASA Astrophysics Data System (ADS)

    Wang, Howard; Zhang, Xin; Tyagi, Madhusudan; Mao, Yimin; Briber, Robert

    Molecular dissolution of microcrystalline cellulose has been achieved through mixing with ionic liquid 1-Ethyl-3-methylimidazolium acetate (EMIMAc), and organic solvent dimethylformamide (DMF). The mechanism of cellulose dissolution in tertiary mixtures has been investigated by combining quasielastic and small angle neutron scattering (QENS and SANS). As SANS data show that cellulose chains take Gaussian-like conformations in homogenous solutions, which exhibit characteristics of having an upper critical solution temperature, the dynamic signals predominantly from EMIMAc molecules indicate strong association with cellulose in the dissolution state. The mean square displacement quantities support the observation of the stoichiometric 3:1 EMIMAc to cellulose unit molar ratio, which is a necessary criterion for the molecular dissolution of cellulose. Analyses of dynamics structure factors reveal the temperature dependence of a slow and a fast process for EMIMAc's bound to cellulose and in DMF, respectively, as well as a very fast process due possibly to the rotational motion of methyl groups, which persisted to near the absolute zero.

  9. Three dimensional shape comparison of flexible proteins using the local-diameter descriptor

    PubMed Central

    Fang, Yi; Liu, Yu-Shen; Ramani, Karthik

    2009-01-01

    Background Techniques for inferring the functions of the protein by comparing their shape similarity have been receiving a lot of attention. Proteins are functional units and their shape flexibility occupies an essential role in various biological processes. Several shape descriptors have demonstrated the capability of protein shape comparison by treating them as rigid bodies. But this may give rise to an incorrect comparison of flexible protein shapes. Results We introduce an efficient approach for comparing flexible protein shapes by adapting a local diameter (LD) descriptor. The LD descriptor, developed recently to handle skeleton based shape deformations [1], is adapted in this work to capture the invariant properties of shape deformations caused by the motion of the protein backbone. Every sampled point on the protein surface is assigned a value measuring the diameter of the 3D shape in the neighborhood of that point. The LD descriptor is built in the form of a one dimensional histogram from the distribution of the diameter values. The histogram based shape representation reduces the shape comparison problem of the flexible protein to a simple distance calculation between 1D feature vectors. Experimental results indicate how the LD descriptor accurately treats the protein shape deformation. In addition, we use the LD descriptor for protein shape retrieval and compare it to the effectiveness of conventional shape descriptors. A sensitivity-specificity plot shows that the LD descriptor performs much better than the conventional shape descriptors in terms of consistency over a family of proteins and discernibility across families of different proteins. Conclusion Our study provides an effective technique for comparing the shape of flexible proteins. The experimental results demonstrate the insensitivity of the LD descriptor to protein shape deformation. The proposed method will be potentially useful for molecule retrieval with similar shapes and rapid structure

  10. Development of structure information from molecular topology for modeling chemical and biological properties: a tribute to the creativity of Lemont Burwell Kier on his 80th Birthday.

    PubMed

    Hall, Lowell H

    2012-06-01

    This review is a salute to Monty Kier's creativity. Emphasis is placed on creative aspects in the development of the representation of molecular topological structure information and the resultant formalisms: molecular connectivity and electrotopological state (E-State). Less attention is given to detailed analysis of individual papers and the generally well known books and book chapters. This discussion reveals creative paths that led to the concept of the atomic descriptors, simple connectivity delta, encoding local topology, and valence delta value which encodes valence electron information. The fundamental developments that led to the creation of molecular connectivity chi indices are described along with extensions to different chi and delta chi formalisms. Continued thinking about structure in the topological sense led to the development of the only valence state electronegativity formalism based entirely on structure, Kier-Hall electronegativity (KHE). That creation further inspired the development of the electronegativity/topology-based atomic intrinsic state along with perturbation terms that together give electrotopological state indices (E-State). Further creation led to atom and bond type E-State descriptors. All these developments are briefly illustrated with examples in QSAR, chemical similarity, and database searching.

  11. [Bayesian regularized BP neural network model for quantitative relationship between the electrochemical reduction potential and molecular structures of chlorinated aromatic compounds].

    PubMed

    Sun, Wei; Zeng, Guang-ming; Wei, Wan-zhi; Huang, Guo-he

    2005-03-01

    Bayesian regularized BP neural network (BRBPNN) technique was applied in QSPR model in environmental field. The BRBPNN model for quantitative relationship between the electrochemical reduction potential (ERP) and chemical structures of 87 chlorinated aromatic compounds was established. The structure descriptor pool is consisted of Cl number (Cl), molecular weight (MW) and 6 quantum chemistry parameters which are calculated by MOPAC2000 built in ChemOffice2004, including energy of the highest occupied molecular orbital (E(HOMO)), energy of the lowest occupied molecular orbital (E(LUMO)), heat of formation(HF), dipole(DIP), electronic energy(EE), core-core repulsion(CCR). The achieved optimal network structure was 6-20-1, which possessed stronger fitting and prediction capacity than that of the stepwise linear regression and with the correlation coefficients square and the mean square error for the training set and the test set as 0.999 and 0.000105, 0.965 and 0.00159 respectively. The sum of square weights between each input neuron and the hidden layer of BRBPNN(6-20-1) indicate the effect of descriptor on the electric potential declining in the order of ELUMO > EHOMO > HF> CCR > EE > DIP. The scatter diagrams show that the EE descriptors had positive effect on ERP, and ELUMO, HF, DIP had negative effects, and EHOMO and CCR showed ambiguous effects. Results show that Bayesian regularized BP neural network is of automated regularization parameter selection capability and thus may ensure the excellent generation ability and robustness. This study threw more light on the applicability of electrochemical treatment for the chlorinated aromatic compounds and the analysis on electrochemical reduction mechanism.

  12. Learning Rotation-Invariant Local Binary Descriptor.

    PubMed

    Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

    2017-08-01

    In this paper, we propose a rotation-invariant local binary descriptor (RI-LBD) learning method for visual recognition. Compared with hand-crafted local binary descriptors, such as local binary pattern and its variants, which require strong prior knowledge, local binary feature learning methods are more efficient and data-adaptive. Unlike existing learning-based local binary descriptors, such as compact binary face descriptor and simultaneous local binary feature learning and encoding, which are susceptible to rotations, our RI-LBD first categorizes each local patch into a rotational binary pattern (RBP), and then jointly learns the orientation for each pattern and the projection matrix to obtain RI-LBDs. As all the rotation variants of a patch belong to the same RBP, they are rotated into the same orientation and projected into the same binary descriptor. Then, we construct a codebook by a clustering method on the learned binary codes, and obtain a histogram feature for each image as the final representation. In order to exploit higher order statistical information, we extend our RI-LBD to the triple rotation-invariant co-occurrence local binary descriptor (TRICo-LBD) learning method, which learns a triple co-occurrence binary code for each local patch. Extensive experimental results on four different visual recognition tasks, including image patch matching, texture classification, face recognition, and scene classification, show that our RI-LBD and TRICo-LBD outperform most existing local descriptors.

  13. Antiproliferative activity of aroylacrylic acids. Structure-activity study based on molecular interaction fields.

    PubMed

    Drakulić, Branko J; Stanojković, Tatjana P; Zižak, Zeljko S; Dabović, Milan M

    2011-08-01

    Antiproliferative activity of 27 phenyl-substituted 4-aryl-4-oxo-2-butenoic acids (aroylacrylic acids) toward Human cervix carcinoma (HeLa), Human chronic myelogenous leukemia (K562) and Human colon tumor (LS174) cell lines in vitro are reported. Compounds are active toward all examined cell lines. The most active compounds bear two or three branched alkyl or cycloalkyl substituents on phenyl moiety having potencies in low micromolar ranges. One of most potent derivatives arrests the cell cycle at S phase in HeLa cells. The 3D QSAR study, using molecular interaction fields (MIF) and derived alignment independent descriptors (GRIND-2), rationalize the structural characteristics correlated with potency of compounds. Covalent chemistry, most possibly involved in the mode of action of reported compounds, was quantitatively accounted using frontier molecular orbitals. Pharmacophoric pattern of most potent compounds are used as a template for virtual screening, to find similar ones in database of compounds screened against DTP-NCI 60 tumor cell lines. Potency of obtained hits is well predicted.

  14. Molecular structure, vibrational, electronic and thermal properties of 4-vinylcyclohexene by quantum chemical calculations

    NASA Astrophysics Data System (ADS)

    Nagabalasubramanian, P. B.; Periandy, S.; Karabacak, Mehmet; Govindarajan, M.

    2015-06-01

    The solid phase FT-IR and FT-Raman spectra of 4-vinylcyclohexene (abbreviated as 4-VCH) have been recorded in the region 4000-100 cm-1. The optimized molecular geometry and vibrational frequencies of the fundamental modes of 4-VCH have been precisely assigned and analyzed with the aid of structure optimizations and normal coordinate force field calculations based on density functional theory (DFT) method at 6-311++G(d,p) level basis set. The theoretical frequencies were properly scaled and compared with experimentally obtained FT-IR and FT-Raman spectra. Also, the effect due the substitution of vinyl group on the ring vibrational frequencies was analyzed and a detailed interpretation of the vibrational spectra of this compound has been made on the basis of the calculated total energy distribution (TED). The time dependent DFT (TD-DFT) method was employed to predict its electronic properties, such as electronic transitions by UV-Visible analysis, HOMO and LUMO energies, molecular electrostatic potential (MEP) and various global reactivity and selectivity descriptors (chemical hardness, chemical potential, softness, electrophilicity index). Stability of the molecule arising from hyper conjugative interaction, charge delocalization has been analyzed using natural bond orbital (NBO) analysis. Atomic charges obtained by Mulliken population analysis and NBO analysis are compared. Thermodynamic properties (heat capacity, entropy and enthalpy) of the title compound at different temperatures are also calculated.

  15. Molecular structure, vibrational spectra and DFT computational studies of melaminium N-acetylglycinate dihydrate

    NASA Astrophysics Data System (ADS)

    Tanak, H.; Pawlus, K.; Marchewka, M. K.

    2016-10-01

    Melaminium N-acetylglycinate dihydrate, an organic material has been synthesized and characterized by X-ray diffraction, FT-IR, and FT-Raman spectroscopies for the protiated and deuteriated crystals. The title complex crystallizes in the triclinic system, and the space group is P-1 with a = 5.642(1) Å, b = 7.773(2) Å, c = 15.775(3) Å, α = 77.28(1)°, β = 84.00(1)°, γ = 73.43(1)° and Z = 2. The molecular geometry, vibrational frequencies and intensity of the vibrational bands have been interpreted with the aid of structure optimization based on density functional method (B3LYP) with the 6-311++G(d,p) basis set. The obtained vibrational wavenumbers and optimized geometric parameters were seen to be in good agreement with the experimental data. The intermolecular hydrogen bonding interactions of the title compound have been investigated using the natural bonding orbital analysis. It reveals that the O-H···O, N-H···N and N-H···O intermolecular interactions significantly influence crystal packing of this molecule. The non-linear optical properties are also addressed theoretically. The predicted NLO properties of the title compound are much greater than ones of urea. In addition, DFT calculations of the title compound, molecular electrostatic potential, thermodynamic properties, frontier orbitals and chemical reactivity descriptors were also performed at 6-311++G(d,p) level of theory.

  16. Speculations on the molecular structure of eumelanin.

    PubMed

    Swift, J A

    2009-04-01

    Eumelanin is the polymeric black pigment commonly found in hair and skin. Its chemical intractability, to all but vigorous oxidizing agents, has hindered satisfactory understanding of its molecular structure. It is well-established that the immediate precursor to polymerization, indole-5,6-quinone (IQ), is biosynthesized from the amino acid tyrosine. Current views are that the polymer consists of single bond connections between random indole and degraded indole units. In this paper, an alternative chemical scheme for the polymerization of IQ is proposed based upon the original suggestion by Horner in 1949 that a Diels-Alder (D-A) reaction might be involved. The proposed basic chemical scheme for eumelanin formation is that D-A addition occurs specifically between the 2- and 3-positions of one IQ molecule and the 7- and 4- positions respectively of a second IQ molecule, that the ensuing diketo bridge is oxidized to carboxyl groups and that, by decarboxylation and aromatization, a fused indole dimer is produced. It is envisaged that, by further D-A addition of more IQ molecules, oligomers of greater molecular mass are produced. Calculations based on published bond lengths and angles for the indole nucleus show that oligomeric units containing a total of up to 11 fused indoles could be packed into a flat circular disc of 20 A diameter. The discs of the extensively conjugated polymer are envisaged to be stacked above each other by pi-pi interaction and with a spacing of 3.4 A to produce cylindrical units, the mass density of which is calculated to be 1.54 gm cm(-3); approximating with actual physical measurements. The size and shape of the predicted cylinders are in concordance with those observed in atomic force microscope investigations of eumelanin proto-particles. The model is also in agreement with published experimental data that 2/3rds of the carbon dioxide liberated during eumelanin formation derives from positions 5- and 6- of the IQ molecule.

  17. Petals' shape descriptor for blooming flowers recognition

    NASA Astrophysics Data System (ADS)

    Tan, Wooi-Nee; Tan, Yi-Fei; Koo, Ah-Choo; Lim, Yan-Peng

    2012-04-01

    This paper proposes a new descriptor to identify the petals' shape of a blooming flower based on the digital images captured in natural scene. The proposed descriptor can be used as one of features in computer aided flower recognition system beside the commonly used features such as number of petals and color. Experiments were conducted on the Malaysia flowers with same number of petals and with similar color across different species of flowers. 35 images from 7 species were used as the training set to set up the reference values of petals' shape descriptor and 7 new images were used as the testing set. The descriptor calculated from the testing set is then compared to the reference values from the training set to achieve the flowers recognition purpose. With the given set of data, complete success in full identification rate was obtained.

  18. [Descriptors of breathlessness in Mexican Spanish].

    PubMed

    Vázquez-García, J C; Balcázar-Cruz, C A; Cervantes-Méndez, G; Mejía-Alfaro, R; Cossío-Alcántara, J; Ramírez-Venegas, A

    2006-05-01

    Breathlessness is the most common symptom of cardiovascular or pulmonary disease. The term encompasses a wide range of descriptors used by patients, however. Identifying those descriptors can be useful for analyzing symptoms and understanding how they arise. The aim of this study was to characterize the descriptors of breathlessness used in Mexican Spanish and to consider their association with various states of respiratory distress and cardiovascular or pulmonary disease. A questionnaire was based on 21 descriptors of breathlessness, some of which had no equivalents in English. The subjects included 15 healthy individuals during a cardiopulmonary stress test, 13 healthy subjects after a carbon dioxide rebreathing procedure, and 10 healthy women during pregnancy. We also included 16 patients with confirmed heart disease in stable condition, 15 patients during exacerbation of asthma, 20 with stable chronic obstructive pulmonary disease, and 15 with diffuse interstitial lung disease also in stable condition. Descriptors of breathlessness were then grouped based on the results of cluster analysis. Seven clusters of phrasal descriptors were identified as possibly representative of types of dyspnea. These clusters of descriptors were categorized as follows: agitation, suffocation, smothering, inhalation, exhalation, panting, and rapidity. Associations between types of dyspnea and the groups of participants were identified based on how frequently they used the terms. At least 7 clusters or groups of descriptors of breathlessness were identified as equivalent to 7 types of dyspnea; some items have no equivalent in English. Healthy subjects with respiratory distress or certain groups of patients with cardiovascular or pulmonary disease are associated with certain types of dyspnea.

  19. Predicting enzymatic function from global binding site descriptors.

    PubMed

    Volkamer, Andrea; Kuhn, Daniel; Rippmann, Friedrich; Rarey, Matthias

    2013-03-01

    Due to the rising number of solved protein structures, computer-based techniques for automatic protein functional annotation and classification into families are of high scientific interest. DoGSiteScorer automatically calculates global descriptors for self-predicted pockets based on the 3D structure of a protein. Protein function predictors on three levels with increasing granularity are built by use of a support vector machine (SVM), based on descriptors of 26632 pockets from enzymes with known structure and enzyme classification. The SVM models represent a generalization of the available descriptor space for each enzyme class, subclass, and substrate-specific sub-subclass. Cross-validation studies show accuracies of 68.2% for predicting the correct main class and accuracies between 62.8% and 80.9% for the six subclasses. Substrate-specific recall rates for a kinase subset are 53.8%. Furthermore, application studies show the ability of the method for predicting the function of unknown proteins and gaining valuable information for the function prediction field. Copyright © 2012 Wiley Periodicals, Inc.

  20. On the alignment of shapes represented by Fourier descriptors

    NASA Astrophysics Data System (ADS)

    Sjöstrand, Karl; Ericsson, Anders; Larsen, Rasmus

    2006-03-01

    The representation of shapes by Fourier descriptors is a time-honored technique that has received relatively little attention lately. Nevertheless, it has its benefits and is suitable for describing a range of medical structures in two dimensions. Delineations in medical applications often consist of continuous outlines of structures, where no information of correspondence between samples exist. In this article, we discuss a Euclidean alignment method that works directly with the functional representation of Fourier descriptors, and that is optimal in a least-squares sense. With corresponding starting points, the alignment of one shape onto another consists of a single expression. If the starting points are arbitrary, we present a simple algorithm to bring a set of shapes into correspondence. Results are given for three different data sets; 62 outlines of the corpus callosum brain structure, 61 outlines of the brain ventricles, and 50 outlines of the right lung. The results show that even though starting points, translations, rotations and scales have been randomized, the alignment succeeds in all cases. As an application of the proposed method, we show how high-quality shape models represented by common landmarks can be constructed in an automatic fashion. If the aligned Fourier descriptors are inverse transformed from the frequency domain to the spatial domain, a set of roughly aligned landmarks are obtained. The positions of these are then adjusted along the contour of the objects using the minimum description length criterion, producing ample correspondences. Results on this are also presented for all three data sets.

  1. The sEDA(=) and pEDA(=) descriptors of the double bonded substituent effect.

    PubMed

    Mazurek, Andrzej; Dobrowolski, Jan Cz

    2013-05-14

    New descriptors of the double bonded substituent effect, sEDA(=) and pEDA(=), were constructed based on quantum chemical calculations and NBO methodology. They show to what extent the σ and π electrons are donated to or withdrawn from the substituted system by a double bonded substituent. The new descriptors differ from descriptors of the classical substituent effect for which the pz orbital of the ipso carbon atom is engaged in the π-electron system of the two neighboring atoms in the ring. For double bonded substituents, the pz orbital participates in double bond formation with only one external atom. Moreover, the external double bond forces localization of the double bond system of the ring, significantly changing the core molecule. We demonstrated good agreement between our descriptors and the Weinhold and Landis' "natural σ and π-electronegativities": so far only descriptors allowing for evaluation of the substitution effect by a double bonded atom. The equivalency between descriptors constructed for 5- and 6-membered model structures as well as linear dependence/independence of the constructed parameters was discussed. Some interrelations between sEDA(=) and pEDA(=) and the other descriptors of (hetero)cyclic systems such as aromaticity and electron density in the ring and bond critical points were also examined.

  2. A contour-based shape descriptor for biomedical image classification and retrieval

    NASA Astrophysics Data System (ADS)

    You, Daekeun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2013-12-01

    Contours, object blobs, and specific feature points are utilized to represent object shapes and extract shape descriptors that can then be used for object detection or image classification. In this research we develop a shape descriptor for biomedical image type (or, modality) classification. We adapt a feature extraction method used in optical character recognition (OCR) for character shape representation, and apply various image preprocessing methods to successfully adapt the method to our application. The proposed shape descriptor is applied to radiology images (e.g., MRI, CT, ultrasound, X-ray, etc.) to assess its usefulness for modality classification. In our experiment we compare our method with other visual descriptors such as CEDD, CLD, Tamura, and PHOG that extract color, texture, or shape information from images. The proposed method achieved the highest classification accuracy of 74.1% among all other individual descriptors in the test, and when combined with CSD (color structure descriptor) showed better performance (78.9%) than using the shape descriptor alone.

  3. Molecular structures and intramolecular dynamics of pentahalides

    NASA Astrophysics Data System (ADS)

    Ischenko, A. A.

    2017-03-01

    This paper reviews advances of modern gas electron diffraction (GED) method combined with high-resolution spectroscopy and quantum chemical calculations in studies of the impact of intramolecular dynamics in free molecules of pentahalides. Some recently developed approaches to the electron diffraction data interpretation, based on direct incorporation of the adiabatic potential energy surface parameters to the diffraction intensity are described. In this way, complementary data of different experimental and computational methods can be directly combined for solving problems of the molecular structure and its dynamics. The possibility to evaluate some important parameters of the adiabatic potential energy surface - barriers to pseudorotation and saddle point of intermediate configuration from diffraction intensities in solving the inverse GED problem is demonstrated on several examples. With increasing accuracy of the electron diffraction intensities and the development of the theoretical background of electron scattering and data interpretation, it has become possible to investigate complex nuclear dynamics in fluxional systems by the GED method. Results of other research groups are also included in the discussion.

  4. Filamentary structure in the Orion molecular cloud

    NASA Technical Reports Server (NTRS)

    Bally, J.; Langer, W. D.; Bally, J.; Langer, W. D.; Bally, J.; Langer, W. D.

    1986-01-01

    A large scale 13CO map (containing 33,000 spectra) of the giant molecular cloud located in the southern part of Orion is presented which contains the Orion Nebula, NGC1977, and the LI641 dark cloud complex. The overall structure of the cloud is filamentary, with individual features having a length up to 40 times their width. This morphology may result from the effects of star formation in the region or embedded magnetic fields in the cloud. We suggest a simple picture for the evolution of the Orion-A cloud and the formation of the major filament. A rotating proto-cloud (counter rotating with respect to the galaxy) contians a b-field aligned with the galaxtic plane. The northern protion of this cloud collapsed first, perhaps triggered by the pressure of the Ori I OB association. The magnetic field combined with the anisotropic pressure produced by the OB-association breaks the symmetry of the pancake instability, a filament rather than a disc is produced. The growth of instabilities in the filament formed sub-condensations which are recent sites of star formation.

  5. Atomic spectral-product representations of molecular electronic structure: metric matrices and atomic-product composition of molecular eigenfunctions.

    PubMed

    Ben-Nun, M; Mills, J D; Hinde, R J; Winstead, C L; Boatz, J A; Gallup, G A; Langhoff, P W

    2009-07-02

    Recent progress is reported in development of ab initio computational methods for the electronic structures of molecules employing the many-electron eigenstates of constituent atoms in spectral-product forms. The approach provides a universal atomic-product description of the electronic structure of matter as an alternative to more commonly employed valence-bond- or molecular-orbital-based representations. The Hamiltonian matrix in this representation is seen to comprise a sum over atomic energies and a pairwise sum over Coulombic interaction terms that depend only on the separations of the individual atomic pairs. Overall electron antisymmetry can be enforced by unitary transformation when appropriate, rather than as a possibly encumbering or unnecessary global constraint. The matrix representative of the antisymmetrizer in the spectral-product basis, which is equivalent to the metric matrix of the corresponding explicitly antisymmetric basis, provides the required transformation to antisymmetric or linearly independent states after Hamiltonian evaluation. Particular attention is focused in the present report on properties of the metric matrix and on the atomic-product compositions of molecular eigenstates as described in the spectral-product representations. Illustrative calculations are reported for simple but prototypically important diatomic (H(2), CH) and triatomic (H(3), CH(2)) molecules employing algorithms and computer codes devised recently for this purpose. This particular implementation of the approach combines Slater-orbital-based one- and two-electron integral evaluations, valence-bond constructions of standard tableau functions and matrices, and transformations to atomic eigenstate-product representations. The calculated metric matrices and corresponding potential energy surfaces obtained in this way elucidate a number of aspects of the spectral-product development, including the nature of closure in the representation, the general redundancy or

  6. The Determination of Molecular Structure from Rotational Spectra

    DOE R&D Accomplishments Database

    Laurie, V. W.; Herschbach, D. R.

    1962-07-01

    An analysis is presented concerning the average molecular configuration variations and their effects on molecular structure determinations. It is noted that the isotopic dependence of the zero-point is often primarily governed by the isotopic variation of the average molecular configuration. (J.R.D.)

  7. Molecular cloning of chicken aggrecan. Structural analyses.

    PubMed Central

    Chandrasekaran, L; Tanzer, M L

    1992-01-01

    The large, aggregating chondroitin sulphate proteoglycan of cartilage, aggrecan, has served as a generic model of proteoglycan structure. Molecular cloning of aggrecans has further defined their amino acid sequences and domain structures. In this study, we have obtained the complete coding sequence of chicken sternal cartilage aggrecan by a combination of cDNA and genomic DNA sequencing. The composite sequence is 6117 bp in length, encoding 1951 amino acids. Comparison of chicken aggrecan protein primary structure with rat, human and bovine aggrecans has disclosed both similarities and differences. The domains which are most highly conserved at 70-80% identity are the N-terminal domains G1 and G2 and the C-terminal domain G3. The chondroitin sulphate domain of chicken aggrecan is smaller than that of rat and human aggrecans and has very distinctive repeat sequences. It has two separate sections, one comprising 12 consecutive Ser-Gly-Glu repeats of 20 amino acids each, adjacent to the other which has 23 discontinuous Ser-Gly-Glu repeats of 10 amino acids each; this latter region, N-terminal to the former one, appears to be unique to chicken aggrecan. The two regions contain a total of 94 potential chondroitin sulphate attachment sites. Genomic comparison shows that, although chicken exons 11-14 are identical in size to the rat and human exons, chicken exon 10 is the smallest of the three species. This is also reflected in the size of its chondroitin sulphate coding region and in the total number of Ser-Gly pairs. The putative keratan sulphate domain shows 31-45% identity with the other species and lacks the repetitive sequences seen in the others. In summary, while the linear arrangement of specific domains of chicken aggrecan is identical to that in the aggrecans of other species, and while there is considerable identity of three separate domains, chicken aggrecan demonstrates unique features, notably in its chondroitin sulphate domain and its keratan sulphate

  8. PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

    PubMed

    Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

    2017-02-03

    The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles.

