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.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

NASA Astrophysics Data System (ADS)

Costanzi, Stefano; Tikhonova, Irina G.; Harden, T. Kendall; Jacobson, Kenneth A.

2009-11-01

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

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.

Investigation on Quantitative Structure Activity Relationships of a Series of Inducible Nitric Oxide.

PubMed

Sharma, Mukesh C; Sharma, S

2016-12-01

A series of 2-dihydro-4-quinazolin with potent highly selective inhibitors of inducible nitric oxide synthase activities was subjected to quantitative structure activity relationships (QSAR) analysis. Statistically significant equations with high correlation coefficient (r 2  = 0.8219) were developed. The k-nearest neighbor model has showed good cross-validated correlation coefficient and external validation values of 0.7866 and 0.7133, respectively. The selected electrostatic field descriptors the presence of blue ball around R1 and R4 in the quinazolinamine moiety showed electronegative groups favorable for nitric oxide synthase activity. The QSAR models may lead to the structural requirements of inducible nitric oxide compounds and help in the design of new compounds.

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

PubMed

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

2008-04-01

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

Assessment of and standardization for quantitative nondestructive test

NASA Technical Reports Server (NTRS)

Neuschaefer, R. W.; Beal, J. B.

1972-01-01

Present capabilities and limitations of nondestructive testing (NDT) as applied to aerospace structures during design, development, production, and operational phases are assessed. It will help determine what useful structural quantitative and qualitative data may be provided from raw materials to vehicle refurbishment. This assessment considers metal alloys systems and bonded composites presently applied in active NASA programs or strong contenders for future use. Quantitative and qualitative data has been summarized from recent literature, and in-house information, and presented along with a description of those structures or standards where the information was obtained. Examples, in tabular form, of NDT technique capabilities and limitations have been provided. NDT techniques discussed and assessed were radiography, ultrasonics, penetrants, thermal, acoustic, and electromagnetic. Quantitative data is sparse; therefore, obtaining statistically reliable flaw detection data must be strongly emphasized. The new requirements for reusable space vehicles have resulted in highly efficient design concepts operating in severe environments. This increases the need for quantitative NDT evaluation of selected structural components, the end item structure, and during refurbishment operations.

Quantitative structure-activity relationship modeling on in vitro endocrine effects and metabolic stability involving 26 selected brominated flame retardants.

PubMed

Harju, Mikael; Hamers, Timo; Kamstra, Jorke H; Sonneveld, Edwin; Boon, Jan P; Tysklind, Mats; Andersson, Patrik L

2007-04-01

In this work, quantitative structure-activity relationships (QSARs) were developed to aid human and environmental risk assessment processes for brominated flame retardants (BFRs). Brominated flame retardants, such as the high-production-volume chemicals polybrominated diphenyl ethers (PBDEs), tetrabromobisphenol A, and hexabromocyclododecane, have been identified as potential endocrine disruptors. Quantitative structure-activity relationship models were built based on the in vitro potencies of 26 selected BFRs. The in vitro assays included interactions with, for example, androgen, progesterone, estrogen, and dioxin (aryl hydrocarbon) receptor, plus competition with thyroxine for its plasma carrier protein (transthyretin), inhibition of estradiol sulfation via sulfotransferase, and finally, rate of metabolization. The QSAR modeling, a number of physicochemical parameters were calculated describing the electronic, lipophilic, and structural characteristics of the molecules. These include frontier molecular orbitals, molecular charges, polarities, log octanol/water partitioning coefficient, and two- and three-dimensional molecularproperties. Experimental properties were included and measured for PBDEs, such as their individual ultraviolet spectra (200-320 nm) and retention times on three different high-performance liquid chromatography columns and one nonpolar gas chromatography column. Quantitative structure-activity relationship models based on androgen antagonism and metabolic degradation rates generally gave similar results, suggesting that lower-brominated PBDEs with bromine substitutions in ortho positions and bromine-free meta- and para positions had the highest potencies and metabolic degradation rates. Predictions made for the constituents of the technical flame retardant Bromkal 70-5DE found BDE 17 to be a potent androgen antagonist and BDE 66, which is a relevant PBDE in environmental samples, to be only a weak antagonist.

NON-TRADITIONAL RESPONSES TO PHARMACEUTICALS IN AQUATIC ECOSYSTEMS

EPA Science Inventory

Quantitation of human and veterinary pharmaceuticals in environmental matrices has resulted in pharmaceuticals in the environment receiving unprecedented attention from the scientific community. Aquatic hazard assessments often use quantitative structure activity relationships an...

The structure-activity relationship of inhibitors of serotonin uptake and receptor binding

NASA Astrophysics Data System (ADS)

Hansch, Corwin; Caldwell, Jonathan

1991-10-01

An analysis of five different datasets of inhibitors of serotonin uptake has yielded quantitative structure/ activity relationships (QSARs) which delineate the role of steric and hydrophobic properties essential for inhibition by phenylethylamine-type analogues.

ESTIMATION OF CHEMICAL SPECIFIC PARAMETERS WITHIN PHYSIOLOGICALLY BASED PHARMACOKINETIC/PHARMACODYNAMIC MODELS

EPA Science Inventory

While relationships between chemical structure and observed properties or activities (QSAR - quantitative structure activity relationship) can be used to predict the behavior of unknown chemicals, this method is semiempirical in nature relying on high quality experimental data to...

Biomacromolecular quantitative structure-activity relationship (BioQSAR): a proof-of-concept study on the modeling, prediction and interpretation of protein-protein binding affinity.

PubMed

Zhou, Peng; Wang, Congcong; Tian, Feifei; Ren, Yanrong; Yang, Chao; Huang, Jian

2013-01-01

Quantitative structure-activity relationship (QSAR), a regression modeling methodology that establishes statistical correlation between structure feature and apparent behavior for a series of congeneric molecules quantitatively, has been widely used to evaluate the activity, toxicity and property of various small-molecule compounds such as drugs, toxicants and surfactants. However, it is surprising to see that such useful technique has only very limited applications to biomacromolecules, albeit the solved 3D atom-resolution structures of proteins, nucleic acids and their complexes have accumulated rapidly in past decades. Here, we present a proof-of-concept paradigm for the modeling, prediction and interpretation of the binding affinity of 144 sequence-nonredundant, structure-available and affinity-known protein complexes (Kastritis et al. Protein Sci 20:482-491, 2011) using a biomacromolecular QSAR (BioQSAR) scheme. We demonstrate that the modeling performance and predictive power of BioQSAR are comparable to or even better than that of traditional knowledge-based strategies, mechanism-type methods and empirical scoring algorithms, while BioQSAR possesses certain additional features compared to the traditional methods, such as adaptability, interpretability, deep-validation and high-efficiency. The BioQSAR scheme could be readily modified to infer the biological behavior and functions of other biomacromolecules, if their X-ray crystal structures, NMR conformation assemblies or computationally modeled structures are available.

Universal structural parameter to quantitatively predict metallic glass properties

DOE PAGES

Ding, Jun; Cheng, Yong-Qiang; Sheng, Howard; ...

2016-12-12

Quantitatively correlating the amorphous structure in metallic glasses (MGs) with their physical properties has been a long-sought goal. Here we introduce flexibility volume' as a universal indicator, to bridge the structural state the MG is in with its properties, on both atomic and macroscopic levels. The flexibility volume combines static atomic volume with dynamics information via atomic vibrations that probe local configurational space and interaction between neighbouring atoms. We demonstrate that flexibility volume is a physically appropriate parameter that can quantitatively predict the shear modulus, which is at the heart of many key properties of MGs. Moreover, the new parametermore » correlates strongly with atomic packing topology, and also with the activation energy for thermally activated relaxation and the propensity for stress-driven shear transformations. These correlations are expected to be robust across a very wide range of MG compositions, processing conditions and length scales.« less

Structured Observation of School Administrator Work Activities: Methodological Limitations and Recommendations for Research, Part II.

ERIC Educational Resources Information Center

Pitner, Nancy J.; Russell, James S.

1986-01-01

This paper critically reviews administrator work activity studies which follow the research of Henry Mintzberg. It discusses directions for future research using qualitative and quantitative methods and discourages research that relies solely on Mintzberg's structure. (Author/JAZ)

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

PubMed

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

Design of cinnamaldehyde amino acid Schiff base compounds based on the quantitative structure–activity relationship

Treesearch

Hui Wang; Mingyue Jiang; Shujun Li; Chung-Yun Hse; Chunde Jin; Fangli Sun; Zhuo Li

2017-01-01

Cinnamaldehyde amino acid Schiff base (CAAS) is a new class of safe, bioactive compounds which could be developed as potential antifungal agents for fungal infections. To design new cinnamaldehyde amino acid Schiff base compounds with high bioactivity, the quantitative structure–activity relationships (QSARs) for CAAS compounds against Aspergillus niger (A. niger) and...

Non-linear quantitative structure-activity relationship for adenine derivatives as competitive inhibitors of adenosine deaminase

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

Sadat Hayatshahi, Sayyed Hamed; Abdolmaleki, Parviz; Safarian, Shahrokh

2005-12-16

Logistic regression and artificial neural networks have been developed as two non-linear models to establish quantitative structure-activity relationships between structural descriptors and biochemical activity of adenosine based competitive inhibitors, toward adenosine deaminase. The training set included 24 compounds with known k {sub i} values. The models were trained to solve two-class problems. Unlike the previous work in which multiple linear regression was used, the highest of positive charge on the molecules was recognized to be in close relation with their inhibition activity, while the electric charge on atom N1 of adenosine was found to be a poor descriptor. Consequently, themore » previously developed equation was improved and the newly formed one could predict the class of 91.66% of compounds correctly. Also optimized 2-3-1 and 3-4-1 neural networks could increase this rate to 95.83%.« less

Quantitative structure-activity relationship of organosulphur compounds as soybean 15-lipoxygenase inhibitors using CoMFA and CoMSIA.

PubMed

Caballero, Julio; Fernández, Michael; Coll, Deysma

2010-12-01

Three-dimensional quantitative structure-activity relationship studies were carried out on a series of 28 organosulphur compounds as 15-lipoxygenase inhibitors using comparative molecular field analysis and comparative molecular similarity indices analysis. Quantitative information on structure-activity relationships is provided for further rational development and direction of selective synthesis. All models were carried out over a training set including 22 compounds. The best comparative molecular field analysis model only included steric field and had a good Q² = 0.789. Comparative molecular similarity indices analysis overcame the comparative molecular field analysis results: the best comparative molecular similarity indices analysis model also only included steric field and had a Q² = 0.894. In addition, this model predicted adequately the compounds contained in the test set. Furthermore, plots of steric comparative molecular similarity indices analysis field allowed conclusions to be drawn for the choice of suitable inhibitors. In this sense, our model should prove useful in future 15-lipoxygenase inhibitor design studies. © 2010 John Wiley & Sons A/S.

In Vivo Characterization of Traumatic Brain Injury Neuropathology with Structural and Functional Neuroimaging

PubMed Central

LEVINE, BRIAN; FUJIWARA, ESTHER; O’CONNOR, CHARLENE; RICHARD, NADINE; KOVACEVIC, NATASA; MANDIC, MARINA; RESTAGNO, ADRIANA; EASDON, CRAIG; ROBERTSON, IAN H.; GRAHAM, SIMON J.; CHEUNG, GORDON; GAO, FUQIANG; SCHWARTZ, MICHAEL L.; BLACK, SANDRA E.

2007-01-01

Quantitative neuroimaging is increasingly used to study the effects of traumatic brain injury (TBI) on brain structure and function. This paper reviews quantitative structural and functional neuroimaging studies of patients with TBI, with an emphasis on the effects of diffuse axonal injury (DAI), the primary neuropathology in TBI. Quantitative structural neuroimaging has evolved from simple planometric measurements through targeted region-of-interest analyses to whole-brain analysis of quantified tissue compartments. Recent studies converge to indicate widespread volume loss of both gray and white matter in patients with moderate-to-severe TBI. These changes can be documented even when patients with focal lesions are excluded. Broadly speaking, performance on standard neuropsychological tests of speeded information processing are related to these changes, but demonstration of specific brain-behavior relationships requires more refined experimental behavioral measures. The functional consequences of these structural changes can be imaged with activation functional neuroimaging. Although this line of research is at an early stage, results indicate that TBI causes a more widely dispersed activation in frontal and posterior cortices. Further progress in analysis of the consequences of TBI on neural structure and function will require control of variability in neuropathology and behavior. PMID:17020478

Enzyme Active Site Interactions by Raman/FTIR, NMR, and Ab Initio Calculations

PubMed Central

Deng, Hua

2017-01-01

Characterization of enzyme active site structure and interactions at high resolution is important for the understanding of the enzyme catalysis. Vibrational frequency and NMR chemical shift measurements of enzyme-bound ligands are often used for such purpose when X-ray structures are not available or when higher resolution active site structures are desired. This review is focused on how ab initio calculations may be integrated with vibrational and NMR chemical shift measurements to quantitatively determine high-resolution ligand structures (up to 0.001 Å for bond length and 0.01 Å for hydrogen bonding distance) and how interaction energies between bound ligand and its surroundings at the active site may be determined. Quantitative characterization of substrate ionic states, bond polarizations, tautomeric forms, conformational changes and its interactions with surroundings in enzyme complexes that mimic ground state or transition state can provide snapshots for visualizing the substrate structural evolution along enzyme-catalyzed reaction pathway. Our results have shown that the integration of spectroscopic studies with theoretical computation greatly enhances our ability to interpret experimental data and significantly increases the reliability of the theoretical analysis. PMID:24018325

Use of reduction rate as a quantitative knob for controlling the twin structure and shape of palladium nanocrystals.

PubMed

Wang, Yi; Peng, Hsin-Chieh; Liu, Jingyue; Huang, Cheng Zhi; Xia, Younan

2015-02-11

Kinetic control is a powerful means for maneuvering the twin structure and shape of metal nanocrystals and thus optimizing their performance in a variety of applications. However, there is only a vague understanding of the explicit roles played by reaction kinetics due to the lack of quantitative information about the kinetic parameters. With Pd as an example, here we demonstrate that kinetic parameters, including rate constant and activation energy, can be derived from spectroscopic measurements and then used to calculate the initial reduction rate and further have this parameter quantitatively correlated with the twin structure of a seed and nanocrystal. On a quantitative basis, we were able to determine the ranges of initial reduction rates required for the formation of nanocrystals with a specific twin structure, including single-crystal, multiply twinned, and stacking fault-lined. This work represents a major step forward toward the deterministic syntheses of colloidal noble-metal nanocrystals with specific twin structures and shapes.

Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines

NASA Astrophysics Data System (ADS)

Hirst, Jonathan D.; King, Ross D.; Sternberg, Michael J. E.

1994-08-01

One of the largest available data sets for developing a quantitative structure-activity relationship (QSAR) — the inhibition of dihydrofolate reductase (DHFR) by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazine derivatives — has been used for a sixfold cross-validation trial of neural networks, inductive logic programming (ILP) and linear regression. No statistically significant difference was found between the predictive capabilities of the methods. However, the representation of molecules by attributes, which is integral to the ILP approach, provides understandable rules about drug-receptor interactions.

Partitioning and lipophilicity in quantitative structure-activity relationships.

PubMed Central

Dearden, J C

1985-01-01

The history of the relationship of biological activity to partition coefficient and related properties is briefly reviewed. The dominance of partition coefficient in quantitation of structure-activity relationships is emphasized, although the importance of other factors is also demonstrated. Various mathematical models of in vivo transport and binding are discussed; most of these involve partitioning as the primary mechanism of transport. The models describe observed quantitative structure-activity relationships (QSARs) well on the whole, confirming that partitioning is of key importance in in vivo behavior of a xenobiotic. The partition coefficient is shown to correlate with numerous other parameters representing bulk, such as molecular weight, volume and surface area, parachor and calculated indices such as molecular connectivity; this is especially so for apolar molecules, because for polar molecules lipophilicity factors into both bulk and polar or hydrogen bonding components. The relationship of partition coefficient to chromatographic parameters is discussed, and it is shown that such parameters, which are often readily obtainable experimentally, can successfully supplant partition coefficient in QSARs. The relationship of aqueous solubility with partition coefficient is examined in detail. Correlations are observed, even with solid compounds, and these can be used to predict solubility. The additive/constitutive nature of partition coefficient is discussed extensively, as are the available schemes for the calculation of partition coefficient. Finally the use of partition coefficient to provide structural information is considered. It is shown that partition coefficient can be a valuable structural tool, especially if the enthalpy and entropy of partitioning are available. PMID:3905374

Quantitative structure activity relationships from optimised ab initio bond lengths: steroid binding affinity and antibacterial activity of nitrofuran derivatives

NASA Astrophysics Data System (ADS)

Smith, P. J.; Popelier, P. L. A.

2004-02-01

The present day abundance of cheap computing power enables the use of quantum chemical ab initio data in Quantitative Structure-Activity Relationships (QSARs). Optimised bond lengths are a new such class of descriptors, which we have successfully used previously in representing electronic effects in medicinal and ecological QSARs (enzyme inhibitory activity, hydrolysis rate constants and pKas). Here we use AM1 and HF/3-21G* bond lengths in conjunction with Partial Least Squares (PLS) and a Genetic Algorithm (GA) to predict the Corticosteroid-Binding Globulin (CBG) binding activity of the classic steroid data set, and the antibacterial activity of nitrofuran derivatives. The current procedure, which does not require molecular alignment, produces good r2 and q2 values. Moreover, it highlights regions in the common steroid skeleton deemed relevant to the active regions of the steroids and nitrofuran derivatives.

A Hierarchical Clustering Methodology for the Estimation of Toxicity

EPA Science Inventory

A Quantitative Structure Activity Relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural sim...

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

NASA Astrophysics Data System (ADS)

Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B.; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert

2015-08-01

Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.

Multicomplex-based pharmacophore-guided 3D-QSAR studies of N-substituted 2'-(aminoaryl)benzothiazoles as Aurora-A inhibitors.

PubMed

He, Gu; Qiu, Minghua; Li, Rui; Ouyang, Liang; Wu, Fengbo; Song, Xiangrong; Cheng, Li; Xiang, Mingli; Yu, Luoting

2012-06-01

Aurora-A has been known as one of the most important targets for cancer therapy, and some Aurora-A inhibitors have entered clinical trails. In this study, combination of the ligand-based and structure-based methods is used to clarify the essential quantitative structure-activity relationship of known Aurora-A inhibitors, and multicomplex-based pharmacophore-guided method has been suggested to generate a comprehensive pharmacophore of Aurora-A kinase based on a collection of crystal structures of Aurora-A-inhibitor complex. This model has been successfully used to identify the bioactive conformation and align 37 structurally diverse N-substituted 2'-(aminoaryl)benzothiazoles derivatives. The quantitative structure-activity relationship analyses have been performed on these Aurora-A inhibitors based on multicomplex-based pharmacophore-guided alignment. These results may provide important information for further design and virtual screening of novel Aurora-A inhibitors. © 2012 John Wiley & Sons A/S.

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Wei, Yu-Tuo; Pang, Zong-Wen; Du, Li-Qin; Chou, Kuo-Chen

2009-01-30

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. (c) 2008 Wiley Periodicals, Inc.

QSAR, QSPR and QSRR in Terms of 3-D-MoRSE Descriptors for In Silico Screening of Clofibric Acid Analogues.

PubMed

Di Tullio, Maurizio; Maccallini, Cristina; Ammazzalorso, Alessandra; Giampietro, Letizia; Amoroso, Rosa; De Filippis, Barbara; Fantacuzzi, Marialuigia; Wiczling, Paweł; Kaliszan, Roman

2012-07-01

A series of 27 analogues of clofibric acid, mostly heteroarylalkanoic derivatives, have been analyzed by a novel high-throughput reversed-phase HPLC method employing combined gradient of eluent's pH and organic modifier content. The such determined hydrophobicity (lipophilicity) parameters, log kw , and acidity constants, pKa , were subjected to multiple regression analysis to get a QSRR (Quantitative StructureRetention Relationships) and a QSPR (Quantitative Structure-Property Relationships) equation, respectively, describing these pharmacokinetics-determining physicochemical parameters in terms of the calculation chemistry derived structural descriptors. The previously determined in vitro log EC50 values - transactivation activity towards PPARα (human Peroxisome Proliferator-Activated Receptor α) - have also been described in a QSAR (Quantitative StructureActivity Relationships) equation in terms of the 3-D-MoRSE descriptors (3D-Molecule Representation of Structures based on Electron diffraction descriptors). The QSAR model derived can serve for an a priori prediction of bioactivity in vitro of any designed analogue, whereas the QSRR and the QSPR models can be used to evaluate lipophilicity and acidity, respectively, of the compounds, and hence to rational guide selection of structures of proper pharmacokinetics. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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

1998-03-01

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

The quantitative structure-insecticidal activity relationships from plant derived compounds against chikungunya and zika Aedes aegypti (Diptera:Culicidae) vector.

PubMed

Saavedra, Laura M; Romanelli, Gustavo P; Rozo, Ciro E; Duchowicz, Pablo R

2018-01-01

The insecticidal activity of a series of 62 plant derived molecules against the chikungunya, dengue and zika vector, the Aedes aegypti (Diptera:Culicidae) mosquito, is subjected to a Quantitative Structure-Activity Relationships (QSAR) analysis. The Replacement Method (RM) variable subset selection technique based on Multivariable Linear Regression (MLR) proves to be successful for exploring 4885 molecular descriptors calculated with Dragon 6. The predictive capability of the obtained models is confirmed through an external test set of compounds, Leave-One-Out (LOO) cross-validation and Y-Randomization. The present study constitutes a first necessary computational step for designing less toxic insecticides. Copyright © 2017 Elsevier B.V. All rights reserved.

Augmented multivariate image analysis applied to quantitative structure-activity relationship modeling of the phytotoxicities of benzoxazinone herbicides and related compounds on problematic weeds.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2013-09-11

Two of major weeds affecting cereal crops worldwide are Avena fatua L. (wild oat) and Lolium rigidum Gaud. (rigid ryegrass). Thus, development of new herbicides against these weeds is required; in line with this, benzoxazinones, their degradation products, and analogues have been shown to be important allelochemicals and natural herbicides. Despite earlier structure-activity studies demonstrating that hydrophobicity (log P) of aminophenoxazines correlates to phytotoxicity, our findings for a series of benzoxazinone derivatives do not show any relationship between phytotoxicity and log P nor with other two usual molecular descriptors. On the other hand, a quantitative structure-activity relationship (QSAR) analysis based on molecular graphs representing structural shape, atomic sizes, and colors to encode other atomic properties performed very accurately for the prediction of phytotoxicities of these compounds against wild oat and rigid ryegrass. Therefore, these QSAR models can be used to estimate the phytotoxicity of new congeners of benzoxazinone herbicides toward A. fatua L. and L. rigidum Gaud.

Tannin structural elucidation and quantitative ³¹P NMR analysis. 1. Model compounds.

PubMed

Melone, Federica; Saladino, Raffaele; Lange, Heiko; Crestini, Claudia

2013-10-02

Tannins and flavonoids are secondary metabolites of plants that display a wide array of biological activities. This peculiarity is related to the inhibition of extracellular enzymes that occurs through the complexation of peptides by tannins. Not only the nature of these interactions, but more fundamentally also the structure of these heterogeneous polyphenolic molecules are not completely clear. This first paper describes the development of a new analytical method for the structural characterization of tannins on the basis of tannin model compounds employing an in situ labeling of all labile H groups (aliphatic OH, phenolic OH, and carboxylic acids) with a phosphorus reagent. The ³¹P NMR analysis of ³¹P-labeled samples allowed the unprecedented quantitative and qualitative structural characterization of hydrolyzable tannins, proanthocyanidins, and catechin tannin model compounds, forming the foundations for the quantitative structural elucidation of a variety of actual tannin samples described in part 2 of this series.

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.

Using Quantitative Structure-Activity Relationship Modeling to Quantitatively Predict the Developmental Toxicity of Halogenated Azole compounds

EPA Science Inventory

Developmental toxicity is a relevant endpoint for the comprehensive assessment of human health risk from chemical exposure. However, animal developmental toxicity studies remain unavailable for many environmental contaminants due to the complexity and cost of these types of analy...

Obscure phenomena in statistical analysis of quantitative structure-activity relationships. Part 1: Multicollinearity of physicochemical descriptors.

PubMed

Mager, P P; Rothe, H

1990-10-01

Multicollinearity of physicochemical descriptors leads to serious consequences in quantitative structure-activity relationship (QSAR) analysis, such as incorrect estimators and test statistics of regression coefficients of the ordinary least-squares (OLS) model applied usually to QSARs. Beside the diagnosis of the known simple collinearity, principal component regression analysis (PCRA) also allows the diagnosis of various types of multicollinearity. Only if the absolute values of PCRA estimators are order statistics that decrease monotonically, the effects of multicollinearity can be circumvented. Otherwise, obscure phenomena may be observed, such as good data recognition but low predictive model power of a QSAR model.

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

NASA Astrophysics Data System (ADS)

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

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

Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.

PubMed

Mendenhall, Jeffrey; Meiler, Jens

2016-02-01

Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both enrichment false positive rate and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22-46 % over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods.

Improving Quantitative Structure-Activity Relationship Models using Artificial Neural Networks Trained with Dropout

PubMed Central

Mendenhall, Jeffrey; Meiler, Jens

2016-01-01

Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery (LB-CADD) pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both Enrichment false positive rate (FPR) and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22–46% over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods. PMID:26830599

Aquatic toxicity of acrylates and methacrylates: quantitative structure-activity relationships based on Kow and LC50

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

Reinert, K.H.

1987-12-01

Recent EPA scrutiny of acrylate and methacrylate monomers has resulted in restrictive consent orders and Significant New Use Rules under the Toxic Substances Control Act, based on structure-activity relationships using mouse skin painting studies. The concern is centered on human health issues regarding worker and consumer exposure. Environmental issues, such as aquatic toxicity, are still of concern. Understanding the relationships and environmental risks to aquatic organisms may improve the understanding of the potential risks to human health. This study evaluates the quantitative structure-activity relationships from measured log Kow's and log LC50's for Pimephales promelas (fathead minnow) and Carassius auratus (goldfish).more » Scientific support of the current regulations is also addressed. Two monomer classes were designated: acrylates and methacrylates. Spearman rank correlation and linear regression were run. Based on this study, an ecotoxicological difference exists between acrylates and methacrylates. Regulatory activities and scientific study should reflect this difference.« less

Insight into the structural requirements of aminopyrimidine derivatives for good potency against both purified enzyme and whole cells of M. tuberculosis: combination of HQSAR, CoMSIA, and MD simulation studies.

PubMed

Punkvang, Auradee; Hannongbua, Supa; Saparpakorn, Patchreenart; Pungpo, Pornpan

2016-05-01

The Mycobacterium tuberculosis protein kinase B (PknB) is critical for growth and survival of M. tuberculosis within the host. The series of aminopyrimidine derivatives show impressive activity against PknB (IC50 < .5 μM). However, most of them show weak or no cellular activity against M. tuberculosis (MIC > 63 μM). Consequently, the key structural features related to activity against of both PknB and M. tuberculosis need to be investigated. Here, two- and three-dimensional quantitative structure-activity relationship (2D and 3D QSAR) analyses combined with molecular dynamics (MD) simulations were employed with the aim to evaluate these key structural features of aminopyrimidine derivatives. Hologram quantitative structure-activity relationship (HQSAR) and CoMSIA models constructed from IC50 and MIC values of aminopyrimidine compounds could establish the structural requirements for better activity against of both PknB and M. tuberculosis. The NH linker and the R1 substituent of the template compound are not only crucial for the biological activity against PknB but also for the biological activity against M. tuberculosis. Moreover, the results obtained from MD simulations show that these moieties are the key fragments for binding of aminopyrimidine compounds in PknB. The combination of QSAR analysis and MD simulations helps us to provide a structural concept that could guide future design of PknB inhibitors with improved potency against both the purified enzyme and whole M. tuberculosis cells.

Antitumor activity of 3,4-ethylenedioxythiophene derivatives and quantitative structure-activity relationship analysis

NASA Astrophysics Data System (ADS)

Jukić, Marijana; Rastija, Vesna; Opačak-Bernardi, Teuta; Stolić, Ivana; Krstulović, Luka; Bajić, Miroslav; Glavaš-Obrovac, Ljubica

2017-04-01

The aim of this study was to evaluate nine newly synthesized amidine derivatives of 3,4- ethylenedioxythiophene (3,4-EDOT) for their cytotoxic activity against a panel of human cancer cell lines and to perform a quantitative structure-activity relationship (QSAR) analysis for the antitumor activity of a total of 27 3,4-ethylenedioxythiophene derivatives. Induction of apoptosis was investigated on the selected compounds, along with delivery options for the optimization of activity. The best obtained QSAR models include the following group of descriptors: BCUT, WHIM, 2D autocorrelations, 3D-MoRSE, GETAWAY descriptors, 2D frequency fingerprint and information indices. Obtained QSAR models should be relieved in elucidation of important physicochemical and structural requirements for this biological activity. Highly potent molecules have a symmetrical arrangement of substituents along the x axis, high frequency of distance between N and O atoms at topological distance 9, as well as between C and N atoms at topological distance 10, and more C atoms located at topological distances 6 and 3. Based on the conclusion given in the QSAR analysis, a new compound with possible great activity was proposed.

Design of cinnamaldehyde amino acid Schiff base compounds based on the quantitative structure-activity relationship.

PubMed

Wang, Hui; Jiang, Mingyue; Li, Shujun; Hse, Chung-Yun; Jin, Chunde; Sun, Fangli; Li, Zhuo

2017-09-01

Cinnamaldehyde amino acid Schiff base (CAAS) is a new class of safe, bioactive compounds which could be developed as potential antifungal agents for fungal infections. To design new cinnamaldehyde amino acid Schiff base compounds with high bioactivity, the quantitative structure-activity relationships (QSARs) for CAAS compounds against Aspergillus niger ( A. niger ) and Penicillium citrinum (P. citrinum) were analysed. The QSAR models ( R 2  = 0.9346 for A. niger , R 2  = 0.9590 for P. citrinum, ) were constructed and validated. The models indicated that the molecular polarity and the Max atomic orbital electronic population had a significant effect on antifungal activity. Based on the best QSAR models, two new compounds were designed and synthesized. Antifungal activity tests proved that both of them have great bioactivity against the selected fungi.

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

Development of Novel Repellents Using Structure - Activity Modeling of Compounds in the USDA Archival Database

DTIC Science & Technology

2011-01-01

used in efforts to develop QSAR models. Measurement of Repellent Efficacy Screening for Repellency of Compounds with Unknown Toxicology In screening...CPT) were used to develop Quantitative Structure Activity Relationship ( QSAR ) models to predict repellency. Successful prediction of novel...acylpiperidine QSAR models employed 4 descriptors to describe the relationship between structure and repellent duration. The ANN model of the carboxamides did not

Quantitative functional characterization of conserved molecular interactions in the active site of mannitol 2-dehydrogenase

PubMed Central

Lucas, James E; Siegel, Justin B

2015-01-01

Enzyme active site residues are often highly conserved, indicating a significant role in function. In this study we quantitate the functional contribution for all conserved molecular interactions occurring within a Michaelis complex for mannitol 2-dehydrogenase derived from Pseudomonas fluorescens (pfMDH). Through systematic mutagenesis of active site residues, we reveal that the molecular interactions in pfMDH mediated by highly conserved residues not directly involved in reaction chemistry can be as important to catalysis as those directly involved in the reaction chemistry. This quantitative analysis of the molecular interactions within the pfMDH active site provides direct insight into the functional role of each molecular interaction, several of which were unexpected based on canonical sequence conservation and structural analyses. PMID:25752240

Antifeedant effect of polygodial and drimenol derivatives against Spodoptera frugiperda and Epilachna paenulata and quantitative structure-activity analysis.

PubMed

Montenegro, Iván J; Del Corral, Soledad; Diaz Napal, Georgina N; Carpinella, María C; Mellado, Marco; Madrid, Alejandro M; Villena, Joan; Palacios, Sara M; Cuellar, Mauricio A

2018-07-01

The antifeedant activity of 18 sesquiterpenoids of the drimane family (polygodial, drimenol and derivatives) was investigated. Polygodial, drimanic and nordrimanic derivatives were found to exert antifeedant effects against two insect species, Spodoptera frugiperda and Epilachna paenulata, which are pests of agronomic interest, indicating that they have potential as biopesticide agents. Among the 18 compounds tested, the epoxynordrimane compound (11) and isonordrimenone (4) showed the highest activity [50% effective concentration (EC 50 ) = 23.28 and 25.63 nmol cm - 2 , respectively, against S. frugiperda, and 50.50 and 59.00 nmol/cm 2 , respectively, against E. paenulata]. The results suggest that drimanic compounds have potential as new agents against S. frugiperda and E. paenulata. A quantitative structure-activity relationship (QSAR) analysis of the whole series, supported by electronic studies, suggested that drimanic compounds have structural features necessary for increasing antifeedant activity, namely a C-9 carbonyl group and an epoxide at C-8 and C-9. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship.

PubMed

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

2011-08-22

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.

Synthesis, quantitative structure-property relationship study of novel fluorescence active 2-pyrazolines and application.

PubMed

Girgis, Adel S; Basta, Altaf H; El-Saied, Houssni; Mohamed, Mohamed A; Bedair, Ahmad H; Salim, Ahmad S

2018-03-01

A variety of fluorescence-active fluorinated pyrazolines 13-33 was synthesized in good yields through cyclocondensation reaction of propenones 1-9 with aryl hydrazines 10-12 . Some of the synthesized compounds provided promising fluorescence properties with quantum yield ( Φ ) higher than that of quinine sulfate (standard reference). Quantitative structure-property relationship studies were undertaken supporting the exhibited fluorescence properties and estimating the parameters governing properties. Five synthesized fluorescence-active pyrazolines ( 13 , 15 , 18 , 19 and 23 ) with variable Φ were selected for treating two types of paper sheets (Fabriano and Bible paper). These investigated fluorescence compounds, especially compounds 19 and 23 , provide improvements in strength properties of paper sheets. Based on the observed performance they can be used as markers in security documents.

Synthesis, quantitative structure-property relationship study of novel fluorescence active 2-pyrazolines and application

NASA Astrophysics Data System (ADS)

Girgis, Adel S.; Basta, Altaf H.; El-Saied, Houssni; Mohamed, Mohamed A.; Bedair, Ahmad H.; Salim, Ahmad S.

2018-03-01

A variety of fluorescence-active fluorinated pyrazolines 13-33 was synthesized in good yields through cyclocondensation reaction of propenones 1-9 with aryl hydrazines 10-12. Some of the synthesized compounds provided promising fluorescence properties with quantum yield (Φ) higher than that of quinine sulfate (standard reference). Quantitative structure-property relationship studies were undertaken supporting the exhibited fluorescence properties and estimating the parameters governing properties. Five synthesized fluorescence-active pyrazolines (13, 15, 18, 19 and 23) with variable Φ were selected for treating two types of paper sheets (Fabriano and Bible paper). These investigated fluorescence compounds, especially compounds 19 and 23, provide improvements in strength properties of paper sheets. Based on the observed performance they can be used as markers in security documents.

Design, synthesis, antiviral bioactivity and three-dimensional quantitative structure-activity relationship study of novel ferulic acid ester derivatives containing quinazoline moiety.

PubMed

Wu, Zengxue; Zhang, Jian; Chen, Jixiang; Pan, Jianke; Zhao, Lei; Liu, Dengyue; Zhang, Awei; Chen, Jin; Hu, Deyu; Song, Baoan

2017-10-01

Ferulic acid and quinazoline derivatives possess good antiviral activities. In order to develop novel compounds with high antiviral activities, a series of ferulic acid ester derivatives containing quinazoline were synthesized and evaluated for their antiviral activities. Bioassays indicated that some of the compounds exhibited good antiviral activities in vivo against tobacco mosaic virus (TMV) and cucumber mosaic virus (CMV). One of the compounds demonstrated significant curative and protective activities against TMV and CMV, with EC 50 values of 162.14, 114.61 and 255.49, 138.81 mg L -1 , respectively, better than those of ningnanmycin (324.51, 168.84 and 373.88, 272.70 mg L -1 ). The values of q 2 and r 2 for comparative molecular field analysis and comparative molecular similarity index analysis in the TMV (0.508, 0.663 and 0.992, 0.930) and CMV (0.530, 0.626 and 0.997, 0.981) models presented good predictive abilities. Some of the title compounds demonstrated good antiviral activities. Three-dimensional quantitative structure-activity relationship models revealed that the antiviral activities depend on steric and electrostatic properties. These results could provide significant structural insights for the design of highly active ferulic acid derivatives. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

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 detail with numerical examples.