  9. Fractal and Euclidean descriptors of platelet shape.

    PubMed

    Kraus, Max-Joseph; Neeb, Heiko; Strasser, Erwin F

    2014-01-01

    Platelet shape change is a dynamic membrane surface process that exhibits remarkable morphological heterogeneity. Once the outline of an irregular shape is identified and segmented from a digital image, several mathematical descriptors can be applied to numerical characterize the irregularity of the shapes surface. 13072 platelet outlines (PLO) were segmented automatically from 1928 microscopic images using a newly developed algorithm for the software product Matlab R2012b. The fractal dimension (FD), circularity, eccentricity, area and perimeter of each PLO were determined. 972 PLO were randomly assigned for computer-assisted manual measurement of platelet diameter as well as number, width and length of filopodia per platelet. FD can be used as a surrogate parameter for determining the roughness of the PLO and circularity can be used as a surrogate to estimate the number and length of filopodia. The relationship between FD and perimeter of the PLO reveals the existence of distinct groups of platelets with significant structural differences which may be caused by platelet activation. This new method allows for the standardized continuous numerical classification of platelet shape and its dynamic change, which is useful for the analysis of altered platelet activity (e.g. inflammatory diseases, contact activation, drug testing).

  10. Shape Signatures: New Descriptors for Predicting Cardiotoxicity In Silico

    PubMed Central

    Chekmarev, Dmitriy S.; Kholodovych, Vladyslav; Balakin, Konstantin V.; Ivanenkov, Yan; Ekins, Sean; Welsh, William J.

    2009-01-01

    Shape Signatures is a new computational tool that is being evaluated for applications in computational toxicology and drug discovery. The method employs a customized ray-tracing algorithm to explore the volume enclosed by the surface of a molecule and then uses the output to construct compact histograms (i.e., signatures) that encode for molecular shape and polarity. In the present study, we extend the application of the Shape Signatures methodology to the domain of computational models for cardiotoxicity. The Shape Signatures method is used to generate molecular descriptors that are then utilized with widely used classification techniques such as k nearest neighbors (k-NN), support vector machines (SVM), and Kohonen self-organizing maps (SOM). The performances of these approaches were assessed by applying them to a data set of compounds with varying affinity toward the 5-HT2B receptor as well as a set of human ether-a-go-go-related gene (hERG) potassium channel inhibitors. Our classification models for 5-HT2B represented the first attempt at global computational models for this receptor and exhibited average accuracies in the range of 73−83%. This level of performance is comparable to using commercially available molecular descriptors. The overall accuracy of the hERG Shape Signatures–SVM models was 69−73%, in line with other computational models published to date. Our data indicate that Shape Signatures descriptors can be used with SVM and Kohonen SOM and perform better in classification problems related to the analysis of highly clustered and heterogeneous property spaces. Such models may have utility for predicting the potential for cardiotoxicity in drug discovery mediated by the 5-HT2B receptor and hERG. PMID:18461975

  11. Structure based design, synthesis, pharmacophore modeling, virtual screening, and molecular docking studies for identification of novel cyclophilin D inhibitors.

    PubMed

    Valasani, Koteswara Rao; Vangavaragu, Jhansi Rani; Day, Victor W; Yan, Shirley ShiDu

    2014-03-24

    Cyclophilin D (CypD) is a peptidyl prolyl isomerase F that resides in the mitochondrial matrix and associates with the inner mitochondrial membrane during the mitochondrial membrane permeability transition. CypD plays a central role in opening the mitochondrial membrane permeability transition pore (mPTP) leading to cell death and has been linked to Alzheimer's disease (AD). Because CypD interacts with amyloid beta (Aβ) to exacerbate mitochondrial and neuronal stress, it is a potential target for drugs to treat AD. Since appropriately designed small organic molecules might bind to CypD and block its interaction with Aβ, 20 trial compounds were designed using known procedures that started with fundamental pyrimidine and sulfonamide scaffolds know to have useful therapeutic effects. Two-dimensional (2D) quantitative structure-activity relationship (QSAR) methods were applied to 40 compounds with known IC50 values. These formed a training set and were followed by a trial set of 20 designed compounds. A correlation analysis was carried out comparing the statistics of the measured IC50 with predicted values for both sets. Selectivity-determining descriptors were interpreted graphically in terms of principle component analyses. These descriptors can be very useful for predicting activity enhancement for lead compounds. A 3D pharmacophore model was also created. Molecular dynamics simulations were carried out for the 20 trial compounds with known IC50 values, and molecular descriptors were determined by 2D QSAR studies using the Lipinski rule-of-five. Fifteen of the 20 molecules satisfied all 5 Lipinski rules, and the remaining 5 satisfied 4 of the 5 Lipinski criteria and nearly satisfied the fifth. Our previous use of 2D QSAR, 3D pharmacophore models, and molecular docking experiments to successfully predict activity indicates that this can be a very powerful technique for screening large numbers of new compounds as active drug candidates. These studies will hopefully

  12. QSPR modeling of octanol/water partition coefficient for vitamins by optimal descriptors calculated with SMILES.

    PubMed

    Toropov, A A; Toropova, A P; Raska, I

    2008-04-01

    Simplified molecular input line entry system (SMILES) has been utilized in constructing quantitative structure-property relationships (QSPR) for octanol/water partition coefficient of vitamins and organic compounds of different classes by optimal descriptors. Statistical characteristics of the best model (vitamins) are the following: n=17, R(2)=0.9841, s=0.634, F=931 (training set); n=7, R(2)=0.9928, s=0.773, F=690 (test set). Using this approach for modeling octanol/water partition coefficient for a set of organic compounds gives a model that is statistically characterized by n=69, R(2)=0.9872, s=0.156, F=5184 (training set) and n=70, R(2)=0.9841, s=0.179, F=4195 (test set).

  13. Molecular structure of gaseous isatin as studied by electron diffraction and quantum chemical calculations

    NASA Astrophysics Data System (ADS)

    Belyakov, Alexander V.; Nikolaenko, Kirill O.; Davidovich, Pavel B.; Ivanov, Anatolii D.; Garabadzhiu, Alexander V.; Rykov, Anatolii N.; Shishkov, Igor F.

    2017-03-01

    The molecular structure of isatin, indole-2,3-dione, was studied by gas-phase electron diffraction (GED) and quantum chemical calculations (M062X and MP2 methods with aug-cc-pVTZ basis set). The best fit of the experimental scattering intensities (R-factor = 4.4%) was obtained for a molecular model of Cs symmetry. The structure of the benzene ring deviates from a regular hexagon due to the adjacent pyrrole heterocycle. The small differences between similar geometric parameters were constrained at the values calculated at the M062X level. The experimental structural parameters agree well with the results of theoretical calculations. The bonds in the benzene moiety are in agreement with their standard values. The (Odbnd)Csbnd C(dbnd O) carbon-carbon bond of the pyrrole moiety (1.573(7) Å) is remarkably lengthened in comparison with standard C(sp2)sbnd C(sp2) value, 1.425(11) Å for N-methylpyrrole. According to NBO analysis of isatin, glyoxal and pyrrole-2,3-dione molecules this lengthening cannot be attributed to the steric interactions of Cdbnd O bonds alone and is, mainly, due to the electrostatic repulsion and hyperconjugation that is delocalization of oxygen lone pairs of π-type into the corresponding carbon-carbon antibonding orbital, nπ(O) → σ∗(Csbnd C). Deletion of σ∗(Csbnd C) orbital followed by subsequent geometry optimization led to shortening of the corresponding Csbnd C bond by 0.06 Å. According to different aromaticity descriptors, aromaticity of benzene moiety of isatin is smaller in comparison with benzene molecule. External magnetic field induces diatropic ring current in benzene moiety of isatin.

  14. The interaction of flavonoid-lysozyme and the relationship between molecular structure of flavonoids and their binding activity to lysozyme.

    PubMed

    Yang, Ran; Yu, Lanlan; Zeng, Huajin; Liang, Ruiling; Chen, Xiaolan; Qu, Lingbo

    2012-11-01

    In this work, the interactions of twelve structurally different flavonoids with Lysozyme (Lys) were studied by fluorescence quenching method. The interaction mechanism and binding properties were investigated. It was found that the binding capacities of flavonoids to Lys were highly depend on the number and position of hydrogen, the kind and position of glycosyl. To explore the selectivity of the bindings of flavonoids with Lys, the structure descriptors of the flavonoids were calculated under QSAR software package of Cerius2, the quantitative relationship between the structures of flavonoids and their binding activities to Lys (QSAR) was performed through genetic function approximation (GFA) regression analysis. The QSAR regression equation was K(A) = 37850.460 + 1630.01Dipole +3038.330HD-171.795MR. (r = 0.858, r(CV)(2) = 0.444, F((11,3)) = 7.48), where K(A) is binding constants, Dipole, HD and MR was dipole moment, number of hydrogen-bond donor and molecular refractivity, respectively. The obtained results make us understand better how the molecular structures influencing their binding to protein which may open up new avenues for the design of the most suitable flavonoids derivatives with structure variants.

  15. Quantitative Structure-Cytotoxicity Relationship of Bioactive Heterocycles by the Semi-empirical Molecular Orbital Method with the Concept of Absolute Hardness

    NASA Astrophysics Data System (ADS)

    Ishihara, Mariko; Sakagami, Hiroshi; Kawase, Masami; Motohashi, Noboru

    The relationship between the cytotoxicity of N-heterocycles (13 4-trifluoromethylimidazole, 15 phenoxazine and 12 5-trifluoromethyloxazole derivatives), O-heterocycles (11 3-formylchromone and 20 coumarin derivatives) and seven vitamin K2 derivatives against eight tumor cell lines (HSC-2, HSC-3, HSC-4, T98G, HSG, HepG2, HL-60, MT-4) and a maximum of 15 chemical descriptors was investigated using CAChe Worksystem 4.9 project reader. After determination of the conformation of these compounds and approximation to the molecular form present in vivo (biomimetic) by CONFLEX5, the most stable structure was determined by CAChe Worksystem 4.9 MOPAC (PM3). The present study demonstrates the best relationship between the cytotoxic activity and molecular shape or molecular weight of these compounds. Their biological activities can be estimated by hardness and softness, and by using η-χ activity diagrams.

  16. Structure and dynamics of layered molecular assemblies

    NASA Astrophysics Data System (ADS)

    Horne, Jennifer Conrad

    This dissertation focuses on the goal of understanding and controlling layered material properties from a molecular perspective. With this understanding, materials can be synthetically tailored to exhibit predetermined bulk properties. This investigation describes the optical response of a family of metal-phosphonate (MP) monolayers and multilayers, materials that are potentially useful because the films are easy to synthesize and are chemically and thermally stable. MP films have shown potential in a variety of chemical sensing and optical applications, and in this dissertation, the suitability of MP films for optical information storage is explored For this application, the extent of photonic energy transport within and between optically active layers is an important factor in determining the stability and specificity of optical modifications made to a material. Intralayer and interlayer energy transport processes can be studied selectively in MP films because the composition, and thus the properties, of each layer are controlled synthetically. It was determined by fluorescence relaxation dynamics in conjunction with atomic force microscopy (AFM) that the substrate and layer morphologies are key factors in determining the layer optical and physical properties. The initial MP layers in a multilayer are structurally heterogeneous, characterized by randomly distributed islands that are ~50 A in diameter. The population dynamics measured for these layers are non-exponential, chromophore concentration-independent, and identical for two different chromophores. The data is explained in the context of an excitation hopping model in a system where the surface is characterized by islands of aggregated chromophores as well as non-aggregated monomers. Within a MP monolayer, the dynamics are dominated by intra-island excitation hopping. Forster (dipolar) energy transfer between the energetically overlapped chromophores does not play a significant role in determining the

  17. CORAL Software: Analysis of Impacts of Pharmaceutical Agents Upon Metabolism via the Optimal Descriptors.

    PubMed

    Toropova, Mariya A; Raska, Ivan; Toporova, Alla P; Raskova, Maria

    2017-01-01

    The CORAL software has been developed as a tool to build up quantitative structure- activity relationships (QSAR) for various endpoints. The task of the present work was to estimate and to compare QSAR models for biochemical activity of various therapeutic agents, which are built up by the CORAL software. The Monte Carlo technique gives possibility to build up predictive model of an endpoint by means of selection of so-called correlation weights of various molecular features extracted from simplified molecular input-line entry system (SMILES). Descriptors calculated with these weights are basis for building up correlations &quot;structure - endpoint&quot;. Optimal descriptors, which are aimed to predict values of endpoints with apparent influence upon metabolism are crytically compared in aspect of their robustness and heuristic potential. Arguments which are confirming the necessity of reformulation of basics of QSARs are listed: (i) each QSAR model is stochastic experiment. The result of this experiment is defined by distribution into the training set and validation set; (ii) predictive potential of a model should be checked up with a group of different splits; and (iii) only model stochastically stable for a group of splits can be estimated as a reliable tool for the prediction. Examples of the improvement of the models previously suggested are demonstrated. The current version of the CORAL software remains a convenient tool to build up predictive models. The Monte Carlo technique involved for the software confirms the principle "QSAR is a random event" is important paradigm for the QSPR/QSAR analyses. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. Molecular clouds and galactic spiral structure

    NASA Technical Reports Server (NTRS)

    Dame, T. M.

    1984-01-01

    Galactic CO line emission at 115 GHz was surveyed in order to study the distribution of molecular clouds in the inner galaxy. Comparison of this survey with similar H1 data reveals a detailed correlation with the most intense 21 cm features. To each of the classical 21 cm H1 spiral arms of the inner galaxy there corresponds a CO molecular arm which is generally more clearly defined and of higher contrast. A simple model is devised for the galactic distribution of molecular clouds. The modeling results suggest that molecular clouds are essentially transient objects, existing for 15 to 40 million years after their formation in a spiral arm, and are largely confined to spiral features about 300 pc wide.

  19. Similarity Measure for Molecular Structure: A Brief Review

    NASA Astrophysics Data System (ADS)

    Bero, S. A.; Muda, A. K.; Choo, Y. H.; Muda, N. A.; Pratama, S. F.

    2017-09-01

    Similarity or distance measures have been used widely to calculate the similarity or dissimilarity between two samples of dataset. Cheminformatics is known as the domain that dealing with chemical information and both similarity and distance coefficient have been an important role for matching, searching and classification of chemical information. There are various types of similarity/distance coefficient used in molecular structure similarity searching. Generally, the calculation using similarity/distance coefficient is focusing more on 2-dimensional (2D) rather than 3-dimensional (3D) structure. In this paper, the popular similarity/distance coefficients for molecular structure will be reviewed together with the review on 3D molecular structure.

  20. Geodesic invariant feature: a local descriptor in depth.

    PubMed

    Liu, Yazhou; Lasang, Pongsak; Siegel, Mel; Sun, Quansen

    2015-01-01

    Different from the photometric images, depth images resolve the distance ambiguity of the scene, while the properties, such as weak texture, high noise, and low resolution, may limit the representation ability of the well-developed descriptors, which are elaborately designed for the photometric images. In this paper, a novel depth descriptor, geodesic invariant feature (GIF), is presented for representing the parts of the articulate objects in depth images. GIF is a multilevel feature representation framework, which is proposed based on the nature of depth images. Low-level, geodesic gradient is introduced to obtain the invariance to the articulate motion, such as scale and rotation variation. Midlevel, superpixel clustering is applied to reduce depth image redundancy, resulting in faster processing speed and better robustness to noise. High-level, deep network is used to exploit the nonlinearity of the data, which further improves the classification accuracy. The proposed descriptor is capable of encoding the local structures in the depth data effectively and efficiently. Comparisons with the state-of-the-art methods reveal the superiority of the proposed method.

  1. Automated detection of microaneurysms using robust blob descriptors

    NASA Astrophysics Data System (ADS)

    Adal, K.; Ali, S.; Sidibé, D.; Karnowski, T.; Chaum, E.; Mériaudeau, F.

    2013-03-01

    Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fundus images. Then, Hessian-based candidate selection algorithm is applied to extract image regions which are more likely to be MAs. For each candidate region, robust low-level blob descriptors such as Speeded Up Robust Features (SURF) and Intensity Normalized Radon Transform are extracted to characterize candidate MA regions. The combined features are then classified using SVM which has been trained using ten manually annotated training images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. Preliminary results show the competitiveness of the proposed candidate selection techniques against state-of-the art methods as well as the promising future for the proposed descriptors to be used in the localization of MAs from fundus images.

  2. AllergenFP: allergenicity prediction by descriptor fingerprints.

    PubMed

    Dimitrov, Ivan; Naneva, Lyudmila; Doytchinova, Irini; Bangov, Ivan

    2014-03-15

    Allergenicity, like antigenicity and immunogenicity, is a property encoded linearly and non-linearly, and therefore the alignment-based approaches are not able to identify this property unambiguously. A novel alignment-free descriptor-based fingerprint approach is presented here and applied to identify allergens and non-allergens. The approach was implemented into a four step algorithm. Initially, the protein sequences are described by amino acid principal properties as hydrophobicity, size, relative abundance, helix and β-strand forming propensities. Then, the generated strings of different length are converted into vectors with equal length by auto- and cross-covariance (ACC). The vectors were transformed into binary fingerprints and compared in terms of Tanimoto coefficient. The approach was applied to a set of 2427 known allergens and 2427 non-allergens and identified correctly 88% of them with Matthews correlation coefficient of 0.759. The descriptor fingerprint approach presented here is universal. It could be applied for any classification problem in computational biology. The set of E-descriptors is able to capture the main structural and physicochemical properties of amino acids building the proteins. The ACC transformation overcomes the main problem in the alignment-based comparative studies arising from the different length of the aligned protein sequences. The conversion of protein ACC values into binary descriptor fingerprints allows similarity search and classification. The algorithm described in the present study was implemented in a specially designed Web site, named AllergenFP (FP stands for FingerPrint). AllergenFP is written in Python, with GIU in HTML. It is freely accessible at http://ddg-pharmfac.net/Allergen FP. idoytchinova@pharmfac.net or ivanbangov@shu-bg.net.

  3. Lewis Structures Are Models for Predicting Molecular Structure, Not Electronic Structure

    NASA Astrophysics Data System (ADS)

    Purser, Gordon H.

    1999-07-01

    This article argues against a close relationship between Lewis dot structures and electron structure obtained from quantum mechanical calculations. Lewis structures are a powerful tool for structure prediction, though they are classical models of bonding and do not predict electronic structure. The "best" Lewis structures are those that, when combined with the VSEPR model, allow the accurate prediction of molecular properties, such as polarity, bond length, bond angle, and bond strength. These structures are achieved by minimizing formal charges within the molecule, even if it requires an expanded octet on atoms beyond the second period. Lewis structures that show an expanded octet do not imply full d-orbital involvement in the bonding. They suggest that the presence of low-lying d-orbitals is important in producing observed molecular structures. Based on this work, the presence of electron density, not a large separation in charge, is responsible for the short bond lengths and large angles in species containing nonmetal atoms from beyond the second period. This result contradicts results obtained from natural population analysis, a method that attempts to derive Lewis structures from molecular orbital calculations.

  4. Design, synthesis, crystal structure, insecticidal activity, molecular docking, and QSAR studies of novel N3-substituted imidacloprid derivatives.

    PubMed

    Wang, Mei-Juan; Zhao, Xiao-Bo; Wu, Dan; Liu, Ying-Qian; Zhang, Yan; Nan, Xiang; Liu, Huanxiang; Yu, Hai-Tao; Hu, Guan-Fang; Yan, Li-Ting

    2014-06-18

    Three novel series of N3-substituted imidacloprid derivatives were designed and synthesized, and their structures were identified on the basis of satisfactory analytical and spectral ((1)H NMR, (13)C NMR, MS, elemental analysis, and X-ray) data. Preliminary bioassays indicated that all of the derivatives exhibited significant insecticidal activities against Aphis craccivora, with LC50 values ranging from 0.00895 to 0.49947 mmol/L, and the insecticidal activities of some of them were comparable to those of the control imidacloprid. Some key structural features related to their insecticidal activities were identified, and the binding modes between target compounds and nAChR model were also further explored by molecular docking. By comparing the interaction features of imidacloprid and compound 26 with highest insecticidal activity, the origin of the high insecticidal activity of compound 26 was identified. On the basis of the conformations generated by molecular docking, a satisfactory 2D-QSAR model with six selected descriptors was built using genetic algorithm-multiple linear regression (GA-MLR) method. The analysis of the built model showed the molecular size, shape, and the ability to form hydrogen bond were important for insecticidal potency. The information obtained in the study will be very helpful for the design of new derivatives with high insecticidal activities.

  5. Replenishing data descriptors in a DMA injection FIFO buffer

    DOEpatents

    Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Cernohous, Bob R [Rochester, MN; Heidelberger, Philip [Cortlandt Manor, NY; Kumar, Sameer [White Plains, NY; Parker, Jeffrey J [Rochester, MN

    2011-10-11

    Methods, apparatus, and products are disclosed for replenishing data descriptors in a Direct Memory Access (`DMA`) injection first-in-first-out (`FIFO`) buffer that include: determining, by a messaging module on an origin compute node, whether a number of data descriptors in a DMA injection FIFO buffer exceeds a predetermined threshold, each data descriptor specifying an application message for transmission to a target compute node; queuing, by the messaging module, a plurality of new data descriptors in a pending descriptor queue if the number of the data descriptors in the DMA injection FIFO buffer exceeds the predetermined threshold; establishing, by the messaging module, interrupt criteria that specify when to replenish the injection FIFO buffer with the plurality of new data descriptors in the pending descriptor queue; and injecting, by the messaging module, the plurality of new data descriptors into the injection FIFO buffer in dependence upon the interrupt criteria.

  6. Performance comparison of partial least squares-related variable selection methods for quantitative structure retention relationships modelling of retention times in reversed-phase liquid chromatography.

    PubMed

    Talebi, Mohammad; Schuster, Georg; Shellie, Robert A; Szucs, Roman; Haddad, Paul R

    2015-12-11

    The relative performance of six multivariate data analysis methods derived from or combined with partial least squares (PLS) has been compared in the context of quantitative structure-retention relationships (QSRR). These methods include, GA (genetic algorithm)-PLS, Monte Carlo uninformative variable elimination (MC-UVE), competitive adaptive reweighted sampling (CARS), iteratively retaining informative variables (IRIV), variable iterative space shrinkage approach (VISSA) and PLS with automated backward selection of predictors (autoPLS). A set of 825 molecular descriptors was computed for 86 suspected sports doping compounds and used for predicting their gradient retention times in reversed-phase liquid chromatography (RPLC). The correlation between molecular descriptors selected by each technique and the retention time was established using the PLS method. All models derived from a selected subset of descriptors outperformed the reference PLS model derived from all descriptors, with very small demands of computational time and effort. A performance comparison indicated great diversity of these methods in selecting the most relevant molecular descriptors, ranging from 28 for CARS to 263 for MC-UVE. While VISSA provided the lowest degree of over-fitting for the training set, CARS demonstrated the best compromise between the prediction accuracy and the number of selected descriptors, with the prediction error of as low as 46s for the external test set. Only ten descriptors were found to be common for all models, with the characteristics of these descriptors being representative of the retention mechanism in RPLC.

  7. Mammographic images segmentation using texture descriptors.

    PubMed

    Mascaro, Angelica A; Mello, Carlos A B; Santos, Wellington P; Cavalcanti, George D C

    2009-01-01

    Tissue classification in mammography can help the diagnosis of breast cancer by separating healthy tissue from lesions. We present herein the use of three texture descriptors for breast tissue segmentation purposes: the Sum Histogram, the Gray Level Co-Occurrence Matrix (GLCM) and the Local Binary Pattern (LBP). A modification of the LBP is also proposed for a better distinction of the tissues. In order to segment the image into its tissues, these descriptors are compared using a fidelity index and two clustering algorithms: k-Means and SOM (Self-Organizing Maps).

  8. Dual-tree complex wavelet transform applied on color descriptors for remote-sensed images retrieval

    NASA Astrophysics Data System (ADS)

    Sebai, Houria; Kourgli, Assia; Serir, Amina

    2015-01-01

    This paper highlights color component features that improve high-resolution satellite (HRS) images retrieval. Color component correlation across image lines and columns is used to define a revised color space. It is designed to simultaneously take both color and neighborhood information. From this space, color descriptors, namely rotation invariant uniform local binary pattern, histogram of gradient, and a modified version of local variance are derived through dual-tree complex wavelet transform (DT-CWT). A new color descriptor called smoothed local variance (SLV) using an edge-preserving smoothing filter is introduced. It is intended to offer an efficient way to represent texture/structure information using an invariant to rotation descriptor. This descriptor takes advantage of DT-CWT representation to enhance the retrieval performance of HRS images. We report an evaluation of the SLV descriptor associated with the new color space using different similarity distances in our content-based image retrieval scheme. We also perform comparison with some standard features. Experimental results show that SLV descriptor allied to DT-CWT representation outperforms the other approaches.

  9. Histogram of oriented phase (HOP): a new descriptor based on phase congruency

    NASA Astrophysics Data System (ADS)

    Ragb, Hussin K.; Asari, Vijayan K.

    2016-05-01

    In this paper we present a low level image descriptor called Histogram of Oriented Phase based on phase congruency concept and the Principal Component Analysis (PCA). Since the phase of the signal conveys more information regarding signal structure than the magnitude, the proposed descriptor can precisely identify and localize image features over the gradient based techniques, especially in the regions affected by illumination changes. The proposed features can be formed by extracting the phase congruency information for each pixel in the image with respect to its neighborhood. Histograms of the phase congruency values of the local regions in the image are computed with respect to its orientation. These histograms are concatenated to construct the Histogram of Oriented Phase (HOP) features. The dimensionality of HOP features is reduced using PCA algorithm to form HOP-PCA descriptor. The dimensionless quantity of the phase congruency leads the HOP-PCA descriptor to be more robust to the image scale variations as well as contrast and illumination changes. Several experiments were performed using INRIA and DaimlerChrysler datasets to evaluate the performance of the HOP-PCA descriptor. The experimental results show that the proposed descriptor has better detection performance and less error rates than a set of the state of the art feature extraction methodologies.

  10. Molecular properties of psychopharmacological drugs determining non-competitive inhibition of 5-HT3A receptors.

    PubMed

    Kornhuber, Johannes; Terfloth, Lothar; Bleich, Stefan; Wiltfang, Jens; Rupprecht, Rainer

    2009-06-01

    We developed a structure-property-activity relationship (SPAR)-model for psychopharmacological drugs acting as non-competitive 5-HT(3A) receptor antagonists by using a decision-tree learner provided by the RapidMiner machine learning tool. A single molecular descriptor, namely the molecular dipole moment per molecular weight (mu/MW), predicts whether or not a substance non-competitively antagonizes 5-HT-induced Na(+) currents. A low mu/MW is compatible with drug-cumulation in apolar lipid rafts. This study confirms that size-intensive descriptors allow the development of compact SPAR models.

  11. Modifications of the chemical structure of phenolics differentially affect physiological activities in pulvinar cells of Mimosa pudica L. II. Influence of various molecular properties in relation to membrane transport.

    PubMed

    Rocher, Françoise; Roblin, Gabriel; Chollet, Jean-François

    2017-03-01

    Early prediction of compound absorption by cells is of considerable importance in the building of an integrated scheme describing the impact of a compound on intracellular biological processes. In this scope, we study the structure-activity relationships of several benzoic acid-related phenolics which are involved in many plant biological phenomena (growth, flowering, allelopathy, defense processes). Using the partial least squares (PLS) regression method, the impact of molecular descriptors that have been shown to play an important role concerning the uptake of pharmacologically active compounds by animal cells was analyzed in terms of the modification of membrane potential, variations in proton flux, and inhibition of the osmocontractile reaction of pulvinar cells of Mimosa pudica leaves. The hydrogen bond donors (HBD) and hydrogen bond acceptors (HBA), polar surface area (PSA), halogen ratio (Hal ratio), number of rotatable bonds (FRB), molar volume (MV), molecular weight (MW), and molar refractivity (MR) were considered in addition to two physicochemical properties (logD and the amount of non-dissociated form in relation to pKa). HBD + HBA and PSA predominantly impacted the three biological processes compared to the other descriptors. The coefficient of determination in the quantitative structure-activity relationship (QSAR) models indicated that a major part of the observed seismonasty inhibition and proton flux modification can be explained by the impact of these descriptors, whereas this was not the case for membrane potential variations. These results indicate that the transmembrane transport of the compounds is a predominant component. An increasing number of implicated descriptors as the biological processes become more complex may reflect their impacts on an increasing number of sites in the cell. The determination of the most efficient effectors may lead to a practical use to improve drugs in the control of microbial attacks on plants.

  12. Structures of High Density Molecular Fluids

    SciTech Connect

    Baer, B; Cynn, H; Iota, V; Yoo, C-S

    2002-02-01

    The goal of this proposal is to develop an in-situ probe for high density molecular fluids. We will, therefore, use Coherent Anti-Stokes Raman Spectroscopy (CARS) applied to laser heated samples in a diamond-anvil cell (DAC) to investigate molecular fluids at simultaneous conditions of high temperatures (T > 2000K) and high pressures (P > 10 GPa.) Temperatures sufficient to populate vibrational levels above the ground state will allow the vibrational potential to be mapped by CARS. A system capable of heating and probing these samples will be constructed. Furthermore, the techniques that enable a sample to be sufficiently heated and probed while held at static high pressure in a diamond-anvil-cell will be developed. This will be an in-situ investigation of simple molecules under conditions relevant to the study of detonation chemistry and the Jovain planet interiors using state of the art non-linear spectroscopy, diamond-anvil-cells, and laser heating technology.

  13. Usefulness of descriptors in phenotyping germplasm collections

    USDA-ARS?s Scientific Manuscript database

    A large number of crop germplasm collections are maintained within the U.S. National Plant Germplasm System (NPGS). For each of these crop collections, Crop Germplasm committees (CGC), crop curators, and collection staff have established extensive lists of descriptors or phenotypic traits by which t...

  14. Colour Chemistry, Part I, Principles, Colour, and Molecular Structure

    ERIC Educational Resources Information Center

    Hallas, G.

    1975-01-01

    Discusses various topics in color chemistry, including the electromagnetic spectrum, the absorption and reflection of light, additive and subtractive color mixing, and the molecular structure of simple colored substances. (MLH)

  15. Colour Chemistry, Part I, Principles, Colour, and Molecular Structure

    ERIC Educational Resources Information Center

    Hallas, G.

    1975-01-01

    Discusses various topics in color chemistry, including the electromagnetic spectrum, the absorption and reflection of light, additive and subtractive color mixing, and the molecular structure of simple colored substances. (MLH)

  16. Sculpting Molecular Potentials to Design Optimized Materials: The Inverse Design of New Molecular Structures

    DTIC Science & Technology

    2010-05-10

    REPORT Final Report on " Sculpting Molecular Potentials to Design Optimized Materials: The Inverse Design of New Molecular Structures" (Agreement...Beratan, Weitao Yang, Michael J. Therien, Koen Clays Duke University Office of Research Support Duke University Durham, NC 27705 - REPORT...Prescribed by ANSI Std. Z39.18 - 31-Jul-2009 Final Report on " Sculpting Molecular Potentials to Design Optimized Materials: The Inverse Design of New

  17. Retention prediction of low molecular weight anions in ion chromatography based on quantitative structure-retention relationships applied to the linear solvent strength model.

    PubMed

    Park, Soo Hyun; Haddad, Paul R; Talebi, Mohammad; Tyteca, Eva; Amos, Ruth I J; Szucs, Roman; Dolan, John W; Pohl, Christopher A

    2017-02-24

    Quantitative Structure-Retention Relationships (QSRRs) represent a popular technique to predict the retention times of analytes, based on molecular descriptors encoding the chemical structures of the analytes. The linear solvent strength (LSS) model relating the retention factor, k to the eluent concentration (log k=a-blog [eluent]), is a well-known and accurate retention model in ion chromatography (IC). In this work, QSRRs for inorganic and small organic anions were used to predict the regression parameters a and b in the LSS model (and hence retention times) for these analytes under a wide range of eluent conditions, based solely on their chemical structures. This approach was performed on retention data of inorganic and small organic anions from the "Virtual Column" software (Thermo Fisher Scientific). These retention data were recalibrated via a "porting" methodology on three columns (AS20, AS19, and AS11HC), prior to the QSRR modeling. This provided retention data more applicable on recently produced columns which may exhibit changes of column behavior due to batch-to-batch variability. Molecular descriptors for the analytes were calculated with Dragon software using the geometry-optimized molecular structures, employing the AM1 semi-empirical method. An optimal subset of molecular descriptors was then selected using an evolutionary algorithm (EA). Finally, the QSRR models were generated by multiple linear regression (MLR). As a result, six QSRR models with good predictive performance were successfully derived for a- and b-values on three columns (R(2)>0.98 and RMSE<0.11). External validation showed the possibility of using the developed QSRR models as predictive tools in IC (Qext(F3)(2)>0.7 and RMSEP<0.4). Moreover, it was demonstrated that the obtained QSRR models for the a- and b-values can predict the retention times for new analytes with good accuracy and predictability (R(2) of 0.98, RMSE of 0.89min, Qext(F3)(2) of 0.96 and RMSEP of 1.18min).

  18. Molecular structure of the lecithin ripple phase.

    PubMed

    de Vries, Alex H; Yefimov, Serge; Mark, Alan E; Marrink, Siewert J

    2005-04-12

    Molecular dynamics simulations of lecithin lipid bilayers in water as they are cooled from the liquid crystalline phase show the spontaneous formation of rippled bilayers. The ripple consists of two domains of different length and orientation, connected by a kink. The organization of the lipids in one domain of the ripple is found to be that of a splayed gel; in the other domain the lipids are gel-like and fully interdigitated. In the concave part of the kink region between the domains the lipids are disordered. The results are consistent with the experimental information available and provide an atomic-level model that may be tested by further experiments.

  19. Molecular structure of the lecithin ripple phase

    PubMed Central

    de Vries, Alex H.; Yefimov, Serge; Mark, Alan E.; Marrink, Siewert J.

    2005-01-01

    Molecular dynamics simulations of lecithin lipid bilayers in water as they are cooled from the liquid crystalline phase show the spontaneous formation of rippled bilayers. The ripple consists of two domains of different length and orientation, connected by a kink. The organization of the lipids in one domain of the ripple is found to be that of a splayed gel; in the other domain the lipids are gel-like and fully interdigitated. In the concave part of the kink region between the domains the lipids are disordered. The results are consistent with the experimental information available and provide an atomic-level model that may be tested by further experiments. PMID:15809443

  20. Molecular moment similarity between several nucleoside analogs of thymidine and thymidine. sil@watson.ibm.com.

    PubMed

    Silverman, B D; Pitman, M C; Platt, D E

    1999-06-01

    Molecular moment descriptors of the shape and charge distributions of twenty five nucleoside structures have been examined. The structures include thymidine as well as the difluorotoluene nucleoside analog which has been found to pair efficiently with adenine by polymerase catalysis. The remaining twenty three structures have been chosen to be as structurally similar to thymidine and to the difluorotoluene nucleoside analog as possible. The moment descriptors which include a description of the relationship of molecular charge to shape show the difluorotoluene nucleoside to be one of the most proximate molecules to thymidine in the space of the molecular moments. The calculations, therefore, suggest that polymerase specificity might be not only a consequence of molecular steric features alone but also of the molecular electrostatic environment and its registration with molecular shape.

  1. Instructional Approach to Molecular Electronic Structure Theory

    ERIC Educational Resources Information Center

    Dykstra, Clifford E.; Schaefer, Henry F.

    1977-01-01

    Describes a graduate quantum mechanics projects in which students write a computer program that performs ab initio calculations on the electronic structure of a simple molecule. Theoretical potential energy curves are produced. (MLH)

  2. Beyond Rotatable Bond Counts: Capturing 3D Conformational Flexibility in a Single Descriptor

    PubMed Central

    2016-01-01

    A new molecular descriptor, nConf20, based on chemical connectivity, is presented which captures the accessible conformational space of a molecule. Currently the best available two-dimensional descriptors for quantifying the flexibility of a particular molecule are the rotatable bond count (RBC) and the Kier flexibility index. We present a descriptor which captures this information by sampling the conformational space of a molecule using the RDKit conformer generator. Flexibility has previously been identified as a key feature in determining whether a molecule is likely to crystallize or not. For this application, nConf20 significantly outperforms previously reported single-variable classifiers and also assists rule-based analysis of black-box machine learning classification algorithms. PMID:28024401

  3. Beyond Rotatable Bond Counts: Capturing 3D Conformational Flexibility in a Single Descriptor.

    PubMed

    Wicker, Jerome G P; Cooper, Richard I

    2016-12-27

    A new molecular descriptor, nConf20, based on chemical connectivity, is presented which captures the accessible conformational space of a molecule. Currently the best available two-dimensional descriptors for quantifying the flexibility of a particular molecule are the rotatable bond count (RBC) and the Kier flexibility index. We present a descriptor which captures this information by sampling the conformational space of a molecule using the RDKit conformer generator. Flexibility has previously been identified as a key feature in determining whether a molecule is likely to crystallize or not. For this application, nConf20 significantly outperforms previously reported single-variable classifiers and also assists rule-based analysis of black-box machine learning classification algorithms.

  4. Hygrothermal aging effects on buried molecular structures at epoxy interfaces.

    PubMed

    Myers, John N; Zhang, Chi; Lee, Kang-Wook; Williamson, Jaimal; Chen, Zhan

    2014-01-14

    Interfacial properties such as adhesion are determined by interfacial molecular structures. Adhesive interfaces in microelectronic packages that include organic polymers such as epoxy are susceptible to delamination during accelerated stress testing. Infrared-visible sum frequency generation vibrational spectroscopy (SFG) and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) were used to study molecular structures at buried epoxy interfaces during hygrothermal aging to relate molecular structural changes at buried interfaces to decreases in macroscopic adhesion strength. SFG peaks associated with strongly hydrogen bonded water were detected at hydrophilic epoxy interfaces. Ordered interfacial water was also correlated to large decreases in interfacial adhesion strength that occurred as a result of hygrothermal aging, which suggests that water diffused to the interface and replaced original hydrogen bond networks. No water peaks were observed at hydrophobic epoxy interfaces, which was correlated with a much smaller decrease in adhesion strength from the same aging process. ATR-FTIR water signals observed in the epoxy bulk were mainly contributed by relatively weakly hydrogen bonded water molecules, which suggests that the bulk and interfacial water structure was different. Changes in interfacial methyl structures were observed regardless of the interfacial hydrophobicity which could be due to water acting as a plasticizer that restructured both the bulk and interfacial molecular structure. This research demonstrates that SFG studies of molecular structural changes at buried epoxy interfaces during hygrothermal aging can contribute to the understanding of moisture-induced failure mechanisms in electronic packages that contain organic adhesives.

  5. Quantitative structure-activity relationship and molecular docking studies of a series of quinazolinonyl analogues as inhibitors of gamma amino butyric acid aminotransferase.

    PubMed

    Abdulfatai, Usman; Uzairu, Adamu; Uba, Sani

    2017-01-01

    Quantitative structure-activity relationship and molecular docking studies were carried out on a series of quinazolinonyl analogues as anticonvulsant inhibitors. Density Functional Theory (DFT) quantum chemical calculation method was used to find the optimized geometry of the anticonvulsants inhibitors. Four types of molecular descriptors were used to derive a quantitative relation between anticonvulsant activity and structural properties. The relevant molecular descriptors were selected by Genetic Function Algorithm (GFA). The best model was validated and found to be statistically significant with squared correlation coefficient (R(2)) of 0.934, adjusted squared correlation coefficient (R(2)adj) value of 0.912, Leave one out (LOO) cross validation coefficient (Q(2)) value of 0.8695 and the external validation (R(2)pred) of 0.72. Docking analysis revealed that the best compound with the docking scores of -9.5 kcal/mol formed hydrophobic interaction and H-bonding with amino acid residues of gamma aminobutyric acid aminotransferase (GABAAT). This research has shown that the binding affinity generated was found to be better than the commercially sold anti-epilepsy drug, vigabatrin. Also, it was found to be better than the one reported by other researcher. Our QSAR model and molecular docking results corroborate with each other and propose the directions for the design of new inhibitors with better activity against GABAAT. The present study will help in rational drug design and synthesis of new selective GABAAT inhibitors with predetermined affinity and activity and provides valuable information for the understanding of interactions between GABAAT and the anticonvulsants inhibitors.

  6. Prediction of soil sorption coefficients using model molecular structures for organic matter and the quantum mechanical COSMO-SAC model.

    PubMed

    Phillips, Kathy L; Di Toro, Dominic M; Sandler, Stanley I

    2011-02-01

    The soil sorption coefficient, K(OC), is an important property affecting the environmental fate of organic molecules. Difficulties associated with measuring K(OC) have led to many attempts to predict this property, but most rely on empirical descriptors for the soil phase determined from correlations with measured K(OC) data, and are thereby limited by the data quality and diversity. A new method is presented to predict K(OC) for nonionic organic compounds that requires only molecular structures. No calibration is performed. Using model humic acid (HA) and fulvic acid (FA) molecular structures from the literature, the soil organic matter is modeled as an organic solvent composed of HA or FA molecules. K(OC) is predicted as an organic solvent-water partition coefficient using the quantum mechanics-based model COSMO-SAC. The log K(OC) values for a set of 440 diverse, environmentally relevant chemicals are predicted with a root-mean-square error of 0.84-1.08, depending on which model HA or FA is used.

  7. DFT analysis on the molecular structure, vibrational and electronic spectra of 2-(cyclohexylamino)ethanesulfonic acid

    NASA Astrophysics Data System (ADS)

    Renuga Devi, T. S.; Sharmi kumar, J.; Ramkumaar, G. R.

    2015-02-01

    The FTIR and FT-Raman spectra of 2-(cyclohexylamino)ethanesulfonic acid were recorded in the regions 4000-400 cm-1 and 4000-50 cm-1 respectively. The structural and spectroscopic data of the molecule in the ground state were calculated using Hartee-Fock and Density functional method (B3LYP) with the correlation consistent-polarized valence double zeta (cc-pVDZ) basis set and 6-311++G(d,p) basis set. The most stable conformer was optimized and the structural and vibrational parameters were determined based on this. The complete assignments were performed based on the Potential Energy Distribution (PED) of the vibrational modes, calculated using Vibrational Energy Distribution Analysis (VEDA) 4 program. With the observed FTIR and FT-Raman data, a complete vibrational assignment and analysis of the fundamental modes of the compound were carried out. Thermodynamic properties and Atomic charges were calculated using both Hartee-Fock and density functional method using the cc-pVDZ basis set and compared. The calculated HOMO-LUMO energy gap revealed that charge transfer occurs within the molecule. 1H and 13C NMR chemical shifts of the molecule were calculated using Gauge Including Atomic Orbital (GIAO) method and were compared with experimental results. Stability of the molecule arising from hyperconjugative interactions, charge delocalization have been analyzed using Natural Bond Orbital (NBO) analysis. The first order hyperpolarizability (β) and Molecular Electrostatic Potential (MEP) of the molecule was computed using DFT calculations. The electron density based local reactivity descriptor such as Fukui functions were calculated to explain the chemical reactivity site in the molecule.

  8. DFT analysis on the molecular structure, vibrational and electronic spectra of 2-(cyclohexylamino)ethanesulfonic acid.

    PubMed

    Renuga Devi, T S; Sharmi kumar, J; Ramkumaar, G R

    2015-02-25

    The FTIR and FT-Raman spectra of 2-(cyclohexylamino)ethanesulfonic acid were recorded in the regions 4000-400 cm(-1) and 4000-50 cm(-1) respectively. The structural and spectroscopic data of the molecule in the ground state were calculated using Hartee-Fock and Density functional method (B3LYP) with the correlation consistent-polarized valence double zeta (cc-pVDZ) basis set and 6-311++G(d,p) basis set. The most stable conformer was optimized and the structural and vibrational parameters were determined based on this. The complete assignments were performed based on the Potential Energy Distribution (PED) of the vibrational modes, calculated using Vibrational Energy Distribution Analysis (VEDA) 4 program. With the observed FTIR and FT-Raman data, a complete vibrational assignment and analysis of the fundamental modes of the compound were carried out. Thermodynamic properties and Atomic charges were calculated using both Hartee-Fock and density functional method using the cc-pVDZ basis set and compared. The calculated HOMO-LUMO energy gap revealed that charge transfer occurs within the molecule. (1)H and (13)C NMR chemical shifts of the molecule were calculated using Gauge Including Atomic Orbital (GIAO) method and were compared with experimental results. Stability of the molecule arising from hyperconjugative interactions, charge delocalization have been analyzed using Natural Bond Orbital (NBO) analysis. The first order hyperpolarizability (β) and Molecular Electrostatic Potential (MEP) of the molecule was computed using DFT calculations. The electron density based local reactivity descriptor such as Fukui functions were calculated to explain the chemical reactivity site in the molecule.

  9. Externally predictive single-descriptor based QSPRs for physico-chemical properties of polychlorinated-naphthalenes: Exploring relationships of logS(W), logK(OA), and logK(OW) with electron-correlation.

    PubMed

    Chayawan; Vikas

    2015-10-15

    Quantitative structure-property relationships (QSPRs), based only on a single-parameter, are proposed for the prediction of physico-chemical properties, namely, aqueous solubility (logSW), octanol-water partition coefficient (logKOW) and octanol-air partition coefficient (logKOA) of polychloronaphthalenes (PCNs) including all the 75 chloronaphthalene congeners. The QSPR models are developed using molecular descriptors computed through quantum mechanical methods including ab-initio as well as advanced semi-empirical methods. The predictivity of the developed models is tested through state-of-the-art external validation procedures employing an external prediction set of compounds. To analyse the role of instantaneous interactions between electrons (the electron-correlation), the models are also compared with those developed using only the electron-correlation contribution of the quantum chemical descriptor. The electron-correlation contribution towards the chemical hardness and the LUMO energy are observed to be the best predictors for octanol-water partition coefficient, whereas for the octanol-air partition coefficient, the total electronic energy and electron-correlation energy are found to be reliable descriptors, in fact, even better than the polarisability. For aqueous solubility of PCNs, the absolute electronegativity is observed to be the best predictor. This work suggests that the electron-correlation contribution of a quantum-chemical descriptor can be used as a reliable indicator for physico-chemical properties, particularly the partition coefficients.

  10. Structure-retention behaviour of biologically active fused 1,2,4-triazinones--correlation with in silico molecular properties.

    PubMed

    Sztanke, Małgorzata; Tuzimski, Tomasz; Janicka, Małgorzata; Sztanke, Krzysztof

    2015-02-20

    The chromatographic behaviour and significant lipophilicity/hydrophobicity indices (log k(w), S, φ(0)) are presented for 21 biologically active fused 1,2,4-triazinones based on the linear relationship: log k = log k(w)-Sφ established for the retention on LC-18 HPLC column, using as mobile phases mixtures of three organic modifiers with water. The effect of these mobile phase modifiers on the chromatographic behaviour of solutes was established and the organic modifier of choice is suggested. The complex correlation of slopes versus intercepts obtained for acetonitrile, contrary to linear ones obtained for methanol and dioxane are disclosed. The observed difference in retention mechanism for acetonitrile compared to methanol and dioxane is explained by intermolecular interactions encoded in lipophilicity. Linear correlations with statistically significant levels between log kw values determined from three different chromatographic systems were obtained. The relationships between log k(w) constants (derived from the linear model for methanol-water mobile phases) and predicted log P and log S values by the use of various computational methods were investigated and these were established with high correlation coefficients. The predicted log P values plotted against φ(0 (MeOH)) indices showed the best fit. Principal component analysis was used to compare various lipophilicity parameters of the solutes and their in silico biological descriptors relevant to optimal pharmacokinetics profile. The similarities and dissimilarities between all the variables and molecular structures of solutes are presented. Statistically significant correlations were found between the chromatographic lipophilicity indices and the calculated pharmacokinetic descriptors: fraction unbound in brain (f(u, brain)), oral bioavailability (%F), permeability and intestinal absorption in jejunum (Caco-2), skin permeation (log K(p)) and blood/brain concentration (log BB). Copyright © 2014 Elsevier B

  11. Quantum-chemistry descriptors for photosensitizers based on macrocycles.

    PubMed

    Bettanin, Fernanda; Antonio, Felipe C T; Honorio, Kathia M; Homem-de-Mello, Paula

    2017-02-01

    Phthalocyanines, porphyrins, and chlorins have been widely studied as photosensitizers. Both experimental and computational strategies are employed in order to propose new and more active molecules derived from those macrocycles. In this context, there are two main strategies used: (i) the addition of different substituents and (ii) the complexation of the macrocycle with different metallic ions. In this work, we present selected descriptors based on quantum chemistry calculations for forty macrocycles, including some approved drugs. We have found that density functional theory is a suitable methodology to study the large sets of molecules when applying the B3LYP/LanL2DZ methodology for geometry optimization and TD-OLYP/6-31G(d) for absorption spectrum. The inclusion of solvent effects by means of continuum model is important in order to obtain the accurate electronic data. We have verified that by bonding charged or polar substituents to the macrocycle, it is possible to enhance water solvation as well as to improve spectroscopic properties because molecular orbital contributions for Q band can be affected by some substituents. Selected descriptors, electronic and steric, were pointed out as important to propose the new photosensitizers. © 2017 John Wiley & Sons A/S.

  12. Quantitative structure-activity relationships and comparative molecular field analysis of TIBO derivatised HIV-1 reverse transcriptase inhibitors

    NASA Astrophysics Data System (ADS)

    Hannongbua, Supa; Pungpo, Pornpan; Limtrakul, Jumras; Wolschann, Peter

    1999-11-01

    Quantitative structure-activity relationships (QSAR) and Comparative Molecular Field Analysis (CoMFA) have been applied in order to explain the structural requirements of HIV-1 reverse transcriptase (HIV-1 RT) inhibitory activity of TIBO derivatives on the MT-4 cells. The best QSAR model is satisfactory in both statistical significance and predictive ability. The derived structural descriptors indicate the importance of electronic contributions toward the HIV-1 RT inhibition of this class of compounds. However, it could not reveal any hydrophobic influence because of high collinearity between C2 and log P variables. In order to cope with steric interaction in the correlation, 3D-QSAR was performed using CoMFA. The obtained CoMFA model shows high predictive ability, r2 cv=0.771, and clearly demonstrates its potential in the steric feature of the molecules through contour maps, explaining a majority (81.8%) of the variance in the data. Consequently, these results can be useful in identifying the structural requirements of TIBO derivatives and helpful for better understanding the HIV-1 RT inhibition. Eventually, they provide a beneficial basis to design new and more potent inhibitors of HIV-1 RT.