Synthesis and quantitative structure-antifungal activity relationships of clovane derivatives against Botrytis cinerea.

PubMed

Saiz-Urra, Liane; Racero, Juan C; Macías-Sáchez, Antonio J; Hernández-Galán, Rosario; Hanson, James R; Perez-Gonzalez, Maykel; Collado, Isidro G

2009-03-25

Twenty-three clovane derivatives, nine described here for the first time, bearing substituents on carbon C-2, have been synthesized and evaluated for their in vitro antifungal activity against the phytopathogenic fungus Botrytis cinerea. The results showed that compounds 9, 14, 16, and 18 bearing nitrogen atoms in the chain attached at C-2 displayed potent antifungal activity, whereas mercapto derivatives 13, 19, and 22 displayed low activity. The antifungal activity showed a clear structure-activity relationship (SAR) trend, which confirmed the importance of the nature of the C-2 chain on the antifungal activity. On the basis of these observations, the metabolism of compounds 8 and 14 by the fungus B. cinerea, and the metabolism of other clovanes by this fungus, described previously, a pro-drug action mechanism for 2-alkoxyclovane compounds is proposed. Quantitative structure-activity relationship (QSAR) studies were performed to rationalize the results and to suggest further optimization, using a topological sub-structural molecular design (TOPS-MODE) approach. The model displayed good fit and predictive capability, describing 85.5% of the experimental variance, with a standard deviation of 9.502 and yielding high values of cross-validation determination coefficients (q2CV-LOO = 0.784 and q2boot = 0.673). The most significant variables were the spectral moments weighted by bond dipole moment (Dip), hydrophobicity (Hyd), and the combined dipolarity/polarizability Abraham molecular descriptor (Ab-pi2H).

A combinatorial feature selection approach to describe the QSAR of dual site inhibitors of acetylcholinesterase.

PubMed

Asadabadi, Ebrahim Barzegari; Abdolmaleki, Parviz; Barkooie, Seyyed Mohsen Hosseini; Jahandideh, Samad; Rezaei, Mohammad Ali

2009-12-01

Regarding the great potential of dual binding site inhibitors of acetylcholinesterase as the future potent drugs of Alzheimer's disease, this study was devoted to extraction of the most effective structural features of these inhibitors from among a large number of quantitative descriptors. To do this, we adopted a unique approach in quantitative structure-activity relationships. An efficient feature selection method was emphasized in such an approach, using the confirmative results of different routine and novel feature selection methods. The proposed methods generated quite consistent results ensuring the effectiveness of the selected structural features.

Structural parameterization and functional prediction of antigenic polypeptome sequences with biological activity through quantitative sequence-activity models (QSAM) by molecular electronegativity edge-distance vector (VMED).

PubMed

Li, ZhiLiang; Wu, ShiRong; Chen, ZeCong; Ye, Nancy; Yang, ShengXi; Liao, ChunYang; Zhang, MengJun; Yang, Li; Mei, Hu; Yang, Yan; Zhao, Na; Zhou, Yuan; Zhou, Ping; Xiong, Qing; Xu, Hong; Liu, ShuShen; Ling, ZiHua; Chen, Gang; Li, GenRong

2007-10-01

Only from the primary structures of peptides, a new set of descriptors called the molecular electronegativity edge-distance vector (VMED) was proposed and applied to describing and characterizing the molecular structures of oligopeptides and polypeptides, based on the electronegativity of each atom or electronic charge index (ECI) of atomic clusters and the bonding distance between atom-pairs. Here, the molecular structures of antigenic polypeptides were well expressed in order to propose the automated technique for the computerized identification of helper T lymphocyte (Th) epitopes. Furthermore, a modified MED vector was proposed from the primary structures of polypeptides, based on the ECI and the relative bonding distance of the fundamental skeleton groups. The side-chains of each amino acid were here treated as a pseudo-atom. The developed VMED was easy to calculate and able to work. Some quantitative model was established for 28 immunogenic or antigenic polypeptides (AGPP) with 14 (1-14) A(d) and 14 other restricted activities assigned as "1"(+) and "0"(-), respectively. The latter comprised 6 A(b)(15-20), 3 A(k)(21-23), 2 E(k)(24-26), 2 H-2(k)(27 and 28) restricted sequences. Good results were obtained with 90% correct classification (only 2 wrong ones for 20 training samples) and 100% correct prediction (none wrong for 8 testing samples); while contrastively 100% correct classification (none wrong for 20 training samples) and 88% correct classification (1 wrong for 8 testing samples). Both stochastic samplings and cross validations were performed to demonstrate good performance. The described method may also be suitable for estimation and prediction of classes I and II for major histocompatibility antigen (MHC) epitope of human. It will be useful in immune identification and recognition of proteins and genes and in the design and development of subunit vaccines. Several quantitative structure activity relationship (QSAR) models were developed for various oligopeptides and polypeptides including 58 dipeptides and 31 pentapeptides with angiotensin converting enzyme (ACE) inhibition by multiple linear regression (MLR) method. In order to explain the ability to characterize molecular structure of polypeptides, a molecular modeling investigation on QSAR was performed for functional prediction of polypeptide sequences with antigenic activity and heptapeptide sequences with tachykinin activity through quantitative sequence-activity models (QSAMs) by the molecular electronegativity edge-distance vector (VMED). The results showed that VMED exhibited both excellent structural selectivity and good activity prediction. Moreover, the results showed that VMED behaved quite well for both QSAR and QSAM of poly-and oligopeptides, which exhibited both good estimation ability and prediction power, equal to or better than those reported in the previous references. Finally, a preliminary conclusion was drawn: both classical and modified MED vectors were very useful structural descriptors. Some suggestions were proposed for further studies on QSAR/QSAM of proteins in various fields.

IN SILICO MODELLING OF HAZARDOUS ENDPOINTS: CURRENT PROBLEMS AND PROSPECTIVES

EPA Science Inventory

The primary hurdles for Quantitative Structure-Activity Relationships (QSARs) to overcome their acceptance for regulatory purposes will be discussed. They include (a) the development of more mechanistic representations of chemical structure, (b) the classification of toxicity pa...

Predicting the activity of drugs for a group of imidazopyridine anticoccidial compounds.

PubMed

Si, Hongzong; Lian, Ning; Yuan, Shuping; Fu, Aiping; Duan, Yun-Bo; Zhang, Kejun; Yao, Xiaojun

2009-10-01

Gene expression programming (GEP) is a novel machine learning technique. The GEP is used to build nonlinear quantitative structure-activity relationship model for the prediction of the IC(50) for the imidazopyridine anticoccidial compounds. This model is based on descriptors which are calculated from the molecular structure. Four descriptors are selected from the descriptors' pool by heuristic method (HM) to build multivariable linear model. The GEP method produced a nonlinear quantitative model with a correlation coefficient and a mean error of 0.96 and 0.24 for the training set, 0.91 and 0.52 for the test set, respectively. It is shown that the GEP predicted results are in good agreement with experimental ones.

Rapid Scanning Structure-Activity Relationships in Combinatorial Data Sets: Identification of Activity Switches

PubMed Central

Medina-Franco, José L.; Edwards, Bruce S.; Pinilla, Clemencia; Appel, Jon R.; Giulianotti, Marc A.; Santos, Radleigh G.; Yongye, Austin B.; Sklar, Larry A.; Houghten, Richard A.

2013-01-01

We present a general approach to describe the structure-activity relationships (SAR) of combinatorial data sets with activity for two biological endpoints with emphasis on the rapid identification of substitutions that have a large impact on activity and selectivity. The approach uses Dual-Activity Difference (DAD) maps that represent a visual and quantitative analysis of all pairwise comparisons of one, two, or more substitutions around a molecular template. Scanning the SAR of data sets using DAD maps allows the visual and quantitative identification of activity switches defined as specific substitutions that have an opposite effect on the activity of the compounds against two targets. The approach also rapidly identifies single- and double-target R-cliffs, i.e., compounds where a single or double substitution around the central scaffold dramatically modifies the activity for one or two targets, respectively. The approach introduced in this report can be applied to any analogue series with two biological activity endpoints. To illustrate the approach, we discuss the SAR of 106 pyrrolidine bis-diketopiperazines tested against two formylpeptide receptors obtained from positional scanning deconvolution methods of mixture-based libraries. PMID:23705689

Toxicity challenges in environmental chemicals: Prediction of human plasma protein binding through quantitative structure-activity relationship (QSAR) models (2016 IVIVE Workshop Proceedings)

EPA Science Inventory

Physiologically based pharmacokinetic (PBPK) models bridge the gap between in vitro assays and in vivo effects by accounting for the adsorption, distribution, metabolism, and excretion of xenobiotics, which is especially useful in the assessment of human toxicity. Quantitative st...

QSAR study of anthranilic acid sulfonamides as inhibitors of methionine aminopeptidase-2 using LS-SVM and GRNN based on principal components.

PubMed

Shahlaei, Mohsen; Sabet, Razieh; Ziari, Maryam Bahman; Moeinifard, Behzad; Fassihi, Afshin; Karbakhsh, Reza

2010-10-01

Quantitative relationships between molecular structure and methionine aminopeptidase-2 inhibitory activity of a series of cytotoxic anthranilic acid sulfonamide derivatives were discovered. We have demonstrated the detailed application of two efficient nonlinear methods for evaluation of quantitative structure-activity relationships of the studied compounds. Components produced by principal component analysis as input of developed nonlinear models were used. The performance of the developed models namely PC-GRNN and PC-LS-SVM were tested by several validation methods. The resulted PC-LS-SVM model had a high statistical quality (R(2)=0.91 and R(CV)(2)=0.81) for predicting the cytotoxic activity of the compounds. Comparison between predictability of PC-GRNN and PC-LS-SVM indicates that later method has higher ability to predict the activity of the studied molecules. Copyright (c) 2010 Elsevier Masson SAS. All rights reserved.

Three-dimensional quantitative structure-activity relationship study on anti-cancer activity of 3,4-dihydroquinazoline derivatives against human lung cancer A549 cells

NASA Astrophysics Data System (ADS)

Cho, Sehyeon; Choi, Min Ji; Kim, Minju; Lee, Sunhoe; Lee, Jinsung; Lee, Seok Joon; Cho, Haelim; Lee, Kyung-Tae; Lee, Jae Yeol

2015-03-01

A series of 3,4-dihydroquinazoline derivatives with anti-cancer activities against human lung cancer A549 cells were subjected to three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using the comparative molecular similarity indices analysis (CoMSIA) approaches. The most potent compound, 1 was used to align the molecules. As a result, the best prediction was obtained with CoMSIA combined the steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor fields (q2 = 0.720, r2 = 0.897). This model was validated by an external test set of 6 compounds giving satisfactory predictive r2 value of 0.923 as well as the scrambling stability test. This model would guide the design of potent 3,4-dihydroquinazoline derivatives as anti-cancer agent for the treatment of human lung cancer.

Three classes of glucocerebrosidase inhibitors identified by quantitative high-throughput screening are chaperone leads for Gaucher disease

PubMed Central

Zheng, Wei; Padia, Janak; Urban, Daniel J.; Jadhav, Ajit; Goker-Alpan, Ozlem; Simeonov, Anton; Goldin, Ehud; Auld, Douglas; LaMarca, Mary E.; Inglese, James; Austin, Christopher P.; Sidransky, Ellen

2007-01-01

Gaucher disease is an autosomal recessive lysosomal storage disorder caused by mutations in the glucocerebrosidase gene. Missense mutations result in reduced enzyme activity that may be due to misfolding, raising the possibility of small-molecule chaperone correction of the defect. Screening large compound libraries by quantitative high-throughput screening (qHTS) provides comprehensive information on the potency, efficacy, and structure–activity relationships (SAR) of active compounds directly from the primary screen, facilitating identification of leads for medicinal chemistry optimization. We used qHTS to rapidly identify three structural series of potent, selective, nonsugar glucocerebrosidase inhibitors. The three structural classes had excellent potencies and efficacies and, importantly, high selectivity against closely related hydrolases. Preliminary SAR data were used to select compounds with high activity in both enzyme and cell-based assays. Compounds from two of these structural series increased N370S mutant glucocerebrosidase activity by 40–90% in patient cell lines and enhanced lysosomal colocalization, indicating chaperone activity. These small molecules have potential as leads for chaperone therapy for Gaucher disease, and this paradigm promises to accelerate the development of leads for other rare genetic disorders. PMID:17670938

2D- and 3D-quantitative structure-activity relationship studies for a series of phenazine N,N'-dioxide as antitumour agents.

PubMed

Cunha, Jonathan Da; Lavaggi, María Laura; Abasolo, María Inés; Cerecetto, Hugo; González, Mercedes

2011-12-01

Hypoxic regions of tumours are associated with increased resistance to radiation and chemotherapy. Nevertheless, hypoxia has been used as a tool for specific activation of some antitumour prodrugs, named bioreductive agents. Phenazine dioxides are an example of such bioreductive prodrugs. Our 2D-quantitative structure activity relationship studies established that phenazine dioxides electronic and lipophilic descriptors are related to survival fraction in oxia or in hypoxia. Additionally, statistically significant models, derived by partial least squares, were obtained between survival fraction in oxia and comparative molecular field analysis standard model (r² = 0.755, q² = 0.505 and F = 26.70) or comparative molecular similarity indices analysis-combined steric and electrostatic fields (r² = 0.757, q² = 0.527 and F = 14.93), and survival fraction in hypoxia and comparative molecular field analysis standard model (r² = 0.736, q² = 0.521 and F = 18.63) or comparative molecular similarity indices analysis-hydrogen bond acceptor field (r² = 0.858, q² = 0.737 and F = 27.19). Categorical classification was used for the biological parameter selective cytotoxicity emerging also good models, derived by soft independent modelling of class analogy, with both comparative molecular field analysis standard model (96% of overall classification accuracy) and comparative molecular similarity indices analysis-steric field (92% of overall classification accuracy). 2D- and 3D-quantitative structure-activity relationships models provided important insights into the chemical and structural basis involved in the molecular recognition process of these phenazines as bioreductive agents and should be useful for the design of new structurally related analogues with improved potency. © 2011 John Wiley & Sons A/S.

Are the Chemical Structures in your QSAR Correct?

EPA Science Inventory

Quantitative structure-activity relationships (QSARs) are used to predict many different endpoints, utilize hundreds and even thousands of different parameters (or descriptors), and are created using a variety of approaches. The one thing they all have in common is the assumptio...

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

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

COMPUTER-AIDED DRUG DISCOVERY AND DEVELOPMENT (CADDD): in silico-chemico-biological approach

PubMed Central

Kapetanovic, I.M.

2008-01-01

It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415

Quantitative studies on structure-DPPH• scavenging activity relationships of food phenolic acids.

PubMed

Jing, Pu; Zhao, Shu-Juan; Jian, Wen-Jie; Qian, Bing-Jun; Dong, Ying; Pang, Jie

2012-11-01

Phenolic acids are potent antioxidants, yet the quantitative structure-activity relationships of phenolic acids remain unclear. The purpose of this study was to establish 3D-QSAR models able to predict phenolic acids with high DPPH• scavenging activity and understand their structure-activity relationships. The model has been established by using a training set of compounds with cross-validated q2 = 0.638/0.855, non-cross-validated r2 = 0.984/0.986, standard error of estimate = 0.236/0.216, and F = 139.126/208.320 for the best CoMFA/CoMSIA models. The predictive ability of the models was validated with the correlation coefficient r2(pred) = 0.971/0.996 (>0.6) for each model. Additionally, the contour map results suggested that structural characteristics of phenolics acids favorable for the high DPPH• scavenging activity might include: (1) bulky and/or electron-donating substituent groups on the phenol ring; (2) electron-donating groups at the meta-position and/or hydrophobic groups at the meta-/ortho-position; (3) hydrogen-bond donor/electron-donating groups at the ortho-position. The results have been confirmed based on structural analyses of phenolic acids and their DPPH• scavenging data from eight recent publications. The findings may provide deeper insight into the antioxidant mechanisms and provide useful information for selecting phenolic acids for free radical scavenging properties.

NEW 3D TECHNIQUES FOR RANKING AND PRIORITIZATION OF CHEMICAL INVENTORIES

EPA Science Inventory

New three-dimensional quantitative structure activity (3-D QSAR) techniques for prioritizing chemical inventories for endocrine activity will be presented. The Common Reactivity Pattern (COREPA) approach permits identification of common steric and/or electronic patterns associate...

Common and distinct neural correlates of personal and vicarious reward: A quantitative meta-analysis

PubMed Central

Morelli, Sylvia A.; Sacchet, Matthew D.; Zaki, Jamil

2015-01-01

Individuals experience reward not only when directly receiving positive outcomes (e.g., food or money), but also when observing others receive such outcomes. This latter phenomenon, known as vicarious reward, is a perennial topic of interest among psychologists and economists. More recently, neuroscientists have begun exploring the neuroanatomy underlying vicarious reward. Here we present a quantitative whole-brain meta-analysis of this emerging literature. We identified 25 functional neuroimaging studies that included contrasts between vicarious reward and a neutral control, and subjected these contrasts to an activation likelihood estimate (ALE) meta-analysis. This analysis revealed a consistent pattern of activation across studies, spanning structures typically associated with the computation of value (especially ventromedial prefrontal cortex) and mentalizing (including dorsomedial prefrontal cortex and superior temporal sulcus). We further quantitatively compared this activation pattern to activation foci from a previous meta-analysis of personal reward. Conjunction analyses yielded overlapping VMPFC activity in response to personal and vicarious reward. Contrast analyses identified preferential engagement of the nucleus accumbens in response to personal as compared to vicarious reward, and in mentalizing-related structures in response to vicarious as compared to personal reward. These data shed light on the common and unique components of the reward that individuals experience directly and through their social connections. PMID:25554428

Three-dimensional quantitative structure-activity relationship studies on c-Src inhibitors based on different docking methods.

PubMed

Bairy, Santhosh Kumar; Suneel Kumar, B V S; Bhalla, Joseph Uday Tej; Pramod, A B; Ravikumar, Muttineni

2009-04-01

c-Src kinase play an important role in cell growth and differentiation and its inhibitors can be useful for the treatment of various diseases, including cancer, osteoporosis, and metastatic bone disease. Three dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out on quinazolin derivatives inhibiting c-Src kinase. Molecular field analysis (MFA) models with four different alignment techniques, namely, GLIDE, GOLD, LIGANDFIT and Least squares based methods were developed. glide based MFA model showed better results (Leave one out cross validation correlation coefficient r(2)(cv) = 0.923 and non-cross validation correlation coefficient r(2)= 0.958) when compared with other models. These results help us to understand the nature of descriptors required for activity of these compounds and thereby provide guidelines to design novel and potent c-Src kinase inhibitors.

TIPdb-3D: the three-dimensional structure database of phytochemicals from Taiwan indigenous plants.

PubMed

Tung, Chun-Wei; Lin, Ying-Chi; Chang, Hsun-Shuo; Wang, Chia-Chi; Chen, Ih-Sheng; Jheng, Jhao-Liang; Li, Jih-Heng

2014-01-01

The rich indigenous and endemic plants in Taiwan serve as a resourceful bank for biologically active phytochemicals. Based on our TIPdb database curating bioactive phytochemicals from Taiwan indigenous plants, this study presents a three-dimensional (3D) chemical structure database named TIPdb-3D to support the discovery of novel pharmacologically active compounds. The Merck Molecular Force Field (MMFF94) was used to generate 3D structures of phytochemicals in TIPdb. The 3D structures could facilitate the analysis of 3D quantitative structure-activity relationship, the exploration of chemical space and the identification of potential pharmacologically active compounds using protein-ligand docking. Database URL: http://cwtung.kmu.edu.tw/tipdb. © The Author(s) 2014. Published by Oxford University Press.

Chromanyl-isoxazolidines as Antibacterial agents: Synthesis, Biological Evaluation, Quantitative Structure Activity Relationship, and Molecular Docking Studies.

PubMed

Singh, Gagandeep; Sharma, Anuradha; Kaur, Harpreet; Ishar, Mohan Paul S

2016-02-01

Regio- and stereoselective 1,3-dipolar cycloadditions of C-(chrom-4-one-3-yl)-N-phenylnitrones (N) with different mono-substituted, disubstituted, and cyclic dipolarophiles were carried out to obtain substituted N-phenyl-3'-(chrom-4-one-3-yl)-isoxazolidines (1-40). All the synthesized compounds were assayed for their in vitro antibacterial activity and display significant inhibitory potential; in particular, compound 32 exhibited good inhibitory activity against Salmonella typhymurium-1 & Salmonella typhymurium-2 with minimum inhibitory concentration value of 1.56 μg/mL and also showed good potential against methicillin-resistant Staphylococcus aureus with minimum inhibitory concentration 3.12 μg/mL. Quantitative structure activity relationship investigations with stepwise multiple linear regression analysis and docking simulation studies have been performed for validation of the observed antibacterial potential of the investigated compounds for determination of the most important parameters regulating antibacterial activities. © 2015 John Wiley & Sons A/S.

Critical behavior of subcellular density organization during neutrophil activation and migration.

PubMed

Baker-Groberg, Sandra M; Phillips, Kevin G; Healy, Laura D; Itakura, Asako; Porter, Juliana E; Newton, Paul K; Nan, Xiaolin; McCarty, Owen J T

2015-12-01

Physical theories of active matter continue to provide a quantitative understanding of dynamic cellular phenomena, including cell locomotion. Although various investigations of the rheology of cells have identified important viscoelastic and traction force parameters for use in these theoretical approaches, a key variable has remained elusive both in theoretical and experimental approaches: the spatiotemporal behavior of the subcellular density. The evolution of the subcellular density has been qualitatively observed for decades as it provides the source of image contrast in label-free imaging modalities (e.g., differential interference contrast, phase contrast) used to investigate cellular specimens. While these modalities directly visualize cell structure, they do not provide quantitative access to the structures being visualized. We present an established quantitative imaging approach, non-interferometric quantitative phase microscopy, to elucidate the subcellular density dynamics in neutrophils undergoing chemokinesis following uniform bacterial peptide stimulation. Through this approach, we identify a power law dependence of the neutrophil mean density on time with a critical point, suggesting a critical density is required for motility on 2D substrates. Next we elucidate a continuum law relating mean cell density, area, and total mass that is conserved during neutrophil polarization and migration. Together, our approach and quantitative findings will enable investigators to define the physics coupling cytoskeletal dynamics with subcellular density dynamics during cell migration.

Critical behavior of subcellular density organization during neutrophil activation and migration

PubMed Central

Baker-Groberg, Sandra M.; Phillips, Kevin G.; Healy, Laura D.; Itakura, Asako; Porter, Juliana E.; Newton, Paul K.; Nan, Xiaolin; McCarty, Owen J.T.

2015-01-01

Physical theories of active matter continue to provide a quantitative understanding of dynamic cellular phenomena, including cell locomotion. Although various investigations of the rheology of cells have identified important viscoelastic and traction force parameters for use in these theoretical approaches, a key variable has remained elusive both in theoretical and experimental approaches: the spatiotemporal behavior of the subcellular density. The evolution of the subcellular density has been qualitatively observed for decades as it provides the source of image contrast in label-free imaging modalities (e.g., differential interference contrast, phase contrast) used to investigate cellular specimens. While these modalities directly visualize cell structure, they do not provide quantitative access to the structures being visualized. We present an established quantitative imaging approach, non-interferometric quantitative phase microscopy, to elucidate the subcellular density dynamics in neutrophils undergoing chemokinesis following uniform bacterial peptide stimulation. Through this approach, we identify a power law dependence of the neutrophil mean density on time with a critical point, suggesting a critical density is required for motility on 2D substrates. Next we elucidate a continuum law relating mean cell density, area, and total mass that is conserved during neutrophil polarization and migration. Together, our approach and quantitative findings will enable investigators to define the physics coupling cytoskeletal dynamics with subcellular density dynamics during cell migration. PMID:26640599

Validating a Lifestyle Physical Activity Measure for People with Serious Mental Illness

ERIC Educational Resources Information Center

Bezyak, Jill L.; Chan, Fong; Chiu, Chung-Yi; Kaya, Cahit; Huck, Garrett

2014-01-01

Purpose: To evaluate the measurement structure of the "Physical Activity Scale for Individuals With Physical Disabilities" (PASIPD) as an assessment tool of lifestyle physical activities for people with severe mental illness. Method: A quantitative descriptive research design using factor analysis was employed. A sample of 72 individuals…

TIPdb-3D: the three-dimensional structure database of phytochemicals from Taiwan indigenous plants

PubMed Central

Tung, Chun-Wei; Lin, Ying-Chi; Chang, Hsun-Shuo; Wang, Chia-Chi; Chen, Ih-Sheng; Jheng, Jhao-Liang; Li, Jih-Heng

2014-01-01

The rich indigenous and endemic plants in Taiwan serve as a resourceful bank for biologically active phytochemicals. Based on our TIPdb database curating bioactive phytochemicals from Taiwan indigenous plants, this study presents a three-dimensional (3D) chemical structure database named TIPdb-3D to support the discovery of novel pharmacologically active compounds. The Merck Molecular Force Field (MMFF94) was used to generate 3D structures of phytochemicals in TIPdb. The 3D structures could facilitate the analysis of 3D quantitative structure–activity relationship, the exploration of chemical space and the identification of potential pharmacologically active compounds using protein–ligand docking. Database URL: http://cwtung.kmu.edu.tw/tipdb. PMID:24930145

QSAR, DFT and quantum chemical studies on the inhibition potentials of some carbozones for the corrosion of mild steel in HCl.

PubMed

Eddy, Nnabuk O; Ita, Benedict I

2011-02-01

Experimental aspects of the inhibition of the corrosion of mild steel in HCl solutions by some carbozones were studied using gravimetric, thermometric and gasometric methods, while a theoretical study was carried out using density functional theory, a quantitative structure-activity relation, and quantum chemical principles. The results obtained indicated that the studied carbozones are good adsorption inhibitors for the corrosion of mild steel in HCl. The inhibition efficiencies of the studied carbozones were found to increase with increasing concentration of the respective inhibitor. A strong correlation was found between the average inhibition efficiency and some quantum chemical parameters, and also between the experimental and theoretical inhibition efficiencies (obtained from the quantitative structure-activity relation).

Correlation between structure, retention, property, and activity of biologically relevant 1,7-bis(aminoalkyl)diazachrysene derivatives.

PubMed

Šegan, Sandra; Trifković, Jelena; Verbić, Tatjana; Opsenica, Dejan; Zlatović, Mario; Burnett, James; Šolaja, Bogdan; Milojković-Opsenica, Dušanka

2013-01-01

The physicochemical properties, retention parameters (R(M)(0)), partition coefficients (logP(OW)), and pK(a) values for a series of thirteen 1,7-bis(aminoalkyl) diazachrysene (1,7-DAAC) derivatives were determined in order to reveal the characteristics responsible for their biological behavior. The investigated compounds inhibit three unrelated pathogens (the Botulinum neurotoxin serotype A light chain (BoNT/A LC), Plasmodium falciparum malaria, and Ebola filovirus) via three different mechanisms of action. To determine the most influential factors governing the retention and activities of the investigated diazachrysenes, R(M)(0), logP(OW), and biological activity values were correlated with 2D and 3D molecular descriptors, using a partial least squares regression. The resulting quantitative structure-retention (property) relationships indicate the importance of descriptors related to the hydrophobicity of the molecules (e.g., predicted partition coefficients and hydrophobic surface area). Quantitative structure-activity relationship models for describing biological activity against the BoNT/A LC and malarial strains also include overall compound polarity, electron density distribution, and proton donor/acceptor potential. Furthermore, models for Ebola filovirus inhibition are presented qualitatively to provide insights into parameters that may contribute to the compounds' antiviral activities. Overall, the models form the basis for selecting structural features that significantly affect the compound's absorption, distribution, metabolism, excretion, and toxicity profiles. Copyright © 2012 Elsevier B.V. All rights reserved.

Quantitative structure parameters from the NMR spectroscopy of quadrupolar nuclei

DOE PAGES

Perras, Frederic A.

2015-12-15

Here, nuclear magnetic resonance (NMR) spectroscopy is one of the most important characterization tools in chemistry, however, 3/4 of the NMR active nuclei are underutilized due to their quadrupolar nature. This short review centers on the development of methods that use solid-state NMR of quadrupolar nuclei for obtaining quantitative structural information. Namely, techniques using dipolar recoupling as well as the resolution afforded by double-rotation are presented for the measurement of spin–spin coupling between quadrupoles, enabling the measurement of internuclear distances and connectivities.

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.

On Topological Indices of Certain Families of Nanostar Dendrimers.

PubMed

Husin, Mohamad Nazri; Hasni, Roslan; Arif, Nabeel Ezzulddin; Imran, Muhammad

2016-06-24

A topological index of graph G is a numerical parameter related to G which characterizes its molecular topology and is usually graph invariant. In the field of quantitative structure-activity (QSAR)/quantitative structure-activity structure-property (QSPR) research, theoretical properties of the chemical compounds and their molecular topological indices such as the Randić connectivity index, atom-bond connectivity (ABC) index and geometric-arithmetic (GA) index are used to predict the bioactivity of different chemical compounds. A dendrimer is an artificially manufactured or synthesized molecule built up from the branched units called monomers. In this paper, the fourth version of ABC index and the fifth version of GA index of certain families of nanostar dendrimers are investigated. We derive the analytical closed formulas for these families of nanostar dendrimers. The obtained results can be of use in molecular data mining, particularly in researching the uniqueness of tested (hyper-branched) molecular graphs.

20180312 - Structure-based QSAR Models to Predict Systemic Toxicity Points of Departure (SOT)

EPA Science Inventory

Human health risk assessment associated with environmental chemical exposure is limited by the tens of thousands of chemicals with little or no experimental in vivo toxicity data. Data gap filling techniques, such as quantitative structure activity relationship (QSAR) models base...

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

PubMed Central

Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J.

2014-01-01

Abstract. Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed. PMID:26157976

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders.

PubMed

Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J

2014-10-01

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

Structure modification and functionality of whey proteins: quantitative structure-activity relationship approach.

PubMed

Nakai, S; Li-Chan, E

1985-10-01

According to the original idea of quantitative structure-activity relationship, electric, hydrophobic, and structural parameters should be taken into consideration for elucidating functionality. Changes in these parameters are reflected in the property of protein solubility upon modification of whey proteins by heating. Although solubility is itself a functional property, it has been utilized to explain other functionalities of proteins. However, better correlations were obtained when hydrophobic parameters of the proteins were used in conjunction with solubility. Various treatments reported in the literature were applied to whey protein concentrate in an attempt to obtain whipping and gelling properties similar to those of egg white. Mapping simplex optimization was used to search for the best results. Improvement in whipping properties by pepsin hydrolysis may have been due to higher protein solubility, and good gelling properties resulting from polyphosphate treatment may have been due to an increase in exposable hydrophobicity. However, the results of angel food cake making were still unsatisfactory.

Hologram quantitative structure-activity relationship and comparative molecular field analysis studies within a series of tricyclic phthalimide HIV-1 integrase inhibitors.

PubMed

Magalhães, Uiaran de Oliveira; Souza, Alessandra Mendonça Teles de; Albuquerque, Magaly Girão; Brito, Monique Araújo de; Bello, Murilo Lamim; Cabral, Lucio Mendes; Rodrigues, Carlos Rangel

2013-01-01

Acquired immunodeficiency syndrome is a public health problem worldwide caused by the Human immunodeficiency virus (HIV). Treatment with antiretroviral drugs is the best option for viral suppression, reducing morbidity and mortality. However, viral resistance in HIV-1 therapy has been reported. HIV-1 integrase (IN) is an essential enzyme for effective viral replication and an attractive target for the development of new inhibitors. In the study reported here, two- and three-dimensional quantitative structure-activity relationship (2D/3D-QSAR) studies, applying hologram quantitative structure-activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) methods, respectively, were performed on a series of tricyclic phthalimide HIV-1 IN inhibitors. The best HQSAR model (q (2) = 0.802, r (2) = 0.972) was obtained using atoms, bonds, and connectivity as the fragment distinction, a fragment size of 2-5 atoms, hologram length of 61 bins, and six components. The best CoMFA model (q (2) = 0.748, r (2) = 0.974) was obtained with alignment of all atoms of the tricyclic phthalimide moiety (alignment II). The HQSAR contribution map identified that the carbonyl-hydroxy-aromatic nitrogen motif made a positive contribution to the activity of the compounds. Furthermore, CoMFA contour maps suggested that bulky groups in meta and para positions in the phenyl ring would increase the biological activity of this class. The conclusions of this work may lead to a better understanding of HIV-1 IN inhibition and contribute to the design of new and more potent derivatives.

How quantitative measures unravel design principles in multi-stage phosphorylation cascades.

PubMed

Frey, Simone; Millat, Thomas; Hohmann, Stefan; Wolkenhauer, Olaf

2008-09-07

We investigate design principles of linear multi-stage phosphorylation cascades by using quantitative measures for signaling time, signal duration and signal amplitude. We compare alternative pathway structures by varying the number of phosphorylations and the length of the cascade. We show that a model for a weakly activated pathway does not reflect the biological context well, unless it is restricted to certain parameter combinations. Focusing therefore on a more general model, we compare alternative structures with respect to a multivariate optimization criterion. We test the hypothesis that the structure of a linear multi-stage phosphorylation cascade is the result of an optimization process aiming for a fast response, defined by the minimum of the product of signaling time and signal duration. It is then shown that certain pathway structures minimize this criterion. Several popular models of MAPK cascades form the basis of our study. These models represent different levels of approximation, which we compare and discuss with respect to the quantitative measures.

Quantitative Structure-Activity Relationship Modeling Coupled with Molecular Docking Analysis in Screening of Angiotensin I-Converting Enzyme Inhibitory Peptides from Qula Casein Hydrolysates Obtained by Two-Enzyme Combination Hydrolysis.

PubMed

Lin, Kai; Zhang, Lanwei; Han, Xue; Meng, Zhaoxu; Zhang, Jianming; Wu, Yifan; Cheng, Dayou

2018-03-28

In this study, Qula casein derived from yak milk casein was hydrolyzed using a two-enzyme combination approach, and high angiotensin I-converting enzyme (ACE) inhibitory activity peptides were screened by quantitative structure-activity relationship (QSAR) modeling integrated with molecular docking analysis. Hydrolysates (<3 kDa) derived from combinations of thermolysin + alcalase and thermolysin + proteinase K demonstrated high ACE inhibitory activities. Peptide sequences in hydrolysates derived from these two combinations were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). On the basis of the QSAR modeling prediction, a total of 16 peptides were selected for molecular docking analysis. The docking study revealed that four of the peptides (KFPQY, MPFPKYP, MFPPQ, and QWQVL) bound the active site of ACE. These four novel peptides were chemically synthesized, and their IC 50 was determined. Among these peptides, KFPQY showed the highest ACE inhibitory activity (IC 50 = 12.37 ± 0.43 μM). Our study indicated that Qula casein presents an excellent source to produce ACE inhibitory peptides.

Progress with modeling activity landscapes in drug discovery.

PubMed

Vogt, Martin

2018-04-19

Activity landscapes (ALs) are representations and models of compound data sets annotated with a target-specific activity. In contrast to quantitative structure-activity relationship (QSAR) models, ALs aim at characterizing structure-activity relationships (SARs) on a large-scale level encompassing all active compounds for specific targets. The popularity of AL modeling has grown substantially with the public availability of large activity-annotated compound data sets. AL modeling crucially depends on molecular representations and similarity metrics used to assess structural similarity. Areas covered: The concepts of AL modeling are introduced and its basis in quantitatively assessing molecular similarity is discussed. The different types of AL modeling approaches are introduced. AL designs can broadly be divided into three categories: compound-pair based, dimensionality reduction, and network approaches. Recent developments for each of these categories are discussed focusing on the application of mathematical, statistical, and machine learning tools for AL modeling. AL modeling using chemical space networks is covered in more detail. Expert opinion: AL modeling has remained a largely descriptive approach for the analysis of SARs. Beyond mere visualization, the application of analytical tools from statistics, machine learning and network theory has aided in the sophistication of AL designs and provides a step forward in transforming ALs from descriptive to predictive tools. To this end, optimizing representations that encode activity relevant features of molecules might prove to be a crucial step.