  13. State-Space Stabilizing Controllers for Descriptor Systems

    NASA Astrophysics Data System (ADS)

    Inoue, Masaki; Wada, Teruyo; Ikeda, Masao; Uezato, Eiho

    This paper considers stabilization of linear time-invariant descriptor systems by dynamic output feedback controllers. We deal with general descriptor systems including those being irregular or impulsive, and derive state-space stabilizing controllers. On the derivation process of the state-space controllers, we first consider descriptor-type controllers. We present a necessary and sufficient condition for the existence of a descriptor-type controller which makes the closed-loop descriptor system regular, impulse-free, and stable. The condition is expressed in terms of linear matrix inequalities (LMIs), and we show that coefficient matrices of any descriptor-type stabilizing controller of the same size as the given descriptor system can be represented by the solution of the LMIs. Then, we present a necessary and sufficient condition for the descriptor-type controller to be transformable to an input-output equivalent state-space controller with the dimension of the dynamic order (the rank of the coefficient matrix for the time-derivative of the descriptor variable) of the given descriptor system, that is, a state-space stabilizing controller. The transformability condition is mild and almost always satisfied by the obtained descriptor-type controller. Furthermore, even if the transformability condition is not satisfied, a slightly modified solution of the LMIs, which always exists, gives a descriptor-type controller being transformable to a state-space controller. The transformation is carried out analytically, thus the coefficient matrices of any such state-space stabilizing controller can be expressed by the solution of the LMIs. We also reveal that if we restrict the classes of descriptor systems or descriptor-type controllers such that their transfer functions are strictly proper, the descriptor-type controllers obtained by the LMI condition are always transformable to state-space controllers.

  14. Marine Toxins Origin, Structure, and Molecular Pharmacology

    DTIC Science & Technology

    1990-01-01

    thin-layer chromatography (TLC) were instrumental in the initial isolation and purification processes. Mass spectrometry (MS), infrared spectroscopy ...Frederick, MD 21701-5011 Methods of detection, metabolism, and pathophysiology of the brevetoxins, PbTx-2 and PbTx-3, are summarized. Infrared spectros...1R), circular dichroism (CD), nuclear magnetic resonance spectroscopy (NMR), and X-ray crystal- lography all played important roles in structure

  15. Molecular Eigensolution Symmetry Analysis and Fine Structure

    PubMed Central

    Harter, William G.; Mitchell, Justin C.

    2013-01-01

    Spectra of high-symmetry molecules contain fine and superfine level cluster structure related to J-tunneling between hills and valleys on rovibronic energy surfaces (RES). Such graphic visualizations help disentangle multi-level dynamics, selection rules, and state mixing effects including widespread violation of nuclear spin symmetry species. A review of RES analysis compares it to that of potential energy surfaces (PES) used in Born–Oppenheimer approximations. Both take advantage of adiabatic coupling in order to visualize Hamiltonian eigensolutions. RES of symmetric and D2 asymmetric top rank-2-tensor Hamiltonians are compared with Oh spherical top rank-4-tensor fine-structure clusters of 6-fold and 8-fold tunneling multiplets. Then extreme 12-fold and 24-fold multiplets are analyzed by RES plots of higher rank tensor Hamiltonians. Such extreme clustering is rare in fundamental bands but prevalent in hot bands, and analysis of its superfine structure requires more efficient labeling and a more powerful group theory. This is introduced using elementary examples involving two groups of order-6 (C6 and D3~C3v), then applied to families of Oh clusters in SF6 spectra and to extreme clusters. PMID:23344041

  16. Big Data of Materials Science: Critical Role of the Descriptor

    NASA Astrophysics Data System (ADS)

    Ghiringhelli, Luca M.; Vybiral, Jan; Levchenko, Sergey V.; Draxl, Claudia; Scheffler, Matthias

    2015-03-01

    Statistical learning of materials properties or functions so far starts with a largely silent, nonchallenged step: the choice of the set of descriptive parameters (termed descriptor). However, when the scientific connection between the descriptor and the actuating mechanisms is unclear, the causality of the learned descriptor-property relation is uncertain. Thus, a trustful prediction of new promising materials, identification of anomalies, and scientific advancement are doubtful. We analyze this issue and define requirements for a suitable descriptor. For a classic example, the energy difference of zinc blende or wurtzite and rocksalt semiconductors, we demonstrate how a meaningful descriptor can be found systematically.

  17. A modified descriptor for blob detection in nonlinear scale space

    NASA Astrophysics Data System (ADS)

    Zhao, Liangjin; Ding, Yan; Xu, Hong

    2017-01-01

    In this paper, we present a novel binary descriptor with orientation, which called Intensity-Centroid LDB (IC-LDB). This descriptor resolves the problems that the current non-binary descriptors are too compute-expensive to achieve real-time performance in the nonlinear scale space and that the original Local Difference Binary (LDB) descriptors do not have an orientation component to keep rotation invariant. Experimental results demonstrate that IC-LDB proposed in this paper was faster than previously non-binary descriptors which were used in nonlinear scale space, while performing as well in many situations.

  18. 3D descriptors calculation and conformational search to investigate potential bioactive conformations, with application in 3D-QSAR and virtual screening in drug design.

    PubMed

    da Silva, Carlos Henrique Tomich de Paula; Taft, Carlton Anthony

    2017-10-01

    The knowledge of the bioactive conformation for an active hit is relevant because of the easier interpretation and the general quality of the recognition models of protein and ligand. With the aim of investigating potential bioactive conformations without previous structural knowledge of the molecular target, we present herewith a 'protocol' that could be used which includes generation of low-energy conformations, calculations of tridimensional descriptors and investigation of structural similarity via principal component analysis. The protocol was used in the search for potential bioactive conformations. An initial selection of targets was made from a set of protein-ligand complexes with structure deposited in the Protein Data Bank, which was systematically filtered by lead-like rules, resulting in 45 ligands of 8 important therapeutic targets. After extensive optimization of the protocol and parameters of both OMEGA and Pentacle softwares, the best results were obtained for series of compounds such as the beta-trypsin and urokinase inhibitors, which are more structurally related among each other, inside the respective therapeutic class. Future improvements of the protocol, including a suitable choice and combination of robust 3D descriptors, could yield more reliable and less restrictive results, with general and diverse applications in drug design, in particular for improving the 3D-QSAR methodologies as well as virtual screening experiments for a more reliable selection of new lead compounds for different molecular targets.

  19. Feature Point Descriptors: Infrared and Visible Spectra

    PubMed Central

    Ricaurte, Pablo; Chilán, Carmen; Aguilera-Carrasco, Cristhian A.; Vintimilla, Boris X.; Sappa, Angel D.

    2014-01-01

    This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given. PMID:24566634

  20. Video Segmentation Descriptors for Event Recognition

    DTIC Science & Technology

    2014-12-08

    spatial sizes and motion intensities (2. k ). IV. VIDEO SEGMENTATION Various video segmentation techniques have been proposed based on superpixels [26...to cluster STTs according to color and motion through a meanshift [24] over- segmentation . The second pass iteratively fuses the yielded supertubes...video motion descriptor based on a multi-scale video segmentation to provide a multi- layered output as well as connections with the rich interactions

  1. Giant Molecular Cloud Structure and Evolution

    NASA Technical Reports Server (NTRS)

    Hollenbach, David (Technical Monitor); Bodenheimer, P. H.

    2003-01-01

    Bodenheimer and Burkert extended earlier calculations of cloud core models to study collapse and fragmentation. The initial condition for an SPH collapse calculation is the density distribution of a Bonnor-Ebert sphere, with near balance between turbulent plus thermal energy and gravitational energy. The main parameter is the turbulent Mach number. For each Mach number several runs are made, each with a different random realization of the initial turbulent velocity field. The turbulence decays on a dynamical time scale, leading the cloud into collapse. The collapse proceeds isothermally until the density has increased to about 10(exp 13) g cm(exp -3). Then heating is included in the dense regions. The nature of the fragmentation is investigated. About 15 different runs have been performed with Mach numbers ranging from 0.3 to 3.5 (the typical value observed in molecular cloud cores is 0.7). The results show a definite trend of increasing multiplicity with increasing Mach number (M), with the number of fragments approximately proportional to (1 + M). In general, this result agrees with that of Fisher, Klein, and McKee who published three cases with an AMR grid code. However our results show that there is a large spread about this curve. For example, for M=0.3 one case resulted in no fragmentation while a second produced three fragments. Thus it is not only the value of M but also the details of the superposition of the various velocity modes that play a critical role in the formation of binaries. Also, the simulations produce a wide range of separations (10-1000 AU) for the multiple systems, in rough agreement with observations. These results are discussed in two conference proceedings.

  2. Complementary molecular information changes our perception of food web structure.

    PubMed

    Wirta, Helena K; Hebert, Paul D N; Kaartinen, Riikka; Prosser, Sean W; Várkonyi, Gergely; Roslin, Tomas

    2014-02-04

    How networks of ecological interactions are structured has a major impact on their functioning. However, accurately resolving both the nodes of the webs and the links between them is fraught with difficulties. We ask whether the new resolution conferred by molecular information changes perceptions of network structure. To probe a network of antagonistic interactions in the High Arctic, we use two complementary sources of molecular data: parasitoid DNA sequenced from the tissues of their hosts and host DNA sequenced from the gut of adult parasitoids. The information added by molecular analysis radically changes the properties of interaction structure. Overall, three times as many interaction types were revealed by combining molecular information from parasitoids and hosts with rearing data, versus rearing data alone. At the species level, our results alter the perceived host specificity of parasitoids, the parasitoid load of host species, and the web-wide role of predators with a cryptic lifestyle. As the northernmost network of host-parasitoid interactions quantified, our data point exerts high leverage on global comparisons of food web structure. However, how we view its structure will depend on what information we use: compared with variation among networks quantified at other sites, the properties of our web vary as much or much more depending on the techniques used to reconstruct it. We thus urge ecologists to combine multiple pieces of evidence in assessing the structure of interaction webs, and suggest that current perceptions of interaction structure may be strongly affected by the methods used to construct them.

  3. Complementary molecular information changes our perception of food web structure

    PubMed Central

    Wirta, Helena K.; Hebert, Paul D. N.; Kaartinen, Riikka; Prosser, Sean W.; Várkonyi, Gergely; Roslin, Tomas

    2014-01-01

    How networks of ecological interactions are structured has a major impact on their functioning. However, accurately resolving both the nodes of the webs and the links between them is fraught with difficulties. We ask whether the new resolution conferred by molecular information changes perceptions of network structure. To probe a network of antagonistic interactions in the High Arctic, we use two complementary sources of molecular data: parasitoid DNA sequenced from the tissues of their hosts and host DNA sequenced from the gut of adult parasitoids. The information added by molecular analysis radically changes the properties of interaction structure. Overall, three times as many interaction types were revealed by combining molecular information from parasitoids and hosts with rearing data, versus rearing data alone. At the species level, our results alter the perceived host specificity of parasitoids, the parasitoid load of host species, and the web-wide role of predators with a cryptic lifestyle. As the northernmost network of host–parasitoid interactions quantified, our data point exerts high leverage on global comparisons of food web structure. However, how we view its structure will depend on what information we use: compared with variation among networks quantified at other sites, the properties of our web vary as much or much more depending on the techniques used to reconstruct it. We thus urge ecologists to combine multiple pieces of evidence in assessing the structure of interaction webs, and suggest that current perceptions of interaction structure may be strongly affected by the methods used to construct them. PMID:24449902

  4. Ionization probes of molecular structure and chemistry

    SciTech Connect

    Johnson, P.M.

    1993-12-01

    Various photoionization processes provide very sensitive probes for the detection and understanding of the spectra of molecules relevant to combustion processes. The detection of ionization can be selective by using resonant multiphoton ionization or by exploiting the fact that different molecules have different sets of ionization potentials. Therefore, the structure and dynamics of individual molecules can be studied even in a mixed sample. The authors are continuing to develop methods for the selective spectroscopic detection of molecules by ionization, and to use these methods for the study of some molecules of combustion interest.

  5. Syntheses and molecular structures of new cali.

    PubMed

    Attner, J; Radius, U

    2001-01-01

    An unusual disproportionation reaction of the molybdenum(IV) and tungsten(IV) chlorides [MCl4L2] (M=Mo, L=Et2S, Et2O; M=W; L= Et2S) in the presence of p-tBu-calix[4]arene (Cax(OH)4) and triethylamine leads to d0 complexes [(CaxO4)[CaxO2(OH)2]M] (1) and d3 compounds (HNEt3)2[(CaxO4)2M2] (2). Complexes la (M = Mo), 1b (M = W), and the HCl adduct of 2a (M = Mo) have been structurally characterized. Compound 1a represents one of the few examples of a well-characterized molybdenum(VI) hexa-alkoxide complex of the type [Mo(OR)6]. Isolation and structural characterization of the side product [(CaxO4W)[kappa2(O)-kappa1(O)-CaxO3(OH)](CaxO4WCl)] (3) suggests the intermediacy of chloro-containing calix[4]arene complexes in these reaction mixtures. The reaction of 1a with HCI provides [CaxO4MoCl2] (4a), the first well-defined example of a mixed molybdenum(VI) alkoxide halide compound of the general formula [MoClx(OR)6-x].

  6. Molecular Dynamics Simulations and Structural Analysis of Giardia duodenalis 14-3-3 Protein-Protein Interactions.

    PubMed

    Cau, Ylenia; Fiorillo, Annarita; Mori, Mattia; Ilari, Andrea; Botta, Maurizo; Lalle, Marco

    2015-12-28

    Giardiasis is a gastrointestinal diarrheal illness caused by the protozoan parasite Giardia duodenalis, which affects annually over 200 million people worldwide. The limited antigiardial drug arsenal and the emergence of clinical cases refractory to standard treatments dictate the need for new chemotherapeutics. The 14-3-3 family of regulatory proteins, extensively involved in protein-protein interactions (PPIs) with pSer/pThr clients, represents a highly promising target. Despite homology with human counterparts, the single 14-3-3 of G. duodenalis (g14-3-3) is characterized by a constitutive phosphorylation in a region critical for target binding, thus affecting the function and the conformation of g14-3-3/clients interaction. However, to approach the design of specific small molecule modulators of g14-3-3 PPIs, structural elucidations are required. Here, we present a detailed computational and crystallographic study exploring the implications of g14-3-3 phosphorylation on protein structure and target binding. Self-Guided Langevin Dynamics and classical molecular dynamics simulations show that phosphorylation affects locally and globally g14-3-3 conformation, inducing a structural rearrangement more suitable for target binding. Profitable features for g14-3-3/clients interaction were highlighted using a hydrophobicity-based descriptor to characterize g14-3-3 client peptides. Finally, the X-ray structure of g14-3-3 in complex with a mode-1 prototype phosphopeptide was solved and combined with structure-based simulations to identify molecular features relevant for clients binding to g14-3-3. The data presented herein provide a further and structural understanding of g14-3-3 features and set the basis for drug design studies.

  7. Microwave spectrum and molecular structure of PNO

    NASA Astrophysics Data System (ADS)

    Okabayashi, Toshiaki; Yamazaki, Emi; Tanimoto, Mitsutoshi

    1999-08-01

    The microwave spectra of P14N16O and its isotopomers P15N16O and P14N18O were observed in a dc glow discharge plasma of a mixture of nitric oxide and hydrogen gases over solid red phosphorus placed on the stainless steel electrode. Rotational transitions of the parent P14N16O species were measured in the ground state as well as in the vibrationally excited ν1 (PN str.), ν2 (bend), and 2ν2 states. The l=0 substate of the 2ν2 state interacts with the ν1 state through a Fermi resonance. The rotational constants determined for the ground states of the three isotopomers yield the substitution structure, rs(PN)=151.6516(87) pm and rs(NO)=119.5025(80) pm.

  8. Molecular structures and properties of starches of Australian wild rice.

    PubMed

    Tikapunya, Tiparat; Zou, Wei; Yu, Wenwen; Powell, Prudence O; Fox, Glen P; Furtado, Agnelo; Henry, Robert J; Gilbert, Robert G

    2017-09-15

    Australian wild rices have significant genetic differences from domesticated rices, which might provide rices with different starch molecular structure and thus different functional properties. Molecular structure, gelatinization properties, and pasting behaviours of starch of three Australian wild rices (Oryza australiensis, taxa A (O. rufipogon like) and taxa B (O. meridionalis like)) were determined and compared to domesticated indica and japonica rice. These had higher amylose content, more shorter amylose chains and fewer short amylopectin chains, resulted in a high gelatinization temperature in these wild rices. Compared to domesticated japonica rice, taxa A had a lower pasting viscosity; taxa B had a similar pasting viscosity but lower final viscosity. The significantly different starch molecular structure from that of normal domesticated rices, and concomitantly different properties, suggest advantageous uses in products such as rice crackers or rice pudding, and a source of nutritionally-desirable slowly digestible starch. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Molecular structure of vapor-deposited amorphous selenium

    NASA Astrophysics Data System (ADS)

    Goldan, A. H.; Li, C.; Pennycook, S. J.; Schneider, J.; Blom, A.; Zhao, W.

    2016-10-01

    The structure of amorphous selenium is clouded with much uncertainty and contradictory results regarding the dominance of polymeric chains versus monomer rings. The analysis of the diffraction radial distribution functions are inconclusive because of the similarities between the crystalline allotropes of selenium in terms of the coordination number, bond length, bond angle, and dihedral angle. Here, we took a much different approach and probed the molecular symmetry of the thermodynamically unstable amorphous state via analysis of structural phase transformations. We verified the structure of the converted metastable and stable crystalline structures using scanning transmission electron microscopy. In addition, given that no experimental technique can tell us the exact three-dimensional atomic arrangements in glassy semiconductors, we performed molecular-dynamic simulations using a well-established empirical three-body interatomic potential. We developed a true vapor-deposited process for the deposition of selenium molecules onto a substrate using empirical molecular vapor compositions and densities. We prepared both vapor-deposited and melt-quenched samples and showed that the simulated radial distribution functions match very well to experiment. The combination of our experimental and molecular-dynamic analyses shows that the structures of vapor- and melt-quenched glassy/amorphous selenium are quite different, based primarily on rings and chains, respectively, reflecting the predominant structure of the parent phase in its thermodynamic equilibrium.

  10. Screening and ranking of POPs for global half-life: QSAR approaches for prioritization based on molecular structure.

    PubMed

    Gramatica, Paola; Papa, Ester

    2007-04-15

    Persistence in the environment is an important criterion in prioritizing hazardous chemicals and in identifying new persistent organic pollutants (POPs). Degradation half-life in various compartments is among the more commonly used criteria for studying environmental persistence, but the limited availability of experimental data or reliable estimates is a serious problem. Available half-life data for degradation in air, water, sediment, and soil, for a set of 250 organic POP-type chemicals, were combined in a multivariate approach by principal component analysis to obtain a ranking of the studied organic pollutants according to their relative overall half-life. A global half-life index (GHLI) applicable for POP screening purposes is proposed. The reliability of this index was verified in comparison with multimedia model results. This global index was then modeled as a cumulative end-point using a QSAR approach based on few theoretical molecular descriptors, and a simple and robust regression model externally validated for its predictive ability was derived. The application of this model could allow a fast preliminary identification and prioritization of not yet known POPs, just from the knowledge of their molecular structure. This model can be applied a priori also in the chemical design of safer and alternative non-POP compounds.

  11. SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

    PubMed

    Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

    2013-03-01

    Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors.

  12. Comprehensive Molecular Structure of the Eukaryotic Ribosome

    PubMed Central

    Taylor, Derek J.; Devkota, Batsal; Huang, Andrew D.; Topf, Maya; Narayanan, Eswar; Sali, Andrej; Harvey, Stephen C.; Frank, Joachim

    2009-01-01

    Despite the emergence of a large number of X-ray crystallographic models of the bacterial 70S ribosome over the past decade, an accurate atomic model of the eukaryotic 80S ribosome is still not available. Eukaryotic ribosomes possess more ribosomal proteins and ribosomal RNA than bacterial ribosomes, which are implicated in extra-ribosomal functions in the eukaryotic cells. By combining cryo-EM with RNA and protein homology modeling, we obtained an atomic model of the yeast 80S ribosome complete with all ribosomal RNA expansion segments and all ribosomal proteins for which a structural homolog can be identified. Mutation or deletion of 80S ribosomal proteins can abrogate maturation of the ribosome, leading to several human diseases. We have localized one such protein unique to eukaryotes, rpS19e, whose mutations are associated with Diamond-Blackfan anemia in humans. Additionally, we characterize crucial and novel interactions between the dynamic stalk base of the ribosome with eukaryotic elongation factor 2. PMID:20004163

  13. Molecular Evolution, Structure, and Function of Peroxidasins

    PubMed Central

    Soudi, Monika; Zamocky, Marcel; Jakopitsch, Christa; Furtmüller, Paul G; Obinger, Christian

    2012-01-01

    Peroxidasins represent the subfamily 2 of the peroxidase-cyclooxygenase superfamily and are closely related to chordata peroxidases (subfamily 1) and peroxinectins (subfamily 3). They are multidomain proteins containing a heme peroxidase domain with high homology to human lactoperoxidase that mediates one- and two-electron oxidation reactions. Additional domains of the secreted and glycosylated metalloproteins are type C-like immunoglobulin domains, typical leucine-rich repeats, as well as a von Willebrand factor C module. These are typical motifs of extracellular proteins that mediate protein–protein interactions. We have reconstructed the phylogeny of this new family of oxidoreductases and show the presence of four invertebrate clades as well as one vertebrate clade that includes also two different human representatives. The variability of domain assembly in the various clades was analyzed, as was the occurrence of relevant catalytic residues in the peroxidase domain based on the knowledge of catalysis of the mammalian homologues. Finally, the few reports on expression, localization, enzymatic activity, and physiological roles in the model organisms Drosophila melanogaster, Caenorhabditis elegans, and Homo sapiens are critically reviewed. Roles attributed to peroxidasins include antimicrobial defense, extracellular matrix formation, and consolidation at various developmental stages. Many research questions need to be solved in future, including detailed biochemical/physical studies and elucidation of the three dimensional structure of a model peroxidasin as well as the relation and interplay of the domains and the in vivo functions in various organisms including man. PMID:22976969

  14. RxnFinder: biochemical reaction search engines using molecular structures, molecular fragments and reaction similarity.

    PubMed

    Hu, Qian-Nan; Deng, Zhe; Hu, Huanan; Cao, Dong-Sheng; Liang, Yi-Zeng

    2011-09-01

    Biochemical reactions play a key role to help sustain life and allow cells to grow. RxnFinder was developed to search biochemical reactions from KEGG reaction database using three search criteria: molecular structures, molecular fragments and reaction similarity. RxnFinder is helpful to get reference reactions for biosynthesis and xenobiotics metabolism. RxnFinder is freely available via: http://sdd.whu.edu.cn/rxnfinder. qnhu@whu.edu.cn.

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

    PubMed Central

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

    2015-01-01

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

  16. Importance of Molecular Structure on the Thermophoresis of Binary Mixtures.

    PubMed

    Kumar, Pardeep; Goswami, Debabrata

    2014-12-26

    Using thermal lens spectroscopy, we study the role of molecular structural isomers of butanol on the thermophoresis (or Soret effect) of binary mixtures of methanol in butanol. In this study, we show that the thermal lens signal due to the Soret effect changes its sign for all the different concentrations of binary mixtures of butanol with methanol except for the one containing tertiary-butanol. The magnitude and sign of the Soret coefficients strongly depend on the molecular structure of the isomers of butanol in the binary mixture with methanol. This isomerization dependence is in stark contrast to the expected mass dependence of the Soret effect.

  17. Predicting aqueous solubility of environmentally relevant compounds from molecular features: a simple but highly effective four-dimensional model based on Project to Latent Structures.

    PubMed

    Xiao, Feng; Gulliver, John S; Simcik, Matt F

    2013-09-15

    The aqueous solubility (log S) of xenobiotic chemicals has been identified as a key characteristic in determining their bioaccessibility/bioavailability and their fate and transport in aquatic environments. We here explore and evaluate the use of a state-of-the-art data analysis technique (Project to Latent Structures, PLS) to estimate log S of environmentally relevant chemicals. A large number (n = 624) of molecular descriptors was computed for over 1400 organic chemicals, and then refined by a feature selection technique. Candidate predictor descriptors were fitted to data by means of PLS, which was optimized by an internal leave-one-out cross-validation technique and validated by an external data set. The final (best) PLS model with only four variables (AlogP, X1sol, Mv, and E) exhibited noteworthy stability and good predictive power. It was able to explain 91% of the data (n = 1400) variance with an average absolute error of 0.5 log units through the solubilities span over 12 orders of magnitude. The newly proposed model is transparent, easily portable from one user to another, and robust enough to accurately estimate log S of a wide range of emerging contaminants.

  18. Study on molecular structure, spectroscopic behavior, NBO, and NLO analysis of 3-methylbezothiazole-2-thione.

    PubMed

    Chand, Satish; Al-Omary, Fatmah A M; El-Emam, Ali A; Shukla, Vikas K; Prasad, Onkar; Sinha, Leena

    2015-07-05

    Experimentally observed spectral data (FT-TR and FT-Raman) of 3-methylbezothiazole-2-thione (3MBT2T) were compared with the spectral data obtained by DFT/B3LYP method using 6-311++G(d,p) basis set. UV-Vis spectrum of the title compound was recorded and the electronic properties, such as frontier molecular orbitals and band gap energies were calculated by TD-DFT approach. The molecular properties like dipole moment, polarizability, first static hyperpolarizability, molecular electrostatic potential surface (MEPs), and contour map were calculated to get a better comprehension of the properties of the title molecule. Natural bond orbital (NBO) analysis was applied to investigate the stability of the molecule arising from charge delocalization. Global and local reactivity descriptors were also computed to predict reactivity and reactive sites on the molecule. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Reshaping Plant Biology: Qualitative and Quantitative Descriptors for Plant Morphology

    PubMed Central

    Balduzzi, Mathilde; Binder, Brad M.; Bucksch, Alexander; Chang, Cynthia; Hong, Lilan; Iyer-Pascuzzi, Anjali S.; Pradal, Christophe; Sparks, Erin E.

    2017-01-01

    An emerging challenge in plant biology is to develop qualitative and quantitative measures to describe the appearance of plants through the integration of mathematics and biology. A major hurdle in developing these metrics is finding common terminology across fields. In this review, we define approaches for analyzing plant geometry, topology, and shape, and provide examples for how these terms have been and can be applied to plants. In leaf morphological quantifications both geometry and shape have been used to gain insight into leaf function and evolution. For the analysis of cell growth and expansion, we highlight the utility of geometric descriptors for understanding sepal and hypocotyl development. For branched structures, we describe how topology has been applied to quantify root system architecture to lend insight into root function. Lastly, we discuss the importance of using morphological descriptors in ecology to assess how communities interact, function, and respond within different environments. This review aims to provide a basic description of the mathematical principles underlying morphological quantifications. PMID:28217137

  20. A discriminant multi-scale histopathology descriptor using dictionary learning

    NASA Astrophysics Data System (ADS)

    Romo, David; García-Arteaga, Juan D.; Arbeláez, Pablo; Romero, Eduardo

    2014-03-01

    When examining a histological sample, an expert must not only identify structures at different scale and conceptual levels, i.e. cellular, tissular and organic, but also recognize and integrate the visual cues of specific pathologies and histological concepts such as "gland", "carcinoma" or "collagen". It is necessary then to code the texture and color so that the relevant information present at different scales is emphasized and preserved. In this article we propose a novel multi-scale image descriptor using dictionaries that learn and code discriminant visual elements associated with specific histological concepts. The dictionaries are built separately for each concept using sparse coding algorithms. The descriptor's discrimination capacity is evaluated using a naive strategy that assigns a particular image to the class best represented by a particular dictionary. Results show how, even using this very simple approach, average recall and precision measures of 0.81 and 0.86 were obtained for the challenging problem of classifying epidermis, eccrine glands, hair follicle and nodular carcinoma in basal skin carcinoma images.

  1. Reshaping Plant Biology: Qualitative and Quantitative Descriptors for Plant Morphology.

    PubMed

    Balduzzi, Mathilde; Binder, Brad M; Bucksch, Alexander; Chang, Cynthia; Hong, Lilan; Iyer-Pascuzzi, Anjali S; Pradal, Christophe; Sparks, Erin E

    2017-01-01

    An emerging challenge in plant biology is to develop qualitative and quantitative measures to describe the appearance of plants through the integration of mathematics and biology. A major hurdle in developing these metrics is finding common terminology across fields. In this review, we define approaches for analyzing plant geometry, topology, and shape, and provide examples for how these terms have been and can be applied to plants. In leaf morphological quantifications both geometry and shape have been used to gain insight into leaf function and evolution. For the analysis of cell growth and expansion, we highlight the utility of geometric descriptors for understanding sepal and hypocotyl development. For branched structures, we describe how topology has been applied to quantify root system architecture to lend insight into root function. Lastly, we discuss the importance of using morphological descriptors in ecology to assess how communities interact, function, and respond within different environments. This review aims to provide a basic description of the mathematical principles underlying morphological quantifications.

  2. Dominant color correlogram descriptor for content-based image retrieval

    NASA Astrophysics Data System (ADS)

    Fierro-Radilla, Atoany; Perez-Daniel, Karina; Nakano-Miyatake, Mariko; Benois, Jenny

    2015-03-01

    Content-based image retrieval (CBIR) has become an interesting and urgent research topic due to the increase of necessity of indexing and classification of multimedia content in large databases. The low level visual descriptors, such as color-based, texture-based and shape-based descriptors, have been used for the CBIR task. In this paper we propose a color-based descriptor which describes well image contents, integrating both global feature provided by dominant color and local features provided by color correlogram. The performance of the proposed descriptor, called Dominant Color Correlogram descriptor (DCCD), is evaluated comparing with some MPEG-7 visual descriptors and other color-based descriptors reported in the literature, using two image datasets with different size and contents. The performance of the proposed descriptor is assessed using three different metrics commonly used in image retrieval task, which are ARP (Average Retrieval Precision), ARR (Average Retrieval Rate) and ANMRR (Average Normalized Modified Retrieval Rank). Also precision-recall curves are provided to show a better performance of the proposed descriptor compared with other color-based descriptors.

  3. Structural properties of CHAPS micelles, studied by molecular dynamics simulations.

    PubMed

    Herrera, Fernando E; Garay, A Sergio; Rodrigues, Daniel E

    2014-04-10

    Detergents are essential tools to study biological membranes, and they are frequently used to solubilize lipids and integral membrane proteins. Particularly the nondenaturing zwitterionic detergent usually named CHAPS was designed for membrane biochemistry and integrates the characteristics of the sulfobetaine-type detergents and bile salts. Despite the available experimental data little is known about the molecular structure of its micelles. In this work, molecular dynamics simulations were performed to study the aggregation in micelles of several numbers of CHAPS (≤ 18) starting from a homogeneous water dilution. The force field parameters to describe the interactions of the molecule were developed and validated. After 50 ns of simulation almost all the systems result in the formation of stable micelles. The molecular shape (gyration radii, volume, surface) and the molecular structure (RDF, salt bridges, H-bonds, SAS) of the micelles were characterized. It was found that the main interactions that lead to the stability of the micelles are the electrostatic ones among the polar groups of the tails and the OH's from the ring moiety. Unlike micelles of other compounds, CHAPS show a grainlike heterogeneity with hydrophobic micropockets. The results are in complete agreement with the available experimental information from NMR, TEM, and SAXS studies, allowing the modeling of the molecular structure of CHAPS micelles. Finally, we hope that the new force field parameters for this detergent will be a significant contribution to the knowledge of such an interesting molecule.

  4. From non-random molecular structure to life and mind

    NASA Technical Reports Server (NTRS)

    Fox, S. W.

    1989-01-01

    The evolutionary hierarchy molecular structure-->macromolecular structure-->protobiological structure-->biological structure-->biological functions has been traced by experiments. The sequence always moves through protein. Extension of the experiments traces the formation of nucleic acids instructed by proteins. The proteins themselves were, in this picture, instructed by the self-sequencing of precursor amino acids. While the sequence indicated explains the thread of the emergence of life, protein in cellular membrane also provides the only known material basis for the emergence of mind in the context of emergence of life.

  5. From non-random molecular structure to life and mind

    NASA Technical Reports Server (NTRS)

    Fox, S. W.

    1989-01-01

    The evolutionary hierarchy molecular structure-->macromolecular structure-->protobiological structure-->biological structure-->biological functions has been traced by experiments. The sequence always moves through protein. Extension of the experiments traces the formation of nucleic acids instructed by proteins. The proteins themselves were, in this picture, instructed by the self-sequencing of precursor amino acids. While the sequence indicated explains the thread of the emergence of life, protein in cellular membrane also provides the only known material basis for the emergence of mind in the context of emergence of life.

  6. Determination of structure parameters in molecular tunnelling ionisation model

    NASA Astrophysics Data System (ADS)

    Wang, Jun-Ping; Zhao, Song-Feng; Zhang, Cai-Rong; Li, Wei; Zhou, Xiao-Xin

    2014-04-01

    We extracted the accurate structure parameters in a molecular tunnelling ionisation model (the so-called MO-ADK model) for 23 selected linear molecules including some inner orbitals. The molecular wave functions with the correct asymptotic behaviour are obtained by solving the time-independent Schrödinger equation with B-spline functions and molecular potentials numerically constructed using the modified Leeuwen-Baerends (LBα) model. We show that the orientation-dependent ionisation rate reflects the shape of the ionising orbitals in general. The influences of the Stark shifts of the energy levels on the orientation-dependent ionisation rates of the polar molecules are studied. We also examine the angle-dependent ionisation rates (or probabilities) based on the MO-ADK model by comparing with the molecular strong-field approximation calculations and with recent experimental measurements.

  7. ALMA Reveals Internal Structure of Molecular Clouds in the LMC

    NASA Astrophysics Data System (ADS)

    Sawada, T.; Hasegawa, T.; Koda, J.

    2015-12-01

    We carried out high-resolution (0.7 pc) CO J=1-0 mosaic observations of five giant molecular clouds, which cover a wide range of evolutionary stages based on their associations to recent star formation, in the Large Magellanic Cloud with ALMA. The observations revealed a variety of spatial structures of the gas, from faint and diffuse emission to bright and compact structures. The variation of structures, which is similar to that seen in the Milky Way, is quantified by the brightness distribution function (BDF) and brightness distribution index (BDI) established in our prior studies. The structured molecular gas may indicate the readiness for, rather than the outcome of, star formation.

  8. In silico evaluation, molecular docking and QSAR analysis of quinazoline-based EGFR-T790M inhibitors.

    PubMed

    Asadollahi-Baboli, M

    2016-08-01

    Mutated epidermal growth factor receptor (EGFR-T790M) inhibitors hold promise as new agents against cancer. Molecular docking and QSAR analysis were performed based on a series of fifty-three quinazoline derivatives to elucidate key structural and physicochemical properties affecting inhibitory activity. Molecular docking analysis identified the true conformations of ligands in the receptor's active pocket. The structural features of the ligands, expressed as molecular descriptors, were derived from the obtained docked conformations. Non-linear and spline QSAR models were developed through novel genetic algorithm and artificial neural network (GA-ANN) and multivariate adaptive regression spline techniques, respectively. The former technique was employed to consider non-linear relation between molecular descriptors and inhibitory activity of quinazoline derivatives. The later technique was also used to describe the non-linearity using basis functions and sub-region equations for each descriptor. Our QSAR model gave a high predictive performance [Formula: see text] and [Formula: see text]) using diverse validation techniques. Eight new compounds were designed using our QSAR model as potent EGFR-T790M inhibitors. Overall, the proposed in silico strategy based on docked derived descriptor and non-linear descriptor subset selection may help design novel quinazoline derivatives with improved EGFR-T790M inhibitory activity.

  9. Principal component analysis of HPLC retention data and molecular modeling structural parameters of cardiovascular system drugs in view of their pharmacological activity.

    PubMed

    Stasiak, Jolanta; Koba, Marcin; Bober, Leszek; Baczek, Tomasz

    2010-07-09

    Evaluation of relationships between molecular modeling structural parameters and high-performance liquid chromatography (HPLC) retention data of 11 cardiovascular system drugs by principal component analysis (PCA) in relation to their pharmacological activity was performed. The six retention data parameters were determined on three different HPLC columns (Nucleosil C18 AB with octadecylsilica stationary phase, IAM PC C10/C3 with chemically bounded phosphatidylcholine, and Nucleosil 100-5 OH with chemically bounded propanodiole), and using isocratically acetonitrile: Britton-Robinson buffer as the mobile phase. Additionally, molecular modeling studies were performed with the use of HyperChem software and MM+ molecular mechanics with the semi-empirical AM1 method deriving 20 structural descriptors. Factor analysis obtained with the use of various sets of parameters: structural parameters, HPLC retention data, and all 26 considered parameters, led to the extraction of two main factors. The first principal component (factor 1) accounted for 44-57% of the variance in the data. The second principal component (factor 2) explained 29-33% of data variance. Moreover, the total data variance explained by the first two factors was at the level of 73-90%. More importantly, the PCA analysis of the HPLC retention data and structural parameters allows the segregation of circulatory system drugs according to their pharmacological (cardiovascular) properties as shown by the distribution of the individual drugs on the plane determined by the two principal components (factors 1 and 2).

  10. Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity

    PubMed Central

    Stasiak, Jolanta; Koba, Marcin; Bober, Leszek; Bączek, Tomasz

    2010-01-01

    Evaluation of relationships between molecular modeling structural parameters and high-performance liquid chromatography (HPLC) retention data of 11 cardiovascular system drugs by principal component analysis (PCA) in relation to their pharmacological activity was performed. The six retention data parameters were determined on three different HPLC columns (Nucleosil C18 AB with octadecylsilica stationary phase, IAM PC C10/C3 with chemically bounded phosphatidylcholine, and Nucleosil 100-5 OH with chemically bounded propanodiole), and using isocratically acetonitrile: Britton-Robinson buffer as the mobile phase. Additionally, molecular modeling studies were performed with the use of HyperChem software and MM+ molecular mechanics with the semi-empirical AM1 method deriving 20 structural descriptors. Factor analysis obtained with the use of various sets of parameters: structural parameters, HPLC retention data, and all 26 considered parameters, led to the extraction of two main factors. The first principal component (factor 1) accounted for 44–57% of the variance in the data. The second principal component (factor 2) explained 29–33% of data variance. Moreover, the total data variance explained by the first two factors was at the level of 73–90%. More importantly, the PCA analysis of the HPLC retention data and structural parameters allows the segregation of circulatory system drugs according to their pharmacological (cardiovascular) properties as shown by the distribution of the individual drugs on the plane determined by the two principal components (factors 1 and 2). PMID:20717530

  11. Origin and structure of polar domains in doped molecular crystals

    PubMed Central

    Meirzadeh, E.; Azuri, I.; Qi, Y.; Ehre, D.; Rappe, A. M.; Lahav, M.; Kronik, L.; Lubomirsky, I.

    2016-01-01

    Doping is a primary tool for the modification of the properties of materials. Occlusion of guest molecules in crystals generally reduces their symmetry by the creation of polar domains, which engender polarization and pyroelectricity in the doped crystals. Here we describe a molecular-level determination of the structure of such polar domains, as created by low dopant concentrations (<0.5%). The approach comprises crystal engineering and pyroelectric measurements, together with dispersion-corrected density functional theory and classical molecular dynamics calculations of the doped crystals, using neutron diffraction data of the host at different temperatures. This approach is illustrated using centrosymmetric α-glycine crystals doped with minute amounts of different L-amino acids. The experimentally determined pyroelectric coefficients are explained by the structure and polarization calculations, thus providing strong support for the local and global understanding of how different dopants influence the properties of molecular crystals. PMID:27824050

  12. The Oligomeric Structure of High Molecular Weight Adiponectin

    PubMed Central

    Suzuki, Shinji; Wilson-Kubalek, Elizabeth M.; Wert, David; Tsao, Tsu-Shuen; Lee, David H.

    2007-01-01

    There is great interest in the structure of adiponectin as its oligomeric state may specify its biological activities. It occurs as a trimer, a hexamer and a high molecular weight complex. Epidemiological data indicates that the high molecular weight form is significant with low serum levels in type 2 diabetics but to date, has not been well-defined. To resolve this issue, characterization of this oligomer from bovine serum and 3T3-L1 adipocytes by sedimentation equilibrium centrifugation and gel electrophoresis respectively, was carried out, revealing that it is octadecameric. Further studies by dynamic light scattering and electron microscopy established that bovine and possibly mouse high molecular weight adiponectin is C1q-like in structure. PMID:17292892

  13. Molecular structure of DNA by scanning tunneling microscopy.

    PubMed

    Cricenti, A; Selci, S; Felici, A C; Generosi, R; Gori, E; Djaczenko, W; Chiarotti, G

    1989-09-15

    Uncoated DNA molecules marked with an activated tris(l-aziridinyl) phosphine oxide (TAPO) solution were deposited on gold substrates and imaged in air with the use of a high-resolution scanning tunneling microscope (STM). Constant-current and gap-modulated STM images show clear evidence of the helicity of the DNA structure: pitch periodicity ranges from 25 to 35 angstroms, whereas the average diameter is 20 angstroms. Molecular structure within a single helix turn was also observed.

  14. Molecular Structure of DNA by Scanning Tunneling Microscopy

    NASA Astrophysics Data System (ADS)

    Cricenti, A.; Selci, S.; Felici, A. C.; Generosi, R.; Gori, E.; Djaczenko, W.; Chiarotti, G.

    1989-09-01

    Uncoated DNA molecules marked with an activated tris(1-aziridinyl) phosphine oxide (TAPO) solution were deposited on gold substrates and imaged in air with the use of a high-resolution scanning tunneling microscope (STM). Constant-current and gap-modulated STM images show clear evidence of the helicity of the DNA structure: pitch periodicity ranges from 25 and 35 angstroms, whereas the average diameter is 20 angstroms. Molecular structure within a single helix turn was also observed.

  15. Rattlesnake Neurotoxin Structure, Mechanism of Action, Immunology and Molecular Biology

    DTIC Science & Technology

    1992-09-10

    Aird, S. D., and Kaiser, I. I. (1988) Physiological and immunological properties of small myotoxins from -Zhe venom of the midget faded rattlesnake ...AD-A258 669 AD RATTLESNAKE NEUROTOXIN STRUCTURE, MECHANISM OF ACTION, IMMUNOLOGY AND MOLECULAR BIOLOGY FINAL REPORT D TIC IVAN I. KAISER ELECTE S DEC...u m_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 6 2 7 8 7 A I 6 2 7 8 7 A 8 7 7 I A A [ ~A 3 1 7 8 2 1 (u) Rattlesnake neurotoxin structure

  16. Connecting molecular structure and exciton diffusion length in rubrene derivatives.

    PubMed

    Mullenbach, Tyler K; McGarry, Kathryn A; Luhman, Wade A; Douglas, Christopher J; Holmes, Russell J

    2013-07-19

    Connecting molecular structure and exciton diffusion length in rubrene derivatives demonstrates how the diffusion length of rubrene can be enhanced through targeted functionalization aiming to enhance self-Förster energy transfer. Functionalization adds steric bulk, forcing the molecules farther apart on average, and leading to increased photoluminescence efficiency. A diffusion length enhancement greater than 50% is realized over unsubstituted rubrene.

  17. Crystal and molecular structure of lancerodiol–p–hydroxybenzoate

    PubMed Central

    Abd El–Razek, Mohamed H.; Hegazy, Mohamed–Elamir F.; Mohamed, Abou El–Hamd H.

    2010-01-01

    Lancerodiol–p–hydroxybenzoate was isolated from the leaves of Ferula sinaica L. (Apiaceae) as light needle crystals. This work reports for the first time the molecular structure and relative configuration of compound 1, established by X-ray analysis. PMID:21808543

  18. Learning physical descriptors for materials science by compressed sensing

    NASA Astrophysics Data System (ADS)

    Ghiringhelli, Luca M.; Vybiral, Jan; Ahmetcik, Emre; Ouyang, Runhai; Levchenko, Sergey V.; Draxl, Claudia; Scheffler, Matthias

    2017-02-01

    The availability of big data in materials science offers new routes for analyzing materials properties and functions and achieving scientific understanding. Finding structure in these data that is not directly visible by standard tools and exploitation of the scientific information requires new and dedicated methodology based on approaches from statistical learning, compressed sensing, and other recent methods from applied mathematics, computer science, statistics, signal processing, and information science. In this paper, we explain and demonstrate a compressed-sensing based methodology for feature selection, specifically for discovering physical descriptors, i.e., physical parameters that describe the material and its properties of interest, and associated equations that explicitly and quantitatively describe those relevant properties. As showcase application and proof of concept, we describe how to build a physical model for the quantitative prediction of the crystal structure of binary compound semiconductors.

  19. Universal fragment descriptors for predicting properties of inorganic crystals

    NASA Astrophysics Data System (ADS)

    Isayev, Olexandr; Oses, Corey; Toher, Cormac; Gossett, Eric; Curtarolo, Stefano; Tropsha, Alexander

    2017-06-01

    Although historically materials discovery has been driven by a laborious trial-and-error process, knowledge-driven materials design can now be enabled by the rational combination of Machine Learning methods and materials databases. Here, data from the AFLOW repository for ab initio calculations is combined with Quantitative Materials Structure-Property Relationship models to predict important properties: metal/insulator classification, band gap energy, bulk/shear moduli, Debye temperature and heat capacities. The prediction's accuracy compares well with the quality of the training data for virtually any stoichiometric inorganic crystalline material, reciprocating the available thermomechanical experimental data. The universality of the approach is attributed to the construction of the descriptors: Property-Labelled Materials Fragments. The representations require only minimal structural input allowing straightforward implementations of simple heuristic design rules.

  20. Universal fragment descriptors for predicting properties of inorganic crystals

    PubMed Central

    Isayev, Olexandr; Oses, Corey; Toher, Cormac; Gossett, Eric; Curtarolo, Stefano; Tropsha, Alexander

    2017-01-01

    Although historically materials discovery has been driven by a laborious trial-and-error process, knowledge-driven materials design can now be enabled by the rational combination of Machine Learning methods and materials databases. Here, data from the AFLOW repository for ab initio calculations is combined with Quantitative Materials Structure-Property Relationship models to predict important properties: metal/insulator classification, band gap energy, bulk/shear moduli, Debye temperature and heat capacities. The prediction's accuracy compares well with the quality of the training data for virtually any stoichiometric inorganic crystalline material, reciprocating the available thermomechanical experimental data. The universality of the approach is attributed to the construction of the descriptors: Property-Labelled Materials Fragments. The representations require only minimal structural input allowing straightforward implementations of simple heuristic design rules. PMID:28580961

  1. Mechanistic Details and Reactivity Descriptors in Oxidation and Acid Catalysis of Methanol

    SciTech Connect

    Deshlahra, Prashant; Carr, Robert T.; Chai, Song-Hai; Iglesia, Enrique

    2015-02-06

    Acid and redox reaction rates of CH₃OH-O₂ mixtures on polyoxometalate (POM) clusters, together with isotopic, spectroscopic, and theoretical assessments of catalyst properties and reaction pathways, were used to define rigorous descriptors of reactivity and to probe the compositional effects for oxidative dehydrogenation (ODH) and dehydration reactions. ³¹P-MAS NMR, transmission electron microscopy and titrations of protons with di-tert-butylpyridine during catalysis showed that POM clusters retained their Keggin structure upon dispersion on SiO₂ and after use in CH₃OH reactions. The effects of CH₃OH and O₂ pressures and of D-substitution on ODH rates show that C-H activation in molecularly adsorbed CH₃OH is the sole kinetically relevant step and leads to reduced centers as intermediates present at low coverages; their concentrations, measured from UV-vis spectra obtained during catalysis, are consistent with the effects of CH₃OH/O₂ ratios predicted from the elementary steps proposed. First-order ODH rate constants depend strongly on the addenda atoms (Mo vs W) but weakly on the central atom (P vs Si) in POM clusters, because C-H activation steps inject electrons into the lowest unoccupied molecular orbitals (LUMO) of the clusters, which are the d-orbitals at Mo⁶⁺ and W⁶⁺ centers. H-atom addition energies (HAE) at O-atoms in POM clusters represent the relevant theoretical probe of the LUMO energies and of ODH reactivity. The calculated energies of ODH transition states at each O-atom depend linearly on their HAE values with slopes near unity, as predicted for late transition states in which electron transfer and C-H cleavage are essentially complete. HAE values averaged over all accessible O-atoms in POM clusters provide the appropriate reactivity descriptor for oxides whose known structures allow accurate HAE calculations. CH₃OH dehydration proceeds via parallel pathways mediated by late carbenium-ion transition states; effects of

  2. Synthesis, crystal structure, Hirshfeld surface analysis, spectroscopic characterization, reactivity study by DFT and MD approaches and molecular docking study of a novel chalcone derivative

    NASA Astrophysics Data System (ADS)

    Arshad, Suhana; Pillai, Renjith Raveendran; Zainuri, Dian Alwani; Khalib, Nuridayanti Che; Razak, Ibrahim Abdul; Armaković, Stevan; Armaković, Sanja J.; Panicker, C. Yohannan; Van Alsenoy, C.

    2017-05-01

    In the present study, the title compound named as (E)-1-(4-bromophenyl)-3-(4-(trifluoromethyl)phenyl)prop-2-en-1-one was synthesized and structurally characterized by single-crystal X-ray diffraction. The compound crystallizes in monoclinic crystal system in P21/c space group, unit cell parameters a = 16.7629 (12) Å, b = 13.9681 (10) Å, c = 5.8740 (4) Å, β = 96.3860 (12)° and Z = 4. Hirshfeld surface analysis revealed that the molecular structure is dominated by H⋯H, C⋯H/H⋯C, Br⋯F/F⋯Br and F⋯F contacts. The FT-IR spectrum was recorded and interpreted in details with the aid of Density Functional Theory (DFT) calculations and Potential Energy Distribution (PED) analysis. Average local ionization energies (ALIE) and Fukui functions have been used as quantum-molecular descriptors to locate the molecule sites that could be of importance from the aspect of reactivity. Degradation properties have been assessed by calculations of bond dissociation energies (BDE) for hydrogen abstraction and the rest of the single acyclic bonds, while molecular dynamics (MD) simulations were used in order to calculate radial distribution functions and determine the atoms with significant interactions with water. In order to understand how the title molecule inhibits and hence increases the catalytic efficiency of MOA-B enzyme, molecular docking study was performed.