Identifying Metabolically Active Chemicals Using a Consensus Quantitative Structure Activity Model for Estrogen Receptor Binding

EPA Science Inventory

Endocrine disrupting chemicals (EDCs) are abundant throughout the environment and can alter neurodevelopment, behavior, and reproductive success of humans and other species by perturbing signaling pathways related to the estrogen receptor (ER). A recent study compared results acr...

Quantitative Collection and Enzymatic Activity of Glucose Oxidase Nanotubes Fabricated by Templated Layer-by-Layer Assembly.

PubMed

Zhang, Shouwei; Demoustier-Champagne, Sophie; Jonas, Alain M

2015-08-10

We report on the fabrication of enzyme nanotubes in nanoporous polycarbonate membranes via the layer-by-layer (LbL) alternate assembly of polyethylenimine (PEI) and glucose oxidase (GOX), followed by dissolution of the sacrificial template in CH2Cl2, collection, and final dispersion in water. An adjuvant-assisted filtration methodology is exploited to extract quantitatively the nanotubes without loss of activity and morphology. Different water-soluble CH2Cl2-insoluble adjuvants are tested for maximal enzyme activity and nanotube stability; whereas NaCl disrupts the tubes by screening electrostatic interactions, the high osmotic pressure created by fructose also contributes to loosening the nanotubular structures. These issues are solved when using neutral, high molar mass dextran. The enzymatic activity of intact free nanotubes in water is then quantitatively compared to membrane-embedded nanotubes, showing that the liberated nanotubes have a higher catalytic activity in proportion to their larger exposed surface. Our study thus discloses a robust and general methodology for the fabrication and quantitative collection of enzymatic nanotubes and shows that LbL assembly provides access to efficient enzyme carriers for use as catalytic swarming agents.

A Short Review of the Generation of Molecular Descriptors and Their Applications in Quantitative Structure Property/Activity Relationships.

PubMed

Sahoo, Sagarika; Adhikari, Chandana; Kuanar, Minati; Mishra, Bijay K

2016-01-01

Synthesis of organic compounds with specific biological activity or physicochemical characteristics needs a thorough analysis of the enumerable data set obtained from literature. Quantitative structure property/activity relationships have made it simple by predicting the structure of the compound with any optimized activity. For that there is a paramount data set of molecular descriptors (MD). This review is a survey on the generation of the molecular descriptors and its probable applications in QSP/AR. Literatures have been collected from a wide class of research journals, citable web reports, seminar proceedings and books. The MDs were classified according to their generation. The applications of the MDs on the QSP/AR have also been reported in this review. The MDs can be classified into experimental and theoretical types, having a sub classification of the later into structural and quantum chemical descriptors. The structural parameters are derived from molecular graphs or topology of the molecules. Even the pixel of the molecular image can be used as molecular descriptor. In QSPR studies the physicochemical properties include boiling point, heat capacity, density, refractive index, molar volume, surface tension, heat of formation, octanol-water partition coefficient, solubility, chromatographic retention indices etc. Among biological activities toxicity, antimalarial activity, sensory irritant, potencies of local anesthetic, tadpole narcosis, antifungal activity, enzyme inhibiting activity are some important parameters in the QSAR studies. The classification of the MDs is mostly generic in nature. The application of the MDs in QSP/AR also has a generic link. Experimental MDs are more suitable in correlation analysis than the theoretical ones but are more expensive for generation. In advent of sophisticated computational tools and experimental design proliferation of MDs is inevitable, but for a highly optimized MD, studies on generation of MD is an unending process.

4-Aminoquinolines Active against Chloroquine-Resistant Plasmodium falciparum: Basis of Antiparasite Activity and Quantitative Structure-Activity Relationship Analyses▿

PubMed Central

Hocart, Simon J.; Liu, Huayin; Deng, Haiyan; De, Dibyendu; Krogstad, Frances M.; Krogstad, Donald J.

2011-01-01

Chloroquine (CQ) is a safe and economical 4-aminoquinoline (AQ) antimalarial. However, its value has been severely compromised by the increasing prevalence of CQ resistance. This study examined 108 AQs, including 68 newly synthesized compounds. Of these 108 AQs, 32 (30%) were active only against CQ-susceptible Plasmodium falciparum strains and 59 (55%) were active against both CQ-susceptible and CQ-resistant P. falciparum strains (50% inhibitory concentrations [IC50s], ≤25 nM). All AQs active against both CQ-susceptible and CQ-resistant P. falciparum strains shared four structural features: (i) an AQ ring without alkyl substitution, (ii) a halogen at position 7 (Cl, Br, or I but not F), (iii) a protonatable nitrogen at position 1, and (iv) a second protonatable nitrogen at the end of the side chain distal from the point of attachment to the AQ ring via the nitrogen at position 4. For activity against CQ-resistant parasites, side chain lengths of ≤3 or ≥10 carbons were necessary but not sufficient; they were identified as essential factors by visual comparison of 2-dimensional (2-D) structures in relation to the antiparasite activities of the AQs and were confirmed by computer-based 3-D comparisons and differential contour plots of activity against P. falciparum. The advantage of the method reported here (refinement of quantitative structure-activity relationship [QSAR] descriptors by random assignment of compounds to multiple training and test sets) is that it retains QSAR descriptors according to their abilities to predict the activities of unknown test compounds rather than according to how well they fit the activities of the compounds in the training sets. PMID:21383099

Experimental and QSAR study on the surface activities of alkyl imidazoline surfactants

NASA Astrophysics Data System (ADS)

Kong, Xiangjun; Qian, Chengduo; Fan, Weiyu; Liang, Zupei

2018-03-01

15 alkyl imidazoline surfactants with different structures were synthesized and their critical micelle concentration (CMC) and surface tension under the CMC (σcmc) in aqueous solution were measured at 298 K. 54 kinds of molecular structure descriptors were selected as independent variables and the quantitative structure-activity relationship (QSAR) between surface activities of alkyl imidazoline and molecular structure were built through the genetic function approximation (GFA) method. Experimental results showed that the maximum surface excess of alkyl imidazoline molecules at the gas-liquid interface increased and the area occupied by each surfactant molecule and the free energies of micellization ΔGm decreased with increasing carbon number (NC) of the hydrophobic chain or decreasing hydrophilicity of counterions, which resulted in a CMC and σcmc decrease, while the log CMC and NC had a linear relationship and a negative correlation. The GFA-QSAR model, which was generated by a training set composed of 13 kinds of alkyl imidazoline though GFA method regression analysis, was highly correlated with predicted values and experimental values of the CMC. The correlation coefficient R was 0.9991, which means high prediction accuracy. The prediction error of 2 kinds of alkyl imidazoline CMCs in the Validation Set that quantitatively analyzed the influence of the alkyl imidazoline molecular structure on the CMC was less than 4%.

Quantitative structure property relationships for the adsorption of pharmaceuticals onto activated carbon.

PubMed

Dickenson, E R V; Drewes, J E

2010-01-01

Isotherms were determined for the adsorption of five pharmaceutical residues, primidone, carbamazepine, ibuprofen, naproxen and diclofenac, to Calgon Filtrasorb 300 powdered activated carbon (PAC). The sorption behavior was examined in ultra-pure and wastewater effluent organic matter (EfOM) matrices, where more sorption was observed in the ultra-pure water for PAC doses greater than 10 mg/L suggesting the presence of EfOM hinders the sorption of the pharmaceuticals to the PAC. Adsorption behaviors were described by the Freundlich isotherm model. Quantitative structure property relationships (QSPRs) in the form of polyparameter linear solvation energy relationships were developed for simulating the Freundlich adsorption capacity in both ultra-pure and EfOM matrices. The significant 3D-based descriptors for the QSPRs were the molar volume, polarizability and hydrogen-bond donor parameters.

On the virtues of automated quantitative structure-activity relationship: the new kid on the block.

PubMed

de Oliveira, Marcelo T; Katekawa, Edson

2018-02-01

Quantitative structure-activity relationship (QSAR) has proved to be an invaluable tool in medicinal chemistry. Data availability at unprecedented levels through various databases have collaborated to a resurgence in the interest for QSAR. In this context, rapid generation of quality predictive models is highly desirable for hit identification and lead optimization. We showcase the application of an automated QSAR approach, which randomly selects multiple training/test sets and utilizes machine-learning algorithms to generate predictive models. Results demonstrate that AutoQSAR produces models of improved or similar quality to those generated by practitioners in the field but in just a fraction of the time. Despite the potential of the concept to the benefit of the community, the AutoQSAR opportunity has been largely undervalued.

AutoQSAR: an automated machine learning tool for best-practice quantitative structure-activity relationship modeling.

PubMed

Dixon, Steven L; Duan, Jianxin; Smith, Ethan; Von Bargen, Christopher D; Sherman, Woody; Repasky, Matthew P

2016-10-01

We introduce AutoQSAR, an automated machine-learning application to build, validate and deploy quantitative structure-activity relationship (QSAR) models. The process of descriptor generation, feature selection and the creation of a large number of QSAR models has been automated into a single workflow within AutoQSAR. The models are built using a variety of machine-learning methods, and each model is scored using a novel approach. Effectiveness of the method is demonstrated through comparison with literature QSAR models using identical datasets for six end points: protein-ligand binding affinity, solubility, blood-brain barrier permeability, carcinogenicity, mutagenicity and bioaccumulation in fish. AutoQSAR demonstrates similar or better predictive performance as compared with published results for four of the six endpoints while requiring minimal human time and expertise.

Quantitative structure-activity relationships studies of CCR5 inhibitors and toxicity of aromatic compounds using gene expression programming.

PubMed

Shi, Weimin; Zhang, Xiaoya; Shen, Qi

2010-01-01

Quantitative structure-activity relationship (QSAR) study of chemokine receptor 5 (CCR5) binding affinity of substituted 1-(3,3-diphenylpropyl)-piperidinyl amides and ureas and toxicity of aromatic compounds have been performed. The gene expression programming (GEP) was used to select variables and produce nonlinear QSAR models simultaneously using the selected variables. In our GEP implementation, a simple and convenient method was proposed to infer the K-expression from the number of arguments of the function in a gene, without building the expression tree. The results were compared to those obtained by artificial neural network (ANN) and support vector machine (SVM). It has been demonstrated that the GEP is a useful tool for QSAR modeling. Copyright 2009 Elsevier Masson SAS. All rights reserved.

PREDICTING THE ADSORPTION CAPACITY OF ACTIVATED CARBON FOR ORGANIC CONTAMINANTS FROM ADSORBENT AND ADSORBATE PROPERTIES

EPA Science Inventory

A quantitative structure-property relationship (QSPR) was developed and combined with the Polanyi-Dubinin-Manes model to predict adsorption isotherms of emerging contaminants on activated carbons with a wide range of physico-chemical properties. Affinity coefficients (β_l

Identifying Metabolically Active Chemicals Using a Consensus Quantitative Structure Activity Relationship Model for Estrogen Receptor Binding

EPA Science Inventory

Traditional toxicity testing provides insight into the mechanisms underlying toxicological responses but requires a high investment in a large number of resources. The new paradigm of testing approaches involves rapid screening studies able to evaluate thousands of chemicals acro...

Quantitative Structure-Activity Relationships for Organophosphate Enzyme Inhibition (Briefing Charts)

DTIC Science & Technology

2011-09-22

OPs) are a group of pesticides that inhibit enzymes such as acetylcholinesterase. Numerous OP structural variants exist and toxicity data can be...and human toxicity studies especially for OPs lacking experimental data. 15. SUBJECT TERMS QSAR Organophosphates...structure and mechanism of toxicity c) Linking QSAR and OP PBPK/PD 2. Methods a) Physiochemical Descriptors b) Regression Techniques 3. Results a

Exploiting mAb structure characteristics for a directed QbD implementation in early process development.

PubMed

Karlberg, Micael; von Stosch, Moritz; Glassey, Jarka

2018-03-07

In today's biopharmaceutical industries, the lead time to develop and produce a new monoclonal antibody takes years before it can be launched commercially. The reasons lie in the complexity of the monoclonal antibodies and the need for high product quality to ensure clinical safety which has a significant impact on the process development time. Frameworks such as quality by design are becoming widely used by the pharmaceutical industries as they introduce a systematic approach for building quality into the product. However, full implementation of quality by design has still not been achieved due to attrition mainly from limited risk assessment of product properties as well as the large number of process factors affecting product quality that needs to be investigated during the process development. This has introduced a need for better methods and tools that can be used for early risk assessment and predictions of critical product properties and process factors to enhance process development and reduce costs. In this review, we investigate how the quantitative structure-activity relationships framework can be applied to an existing process development framework such as quality by design in order to increase product understanding based on the protein structure of monoclonal antibodies. Compared to quality by design, where the effect of process parameters on the drug product are explored, quantitative structure-activity relationships gives a reversed perspective which investigates how the protein structure can affect the performance in different unit operations. This provides valuable information that can be used during the early process development of new drug products where limited process understanding is available. Thus, quantitative structure-activity relationships methodology is explored and explained in detail and we investigate the means of directly linking the structural properties of monoclonal antibodies to process data. The resulting information as a decision tool can help to enhance the risk assessment to better aid process development and thereby overcome some of the limitations and challenges present in QbD implementation today.

Quantitative structure-activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods.

PubMed

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure-activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7-7-1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure-activity relationship model suggested is robust and satisfactory.

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

PubMed

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

2009-10-01

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

Quantitative structure-cytotoxicity relationship of piperic acid amides.

PubMed

Shimada, Chiyako; Uesawa, Yoshihiro; Ishihara, Mariko; Kagaya, Hajime; Kanamoto, Taisei; Terakubo, Shigemi; Nakashima, Hideki; Takao, Koichi; Miyashiro, Takaki; Sugita, Yoshiaki; Sakagami, Hiroshi

2014-09-01

A total of 12 piperic acid amides, including piperine, were subjected to quantitative structure-activity relationship (QSAR) analysis, based on their cytotoxicity, tumor selectivity and anti-HIV activity, in order to find new biological activities. Cytotoxicity against four human oral squamous cell carcinoma (OSCC) cell lines and three human oral normal cells was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Tumor selectivity was evaluated by the ratio of the mean 50% cytotoxic concentration (CC50) against normal oral cells to that against OSCC cell lines. Anti-HIV activity was evaluated by the ratio of the CC50 to 50% HIV infection-cytoprotective concentration (EC50). Physicochemical, structural, and quantum-chemical parameters were calculated based on the conformations optimized by LowModeMD method followed by density functional theory method. All compounds showed low-to-moderate tumor selectivity, but no anti-HIV activity. N-Piperoyldopamine ( 8: ) which has a catechol moiety, showed the highest tumor selectivity, possibly due to its unique molecular shape and electrostatic interaction, especially its largest partial equalization of orbital electronegativities and vsurf descriptors. The present study suggests that molecular shape and ability for electrostatic interaction are useful parameters for estimating the tumor selectivity of piperic acid amides. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Effect of substituents on prediction of TLC retention of tetra-dentate Schiff bases and their Copper(II) and Nickel(II) complexes.

PubMed

Stevanović, Nikola R; Perušković, Danica S; Gašić, Uroš M; Antunović, Vesna R; Lolić, Aleksandar Đ; Baošić, Rada M

2017-03-01

The objectives of this study were to gain insights into structure-retention relationships and to propose the model to estimating their retention. Chromatographic investigation of series of 36 Schiff bases and their copper(II) and nickel(II) complexes was performed under both normal- and reverse-phase conditions. Chemical structures of the compounds were characterized by molecular descriptors which are calculated from the structure and related to the chromatographic retention parameters by multiple linear regression analysis. Effects of chelation on retention parameters of investigated compounds, under normal- and reverse-phase chromatographic conditions, were analyzed by principal component analysis, quantitative structure-retention relationship and quantitative structure-activity relationship models were developed on the basis of theoretical molecular descriptors, calculated exclusively from molecular structure, and parameters of retention and lipophilicity. Copyright © 2016 John Wiley & Sons, Ltd.

HomoSAR: bridging comparative protein modeling with quantitative structural activity relationship to design new peptides.

PubMed

Borkar, Mahesh R; Pissurlenkar, Raghuvir R S; Coutinho, Evans C

2013-11-15

Peptides play significant roles in the biological world. To optimize activity for a specific therapeutic target, peptide library synthesis is inevitable; which is a time consuming and expensive. Computational approaches provide a promising way to simply elucidate the structural basis in the design of new peptides. Earlier, we proposed a novel methodology termed HomoSAR to gain insight into the structure activity relationships underlying peptides. Based on an integrated approach, HomoSAR uses the principles of homology modeling in conjunction with the quantitative structural activity relationship formalism to predict and design new peptide sequences with the optimum activity. In the present study, we establish that the HomoSAR methodology can be universally applied to all classes of peptides irrespective of sequence length by studying HomoSAR on three peptide datasets viz., angiotensin-converting enzyme inhibitory peptides, CAMEL-s antibiotic peptides, and hAmphiphysin-1 SH3 domain binding peptides, using a set of descriptors related to the hydrophobic, steric, and electronic properties of the 20 natural amino acids. Models generated for all three datasets have statistically significant correlation coefficients (r(2)) and predictive r2 (r(pred)2) and cross validated coefficient ( q(LOO)2). The daintiness of this technique lies in its simplicity and ability to extract all the information contained in the peptides to elucidate the underlying structure activity relationships. The difficulties of correlating both sequence diversity and variation in length of the peptides with their biological activity can be addressed. The study has been able to identify the preferred or detrimental nature of amino acids at specific positions in the peptide sequences. Copyright © 2013 Wiley Periodicals, Inc.

Inositolphosphoglycan mediators structurally related to glycosyl phosphatidylinositol anchors: synthesis, structure and biological activity.

PubMed

Martín-Lomas, M; Khiar, N; García, S; Koessler, J L; Nieto, P M; Rademacher, T W

2000-10-02

The preparation of the pseudopentasaccharide 1a, an inositol-phosphoglycan (IPG) that contains the conserved linear structure of glycosyl phosphatidylinositol anchors (GPI anchors), was carried out by using a highly convergent 2+3-block synthesis approach which involves imidate and sulfoxide glycosylation reactions. The preferred solution conformation of this structure was determined by using NMR spectroscopy and molecular dynamics simulations prior to carrying out quantitative structure--activity relationship studies in connection with the insulin signalling process. The ability of 1a to stimulate lipogenesis in rat adipocytes as well as to inhibit cAMP dependent protein kinase and to activate pyruvate dehydrogenase phosphatase was investigated. Compound 1a did not show any significant activity, which may be taken as a strong indication that the GPI anchors are not the precursors of the IPG mediators.

PREDICTING THE ADSORPTION CAPACITY OF ACTIVATED CARBON FOR EMERGING ORGANIC CONTAMINANTS FROM FUNDAMENTAL ADSORBENT AND ADSORBATE PROPERTIES - PRESENTATION

EPA Science Inventory

A quantitative structure-property relationship (QSPR) was developed and combined with the Polanyi-Dubinin-Manes model to predict adsorption isotherms of emerging contaminants on activated carbons with a wide range of physico-chemical properties. Affinity coefficients (β_l

Characteristics of urban parks associated with park use and physical activity: a review of qualitative research.

PubMed

McCormack, Gavin R; Rock, Melanie; Toohey, Ann M; Hignell, Danica

2010-07-01

Given that recent literature reviews on physical activity in urban parks deliberately excluded qualitative findings, we reviewed qualitative research on this topic informed by a published classification scheme based on quantitative research. Twenty-one studies met our inclusion criteria. These studies relied mainly on semi-structured interviews with individuals or in focus groups; only five studies involved in situ observation. Our synthesis aligns with previous quantitative research showing that attributes including safety, aesthetics, amenities, maintenance, and proximity are important for encouraging park use. Furthermore, our synthesis of qualitative research suggests that perceptions of the social environment entwine inextricably with perceptions of the physical environment. If so, physical attributes of parks as well as perceptions of these attributes (formed in relation to broader social contexts) may influence physical activity patterns. Both qualitative and quantitative methods provide useful information for interpreting such patterns, and in particular, when designing and assessing interventions intended to improve the amount and intensity of physical activity. 2010 Elsevier Ltd. All rights reserved.

Evolution of the international workshops on quantitative structure-activity relationships (QSARs) in environmental toxicology.

PubMed

Kaiser, K L E

2007-01-01

This presentation will review the evolution of the workshops from a scientific and personal perspective. From their modest beginning in 1983, the workshops have developed into larger international meetings, regularly held every two years. Their initial focus on the aquatic sphere soon expanded to include properties and effects on atmospheric and terrestrial species, including man. Concurrent with this broadening of their scientific scope, the workshops have become an important forum for the early dissemination of all aspects of qualitative and quantitative structure-activity research in ecotoxicology and human health effects. Over the last few decades, the field of quantitative structure/activity relationships (QSARs) has quickly emerged as a major scientific method in understanding the properties and effects of chemicals on the environment and human health. From substances that only affect cell membranes to those that bind strongly to a specific enzyme, QSARs provides insight into the biological effects and chemical and physical properties of substances. QSARs are useful for delineating the quantitative changes in biological effects resulting from minor but systematic variations of the structure of a compound with a specific mode of action. In addition, more holistic approaches are being devised that result in our ability to predict the effects of structurally unrelated compounds with (potentially) different modes of action. Research in QSAR environmental toxicology has led to many improvements in the manufacturing, use, and disposal of chemicals. Furthermore, it has led to national policies and international agreements, from use restrictions or outright bans of compounds, such as polychlorinated biphenyls (PCBs), mirex, and highly chlorinated pesticides (e.g. DDT, dieldrin) for the protection of avian predators, to alternatives for ozone-depleting compounds, to better waste treatment systems, to more powerful and specific acting drugs. Most of the recent advances in drug development could not have been achieved without the use of QSARs in one form or another. The pace of such developments is rapid and QSARs are the keystone to that progress. These workshops have contributed to this progress and will continue to do so in the future.

qPCR for Second Year Undergraduates: A Short, Structured Inquiry to Illustrate Differential Gene Expression

ERIC Educational Resources Information Center

McCauslin, Christine Seitz; Gunn, Kathryn Elaine; Pirone, Dana; Staiger, Jennifer

2015-01-01

We describe a structured inquiry laboratory exercise that examines transcriptional regulation of the "NOS2" gene under conditions that simulate the inflammatory response in macrophages. Using quantitative PCR and the comparative C[subscript T] method, students are able determine whether transcriptional activation of "NOS2"…

Quantitative NDE of Composite Structures at NASA

NASA Technical Reports Server (NTRS)

Cramer, K. Elliott; Leckey, Cara A. C.; Howell, Patricia A.; Johnston, Patrick H.; Burke, Eric R.; Zalameda, Joseph N.; Winfree, William P.; Seebo, Jeffery P.

2015-01-01

The use of composite materials continues to increase in the aerospace community due to the potential benefits of reduced weight, increased strength, and manufacturability. Ongoing work at NASA involves the use of the large-scale composite structures for spacecraft (payload shrouds, cryotanks, crew modules, etc). NASA is also working to enable the use and certification of composites in aircraft structures through the Advanced Composites Project (ACP). The rapid, in situ characterization of a wide range of the composite materials and structures has become a critical concern for the industry. In many applications it is necessary to monitor changes in these materials over a long time. The quantitative characterization of composite defects such as fiber waviness, reduced bond strength, delamination damage, and microcracking are of particular interest. The research approaches of NASA's Nondestructive Evaluation Sciences Branch include investigation of conventional, guided wave, and phase sensitive ultrasonic methods, infrared thermography and x-ray computed tomography techniques. The use of simulation tools for optimizing and developing these methods is also an active area of research. This paper will focus on current research activities related to large area NDE for rapidly characterizing aerospace composites.

Molecule kernels: a descriptor- and alignment-free quantitative structure-activity relationship approach.

PubMed

Mohr, Johannes A; Jain, Brijnesh J; Obermayer, Klaus

2008-09-01

Quantitative structure activity relationship (QSAR) analysis is traditionally based on extracting a set of molecular descriptors and using them to build a predictive model. In this work, we propose a QSAR approach based directly on the similarity between the 3D structures of a set of molecules measured by a so-called molecule kernel, which is independent of the spatial prealignment of the compounds. Predictors can be build using the molecule kernel in conjunction with the potential support vector machine (P-SVM), a recently proposed machine learning method for dyadic data. The resulting models make direct use of the structural similarities between the compounds in the test set and a subset of the training set and do not require an explicit descriptor construction. We evaluated the predictive performance of the proposed method on one classification and four regression QSAR datasets and compared its results to the results reported in the literature for several state-of-the-art descriptor-based and 3D QSAR approaches. In this comparison, the proposed molecule kernel method performed better than the other QSAR methods.

A Comparative Study on Selective PPAR Modulators through Quantitative Structure-activity Relationship, Pharmacophore and Docking Analyses.

PubMed

Nandy, Ashis; Roy, Kunal; Saha, Achintya

2018-01-01

Metabolic syndrome is a matrix of different metabolic disorders which are the leading cause of death in human beings. Peroxysome proliferated activated receptor (PPAR) is a nuclear receptor involved in metabolism of fats and glucose. In order to explore structural requirements for selective PPAR modulators to control lipid and carbohydrate metabolism, the multi-cheminformatics studies have been performed. In silico modeling studies have been performed on a diverse set of PPAR modulators through quantitative structure-activity relationship (QSAR), pharmacophore mapping and docking studies. It is observed that the presence of an amide fragment (-CONHRPh) has a detrimental effect while an aliphatic ether linkage has a beneficial effect on PPARα modulation. On the other hand, the presence of an amide fragment has a positive effect on PPARδ modulation, but the aliphatic ether linkage and substituted aromatic ring in the molecular scaffold are very much essential for imparting potent and selective PPARγ modulation. Negative ionizable features (i.e. polar fragments) must be present in PPARδ and α modulators, but a hydrophobic feature is the prime requirement for PPARγ modulation. Here, the essential structural features have been explored for selective modulation of each subtype of PPAR in order to design new modulators with improved activity/selectivity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

In Vitro Antioxidant Activity of Selected 4-Hydroxy-chromene-2-one Derivatives—SAR, QSAR and DFT Studies

PubMed Central

Mladenović, Milan; Mihailović, Mirjana; Bogojević, Desanka; Matić, Sanja; Nićiforović, Neda; Mihailović, Vladimir; Vuković, Nenad; Sukdolak, Slobodan; Solujić, Slavica

2011-01-01

The series of fifteen synthesized 4-hydroxycoumarin derivatives was subjected to antioxidant activity evaluation in vitro, through total antioxidant capacity, 1,1-diphenyl-2-picryl-hydrazyl (DPPH), hydroxyl radical, lipid peroxide scavenging and chelating activity. The highest activity was detected during the radicals scavenging, with 2b, 6b, 2c, and 4c noticed as the most active. The antioxidant activity was further quantified by the quantitative structure-activity relationships (QSAR) studies. For this purpose, the structures were optimized using Paramethric Method 6 (PM6) semi-empirical and Density Functional Theory (DFT) B3LYP methods. Bond dissociation enthalpies of coumarin 4-OH, Natural Bond Orbital (NBO) gained hybridization of the oxygen, acidity of the hydrogen atom and various molecular descriptors obtained, were correlated with biological activity, after which we designed 20 new antioxidant structures, using the most favorable structural motifs, with much improved predicted activity in vitro. PMID:21686153

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

PubMed

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

2015-01-01

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

Mathematical modeling of tetrahydroimidazole benzodiazepine-1-one derivatives as an anti HIV agent

NASA Astrophysics Data System (ADS)

Ojha, Lokendra Kumar

2017-07-01

The goal of the present work is the study of drug receptor interaction via QSAR (Quantitative Structure-Activity Relationship) analysis for 89 set of TIBO (Tetrahydroimidazole Benzodiazepine-1-one) derivatives. MLR (Multiple Linear Regression) method is utilized to generate predictive models of quantitative structure-activity relationships between a set of molecular descriptors and biological activity (IC50). The best QSAR model was selected having a correlation coefficient (r) of 0.9299 and Standard Error of Estimation (SEE) of 0.5022, Fisher Ratio (F) of 159.822 and Quality factor (Q) of 1.852. This model is statistically significant and strongly favours the substitution of sulphur atom, IS i.e. indicator parameter for -Z position of the TIBO derivatives. Two other parameter logP (octanol-water partition coefficient) and SAG (Surface Area Grid) also played a vital role in the generation of best QSAR model. All three descriptor shows very good stability towards data variation in leave-one-out (LOO).

40 CFR 98.126 - Data reporting requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... gases must submit a one-time report by June 30, 2011, that describes any measurements, research, or... described in § 98.123(c)(1)(vi)(A)(3). Use of quantitative structure activity relationships (QSARs) is an...

40 CFR 98.126 - Data reporting requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... gases must submit a one-time report by June 30, 2011, that describes any measurements, research, or... described in § 98.123(c)(1)(vi)(A)(3). Use of quantitative structure activity relationships (QSARs) is an...

The ribosome uses two active mechanisms to unwind messenger RNA during translation.

PubMed

Qu, Xiaohui; Wen, Jin-Der; Lancaster, Laura; Noller, Harry F; Bustamante, Carlos; Tinoco, Ignacio

2011-07-06

The ribosome translates the genetic information encoded in messenger RNA into protein. Folded structures in the coding region of an mRNA represent a kinetic barrier that lowers the peptide elongation rate, as the ribosome must disrupt structures it encounters in the mRNA at its entry site to allow translocation to the next codon. Such structures are exploited by the cell to create diverse strategies for translation regulation, such as programmed frameshifting, the modulation of protein expression levels, ribosome localization and co-translational protein folding. Although strand separation activity is inherent to the ribosome, requiring no exogenous helicases, its mechanism is still unknown. Here, using a single-molecule optical tweezers assay on mRNA hairpins, we find that the translation rate of identical codons at the decoding centre is greatly influenced by the GC content of folded structures at the mRNA entry site. Furthermore, force applied to the ends of the hairpin to favour its unfolding significantly speeds translation. Quantitative analysis of the force dependence of its helicase activity reveals that the ribosome, unlike previously studied helicases, uses two distinct active mechanisms to unwind mRNA structure: it destabilizes the helical junction at the mRNA entry site by biasing its thermal fluctuations towards the open state, increasing the probability of the ribosome translocating unhindered; and it mechanically pulls apart the mRNA single strands of the closed junction during the conformational changes that accompany ribosome translocation. The second of these mechanisms ensures a minimal basal rate of translation in the cell; specialized, mechanically stable structures are required to stall the ribosome temporarily. Our results establish a quantitative mechanical basis for understanding the mechanism of regulation of the elongation rate of translation by structured mRNAs. ©2011 Macmillan Publishers Limited. All rights reserved

Activation of a camptothecin prodrug by specific carboxylesterases as predicted by quantitative structure-activity relationship and molecular docking studies.

PubMed

Yoon, Kyoung Jin P; Krull, Erik J; Morton, Christopher L; Bornmann, William G; Lee, Richard E; Potter, Philip M; Danks, Mary K

2003-11-01

7-Ethyl-10-[4-(1-piperidino)-1-piperidino]carbonyloxycamptothecin (irinotecan, CPT-11) is a camptothecin prodrug that is metabolized by carboxylesterases (CE) to the active metabolite 7-ethyl-10-hydroxycamptothecin (SN-38), a topoisomerase I inhibitor. CPT-11 has shown encouraging antitumor activity against a broad spectrum of tumor types in early clinical trials, but hematopoietic and gastrointestinal toxicity limit its administration. To increase the therapeutic index of CPT-11 and to develop other prodrug analogues for enzyme/prodrug gene therapy applications, our laboratories propose to develop camptothecin prodrugs that will be activated by specific CEs. Specific analogues might then be predicted to be activated, for example, predominantly by human liver CE(hCE1), by human intestinal CE (hiCE), or in gene therapy approaches using a rabbit liver CE (rCE). This study describes a molecular modeling approach to relate the structure of rCE-activated camptothecin prodrugs with their biological activation. Comparative molecular field analysis, comparative molecular similarity index analysis, and docking studies were used to predict the biological activity of a 4-benzylpiperazine derivative of CPT-11 [7-ethyl-10-[4-(1-benzyl)-1-piperazino]carbonyloxycamptothecin (BP-CPT)] in U373MG glioma cell lines transfected with plasmids encoding rCE or hiCE. BP-CPT has been reported to be activated more efficiently than CPT-11 by a rat serum esterase activity; however, three-dimensional quantitative structure-activity relationship studies predicted that rCE would activate BP-CPT less efficiently than CPT-11. This was confirmed by both growth inhibition experiments and kinetic studies. The method is being used to design camptothecin prodrugs predicted to be activated by specific CEs.

Absolute activity quantitation from projections using an analytical approach: comparison with iterative methods in Tc-99m and I-123 brain SPECT

NASA Astrophysics Data System (ADS)

Fakhri, G. El; Kijewski, M. F.; Moore, S. C.

2001-06-01

Estimates of SPECT activity within certain deep brain structures could be useful for clinical tasks such as early prediction of Alzheimer's disease with Tc-99m or Parkinson's disease with I-123; however, such estimates are biased by poor spatial resolution and inaccurate scatter and attenuation corrections. We compared an analytical approach (AA) of more accurate quantitation to a slower iterative approach (IA). Monte Carlo simulated projections of 12 normal and 12 pathologic Tc-99m perfusion studies, as well as 12, normal and 12 pathologic I-123 neurotransmission studies, were generated using a digital brain phantom and corrected for scatter by a multispectral fitting procedure. The AA included attenuation correction by a modified Metz-Fan algorithm and activity estimation by a technique that incorporated Metz filtering to compensate for variable collimator response (VCR), IA-modeled attenuation, and VCR in the projector/backprojector of an ordered subsets-expectation maximization (OSEM) algorithm. Bias and standard deviation over the 12 normal and 12 pathologic patients were calculated with respect to the reference values in the corpus callosum, caudate nucleus, and putamen. The IA and AA yielded similar quantitation results in both Tc-99m and I-123 studies in all brain structures considered in both normal and pathologic patients. The bias with respect to the reference activity distributions was less than 7% for Tc-99m studies, but greater than 30% for I-123 studies, due to partial volume effect in the striata. Our results were validated using I-123 physical acquisitions of an anthropomorphic brain phantom. The IA yielded quantitation accuracy comparable to that obtained with IA, while requiring much less processing time. However, in most conditions, IA yielded lower noise for the same bias than did AA.

DEVELOPMENT OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS (QSARS) TO PREDICT TOXICITY FOR A VARIETY OF HUMAN AND ECOLOGICAL ENDPOINTS

EPA Science Inventory

A web accessible software tool is being developed to predict the toxicity of unknown chemicals for a wide variety of endpoints. The tool will enable a user to easily predict the toxicity of a query compound by simply entering its structure in a 2-dimensional (2-D) chemical sketc...

Functional stability of cerebral circulatory system

NASA Technical Reports Server (NTRS)

Moskalenko, Y. Y.

1980-01-01

The functional stability of the cerebral circulation system seems to be based on the active mechanisms and on those stemming from specific of the biophysical structure of the system under study. This latter parameter has some relevant criteria for its quantitative estimation. The data obtained suggest that the essential part of the mechanism for active responses of cerebral vessels which maintains the functional stability of this portion of the vascular system, consists of a neurogenic component involving central nervous structures localized, for instance, in the medulla oblongata.