  3. Notes on quantitative structure-property relationships (QSPR), part 3: density functions origin shift as a source of quantum QSPR algorithms in molecular spaces.

    PubMed

    Carbó-Dorca, Ramon

    2013-04-05

    A general algorithm implementing a useful variant of quantum quantitative structure-property relationships (QQSPR) theory is described. Based on quantum similarity framework and previous theoretical developments on the subject, the present QQSPR procedure relies on the possibility to perform geometrical origin shifts over molecular density function sets. In this way, molecular collections attached to known properties can be easily used over other quantum mechanically well-described molecular structures for the estimation of their unknown property values. The proposed procedure takes quantum mechanical expectation value as provider of causal relation background and overcomes the dimensionality paradox, which haunts classical descriptor space QSPR. Also, contrarily to classical procedures, which are also attached to heavy statistical gear, the present QQSPR approach might use a geometrical assessment only or just some simple statistical outline or both. From an applied point of view, several easily reachable computational levels can be set up. A Fortran 95 program: QQSPR-n is described with two versions, which might be downloaded from a dedicated web site. Various practical examples are provided, yielding excellent results. Finally, it is also shown that an equivalent molecular space classical QSPR formalism can be easily developed.

  4. The Classification of HEp-2 Cell Patterns Using Fractal Descriptor.

    PubMed

    Xu, Rudan; Sun, Yuanyuan; Yang, Zhihao; Song, Bo; Hu, Xiaopeng

    2015-07-01

    Indirect immunofluorescence (IIF) with HEp-2 cells is considered as a powerful, sensitive and comprehensive technique for analyzing antinuclear autoantibodies (ANAs). The automatic classification of the HEp-2 cell images from IIF has played an important role in diagnosis. Fractal dimension can be used on the analysis of image representing and also on the property quantification like texture complexity and spatial occupation. In this study, we apply the fractal theory in the application of HEp-2 cell staining pattern classification, utilizing fractal descriptor firstly in the HEp-2 cell pattern classification with the help of morphological descriptor and pixel difference descriptor. The method is applied to the data set of MIVIA and uses the support vector machine (SVM) classifier. Experimental results show that the fractal descriptor combining with morphological descriptor and pixel difference descriptor makes the precisions of six patterns more stable, all above 50%, achieving 67.17% overall accuracy at best with relatively simple feature vectors.

  5. Trainable Siamese keypoint descriptors for real-time applications

    NASA Astrophysics Data System (ADS)

    Fedorenko, Fedor A.; Ivanova, Alena A.; Limonova, Elena E.; Konovalenko, Ivan A.

    2017-02-01

    Computing image patch descriptors for correspondence problems relies heavily on hand-crafted feature transformations, e.g. SIFT, SURF. In this paper, we explore a Siamese pairing of fully connected neural networks for the purpose of learning discriminative local feature descriptors. Resulting ANN computes 128-D descriptors, and demonstrates consistent speedup as compared to such state-of-the-art methods as SIFT and FREAK on PCs as well as in embedded systems. We use L2 distance to reflect descriptor similarity during both training and testing. In this way, feature descriptors we propose can be easily compared to their hand-crafted counterparts. We also created a dataset augmented with synthetic data for learning local features, and it is available online. The augmentations provide training data for our descriptors to generalise well against scaling and rotation, shift, Gaussian noise, and illumination changes.

  6. Invariant Descriptor Learning Using a Siamese Convolutional Neural Network

    NASA Astrophysics Data System (ADS)

    Chen, L.; Rottensteiner, F.; Heipke, C.

    2016-06-01

    In this paper we describe learning of a descriptor based on the Siamese Convolutional Neural Network (CNN) architecture and evaluate our results on a standard patch comparison dataset. The descriptor learning architecture is composed of an input module, a Siamese CNN descriptor module and a cost computation module that is based on the L2 Norm. The cost function we use pulls the descriptors of matching patches close to each other in feature space while pushing the descriptors for non-matching pairs away from each other. Compared to related work, we optimize the training parameters by combining a moving average strategy for gradients and Nesterov's Accelerated Gradient. Experiments show that our learned descriptor reaches a good performance and achieves state-of-art results in terms of the false positive rate at a 95 % recall rate on standard benchmark datasets.

  7. Reduced density gradient as a novel approach for estimating QSAR descriptors, and its application to 1, 4-dihydropyridine derivatives with potential antihypertensive effects.

    PubMed

    Jardínez, Christiaan; Vela, Alberto; Cruz-Borbolla, Julián; Alvarez-Mendez, Rodrigo J; Alvarado-Rodríguez, José G

    2016-12-01

    The relationship between the chemical structure and biological activity (log IC50) of 40 derivatives of 1,4-dihydropyridines (DHPs) was studied using density functional theory (DFT) and multiple linear regression analysis methods. With the aim of improving the quantitative structure-activity relationship (QSAR) model, the reduced density gradient s( r) of the optimized equilibrium geometries was used as a descriptor to include weak non-covalent interactions. The QSAR model highlights the correlation between the log IC50 with highest molecular orbital energy (E HOMO), molecular volume (V), partition coefficient (log P), non-covalent interactions NCI(H4-G) and the dual descriptor [Δf(r)]. The model yielded values of R (2)=79.57 and Q (2)=69.67 that were validated with the next four internal analytical validations DK=0.076, DQ=-0.006, R (P) =0.056, and R (N)=0.000, and the external validation Q (2)boot=64.26. The QSAR model found can be used to estimate biological activity with high reliability in new compounds based on a DHP series. Graphical abstract The good correlation between the log IC50 with the NCI (H4-G) estimated by the reduced density gradient approach of the DHP derivatives.

  8. Fingerprint identification using SIFT-based minutia descriptors and improved all descriptor-pair matching.

    PubMed

    Zhou, Ru; Zhong, Dexing; Han, Jiuqiang

    2013-03-06

    The performance of conventional minutiae-based fingerprint authentication algorithms degrades significantly when dealing with low quality fingerprints with lots of cuts or scratches. A similar degradation of the minutiae-based algorithms is observed when small overlapping areas appear because of the quite narrow width of the sensors. Based on the detection of minutiae, Scale Invariant Feature Transformation (SIFT) descriptors are employed to fulfill verification tasks in the above difficult scenarios. However, the original SIFT algorithm is not suitable for fingerprint because of: (1) the similar patterns of parallel ridges; and (2) high computational resource consumption. To enhance the efficiency and effectiveness of the algorithm for fingerprint verification, we propose a SIFT-based Minutia Descriptor (SMD) to improve the SIFT algorithm through image processing, descriptor extraction and matcher. A two-step fast matcher, named improved All Descriptor-Pair Matching (iADM), is also proposed to implement the 1:N verifications in real-time. Fingerprint Identification using SMD and iADM (FISiA) achieved a significant improvement with respect to accuracy in representative databases compared with the conventional minutiae-based method. The speed of FISiA also can meet real-time requirements.

  9. Fingerprint Identification Using SIFT-Based Minutia Descriptors and Improved All Descriptor-Pair Matching

    PubMed Central

    Zhou, Ru; Zhong, Dexing; Han, Jiuqiang

    2013-01-01

    The performance of conventional minutiae-based fingerprint authentication algorithms degrades significantly when dealing with low quality fingerprints with lots of cuts or scratches. A similar degradation of the minutiae-based algorithms is observed when small overlapping areas appear because of the quite narrow width of the sensors. Based on the detection of minutiae, Scale Invariant Feature Transformation (SIFT) descriptors are employed to fulfill verification tasks in the above difficult scenarios. However, the original SIFT algorithm is not suitable for fingerprint because of: (1) the similar patterns of parallel ridges; and (2) high computational resource consumption. To enhance the efficiency and effectiveness of the algorithm for fingerprint verification, we propose a SIFT-based Minutia Descriptor (SMD) to improve the SIFT algorithm through image processing, descriptor extraction and matcher. A two-step fast matcher, named improved All Descriptor-Pair Matching (iADM), is also proposed to implement the 1:N verifications in real-time. Fingerprint Identification using SMD and iADM (FISiA) achieved a significant improvement with respect to accuracy in representative databases compared with the conventional minutiae-based method. The speed of FISiA also can meet real-time requirements. PMID:23467056

  10. Extracting Structure Parameters of Dimers for Molecular Tunneling Ionization Model

    NASA Astrophysics Data System (ADS)

    Song-Feng, Zhao; Fang, Huang; Guo-Li, Wang; Xiao-Xin, Zhou

    2016-03-01

    We determine structure parameters of the highest occupied molecular orbital (HOMO) of 27 dimers for the molecular tunneling ionization (so called MO-ADK) model of Tong et al. [Phys. Rev. A 66 (2002) 033402]. The molecular wave functions with correct asymptotic behavior are obtained by solving the time-independent Schrödinger equation with B-spline functions and molecular potentials which are numerically created using the density functional theory. We examine the alignment-dependent tunneling ionization probabilities from MO-ADK model for several molecules by comparing with the molecular strong-field approximation (MO-SFA) calculations. We show the molecular Perelomov-Popov-Terent'ev (MO-PPT) can successfully give the laser wavelength dependence of ionization rates (or probabilities). Based on the MO-PPT model, two diatomic molecules having valence orbital with antibonding systems (i.e., Cl2, Ne2) show strong ionization suppression when compared with their corresponding closest companion atoms. Supported by National Natural Science Foundation of China under Grant Nos. 11164025, 11264036, 11465016, 11364038, the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20116203120001, and the Basic Scientific Research Foundation for Institution of Higher Learning of Gansu Province

  11. Molecular design for growth of supramolecular membranes with hierarchical structure.

    PubMed

    Zha, R Helen; Velichko, Yuri S; Bitton, Ronit; Stupp, Samuel I

    2016-02-07

    Membranes with hierarchical structure exist in biological systems, and bio-inspired building blocks have been used to grow synthetic analogues in the laboratory through self-assembly. The formation of these synthetic membranes is initiated at the interface of two aqueous solutions, one containing cationic peptide amphiphiles (PA) and the other containing the anionic biopolymer hyaluronic acid (HA). The membrane growth process starts within milliseconds of interface formation and continues over much longer timescales to generate robust membranes with supramolecular PA-HA nanofibers oriented orthogonal to the interface. Computer simulation indicates that formation of these hierarchically structured membranes requires strong interactions between molecular components at early time points in order to generate a diffusion barrier between both solutions. Experimental studies using structurally designed PAs confirm simulation results by showing that only PAs with high ζ potential are able to yield hierarchically structured membranes. Furthermore, the chemical structure of such PAs must incorporate residues that form β-sheets, which facilitates self-assembly of long nanofibers. In contrast, PAs that form low aspect ratio nanostructures interact weakly with HA and yield membranes that exhibit non-fibrous fingering protrusions. Furthermore, experimental results show that increasing HA molecular weight decreases the growth rate of orthogonal nanofibers. This result is supported by simulation results suggesting that the thickness of the interfacial contact layer generated immediately after initiation of self-assembly increases with polymer molecular weight.

  12. MPEG-7 Descriptors for Earth Observation Satellite Images

    NASA Astrophysics Data System (ADS)

    Nieto, X. Giro I.; Marques Acosta, F.

    The amount of digital multimedia information has experienced a spectacular growth during the last years thanks to the advances on digital systems of image, video and audio acquisition. As a response to the need of organising all this information, ISO/IEC has developed a new standard for multimedia content description called MPEG-7. Among other topics, MPEG-7 defines a set of multimedia descriptors that can be automatically generated using signal processing techniques. Earth Observation Satellites generate large quantities of images stored on enormous databases that can take advantage of the new standard. An automatic indexation of these images using MPEG-7 metadata can improve their contents management as well as simplify interaction between independent databases. This paper gives an overall description on MPEG-7 standard focusing on the low-level Visual Descriptors. These descriptors can be grouped into four categories: color, texture, shape and motion. Visual Color Descriptors represent the colour distribution of an image in terms of a specified colour space. Visual Texture Descriptors define the visual pattern of an image according to its homogenities and non-homogenities. Visual Shape Descriptors describe the shape of 2D and 3D objects being, at the same time, invariant to scaling, rotation and translation. Motion Descriptors give the essential characteristics of objects and camera motions. These descriptors can be used individually or in combination to index and retrieve satellite images of the Earth from a database. For example, oceans and glaciars can be discerned based on their Colour Descriptors, also cities and deserts based on the Texture Descriptors, island images can be grouped using the Shape Descriptors, and cyclone trajectories studied and compared using the Motion Descriptors.

  13. An Efficient Wide-Baseline Dense Matching Descriptor

    NASA Astrophysics Data System (ADS)

    Wan, Yanli; Miao, Zhenjiang; Tang, Zhen; Wan, Lili; Wang, Zhe

    This letter proposes an efficient local descriptor for wide-baseline dense matching. It improves the existing Daisy descriptor by combining intensity-based Haar wavelet response with a new color-based ratio model. The color ratio model is invariant to changes of viewing direction, object geometry, and the direction, intensity and spectral power distribution of the illumination. The experiments show that our descriptor has high discriminative power and robustness.

  14. Molecular, Functional, and Structural Imaging of Major Depressive Disorder.

    PubMed

    Zhang, Kai; Zhu, Yunqi; Zhu, Yuankai; Wu, Shuang; Liu, Hao; Zhang, Wei; Xu, Caiyun; Zhang, Hong; Hayashi, Takuya; Tian, Mei

    2016-06-01

    Major depressive disorder (MDD) is a significant cause of morbidity and mortality worldwide, correlating with genetic susceptibility and environmental risk factors. Molecular, functional, and structural imaging approaches have been increasingly used to detect neurobiological changes, analyze neurochemical correlates, and parse pathophysiological mechanisms underlying MDD. We reviewed recent neuroimaging publications on MDD in terms of molecular, functional, and structural alterations as detected mainly by magnetic resonance imaging (MRI) and positron emission tomography. Altered structure and function of brain regions involved in the cognitive control of affective state have been demonstrated. An abnormal default mode network, as revealed by resting-state functional MRI, is likely associated with aberrant metabolic and serotonergic function revealed by radionuclide imaging. Further multi-modal investigations are essential to clarify the characteristics of the cortical network and serotonergic system associated with behavioral and genetic variations in MDD.

  15. Photoelectron Angular Distribution and Molecular Structure in Multiply Charged Anions

    SciTech Connect

    Xing, Xiaopeng; Wang, Xue B.; Wang, Lai S.

    2009-02-12

    Photoelectrons emitted from multiply charged anions (MCAs) carry information of the intramolecular Coulomb repulsion (ICR), which is dependent on molecular structures. Using photoelectron imaging, we observed the effects of ICR on photoelectron angular distributions (PAD) of the three isomers of benzene dicarboxylate dianions C6H4(CO2)22– (o-, m- and p-BDC2–). Photoelectrons were observed to peak along the laser polarization due to the ICR, but the anisotropy was the largest for p-BDC2–, followed by the m- and o-isomer. The observed anisotropy is related to the direction of the ICR or the detailed molecular structures, suggesting that photoelectron imaging may allow structural information to be obtained for complex multiply charged anions.

  16. MOLVIE: an interactive visualization environment for molecular structures.

    PubMed

    Sun, Huandong; Li, Ming; Xu, Ying

    2003-05-01

    A Molecular visualization interactive environment (MOLVIE), is designed to display three-dimensional (3D) structures of molecules and support the structural analysis and research on proteins. The paper presents the features, design considerations and applications of MOLVIE, especially the new functions used to compare the structures of two molecules and view the partial fragment of a molecule. Being developed in JAVA, MOLVIE is platform-independent. Moreover, it may run on a webpage as an applet for remote users. MOLVIE is available at http://www.cs.ucsb.edu/~mli/Bioinf/software/index.html.

  17. Building bridges between cellular and molecular structural biology.

    PubMed

    Patwardhan, Ardan; Brandt, Robert; Butcher, Sarah J; Collinson, Lucy; Gault, David; Grünewald, Kay; Hecksel, Corey; Huiskonen, Juha T; Iudin, Andrii; Jones, Martin L; Korir, Paul K; Koster, Abraham J; Lagerstedt, Ingvar; Lawson, Catherine L; Mastronarde, David; McCormick, Matthew; Parkinson, Helen; Rosenthal, Peter B; Saalfeld, Stephan; Saibil, Helen R; Sarntivijai, Sirarat; Solanes Valero, Irene; Subramaniam, Sriram; Swedlow, Jason R; Tudose, Ilinca; Winn, Martyn; Kleywegt, Gerard J

    2017-07-06

    The integration of cellular and molecular structural data is key to understanding the function of macromolecular assemblies and complexes in their in vivo context. Here we report on the outcomes of a workshop that discussed how to integrate structural data from a range of public archives. The workshop identified two main priorities: the development of tools and file formats to support segmentation (that is, the decomposition of a three-dimensional volume into regions that can be associated with defined objects), and the development of tools to support the annotation of biological structures.

  18. Molecular and electronic structure of electroactive self-assembled monolayers

    NASA Astrophysics Data System (ADS)

    Méndez De Leo, Lucila P.; de la Llave, Ezequiel; Scherlis, Damián; Williams, Federico J.

    2013-03-01

    Self-assembled monolayers (SAMs) containing electroactive functional groups are excellent model systems for the formation of electronic devices by self-assembly. In particular ferrocene-terminated alkanethiol SAMs have been extensively studied in the past. However, there are still open questions related with their electronic structure including the influence of the ferrocene group in the SAM-induced work function changes of the underlying metal. We have thus carried out a thorough experimental and theoretical investigation in order to determine the molecular and electronic structure of ferrocene-terminated alkanethiol SAMs on Au surfaces. In agreement with previous studies we found that the Fc-containing alkanethiol molecules adsorb forming a thiolate bond with the Au surface with a molecular geometry 30° tilted with respect to the surface normal. Measured surface coverages indicate the formation of a compact monolayer. We found for the first time that the ferrocene group has little influence on the observed work function decrease which is largely determined by the alkanethiol. Furthermore, the ferrocene moiety lies 14 Å above the metal surface covalently bonded to the alkanethiol SAM and its HOMO is located at -1.6 eV below the Fermi level. Our results provide new valuable insight into the molecular and electronic structure of electroactive SAMs which are of fundamental importance in the field of molecular electronics.

  19. Molecular and electronic structure of electroactive self-assembled monolayers.

    PubMed

    Méndez De Leo, Lucila P; de la Llave, Ezequiel; Scherlis, Damián; Williams, Federico J

    2013-03-21

    Self-assembled monolayers (SAMs) containing electroactive functional groups are excellent model systems for the formation of electronic devices by self-assembly. In particular ferrocene-terminated alkanethiol SAMs have been extensively studied in the past. However, there are still open questions related with their electronic structure including the influence of the ferrocene group in the SAM-induced work function changes of the underlying metal. We have thus carried out a thorough experimental and theoretical investigation in order to determine the molecular and electronic structure of ferrocene-terminated alkanethiol SAMs on Au surfaces. In agreement with previous studies we found that the Fc-containing alkanethiol molecules adsorb forming a thiolate bond with the Au surface with a molecular geometry 30° tilted with respect to the surface normal. Measured surface coverages indicate the formation of a compact monolayer. We found for the first time that the ferrocene group has little influence on the observed work function decrease which is largely determined by the alkanethiol. Furthermore, the ferrocene moiety lies 14 Å above the metal surface covalently bonded to the alkanethiol SAM and its HOMO is located at -1.6 eV below the Fermi level. Our results provide new valuable insight into the molecular and electronic structure of electroactive SAMs which are of fundamental importance in the field of molecular electronics.

  20. Cytoskeleton Molecular Motors: Structures and Their Functions in Neuron.

    PubMed

    Xiao, Qingpin; Hu, Xiaohui; Wei, Zhiyi; Tam, Kin Yip

    2016-01-01

    Cells make use of molecular motors to transport small molecules, macromolecules and cellular organelles to target region to execute biological functions, which is utmost important for polarized cells, such as neurons. In particular, cytoskeleton motors play fundamental roles in neuron polarization, extension, shape and neurotransmission. Cytoskeleton motors comprise of myosin, kinesin and cytoplasmic dynein. F-actin filaments act as myosin track, while kinesin and cytoplasmic dynein move on microtubules. Cytoskeleton motors work together to build a highly polarized and regulated system in neuronal cells via different molecular mechanisms and functional regulations. This review discusses the structures and working mechanisms of the cytoskeleton motors in neurons.

  1. On calculating the equilibrium structure of molecular crystals.

    SciTech Connect

    Mattsson, Ann Elisabet; Wixom, Ryan R.; Mattsson, Thomas Kjell Rene

    2010-03-01

    The difficulty of calculating the ambient properties of molecular crystals, such as the explosive PETN, has long hampered much needed computational investigations of these materials. One reason for the shortcomings is that the exchange-correlation functionals available for Density Functional Theory (DFT) based calculations do not correctly describe the weak intermolecular van der Waals' forces present in molecular crystals. However, this weak interaction also poses other challenges for the computational schemes used. We will discuss these issues in the context of calculations of lattice constants and structure of PETN with a number of different functionals, and also discuss if these limitations can be circumvented for studies at non-ambient conditions.

  2. Cytoskeleton Molecular Motors: Structures and Their Functions in Neuron

    PubMed Central

    Xiao, Qingpin; Hu, Xiaohui; Wei, Zhiyi; Tam, Kin Yip

    2016-01-01

    Cells make use of molecular motors to transport small molecules, macromolecules and cellular organelles to target region to execute biological functions, which is utmost important for polarized cells, such as neurons. In particular, cytoskeleton motors play fundamental roles in neuron polarization, extension, shape and neurotransmission. Cytoskeleton motors comprise of myosin, kinesin and cytoplasmic dynein. F-actin filaments act as myosin track, while kinesin and cytoplasmic dynein move on microtubules. Cytoskeleton motors work together to build a highly polarized and regulated system in neuronal cells via different molecular mechanisms and functional regulations. This review discusses the structures and working mechanisms of the cytoskeleton motors in neurons. PMID:27570482

  3. Three-dimensional depth profiling of molecular structures.

    PubMed

    Wucher, A; Cheng, J; Zheng, L; Winograd, N

    2009-04-01

    Molecular time of flight secondary ion mass spectrometry (ToF-SIMS) imaging and cluster ion beam erosion are combined to perform a three-dimensional chemical analysis of molecular films. The resulting dataset allows a number of artifacts inherent in sputter depth profiling to be assessed. These artifacts arise from lateral inhomogeneities of either the erosion rate or the sample itself. Using a test structure based on a trehalose film deposited on Si, we demonstrate that the "local" depth resolution may approach values which are close to the physical limit introduced by the information depth of the (static) ToF-SIMS method itself.

  4. Infrared face recognition using texture descriptors

    NASA Astrophysics Data System (ADS)

    Akhloufi, Moulay A.; Bendada, Abdelhakim

    2010-05-01

    Face recognition is an area of computer vision that has attracted a lot of interest from the research community. A growing demand for robust face recognition software in security applications has driven the development of interesting approaches in this field. A large quantity of research in face recognition deals with visible face images. In the visible spectrum the illumination and face expressions changes represent a significant challenge for the recognition system. To avoid these problems, researchers proposed recently the use of 3D and infrared imaging for face recognition. In this work, we introduce a new framework for infrared face recognition using texture descriptors. This framework exploits linear and non linear dimensionality reduction techniques for face learning and recognition in the texture space. Active and passive infrared imaging modalities are used and comparison with visible face recognition is performed. Two multispectral face recognition databases were used in our experiments: Equinox Database (Visible, SWIR, MWIR, LWIR) and Laval University Multispectral Database (Visible, NIR, MWIR, LWIR). The obtained results show high increase in recognition performance when texture descriptors like LBP (Local Binary Pattern) and LTP (Local Ternary Pattern) are used. The best result was obtained in the short wave infrared spectrum (SWIR) using non linear dimensionality reduction techniques.

  5. Heliconia phenotypic diversity based on qualitative descriptors.

    PubMed

    Guimarães, W N R; Martins, L S S; Castro, C E F; Carvalho Filho, J L S; Loges, V

    2014-04-17

    The aim of this study was to characterize Heliconia genotypes phenotypically using 26 qualitative descriptors. The evaluations were conducted in five flowering stems per clump in three replicates of 22 Heliconia genotypes. Data were subjected to multivariate analysis, the Mahalanobis dissimilarity measure was estimated, and the dendrogram was generated using the nearest neighbor method. From the values generated by the dissimilarity matrix and the clusters formed among the Heliconia genotypes studied, the phenotypic characterizations that best differentiated the genotypes were: pseudostem and wax green tone (light or dark green), leaf-wax petiole, the petiole hair, cleft margin at the base of the petiole, midrib underside shade of green, wax midrib underside, color sheet (light or dark green), unequal lamina base, torn limb, inflorescence-wax, position of inflorescence, bract leaf in apex, twisting of the rachis, and type of bloom. These results will be applied in the preparation of a catalog for Heliconia descriptors, in the selection of different genotypes with most promising characteristics for crosses, and for the characterization of new genotypes to be introduced in germplasm collections.

  6. A robust HOG-based descriptor for pattern recognition

    NASA Astrophysics Data System (ADS)

    Diaz-Escobar, Julia; Kober, Vitaly

    2016-09-01

    The Histogram of Oriented Gradients (HOG) is a popular feature descriptor used in computer vision and image processing. The technique counts occurrences of gradient orientation in localized portions of an image. The descriptor is sensible to the presence in images of noise, nonuniform illumination, and low contrast. In this work, we propose a robust HOG-based descriptor using the local energy model and phase congruency approach. Computer simulation results are presented for recognition of objects in images affected by additive noise, nonuniform illumination, and geometric distortions using the proposed and conventional HOG descriptors.