Quantitative structure activity relationship studies of mushroom tyrosinase inhibitors

NASA Astrophysics Data System (ADS)

Xue, Chao-Bin; Luo, Wan-Chun; Ding, Qi; Liu, Shou-Zhu; Gao, Xing-Xiang

2008-05-01

Here, we report our results from quantitative structure-activity relationship studies on tyrosinase inhibitors. Interactions between benzoic acid derivatives and tyrosinase active sites were also studied using a molecular docking method. These studies indicated that one possible mechanism for the interaction between benzoic acid derivatives and the tyrosinase active site is the formation of a hydrogen-bond between the hydroxyl (aOH) and carbonyl oxygen atoms of Tyr98, which stabilized the position of Tyr98 and prevented Tyr98 from participating in the interaction between tyrosinase and ORF378. Tyrosinase, also known as phenoloxidase, is a key enzyme in animals, plants and insects that is responsible for catalyzing the hydroxylation of tyrosine into o-diphenols and the oxidation of o-diphenols into o-quinones. In the present study, the bioactivities of 48 derivatives of benzaldehyde, benzoic acid, and cinnamic acid compounds were used to construct three-dimensional quantitative structure-activity relationship (3D-QSAR) models using comparative molecular field (CoMFA) and comparative molecular similarity indices (CoMSIA) analyses. After superimposition using common substructure-based alignments, robust and predictive 3D-QSAR models were obtained from CoMFA ( q 2 = 0.855, r 2 = 0.978) and CoMSIA ( q 2 = 0.841, r 2 = 0.946), with 6 optimum components. Chemical descriptors, including electronic (Hammett σ), hydrophobic (π), and steric (MR) parameters, hydrogen bond acceptor (H-acc), and indicator variable ( I), were used to construct a 2D-QSAR model. The results of this QSAR indicated that π, MR, and H-acc account for 34.9, 31.6, and 26.7% of the calculated biological variance, respectively. The molecular interactions between ligand and target were studied using a flexible docking method (FlexX). The best scored candidates were docked flexibly, and the interaction between the benzoic acid derivatives and the tyrosinase active site was elucidated in detail. We believe that the QSAR models built here provide important information necessary for the design of novel tyrosinase inhibitors.

Synthesis and biological activities of turkesterone 11α-acyl derivatives

PubMed Central

Dinan, Laurence; Bourne, Pauline; Whiting, Pensri; Tsitsekli, Ada; Saatov, Ziyadilla; Dhadialla, Tarlochan S.; Hormann, Robert E.; Lafont, René; Coll, Josep

2003-01-01

Turkesterone is a phytoecdysteroid possessing an 11α-hydroxyl group. It is an analogue of the insect steroid hormone 20-hydroxyecdysone. Previous ecdysteroid QSAR and molecular modelling studies predicted that the cavity of the ligand binding domain of the ecdysteroid receptor would possess space in the vicinity of C-11/C-12 of the ecdysteroid. We report the regioselective synthesis of a series of turkesterone 11α-acyl derivatives in order to explore this possibility. The structures of the analogues have been unambiguously determined by spectroscopic means (NMR and low-resolution mass spectrometry). Purity was verified by HPLC. Biological activities have been determined in Drosophila melanogaster BII cell-based bioassay for ecdysteroid agonists and in an in vitro radioligand-displacement assay using bacterially-expressed D. melanogaster EcR/USP receptor proteins. The 11α-acyl derivatives do retain a significant amount of biological activity relative to the parent ecdysteroid. Further, although activity initially drops with the extension of the acyl chain length (C2 to C4), it then increases (C6 to C10), before decreasing again (C14 and C20). The implications of these findings for the interaction of ecdysteroids with the ecdysteroid receptor and potential applications in the generation of affinity-labelled and fluorescently-tagged ecdysteroids are discussed. Abbreviation: CoMFA comparative molecular field analysis DCM dichloromethane DMF dimethylformamide DMP 2,2-dimethoxypropane 4D-QSAR 4-dimensional quantitative structure-activity relationship EcR ecdysteroid receptor EcRE ecdysteroid response element HPLC high-performance liquid chromatography LBD ligand-binding domain NMR nuclear magnetic resonance ponA ponasterone A QSAR quantitative structure-activity relationship RXR retinoid X receptor SAR structure-activity relationship SPE solid-phase extraction THF tetrahydrofuran TLC thin-layer chromatography p-TsOH para-toluenesulphonic acid USP ultraspiracle UV-VIS ultraviolet-visible PMID:15841223

Toxicity Estimation Software Tool (TEST)

EPA Science Inventory

The Toxicity Estimation Software Tool (TEST) was developed to allow users to easily estimate the toxicity of chemicals using Quantitative Structure Activity Relationships (QSARs) methodologies. QSARs are mathematical models used to predict measures of toxicity from the physical c...

Combinatorial QSAR Modeling of Rat Acute Toxicity by Oral Exposure

EPA Science Inventory

Quantitative Structure-Activity Relationship (QSAR) toxicity models have become popular tools for identifying potential toxic compounds and prioritizing candidates for animal toxicity tests. However, few QSAR studies have successfully modeled large, diverse mammalian toxicity end...

A Way Forward Commentary

EPA Science Inventory

Models for predicting adverse outcomes can help reduce and focus animal testing with new and existing chemicals. This short "thought starter" describes how quantitative-structure activity relationship and systems biology models can be used to help define toxicity pathways and li...

Quantitative structure-activity relationships for predicting potential ecological hazard of organic chemicals for use in regulatory risk assessments.

PubMed

Comber, Mike H I; Walker, John D; Watts, Chris; Hermens, Joop

2003-08-01

The use of quantitative structure-activity relationships (QSARs) for deriving the predicted no-effect concentration of discrete organic chemicals for the purposes of conducting a regulatory risk assessment in Europe and the United States is described. In the United States, under the Toxic Substances Control Act (TSCA), the TSCA Interagency Testing Committee and the U.S. Environmental Protection Agency (U.S. EPA) use SARs to estimate the hazards of existing and new chemicals. Within the Existing Substances Regulation in Europe, QSARs may be used for data evaluation, test strategy indications, and the identification and filling of data gaps. To illustrate where and when QSARs may be useful and when their use is more problematic, an example, methyl tertiary-butyl ether (MTBE), is given and the predicted and experimental data are compared. Improvements needed for new QSARs and tools for developing and using QSARs are discussed.

QSAR for cholinesterase inhibition by organophosphorus esters and CNDO/2 calculations for organophosphorus ester hydrolysis. [quantitative structure-activity relationship, complete neglect of differential overlap

NASA Technical Reports Server (NTRS)

Johnson, H.; Kenley, R. A.; Rynard, C.; Golub, M. A.

1985-01-01

Quantitative structure-activity relationships were derived for acetyl- and butyrylcholinesterase inhibition by various organophosphorus esters. Bimolecular inhibition rate constants correlate well with hydrophobic substituent constants, and with the presence or absence of cationic groups on the inhibitor, but not with steric substituent constants. CNDO/2 calculations were performed on a separate set of organophosphorus esters, RR-primeP(O)X, where R and R-prime are alkyl and/or alkoxy groups and X is fluorine, chlorine or a phenoxy group. For each subset with the same X, the CNDO-derived net atomic charge at the central phosphorus atom in the ester correlates well with the alkaline hydrolysis rate constant. For the whole set of esters with different X, two equations were derived that relate either charge and leaving group steric bulk, or orbital energy and bond order to the hydrolysis rate constant.

Design, synthesis, antiviral activity and three-dimensional quantitative structure-activity relationship study of novel 1,4-pentadien-3-one derivatives containing the 1,3,4-oxadiazole moiety.

PubMed

Gan, Xiuhai; Hu, Deyu; Li, Pei; Wu, Jian; Chen, Xuewen; Xue, Wei; Song, Baoan

2016-03-01

1,4-Pentadien-3-one and 1,3,4-oxadiazole derivatives possess good antiviral activities, and their substructure units are usually used in antiviral agent design. In order to discover novel molecules with high antiviral activities, a series of 1,4-pentadien-3-one derivatives containing the 1,3,4-oxadiazole moiety were designed and synthesised. Bioassays showed that most of the title compounds exhibited good inhibitory activities against tobacco mosaic virus (TMV) in vivo. The compound 8f possessing the best protective activity against TMV had an EC50 value of 135.56 mg L(-1) , which was superior to that of ribavirin (435.99 mg L(-1) ). Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques were used in three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of protective activities, with values of q(2) and r(2) for the CoMFA and CoMSIA models of 0.751 and 0.775 and 0.936 and 0.925 respectively. Compound 8k with higher protective activity (EC50 = 123.53 mg L(-1) ) according to bioassay was designed and synthesised on the basis of the 3D-QSAR models. Some of the title compounds displayed good antiviral activities. 3D-QSAR models revealed that the appropriate compact electron-withdrawing and hydrophobic group at the benzene ring could enhance antiviral activity. These results could provide important structural insights for the design of highly active 1,4-pentadien-3-one derivatives. © 2015 Society of Chemical Industry.

Rational design, synthesis, biologic evaluation, and structure-activity relationship studies of novel 1-indanone alpha(1)-adrenoceptor antagonists.

PubMed

Li, Minyong; Xia, Lin

2007-11-01

In the present report, a novel series of 1-indanone alpha(1)-adrenoceptor antagonists were designed and synthesized based on 3D-pharmacophore model. Their in vitro alpha(1)-adrenoceptor antagonistic assay showed that three compounds (2a, 2m, and 2o) had similar or improved alpha(1)-adrenoceptor antagonistic activities relative to the positive control prazosin. Based on these results, a three-dimensional quantitative structure-activity relationship study was performed using a Self-Organizing Molecular Field Analysis method to provide insight for the future development of alpha(1)-adrenoceptor antagonists.

Differential modulation of FXR activity by chlorophacinone and ivermectin analogs

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

Hsu, Chia-Wen

Chemicals that alter normal function of farnesoid X receptor (FXR) have been shown to affect the homeostasis of bile acids, glucose, and lipids. Several structural classes of environmental chemicals and drugs that modulated FXR transactivation were previously identified by quantitative high-throughput screening (qHTS) of the Tox21 10 K chemical collection. In the present study, we validated the FXR antagonist activity of selected structural classes, including avermectin anthelmintics, dihydropyridine calcium channel blockers, 1,3-indandione rodenticides, and pyrethroid pesticides, using in vitro assay and quantitative structural-activity relationship (QSAR) analysis approaches. (Z)-Guggulsterone, chlorophacinone, ivermectin, and their analogs were profiled for their ability to altermore » CDCA-mediated FXR binding using a panel of 154 coregulator motifs and to induce or inhibit transactivation and coactivator recruitment activities of constitutive androstane receptor (CAR), liver X receptor alpha (LXRα), or pregnane X receptor (PXR). Our results showed that chlorophacinone and ivermectin had distinct modes of action (MOA) in modulating FXR-coregulator interactions and compound selectivity against the four aforementioned functionally-relevant nuclear receptors. These findings collectively provide mechanistic insights regarding compound activities against FXR and possible explanations for in vivo toxicological observations of chlorophacinone, ivermectin, and their analogs. - Highlights: • A subset of Tox21 chemicals was investigated for FXR antagonism. • In vitro and computational approaches were used to evaluate FXR antagonists. • Chlorophacinone and ivermectin had distinct patterns in modulating FXR activity.« less

Relating Anaerobic Digestion Microbial Community and Process Function.

PubMed

Venkiteshwaran, Kaushik; Bocher, Benjamin; Maki, James; Zitomer, Daniel

2015-01-01

Anaerobic digestion (AD) involves a consortium of microorganisms that convert substrates into biogas containing methane for renewable energy. The technology has suffered from the perception of being periodically unstable due to limited understanding of the relationship between microbial community structure and function. The emphasis of this review is to describe microbial communities in digesters and quantitative and qualitative relationships between community structure and digester function. Progress has been made in the past few decades to identify key microorganisms influencing AD. Yet, more work is required to realize robust, quantitative relationships between microbial community structure and functions such as methane production rate and resilience after perturbations. Other promising areas of research for improved AD may include methods to increase/control (1) hydrolysis rate, (2) direct interspecies electron transfer to methanogens, (3) community structure-function relationships of methanogens, (4) methanogenesis via acetate oxidation, and (5) bioaugmentation to study community-activity relationships or improve engineered bioprocesses.

Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.

PubMed

Weidlich, Iwona E; Pevzner, Yuri; Miller, Benjamin T; Filippov, Igor V; Woodcock, H Lee; Brooks, Bernard R

2015-01-05

Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a web-based tool for structure activity relationship and quantitative structure activity relationship modeling to add to the services provided by CHARMMing (www.charmming.org). This new module implements some of the most recent advances in modern machine learning algorithms-Random Forest, Support Vector Machine, Stochastic Gradient Descent, Gradient Tree Boosting, so forth. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity. © 2014 Wiley Periodicals, Inc.

SEDIMENT-ASSOCIATED REACTIONS OF AROMATIC AMINES: QSAR DEVELOPMENT

EPA Science Inventory

Despite the common occurrence of the aromatic amine functional group in environmental contaminants, few quantitative structure-activity relationships (QSARs) have been developed to predict sorption kinetics for aromatic amines in natural soils and sediments. Towards the goal of d...

Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

EPA Science Inventory

Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

Understanding ligninase-mediated reactions of endocrine disrupting chemicals in water: reaction rates and quantitative structure-activity relationships.

PubMed

Mao, Liang; Colosi, Lisa M; Gao, Shixiang; Huang, Qingguo

2011-07-15

We have verified in our previous work that lignin peroxidase (LiP) mediates effective removal of selected natural and synthetic estrogens. The efficiency of these reactions was greatly enhanced in the presence of veratryl alcohol (VA), a chemical that is produced along with LiP by certain white rot fungi, for example, Phanerochaete chrysosporium. In this study, we systematically evaluated the kinetic behaviors of LiP-mediated reactions for six endocrine disrupting compounds (EDCs), that is, steroid estrogens and their structural analogs, in both the presence and absence of VA. Resulting kinetic parameters were then correlated with structural features of LiP/substrate binding complexes, as quantified using molecular simulation, to create quantitative structure-activity relationship (QSAR) equations. These equations suggest that binding distance between a substrate's phenolic proton and δN of HIS47's imidazole ring plays an important role in modulating substrate reactivity toward LiP in both the presence and absence of VA. This information provides insight into an important enzymatic reaction process that occurs in the natural environment affecting EDC transformation, a process that may be used in engineered systems to achieve EDC removal from water.

Synthesis, QSAR, and Molecular Dynamics Simulation of Amidino-substituted Benzimidazoles as Dipeptidyl Peptidase III Inhibitors.

PubMed

Rastija, Vesna; Agić, Dejan; Tomiš, Sanja; Nikolič, Sonja; Hranjec, Marijana; Grace, Karminski-Zamola; Abramić, Marija

2015-01-01

A molecular modeling study is performed on series of benzimidazol-based inhibitors of human dipeptidyl peptidase III (DPP III). An eight novel compounds were synthesized in excellent yields using green chemistry approach. This study is aimed to elucidate the structural features of benzimidazole derivatives required for antagonism of human DPP III activity using Quantitative Structure-Activity Relationship (QSAR) analysis, and to understand the mechanism of one of the most potent inhibitor binding into the active site of this enzyme, by molecular dynamics (MD) simulations. The best model obtained includes S3K and RDF045m descriptors which have explained 89.4 % of inhibitory activity. Depicted moiety for strong inhibition activity matches to the structure of most potent compound. MD simulation has revealed importance of imidazolinyl and phenyl groups in the mechanism of binding into the active site of human DPP III.

Application of quantitative structure activity relationship (QSAR) models to predict ozone toxicity in the lung.

PubMed

Kafoury, Ramzi M; Huang, Ming-Ju

2005-08-01

The sequence of events leading to ozone-induced airway inflammation is not well known. To elucidate the molecular and cellular events underlying ozone toxicity in the lung, we hypothesized that lipid ozonation products (LOPs) generated by the reaction of ozone with unsaturated fatty acids in the epithelial lining fluid and cell membranes play a key role in mediating ozone-induced airway inflammation. To test our hypothesis, we ozonized 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) and generated LOPs. Confluent human bronchial epithelial cells were exposed to the derivatives of ozonized POPC-9-oxononanoyl, 9-hydroxy-9-hydroperoxynonanoyl, and 8-(5-octyl-1,2,4-trioxolan-3-yl-)octanoyl-at a concentration of 10 muM, and the activity of phospholipases A2 (PLA2), C (PLC), and D (PLD) was measured (1, 0.5, and 1 h, respectively). Quantitative structure-activity relationship (QSAR) models were utilized to predict the biological activity of LOPs in airway epithelial cells. The QSAR results showed a strong correlation between experimental and computed activity (r = 0.97, 0.98, 0.99, for PLA2, PLC, and PLD, respectively). The results indicate that QSAR models can be utilized to predict the biological activity of the various ozone-derived LOP species in the lung. Copyright 2005 Wiley Periodicals, Inc.

Combining molecular docking and QSAR studies for modeling the anti-tyrosinase activity of aromatic heterocycle thiosemicarbazone analogues

NASA Astrophysics Data System (ADS)

Dong, Huanhuan; Liu, Jing; Liu, Xiaoru; Yu, Yanying; Cao, Shuwen

2018-01-01

A collection of thirty-six aromatic heterocycle thiosemicarbazone analogues presented a broad span of anti-tyrosinase activities were designed and obtained. A robust and reliable two-dimensional quantitative structure-activity relationship model, as evidenced by the high q2 and r2 values (0.848 and 0.893, respectively), was gained based on the analogues to predict the quantitative chemical-biological relationship and the new modifier direction. Inhibitory activities of the compounds were found to greatly depend on molecular shape and orbital energy. Substituents brought out large ovality and high highest-occupied molecular orbital energy values helped to improve the activity of these analogues. The molecular docking results provided visual evidence for QSAR analysis and inhibition mechanism. Based on these, two novel tyrosinase inhibitors O04 and O05 with predicted IC50 of 0.5384 and 0.8752 nM were designed and suggested for further research.

Decoration of Chondroitin Polysaccharide with Threonine: Synthesis, Conformational Study, and Ice-Recrystallization Inhibition Activity.

PubMed

Laezza, Antonio; Casillo, Angela; Cosconati, Sandro; Biggs, Caroline I; Fabozzi, Antonio; Paduano, Luigi; Iadonisi, Alfonso; Novellino, Ettore; Gibson, Matthew I; Randazzo, Antonio; Corsaro, Maria M; Bedini, Emiliano

2017-08-14

Several threonine (Thr)- and alanine (Ala)-rich antifreeze glycoproteins (AFGPs) and polysaccharides act in nature as ice recrystallization inhibitors. Among them, the Thr-decorated capsular polysaccharide (CPS) from the cold-adapted Colwellia psychrerythraea 34H bacterium was recently investigated for its cryoprotectant activity. A semisynthetic mimic thereof was here prepared from microbial sourced chondroitin through a four-step strategy, involving a partial protection of the chondroitin polysaccharide as a key step for gaining an unprecedented quantitative amidation of its glucuronic acid units. In-depth NMR and computational analysis suggested a fairly linear conformation for the semisynthetic polysaccharide, for which the antifreeze activity by a quantitative ice recrystallization inhibition assay was measured. We compared the structure-activity relationships for the Thr-derivatized chondroitin and the natural Thr-decorated CPS from C. psychrerythraea.

Quantitative Analysis of the Morphology of {101} and {001} Faceted Anatase TiO 2 Nanocrystals and Its Implication on Photocatalytic Activity

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

Liu, Jue; Olds, Daniel; Peng, Rui

The atomistic structure and morphology (shape and size) of nanomaterials have strong influences on their physical and chemical properties. However, many characterization techniques focus exclusively on one length-scale regime or another when developing quantitative morphology/structural models. In this article, we demonstrate that powder X-ray diffraction and neutron pair distribution function (PDF) can be used to obtain accurate average morphology and atomistic structure of {001} and {101} faceted anatase TiO 2 nanocrystals based on differential evolution refinements using Debye scattering equation calculations. It is also demonstrated that the morphology polydispersity of TiO 2 nanocrystals can be effectively obtained from the diffractionmore » data via a numerical refinement routine. The morphology refinement results are in good agreement with those from transmission electron microscopy and the modeling of small angle neutron scattering data. This method is successfully used to quantify the facet-specified photocatalytic hydrogen evolution activity of anatase TiO 2 nanocrystals with different {001} to {101} ratios. It is found that the sample with an intermediate amount of both {001} and {101} facets shows the best photocatalytic hydrogen evolution reaction (HER) activity. It is expected that the simultaneous structure and morphology refinement technique can be generally used to study the relationship between morphology and functionality of nanomaterials.« less

Quantitative Analysis of the Morphology of {101} and {001} Faceted Anatase TiO 2 Nanocrystals and Its Implication on Photocatalytic Activity

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

Liu, Jue; Olds, Daniel; Peng, Rui

The atomistic structure and morphology (shape and size) of nanomaterials have strong influences on their physical and chemical properties. However, many characterization techniques focus exclusively on one length-scale regime or another when developing quantitative morphology/structural models. In this article, we demonstrate that powder X-ray diffraction and neutron pair distribution function (PDF) can be used to obtain accurate average morphology and atomistic structure of {001} and {101} faceted anatase TiO 2 nanocrystals based on differential evolution refinements using Debye scattering equation calculations. It is also demonstrated that the morphology polydispersity of TiO 2 nanocrystals can be effectively obtained from the diffractionmore » data via a numerical refinement routine. The morphology refinement results are in good agreement with those from transmission electron microscopy and the modeling of small angle neutron scattering data. This method is successfully used to quantify the facet-specified photocatalytic hydrogen evolution activity of anatase TiO 2 nanocrystals with different {001} to {101} ratios. It is found that the sample with an intermediate amount of both {001} and {101} facets shows the best photocatalytic hydrogen evolution reaction (HER) activity. As a result, it is expected that the simultaneous structure and morphology refinement technique can be generally used to study the relationship between morphology and functionality of nanomaterials.« less

Quantitative Analysis of the Morphology of {101} and {001} Faceted Anatase TiO 2 Nanocrystals and Its Implication on Photocatalytic Activity

DOE PAGES

Liu, Jue; Olds, Daniel; Peng, Rui; ...

2017-06-14

The atomistic structure and morphology (shape and size) of nanomaterials have strong influences on their physical and chemical properties. However, many characterization techniques focus exclusively on one length-scale regime or another when developing quantitative morphology/structural models. In this article, we demonstrate that powder X-ray diffraction and neutron pair distribution function (PDF) can be used to obtain accurate average morphology and atomistic structure of {001} and {101} faceted anatase TiO 2 nanocrystals based on differential evolution refinements using Debye scattering equation calculations. It is also demonstrated that the morphology polydispersity of TiO 2 nanocrystals can be effectively obtained from the diffractionmore » data via a numerical refinement routine. The morphology refinement results are in good agreement with those from transmission electron microscopy and the modeling of small angle neutron scattering data. This method is successfully used to quantify the facet-specified photocatalytic hydrogen evolution activity of anatase TiO 2 nanocrystals with different {001} to {101} ratios. It is found that the sample with an intermediate amount of both {001} and {101} facets shows the best photocatalytic hydrogen evolution reaction (HER) activity. As a result, it is expected that the simultaneous structure and morphology refinement technique can be generally used to study the relationship between morphology and functionality of nanomaterials.« less

Design and prediction of new anticoagulants as a selective Factor IXa inhibitor via three-dimensional quantitative structure-property relationships of amidinobenzothiophene derivatives

PubMed Central

Gao, Jia-Suo; Tong, Xu-Peng; Chang, Yi-Qun; He, Yu-Xuan; Mei, Yu-Dan; Tan, Pei-Hong; Guo, Jia-Liang; Liao, Guo-Chao; Xiao, Gao-Keng; Chen, Wei-Min; Zhou, Shu-Feng; Sun, Ping-Hua

2015-01-01

Factor IXa (FIXa), a blood coagulation factor, is specifically inhibited at the initiation stage of the coagulation cascade, promising an excellent approach for developing selective and safe anticoagulants. Eighty-four amidinobenzothiophene antithrombotic derivatives targeting FIXa were selected to establish three-dimensional quantitative structure–activity relationship (3D-QSAR) and three-dimensional quantitative structure–selectivity relationship (3D-QSSR) models using comparative molecular field analysis and comparative similarity indices analysis methods. Internal and external cross-validation techniques were investigated as well as region focusing and bootstrapping. The satisfactory q2 values of 0.753 and 0.770, and r2 values of 0.940 and 0.965 for 3D-QSAR and 3D-QSSR, respectively, indicated that the models are available to predict both the inhibitory activity and selectivity on FIXa against Factor Xa, the activated status of Factor X. This work revealed that the steric, hydrophobic, and H-bond factors should appropriately be taken into account in future rational design, especially the modifications at the 2′-position of the benzene and the 6-position of the benzothiophene in the R group, providing helpful clues to design more active and selective FIXa inhibitors for the treatment of thrombosis. On the basis of the three-dimensional quantitative structure–property relationships, 16 new potent molecules have been designed and are predicted to be more active and selective than Compound 33, which has the best activity as reported in the literature. PMID:25848211

COREPA-M: NEW MULTI-DIMENSIONAL FUNCTIONALITY OF THE COREPA METHOD

EPA Science Inventory

The COmmon REactivity PAttern (COREPA) method is a recently developed pattern recognition technique accounting for conformational flexibility of chemicals in 3-D quantitative structure-activity relationships (QSARs). The method is based on the assumption that non-congeneric chemi...

Calculation of Drug Solubilities by Pharmacy Students.

ERIC Educational Resources Information Center

Cates, Lindley A.

1981-01-01

A method of estimating the solubilities of drugs in water is reported that is based on a principle applied in quantitative structure-activity relationships. This procedure involves correlation of partition coefficient values using the octanol/water system and aqueous solubility. (Author/MLW)

2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors

PubMed Central

Zhao, Manman; Zheng, Linfeng; Qiu, Chun

2017-01-01

Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q2 = 0.565 (cross-validated correlation coefficient) and r2 = 0.888 (non-cross-validated correlation coefficient) was built to predict the activity of EGFR inhibitors. The mean absolute error (MAE) of the training set and test set was 0.308 log units and 0.526 log units, respectively. In addition, molecular docking was also employed to investigate the interaction between EGFR inhibitors and EGFR. PMID:28630865

Predicting the performance of fingerprint similarity searching.

PubMed

Vogt, Martin; Bajorath, Jürgen

2011-01-01

Fingerprints are bit string representations of molecular structure that typically encode structural fragments, topological features, or pharmacophore patterns. Various fingerprint designs are utilized in virtual screening and their search performance essentially depends on three parameters: the nature of the fingerprint, the active compounds serving as reference molecules, and the composition of the screening database. It is of considerable interest and practical relevance to predict the performance of fingerprint similarity searching. A quantitative assessment of the potential that a fingerprint search might successfully retrieve active compounds, if available in the screening database, would substantially help to select the type of fingerprint most suitable for a given search problem. The method presented herein utilizes concepts from information theory to relate the fingerprint feature distributions of reference compounds to screening libraries. If these feature distributions do not sufficiently differ, active database compounds that are similar to reference molecules cannot be retrieved because they disappear in the "background." By quantifying the difference in feature distribution using the Kullback-Leibler divergence and relating the divergence to compound recovery rates obtained for different benchmark classes, fingerprint search performance can be quantitatively predicted.

Two-dimensional profiling of carriers in terahertz quantum cascade lasers using calibrated scanning spreading resistance microscopy and scanning capacitance microscopy.

PubMed

Dhar, R S; Ban, D

2013-07-01

The distribution of charge carriers inside the active region of a terahertz (THz) quantum cascade laser (QCL) has been measured with scanning spreading resistance microscopy (SSRM) and scanning capacitance microscopy (SCM). Individual quantum well-barrier modules with a 35.7-nm single module thickness in the active region of the device have been resolved for the first time using high-resolution SSRM and SCM techniques at room temperature. SSRM and SCM measurements on the quantum well-barrier structure were calibrated utilizing known GaAs dopant staircase samples. Doping concentrations derived from SSRM and SCM measurements were found to be in quantitative agreement with the designed average doping values of the n-type active region in the terahertz quantum cascade laser. The secondary ion mass spectroscopy provides a partial picture of internal device parameters, and we have demonstrated with our results the efficacy of uniting calibrated SSRM and SCM to delineate quantitatively the transverse cross-sectional structure of complex two-dimensional terahertz quantum cascade laser devices. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Teacher Trainers' and Trainees' Perceptions, Practices, and Constraints to Active Learning Methods: The Case of English Department in Bahir Dar University

ERIC Educational Resources Information Center

Engidaw, Berhanu

2014-01-01

This study is on teacher trainers and teacher trainees' perceptions and practices of active learning and the constraints to implementing them in the English Department of Bahir Dar University. A mixed study approach that involves a quantitative self administered questionnaire, a semi-structured lesson observation guide, and qualitative in depth…

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

PubMed

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

2014-06-01

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

Synthetic cannabinoids: In silico prediction of the cannabinoid receptor 1 affinity by a quantitative structure-activity relationship model.

PubMed

Paulke, Alexander; Proschak, Ewgenij; Sommer, Kai; Achenbach, Janosch; Wunder, Cora; Toennes, Stefan W

2016-03-14

The number of new synthetic psychoactive compounds increase steadily. Among the group of these psychoactive compounds, the synthetic cannabinoids (SCBs) are most popular and serve as a substitute of herbal cannabis. More than 600 of these substances already exist. For some SCBs the in vitro cannabinoid receptor 1 (CB1) affinity is known, but for the majority it is unknown. A quantitative structure-activity relationship (QSAR) model was developed, which allows the determination of the SCBs affinity to CB1 (expressed as binding constant (Ki)) without reference substances. The chemically advance template search descriptor was used for vector representation of the compound structures. The similarity between two molecules was calculated using the Feature-Pair Distribution Similarity. The Ki values were calculated using the Inverse Distance Weighting method. The prediction model was validated using a cross validation procedure. The predicted Ki values of some new SCBs were in a range between 20 (considerably higher affinity to CB1 than THC) to 468 (considerably lower affinity to CB1 than THC). The present QSAR model can serve as a simple, fast and cheap tool to get a first hint of the biological activity of new synthetic cannabinoids or of other new psychoactive compounds. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The effect of leverage and/or influential on structure-activity relationships.

PubMed

Bolboacă, Sorana D; Jäntschi, Lorentz

2013-05-01

In the spirit of reporting valid and reliable Quantitative Structure-Activity Relationship (QSAR) models, the aim of our research was to assess how the leverage (analysis with Hat matrix, h(i)) and the influential (analysis with Cook's distance, D(i)) of QSAR models may reflect the models reliability and their characteristics. The datasets included in this research were collected from previously published papers. Seven datasets which accomplished the imposed inclusion criteria were analyzed. Three models were obtained for each dataset (full-model, h(i)-model and D(i)-model) and several statistical validation criteria were applied to the models. In 5 out of 7 sets the correlation coefficient increased when compounds with either h(i) or D(i) higher than the threshold were removed. Withdrawn compounds varied from 2 to 4 for h(i)-models and from 1 to 13 for D(i)-models. Validation statistics showed that D(i)-models possess systematically better agreement than both full-models and h(i)-models. Removal of influential compounds from training set significantly improves the model and is recommended to be conducted in the process of quantitative structure-activity relationships developing. Cook's distance approach should be combined with hat matrix analysis in order to identify the compounds candidates for removal.

Twoplex 12/13 C6 aniline stable isotope and linkage-specific sialic acid labeling 2D-LC-MS workflow for quantitative N-glycomics.

PubMed

Albrecht, Simone; Mittermayr, Stefan; Smith, Josh; Martín, Silvia Millán; Doherty, Margaret; Bones, Jonathan

2017-01-01

Quantitative glycomics represents an actively expanding research field ranging from the discovery of disease-associated glycan alterations to the quantitative characterization of N-glycans on therapeutic proteins. Commonly used analytical platforms for comparative relative quantitation of complex glycan samples include MALDI-TOF-MS or chromatographic glycan profiling with subsequent data alignment and statistical evaluation. Limitations of such approaches include run-to-run technical variation and the potential introduction of subjectivity during data processing. Here, we introduce an offline 2D LC-MS E workflow for the fractionation and relative quantitation of twoplex isotopically labeled N-linked oligosaccharides using neutral 12 C 6 and 13 C 6 aniline (Δmass = 6 Da). Additional linkage-specific derivatization of sialic acids using 4-(4,6-dimethoxy-1,3,5-trizain-2-yl)-4-methylmorpholinium chloride offered simultaneous and advanced in-depth structural characterization. The potential of the method was demonstrated for the differential analysis of structurally defined N-glycans released from serum proteins of patients diagnosed with various stages of colorectal cancer. The described twoplex 12 C 6 / 13 C 6 aniline 2D LC-MS platform is ideally suited for differential glycomic analysis of structurally complex N-glycan pools due to combination and analysis of samples in a single LC-MS injection and the associated minimization in technical variation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Quantitative histoenzymatic analysis of the adenohypophysis and adrenal cortex during the early stages of involution].

PubMed

Prochukhanov, R A; Rostovtseva, T I

1977-11-01

A method of quantitative histenzymatic analysis was applied for determination of the involution changes of the neuroendocrine system. The activity of NAD- and NADP-reductases, acid and alkaline phosphatases, glucose-6-phosphoric dehydrogenase, 3-OH-steroid-dehydrogenase, 11-hydroxysteroid dehydrogenases was investigated in the adenohypophysis and in the adrenal cortex of rats aged 4 and 12 months. There were revealed peculiarities attending the structural-metabolic provision of physiological reconstructions of the neuro-endocrine system under conditions of the estral cycle at the early involution stages. An initial reduction of the cell ular-vascular transport with the retention of the functional activity of the intracellular organoids was demonstrated in ageing animals.

Overview of T.E.S.T. (Toxicity Estimation Software Tool)

EPA Science Inventory

This talk provides an overview of T.E.S.T. (Toxicity Estimation Software Tool). T.E.S.T. predicts toxicity values and physical properties using a variety of different QSAR (quantitative structure activity relationship) approaches including hierarchical clustering, group contribut...

Novel carboxamides as potential mosquito reprellents.

USDA-ARS?s Scientific Manuscript database

A model was developed using 167 carboxamide compounds, from the US Department of Agriculture archival database, that were tested as arthropod repellents over the past 60 years. An artificial neural network utilizing CODESSA PRO descriptors was used to construct a Quantitative Structure-Activity Re...

Estimating the Potential Toxicity of Chemicals Associated with Hydraulic Fracturing Operations Using Quantitative Structure-Activity Relationship Modeling

EPA Pesticide Factsheets

Researchers facilitated evaluation of chemicals that lack chronic oral toxicity values using a QSAR model to develop estimates of potential toxicity for chemicals used in HF fluids or found in flowback or produced water

Understanding Outdoor Gyms in Public Open Spaces: A Systematic Review and Integrative Synthesis of Qualitative and Quantitative Evidence

PubMed Central

Lee, Janet Lok Chun; Lo, Temmy Lee Ting

2018-01-01

(1) Background: An outdoor gym (OG) is environmental infrastructure built in a public open space to promote structured physical activity. The provision of OGs is increasingly seen as an important strategy to realize public health agendas promoting habitual physical activity. A systematic review was conducted to synthesize characteristics of OG and OG users’ experiences and perceptions in different cultural contexts; (2) Methods: Online searches of multidisciplinary databases were conducted in health, sport and recreation, and urban planning disciplines. Characteristics of OGs were synthesized by integrating evidence from quantitative, qualitative, and mix-methods studies. The experiences and perceptions of OG users from both qualitative data and survey responses were synthesized through framework analysis; (3) Results: Nine studies met the inclusion criteria (three quantitative studies, four mixed-methods studies, and two pure qualitative studies). None were excluded on the basis of quality. OGs mainly serve adult and older adult population groups. Their size, design, and instructional support vary across studies. The inclusion of functional types of equipment did not have a unified standard. Regarding experiences and perceptions of OGs, five major themes emerged: “health”, “social connectedness”, “affordable”, “support”, and “design and promotion”; (4) Conclusions: The OG characteristics synthesis guides the direction in further studies regarding exploration of design parameters. The qualitative and quantitative synthesis revealed that health was a central theme of users’ experiences. OGs are also spaces where community-dwellers can find social connectedness while participating in structured physical activity at no cost. Findings from this review create knowledge support for OG as environmental infrastructure for further research and facilitate the understanding of users’ experiences and perceptions of OGs in different cultural contexts. PMID:29587402

Synthesis, Antifungal Activity and Structure-Activity Relationships of Novel 3-(Difluoromethyl)-1-methyl-1H-pyrazole-4-carboxylic Acid Amides.

PubMed

Du, Shijie; Tian, Zaimin; Yang, Dongyan; Li, Xiuyun; Li, Hong; Jia, Changqing; Che, Chuanliang; Wang, Mian; Qin, Zhaohai

2015-05-08

A series of novel 3-(difluoromethyl)-1-methyl-1H-pyrazole-4-carboxylic acid amides were synthesized and their activities were tested against seven phytopathogenic fungi by an in vitro mycelia growth inhibition assay. Most of them displayed moderate to excellent activities. Among them N-(2-(5-bromo-1H-indazol-1-yl)phenyl)-3-(difluoro-methyl)-1-methyl-1H-pyrazole-4-carboxamide (9m) exhibited higher antifungal activity against the seven phytopathogenic fungi than boscalid. Topomer CoMFA was employed to develop a three-dimensional quantitative structure-activity relationship model for the compounds. In molecular docking, the carbonyl oxygen atom of 9m could form hydrogen bonds towards the hydroxyl of TYR58 and TRP173 on SDH.

Purity-activity relationships of natural products: the case of anti-TB active ursolic acid.

PubMed

Jaki, Birgit U; Franzblau, Scott G; Chadwick, Lucas R; Lankin, David C; Zhang, Fangqiu; Wang, Yuehong; Pauli, Guido F

2008-10-01

The present study explores the variability of biological responses from the perspective of sample purity and introduces the concept of purity-activity relationships (PARs) in natural product research. The abundant plant triterpene ursolic acid (1) was selected as an exemplary natural product due to the overwhelming number yet inconsistent nature of its approximate 120 reported biological activities, which include anti-TB potential. Nine different samples of ursolic acid with purity certifications were obtained, and their purity was independently assessed by means of quantitative 1H NMR (qHNMR). Biological evaluation consisted of determining MICs against two strains of virulent Mycobacterium tuberculosis and IC50 values in Vero cells. Ab initio structure elucidation provided unequivocal structural confirmation and included an extensive 1H NMR spin system analysis, determination of nearly all J couplings and the complete NOE pattern, and led to the revision of earlier reports. As a net result, a sigmoid PAR profile of 1 was obtained, demonstrating the inverse correlation of purity and anti-TB bioactivity. The results imply that synergistic effects of 1 and its varying impurities are the likely cause of previously reported antimycobacterial potential. Generating PARs is a powerful extension of the routinely performed quantitative correlation of structure and activity ([Q]SAR). Advanced by the use of primary analytical methods such as qHNMR, PARs enable the elucidation of cases like 1 when increasing purity voids biological activity. This underlines the potential of PARs as a tool in drug discovery and synergy research and accentuates the need to routinely combine biological testing with purity assessment.

Discovery of novel glitazones incorporated with phenylalanine and tyrosine: synthesis, antidiabetic activity and structure-activity relationships.

PubMed

Prashantha Kumar, B R; Baig, Nasir R; Sudhir, Sai; Kar, Koyal; Kiranmai, M; Pankaj, M; Joghee, Nanjan M

2012-12-01

We report a series of new glitazones incorporated with phenylalanine and tyrosine. All the compounds were tested for their in vitro glucose uptake activity using rat-hemidiaphragm, both in presence and absence of insulin. Six of the most active compounds from the in vitro screening were taken forward for their in vivo triglyceride and glucose lowering activity against dexamethazone induced hyperlipidemia and insulin resistance in Wistar rats. The liver samples of rats that received the most active compounds, 23 and 24, in the in vivo studies, were subjected to histopathological examination to assess their short term hepatotoxicity. The investigations on the in vitro glucose uptake, in vivo triglyceride and glucose lowering activity are described here along with the quantitative structure-activity relationships. Copyright © 2012 Elsevier Inc. All rights reserved.

Research Review: Neural response to threat in children, adolescents, and adults after child maltreatment - a quantitative meta-analysis.

PubMed

Hein, Tyler C; Monk, Christopher S

2017-03-01

Child maltreatment is common and has long-term consequences for affective function. Investigations of neural consequences of maltreatment have focused on the amygdala. However, developmental neuroscience indicates that other brain regions are also likely to be affected by child maltreatment, particularly in the social information processing network (SIPN). We conducted a quantitative meta-analysis to: confirm that maltreatment is related to greater bilateral amygdala activation in a large sample that was pooled across studies; investigate other SIPN structures that are likely candidates for altered function; and conduct a data-driven examination to identify additional regions that show altered activation in maltreated children, teens, and adults. We conducted an activation likelihood estimation analysis with 1,733 participants across 20 studies of emotion processing in maltreated individuals. Maltreatment is associated with increased bilateral amygdala activation to emotional faces. One SIPN structure is altered: superior temporal gyrus, of the detection node, is hyperactive in maltreated individuals. The results of the whole-brain corrected analysis also show hyperactivation of the parahippocampal gyrus and insula in maltreated individuals. The meta-analysis confirms that maltreatment is related to increased bilateral amygdala reactivity and also shows that maltreatment affects multiple additional structures in the brain that have received little attention in the literature. Thus, although the majority of studies examining maltreatment and brain function have focused on the amygdala, these findings indicate that the neural consequences of child maltreatment involve a broader network of structures. © 2016 Association for Child and Adolescent Mental Health.

DSSTOX (DISTRIBUTED STRUCTURE-SEARCHABLE ...

EPA Pesticide Factsheets

Distributed Structure-Searchable Toxicity Database Network Major trends affecting public toxicity information resources have the potential to significantly alter the future of predictive toxicology. Chemical toxicity screening is undergoing shifts towards greater use of more fundamental information on gene/protein expression patterns and bioactivity and bioassay profiles, the latter generated with highthroughput screening technologies. Curated, systematically organized, and webaccessible toxicity and biological activity data in association with chemical structures, enabling the integration of diverse data information domains, will fuel the next frontier of advancement for QSAR (quantitative structure-activity relationship) and data mining technologies. The DSSTox project is supporting progress towards these goals on many fronts, promoting the use of formalized and structure-annotated toxicity data models, helping to interface these efforts with QSAR modelers, linking data from diverse sources, and creating a large, quality reviewed, central chemical structure information resource linked to various toxicity data sources

INVERSE QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP ANALYSIS FOR IMPROVING PREDICTIONS OF CHEMICAL TOXICITY

EPA Science Inventory

The toxic outcomes associated with environmental contaminants are often not due to the chemical form that was originally introduced into the environment, but rather to the chemical having undergone a transformation prior to reaching the vulnerable species. More importantly, the c...

3D Filament Network Segmentation with Multiple Active Contours

NASA Astrophysics Data System (ADS)

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2014-03-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

Optimal descriptor as a translator of eclectic information into the prediction of membrane damage: the case of a group of ZnO and TiO2 nanoparticles.

PubMed

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

2014-10-01

The development of quantitative structure-activity relationships for nanomaterials needs representation of molecular structure of extremely complex molecular systems. Obviously, various characteristics of nanomaterial could impact associated biochemical endpoints. Following features of TiO2 and ZnO nanoparticles (n=42) are considered here: (i) engineered size (nm); (ii) size in water suspension (nm); (iii) size in phosphate buffered saline (PBS, nm); (iv) concentration (mg/L); and (v) zeta potential (mV). The damage to cellular membranes (units/L) is selected as an endpoint. Quantitative features-activity relationships (QFARs) are calculated by the Monte Carlo technique for three distributions of data representing values associated with membrane damage into the training and validation sets. The obtained models are characterized by the following average statistics: 0.78

Decipher the dynamic coordination between enzymatic activity and structural modulation at focal adhesions in living cells

NASA Astrophysics Data System (ADS)

Lu, Shaoying; Seong, Jihye; Wang, Yi; Chang, Shiou-Chi; Eichorst, John Paul; Ouyang, Mingxing; Li, Julie Y.-S.; Chien, Shu; Wang, Yingxiao

2014-07-01

Focal adhesions (FAs) are dynamic subcellular structures crucial for cell adhesion, migration and differentiation. It remains an enigma how enzymatic activities in these local complexes regulate their structural remodeling in live cells. Utilizing biosensors based on fluorescence resonance energy transfer (FRET), we developed a correlative FRET imaging microscopy (CFIM) approach to quantitatively analyze the subcellular coordination between the enzymatic Src activation and the structural FA disassembly. CFIM reveals that the Src kinase activity only within the microdomain of lipid rafts at the plasma membrane is coupled with FA dynamics. FA disassembly at cell periphery was linearly dependent on this raft-localized Src activity, although cells displayed heterogeneous levels of response to stimulation. Within lipid rafts, the time delay between Src activation and FA disassembly was 1.2 min in cells seeded on low fibronectin concentration ([FN]) and 4.3 min in cells on high [FN]. CFIM further showed that the level of Src-FA coupling, as well as the time delay, was regulated by cell-matrix interactions, as a tight enzyme-structure coupling occurred in FA populations mediated by integrin αvβ3, but not in those by integrin α5β1. Therefore, different FA subpopulations have distinctive regulation mechanisms between their local kinase activity and structural FA dynamics.

Cytotoxic lanostane-type triterpenoids from the fruiting bodies of Ganoderma lucidum and their structure-activity relationships.

PubMed

Chen, Shaodan; Li, Xiangmin; Yong, Tianqiao; Wang, Zhanggen; Su, Jiyan; Jiao, Chunwei; Xie, Yizhen; Yang, Burton B

2017-02-07

We conducted a study of Ganoderma lucidum metabolites and isolated 35 lanostane-type triterpenoids, including 5 new ganoderols (1-5). By spectroscopy, we compared the structures of these compounds with known related compounds in this group. All of the isolated compounds were assayed for their effect against the human breast carcinoma cell line MDA-MB-231 and hepatocellular carcinoma cell line HepG2. Corresponding three-dimensional quantitative structure-activity relationship (3D-QSAR) models were built and analyzed using Discovery Studio. These results provide further evidence for anti-cancer constituents within Ganoderma lucidum, and may provide a theoretical foundation for designing novel therapeutic compounds.

Further evaluation of quantitative structure--activity relationship models for the prediction of the skin sensitization potency of selected fragrance allergens.

PubMed

Patlewicz, Grace Y; Basketter, David A; Pease, Camilla K Smith; Wilson, Karen; Wright, Zoe M; Roberts, David W; Bernard, Guillaume; Arnau, Elena Giménez; Lepoittevin, Jean-Pierre

2004-02-01

Fragrance substances represent a very diverse group of chemicals; a proportion of them are associated with the ability to cause allergic reactions in the skin. Efforts to find substitute materials are hindered by the need to undertake animal testing for determining both skin sensitization hazard and potency. One strategy to avoid such testing is through an understanding of the relationships between chemical structure and skin sensitization, so-called structure-activity relationships. In recent work, we evaluated 2 groups of fragrance chemicals -- saturated aldehydes and alpha,beta-unsaturated aldehydes. Simple quantitative structure-activity relationship (QSAR) models relating the EC3 values [derived from the local lymph node assay (LLNA)] to physicochemical properties were developed for both sets of aldehydes. In the current study, we evaluated an additional group of carbonyl-containing compounds to test the predictive power of the developed QSARs and to extend their scope. The QSAR models were used to predict EC3 values of 10 newly selected compounds. Local lymph node assay data generated for these compounds demonstrated that the original QSARs were fairly accurate, but still required improvement. Development of these QSAR models has provided us with a better understanding of the potential mechanisms of action for aldehydes, and hence how to avoid or limit allergy. Knowledge generated from this work is being incorporated into new/improved rules for sensitization in the expert toxicity prediction system, deductive estimation of risk from existing knowledge (DEREK).

Quantitative structure-activity relationship: promising advances in drug discovery platforms.

PubMed

Wang, Tao; Wu, Mian-Bin; Lin, Jian-Ping; Yang, Li-Rong

2015-12-01

Quantitative structure-activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced. In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization. QSAR should intentionally be used as a powerful tool for fragment-based drug design platforms in the field of drug discovery and design. Although there have been an increasing number of experimentally determined protein structures in recent years, a great number of protein structures cannot be easily obtained (i.e., membrane transport proteins and G-protein coupled receptors). Fragment-based drug discovery, such as QSAR, could be applied further and have a significant role in dealing with these problems. Moreover, along with the development of computer software and hardware, it is believed that QSAR will be increasingly important.

QSAR modeling of cumulative environmental end-points for the prioritization of hazardous chemicals.

PubMed

Gramatica, Paola; Papa, Ester; Sangion, Alessandro

2018-01-24

The hazard of chemicals in the environment is inherently related to the molecular structure and derives simultaneously from various chemical properties/activities/reactivities. Models based on Quantitative Structure Activity Relationships (QSARs) are useful to screen, rank and prioritize chemicals that may have an adverse impact on humans and the environment. This paper reviews a selection of QSAR models (based on theoretical molecular descriptors) developed for cumulative multivariate endpoints, which were derived by mathematical combination of multiple effects and properties. The cumulative end-points provide an integrated holistic point of view to address environmentally relevant properties of chemicals.

77 FR 68773 - FIFRA Scientific Advisory Panel; Notice of Public Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-16

... for physical chemical properties that cannot be easily tested in in vitro systems or stable enough for.... Quantitative structural-activity relationship (QSAR) models and estrogen receptor (ER) expert systems development. High-throughput data generation and analysis (expertise focused on how this methodology can be...

Comparison of Global and Mode of Action-Based Models for Aquatic Toxicity

EPA Science Inventory

The ability to estimate aquatic toxicity for a wide variety of chemicals is a critical need for ecological risk assessment and chemical regulation. The consensus in the literature is that mode of action (MOA) based QSAR (Quantitative Structure Activity Relationship) models yield ...

TOXICITY ASSESSMENT OF PARALYTIC SHELLFISH POISONS (PSPS) USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS

EPA Science Inventory

The most significant harmful algal bloom (HAB) toxin in terms of public health is commonly known as paralytic shellfish poisons (PSPs, "red tides" toxins). PSPs are neurotoxins produced by marine dinoflagellates and some cyanobacteria. PSPs comprise of over 21 natural toxins wi...

QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP (QSAR) MODELS TO PREDICT CHEMICAL TOXICITY FOR VARIOUS HEALTH ENDPOINTS

EPA Science Inventory

Although ranking schemes based on exposure and toxicity have been developed to aid in the prioritization of research funds for identifying chemicals of regulatory concern, there are significant gaps in the availability of experimental toxicity data for most health endpoints. Pred...

Designing a Quantitative Structure-Activity Relationship for the Intrinsic Metabolic Clearance of Environmentally Relevant Chemicals

EPA Science Inventory

Toxicokinetic models serve a vital role in risk assessment by bridging the gap between chemical exposure and potentially toxic endpoints. While intrinsic metabolic clearance rates have a strong impact on toxicokinetics, limited data is available for environmentally relevant chemi...

Toxmatch-a new software tool to aid in the development and evaluation of chemically similar groups.

PubMed

Patlewicz, G; Jeliazkova, N; Gallegos Saliner, A; Worth, A P

2008-01-01

Chemical similarity is a widely used concept in toxicology, and is based on the hypothesis that similar compounds should have similar biological activities. This forms the underlying basis for performing read-across, forming chemical groups and developing (Quantitative) Structure-Activity Relationships ((Q)SARs). Chemical similarity is often perceived as structural similarity but in fact there are a number of other approaches that can be used to assess similarity. A systematic similarity analysis usually comprises two main steps. Firstly the chemical structures to be compared need to be characterised in terms of relevant descriptors which encode their physicochemical, topological, geometrical and/or surface properties. A second step involves a quantitative comparison of those descriptors using similarity (or dissimilarity) indices. This work outlines the use of chemical similarity principles in the formation of endpoint specific chemical groupings. Examples are provided to illustrate the development and evaluation of chemical groupings using a new software application called Toxmatch that was recently commissioned by the European Chemicals Bureau (ECB), of the European Commission's Joint Research Centre. Insights from using this software are highlighted with specific focus on the prospective application of chemical groupings under the new chemicals legislation, REACH.

An advanced application of the quantitative structure-activity relationship concept in electrokinetic chromatography of metal complexes.

PubMed

Oszwałdowski, Sławomir; Timerbaev, Andrei R

2008-02-01

The relevance of the quantitative structure-activity relationship (QSAR) principle in MEKC and microemulsion EKC (MEEKC) of metal-ligand complexes was evaluated for a better understanding of analyte migration mechanism. A series of gallium chelates were applied as test solutes with available experimental migration data in order to reveal the molecular properties that govern the separation. The QSAR models operating with n-octanol-water partition coefficients or van der Waals volumes were found to be valid for estimation of the retention factors (log k') of neutral compounds when using only an aqueous MEEKC electrolyte. On the other hand, consistent approximations of log k' for both uncharged and charged complexes in either EKC mode (and also with hydro-organic BGEs) were achievable with two-parametric QSARs in which the dipole moment is additionally incorporated as a structural descriptor, reflecting the electrostatic solute-pseudostationary phase interaction. The theoretical analysis of significant molecular parameters in MEKC systems, in which the micellar BGE is modified with an organic solvent, confirmed that concomitant consideration of hydrophobic, electrostatic, and solvation factors is essential for explaining the migration behavior of neutral metal complexes.

Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

PubMed

Xu, Yuting; Ma, Junshui; Liaw, Andy; Sheridan, Robert P; Svetnik, Vladimir

2017-10-23

Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR data sets. It was also found that multitask DNN models-those trained on and predicting multiple QSAR properties simultaneously-outperform DNNs trained separately on the individual data sets in many, but not all, tasks. To date there has been no satisfactory explanation of why the QSAR of one task embedded in a multitask DNN can borrow information from other unrelated QSAR tasks. Thus, using multitask DNNs in a way that consistently provides a predictive advantage becomes a challenge. In this work, we explored why multitask DNNs make a difference in predictive performance. Our results show that during prediction a multitask DNN does borrow "signal" from molecules with similar structures in the training sets of the other tasks. However, whether this borrowing leads to better or worse predictive performance depends on whether the activities are correlated. On the basis of this, we have developed a strategy to use multitask DNNs that incorporate prior domain knowledge to select training sets with correlated activities, and we demonstrate its effectiveness on several examples.

Quantitative structure-cytotoxicity relationship of phenylpropanoid amides.

PubMed

Shimada, Chiyako; Uesawa, Yoshihiro; Ishihara, Mariko; Kagaya, Hajime; Kanamoto, Taisei; Terakubo, Shigemi; Nakashima, Hideki; Takao, Koichi; Saito, Takayuki; Sugita, Yoshiaki; Sakagami, Hiroshi

2014-07-01

A total of 12 phenylpropanoid amides were subjected to quantitative structure-activity relationship (QSAR) analysis, based on their cytotoxicity, tumor selectivity and anti-HIV activity, in order to investigate on their biological activities. Cytotoxicity against four human oral squamous cell carcinoma (OSCC) cell lines and three human oral normal cells was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Tumor selectivity was evaluated by the ratio of the mean CC50 (50% cytotoxic concentration) against normal oral cells to that against OSCC cell lines. Anti-HIV activity was evaluated by the ratio of CC50 to EC50 (50% cytoprotective concentration from HIV infection). Physicochemical, structural, and quantum-chemical parameters were calculated based on the conformations optimized by the LowModeMD method followed by density functional theory (DFT) method. Twelve phenylpropanoid amides showed moderate cytotoxicity against both normal and OSCC cell lines. N-Caffeoyl derivatives coupled with vanillylamine and tyramine exhibited relatively higher tumor selectivity. Cytotoxicity against normal cells was correlated with descriptors related to electrostatic interaction such as polar surface area and chemical hardness, whereas cytotoxicity against tumor cells correlated with free energy, surface area and ellipticity. The tumor-selective cytotoxicity correlated with molecular size (surface area) and electrostatic interaction (the maximum electrostatic potential). The molecular size, shape and ability for electrostatic interaction are useful parameters for estimating the tumor selectivity of phenylpropanoid amides. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

2D-QSAR and 3D-QSAR/CoMSIA Studies on a Series of (R)-2-((2-(1H-Indol-2-yl)ethyl)amino)-1-Phenylethan-1-ol with Human β₃-Adrenergic Activity.

PubMed

Apablaza, Gastón; Montoya, Luisa; Morales-Verdejo, Cesar; Mellado, Marco; Cuellar, Mauricio; Lagos, Carlos F; Soto-Delgado, Jorge; Chung, Hery; Pessoa-Mahana, Carlos David; Mella, Jaime

2017-03-05

The β₃ adrenergic receptor is raising as an important drug target for the treatment of pathologies such as diabetes, obesity, depression, and cardiac diseases among others. Several attempts to obtain selective and high affinity ligands have been made. Currently, Mirabegron is the only available drug on the market that targets this receptor approved for the treatment of overactive bladder. However, the FDA (Food and Drug Administration) in USA and the MHRA (Medicines and Healthcare products Regulatory Agency) in UK have made reports of potentially life-threatening side effects associated with the administration of Mirabegron, casting doubts on the continuity of this compound. Therefore, it is of utmost importance to gather information for the rational design and synthesis of new β₃ adrenergic ligands. Herein, we present the first combined 2D-QSAR (two-dimensional Quantitative Structure-Activity Relationship) and 3D-QSAR/CoMSIA (three-dimensional Quantitative Structure-Activity Relationship/Comparative Molecular Similarity Index Analysis) study on a series of potent β₃ adrenergic agonists of indole-alkylamine structure. We found a series of changes that can be made in the steric, hydrogen-bond donor and acceptor, lipophilicity and molar refractivity properties of the compounds to generate new promising molecules. Finally, based on our analysis, a summary and a regiospecific description of the requirements for improving β₃ adrenergic activity is given.

High Add Valued Application of Turpentine in Crop Production through Structural Modification and QSAR Analysis.

PubMed

Gao, Yanqing; Li, Jingjing; Li, Jian; Song, Zhanqian; Shang, Shibin; Rao, Xiaoping

2018-02-08

Turpentine is a volatile component of resin, which is an abundant forest resource in Southern China. As one of the most important components, the integrated application of β-pinene has been studied. The broad-spectrum evaluation of β-pinene and its analogues has, therefore, been necessary. In an attempt to expand the scope of agro-activity trials, the preparation and the evaluation of the herbicidal activity of a series of β-pinene analogues against three agricultural herbs were carried out. In accordance with the overall herbicidal activity, it is noteworthy that compounds 6k , 6l , and 6m demonstrated extreme activity with IC 50 values of 0.065, 0.065, and 0.052 mol active ingredients/hectare against E. crus-galli . The preliminary structure-activity relationship (SAR) was analyzed and the compounds with the appropriate volatility and substituent type that had beneficial herbicidal activity were analyzed. Simultaneously, the quantitative structure-activity relationship (QSAR) model was built and the most important structural features were indicated, which was, to a certain extent, in line with the SAR study. The study aimed to study the application of the forest resource turpentine in agriculture as a potential and alternative approach for comprehensive utilization.

Quantitative Structure-Cytotoxicity Relationship of Oleoylamides.

PubMed

Sakagami, Hiroshi; Uesawa, Yoshihiro; Ishihara, Mariko; Kagaya, Hajime; Kanamoto, Taisei; Terakubo, Shigemi; Nakashima, Hideki; Takao, Koichi; Sugita, Yoshiaki

2015-10-01

Eighteen oleoylamides were subjected to quantitative structure-activity relationship analysis based on their cytotoxicity, tumor selectivity and anti-HIV activity, in order to assess their biological activities. Cytotoxicity against four human oral squamous cell carcinoma (OSCC) cell lines and five human oral normal cells (gingival fibroblast, periodontal ligament fibroblast, pulp cell, oral keratinocyte, primary gingival epithelial cells) was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Tumor-selectivity (TS) was evaluated by the ratio of the mean 50% cytotoxic concentration (CC50) against normal human oral cells to that against OSCC cell lines. Potency-selectivity expression (PSE) was determined by the ratio of TS to CC50 against OSCC. Anti-HIV activity was evaluated by the ratio of CC50 to the concentration leading to 50% cytoprotection from HIV infection (EC50). Physicochemical, structural and quantum-chemical parameters were calculated based on the conformations optimized by the LowModeMD method. Among 18 derivatives, compounds 8: with a catechol group) and 18: with a (2-pyridyl)amino group) had the highest TS. On the other hand, doxorubicin and 5-fluorouracil (5-FU) were more highly cytotoxic to normal epithelial cells, displaying unexpectedly lower TS and PSE values. None of the compounds had anti-HIV activity. Among 330 chemical descriptors, 75, 73 and 19 descriptors significantly correlated to the cytotoxicity to normal and tumor cells, and TS, respectively. Multivariate statistics with chemical descriptors for molecular polarization and hydrophobicity may be useful for the evaluation of cytotoxicity and TS of oleoylamides. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Synthesis and quantitative structure-activity relationship (QSAR) study of novel isoxazoline and oxime derivatives of podophyllotoxin as insecticidal agents.

PubMed

Wang, Yi; Shao, Yonghua; Wang, Yangyang; Fan, Lingling; Yu, Xiang; Zhi, Xiaoyan; Yang, Chun; Qu, Huan; Yao, Xiaojun; Xu, Hui

2012-08-29

In continuation of our program aimed at the discovery and development of natural-product-based insecticidal agents, 33 isoxazoline and oxime derivatives of podophyllotoxin modified in the C and D rings were synthesized and their structures were characterized by Proton nuclear magnetic resonance ((1)H NMR), high-resolution mass spectrometry (HRMS), electrospray ionization-mass spectrometry (ESI-MS), optical rotation, melting point (mp), and infrared (IR) spectroscopy. The stereochemical configurations of compounds 5e, 5f, and 9f were unambiguously determined by X-ray crystallography. Their insecticidal activity was evaluated against the pre-third-instar larvae of northern armyworm, Mythimna separata (Walker), in vivo. Compounds 5e, 9c, 11g, and 11h especially exhibited more promising insecticidal activity than toosendanin, a commercial botanical insecticide extracted from Melia azedarach . A genetic algorithm combined with multiple linear regression (GA-MLR) calculation is performed by the MOBY DIGS package. Five selected descriptors are as follows: one two-dimensional (2D) autocorrelation descriptor (GATS4e), one edge adjacency indice (EEig06x), one RDF descriptor (RDF080v), one three-dimensional (3D) MoRSE descriptor (Mor09v), and one atom-centered fragment (H-052) descriptor. Quantitative structure-activity relationship studies demonstrated that the insecticidal activity of these compounds was mainly influenced by many factors, such as electronic distribution, steric factors, etc. For this model, the standard deviation error in prediction (SDEP) is 0.0592, the correlation coefficient (R(2)) is 0.861, and the leave-one-out cross-validation correlation coefficient (Q(2)loo) is 0.797.

QSAR and 3D QSAR of inhibitors of the epidermal growth factor receptor

NASA Astrophysics Data System (ADS)

Pinto-Bazurco, Mariano; Tsakovska, Ivanka; Pajeva, Ilza

This article reports quantitative structure-activity relationships (QSAR) and 3D QSAR models of 134 structurally diverse inhibitors of the epidermal growth factor receptor (EGFR) tyrosine kinase. Free-Wilson analysis was used to derive the QSAR model. It identified the substituents in aniline, the polycyclic system, and the substituents at the 6- and 7-positions of the polycyclic system as the most important structural features. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used in the 3D QSAR modeling. The steric and electrostatic interactions proved the most important for the inhibitory effect. Both QSAR and 3D QSAR models led to consistent results. On the basis of the statistically significant models, new structures were proposed and their inhibitory activities were predicted.

Quantitative structure-activity relationships for organophosphates binding to acetylcholinesterase.

PubMed

Ruark, Christopher D; Hack, C Eric; Robinson, Peter J; Anderson, Paul E; Gearhart, Jeffery M

2013-02-01

Organophosphates are a group of pesticides and chemical warfare nerve agents that inhibit acetylcholinesterase, the enzyme responsible for hydrolysis of the excitatory neurotransmitter acetylcholine. Numerous structural variants exist for this chemical class, and data regarding their toxicity can be difficult to obtain in a timely fashion. At the same time, their use as pesticides and military weapons is widespread, which presents a major concern and challenge in evaluating human toxicity. To address this concern, a quantitative structure-activity relationship (QSAR) was developed to predict pentavalent organophosphate oxon human acetylcholinesterase bimolecular rate constants. A database of 278 three-dimensional structures and their bimolecular rates was developed from 15 peer-reviewed publications. A database of simplified molecular input line entry notations and their respective acetylcholinesterase bimolecular rate constants are listed in Supplementary Material, Table I. The database was quite diverse, spanning 7 log units of activity. In order to describe their structure, 675 molecular descriptors were calculated using AMPAC 8.0 and CODESSA 2.7.10. Orthogonal projection to latent structures regression, bootstrap leave-random-many-out cross-validation and y-randomization were used to develop an externally validated consensus QSAR model. The domain of applicability was assessed by the William's plot. Six external compounds were outside the warning leverage indicating potential model extrapolation. A number of compounds had residuals >2 or <-2, indicating potential outliers or activity cliffs. The results show that the HOMO-LUMO energy gap contributed most significantly to the binding affinity. A mean training R (2) of 0.80, a mean test set R (2) of 0.76 and a consensus external test set R (2) of 0.66 were achieved using the QSAR. The training and external test set RMSE values were found to be 0.76 and 0.88. The results suggest that this QSAR model can be used in physiologically based pharmacokinetic/pharmacodynamic models of organophosphate toxicity to determine the rate of acetylcholinesterase inhibition.

A quantification model for the structure of clay materials.

PubMed

Tang, Liansheng; Sang, Haitao; Chen, Haokun; Sun, Yinlei; Zhang, Longjian

2016-07-04

In this paper, the quantification for clay structure is explicitly explained, and the approach and goals of quantification are also discussed. The authors consider that the purpose of the quantification for clay structure is to determine some parameters that can be used to quantitatively characterize the impact of clay structure on the macro-mechanical behaviour. According to the system theory and the law of energy conservation, a quantification model for the structure characteristics of clay materials is established and three quantitative parameters (i.e., deformation structure potential, strength structure potential and comprehensive structure potential) are proposed. And the corresponding tests are conducted. The experimental results show that these quantitative parameters can accurately reflect the influence of clay structure on the deformation behaviour, strength behaviour and the relative magnitude of structural influence on the above two quantitative parameters, respectively. These quantitative parameters have explicit mechanical meanings, and can be used to characterize the structural influences of clay on its mechanical behaviour.

Computational Methods in Drug Discovery

PubMed Central

Sliwoski, Gregory; Kothiwale, Sandeepkumar; Meiler, Jens

2014-01-01

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature. PMID:24381236

United States Air Force Graduate Student Summer Support Program (1987). Program Technical Report. Volume 2

DTIC Science & Technology

1987-12-01

Metabolism (VMAX) Using Quantitative Structure- Activity Relationships (QSAR) 17 Directed Motion Doppler Shift Effects on Mitric Oxide (0,0) Gamma Band...chemiluminescence values were observed at characteristic times after adding glucose to the disks. We also produced virus-sized nanoparticles (Glucose...These nanoparticles were able to penetrate a .2 um filter,and they retained their enzymatic activity for weeks. They produced 20-fold greater

Biochemical interpretation of quantitative structure-activity relationships (QSAR) for biodegradation of N-heterocycles: a complementary approach to predict biodegradability.

PubMed

Philipp, Bodo; Hoff, Malte; Germa, Florence; Schink, Bernhard; Beimborn, Dieter; Mersch-Sundermann, Volker

2007-02-15

Prediction of the biodegradability of organic compounds is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. We combined quantitative structure-activity relationships (QSAR) with the systematic collection of biochemical knowledge to establish rules for the prediction of aerobic biodegradation of N-heterocycles. Validated biodegradation data of 194 N-heterocyclic compounds were analyzed using the MULTICASE-method which delivered two QSAR models based on 17 activating (OSAR 1) and on 16 inactivating molecular fragments (GSAR 2), which were statistically significantly linked to efficient or poor biodegradability, respectively. The percentages of correct classifications were over 99% for both models, and cross-validation resulted in 67.9% (GSAR 1) and 70.4% (OSAR 2) correct predictions. Biochemical interpretation of the activating and inactivating characteristics of the molecular fragments delivered plausible mechanistic interpretations and enabled us to establish the following biodegradation rules: (1) Target sites for amidohydrolases and for cytochrome P450 monooxygenases enhance biodegradation of nonaromatic N-heterocycles. (2) Target sites for molybdenum hydroxylases enhance biodegradation of aromatic N-heterocycles. (3) Target sites for hydratation by an urocanase-like mechanism enhance biodegradation of imidazoles. Our complementary approach represents a feasible strategy for generating concrete rules for the prediction of biodegradability of organic compounds.

Quantitative structure--property relationships for enhancing predictions of synthetic organic chemical removal from drinking water by granular activated carbon.

PubMed

Magnuson, Matthew L; Speth, Thomas F

2005-10-01

Granular activated carbon is a frequently explored technology for removing synthetic organic contaminants from drinking water sources. The success of this technology relies on a number of factors based not only on the adsorptive properties of the contaminant but also on properties of the water itself, notably the presence of substances in the water which compete for adsorption sites. Because it is impractical to perform field-scale evaluations for all possible contaminants, the pore surface diffusion model (PSDM) has been developed and used to predict activated carbon column performance using single-solute isotherm data as inputs. Many assumptions are built into this model to account for kinetics of adsorption and competition for adsorption sites. This work further evaluates and expands this model, through the use of quantitative structure-property relationships (QSPRs) to predict the effect of natural organic matter fouling on activated carbon adsorption of specific contaminants. The QSPRs developed are based on a combination of calculated topographical indices and quantum chemical parameters. The QSPRs were evaluated in terms of their statistical predictive ability,the physical significance of the descriptors, and by comparison with field data. The QSPR-enhanced PSDM was judged to give results better than what could previously be obtained.

Quantitative Structure-Cytotoxicity Relationship of Cinnamic Acid Phenetyl Esters.

PubMed

Uesawa, Yoshihiro; Sakagami, Hiroshi; Okudaira, Noriyuki; Toda, Kazuhiro; Takao, Koichi; Kagaya, Hajime; Sugita, Yoshiaki

2018-02-01

Many phenolic acid phenethyl esters possess diverse biological effects including antioxidant, cytoprotective, anti-inflammation and anti-tumor activities. However, most previous antitumor studies have not considered the cytotoxicity against normal cells. Ten cinnamic acid phenetyl esters were subjected to quantitative structure-activity relationship (QSAR) analysis, based on their cytotoxicity and tumor-specificity, in order to find their new biological activities. Cytotoxicity against four human oral squamous cell carcinoma cell lines and three oral normal mesenchymal cells was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Tumor specificity (TS) was evaluated by the ratio of the mean 50% cytotoxic concentration (CC 50 ) against normal oral cells to that against human oral squamous cell carcinoma cell lines. Potency-selectivity expression (PSE) value was calculated by dividing the TS value by CC 50 against tumor cells. Apoptosis markers were detected by western blot analysis. Physicochemical, structural and quantum-chemical parameters were calculated based on the conformations optimized by force-field minimization. Western blot analysis demonstrated that [ 9 ] stimulated the cleavage of caspase-3, suggesting the induction of apoptosis. QSAR analysis demonstrated that TS values were correlated with shape, size and ionization potential. Chemical modification of the lead compound may be a potential choice for designing a new type of anticancer drugs. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Quantitative structure-activity relationship analysis of substituted arylazo pyridone dyes in photocatalytic system: Experimental and theoretical study.

PubMed

Dostanić, J; Lončarević, D; Zlatar, M; Vlahović, F; Jovanović, D M

2016-10-05

A series of arylazo pyridone dyes was synthesized by changing the type of the substituent group in the diazo moiety, ranging from strong electron-donating to strong electron-withdrawing groups. The structural and electronic properties of the investigated dyes was calculated at the M062X/6-31+G(d,p) level of theory. The observed good linear correlations between atomic charges and Hammett σp constants provided a basis to discuss the transmission of electronic substituent effects through a dye framework. The reactivity of synthesized dyes was tested through their decolorization efficiency in TiO2 photocatalytic system (Degussa P-25). Quantitative structure-activity relationship analysis revealed a strong correlation between reactivity of investigated dyes and Hammett substituent constants. The reaction was facilitated by electron-withdrawing groups, and retarded by electron-donating ones. Quantum mechanical calculations was used in order to describe the mechanism of the photocatalytic oxidation reactions of investigated dyes and interpret their reactivities within the framework of the Density Functional Theory (DFT). According to DFT based reactivity descriptors, i.e. Fukui functions and local softness, the active site moves from azo nitrogen atom linked to benzene ring to pyridone carbon atom linked to azo bond, going from dyes with electron-donating groups to dyes with electron-withdrawing groups. Copyright © 2016 Elsevier B.V. All rights reserved.

Pattern, growth, and aging in aggregation kinetics of a Vicsek-like active matter model

NASA Astrophysics Data System (ADS)

Das, Subir K.