  7. Molecular crime scene investigation - dusting for fingerprints.

    PubMed

    Jürgen Bajorath

    2013-12-01

    In chemoinformatics and drug design, fingerprints (FPs) are defined as string representations of molecular structure and properties and are popular descriptors for similarity searching. FPs are generally characterized by the simplicity of their design and ease of use. Despite a long history in chemoinformatics, the potential and limitations of FP searching are often not well under- stood. Standard FPs can also be subjected to engineering techniques to tune them for specific search applications.

  8. Ab initio molecular crystal structures, spectra, and phase diagrams.

    PubMed

    Hirata, So; Gilliard, Kandis; He, Xiao; Li, Jinjin; Sode, Olaseni

    2014-09-16

    Conspectus Molecular crystals are chemists' solids in the sense that their structures and properties can be understood in terms of those of the constituent molecules merely perturbed by a crystalline environment. They form a large and important class of solids including ices of atmospheric species, drugs, explosives, and even some organic optoelectronic materials and supramolecular assemblies. Recently, surprisingly simple yet extremely efficient, versatile, easily implemented, and systematically accurate electronic structure methods for molecular crystals have been developed. The methods, collectively referred to as the embedded-fragment scheme, divide a crystal into monomers and overlapping dimers and apply modern molecular electronic structure methods and software to these fragments of the crystal that are embedded in a self-consistently determined crystalline electrostatic field. They enable facile applications of accurate but otherwise prohibitively expensive ab initio molecular orbital theories such as Møller-Plesset perturbation and coupled-cluster theories to a broad range of properties of solids such as internal energies, enthalpies, structures, equation of state, phonon dispersion curves and density of states, infrared and Raman spectra (including band intensities and sometimes anharmonic effects), inelastic neutron scattering spectra, heat capacities, Gibbs energies, and phase diagrams, while accounting for many-body electrostatic (namely, induction or polarization) effects as well as two-body exchange and dispersion interactions from first principles. They can fundamentally alter the role of computing in the studies of molecular crystals in the same way ab initio molecular orbital theories have transformed research practices in gas-phase physical chemistry and synthetic chemistry in the last half century. In this Account, after a brief summary of formalisms and algorithms, we discuss applications of these methods performed in our group as compelling

  9. Molecular structures in the charmonium spectrum: the XYZ puzzle

    NASA Astrophysics Data System (ADS)

    Ortega, P. G.; Entem, D. R.; Fernández, F.

    2013-06-01

    We study in the framework of a constituent quark model the possible contributions of molecular structures to the XYZ charmonium-like states. We analyze simultaneously the c\\bar{c} structures and the possible molecular components in the coupled channel formalism. In the 1++ sector two states appear which could be identified with X(3872) and X(3940). The recently confirmed X(3915) state appears as a mixture of c\\bar{c} and D\\bar{D} components as a JPC = 0++ state in agreement with the new measurements. A second broad resonance which may correspond with the so-called Y(3940) state is found with these quantum numbers. In the JPC = 1-- sector we also found significant contributions of the molecular structures which may affect the phenomenology. In particular the study allows us to understand the G(3900) state recently observed in Belle and BaBar. All these resonances together with the prediction of the model of a c\\bar{c} structure for Z(3930) provide a reasonable scenario for the so-called XYZ states with masses near 3.9 GeV.

  10. Molecular structure in soil humic substances: The new view

    SciTech Connect

    Sutton, Rebecca; Sposito, Garrison

    2005-04-21

    A critical examination of published data obtained primarily from recent nuclear magnetic resonance spectroscopy, X-ray absorption near-edge structure spectroscopy, electrospray ionization-mass spectrometry, and pyrolysis studies reveals an evolving new view of the molecular structure of soil humic substances. According to the new view, humic substances are collections of diverse, relatively low molecular mass components forming dynamic associations stabilized by hydrophobic interactions and hydrogen bonds. These associations are capable of organizing into micellar structures in suitable aqueous environments. Humic components display contrasting molecular motional behavior and may be spatially segregated on a scale of nanometers. Within this new structural context, these components comprise any molecules intimately associated with a humic substance, such that they cannot be separated effectively by chemical or physical methods. Thus biomolecules strongly bound within humic fractions are by definition humic components, a conclusion that necessarily calls into question key biogeochemical pathways traditionally thought to be required for the formation of humic substances. Further research is needed to elucidate the intermolecular interactions that link humic components into supramolecular associations and to establish the pathways by which these associations emerge from the degradation of organic litter.

  11. Enhanced Molecular Mobility of Ordinarily Structured Regions Drives Polyglutamine Disease*

    PubMed Central

    Lupton, Christopher J.; Steer, David L.; Wintrode, Patrick L.; Bottomley, Stephen P.; Hughes, Victoria A.; Ellisdon, Andrew M.

    2015-01-01

    Polyglutamine expansion is a hallmark of nine neurodegenerative diseases, with protein aggregation intrinsically linked to disease progression. Although polyglutamine expansion accelerates protein aggregation, the misfolding process is frequently instigated by flanking domains. For example, polyglutamine expansion in ataxin-3 allosterically triggers the aggregation of the catalytic Josephin domain. The molecular mechanism that underpins this allosteric aggregation trigger remains to be determined. Here, we establish that polyglutamine expansion increases the molecular mobility of two juxtaposed helices critical to ataxin-3 deubiquitinase activity. Within one of these helices, we identified a highly amyloidogenic sequence motif that instigates aggregation and forms the core of the growing fibril. Critically, by mutating residues within this key region, we decrease local structural fluctuations to slow ataxin-3 aggregation. This provides significant insight, down to the molecular level, into how polyglutamine expansion drives aggregation and explains the positive correlation between polyglutamine tract length, protein aggregation, and disease severity. PMID:26260925

  12. Study of the structuring of pure molecular liquids

    NASA Astrophysics Data System (ADS)

    Letamendia, L.; Duplessix, R.; Nouchi, G.; Vaucamps, C.

    Recent experiments have shown that changes in the slope of specific heat variation as a function of temperature in liquids are not always regular. In this study, the authors consider the possibility that fluid structure can change with temperature, by shifting from one form to another. They study such molecular liquids as benzene, hexafluorobenzene, and quinoleine using Rayleigh-Brillouin and depolarized Rayleigh diffusion, and total intensity diffusion. The authors clearly found anomalies for all collective properties of the medium in the liquids studied, though purely molecular properties were undisturbed. The accidents observed occurred at the same temperatures, whatever the collective or intermolecular property under study. But it took some time (several hours) for them to manifest themselves, which suggests that molecular liquids are characterized by a long thermodynamic equilibrium. Results also show a disturbance in hydrodynamic state at accident temperatures, which are similar to those generated by long spatial correlation processes.

  13. Molecular docking and structure-based drug design strategies.

    PubMed

    Ferreira, Leonardo G; Dos Santos, Ricardo N; Oliva, Glaucius; Andricopulo, Adriano D

    2015-07-22

    Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of novel promising compounds. Broadly used in modern drug design, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets. This approach also estimates the ligand-receptor binding free energy by evaluating critical phenomena involved in the intermolecular recognition process. Today, as a variety of docking algorithms are available, an understanding of the advantages and limitations of each method is of fundamental importance in the development of effective strategies and the generation of relevant results. The purpose of this review is to examine current molecular docking strategies used in drug discovery and medicinal chemistry, exploring the advances in the field and the role played by the integration of structure- and ligand-based methods.

  14. Solution structures and molecular interactions of selective melanocortin receptor antagonists.

    PubMed

    Lee, Chul-Jin; Yun, Ji-Hye; Lim, Sung-Kil; Lee, Weontae

    2010-12-01

    The solution structures and inter-molecular interaction of the cyclic melanocortin antagonists SHU9119, JKC363, HS014, and HS024 with receptor molecules have been determined by NMR spectroscopy and molecular modeling. While SHU9119 is known as a nonselective antagonist, JKC363, HS014, and HS024 are selective for the melanocortin subtype-4 receptor (MC4R) involved in modulation of food intake. Data from NMR and molecular dynamics suggest that the conformation of the Trp9 sidechain in the three MC4R-selective antagonists is quite different from that of SHU9119. This result strongly supports the concept that the spatial orientation of the hydrophobic aromatic residue is more important for determining selectivity than the presence of a basic, "arginine-like" moiety responsible for biological activity. We propose that the conformation of hydrophobic residues of MCR antagonists is critical for receptor-specific selectivity.

  15. Molecular spectroscopy and molecular structure - Selected communications presented at the 1st International Turkish Congress on Molecular Spectroscopy (TURCMOS 2013)

    NASA Astrophysics Data System (ADS)

    Durig, James R.; Fausto, Rui; Ünsalan, Ozan; Bayarı, Sevgi; Kuş, Nihal; Ildız, Gülce Ö.

    2016-01-01

    The First International Turkish Congress on Molecular Spectroscopy (TURCMOS 2013) took place at the Harbiye Cultural Center & Museum, Istanbul, Turkey, September 15-20, 2013. The main aim of the congress was to encourage the exchange of scientific ideas and collaborations all around the world, introduce new techniques and instruments, and discuss recent developments in the field of molecular spectroscopy. Among the different subjects covered, particular emphasis was given to the relevance of spectroscopy to elucidate details of the molecular structure and the chemical and physical behavior of systems ranging from simple molecules to complex biochemical molecules. Besides experimental spectroscopic approaches, related computational and theoretical methods were also considered. In this volume, selected contributions presented at the congress were put together.

  16. Structural and Molecular Modeling Features of P2X Receptors

    PubMed Central

    Alves, Luiz Anastacio; da Silva, João Herminio Martins; Ferreira, Dinarte Neto Moreira; Fidalgo-Neto, Antonio Augusto; Teixeira, Pedro Celso Nogueira; de Souza, Cristina Alves Magalhães; Caffarena, Ernesto Raúl; de Freitas, Mônica Santos

    2014-01-01

    Currently, adenosine 5′-triphosphate (ATP) is recognized as the extracellular messenger that acts through P2 receptors. P2 receptors are divided into two subtypes: P2Y metabotropic receptors and P2X ionotropic receptors, both of which are found in virtually all mammalian cell types studied. Due to the difficulty in studying membrane protein structures by X-ray crystallography or NMR techniques, there is little information about these structures available in the literature. Two structures of the P2X4 receptor in truncated form have been solved by crystallography. Molecular modeling has proven to be an excellent tool for studying ionotropic receptors. Recently, modeling studies carried out on P2X receptors have advanced our knowledge of the P2X receptor structure-function relationships. This review presents a brief history of ion channel structural studies and shows how modeling approaches can be used to address relevant questions about P2X receptors. PMID:24637936

  17. Improving structure-based function prediction using molecular dynamics

    PubMed Central

    Glazer, Dariya S.; Radmer, Randall J.; Altman, Russ B.

    2009-01-01

    Summary The number of molecules with solved three-dimensional structure but unknown function is increasing rapidly. Particularly problematic are novel folds with little detectable similarity to molecules of known function. Experimental assays can determine the functions of such molecules, but are time-consuming and expensive. Computational approaches can identify potential functional sites; however, these approaches generally rely on single static structures and do not use information about dynamics. In fact, structural dynamics can enhance function prediction: we coupled molecular dynamics simulations with structure-based function prediction algorithms that identify Ca2+ binding sites. When applied to 11 challenging proteins, both methods showed substantial improvement in performance, revealing 22 more sites in one case and 12 more in the other, with a modest increase in apparent false positives. Thus, we show that treating molecules as dynamic entities improves the performance of structure-based function prediction methods. PMID:19604472

  18. Graph Theoretical Representation of Atomic Asymmetry and Molecular Chirality of Benzenoids in Two-Dimensional Space

    PubMed Central

    Zhao, Tanfeng; Zhang, Qingyou; Long, Hailin; Xu, Lu

    2014-01-01

    In order to explore atomic asymmetry and molecular chirality in 2D space, benzenoids composed of 3 to 11 hexagons in 2D space were enumerated in our laboratory. These benzenoids are regarded as planar connected polyhexes and have no internal holes; that is, their internal regions are filled with hexagons. The produced dataset was composed of 357,968 benzenoids, including more than 14 million atoms. Rather than simply labeling the huge number of atoms as being either symmetric or asymmetric, this investigation aims at exploring a quantitative graph theoretical descriptor of atomic asymmetry. Based on the particular characteristics in the 2D plane, we suggested the weighted atomic sum as the descriptor of atomic asymmetry. This descriptor is measured by circulating around the molecule going in opposite directions. The investigation demonstrates that the weighted atomic sums are superior to the previously reported quantitative descriptor, atomic sums. The investigation of quantitative descriptors also reveals that the most asymmetric atom is in a structure with a spiral ring with the convex shape going in clockwise direction and concave shape going in anticlockwise direction from the atom. Based on weighted atomic sums, a weighted F index is introduced to quantitatively represent molecular chirality in the plane, rather than merely regarding benzenoids as being either chiral or achiral. By validating with enumerated benzenoids, the results indicate that the weighted F indexes were in accordance with their chiral classification (achiral or chiral) over the whole benzenoids dataset. Furthermore, weighted F indexes were superior to previously available descriptors. Benzenoids possess a variety of shapes and can be extended to practically represent any shape in 2D space—our proposed descriptor has thus the potential to be a general method to represent 2D molecular chirality based on the difference between clockwise and anticlockwise sums around a molecule. PMID:25032832

  19. Salient point region covariance descriptor for target tracking

    NASA Astrophysics Data System (ADS)

    Cakir, Serdar; Aytaç, Tayfun; Yildirim, Alper; Beheshti, Soosan; Gerek, Ö. Nezih; Cetin, A. Enis

    2013-02-01

    Features extracted at salient points are used to construct a region covariance descriptor (RCD) for target tracking. In the classical approach, the RCD is computed by using the features at each pixel location, which increases the computational cost in many cases. This approach is redundant because image statistics do not change significantly between neighboring image pixels. Furthermore, this redundancy may decrease tracking accuracy while tracking large targets because statistics of flat regions dominate region covariance matrix. In the proposed approach, salient points are extracted via the Shi and Tomasi's minimum eigenvalue method over a Hessian matrix, and the RCD features extracted only at these salient points are used in target tracking. Experimental results indicate that the salient point RCD scheme provides comparable and even better tracking results compared to a classical RCD-based approach, scale-invariant feature transform, and speeded-up robust features-based trackers while providing a computationally more efficient structure.

  20. Structures of polycyclic aromatic hydrocarbon adducts by molecular mechanics and molecular dynamics simulations

    SciTech Connect

    Singh, S.B.

    1992-01-01

    The structures of the adducts of (+)- and (-)trans-7,8,dihydroxy-anti-9,10-epoxy-7,8,9,10-tetrahydrobenzo (a)pyrene (anti-BPDE) formed by trans addition to N[sup 2] of guanine have been of great interest because the high biological activity of BPDE in mammalian mutagenesis and tumorigenesis has been attributed to the predominant (+)-adduct, while the (-)-adduct is inactive. Molecular mechanics and dynamics calculations have been employed to elucidate the structural difference between this mirror image adduct pair in a duplex dodecamer, d(5' GCGCGCG-(BPDE)CGCGC3') [center dot] d(5'GCGCGCGCGCGC3'). Minimized potential energy calculations using the program DUPLEX were employed to locate starting structures for the dynamics. Three types of structures were found in the energy minimized conformation space searches for each enantiomer: pyrenyl moiety in the minor groove of a Watson-Crick base paired B-DNA duplex, pyrenyl moiety in the major groove of a B-DNA duplex with syn guanine and Hoogsteen base pairs at the modification site, and intercalation type structures. The minor groove structure is energetically preferred for the (+) enantiomer while both minor groove and major groove structures are favored and of comparable energy in the (-) enantiomer. These energy-minimized duplex dodecamers, as well as an unmodified B-DNA control of the same sequence, were subjected to 100 ps molecular dynamics simulations with solvent and salt with the program AMBER. The duplex dodecamer, d(CGCGAATTCGCG)[sub 2], was subjected to a similar simulation using the crystal structure as starting coordinates. Detailed analysis of the dynamic evolution of the conformational and the helical parameters of all the dodecamer simulations were carried out with Molecular Dynamics Analysis Toolchest.

  1. 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

  2. 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.

  3. Complex correlation measure: a novel descriptor for Poincaré plot.

    PubMed

    Karmakar, Chandan K; Khandoker, Ahsan H; Gubbi, Jayavardhana; Palaniswami, Marimuthu

    2009-08-13

    Poincaré plot is one of the important techniques used for visually representing the heart rate variability. It is valuable due to its ability to display nonlinear aspects of the data sequence. However, the problem lies in capturing temporal information of the plot quantitatively. The standard descriptors used in quantifying the Poincaré plot (SD1, SD2) measure the gross variability of the time series data. Determination of advanced methods for capturing temporal properties pose a significant challenge. In this paper, we propose a novel descriptor "Complex Correlation Measure (CCM)" to quantify the temporal aspect of the Poincaré plot. In contrast to SD1 and SD2, the CCM incorporates point-to-point variation of the signal. First, we have derived expressions for CCM. Then the sensitivity of descriptors has been shown by measuring all descriptors before and after surrogation of the signal. For each case study, lag-1 Poincaré plots were constructed for three groups of subjects (Arrhythmia, Congestive Heart Failure (CHF) and those with Normal Sinus Rhythm (NSR)), and the new measure CCM was computed along with SD1 and SD2. ANOVA analysis distribution was used to define the level of significance of mean and variance of SD1, SD2 and CCM for different groups of subjects. CCM is defined based on the autocorrelation at different lags of the time series, hence giving an in depth measurement of the correlation structure of the Poincaré plot. A surrogate analysis was performed, and the sensitivity of the proposed descriptor was found to be higher as compared to the standard descriptors. Two case studies were conducted for recognizing arrhythmia and congestive heart failure (CHF) subjects from those with NSR, using the Physionet database and demonstrated the usefulness of the proposed descriptors in biomedical applications. CCM was found to be a more significant (p = 6.28E-18) parameter than SD1 and SD2 in discriminating arrhythmia from NSR subjects. In case of assessing

  4. Liver specificity of the carcinogenicity of NOCs: a chemical-molecular perspective.

    PubMed

    Yuan, Jintao; Pu, Yuepu; Yin, Lihong

    2012-11-19

    This study aimed to determine the most significant molecular features associated with the liver specificity of the carcinogenicity of N-nitroso compounds (NOCs). Accordingly, quantitative structure-activity relationship (QSAR) analysis was performed to extract molecular information from NOCs using a topological substructural molecular descriptor (TOPS-MODE) approach. A linear discriminant analysis (LDA) model of a series of NOCs for rat liver was developed using TOPS-MODE descriptors to predict nonliver- and liver-carcinogenic NOCs. Two descriptors exclusively calculated from the molecular structures of the compounds were selected by a genetic algorithm. The descriptors were then weighted with bond distances as well as the Abraham solute descriptor partition between water and aqueous solvent systems to indicate the importance of their roles in liver specificity. The performances of the LDA model were rigorously validated by leave-one-out cross-validation and external validation, with the prediction accuracy reaching 88.3% and 80.0%, respectively. The contributions of the different molecular fragments to rat-liver specificity were computed. The results served as important information related to liver specificity and were analyzed from the chemical-molecular perspective. The resulting model can provide an efficient method to discriminate between as well as extrapolate nonliver- and liver-carcinogenic NOCs. The contribution of the entire nitrosamine molecule was determined as being responsible for the liver specificity of nitrosamine carcinogenicity. Although the QSAR showed limitations in complex hepatocarcinogenicity, the proposed method may considerably help elucidate the role of nitrosamines in liver specificity from the chemical-molecular perspective. The nature of these enzyme-substrate interactions is characterized. Insight into the chemical-structural and biological factors related to the liver-specific biological activity of NOCs is also provided.

  5. The Importance of Discerning Shape in Molecular Pharmacology

    PubMed Central

    Kortagere, Sandhya; Krasowski, Matthew D.; Ekins, Sean

    2010-01-01

    Shape is a fundamentally important molecular feature that often determines the fate of a compound in terms of molecular interactions with preferred and non-preferred biological targets. Complementarity of binding in small molecule-protein, peptide-receptor, antigen-antibody and protein-protein interactions is key to life and survival, but also to targeting molecules with bioactivity. We review the application of shape in various biological systems such as substrate recognition, ligand specificity / selectivity and antibody recognition in the context of computational methods such as docking, quantitative structure activity relationships, classification models and similarity search algorithms. These in silico pharmacology methods have recently demonstrated the importance and applicability of determining molecular shape in drug discovery, virtual screening and predictive toxicology. The results from recently published studies show that shape and shape-based descriptors are at least as useful as other traditional molecular descriptors. PMID:19187977

  6. Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors.

    PubMed

    da Silva, Núbia Rosa; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez

    2015-01-01

    The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.

  7. Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors

    PubMed Central

    da Silva, Núbia Rosa; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez

    2015-01-01

    The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification. PMID:26091501

  8. Molecular modelling of miraculin: Structural analyses and functional hypotheses.

    PubMed

    Paladino, Antonella; Costantini, Susan; Colonna, Giovanni; Facchiano, Angelo M

    2008-02-29

    Miraculin is a plant protein that displays the peculiar property of modifying taste by swiching sour into a sweet taste. Its monomer is flavourless at all pH as well as at high concentration; the dimer form elicits its taste-modifying activity at acidic pH; a tetrameric form is also reported as active. Two histidine residues, located in exposed regions, are the main responsible of miraculin activity, as demonstrated by mutagenesis studies. Since structural data of miraculin are not available, we have predicted its three-dimensional structure and simulated both its dimer and tetramer forms by comparative modelling and molecular docking techniques. Finally, molecular dynamics simulations at different pH conditions have indicated that at acidic pH the dimer assumes a widely open conformation, in agreement with the hypotheses coming from other studies.

  9. Molecular solutes in ionic liquids: a structural perspective.

    PubMed

    Pádua, Agílio A H; Costa Gomes, Margarida F; Canongia Lopes, José N A

    2007-11-01

    Understanding physicochemical properties of ionic liquids is important for their rational use in extractions, reactions, and other applications. Ionic liquids are not simple fluids: their ions are generally asymetric, flexible, with delocalized electrostatic charges, and available in a wide variety. It is difficult to capture their subtle properties with models that are too simplistic. Molecular simulation using atomistic force fields, which describe structures and interactions in detail, is an excellent tool to gain insights into their liquid-state organization, how they solvate different compounds, and what molecular factors determine their properties. The identification of certain ionic liquids as self-organized phases, with aggregated nonpolar and charged domains, provides a new way to interpret the solvation and structure of their mixtures. Many advances are the result of a successful interplay between experiment and modeling, possible in this field where none of the two methodologies had a previous advance.

  10. Toxicological implications of esterases-From molecular structures to functions

    SciTech Connect

    Satoh, Tetsuo . E-mail: satohbri@peach.ifnet.or.jp

    2005-09-01

    This article reports on a keynote lecture at the 10th International Congress of Toxicology sponsored by the International Union of Toxicology and held on July 2004. Current developments in molecular-based studies into the structure and function of cholinesterases, carboxylesterases, and paraoxonases are described. This article covers mechanisms of regulation of gene expression of the various esterases by developmental factors and xenobiotics, as well as the interplay between physiological and chemical regulation of the enzyme activity.

  11. Rattlesnake Neurotoxin Structure, Mechanism of Action, Immunology and Molecular Biology

    DTIC Science & Technology

    1990-09-01

    from the venom of the midget faded . rattlesnake (Crotalus viridis concolor . Toxicon 2&, 319- 323. Rehm, H. and Betz, H. (1982) Binding of B...8217determined. It was shown to have great similarity to the basic subunits of related toxins from the venoms of the South American and midget faded ...AD-A228 003 CONTRACT NO.: DAMD17-89-C-9007 TITLE: RATTLESNAKE NEUROTOXIN STRUCTURE, MECHANISM OF ACTION, IMMUNOLOGY AND MOLECULAR BIOLOGY PRINCIPAL

  12. Optimization techniques in molecular structure and function elucidation.

    PubMed

    Sahinidis, Nikolaos V

    2009-12-01

    This paper discusses recent optimization approaches to the protein side-chain prediction problem, protein structural alignment, and molecular structure determination from X-ray diffraction measurements. The machinery employed to solve these problems has included algorithms from linear programming, dynamic programming, combinatorial optimization, and mixed-integer nonlinear programming. Many of these problems are purely continuous in nature. Yet, to this date, they have been approached mostly via combinatorial optimization algorithms that are applied to discrete approximations. The main purpose of the paper is to offer an introduction and motivate further systems approaches to these problems.

  13. Nanoparticle Probes for Structural and Functional Photoacoustic Molecular Tomography

    PubMed Central

    Chen, Haobin; Yuan, Zhen; Wu, Changfeng

    2015-01-01

    Nowadays, nanoparticle probes have received extensive attention largely due to its potential biomedical applications in structural, functional, and molecular imaging. In addition, photoacoustic tomography (PAT), a method based on the photoacoustic effect, is widely recognized as a robust modality to evaluate the structure and function of biological tissues with high optical contrast and high acoustic resolution. The combination of PAT with nanoparticle probes holds promises for detecting and imaging diseased tissues or monitoring their treatments with high sensitivity. This review will introduce the recent advances in the emerging field of nanoparticle probes and their preclinical applications in PAT, as well as relevant perspectives on future development. PMID:26609534

  14. FilFinder: Filamentary structure in molecular clouds

    NASA Astrophysics Data System (ADS)

    Koch, Eric W.; Rosolowsky, Erik W.