2017-01-01

Via molecular dynamics simulations, we study kinetics in a Vicsek-like phase-separating active matter model. Quantitative results, for isotropic bicontinuous pattern, are presented on the structure, growth, and aging. These are obtained via the two-point equal-time density-density correlation function, the average domain length, and the two-time density autocorrelation function. Both the correlation functions exhibit basic scaling properties, implying self-similarity in the pattern dynamics, for which the average domain size exhibits a power-law growth in time. The equal-time correlation has a short distance behavior that provides reasonable agreement between the corresponding structure factor tail and the Porod law. The autocorrelation decay is a power-law in the average domain size. Apart from these basic similarities, the overall quantitative behavior of the above-mentioned observables is found to be vastly different from those of the corresponding passive limit of the model which also undergoes phase separation. The functional forms of these have been quantified. An exceptionally rapid growth in the active system occurs due to fast coherent motion of the particles, mean-squared-displacements of which exhibit multiple scaling regimes, including a long time ballistic one.

Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

EPA Science Inventory

Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external dataset, the best way to validate the predictive ability of a model is to perform its s...

MOAtox: A comprehensive mode of action and acute aquatic toxicity database for predictive model development (SETAC abstract)

EPA Science Inventory

The mode of toxic action (MOA) has been recognized as a key determinant of chemical toxicity and as an alternative to chemical class-based predictive toxicity modeling. However, the development of quantitative structure activity relationship (QSAR) and other models has been limit...

Relative Chemical Binding Affinities for Trout and Human Estrogen Receptor Using Different Competitive Binding Assays

EPA Science Inventory

Rainbow trout-based assays for estrogenicity are currently being used for development of predictive models based upon quantitative structure activity relationships. A predictive model based on a single species raises the question of whether this information is valid for other spe...

Development of Quantitative Structure-Activity Relationship (QSAR) Models to Predict the Carcinogenic Potency of Chemicals

EPA Science Inventory

Determining the carcinogenicity and carcinogenic potency of new chemicals is both a labor-intensive and time-consuming process. In order to expedite the screening process, there is a need to either: (1) identify alternative toxicity measures (shorter duration) that may be used as...

DEVELOPMENT OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS TO PREDICT TOXICITY FOR A VARIETY OF HUMAN AND ECOLOGICAL ENDPOINTS

EPA Science Inventory

The number of chemicals released into the environment has significantly increased over the past few years, leading to increased risk of human exposure through inhalation, ingestion, or dermal uptake. In addition, the risk also increases with increasing toxicity of the chemical. ...

Representations of Scientists in Canadian High School and College Textbooks

ERIC Educational Resources Information Center

van Eijck, Michiel; Roth, Wolff-Michael

2008-01-01

This study investigated the representations of a select group of scientists (n = 10) in a sample of Canadian high school and college textbooks. Drawing on semiotic and cultural-historical activity theoretical frameworks, we conducted two analyses. A coarse-grained, quantitative analysis of the prevalence and structure of these representations…

USE OF TROUT LIVER SLICES TO ENHANCE MECHANISTIC INTERPRETATION OF ER BINDING FOR COST-EFFECTIVE PRIORITIZATION OF CHEMICALS WITHIN LARGE INVENTORIES

EPA Science Inventory

The cost of testing chemicals as reproductive toxicants precludes the possibility of evaluating large chemical inventories without a robust strategic approach for setting priorities. The use of quantitative structure-activity relationships (QSARs) in early hazard identification m...

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Application of biospeckles for assessment of structural and cellular changes in muscle tissue

NASA Astrophysics Data System (ADS)

Maksymenko, Oleksandr P.; Muravsky, Leonid I.; Berezyuk, Mykola I.

2015-09-01

A modified spatial-temporal speckle correlation technique for operational assessment of structural changes in muscle tissues after slaughtering is considered. Coefficient of biological activity as a quantitative indicator of structural changes of biochemical processes in biological tissues is proposed. The experimental results have shown that this coefficient properly evaluates the biological activity of pig and chicken muscle tissue samples. Studying the degradation processes in muscle tissue during long-time storage in a refrigerator by measuring the spatial-temporal dynamics of biospeckle patterns is carried out. The reduction of the bioactivity level of refrigerated muscle tissue samples connected with the initiation of muscle fiber cracks and ruptures, reduction of sarcomeres, nuclei deformation, nuclear chromatin diminishing, and destruction of mitochondria is analyzed.

The Integral Method, a new approach to quantify bactericidal activity.

PubMed

Gottardi, Waldemar; Pfleiderer, Jörg; Nagl, Markus

2015-08-01

The bactericidal activity (BA) of antimicrobial agents is generally derived from the results of killing assays. A reliable quantitative characterization and particularly a comparison of these substances, however, are impossible with this information. We here propose a new method that takes into account the course of the complete killing curve for assaying BA and that allows a clear-cut quantitative comparison of antimicrobial agents with only one number. The new Integral Method, based on the reciprocal area below the killing curve, reliably calculates an average BA [log10 CFU/min] and, by implementation of the agent's concentration C, the average specific bactericidal activity SBA=BA/C [log10 CFU/min/mM]. Based on experimental killing data, the pertaining BA and SBA values of exemplary active halogen compounds were established, allowing quantitative assertions. N-chlorotaurine (NCT), chloramine T (CAT), monochloramine (NH2Cl), and iodine (I2) showed extremely diverging SBA values of 0.0020±0.0005, 1.11±0.15, 3.49±0.22, and 291±137log10 CFU/min/mM, respectively, against Staphylococcus aureus. This immediately demonstrates an approximately 550-fold stronger activity of CAT, 1730-fold of NH2Cl, and 150,000-fold of I2 compared to NCT. The inferred quantitative assertions and conclusions prove the new method suitable for characterizing bactericidal activity. Its application comprises the effect of defined agents on various bacteria, the consequence of temperature shifts, the influence of varying drug structure, dose-effect relationships, ranking of isosteric agents, comparison of competing commercial antimicrobial formulations, and the effect of additives. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative method of medication system interface evaluation.

PubMed

Pingenot, Alleene Anne; Shanteau, James; Pingenot, James D F

2007-01-01

The objective of this study was to develop a quantitative method of evaluating the user interface for medication system software. A detailed task analysis provided a description of user goals and essential activity. A structural fault analysis was used to develop a detailed description of the system interface. Nurses experienced with use of the system under evaluation provided estimates of failure rates for each point in this simplified fault tree. Means of estimated failure rates provided quantitative data for fault analysis. Authors note that, although failures of steps in the program were frequent, participants reported numerous methods of working around these failures so that overall system failure was rare. However, frequent process failure can affect the time required for processing medications, making a system inefficient. This method of interface analysis, called Software Efficiency Evaluation and Fault Identification Method, provides quantitative information with which prototypes can be compared and problems within an interface identified.

Design and preliminary structure-activity relationship of redox-silent semisynthetic tocotrienol analogues as inhibitors for breast cancer proliferation and invasion.

PubMed

Elnagar, Ahmed Y; Wali, Vikram B; Sylvester, Paul W; El Sayed, Khalid A

2010-01-15

Vitamin E (VE) is a generic term that represents a family of compounds composed of various tocopherol and tocotrienol isoforms. Tocotrienols display potent anti-angiogenic and antiproliferative activities. Redox-silent tocotrienol analogues also display potent anticancer activity. The ultimate objective of this study was to develop semisynthetically C-6-modified redox-silent tocotrienol analogues with enhanced antiproliferative and anti-invasive activities as compared to their parent compound. Examples of these are carbamate and ether analogues of alpha-, gamma-, and delta-tocotrienols (1-3). Various aliphatic, olefinic, and aromatic substituents were used. Steric limitation, electrostatic, hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA) properties were varied at this position and the biological activities of these derivatives were tested. Three-dimensional quantitative structure-activity relationship (3D QSAR) studies were performed using Comparative Molecular Field (CoMFA) and Comparative Molecular Similarity Indices Analyses (CoMSIA) to better understand the structural basis for biological activity and guide the future design of more potent VE analogues. Copyright 2009 Elsevier Ltd. All rights reserved.

Photo-induced self-cleaning and sterilizing activity of Sm3+ doped ZnO nanomaterials.

PubMed

Saif, M; Hafez, H; Nabeel, A I

2013-01-01

Highly active samarium doped zinc oxide self-cleaning and biocidal surfaces (x mol% Sm(3+)/ZnO where x=0, 1, 2 and 4 mol%) with crystalline porous structures were synthesized by hydrothermal method. Sm(3+)/ZnO thin films were characterized by X-ray diffraction (XRD), transmission electron microscope (TEM), scanning electron microscope (SEM), energy dispersive spectroscopic (EDS), UV-visible diffuse reflectance and fluorescence (FL) spectroscopy. The combination between doping and hydrothermal treatments significantly altered the morphology of ZnO into rod and plate-like nanoshapes structure and enhanced its absorption and emission of ultraviolet radiation. The photo-activity in term of quantitative determination of the active oxidative species (()OH) produced on the thin film surfaces was evaluated using fluorescent probe method. The results showed that, the hydrothermally treated 2.0 mol% Sm(3+)/ZnO film (S2) is the highly active one. The optical, structural, morphology and photo-activity properties of the highly active thin film (S2) make it promising surface for self-cleaning and sterilizing applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

Iterative Refinement of a Binding Pocket Model: Active Computational Steering of Lead Optimization

PubMed Central

2012-01-01

Computational approaches for binding affinity prediction are most frequently demonstrated through cross-validation within a series of molecules or through performance shown on a blinded test set. Here, we show how such a system performs in an iterative, temporal lead optimization exercise. A series of gyrase inhibitors with known synthetic order formed the set of molecules that could be selected for “synthesis.” Beginning with a small number of molecules, based only on structures and activities, a model was constructed. Compound selection was done computationally, each time making five selections based on confident predictions of high activity and five selections based on a quantitative measure of three-dimensional structural novelty. Compound selection was followed by model refinement using the new data. Iterative computational candidate selection produced rapid improvements in selected compound activity, and incorporation of explicitly novel compounds uncovered much more diverse active inhibitors than strategies lacking active novelty selection. PMID:23046104

Technique for Determination of Rational Boundaries in Combining Construction and Installation Processes Based on Quantitative Estimation of Technological Connections

NASA Astrophysics Data System (ADS)

Gusev, E. V.; Mukhametzyanov, Z. R.; Razyapov, R. V.

2017-11-01

The problems of the existing methods for the determination of combining and technologically interlinked construction processes and activities are considered under the modern construction conditions of various facilities. The necessity to identify common parameters that characterize the interaction nature of all the technology-related construction and installation processes and activities is shown. The research of the technologies of construction and installation processes for buildings and structures with the goal of determining a common parameter for evaluating the relationship between technologically interconnected processes and construction works are conducted. The result of this research was to identify the quantitative evaluation of interaction construction and installation processes and activities in a minimum technologically necessary volume of the previous process allowing one to plan and organize the execution of a subsequent technologically interconnected process. The quantitative evaluation is used as the basis for the calculation of the optimum range of the combination of processes and activities. The calculation method is based on the use of the graph theory. The authors applied a generic characterization parameter to reveal the technological links between construction and installation processes, and the proposed technique has adaptive properties which are key for wide use in organizational decisions forming. The article provides a written practical significance of the developed technique.

Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives.

PubMed

Zhang, Shuqun; Hou, Bo; Yang, Huaiyu; Zuo, Zhili

2016-05-01

Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer's disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r (2) = 0.988, q (2) = 0.757, ONC = 6; r (2) = 0.966, q (2) = 0.645, ONC = 5; and r (2) = 0.957, q (2) = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r (2) values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors.

Mitochondrial antibodies in primary biliary cirrhosis

PubMed Central

Berg, P. A.; Roitt, I. M.; Doniach, D.; Cooper, H. M.

1969-01-01

The effect on the mitochondrial antigen of different agents known to influence the integrity and structure of membranes has been studied using quantitative complement fixation with autoantibodies from the serum of a patient with primary biliary cirrhosis. The susceptibility to proteolytic enzymes suggests that the antigen is a protein. Activity depends upon an association with phospholipids. Addition of phospholipids prevents loss of antigen during artificial ageing of mitochondria at 37°. Activity is lost after treatment with phospholipases or solvents which extract phospholipids. Antigen is also destroyed by surface active agents which dissociate the link with phospholipid but those which weaken bonds between phospholipids and hydrophobic molecules yield fragments of antigen-containing membrane structures which, nonetheless, still react with the mitochondrial autoantibody. ImagesFIG. 2FIG. 4 PMID:5804537

Purified monomeric ligand.MD-2 complexes reveal molecular and structural requirements for activation and antagonism of TLR4 by Gram-negative bacterial endotoxins.

PubMed

Gioannini, Theresa L; Teghanemt, Athmane; Zhang, DeSheng; Esparza, Gregory; Yu, Liping; Weiss, Jerrold

2014-08-01

A major focus of work in our laboratory concerns the molecular mechanisms and structural bases of Gram-negative bacterial endotoxin recognition by host (e.g., human) endotoxin-recognition proteins that mediate and/or regulate activation of Toll-like receptor (TLR) 4. Here, we review studies of wild-type and variant monomeric endotoxin.MD-2 complexes first produced and characterized in our laboratories. These purified complexes have provided unique experimental reagents, revealing both quantitative and qualitative determinants of TLR4 activation and antagonism. This review is dedicated to the memory of Dr. Theresa L. Gioannini (1949-2014) who played a central role in many of the studies and discoveries that are reviewed.

Fish acute toxicity syndromes and their use in the QSAR approach to hazard assessment.

PubMed Central

McKim, J M; Bradbury, S P; Niemi, G J

1987-01-01

Implementation of the Toxic Substances Control Act of 1977 creates the need to reliably establish testing priorities because laboratory resources are limited and the number of industrial chemicals requiring evaluation is overwhelming. The use of quantitative structure activity relationship (QSAR) models as rapid and predictive screening tools to select more potentially hazardous chemicals for in-depth laboratory evaluation has been proposed. Further implementation and refinement of quantitative structure-toxicity relationships in aquatic toxicology and hazard assessment requires the development of a "mode-of-action" database. With such a database, a qualitative structure-activity relationship can be formulated to assign the proper mode of action, and respective QSAR, to a given chemical structure. In this review, the development of fish acute toxicity syndromes (FATS), which are toxic-response sets based on various behavioral and physiological-biochemical measurements, and their projected use in the mode-of-action database are outlined. Using behavioral parameters monitored in the fathead minnow during acute toxicity testing, FATS associated with acetylcholinesterase (AChE) inhibitors and narcotics could be reliably predicted. However, compounds classified as oxidative phosphorylation uncouplers or stimulants could not be resolved. Refinement of this approach by using respiratory-cardiovascular responses in the rainbow trout, enabled FATS associated with AChE inhibitors, convulsants, narcotics, respiratory blockers, respiratory membrane irritants, and uncouplers to be correctly predicted. PMID:3297660

Quantitative insights for the design of substrate-based SIRT1 inhibitors.

PubMed

Kokkonen, Piia; Mellini, Paolo; Nyrhilä, Olli; Rahnasto-Rilla, Minna; Suuronen, Tiina; Kiviranta, Päivi; Huhtiniemi, Tero; Poso, Antti; Jarho, Elina; Lahtela-Kakkonen, Maija

2014-08-01

Sirtuin 1 (SIRT1) is the most studied human sirtuin and it catalyzes the deacetylation reaction of acetylated lysine residues of its target proteins, for example histones. It is a promising drug target in the treatment of age-related diseases, such as neurodegenerative diseases and cancer. In this study, a series of known substrate-based sirtuin inhibitors was analyzed with comparative molecular field analysis (CoMFA), which is a three-dimensional quantitative structure-activity relationships (3D-QSAR) technique. The CoMFA model was validated both internally and externally, producing the statistical values concordance correlation coefficient (CCC) of 0.88, the mean value r(2)m of 0.66 and Q(2)F3 of 0.89. Based on the CoMFA interaction contours, 13 new potential inhibitors with high predicted activity were designed, and the activities were verified by in vitro measurements. This work proposes an effective approach for the design and activity prediction of new potential substrate-based SIRT1 inhibitors. Copyright © 2014 Elsevier B.V. All rights reserved.

Improving organic tandem solar cells based on water-processed nanoparticles by quantitative 3D nanoimaging.

PubMed

Pedersen, E B L; Angmo, D; Dam, H F; Thydén, K T S; Andersen, T R; Skjønsfjell, E T B; Krebs, F C; Holler, M; Diaz, A; Guizar-Sicairos, M; Breiby, D W; Andreasen, J W

2015-08-28

Organic solar cells have great potential for upscaling due to roll-to-roll processing and a low energy payback time, making them an attractive sustainable energy source for the future. Active layers coated with water-dispersible Landfester particles enable greater control of the layer formation and easier access to the printing industry, which has reduced the use of organic solvents since the 1980s. Through ptychographic X-ray computed tomography (PXCT), we image quantitatively a roll-to-roll coated photovoltaic tandem stack consisting of one bulk heterojunction active layer and one Landfester particle active layer. We extract the layered morphology with structural and density information including the porosity present in the various layers and the silver electrode with high resolution in 3D. The Landfester particle layer is found to have an undesired morphology with negatively correlated top- and bottom interfaces, wide thickness distribution and only partial surface coverage causing electric short circuits through the layer. By top coating a polymer material onto the Landfester nanoparticles we eliminate the structural defects of the layer such as porosity and roughness, and achieve the increased performance larger than 1 V expected for a tandem cell. This study highlights that quantitative imaging of weakly scattering stacked layers of organic materials has become feasible by PXCT, and that this information cannot be obtained by other methods. In the present study, this technique specifically reveals the need to improve the coatability and layer formation of Landfester nanoparticles, thus allowing improved solar cells to be produced.

Citizen surveillance for environmental monitoring: combining the efforts of citizen science and crowdsourcing in a quantitative data framework.

PubMed

Welvaert, Marijke; Caley, Peter

2016-01-01

Citizen science and crowdsourcing have been emerging as methods to collect data for surveillance and/or monitoring activities. They could be gathered under the overarching term citizen surveillance . The discipline, however, still struggles to be widely accepted in the scientific community, mainly because these activities are not embedded in a quantitative framework. This results in an ongoing discussion on how to analyze and make useful inference from these data. When considering the data collection process, we illustrate how citizen surveillance can be classified according to the nature of the underlying observation process measured in two dimensions-the degree of observer reporting intention and the control in observer detection effort. By classifying the observation process in these dimensions we distinguish between crowdsourcing, unstructured citizen science and structured citizen science. This classification helps the determine data processing and statistical treatment of these data for making inference. Using our framework, it is apparent that published studies are overwhelmingly associated with structured citizen science, and there are well developed statistical methods for the resulting data. In contrast, methods for making useful inference from purely crowd-sourced data remain under development, with the challenges of accounting for the unknown observation process considerable. Our quantitative framework for citizen surveillance calls for an integration of citizen science and crowdsourcing and provides a way forward to solve the statistical challenges inherent to citizen-sourced data.

3D Actin Network Centerline Extraction with Multiple Active Contours

PubMed Central

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2013-01-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and actin cables. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we propose a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D Total Internal Reflection Fluorescence Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy. Quantitative evaluation of the method using synthetic images shows that for images with SNR above 5.0, the average vertex error measured by the distance between our result and ground truth is 1 voxel, and the average Hausdorff distance is below 10 voxels. PMID:24316442

[Biochemical characterization of fractionated rat liver chromatin in experimental D-hypovitaminosis and after administration of steroidal drugs].

PubMed

Levitskiĭ, E L; Kholodova, Iu D; Gubskiĭ, Iu I; Primak, R G; Chabannyĭ, V N; Kindruk, N L; Mozzhukhina, T G; Lenchevskaia, L K; Mironova, V N; Saad, L M

1993-01-01

Marked changes in the structural and functional characteristics of liver nuclear chromatin fractions are observed under experimental D-hypovitaminosis, which differ in the degree of transcriptional activity. DNA-polymerase activity and activity of the fraction, enriched with RNA-polymerase I, increases in the active fraction. Free radical LPO reactions are modified in the chromatin fraction with low activity and to the less degree in the active one. Disturbances of chromatine structural properties are caused with the change in the protein and lipid components of chromatin. Administration of ecdysterone preparations (separately and together with vitamin D3) has a partial corrective effect on structural and functional organization of nuclear chromatine. At the action of ecdysterone normalization of LPO reactions modified by pathological changes is observed in the chromatin fraction with low activity and to the less degree in the active one. This kind of influence corrects to the less degree chromatin functional activity and quantitative and qualitative modifications of its protein component. Simultaneous influence of ecdysterone and vitamin D3 leads to the partial normalization of the biochemical indices studied (except for those which characterize LPO reactions) mainly in the active chromatin fraction.

An in vivo quantitative structure-activity relationship for a congeneric series of pyropheophorbide derivatives as photosensitizers for photodynamic therapy.

PubMed

Henderson, B W; Bellnier, D A; Greco, W R; Sharma, A; Pandey, R K; Vaughan, L A; Weishaupt, K R; Dougherty, T J

1997-09-15

An in vivo quantitative structure-activity relationship (QSAR) study was carried out on a congeneric series of pyropheophorbide photosensitizers to identify structural features critical for their antitumor activity in photodynamic therapy (PDT). The structural elements evaluated in this study include the length and shape (alkyl, alkenyl, cyclic, and secondary analogs) of the ether side chain. C3H mice, harboring the radiation-induced fibrosarcoma tumor model, were used to study three biological response endpoints: tumor growth delay, tumor cell lethality, and vascular perfusion. All three endpoints revealed highly similar QSAR patterns that constituted a function of the alkyl ether chain length and drug lipophilicity, which is defined as the log of the octanol:water partition coefficient (log P). When the illumination of tumor, tumor cells, or cutaneous vasculature occurred 24 h after sensitizer administration, activities were minimal with analogs of log P < or = 5, increased dramatically between log P of 5-6, and peaked between log P of 5.6-6.6. Activities declined gradually with higher log P. The lack of activity of the least-lipophilic analogs was explained in large part by their poor biodistribution characteristics, which yielded negligible tumor and plasma drug levels at the time of treatment with light. The progressively lower potencies of the most lipophilic analogs cannot be explained through the overall tumor and plasma pharmacokinetics of photosensitizer because tumor and plasma concentrations progressively increased with lipophilicity. When compensated for differences in tumor photosensitizer concentration, the 1-hexyl derivative (optimal lipophilicity) was 5-fold more potent than the 1-dodecyl derivative (more lipophilic) and 3-fold more potent than the 1-pentyl analog (less lipophilic), indicating that, in addition to the overall tumor pharmacokinetics, pharmacodynamic factors may influence PDT activity. Drug lipophilicity was highly predictive for photodynamic activity. QSAR modeling revealed that direct antitumor effects and vascular PDT effects may be governed by common mechanisms, and that the mere association of high levels of photosensitizer in the tumor tissue is not sufficient for optimal PDT efficiency.

Binary Classification of a Large Collection of Environmental Chemicals from Estrogen Receptor Assays by Quantitative Structure-Activity Relationship and Machine Learning Methods

EPA Science Inventory

ABSTRACT: There are thousands of environmental chemicals subject to regulatory decisions for endocrine disrupting potential. A promising approach to manage this large universe of untested chemicals is to use a prioritization filter that combines in vitro assays with in silico QSA...

Investigation of antigen-antibody interactions of sulfonamides with a monoclonal antibody in a fluorescence polarization immunoassay using 3D-QSAR models

USDA-ARS?s Scientific Manuscript database

A three-dimensional quantitative structure-activity relationship (3D-QSAR) model of sulfonamide analogs binding a monoclonal antibody (MAbSMR) produced against sulfamerazine was carried out by Distance Comparison (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular si...

A Novel Two-Step Hierarchial Quantitative Structure-Activity Relationship Modeling Workflow for Predicting Acute Toxicity of Chemicals in Rodents

EPA Science Inventory

Background: Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public–private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. Methods and results: A database co...

Understanding Knowledge-Sharing Breakdowns: A Meeting of the Quantitative and Qualitative Minds

ERIC Educational Resources Information Center

Soller, Amy

2004-01-01

The rapid advance of distance learning and networking technology has enabled universities and corporations to reach out and educate students across time and space barriers. Although this technology enables structured collaborative learning activities, online groups often do not enjoy the same benefits as face-to-face learners, and their…

INFLUENCE OF MATRIX FORMULATION ON DERMAL PERCUTANEOUS ABSORPTION OF TRIAZOLE FUNGICIDES USING QSAR AND PBPK / PD MODELS

EPA Science Inventory

The objective of this work is to use the Exposure Related Dose Estimating Model (ERDEM) and quantitative structure-activity relationship (QSAR) models to develop an assessment tool for human exposure assessment to triazole fungicides. A dermal exposure route is used for the physi...

Toxic Hazards Research Unit Annual Report: 1987

DTIC Science & Technology

1988-03-01

Low Density Lipoproteins and in Model Membranes 14 Sep Is Cigarette Smoking Neurotoric? Mr. Steven Goden Dr. R. Kutzman 4> ’October 1986 through September 1987 2I ...based pharmcokinetic model phosphoniteo,o-diethylmethyl quantitative structure activity relationship respiratory epithelium Salmonella sensitization j...in Cultured Respiratory Epithelial Cells ----------------------- ------------ 73 6 PHARMACOKINETIC AND PHARMACODYNAMIC MODELING .------------------ 78

Integration of different data gap filling techniques to facilitate assessment of polychlorinated biphenyls: A proof of principle case study (ASCCT meeting)

EPA Science Inventory

Data gap filling techniques are commonly used to predict hazard in the absence of empirical data. The most established techniques are read-across, trend analysis and quantitative structure-activity relationships (QSARs). Toxic equivalency factors (TEFs) are less frequently used d...

Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling

ERIC Educational Resources Information Center

Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J.

2009-01-01

The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…

RELATIONSHIPS OF QUANTITATIVE STRUCTURE-ACTIVITY TO COMPARATIVE TOXICITY OF SELECTED PHENOLS IN THE 'PIMEPHALES PROMELAS' AND 'TETRAHYMENA PYRIFORMIS' TEST SYSTEMS

EPA Science Inventory

The relative toxic response of 27 selected phenols in the 96-hr acute flowthrough Pimephales promelas (fathead minnow) and the 48- to 60-hr chronic static Tetrahymena pyriformis (ciliate protozoan) test systems was evaluated. Log Kow-dependent linear regression analyses revealed ...

Synthetic substances with morphine-like effect

PubMed Central

Braenden, Olav J.; Eddy, Nathan B.; Halbach, H.

1955-01-01

For morphine-, morphinan-, pethidine-, methadone-, and dithienyl-butenylamine groups of analgesic compounds a systematic survey is given of how analgesic activity is quantitatively affected by alteration of the chemical constitution. Features common to the structural formulae of substances with morphine-like analgesic effect are pointed out. ImagesFIG. 1FIG. 1(Contd.) PMID:13284565

DEVELOPMENT OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS (QSARS) TO PREDICT TOXICITY FOR A VARIETY OF HUMAN AND ECOLOGICAL ENDPOINTS

EPA Science Inventory

In general, the accuracy of a predicted toxicity value increases with increase in similarity between the query chemical and the chemicals used to develop a QSAR model. A toxicity estimation methodology employing this finding has been developed. A hierarchical based clustering t...

Quantitative variation in effector activity of ToxA isoforms from Stagonospora nodorum and Pyrenophora tritici-repentis

USDA-ARS?s Scientific Manuscript database

ToxA is a proteinaceous necrotrophic effector produced by Stagonospora nodorum and Pyrenophora tritici-repentis. In this study, all eight mature isoforms of the ToxA protein were purified and compared. Circular dichroism spectra indicated that all isoforms were structurally intact and had indistingu...

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

PubMed

Yang, Guang-Fu; Huang, Xiaoqin

2006-01-01

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

Nonparametric regression applied to quantitative structure-activity relationships

PubMed

Constans; Hirst

2000-03-01

Several nonparametric regressors have been applied to modeling quantitative structure-activity relationship (QSAR) data. The simplest regressor, the Nadaraya-Watson, was assessed in a genuine multivariate setting. Other regressors, the local linear and the shifted Nadaraya-Watson, were implemented within additive models--a computationally more expedient approach, better suited for low-density designs. Performances were benchmarked against the nonlinear method of smoothing splines. A linear reference point was provided by multilinear regression (MLR). Variable selection was explored using systematic combinations of different variables and combinations of principal components. For the data set examined, 47 inhibitors of dopamine beta-hydroxylase, the additive nonparametric regressors have greater predictive accuracy (as measured by the mean absolute error of the predictions or the Pearson correlation in cross-validation trails) than MLR. The use of principal components did not improve the performance of the nonparametric regressors over use of the original descriptors, since the original descriptors are not strongly correlated. It remains to be seen if the nonparametric regressors can be successfully coupled with better variable selection and dimensionality reduction in the context of high-dimensional QSARs.

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

PubMed

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

2012-12-01

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

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.

Quantitative structure activity relationship studies of sulfamide derivatives as carbonic anhydrase inhibitor: as antiglaucoma agents.

PubMed

Kumar, Surendra; Singh, Vineet; Tiwari, Meena

2007-07-01

Selective inhibition of ciliary process enzyme i.e. Carbonic Anhydrase-II is an excellent approach in reducing elevated intraocular pressure, thus treating glaucoma. Due to characteristic physicochemical properties of sulphonamide (Inhibition of Carbonic Anhydrase), they are clinically effective against glaucoma. But the non-specificity of sulphonamide derivatives to isozyme, leads to a range of side effects. Presently, the absence of comparative studies related to the binding of the sulphonamides as inhibitors to CA isozymes limits their use. In this paper we have represented "Three Dimensional Quantitative Structure Activity Relationship" study to characterize structural features of Sulfamide derivative [RR'NSO(2)NH(2)] as inhibitors, that are required for selective binding of carbonic anhydrase isozymes (CAI and CAII). In the analysis, stepwise multiple linear regression was performed using physiochemical parameters as independent variable and CA-I and CA-II inhibitory activity as dependent variable, respectively. The best multiparametric QSAR model obtained for CA-I inhibitory activity shows good statistical significance (r= 0.9714) and predictability (Q(2)=0.8921), involving the Electronic descriptors viz. Highest Occupied Molecular Orbital, Lowest Unoccupied Molecular Orbital and Steric descriptors viz. Principal moment of Inertia at X axis. Similarly, CA-II inhibitory activity also shows good statistical significance (r=0.9644) and predictability (Q(2)=0.8699) involving aforementioned descriptors. The predictive power of the model was successfully tested externally using a set of six compounds as test set for CA-I inhibitory activity and a set of seven compounds in case of CA-II inhibitory activity with good predictive squared correlation coefficient, r(2)(pred)=0.6016 and 0.7662, respectively. Overview of analysis favours substituents with high electronegativity and less bulk at R and R' positions of the parent nucleus, provides a basis to design new Sulfamide derivatives possessing potent and selective carbonic anhydrase-II inhibitory activity.

A Bayesian Active Learning Experimental Design for Inferring Signaling Networks.

PubMed

Ness, Robert O; Sachs, Karen; Mallick, Parag; Vitek, Olga

2018-06-21

Machine learning methods for learning network structure are applied to quantitative proteomics experiments and reverse-engineer intracellular signal transduction networks. They provide insight into the rewiring of signaling within the context of a disease or a phenotype. To learn the causal patterns of influence between proteins in the network, the methods require experiments that include targeted interventions that fix the activity of specific proteins. However, the interventions are costly and add experimental complexity. We describe an active learning strategy for selecting optimal interventions. Our approach takes as inputs pathway databases and historic data sets, expresses them in form of prior probability distributions on network structures, and selects interventions that maximize their expected contribution to structure learning. Evaluations on simulated and real data show that the strategy reduces the detection error of validated edges as compared with an unguided choice of interventions and avoids redundant interventions, thereby increasing the effectiveness of the experiment.

Physicochemical evolution during rice straw and coal co-pyrolysis and its effect on co-gasification reactivity.

PubMed

Wei, Juntao; Gong, Yan; Guo, Qinghua; Ding, Lu; Wang, Fuchen; Yu, Guangsuo

2017-03-01

Physicochemical evolution (i.e. pore structure variation, carbon structure change and active AAEM transformation) during rice straw (RS) and Shenfu bituminous coal (SF) co-pyrolysis was quantitatively determined in this work. Moreover, the corresponding char gasification was conducted using a thermogravimetric analyzer (TGA) and relative reactivity was proposed to quantify the co-pyrolysis impact on co-gasification reactivity. The results showed that the development of pore structure in co-pyrolyzed chars was first inhibited and then enhanced with the decrease of SF proportion. The promotion effect of co-pyrolysis on order degree of co-pyrolyzed chars gradually weakened with increasing RS proportion. Co-pyrolysis mainly enhanced active K transformation in co-pyrolyzed chars and the promotion effect was alleviated with increasing RS proportion. The inhibition effect of co-pyrolysis on co-gasification reactivity weakened with increasing RS proportion and gasification temperature, which was mainly attributed to the combination of carbon structure evolution and active AAEM transformation in co-pyrolysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structure-activity relationships between sterols and their thermal stability in oil matrix.

PubMed

Hu, Yinzhou; Xu, Junli; Huang, Weisu; Zhao, Yajing; Li, Maiquan; Wang, Mengmeng; Zheng, Lufei; Lu, Baiyi

2018-08-30

Structure-activity relationships between 20 sterols and their thermal stabilities were studied in a model oil system. All sterol degradations were found to be consistent with a first-order kinetic model with determination of coefficient (R 2 ) higher than 0.9444. The number of double bonds in the sterol structure was negatively correlated with the thermal stability of sterol, whereas the length of the branch chain was positively correlated with the thermal stability of sterol. A quantitative structure-activity relationship (QSAR) model to predict thermal stability of sterol was developed by using partial least squares regression (PLSR) combined with genetic algorithm (GA). A regression model was built with R 2 of 0.806. Almost all sterol degradation constants can be predicted accurately with R 2 of cross-validation equals to 0.680. Four important variables were selected in optimal QSAR model and the selected variables were observed to be related with information indices, RDF descriptors, and 3D-MoRSE descriptors. Copyright © 2018 Elsevier Ltd. All rights reserved.

2,3,5-Substituted tetrahydrofurans: COX-2 inhibitory activities of 5-hydroxymethyl-/carboxyl-2,3-diaryl-tetrahydro-furan-3-ols.

PubMed

Singh, Palwinder; Mittal, Anu; Kaur, Satwinderjeet; Kumar, Subodh

2008-12-01

5-Hydroxymethyl-/carboxyl-2,3-diaryl-tetrahydro-furan-3-ols have been investigated for their COX-1 and COX-2 inhibitory activities. Compounds 17, 18 and 20 have been identified as showing appreciable COX-2 inhibition and selectivity. The group present at C-5 of tetrahydrofuran and the substituents at the two phenyl rings, through their interactions with active site amino acid residues, significantly affect the activities of these molecules. The quantitative structure-activity relationship studies indicate the role of logP, TPSA, molecular connectivity and valence connectivity towards the activities of these molecules.

Comprehensive chlorophyll composition in the main edible seaweeds.

PubMed

Chen, Kewei; Ríos, José Julián; Pérez-Gálvez, Antonio; Roca, María

2017-08-01

Natural chlorophylls present in seaweeds have been studied regarding their biological activities and health benefit effects. However, detailed studies regarding characterization of the complete chlorophyll profile either qualitatively and quantitatively are scarce. This work deals with the comprehensive spectrometric study of the chlorophyll derivatives present in the five main coloured edible seaweeds. The novel complete MS 2 characterization of five chlorophyll derivatives: chlorophyll c 2 , chlorophyll c 1 , purpurin-18 a, pheophytin d and phytyl-purpurin-18 a has allowed to obtain fragmentation patterns associated with their different structural features. New chlorophyll derivatives have been identified and quantified by first time in red, green and brown seaweeds, including some oxidative structures. Quantitative data of the chlorophyll content comes to achieve significant information for food composition databases in bioactive compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Novel benzanthrone probes for membrane and protein studies

NASA Astrophysics Data System (ADS)

Ryzhova, Olga; Vus, Kateryna; Trusova, Valeriya; Kirilova, Elena; Kirilov, Georgiy; Gorbenko, Galyna; Kinnunen, Paavo

2016-09-01

The applicability of a series of novel benzanthrone dyes to monitoring the changes in physicochemical properties of lipid bilayer and to differentiating between the native and aggregated protein states has been evaluated. Based on the quantitative parameters of the dye-membrane and dye-protein binding derived from the fluorimetric titration data, the most prospective membrane probes and amyloid tracers have been selected from the group of examined compounds. Analysis of the red edge excitation shifts of the membrane- and amyloid-bound dyes provided information on the properties of benzanthrone binding sites within the lipid and protein matrixes. To understand how amyloid specificity of benzanthrones correlates with their structure, quantitative structure activity relationship (QSAR) analysis was performed involving a range of quantum chemical molecular descriptors. A statistically significant model was obtained for predicting the sensitivity of novel benzanthrone dyes to amyloid fibrils.

Data set for the proteomic inventory and quantitative analysis of chicken eggshell matrix proteins during the primary events of eggshell mineralization and the active growth phase of calcification.

PubMed

Marie, Pauline; Labas, Valérie; Brionne, Aurélien; Harichaux, Grégoire; Hennequet-Antier, Christelle; Rodriguez-Navarro, Alejandro B; Nys, Yves; Gautron, Joël

2015-09-01

Chicken eggshell is a biomineral composed of 95% calcite calcium carbonate mineral and of 3.5% organic matrix proteins. The assembly of mineral and its structural organization is controlled by its organic matrix. In a recent study [1], we have used quantitative proteomic, bioinformatic and functional analyses to explore the distribution of 216 eggshell matrix proteins at four key stages of shell mineralization defined as: (1) widespread deposition of amorphous calcium carbonate (ACC), (2) ACC transformation into crystalline calcite aggregates, (3) formation of larger calcite crystal units and (4) rapid growth of calcite as columnar structure with preferential crystal orientation. The current article detailed the quantitative analysis performed at the four stages of shell mineralization to determine the proteins which are the most abundant. Additionally, we reported the enriched GO terms and described the presence of 35 antimicrobial proteins equally distributed at all stages to keep the egg free of bacteria and of 81 proteins, the function of which could not be ascribed.

Data set for the proteomic inventory and quantitative analysis of chicken eggshell matrix proteins during the primary events of eggshell mineralization and the active growth phase of calcification

PubMed Central

Marie, Pauline; Labas, Valérie; Brionne, Aurélien; Harichaux, Grégoire; Hennequet-Antier, Christelle; Rodriguez-Navarro, Alejandro B.; Nys, Yves; Gautron, Joël

2015-01-01

Chicken eggshell is a biomineral composed of 95% calcite calcium carbonate mineral and of 3.5% organic matrix proteins. The assembly of mineral and its structural organization is controlled by its organic matrix. In a recent study [1], we have used quantitative proteomic, bioinformatic and functional analyses to explore the distribution of 216 eggshell matrix proteins at four key stages of shell mineralization defined as: (1) widespread deposition of amorphous calcium carbonate (ACC), (2) ACC transformation into crystalline calcite aggregates, (3) formation of larger calcite crystal units and (4) rapid growth of calcite as columnar structure with preferential crystal orientation. The current article detailed the quantitative analysis performed at the four stages of shell mineralization to determine the proteins which are the most abundant. Additionally, we reported the enriched GO terms and described the presence of 35 antimicrobial proteins equally distributed at all stages to keep the egg free of bacteria and of 81 proteins, the function of which could not be ascribed. PMID:26306314

Synthesis, activity and pharmacophore development for isatin-β-thiosemicarbazones with selective activity towards multidrug resistant cellsa

PubMed Central

Hall, Matthew D.; Salam, Noeris K.; Hellawell, Jennifer L.; Fales, Henry M.; Kensler, Caroline B.; Ludwig, Joseph A.; Szakacs, Gergely; Hibbs, David E.; Gottesman, Michael M.

2009-01-01

We have recently identified a new class of compounds that selectively kill cells that express P-glycoprotein (P-gp, MDR1), the ATPase efflux pump that confers multidrug resistance on cancer cells. Several isatin-β-thiosemicarbazones from our initial study have been validated, and a range of analogs synthesized and tested. A number demonstrated improved MDR1-selective activity over the lead, NSC73306 (1). Pharmacophores for cytotoxicity and MDR1-selectivity were generated to delineate the structural features required for activity. The MDR1-selective pharmacophore highlights the importance of aromatic/hydrophobic features at the N4 position of the thiosemicarbazone, and the reliance on the isatin moiety as key bioisosteric contributors. Additionally, a quantitative structure-activity relationship (QSAR) model that yielded a cross-validated correlation coefficient of 0.85 effectively predicts the cytotoxicty of untested thiosemicarbazones. Together, the models serve as effective approaches for predicting structures with MDR1-selective activity, and aid in directing the search for the mechanism of action of 1. PMID:19397322

Measurement and Prediction of the Thermomechanical Response of Shape Memory Alloy Hybrid Composite Beams

NASA Technical Reports Server (NTRS)

Davis, Brian; Turner, Travis L.; Seelecke, Stefan

2008-01-01

An experimental and numerical investigation into the static and dynamic responses of shape memory alloy hybrid composite (SMAHC) beams is performed to provide quantitative validation of a recently commercialized numerical analysis/design tool for SMAHC structures. The SMAHC beam specimens consist of a composite matrix with embedded pre-strained SMA actuators, which act against the mechanical boundaries of the structure when thermally activated to adaptively stiffen the structure. Numerical results are produced from the numerical model as implemented into the commercial finite element code ABAQUS. A rigorous experimental investigation is undertaken to acquire high fidelity measurements including infrared thermography and projection moire interferometry for full-field temperature and displacement measurements, respectively. High fidelity numerical results are also obtained from the numerical model and include measured parameters, such as geometric imperfection and thermal load. Excellent agreement is achieved between the predicted and measured results of the static and dynamic thermomechanical response, thereby providing quantitative validation of the numerical tool.

Feedbacks Between Soil Structure and Microbial Activities in Soil

NASA Astrophysics Data System (ADS)

Bailey, V. L.; Smith, A. P.; Fansler, S.; Varga, T.; Kemner, K. M.; McCue, L. A.

2017-12-01

Soil structure provides the physical framework for soil microbial habitats. The connectivity and size distribution of soil pores controls the microbial access to nutrient resources for growth and metabolism. Thus, a crucial component of soil research is how a soil's three-dimensional structure and organization influences its biological potential on a multitude of spatial and temporal scales. In an effort to understand microbial processes at scale more consistent with a microbial community, we have used soil aggregates as discrete units of soil microbial habitats. Our research has shown that mean pore diameter (x-ray computed tomography) of soil aggregates varies with the aggregate diameter itself. Analyzing both the bacterial composition (16S) and enzyme activities of individual aggregates showed significant differences in the relative abundances of key members the microbial communities associated with high enzyme activities compared to those with low activities, even though we observed no differences in the size of the biomass, nor in the overall richness or diversity of these communities. We hypothesize that resources and substrates have stimulated key populations in the aggregates identified as highly active, and as such, we conducted further research that explored how such key populations (i.e. fungal or bacterial dominated populations) alter pathways of C accumulation in aggregate size domains and microbial C utilization. Fungi support and stabilize soil structure through both physical and chemical effects of their hyphal networks. In contrast, bacterial-dominated communities are purported to facilitate micro- and fine aggregate stabilization. Here we quantify the direct effects fungal versus bacterial dominated communities on aggregate formation (both the rate of aggregation and the quality, quantity and distribution of SOC contained within aggregates). A quantitative understanding of the different mechanisms through which fungi or bacteria shape aggregate formation could alter how we currently treat our predictions of soil biogeochemistry. Current predictions are largely site- or biome-specific; quantitative mechanisms could underpin "rules" that operate at the pore-scale leading to more robust, mechanistic models.

Computational ligand-based rational design: Role of conformational sampling and force fields in model development.

PubMed

Shim, Jihyun; Mackerell, Alexander D

2011-05-01

A significant number of drug discovery efforts are based on natural products or high throughput screens from which compounds showing potential therapeutic effects are identified without knowledge of the target molecule or its 3D structure. In such cases computational ligand-based drug design (LBDD) can accelerate the drug discovery processes. LBDD is a general approach to elucidate the relationship of a compound's structure and physicochemical attributes to its biological activity. The resulting structure-activity relationship (SAR) may then act as the basis for the prediction of compounds with improved biological attributes. LBDD methods range from pharmacophore models identifying essential features of ligands responsible for their activity, quantitative structure-activity relationships (QSAR) yielding quantitative estimates of activities based on physiochemical properties, and to similarity searching, which explores compounds with similar properties as well as various combinations of the above. A number of recent LBDD approaches involve the use of multiple conformations of the ligands being studied. One of the basic components to generate multiple conformations in LBDD is molecular mechanics (MM), which apply an empirical energy function to relate conformation to energies and forces. The collection of conformations for ligands is then combined with functional data using methods ranging from regression analysis to neural networks, from which the SAR is determined. Accordingly, for effective application of LBDD for SAR determinations it is important that the compounds be accurately modelled such that the appropriate range of conformations accessible to the ligands is identified. Such accurate modelling is largely based on use of the appropriate empirical force field for the molecules being investigated and the approaches used to generate the conformations. The present chapter includes a brief overview of currently used SAR methods in LBDD followed by a more detailed presentation of issues and limitations associated with empirical energy functions and conformational sampling methods.

Toxicity of ionic liquids: database and prediction via quantitative structure-activity relationship method.

PubMed

Zhao, Yongsheng; Zhao, Jihong; Huang, Ying; Zhou, Qing; Zhang, Xiangping; Zhang, Suojiang

2014-08-15

A comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure-Activity relationships (QSAR) model is conducted to predict the toxicities (EC50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R(2)) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R(2) and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs. Copyright © 2014 Elsevier B.V. All rights reserved.

Overview of data and conceptual approaches for derivation of quantitative structure-activity relationships for ecotoxicological effects of organic chemicals.

PubMed

Bradbury, Steven P; Russom, Christine L; Ankley, Gerald T; Schultz, T Wayne; Walker, John D

2003-08-01

The use of quantitative structure-activity relationships (QSARs) in assessing potential toxic effects of organic chemicals on aquatic organisms continues to evolve as computational efficiency and toxicological understanding advance. With the ever-increasing production of new chemicals, and the need to optimize resources to assess thousands of existing chemicals in commerce, regulatory agencies have turned to QSARs as essential tools to help prioritize tiered risk assessments when empirical data are not available to evaluate toxicological effects. Progress in designing scientifically credible QSARs is intimately associated with the development of empirically derived databases of well-defined and quantified toxicity endpoints, which are based on a strategic evaluation of diverse sets of chemical structures, modes of toxic action, and species. This review provides a brief overview of four databases created for the purpose of developing QSARs for estimating toxicity of chemicals to aquatic organisms. The evolution of QSARs based initially on general chemical classification schemes, to models founded on modes of toxic action that range from nonspecific partitioning into hydrophobic cellular membranes to receptor-mediated mechanisms is summarized. Finally, an overview of expert systems that integrate chemical-specific mode of action classification and associated QSAR selection for estimating potential toxicological effects of organic chemicals is presented.

Parabolic quantitative structure-activity relationships and photodynamic therapy: application of a three-compartment model with clearance to the in vivo quantitative structure-activity relationships of a congeneric series of pyropheophorbide derivatives used as photosensitizers for photodynamic therapy.

PubMed

Potter, W R; Henderson, B W; Bellnier, D A; Pandey, R K; Vaughan, L A; Weishaupt, K R; Dougherty, T J

1999-11-01

An open three-compartment pharmacokinetic model was applied to the in vivo quantitative structure-activity relationship (QSAR) data of a homologous series of pyropheophorbide photosensitizers for photodynamic therapy (PDT). The physical model was a lipid compartment sandwiched between two identical aqueous compartments. The first compartment was assumed to clear irreversibly at a rate K0. The measured octanol-water partition coefficients, P(i) (where i is the number of carbons in the alkyl chain) and the clearance rate K0 determined the clearance kinetics of the drugs. Solving the coupled differential equations of the three-compartment model produced clearance kinetics for each of the sensitizers in each of the compartments. The third compartment was found to contain the target of PDT. This series of compounds is quite lipophilic. Therefore these drugs are found mainly in the second compartment. The drug level in the third compartment represents a small fraction of the tissue level and is thus not accessible to direct measurement by extraction. The second compartment of the model accurately predicted the clearance from the serum of mice of the hexyl ether of pyropheophorbide a, one member of this series of compounds. The diffusion and clearance rate constants were those found by fitting the pharmacokinetics of the third compartment to the QSAR data. This result validated the magnitude and mechanistic significance of the rate constants used to model the QSAR data. The PDT response to dose theory was applied to the kinetic behavior of the target compartment drug concentration. This produced a pharmacokinetic-based function connecting PDT response to dose as a function of time postinjection. This mechanistic dose-response function was fitted to published, single time point QSAR data for the pheophorbides. As a result, the PDT target threshold dose together with the predicted QSAR as a function of time postinjection was found.

The QSAR study of flavonoid-metal complexes scavenging rad OH free radical

NASA Astrophysics Data System (ADS)

Wang, Bo-chu; Qian, Jun-zhen; Fan, Ying; Tan, Jun

2014-10-01

Flavonoid-metal complexes have antioxidant activities. However, quantitative structure-activity relationships (QSAR) of flavonoid-metal complexes and their antioxidant activities has still not been tackled. On the basis of 21 structures of flavonoid-metal complexes and their antioxidant activities for scavenging rad OH free radical, we optimised their structures using Gaussian 03 software package and we subsequently calculated and chose 18 quantum chemistry descriptors such as dipole, charge and energy. Then we chose several quantum chemistry descriptors that are very important to the IC50 of flavonoid-metal complexes for scavenging rad OH free radical through method of stepwise linear regression, Meanwhile we obtained 4 new variables through the principal component analysis. Finally, we built the QSAR models based on those important quantum chemistry descriptors and the 4 new variables as the independent variables and the IC50 as the dependent variable using an Artificial Neural Network (ANN), and we validated the two models using experimental data. These results show that the two models in this paper are reliable and predictable.

Focus Groups in Elderly Ophthalmologic Patients: Setting the Stage for Quantitative Preference Elicitation.

PubMed

Danner, Marion; Vennedey, Vera; Hiligsmann, Mickaël; Fauser, Sascha; Stock, Stephanie

2016-02-01

Patients suffering from age-related macular degeneration (AMD) are rarely actively involved in decision-making, despite facing preference-sensitive treatment decisions. This paper presents a qualitative study to prepare quantitative preference elicitation in AMD patients. The aims of this study were (1) to gain familiarity with and learn about the special requirements of the AMD patient population for quantitative data collection; and (2) to select/refine patient-relevant treatment attributes and levels, and gain insights into preference structures. Semi-structured focus group interviews were performed. An interview guide including preselected categories in the form of seven potentially patient-relevant treatment attributes was followed. To identify the most patient-relevant treatment attributes, a ranking exercise was performed. Deductive content analyses were done by two independent reviewers for each attribute to derive subcategories (potential levels of attributes) and depict preference trends. The focus group interviews included 21 patients. The interviews revealed that quantitative preference surveys in this population will have to be interviewer assisted to make the survey feasible for patients. The five most patient-relevant attributes were the effect on visual function [ranking score (RS): 139], injection frequency (RS: 101), approval status (RS: 83), side effects (RS: 79), and monitoring frequency (RS: 76). Attribute and level refinement was based on patients' statements. Preference trends and dependencies between attributes informed the quantitative instrument design. This study suggests that qualitative research is a very helpful step to prepare the design and administration of quantitative preference elicitation instruments. It especially facilitated familiarization with the target population and its preferences, and it supported attribute/level refinement.

Synthesis, fungicidal evaluation and 3D-QSAR studies of novel 1,3,4-thiadiazole xylofuranose derivatives

PubMed Central

Zong, Guanghui; Yan, Xiaojing; Bi, Jiawei; Jiang, Rui; Qin, Yinan; Yuan, Huizhu; Lu, Huizhe; Dong, Yanhong; Jin, Shuhui; Zhang, Jianjun

2017-01-01

1,3,4-Thiadiazole and sugar-derived molecules have proven to be promising agrochemicals with growth promoting, insecticidal and fungicidal activities. In the research field of agricultural fungicide, applying union of active group we synthesized a new set of 1,3,4-thiadiazole xylofuranose derivatives and all of the compounds were characterized by 1H NMR and HRMS. In precise toxicity measurement, some of compounds exhibited more potent fungicidal activities than the most widely used commercial fungicide Chlorothalonil, promoting further research and development. Based on our experimental data, 3D-QSAR (three-dimensional quantitative structure-activity relationship) was established and investigated using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques, helping to better understand the structural requirements of lead compounds with high fungicidal activity and environmental compatibility. PMID:28746366

The effect of the neural activity on topological properties of growing neural networks.

PubMed

Gafarov, F M; Gafarova, V R

2016-09-01

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

Three-dimensional quantitative structure-activity relationship study on antioxidant capacity of curcumin analogues

NASA Astrophysics Data System (ADS)

Chen, Bohong; Zhu, Zhibo; Chen, Min; Dong, Wenqi; Li, Zhen

2014-03-01

A comparative molecular similarity indices analysis (CoMSIA) was performed on a set of 27 curcumin-like diarylpentanoid analogues with the radical scavenging activities. A significant cross-validated correlation coefficient Q2 (0.784), SEP (0.042) for CoMSIA were obtained, indicating the statistical significance of the correlation. Further we adopt a rational approach toward the selection of substituents at various positions in our scaffold,and finally find the favored and disfavoured regions for the enhanced antioxidative activity. The results have been used as a guide to design compounds that, potentially, have better activity against oxidative damage.

Influence of thermodynamic parameter in Lanosterol 14alpha-demethylase inhibitory activity as antifungal agents: a QSAR approach.

PubMed

Vasanthanathan, Poongavanam; Lakshmi, Manickavasagam; Arockia Babu, Marianesan; Kaskhedikar, Sathish Gopalrao

2006-06-01

A quantitative structure activity relationship, Hansch approach was applied on twenty compounds of chromene derivatives as Lanosterol 14alpha-demethylase inhibitory activity against eight fungal organisms. Various physicochemical descriptors and reported minimum inhibitory concentration values of different fungal organisms were used as independent variables and dependent variable respectively. The best models for eight different fungal organisms were first validated by leave-one-out cross validation procedure. It was revealed that thermodynamic parameters were found to have overall significant correlationship with anti fungal activity and these studies provide an insight to design new molecules.

Applications of genetic algorithms on the structure-activity relationship analysis of some cinnamamides.

PubMed

Hou, T J; Wang, J M; Liao, N; Xu, X J

1999-01-01

Quantitative structure-activity relationships (QSARs) for 35 cinnamamides were studied. By using a genetic algorithm (GA), a group of multiple regression models with high fitness scores was generated. From the statistical analyses of the descriptors used in the evolution procedure, the principal features affecting the anticonvulsant activity were found. The significant descriptors include the partition coefficient, the molar refraction, the Hammet sigma constant of the substituents on the benzene ring, and the formation energy of the molecules. It could be found that the steric complementarity and the hydrophobic interaction between the inhibitors and the receptor were very important to the biological activity, while the contribution of the electronic effect was not so obvious. Moreover, by construction of the spline models for these four principal descriptors, the effective range for each descriptor was identified.

Experimental study of reparative regeneration processes in the wound treated with bioactive dressings.

PubMed

Chekmareva, I A

2002-02-01

Quantitative and structural functional analysis of granulation tissue cells during treatment with protein-polysaccharide dressing Collahit F was carried out. The preparation effectively cleansed the wound from detritus, prevented secondary infection due to stimulation of the functional activity of macrophages and due to the effect of its antiseptic component (furagin), and stimulated proliferative activity of fibroblasts and granulation tissue microvessels on day 5 of treatment, thus promoting repair processes in the wound.

Validity of active fault identification through magnetic anomalous using earthquake mechanism, microgravity and topography structure analysis in Cisolok area

NASA Astrophysics Data System (ADS)

Setyonegoro, Wiko; Kurniawan, Telly; Ahadi, Suaidi; Rohadi, Supriyanto; Hardy, Thomas; Prayogo, Angga S.

2017-07-01

Research was conducted to determine the value of the magnetic anomalies to identify anomalous value standard fault, down or up with the type of Meratus trending northeast-southwest Cisolok, Sukabumi. Data collection was performed by setting the measurement grid at intervals of 5 meters distance measurement using a Precision Proton Magnetometer (PPM) -GSM-19T. To identification the active fault using magnetic is needed another parameter. The purpose of this study is to identification active fault using magnetic Anomaly in related with subsurface structure through the validation analysis of earthquake mechanism, microgravity and with Topography Structure in Java Island. Qualitative interpretation is done by analyzing the residual anomaly that has been reduced to the pole while the quantitative interpretation is done by analyzing the pattern of residual anomalies through computation. The results of quantitative interpretation, an anomalous value reduction to the pole magnetic field is at -700 nT to 700 nT while the results of the qualitative interpretation of the modeling of the path AA', BB' and CC' shows the magnetic anomaly at coordinates liquefaction resources with a value of 1028.04, 1416.21, - 1565, -1686.91. The measurement results obtained in Cisolok magnetic anomalies that indicate a high content of alumina (Al) and iron (Fe) which be identified appears through the fault gap towards the northeast through Rajamandala Lembang Fault related to the mechanism in the form of a normal fault with slip rate of 2 mm / year.

Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds

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

Helguera, Aliuska Morales; Molecular Simulation and Drug Design, Chemical Bioactive Center, Central University of Las Villas, Santa Clara, 54830, Villa Clara; Department of Chemistry, Central University of Las Villas, Santa Clara, 54830, Villa Clara

2008-09-01

In this work, Quantitative Structure-Activity Relationship (QSAR) modelling was used as a tool for predicting the carcinogenic potency of a set of 39 nitroso-compounds, which have been bioassayed in male rats by using the oral route of administration. The optimum QSAR model provided evidence of good fit and performance of predicitivity from training set. It was able to account for about 84% of the variance in the experimental activity and exhibited high values of the determination coefficients of cross validations, leave one out and bootstrapping (q{sup 2}{sub LOO} = 78.53 and q{sup 2}{sub Boot} = 74.97). Such a model wasmore » based on spectral moments weighted with Gasteiger-Marsilli atomic charges, polarizability and hydrophobicity, as well as with Abraham indexes, specifically the summation solute hydrogen bond basicity and the combined dipolarity/polarizability. This is the first study to have explored the possibility of combining Abraham solute descriptors with spectral moments. A reasonable interpretation of these molecular descriptors from a toxicological point of view was achieved by means of taking into account bond contributions. The set of relationships so derived revealed the importance of the length of the alkyl chains for determining carcinogenic potential of the chemicals analysed, and were able to explain the difference between mono-substituted and di-substituted nitrosoureas as well as to discriminate between isomeric structures with hydroxyl-alkyl and alkyl substituents in different positions. Moreover, they allowed the recognition of structural alerts in classical structures of two potent nitrosamines, consistent with their biotransformation. These results indicate that this new approach has the potential for improving carcinogenicity predictions based on the identification of structural alerts.« less

Silkworm cocoons inspire models for random fiber and particulate composites

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

Chen Fujia; Porter, David; Vollrath, Fritz

The bioengineering design principles evolved in silkworm cocoons make them ideal natural prototypes and models for structural composites. Cocoons depend for their stiffness and strength on the connectivity of bonding between their constituent materials of silk fibers and sericin binder. Strain-activated mechanisms for loss of bonding connectivity in cocoons can be translated directly into a surprisingly simple yet universal set of physically realistic as well as predictive quantitative structure-property relations for a wide range of technologically important fiber and particulate composite materials.

Silkworm cocoons inspire models for random fiber and particulate composites

NASA Astrophysics Data System (ADS)

Chen, Fujia; Porter, David; Vollrath, Fritz

2010-10-01

The bioengineering design principles evolved in silkworm cocoons make them ideal natural prototypes and models for structural composites. Cocoons depend for their stiffness and strength on the connectivity of bonding between their constituent materials of silk fibers and sericin binder. Strain-activated mechanisms for loss of bonding connectivity in cocoons can be translated directly into a surprisingly simple yet universal set of physically realistic as well as predictive quantitative structure-property relations for a wide range of technologically important fiber and particulate composite materials.

Methods to enable the design of bioactive small molecules targeting RNA

PubMed Central

Disney, Matthew D.; Yildirim, Ilyas; Childs-Disney, Jessica L.

2014-01-01

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including Structure-Activity Relationships Through Sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome. PMID:24357181

Methods to enable the design of bioactive small molecules targeting RNA.

PubMed

Disney, Matthew D; Yildirim, Ilyas; Childs-Disney, Jessica L

2014-02-21

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including structure-activity relationships through sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome.

Single-fluorophore monitoring of DNA hybridization for investigating the effect of secondary structure on the nucleation step.

PubMed

Jo, Joon-Jung; Kim, Min-Ji; Son, Jung-Tae; Kim, Jandi; Shin, Jong-Shik

2009-07-17

Nucleic acid hybridization is one of the essential biological processes involved in storage and transmission of genetic information. Here we quantitatively determined the effect of secondary structure on the hybridization activation energy using structurally defined oligonucleotides. It turned out that activation energy is linearly proportional to the length of a single-stranded region flanking a nucleation site, generating a 0.18 kcal/mol energy barrier per nucleotide. Based on this result, we propose that the presence of single-stranded segments available for non-productive base pairing with a nucleation counterpart extends the searching process for nucleation sites to find a perfect match. This result may provide insights into rational selection of a target mRNA site for siRNA and antisense gene silencing.

M-Polynomials and topological indices of V-Phenylenic Nanotubes and Nanotori.

PubMed

Kwun, Young Chel; Munir, Mobeen; Nazeer, Waqas; Rafique, Shazia; Min Kang, Shin

2017-08-18

V-Phenylenic nanotubes and nanotori are most comprehensively studied nanostructures due to widespread applications in the production of catalytic, gas-sensing and corrosion-resistant materials. Representing chemical compounds with M-polynomial is a recent idea and it produces nice formulas of degree-based topological indices which correlate chemical properties of the material under investigation. These indices are used in the development of quantitative structure-activity relationships (QSARs) in which the biological activity and other properties of molecules like boiling point, stability, strain energy etc. are correlated with their structures. In this paper, we determine general closed formulae for M-polynomials of V-Phylenic nanotubes and nanotori. We recover important topological degree-based indices. We also give different graphs of topological indices and their relations with the parameters of structures.

Novel coumarins and related copper complexes with biological activity: DNA binding, molecular docking and in vitro antiproliferative activity.

PubMed

Pivetta, Tiziana; Valletta, Elisa; Ferino, Giulio; Isaia, Francesco; Pani, Alessandra; Vascellari, Sarah; Castellano, Carlo; Demartin, Francesco; Cabiddu, Maria Grazia; Cadoni, Enzo

2017-12-01

Coumarins show biological activity and are widely exploited for their therapeutic effects. Although a great number of coumarins substituted by heterocyclic moieties have been prepared, few studies have been carried out on coumarins containing pyridine heterocycle, which is known to modulate their physiological activities. We prepared and characterized three novel 3-(pyridin-2-yl)coumarins and their corresponding copper(II) complexes. We extended our investigations also to three known similar coumarins, since no data about their biochemical activity was previously been reported. The antiproliferative activity of the studied compounds was tested against human derived tumor cell lines and one human normal cell line. The DNA binding constants were determined and docking studies with DNA carried out. Selected Quantitative Structure-Activity Relationship (QSAR) descriptors were calculated in order to relate a set of structural and topological descriptors of the studied compounds to their DNA interaction and cytotoxic activity. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing.

PubMed

Leaman, Eric J; Geuther, Brian Q; Behkam, Bahareh

2018-04-20

Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E. coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).

Understanding the Molecular Determinant of Reversible Human Monoamine Oxidase B Inhibitors Containing 2H-Chromen-2-One Core: Structure-Based and Ligand-Based Derived Three-Dimensional Quantitative Structure-Activity Relationships Predictive Models.

PubMed

Mladenović, Milan; Patsilinakos, Alexandros; Pirolli, Adele; Sabatino, Manuela; Ragno, Rino

2017-04-24

Monoamine oxidase B (MAO B) catalyzes the oxidative deamination of aryalkylamines neurotransmitters with concomitant reduction of oxygen to hydrogen peroxide. Consequently, the enzyme's malfunction can induce oxidative damage to mitochondrial DNA and mediates development of Parkinson's disease. Thus, MAO B emerges as a promising target for developing pharmaceuticals potentially useful to treat this vicious neurodegenerative condition. Aiming to contribute to the development of drugs with the reversible mechanism of MAO B inhibition only, herein, an extended in silico-in vitro procedure for the selection of novel MAO B inhibitors is demonstrated, including the following: (1) definition of optimized and validated structure-based three-dimensional (3-D) quantitative structure-activity relationships (QSAR) models derived from available cocrystallized inhibitor-MAO B complexes; (2) elaboration of SAR features for either irreversible or reversible MAO B inhibitors to characterize and improve coumarin-based inhibitor activity (Protein Data Bank ID: 2V61 ) as the most potent reversible lead compound; (3) definition of structure-based (SB) and ligand-based (LB) alignment rule assessments by which virtually any untested potential MAO B inhibitor might be evaluated; (4) predictive ability validation of the best 3-D QSAR model through SB/LB modeling of four coumarin-based external test sets (267 compounds); (5) design and SB/LB alignment of novel coumarin-based scaffolds experimentally validated through synthesis and biological evaluation in vitro. Due to the wide range of molecular diversity within the 3-D QSAR training set and derived features, the selected N probe-derived 3-D QSAR model proves to be a valuable tool for virtual screening (VS) of novel MAO B inhibitors and a platform for design, synthesis and evaluation of novel active structures. Accordingly, six highly active and selective MAO B inhibitors (picomolar to low nanomolar range of activity) were disclosed as a result of rational SB/LB 3D QSAR design; therefore, D123 (IC 50 = 0.83 nM, K i = 0.25 nM) and D124 (IC 50 = 0.97 nM, K i = 0.29 nM) are potential lead candidates as anti-Parkinson's drugs.

Structure-Thermodynamics-Antioxidant Activity Relationships of Selected Natural Phenolic Acids and Derivatives: An Experimental and Theoretical Evaluation

PubMed Central

Zheng, Jie; Liang, Guizhao

2015-01-01

Phenolic acids and derivatives have potential biological functions, however, little is known about the structure-activity relationships and the underlying action mechanisms of these phenolic acids to date. Herein we investigate the structure-thermodynamics-antioxidant relationships of 20 natural phenolic acids and derivatives using DPPH• scavenging assay, density functional theory calculations at the B3LYP/6-311++G(d,p) levels of theory, and quantitative structure-activity relationship (QSAR) modeling. Three main working mechanisms (HAT, SETPT and SPLET) are explored in four micro-environments (gas-phase, benzene, water and ethanol). Computed thermodynamics parameters (BDE, IP, PDE, PA and ETE) are compared with the experimental radical scavenging activities against DPPH•. Available theoretical and experimental investigations have demonstrated that the extended delocalization and intra-molecular hydrogen bonds are the two main contributions to the stability of the radicals. The C = O or C = C in COOH, COOR, C = CCOOH and C = CCOOR groups, and orthodiphenolic functionalities are shown to favorably stabilize the specific radical species to enhance the radical scavenging activities, while the presence of the single OH in the ortho position of the COOH group disfavors the activities. HAT is the thermodynamically preferred mechanism in the gas phase and benzene, whereas SPLET in water and ethanol. Furthermore, our QSAR models robustly represent the structure-activity relationships of these explored compounds in polar media. PMID:25803685

Structure-thermodynamics-antioxidant activity relationships of selected natural phenolic acids and derivatives: an experimental and theoretical evaluation.

PubMed

Chen, Yuzhen; Xiao, Huizhi; Zheng, Jie; Liang, Guizhao

2015-01-01

Phenolic acids and derivatives have potential biological functions, however, little is known about the structure-activity relationships and the underlying action mechanisms of these phenolic acids to date. Herein we investigate the structure-thermodynamics-antioxidant relationships of 20 natural phenolic acids and derivatives using DPPH• scavenging assay, density functional theory calculations at the B3LYP/6-311++G(d,p) levels of theory, and quantitative structure-activity relationship (QSAR) modeling. Three main working mechanisms (HAT, SETPT and SPLET) are explored in four micro-environments (gas-phase, benzene, water and ethanol). Computed thermodynamics parameters (BDE, IP, PDE, PA and ETE) are compared with the experimental radical scavenging activities against DPPH•. Available theoretical and experimental investigations have demonstrated that the extended delocalization and intra-molecular hydrogen bonds are the two main contributions to the stability of the radicals. The C = O or C = C in COOH, COOR, C = CCOOH and C = CCOOR groups, and orthodiphenolic functionalities are shown to favorably stabilize the specific radical species to enhance the radical scavenging activities, while the presence of the single OH in the ortho position of the COOH group disfavors the activities. HAT is the thermodynamically preferred mechanism in the gas phase and benzene, whereas SPLET in water and ethanol. Furthermore, our QSAR models robustly represent the structure-activity relationships of these explored compounds in polar media.

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

PubMed Central

Putz, Mihai V.; Duda-Seiman, Corina; Duda-Seiman, Daniel; Putz, Ana-Maria; Alexandrescu, Iulia; Mernea, Maria; Avram, Speranta

2016-01-01

Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding) and quantitative (for predicting) mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR) offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD) as the revived precursor for comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analysis (CoMSIA); all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine congeners’ (HEPT ligands) antiviral activity against Human Immunodeficiency Virus of first type (HIV-1) and new pharmacophores in treating severe genetic disorders (like depression and psychosis), respectively, all involving 3D pharmacophore interactions. PMID:27399692

Synthesis, fungicidal activity, structure-activity relationships (SARs) and density functional theory (DFT) studies of novel strobilurin analogues containing arylpyrazole rings.

PubMed

Liu, Yuanyuan; Lv, Kunzhi; Li, Yi; Nan, Qiuli; Xu, Jinyuan

2018-05-18

A series of novel strobilurin analogues (1a-1f, 2a-2e, 3a-3e) containing arylpyrazole rings were synthesized and characterized by NMR spectroscopy. The structures of 1f, 2b and 3b were also determined by single crystal X-ray diffraction analysis. These analogues were collected together with other twenty-eight similar compounds 4a-4f, 5a-5h, 6a-6h and 7a-7f from our previous studies, for in vitro bioassays and thorough structure-activity relationships (SARs) studies. Most compounds exhibited excellent-to-good fungicidal activity against Rhizoctonia solani, especially 5c, 7a, 6c, and 3b with 98.94%, 83.40%, 71.40% and 65.87% inhibition rates at 0.1 μg mL -1 , respectively, better than commercial pyraclostrobin. Comparative molecular field analysis (CoMFA) was employed to study three-dimensional quantitative structure-activity relationships (3D-QSARs). Density functional theory (DFT) calculation was also carried out to provide more information regarding SARs. The present work provided some hints for developing novel strobilurin fungicides.

Quantitative analysis of nucleolar chromatin distribution in the complex convoluted nucleoli of Didinium nasutum (Ciliophora).

PubMed

Leonova, Olga G; Karajan, Bella P; Ivlev, Yuri F; Ivanova, Julia L; Skarlato, Sergei O; Popenko, Vladimir I

2013-01-01

We have earlier shown that the typical Didinium nasutum nucleolus is a complex convoluted branched domain, comprising a dense fibrillar component located at the periphery of the nucleolus and a granular component located in the central part. Here our main interest was to study quantitatively the spatial distribution of nucleolar chromatin structures in these convoluted nucleoli. There are no "classical" fibrillar centers in D.nasutum nucleoli. The spatial distribution of nucleolar chromatin bodies, which play the role of nucleolar organizers in the macronucleus of D.nasutum, was studied using 3D reconstructions based on serial ultrathin sections. The relative number of nucleolar chromatin bodies was determined in macronuclei of recently fed, starved D.nasutum cells and in resting cysts. This parameter is shown to correlate with the activity of the nucleolus. However, the relative number of nucleolar chromatin bodies in different regions of the same convoluted nucleolus is approximately the same. This finding suggests equal activity in different parts of the nucleolar domain and indicates the existence of some molecular mechanism enabling it to synchronize this activity in D. nasutum nucleoli. Our data show that D. nasutum nucleoli display bipartite structure. All nucleolar chromatin bodies are shown to be located outside of nucleoli, at the periphery of the fibrillar component.