    2016-08-01

    FilFinder extracts and analyzes filamentary structure in molecular clouds. In particular, it is capable of uniformly extracting structure over a large dynamical range in intensity. It returns the main filament properties: local amplitude and background, width, length, orientation and curvature. FilFinder offers additional tools to, for example, create a filament-only image based on the properties of the radial fits. The resulting mask and skeletons may be saved in FITS format, and property tables may be saved as a CSV, FITS or LaTeX table.

  15. Reproducibility of the NEPTUNE descriptor-based scoring system on whole-slide images and histologic and ultrastructural digital images.

    PubMed

    Barisoni, Laura; Troost, Jonathan P; Nast, Cynthia; Bagnasco, Serena; Avila-Casado, Carmen; Hodgin, Jeffrey; Palmer, Matthew; Rosenberg, Avi; Gasim, Adil; Liensziewski, Chrysta; Merlino, Lino; Chien, Hui-Ping; Chang, Anthony; Meehan, Shane M; Gaut, Joseph; Song, Peter; Holzman, Lawrence; Gibson, Debbie; Kretzler, Matthias; Gillespie, Brenda W; Hewitt, Stephen M

    2016-07-01

    The multicenter Nephrotic Syndrome Study Network (NEPTUNE) digital pathology scoring system employs a novel and comprehensive methodology to document pathologic features from whole-slide images, immunofluorescence and ultrastructural digital images. To estimate inter- and intra-reader concordance of this descriptor-based approach, data from 12 pathologists (eight NEPTUNE and four non-NEPTUNE) with experience from training to 30 years were collected. A descriptor reference manual was generated and a webinar-based protocol for consensus/cross-training implemented. Intra-reader concordance for 51 glomerular descriptors was evaluated on jpeg images by seven NEPTUNE pathologists scoring 131 glomeruli three times (Tests I, II, and III), each test following a consensus webinar review. Inter-reader concordance of glomerular descriptors was evaluated in 315 glomeruli by all pathologists; interstitial fibrosis and tubular atrophy (244 cases, whole-slide images) and four ultrastructural podocyte descriptors (178 cases, jpeg images) were evaluated once by six and five pathologists, respectively. Cohen's kappa for inter-reader concordance for 48/51 glomerular descriptors with sufficient observations was moderate (0.40descriptors based on similar pathologic features improved concordance. Concordance was independent of years of experience, and increased with webinar cross-training. Excellent concordance was achieved for interstitial fibrosis and tubular atrophy. Moderate-to-excellent concordance was achieved for all ultrastructural podocyte descriptors, with good-to-excellent concordance for descriptors commonly used in clinical practice, foot process effacement, and microvillous transformation. NEPTUNE digital pathology scoring system enables novel morphologic profiling of renal structures. For all histologic and ultrastructural descriptors tested with

  16. Reproducibility of the NEPTUNE descriptor-based scoring system on whole-slide images and histologic and ultrastructural digital images

    PubMed Central

    Barisoni, Laura; Troost, Jonathan P; Nast, Cynthia; Bagnasco, Serena; Avila-Casado, Carmen; Hodgin, Jeffrey; Palmer, Matthew; Rosenberg, Avi; Gasim, Adil; Liensziewski, Chrysta; Merlino, Lino; Chien, Hui-Ping; Chang, Anthony; Meehan, Shane M; Gaut, Joseph; Song, Peter; Holzman, Lawrence; Gibson, Debbie; Kretzler, Matthias; Gillespie, Brenda W; Hewitt, Stephen M

    2017-01-01

    The multicenter Nephrotic Syndrome Study Network (NEPTUNE) digital pathology scoring system employs a novel and comprehensive methodology to document pathologic features from whole-slide images, immunofluorescence and ultrastructural digital images. To estimate inter- and intra-reader concordance of this descriptor-based approach, data from 12 pathologists (eight NEPTUNE and four non-NEPTUNE) with experience from training to 30 years were collected. A descriptor reference manual was generated and a webinar-based protocol for consensus/cross-training implemented. Intra-reader concordance for 51 glomerular descriptors was evaluated on jpeg images by seven NEPTUNE pathologists scoring 131 glomeruli three times (Tests I, II, and III), each test following a consensus webinar review. Inter-reader concordance of glomerular descriptors was evaluated in 315 glomeruli by all pathologists; interstitial fibrosis and tubular atrophy (244 cases, whole-slide images) and four ultrastructural podocyte descriptors (178 cases, jpeg images) were evaluated once by six and five pathologists, respectively. Cohen’s kappa for inter-reader concordance for 48/51 glomerular descriptors with sufficient observations was moderate (0.40descriptors based on similar pathologic features improved concordance. Concordance was independent of years of experience, and increased with webinar cross-training. Excellent concordance was achieved for interstitial fibrosis and tubular atrophy. Moderate-to-excellent concordance was achieved for all ultrastructural podocyte descriptors, with good-to-excellent concordance for descriptors commonly used in clinical practice, foot process effacement, and microvillous transformation. NEPTUNE digital pathology scoring system enables novel morphologic profiling of renal structures. For all histologic and ultrastructural descriptors tested with

  17. Aggregating local image descriptors into compact codes.

    PubMed

    Jégou, Hervé; Perronnin, Florent; Douze, Matthijs; Sánchez, Jorge; Pérez, Patrick; Schmid, Cordelia

    2012-09-01

    This paper addresses the problem of large-scale image search. Three constraints have to be taken into account: search accuracy, efficiency, and memory usage. We first present and evaluate different ways of aggregating local image descriptors into a vector and show that the Fisher kernel achieves better performance than the reference bag-of-visual words approach for any given vector dimension. We then jointly optimize dimensionality reduction and indexing in order to obtain a precise vector comparison as well as a compact representation. The evaluation shows that the image representation can be reduced to a few dozen bytes while preserving high accuracy. Searching a 100 million image data set takes about 250 ms on one processor core.

  18. Making texture descriptors invariant to blur.

    PubMed

    Gadermayr, Michael; Uhl, Andreas

    Besides a high distinctiveness, robustness (or invariance) to image degradations is very desirable for texture feature extraction methods in real-world applications. In this paper, focus is on making arbitrary texture descriptors invariant to blur which is often prevalent in real image data. From previous work, we know that most state-of-the-art texture feature extraction methods are unable to cope even with minor blur degradations if the classifier's training stage is based on idealistic data. However, if the training set suffers similarly from the degradations, the obtained accuracies are significantly higher. Exploiting that knowledge, in this approach the level of blur of each image is increased to a certain threshold, based on the estimation of a blur measure. Experiments with synthetically degraded data show that the method is able to generate a high degree of blur invariance without loosing too much distinctiveness. Finally, we show that our method is not limited to ideal Gaussian blur.

  19. Structural Modeling and Molecular Dynamics Simulation of the Actin Filament

    SciTech Connect

    Splettstoesser, Thomas; Holmes, Kenneth; Noe, Frank; Smith, Jeremy C

    2011-01-01

    Actin is a major structural protein of the eukaryotic cytoskeleton and enables cell motility. Here, we present a model of the actin filament (F-actin) that not only incorporates the global structure of the recently published model by Oda et al. but also conserves internal stereochemistry. A comparison is made using molecular dynamics simulation of the model with other recent F-actin models. A number of structural determents such as the protomer propeller angle, the number of hydrogen bonds, and the structural variation among the protomers are analyzed. The MD comparison is found to reflect the evolution in quality of actin models over the last 6 years. In addition, simulations of the model are carried out in states with both ADP or ATP bound and local hydrogen-bonding differences characterized.

  20. Building a chemical space based on fragment descriptors.

    PubMed

    Baskin, Igor; Varnek, Alexandre

    2008-09-01

    This article reviews the application of fragment descriptors at different stages of virtual screening: filtering, similarity search, and direct activity assessment using QSAR/QSPR models. Several case studies are considered. It is demonstrated that the power of fragment descriptors stems from their universality, very high computational efficiency, simplicity of interpretation and versatility.

  1. Fourier descriptor features for acoustic landmine detection

    NASA Astrophysics Data System (ADS)

    Keller, James M.; Cheng, Zhanqi; Gader, Paul D.; Hocaoglu, Ali K.

    2002-08-01

    Signatures of buried landmines are often difficult to separate from those of clutter objects. Often, shape information is not directly obtainable from the sensors used for landmine detection. The Acoustic Sensing Technology (AST), which uses a Laser Doppler Vibrometer (LDV) that measures the spatial pattern of particle velocity amplitude of the ground surface in a variety of frequency bands, offers a unique look at subsurface phenomena. It directly records shape related information. Generally, after preprocessing the frequency band images in a downward looking LDV system, landmines have fairly regular shapes (roughly circular) over a range of frequencies while clutter tends to exhibit irregular shapes different from those of landmines. Therefore, shape description has the potential to be used in discriminating mines from clutter. Normalized Fourier Descriptors (NFD) are shape parameters independent of size, angular orientation, position, and contour starting conditions. In this paper, the stack of 2D frequency images from the LDV system are preprocessed by a linear combination of order statistics (LOS) filter, thresholding, and 2D and 3D connected labeling. Contours are extracted form the connected components and aggregated to produce evenly spaced boundary points. Two types of Normalized Fourier Descriptors are computed from the outlines. Using images obtained from a standard data collection site, these features are analyzed for their ability to discriminate landmines from background and clutter such as wood and stones. From a standard feature selection procedure, it was found that a very small number of features are required to effectively separate landmines from background and clutter using simple pattern recognition algorithms. Details of the experiments are included.

  2. Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

    PubMed Central

    Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

    2010-01-01

    Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

  3. An orientation sensitive approach in biomolecule interaction quantitative structure-activity relationship modeling and its application in ion-exchange chromatography.

    PubMed

    Kittelmann, Jörg; Lang, Katharina M H; Ottens, Marcel; Hubbuch, Jürgen

    2017-01-27

    Quantitative structure-activity relationship (QSAR) modeling for prediction of biomolecule parameters has become an established technique in chromatographic purification process design. Unfortunately available descriptor sets fail to describe the orientation of biomolecules and the effects of ionic strength in the mobile phase on the interaction with the stationary phase. The literature describes several special descriptors used for chromatographic retention modeling, all of these do not describe the screening of electrostatic potential by the mobile phase in use. In this work we introduce two new approaches of descriptor calculations, namely surface patches and plane projection, which capture an oriented binding to charged surfaces and steric hindrance of the interaction with chromatographic ligands with regard to electrostatic potential screening by mobile phase ions. We present the use of the developed descriptor sets for predictive modeling of Langmuir isotherms for proteins at different pH values between pH 5 and 10 and varying ionic strength in the range of 10-100mM. The resulting model has a high correlation of calculated descriptors and experimental results, with a coefficient of determination of 0.82 and a predictive coefficient of determination of 0.92 for unknown molecular structures and conditions. The agreement of calculated molecular interaction orientations with both, experimental results as well as molecular dynamic simulations from literature is shown. The developed descriptors provide the means for improved QSAR models of chromatographic processes, as they reflect the complex interactions of biomolecules with chromatographic phases.

  4. Molecular structures of amyloid and prion fibrils: consensus versus controversy.

    PubMed

    Tycko, Robert; Wickner, Reed B

    2013-07-16

    Many peptides and proteins self-assemble into amyloid fibrils. Examples include mammalian and fungal prion proteins, polypeptides associated with human amyloid diseases, and proteins that may have biologically functional amyloid states. To understand the propensity for polypeptides to form amyloid fibrils and to facilitate rational design of amyloid inhibitors and imaging agents, it is necessary to elucidate the molecular structures of these fibrils. Although fibril structures were largely mysterious 15 years ago, a considerable body of reliable structural information about amyloid fibril structures now exists, with essential contributions from solid state nuclear magnetic resonance (NMR) measurements. This Account reviews results from our laboratories and discusses several structural issues that have been controversial. In many cases, the amino acid sequences of amyloid fibrils do not uniquely determine their molecular structures. Self-propagating, molecular-level polymorphism complicates the structure determination problem and can lead to apparent disagreements between results from different laboratories, particularly when different laboratories study different polymorphs. For 40-residue β-amyloid (Aβ₁₋₄₀) fibrils associated with Alzheimer's disease, we have developed detailed structural models from solid state NMR and electron microscopy data for two polymorphs. These polymorphs have similar peptide conformations, identical in-register parallel β-sheet organizations, but different overall symmetry. Other polymorphs have also been partially characterized by solid state NMR and appear to have similar structures. In contrast, cryo-electron microscopy studies that use significantly different fibril growth conditions have identified structures that appear (at low resolution) to be different from those examined by solid state NMR. Based on solid state NMR and electron paramagnetic resonance (EPR) measurements, the in-register parallel β-sheet organization

  5. Synthesis, XRD crystal structure, spectroscopic characterization, local reactive properties using DFT and molecular dynamics simulations and molecular docking study of (E)-1-(4-bromophenyl)-3-(4-(trifluoromethoxy)phenyl)prop-2-en-1-one

    NASA Astrophysics Data System (ADS)

    Arshad, Suhana; Raveendran Pillai, Renjith; Zainuri, Dian Alwani; Khalib, Nuridayanti Che; Razak, Ibrahim Abdul; Armaković, Stevan; Armaković, Sanja J.; Renjith, Rishikesh; Panicker, C. Yohannan; Van Alsenoy, C.

    2017-06-01

    In the present study, the title compound named as (E)-1-(4-bromophenyl)-3-(4-(trifluoromethoxy)phenyl)prop-2-en-1-one was synthesized and structurally characterized by single-crystal X-ray diffraction. The FT-IR spectrum was recorded and interpreted in details with the aid of Density Functional Theory (DFT) calculations and Potential Energy Distribution (PED) analysis. Average local ionization energies (ALIE) and Fukui functions have been used as quantum-molecular descriptors to locate the molecule sites that could be of importance from the aspect of reactivity. Degradation properties have been assessed by calculations of bond dissociation energies (BDE) for hydrogen abstraction and the rest of the single acyclic bonds, while molecular dynamics (MD) simulations were used in order to calculate radial distribution functions and determine the atoms with significant interactions with water. In order to understand how the title molecule inhibits and hence increases the catalytic efficiency of MOA-B enzyme, molecular docking study was performed to fit the title compound into the binding site of MOA-B enzyme.

  6. Importance of structural information in predicting human acute toxicity from in vitro cytotoxicity data

    SciTech Connect

    Lee, Soyoung; Park, Keunwan; Ahn, Hee-Sung; Kim, Dongsup

    2010-07-15

    In this study, we tried to assess the utility of the structural information of drugs for predicting human acute toxicity from in vitro basal cytotoxicity, and to interpret the informative quality and the pharmacokinetic meaning of each structural descriptor. For this, human acute toxicity data of 67 drugs were taken from literature with their basal cytotoxicity data, and used to develop predictive models. A series of multiple linear regression analyses were performed to construct feasible regression models by combining molecular descriptors and cytotoxicity data. We found that although the molecular descriptors alone had only moderate correlation with human acute toxicity, they were highly useful for explaining the discrepancy between in vitro cytotoxicity and human acute toxicity. Among many possible models, we selected the most explanatory models by changing the number and the type of combined molecular descriptors. The results showed that our selected models had high predictive power (R{sup 2}: between 0.7 and 0.87). Our analysis indicated that those successful models increased the prediction accuracies by providing the information on human pharmacokinetic parameters which are the major reason for the difference between human acute toxicity and cytotoxicity. In addition, we performed a clustering analysis on selected molecular descriptors to assess their informative qualities. The results indicated that the number of single bonds, the number of hydrogen bond donors and valence connectivity indices are closely related to linking cytotoxicity to acute toxicity, which provides insightful explanation about human toxicity beyond cytotoxicity.

  7. Local feature descriptor invariant to monotonic illumination changes

    NASA Astrophysics Data System (ADS)

    Yan, Pu; Liang, Dong; Tang, Jun; Zhu, Ming

    2016-01-01

    This paper presents a monotonic invariant intensity descriptor (MIID) via spectral embedding and nonsubsampled contourlet transform (NSCT). To make the proposed descriptor discriminative, NSCT is used for the construction of multiple support regions. Specifically, the directed graph and the spectral feature vectors of the signless Laplacian matrix are exploited to construct the MIID. We theoretically demonstrate that the proposed descriptor is able to tackle monotonic illumination changes and many other geometric and photometric transformations. We conduct extensive experiments on the standard Oxford dataset and the complex illumination dataset to demonstrate the superiority of proposed descriptor over the existing state-of-the-art descriptors in dealing with image blur, viewpoint changes, illumination changes, and JPEG compression.

  8. Local structure in anisotropic systems determined by molecular dynamics simulation

    NASA Astrophysics Data System (ADS)

    Komolkin, Andrei V.; Maliniak, Arnold

    In the present communication we describe the investigation of local structure using a new visualization technique. The approach is based on two-dimensional pair correlation functions derived from a molecular dynamics computer simulation. We have used this method to analyse a trajectory produced in a simulation of a nematic liquid crystal of 4-n-pentyl-4'-cyanobiphenyl (5CB) (Komolkin et al., 1994, J. chem. Phys., 101, 4103). The molecule is assumed to have cylindrical symmetry, and the liquid crystalline phase is treated as uniaxial. The pair correlation functions or cylindrical distribution functions (CDFs) are calculated in the molecular (m) and laboratory (l) frames, gm2(z1 2, d1 2) and g12(Z1 2, D1 2). Anisotropic molecular organization in the liquid crystal is reflected in laboratory frame CDFs. The molecular excluded volume is determined and the effect of the fast motion in the alkyl chain is observed. The intramolecular distributions are included in the CDFs and indicate the size of the motional amplitude in the chain. Absence of long range order was confirmed, a feature typical for a nematic liquid crystal.

  9. Structural characterization of polymorphs and molecular complexes of finasteride

    NASA Astrophysics Data System (ADS)

    Wawrzycka, Irena; Stȩpniak, Krystyna; Matyjaszczyk, Sławomir; Kozioł, Anna E.; Lis, Tadeusz; Abboud, Khalil A.

    1999-01-01

    The molecular structure of finasteride, 17 β-( N-tert-butylcarbamoyl)-4-aza-5 α-androst-1-en-3-one, and structures of three related crystalline forms have been determined by X-ray analysis. The rigid steroid skeleton of the molecule adopts a half-chair/chair/chair/half-chair conformation. Two peptide groups, one cyclic (lactam) in the ring A and a second being a part of the substituent at C17, are the main factors influencing intermolecular contacts. Different hydrogen-bond interactions of these hydrophilic groups are observed in the crystal structures. An infinite ribbon of finasteride molecules is formed between lactam groups in the orthorhombic homomolecular crystal ( 1) obtained from an ethanol solution. The linear molecular complex finasteride-acetic acid ( 1a) is connected by hydrogen bonds between the lactam of finasteride and the carboxyl group of acetic acid. The crystallization from an ethyl acetate solution gives a complex structure of bis-finasteride monohydrate ethyl acetate clathrate ( 1b) with guest molecule disordered in channels. Crystals of a second (monoclinic) finasteride polymorph ( 2) were obtained during thermal decomposition of 1a, and sublimation of 1, 1a and 1b. Two polymorphic forms show different IR spectra.

  10. 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.

  11. 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.

  12. Large Molecule Structures by Broadband Fourier Transform Molecular Rotational Spectroscopy

    NASA Astrophysics Data System (ADS)

    Evangelisti, Luca; Seifert, Nathan A.; Spada, Lorenzo; Pate, Brooks

    2016-06-01

    Fourier transform molecular rotational resonance spectroscopy (FT-MRR) using pulsed jet molecular beam sources is a high-resolution spectroscopy technique that can be used for chiral analysis of molecules with multiple chiral centers. The sensitivity of the molecular rotational spectrum pattern to small changes in the three dimensional structure makes it possible to identify diastereomers without prior chemical separation. For larger molecules, there is the additional challenge that different conformations of each diastereomer may be present and these need to be differentiated from the diastereomers in the spectral analysis. Broadband rotational spectra of several larger molecules have been measured using a chirped-pulse FT-MRR spectrometer. Measurements of nootkatone (C15H22O), cedrol (C15H26O), ambroxide (C16H28O) and sclareolide (C16H26O2) are presented. These spectra are measured with high sensitivity (signal-to-noise ratio near 1,000:1) and permit structure determination of the most populated isomers using isotopic analysis of the 13C and 18O isotopologues in natural abundance. The accuracy of quantum chemistry calculations to identify diastereomers and conformers and to predict the dipole moment properties needed for three wave mixing measurements is examined.

  13. DFT calculations on molecular structure, spectral analysis, multiple interactions, reactivity, NLO property and molecular docking study of flavanol-2,4-dinitrophenylhydrazone

    NASA Astrophysics Data System (ADS)

    Singh, Ravindra Kumar; Singh, Ashok Kumar

    2017-02-01

    A new flavanol-2,4-dinitrophenylhydrazone (FDNP) was synthesized and its structure was confirmed by FT-IR, FT-Raman, 1H NMR, mass spectrometry and elemental analysis. All quantum chemical calculations were carried out at level of density functional theory (DFT) with B3LYP functional using 6-311++ G (d,p) basis atomic set. UV-Vis absorption spectra for the singlet-singlet transition computed for fully optimized ground state geometry using Time-Dependent-Density Functional Theory (TD-DFT) with CAM-B3LYP functional was found to be in consistent with that of experimental findings. Analysis of vibrational (FT-IR and FT-Raman) spectrum and their assignments has been done by computing Potential Energy Distribution (PED) using Gar2ped. HOMO-LUMO analysis was performed and reactivity descriptors were calculated. Calculated global electrophilicity index (ω = 7.986 eV) shows molecule to be a strong electrophile. 1H NMR chemical shift calculated with the help of gauge-including atomic orbital (GIAO) approach shows agreement with experimental data. Various intramolecular interactions were analysed by AIM approach. DFT computed total first static hyperpolarizability (β0 = 189.03 × 10-30 esu) indicates that title molecule can be used as attractive future NLO material. Solvent induced effects on the NLO properties studied by using self-consistent reaction field (SCRF) method shows that β0 value increases with increase in solvent polarity. To study the thermal behaviour of title molecule, thermodynamic properties such as heat capacity, entropy and enthalpy change at various temperatures have been calculated and reported. Molecular docking results suggests title molecule to be a potential kinase inhibitor and might be used in future for designing of new anticancer drug.

  14. Discovering structural alerts for mutagenicity using stable emerging molecular patterns.

    PubMed

    Métivier, Jean-Philippe; Lepailleur, Alban; Buzmakov, Aleksey; Poezevara, Guillaume; Crémilleux, Bruno; Kuznetsov, Sergei O; Le Goff, Jérémie; Napoli, Amedeo; Bureau, Ronan; Cuissart, Bertrand

    2015-05-26

    This study is dedicated to the introduction of a novel method that automatically extracts potential structural alerts from a data set of molecules. These triggering structures can be further used for knowledge discovery and classification purposes. Computation of the structural alerts results from an implementation of a sophisticated workflow that integrates a graph mining tool guided by growth rate and stability. The growth rate is a well-established measurement of contrast between classes. Moreover, the extracted patterns correspond to formal concepts; the most robust patterns, named the stable emerging patterns (SEPs), can then be identified thanks to their stability, a new notion originating from the domain of formal concept analysis. All of these elements are explained in the paper from the point of view of computation. The method was applied to a molecular data set on mutagenicity. The experimental results demonstrate its efficiency: it automatically outputs a manageable number of structural patterns that are strongly related to mutagenicity. Moreover, a part of the resulting structures corresponds to already known structural alerts. Finally, an in-depth chemical analysis relying on these structures demonstrates how the method can initiate promising processes of chemical knowledge discovery.

  15. Theoretical investigation of the molecular structure of the isoquercitrin molecule

    NASA Astrophysics Data System (ADS)

    Cornard, J. P.; Boudet, A. C.; Merlin, J. C.

    1999-09-01

    Isoquercitrin is a glycosilated flavonoid that has received a great deal of attention because of its numerous biological effects. We present a theoretical study on isoquercitrin using both empirical (Molecular Mechanics (MM), with MMX force field) and quantum chemical (AM1 semiempirical method) techniques. The most stable structures of the molecule obtained by MM calculations have been used as input data for the semiempirical treatment. The position and orientation of the glucose moiety with regard to the remainder of the molecule have been investigated. The flexibility of isoquercitrin principally lies in rotations around the inter-ring bond and the sugar link. In order to know the structural modifications generated by the substitution by a sugar, geometrical parameters of quercetin (aglycon) and isoquercitrin have been compared. The good accordance between theoretical and experimental electronic spectra permits to confirm the reliability of the structural model.

  16. State of water, molecular structure, and cytotoxicity of silk hydrogels.

    PubMed

    Numata, Keiji; Katashima, Takuya; Sakai, Takamasa

    2011-06-13

    A novel technique was developed to regulate the bulk water content of silk hydrogels by adjusting the concentrations of silk proteins, which is helpful to investigate the effects of the state of water in polymeric hydrogel on its biological functions, such as cytotoxicity. Gelation of the silk hydrogel was induced with ethanol and its gelation behavior was analyzed by rheometry. The silk hydrogels prepared at various silk concentrations were characterized with respect to their water content, molecular and network structures, state of water, mechanical properties, and cytotoxicity to human mesenchymal stem cells. The network structure of silk hydrogel was heterogeneous with β-sheet and fibrillar structures. The influence of the state of water in the silk hydrogel on the cytotoxicity was recognized by means of differential scanning calorimetry and cell proliferation assay, which revealed that the bound water will support cell-adhesion proteins in the cellular matrix to interact with the surface of the silk hydrogels.

  17. Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

    PubMed

    Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

    2014-01-27

    The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. T