Use of the ciliated protozoan Tetrahymena pyriformis for the assessment of toxicity and quantitative structure--activity relationships of xenobiotics: comparison with the Microtox test.

PubMed

Bogaerts, P; Bohatier, J; Bonnemoy, F

2001-07-01

Cytotoxicity and quantitative structure-activity relationships of 13 inorganic and 21 organic substances were determined using three bioassays performed on the ciliated protozoan Tetrahymena pyriformis and the luminescent bacterium Vibrio fischeri. The best concordance of toxicity results was observed between the T. pyriformis FDA--esterase activity and population growth inhibition tests for the organic compounds. The sensitivity of these two assays is compared with that of the Microtox test. The T. pyriformis FDA test showed a high sensitivity is most cases. The aim of the current research was to determine whether the relative toxicity of metal ions and organic molecules, with these three bioassays, was predictable using three ion characteristics and hydrophobicity, respectively. For metal ions, the variable that best modeled the toxicity data obtained with the two T. pyriformis tests was the softness index [sigma(p), i.e., (coordinate bond energy of the metal fluoride--coordinate bond energy of the metal iodide)/(coordinate bond energy of the metal fluoride)]. No correlation was found with the Microtox test. For organic compounds, a significant correlation was observed between the hydrophobicity coefficient and the toxicity data. This correlation is closer with the two tests using Tetrahymena. Copyright 2001 Academic Press.

Rational Quantitative Structure-Activity Relationship (RQSAR) Screen for PXR and CAR Isoform-Specific Nuclear Receptor Ligands

PubMed Central

Dring, Ann M.; Anderson, Linnea E.; Qamar, Saima; Stoner, Matthew A.

2010-01-01

Constitutive androstane receptor (CAR) and pregnane X receptor (PXR) are closely related orphan nuclear receptor proteins that share several ligands and target overlapping sets of genes involved in homeostasis and all phases of drug metabolism. CAR and PXR are involved in the development of certain diseases, including diabetes, metabolic syndrome and obesity. Ligand screens for these receptors so far have typically focused on steroid hormone analogs with pharmacophore-based approaches, only to find relatively few new hits. Multiple CAR isoforms have been detected in human liver, with the most abundant being the constitutively active reference, CAR1, and the ligand-dependent isoform CAR3. It has been assumed that any compound that binds CAR1 should also activate CAR3, and so CAR3 can be used as a ligand-activated surrogate for CAR1 studies. The possibility of CAR3-specific ligands has not, so far, been addressed. To investigate the differences between CAR1, CAR3 and PXR, and to look for more CAR ligands that may be of use in quantitative structure-activity relationship (QSAR) studies, we performed a luciferase transactivation assay screen of 60 mostly non-steroid compounds. Known active compounds with different core chemistries were chosen as starting points and structural variants were rationally selected for screening. Distinct differences in agonist versus inverse agonist/antagonist effects were seen in 49 compounds that had some ligand effect on at least one receptor and 18 that had effects on all three receptors; eight were CAR1 ligands only, three were CAR3 only ligands and four affected PXR only. This work provides evidence for new CAR ligands, some of which have CAR3-specific effects, and provides observational data on CAR and PXR ligands with which to inform in silico strategies. Compounds that demonstrated unique activity on any one receptor are potentially valuable diagnostic tools for the investigation of in vivo molecular targets. PMID:20869355

Atom-based 3D-QSAR, induced fit docking, and molecular dynamics simulations study of thieno[2,3-b]pyridines negative allosteric modulators of mGluR5.

PubMed

Vijaya Prabhu, Sitrarasu; Singh, Sanjeev Kumar

2018-05-28

Atom-based three dimensional-quantitative structure-activity relationship (3D-QSAR) model was developed on the basis of 5-point pharmacophore hypothesis (AARRR) with two hydrogen bond acceptors (A) and three aromatic rings for the derivatives of thieno[2,3-b]pyridine, which modulates the activity to inhibit the mGluR5 receptor. Generation of a highly predictive 3D-QSAR model was performed using the alignment of predicted pharmacophore hypothesis for the training set (R 2  = 0.84, SD = 0.26, F = 45.8, N = 29) and test set (Q 2  = 0.74, RMSE = 0.235, Pearson-R = 0.94, N = 9). The best pharmacophore hypothesis AARRR was selected, and developed three dimensional-quantitative structure activity relationship (3D-QSAR) model also supported the outcome of this study by means of favorable and unfavorable electron withdrawing group and hydrophobic regions of most active compound 42d and least active compound 18b. Following, induced fit docking and binding free energy calculations reveals the reliable binding orientation of the compounds. Finally, molecular dynamics simulations for 100 ns were performed to depict the protein-ligand stability. We anticipate that the resulted outcome could be supportive to discover potent negative allosteric modulators for metabotropic glutamate receptor 5 (mGluR5).

Dietary flavonoids modulate CYP2C to improve drug oral bioavailability and their qualitative/quantitative structure-activity relationship.

PubMed

Wang, Hong-Jaan; Pao, Li-Heng; Hsiong, Cheng-Huei; Shih, Tung-Yuan; Lee, Meei-Shyuan; Hu, Oliver Yoa-Pu

2014-03-01

This study aims to improve the drug oral bioavailability by co-administration with flavonoid inhibitors of the CYP2C isozyme and to establish qualitative and quantitative (QSAR) structure-activity relationships (SAR) between flavonoids and CYP2C. A total of 40 naturally occurring flavonoids were screened in vitro for CYP2C inhibition. Enzyme activity was determined by measuring conversion of tolbutamide to 4-hydroxytolbutamide by rat liver microsomes. The percent inhibition and IC50 of each flavonoid were calculated and used to develop SAR and QSAR. The most effective flavonoid was orally co-administered in vivo with a cholesterol-reducing drug, fluvastatin, which is normally metabolized by CYP2C. The most potent CYP2C inhibitor identified in vitro was tamarixetin (IC50 = 1.4 μM). This flavonoid enhanced the oral bioavailability of fluvastatin in vivo, producing a >2-fold increase in the area under the concentration-time curve and in the peak plasma concentration. SAR analysis indicated that the presence of a 2,3-double bond in the C ring, hydroxylation at positions 5, 6, and 7, and glycosylation had important effects on flavonoid-CYP2C interactions. These findings should prove useful for predicting the inhibition of CYP2C activity by other untested flavonoid-like compounds. In the present study, tamarixetin significantly inhibited CYP2C activity in vitro and in vivo. Thus, the use of tamarixetin could improve the therapeutic efficacy of drugs with low bioavailability.

QSAR, docking and ADMET studies of artemisinin derivatives for antimalarial activity targeting plasmepsin II, a hemoglobin-degrading enzyme from P. falciparum.

PubMed

Qidwai, Tabish; Yadav, Dharmendra K; Khan, Feroz; Dhawan, Sangeeta; Bhakuni, R S

2012-01-01

This work presents the development of quantitative structure activity relationship (QSAR) model to predict the antimalarial activity of artemisinin derivatives. The structures of the molecules are represented by chemical descriptors that encode topological, geometric, and electronic structure features. Screening through QSAR model suggested that compounds A24, A24a, A53, A54, A62 and A64 possess significant antimalarial activity. Linear model is developed by the multiple linear regression method to link structures to their reported antimalarial activity. The correlation in terms of regression coefficient (r(2)) was 0.90 and prediction accuracy of model in terms of cross validation regression coefficient (rCV(2)) was 0.82. This study indicates that chemical properties viz., atom count (all atoms), connectivity index (order 1, standard), ring count (all rings), shape index (basic kappa, order 2), and solvent accessibility surface area are well correlated with antimalarial activity. The docking study showed high binding affinity of predicted active compounds against antimalarial target Plasmepsins (Plm-II). Further studies for oral bioavailability, ADMET and toxicity risk assessment suggest that compound A24, A24a, A53, A54, A62 and A64 exhibits marked antimalarial activity comparable to standard antimalarial drugs. Later one of the predicted active compound A64 was chemically synthesized, structure elucidated by NMR and in vivo tested in multidrug resistant strain of Plasmodium yoelii nigeriensis infected mice. The experimental results obtained agreed well with the predicted values.

Differences in Monoamine Oxidase Activity in the Brain of Wistar and August Rats with High and Low Locomotor Activity: A Cytochemical Study.

PubMed

Sergutina, A V; Rakhmanova, V I

2016-06-01

Monoamine oxidase activity was quantitatively assessed by cytochemical method in brain structures (layers III and V of the sensorimotor cortex, caudate nucleus, nucleus accumbens, hippocampal CA3 field) of rats of August line and Wistar population with high and low locomotor activity in the open fi eld test. Monoamine oxidase activity (substrate tryptamine) predominated in the nucleus accumbens of Wistar rats with high motor activity in comparison with rats with low locomotor activity. In August rats, enzyme activity (substrates tryptamine and serotonin) predominated in the hippocampus of animals with high motor activity. Comparison of August rats with low locomotor activity and Wistar rats with high motor activity (i.e. animals demonstrating maximum differences in motor function) revealed significantly higher activity of the enzyme (substrates tryptamine and serotonin) in the hippocampus of Wistar rats. The study demonstrates clear-cut morphochemical specificity of monoaminergic metabolism based on the differences in the cytochemical parameter "monoamine oxidase activity", in the studied brain structures, responsible for the formation and realization of goal-directed behavior in Wistar and August rats.

Quantitative Methods in Psychology: Inevitable and Useless

PubMed Central

Toomela, Aaro

2010-01-01

Science begins with the question, what do I want to know? Science becomes science, however, only when this question is justified and the appropriate methodology is chosen for answering the research question. Research question should precede the other questions; methods should be chosen according to the research question and not vice versa. Modern quantitative psychology has accepted method as primary; research questions are adjusted to the methods. For understanding thinking in modern quantitative psychology, two epistemologies should be distinguished: structural-systemic that is based on Aristotelian thinking, and associative-quantitative that is based on Cartesian–Humean thinking. The first aims at understanding the structure that underlies the studied processes; the second looks for identification of cause–effect relationships between the events with no possible access to the understanding of the structures that underlie the processes. Quantitative methodology in particular as well as mathematical psychology in general, is useless for answering questions about structures and processes that underlie observed behaviors. Nevertheless, quantitative science is almost inevitable in a situation where the systemic-structural basis of behavior is not well understood; all sorts of applied decisions can be made on the basis of quantitative studies. In order to proceed, psychology should study structures; methodologically, constructive experiments should be added to observations and analytic experiments. PMID:21833199

Quantitative methods in psychology: inevitable and useless.

PubMed

Toomela, Aaro

2010-01-01

Science begins with the question, what do I want to know? Science becomes science, however, only when this question is justified and the appropriate methodology is chosen for answering the research question. Research question should precede the other questions; methods should be chosen according to the research question and not vice versa. Modern quantitative psychology has accepted method as primary; research questions are adjusted to the methods. For understanding thinking in modern quantitative psychology, two epistemologies should be distinguished: structural-systemic that is based on Aristotelian thinking, and associative-quantitative that is based on Cartesian-Humean thinking. The first aims at understanding the structure that underlies the studied processes; the second looks for identification of cause-effect relationships between the events with no possible access to the understanding of the structures that underlie the processes. Quantitative methodology in particular as well as mathematical psychology in general, is useless for answering questions about structures and processes that underlie observed behaviors. Nevertheless, quantitative science is almost inevitable in a situation where the systemic-structural basis of behavior is not well understood; all sorts of applied decisions can be made on the basis of quantitative studies. In order to proceed, psychology should study structures; methodologically, constructive experiments should be added to observations and analytic experiments.

Using ToxCast in vitro Assays in the Hierarchical Quantitative Structure-Activity Relationship (QSAR) Modeling for Predicting in vivo Toxicity of Chemicals

EPA Science Inventory

The goal of chemical toxicology research is utilizing short term bioassays and/or robust computational methods to predict in vivo toxicity endpoints for chemicals. The ToxCast program established at the US Environmental Protection Agency (EPA) is addressing this goal by using ca....

The Role of Feature Selection and Statistical Weighting in Predicting In Vivo Toxicity Using In Vitro Assay and QSAR Data (SOT)

EPA Science Inventory

Our study assesses the value of both in vitro assay and quantitative structure activity relationship (QSAR) data in predicting in vivo toxicity using numerous statistical models and approaches to process the data. Our models are built on datasets of (i) 586 chemicals for which bo...

Physiotherapists' beliefs and attitudes influence clinical practice in chronic low back pain: a systematic review of quantitative and qualitative studies.

PubMed

Gardner, Tania; Refshauge, Kathryn; Smith, Lorraine; McAuley, James; Hübscher, Markus; Goodall, Stephen

2017-07-01

What influence do physiotherapists' beliefs and attitudes about chronic low back pain have on their clinical management of people with chronic low back pain? Systematic review with data from quantitative and qualitative studies. Quantitative and qualitative studies were included if they investigated an association between physiotherapists' attitudes and beliefs about chronic low back pain and their clinical management of people with chronic low back pain. Five quantitative and five qualitative studies were included. Quantitative studies used measures of treatment orientation and fear avoidance to indicate physiotherapists' beliefs and attitudes about chronic low back pain. Quantitative studies showed that a higher biomedical orientation score (indicating a belief that pain and disability result from a specific structural impairment, and treatment is selected to address that impairment) was associated with: advice to delay return to work, advice to delay return to activity, and a belief that return to work or activity is a threat to the patient. Physiotherapists' fear avoidance scores were positively correlated with: increased certification of sick leave, advice to avoid return to work, and advice to avoid return to normal activity. Qualitative studies revealed two main themes attributed to beliefs and attitudes of physiotherapists who have a relationship to their management of chronic low back pain: treatment orientation and patient factors. Both quantitative and qualitative studies showed a relationship between treatment orientation and clinical practice. The inclusion of qualitative studies captured the influence of patient factors in clinical practice in chronic low back pain. There is a need to recognise that both beliefs and attitudes regarding treatment orientation of physiotherapists, and therapist-patient factors need to be considered when introducing new clinical practice models, so that the adoption of new clinical practice is maximised. [Gardner T, Refshauge K, Smith L, McAuley J, Hübscher M, Goodall S (2017) Physiotherapists' beliefs and attitudes influence clinical practice in chronic low back pain: a systematic review of quantitative and qualitative studies. Journal of Physiotherapy 63: 132-143]. Copyright © 2017 Australian Physiotherapy Association. Published by Elsevier B.V. All rights reserved.

Change of synovial vascularity in a single finger joint assessed by power doppler sonography correlated with radiographic change in rheumatoid arthritis: comparative study of a novel quantitative score with a semiquantitative score.

PubMed

Fukae, Jun; Kon, Yujiro; Henmi, Mihoko; Sakamoto, Fumihiko; Narita, Akihiro; Shimizu, Masato; Tanimura, Kazuhide; Matsuhashi, Megumi; Kamishima, Tamotsu; Atsumi, Tatsuya; Koike, Takao

2010-05-01

To investigate the relationship between synovial vascularity assessed by quantitative power Doppler sonography (PDS) and progression of structural bone damage in a single finger joint in patients with rheumatoid arthritis (RA). We studied 190 metacarpophalangeal (MCP) joints and 190 proximal interphalangeal (PIP) joints of 19 patients with active RA who had initial treatment with disease-modifying antirheumatic drugs (DMARDs). Patients were examined by clinical and laboratory assessments throughout the study. Hand and foot radiography was performed at baseline and the twentieth week. Magnetic resonance imaging (MRI) was performed at baseline. PDS was performed at baseline and the eighth week. Synovial vascularity was evaluated according to both quantitative and semiquantitative methods. Quantitative PDS was significantly correlated with the enhancement rate of MRI in each single finger joint. Comparing quantitative synovial vascularity and radiographic change in single MCP or PIP joints, the level of vascularity at baseline showed a significant positive correlation with radiographic progression at the twentieth week. The change of vascularity in response to DMARDs, defined as the percentage change in vascularity by the eighth week from baseline, was inversely correlated with radiographic progression in each MCP joint. The quantitative PDS method was more useful than the semiquantitative method for the evaluation of synovial vascularity in a single finger joint. The change of synovial vascularity in a single finger joint determined by quantitative PDS could numerically predict its radiographic progression. Using vascularity as a guide to consider a therapeutic approach would have benefits for patients with active RA.

Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.

PubMed

Gupta, Shikha; Basant, Nikita; Rai, Premanjali; Singh, Kunwar P

2015-11-01

Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and development of computational approaches has widely been advocated. In this study, artificial intelligence (AI)-based ten different qualitative and quantitative structure-property relationship (QSPR) models (MLPN, RBFN, PNN/GRNN, CCN, SVM, GEP, GMDH, SDT, DTF, DTB) were established for the prediction of the adsorption capacity of structurally diverse chemicals to activated carbon following the OECD guidelines. Structural diversity of the chemicals and nonlinear dependence in the data were evaluated using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation procedures performed employing a wide series of statistical checks. In complete dataset, the qualitative models rendered classification accuracies between 97.04 and 99.93%, while the quantitative models yielded correlation (R(2)) values of 0.877-0.977 between the measured and the predicted endpoint values. The quantitative prediction accuracies for the higher molecular weight (MW) compounds (class 4) were relatively better than those for the low MW compounds. Both in the qualitative and quantitative models, the Polarizability was the most influential descriptor. Structural alerts responsible for the extreme adsorption behavior of the compounds were identified. Higher number of carbon and presence of higher halogens in a molecule rendered higher binding affinity. Proposed QSPR models performed well and outperformed the previous reports. A relatively better performance of the ensemble learning models (DTF, DTB) may be attributed to the strengths of the bagging and boosting algorithms which enhance the predictive accuracies. The proposed AI models can be useful tools in screening the chemicals for their binding affinities toward carbon for their safe management.

Strong Electron Correlation in Photoionization of Spin-Orbit Doublets

NASA Astrophysics Data System (ADS)

Amusia, M. Ya.; Chernsheva, L. V.; Mnason, S. T.; Msezane, A. Z.; Radojevic, V.

2002-05-01

A new and explicitly many-body aspect of the "leveraging" of the spin-orbit interaction is demonstrated, spin-orbit activated interchannel coupling, which can significantly alter the photoionization cross section of a spin-orbit doublet. As an example, using a modified version of the Spin-Polarized Random-Phase-Approximation with Exchange methodology, a recently observed structure in the photoionization of Xe 3d(A. Kivimaki et al, Phys. Rev. A 63), 012716 (2000) has been explained both qualitatively and quantitatively. The structure is entirely due to this new spin-orbit activated interchannel coupling effect, which should be a general feature of inner-shell photoionization. This work was supported by NSF, NASA, DOE and ISTC.

Imidazole derivatives as angiotensin II AT1 receptor blockers: Benchmarks, drug-like calculations and quantitative structure-activity relationships modeling

NASA Astrophysics Data System (ADS)

Alloui, Mebarka; Belaidi, Salah; Othmani, Hasna; Jaidane, Nejm-Eddine; Hochlaf, Majdi

2018-03-01

We performed benchmark studies on the molecular geometry, electron properties and vibrational analysis of imidazole using semi-empirical, density functional theory and post Hartree-Fock methods. These studies validated the use of AM1 for the treatment of larger systems. Then, we treated the structural, physical and chemical relationships for a series of imidazole derivatives acting as angiotensin II AT1 receptor blockers using AM1. QSAR studies were done for these imidazole derivatives using a combination of various physicochemical descriptors. A multiple linear regression procedure was used to design the relationships between molecular descriptor and the activity of imidazole derivatives. Results validate the derived QSAR model.

Structure-activity correlations for organophosphorus ester anticholinesterases. Part 2: CNDO/2 calculations applied to ester hydrolysis rates

NASA Technical Reports Server (NTRS)

Johnson, H.; Kenley, R. A.; Rynard, C.; Golub, M. A.

1984-01-01

Quantitative structure-activity relationships are presented for the hydrolysis of organophosphorus esters, RR'P(O)X, where R and R' are alkyl and/or alkoxy groups and X is fluorine, chlorine or a phenoxy group. CNDO/2 calculations provide values for molecular parameters that correlate with alkaline hydrolysis rates. For each subset of esters with the same leaving group, X, the CNDO-derived net atomic charge at the central phosphorus atom correlates well with the alkaline hydrolysis rate constants. For the whole set of esters with different leaving groups, equations are derived that relate charge, orbital energy and bond order to the hydrolysis rate constants.

Stress-dependence of kinetic transitions at atomistic defects

NASA Astrophysics Data System (ADS)

Ball, S. L.; Alexander, K. C.; Schuh, C. A.

2018-01-01

The full second-rank activation volume tensors associated with vacancy migration in FCC copper and HCP titanium as well as transition events in the Σ5 (2 1 0) grain boundary in copper are calculated and analyzed. The full tensorial results quantitatively illustrate how the conventional use of an activation volume scalar in atomistic studies of the kinetic processes of complex defects can miss important stress dependencies, in that neither hydrostatic pressure nor deviatoric stress dependencies can be considered alone as dominating the response. The results speak to the importance of anisotropies in the stress-dependence of atomistic kinetics, including crystal structure anisotropy, elastic anisotropy, and defect structure or migration-path anisotropies.

Correlation between Hierarchical Structure and Processing Control of Large-area Spray-coated Polymer Solar Cells toward High Performance

PubMed Central

Huang, Yu-Ching; Tsao, Cheng-Si; Cha, Hou-Chin; Chuang, Chih-Min; Su, Chun-Jen; Jeng, U-Ser; Chen, Charn-Ying

2016-01-01

The formation mechanism of a spray-coated film is different from that of a spin-coated film. This study employs grazing incidence small- and wide-angle X-ray Scattering (GISAXS and GIWAXS, respectively) quantitatively and systematically to investigate the hierarchical structure and phase-separated behavior of a spray-deposited blend film. The formation of PCBM clusters involves mutual interactions with both the P3HT crystal domains and droplet boundary. The processing control and the formed hierarchical structure of the active layer in the spray-coated polymer/fullerene blend film are compared to those in the spin-coated film. How the different post-treatments, such as thermal and solvent vapor annealing, tailor the hierarchical structure of the spray-coated films is quantitatively studied. Finally, the relationship between the processing control and tailored BHJ structures and the performance of polymer solar cell devices is established here, taking into account the evolution of the device area from 1 × 0.3 and 1 × 1 cm2. The formation and control of the special networks formed by the PCBM cluster and P3HT crystallites, respectively, are related to the droplet boundary. These structures are favorable for the transverse transport of electrons and holes. PMID:26817585

Exploring glycogen biosynthesis through Monte Carlo simulation.

PubMed

Zhang, Peng; Nada, Sharif S; Tan, Xinle; Deng, Bin; Sullivan, Mitchell A; Gilbert, Robert G

2018-05-08

Glycogen, a complex branched polymer of glucose (average chain length ~10 monomer units), is the blood-sugar reservoir in humans and other animals. Certain aspects of its molecular structure relevant to its biological functions are currently unamenable to experimental exploration. Knowledge of these is needed to develop future models for quantitative data-fitting to obtain mechanistic understanding of the biosynthetic processes that give rise to glycogen structure. Monte Carlo simulations of the biosynthesis of this structure with realistic macromolecular parameters reveal how chain growth and stoppage (the latter assumed to be through both the action of glycogen branching enzyme and other degradative enzymes, and by hindrance) control structural features. The simulated chain-length, pair-distance and radial density distributions agree semi-quantitatively with the limited available data. The simulations indicate that a steady state in molecular structure and size is rapidly obtained, that molecular density reaches a maximum near the center of the particle (not at the periphery, as is the case with dendrimers), and that particle size is controlled by both enzyme activity and hindrance. This knowledge will aid in the understanding of diabetes (loss of blood-sugar control), which has been found to involve subtle differences in glycogen molecular structure. Copyright © 2018 Elsevier B.V. All rights reserved.

Reactivity of propene, n-butene, and isobutene in the hydrogen transfer steps of n-hexane cracking over zeolites of different structure

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

Lukyanov, D.B.

The reaction of n-hexane cracking over HZSM-5, HY zeolite and mordenite (HM) was studied in accordance with the procedure of the [beta]-test recently proposed for quantitative characterization of zeolite hydrogen transfer activity. It is shown that this procedure allows one to obtain quantitative data on propene, n-butene, and isobutene reactivities in the hydrogen transfer steps of the reaction. The results demonstrate that in the absence of steric constraints (large pore HY and HM zeolites) isobutene is approximately 5 times more reactive in hydrogen transfer than n-butene. The latter, in turn, is about 1.3 times more reactive than propene. With mediummore » pore HZSM-5, steric inhibition of the hydrogen transfer between n-hexane and isobutene is observed. This results in a sharp decrease in the isobutene reactivity: over HZSM-5 zeolites isobutene is only 1.2 times more reactive in hydrogen transfer than n-butene. On the basis of these data it is concluded that the [beta]-test measures the [open quotes]real[close quotes] hydrogen transfer activity of zeolites, i.e., the activity that summarizes the effects of the acidic and structural properties of zeolites. An attempt is made to estimate the [open quotes]ideal[close quotes] zeolite hydrogen transfer activity, i.e., the activity determined by the zeolite acidic properties only. The estimations obtained show that this activity is approximately 1.8 and 1.6 times higher for HM zeolite in comparison with HZSM-5 and HY zeolites, respectively. 16 refs., 4 figs., 2 tabs.« less

Quantitative Analysis of the Effective Functional Structure in Yeast Glycolysis

PubMed Central

De la Fuente, Ildefonso M.; Cortes, Jesus M.

2012-01-01

The understanding of the effective functionality that governs the enzymatic self-organized processes in cellular conditions is a crucial topic in the post-genomic era. In recent studies, Transfer Entropy has been proposed as a rigorous, robust and self-consistent method for the causal quantification of the functional information flow among nonlinear processes. Here, in order to quantify the functional connectivity for the glycolytic enzymes in dissipative conditions we have analyzed different catalytic patterns using the technique of Transfer Entropy. The data were obtained by means of a yeast glycolytic model formed by three delay differential equations where the enzymatic rate equations of the irreversible stages have been explicitly considered. These enzymatic activity functions were previously modeled and tested experimentally by other different groups. The results show the emergence of a new kind of dynamical functional structure, characterized by changing connectivity flows and a metabolic invariant that constrains the activity of the irreversible enzymes. In addition to the classical topological structure characterized by the specific location of enzymes, substrates, products and feedback-regulatory metabolites, an effective functional structure emerges in the modeled glycolytic system, which is dynamical and characterized by notable variations of the functional interactions. The dynamical structure also exhibits a metabolic invariant which constrains the functional attributes of the enzymes. Finally, in accordance with the classical biochemical studies, our numerical analysis reveals in a quantitative manner that the enzyme phosphofructokinase is the key-core of the metabolic system, behaving for all conditions as the main source of the effective causal flows in yeast glycolysis. PMID:22393350

Dragon boat racing and health-related quality of life of breast cancer survivors: a mixed methods evaluation.

PubMed

Ray, Heather A; Verhoef, Marja J

2013-08-05

Breast cancer survivors who participate in physical activity (PA) are reported to experience improved health-related quality of life (HRQOL). However, the quantitative research exploring the relationship between the team-based activity of dragon boat racing and the HRQOL of breast cancer survivors is limited. Given the rising number of breast cancer survivors, and their growing attraction to dragon boating, further exploration of the influence of this activity on HRQOL is warranted. This study is designed to: 1) quantitatively assess whether and how breast cancer survivors' participation in a season of dragon boat racing is related to HRQOL and 2) qualitatively explore the survivors' lived experience of dragon boating and how and why this experience is perceived to influence HRQOL. A mixed methods sequential explanatory design was used with the purpose of complementing quantitative findings with qualitative data. Quantitative data measuring HRQOL were collected at baseline and post-season (N=100); semi-structured qualitative interviews were used to elicit a personal account of the dragon boat experience (N=15). Statistically significant improvements were shown for HRQOL, physical, functional, emotional and spiritual well-being, breast cancer-specific concerns and cancer-related fatigue. A trend towards significance was shown for social/family well-being. Qualitative data elaborated on the quantitative findings, greatly enhancing the understanding of how and why dragon boat racing influences HRQOL. The use of a mixed methods design effectively captured the complex yet positive influence of dragon boating on survivor HRQOL. These findings contribute to a growing body of literature supporting the value of dragon boat racing as a viable PA intervention for enhancing survivor HRQOL.

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

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2012-12-01

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

Comparison of fate profiles of PAHs in soil, sediments and mangrove leaves after oil spills by QSAR and QSPR.

PubMed

Tansel, Berrin; Lee, Mengshan; Tansel, Derya Z

2013-08-15

First order removal rates for 15 polyaromatic hydrocarbons (PAHs) in soil, sediments and mangrove leaves were compared in relation to the parameters used in fate transport analyses (i.e., octanol-water partition coefficient, organic carbon-water partition coefficient, solubility, diffusivity in water, HOMO-LUMO gap, molecular size, molecular aspect ratio). The quantitative structure activity relationships (QSAR) and quantitative structure property relationships (QSPR) showed that the rate of disappearance of PAHs is correlated with their diffusivities in water as well as molecular volumes in different media. Strong correlations for the rate of disappearance of PAHs in sediments could not be obtained in relation to most of the parameters evaluated. The analyses showed that the QSAR and QSPR correlations developed for removal rates of PAHs in soils would not be adequate for sediments and plant tissues. Copyright © 2013 Elsevier Ltd. All rights reserved.

Quantitative structure-activity relationships for green algae growth inhibition by polymer particles.

PubMed

Nolte, Tom M; Peijnenburg, Willie J G M; Hendriks, A Jan; van de Meent, Dik

2017-07-01

After use and disposal of chemical products, many types of polymer particles end up in the aquatic environment with potential toxic effects to primary producers like green algae. In this study, we have developed Quantitative Structure-Activity Relationships (QSARs) for a set of highly structural diverse polymers which are capable to estimate green algae growth inhibition (EC50). The model (N = 43, R 2  = 0.73, RMSE = 0.28) is a regression-based decision tree using one structural descriptor for each of three polymer classes separated based on charge. The QSAR is applicable to linear homo polymers as well as copolymers and does not require information on the size of the polymer particle or underlying core material. Highly branched polymers, non-nitrogen cationic polymers and polymeric surfactants are not included in the model and thus cannot be evaluated. The model works best for cationic and non-ionic polymers for which cellular adsorption, disruption of the cell wall and photosynthesis inhibition were the mechanisms of action. For anionic polymers, specific properties of the polymer and test characteristics need to be known for detailed assessment. The data and QSAR results for anionic polymers, when combined with molecular dynamics simulations indicated that nutrient depletion is likely the dominant mode of toxicity. Nutrient depletion in turn, is determined by the non-linear interplay between polymer charge density and backbone flexibility. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantification is Neither Necessary Nor Sufficient for Measurement

NASA Astrophysics Data System (ADS)

Mari, Luca; Maul, Andrew; Torres Irribarra, David; Wilson, Mark

2013-09-01

Being an infrastructural, widespread activity, measurement is laden with stereotypes. Some of these concern the role of measurement in the relation between quality and quantity. In particular, it is sometimes argued or assumed that quantification is necessary for measurement; it is also sometimes argued or assumed that quantification is sufficient for or synonymous with measurement. To assess the validity of these positions the concepts of measurement and quantitative evaluation should be independently defined and their relationship analyzed. We contend that the defining characteristic of measurement should be the structure of the process, not a feature of its results. Under this perspective, quantitative evaluation is neither sufficient nor necessary for measurement.

Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

PubMed

Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

2018-05-02

Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI

PubMed Central

Chaudhary, Umair J.; Centeno, Maria; Thornton, Rachel C.; Rodionov, Roman; Vulliemoz, Serge; McEvoy, Andrew W.; Diehl, Beate; Walker, Matthew C.; Duncan, John S.; Carmichael, David W.; Lemieux, Louis

2016-01-01

Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as ‘ON’ blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum. PMID:27114897

Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI.

PubMed

Chaudhary, Umair J; Centeno, Maria; Thornton, Rachel C; Rodionov, Roman; Vulliemoz, Serge; McEvoy, Andrew W; Diehl, Beate; Walker, Matthew C; Duncan, John S; Carmichael, David W; Lemieux, Louis

2016-01-01

Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as 'ON' blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum.

Comparative pharmacodynamic analysis of imidazoline compounds using rat model of ocular mydriasis with a test of quantitative structure-activity relationships.

PubMed

Raczak-Gutknecht, Joanna; Nasal, Antoni; Frąckowiak, Teresa; Kornicka, Anita; Sączewski, Franciszek; Wawrzyniak, Renata; Kubik, Łukasz; Kaliszan, Roman

2017-09-10

Imidazol(in)e derivatives, having the chemical structure similar to clonidine, exert diverse pharmacological activities connected with their interactions with alpha2-adrenergic receptors, e.g. hypotension, bradycardia, sedation as well as antinociceptive, anxiolytic, antiarrhythmic, muscle relaxant and mydriatic effects. The mechanism of pupillary dilation observed after systemic administration of imidazol(in)es to rats, mice and cats depends on the stimulation of postsynaptic alpha2-adrenoceptors within the brain. It was proved that the central nervous system (CNS)-localized I1-imidazoline receptors are not engaged in those effects. It appeared interesting to analyze the CNS-mediated pharmacodynamics of imidazole(in)e agents in terms of their chromatographic and calculation chemistry-derived parameters. In the present study a systematic determination and comparative pharmacometric analysis of mydriatic effects in rats were performed on a series of 20 imidazol(in)e agents, composed of the well-known drugs and of the substances used in experimental pharmacology. The eye pupil dilatory activities of the compounds were assessed in anesthetized Wistar rats according to the established Koss method. Among twenty imidazol(in)e derivatives studied, 18 produced diverse dose-dependent mydriatic effects. In the quantitative structure-activity relationships (QSAR) analysis, the pharmacological data (half maximum mydriatic effect - ED 50 in μmol/kg) were considered along with the structural parameters of the agents from molecular modeling. The theoretically calculated lipophilicity parameters, CLOGP, of imidazol(in)es, as well as their lipophilicity parameters from HPLC, logk w , were also considered. The attempts to derive statistically significant QSAR equations for a full series of the agents under study were unsuccessful. However, for a subgroup of eight apparently structurally related imidazol(in)es a significant relationship between log(1/ED 50 ) and logk w values was obtained. The lack of "predictive" QSAR for the whole series of the structurally diverse agents is probably due to a complex mechanism of the ligand-alpha2-adrenergic receptor interactions, which are predominantly of a highly structurally specific polar nature. Such interactions are difficult to quantify with the established chemical structural descriptors, contrary to the less specific, molecular bulkiness-related interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

[Studies on the structure-activity relationship of retinoids--Hansch analysis and 3D-OSAR studies on specific ligands of retinoid x receptor].

PubMed

Huang, N; Chu, F; Guo, Z

1998-06-01

Retinoids (Vitamin A, its metabolites and synthetic analogues) play important roles in a variety of biological processes, including cellular differentiation, proliferation and apoptosis. The many diverse actions of retinoids attribute to the ability of regulating transcription of different target genes through activation of multiple retinoid nuclear receptors (RAR of RXR). So, retinoids with selective binding ability to specific receptor may not only have improved therapeutic indices, but may also be invaluable for elucidating the molecular mechanism of retinoidal transcriptional activation. Based on the two dimensional and three dimensional quantitative structure-activity relationships of specific ligands of RXR, we carried out mimesis of environment of ligands interacting with their receptor and, to some extent, mapping the topological and physico-chemical characteristics of receptor. The knowledge of the QSAR study will offer detailed molecular information for design, synthesis and biological evaluation in drug research and development.

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

A knowledge-guided active model method of cortical structure segmentation on pediatric MR images.

PubMed

Shan, Zuyao Y; Parra, Carlos; Ji, Qing; Jain, Jinesh; Reddick, Wilburn E

2006-10-01

To develop an automated method for quantification of cortical structures on pediatric MR images. A knowledge-guided active model (KAM) approach was proposed with a novel object function similar to the Gibbs free energy function. Triangular mesh models were transformed to images of a given subject by maximizing entropy, and then actively slithered to boundaries of structures by minimizing enthalpy. Volumetric results and image similarities of 10 different cortical structures segmented by KAM were compared with those traced manually. Furthermore, the segmentation performances of KAM and SPM2, (statistical parametric mapping, a MATLAB software package) were compared. The averaged volumetric agreements between KAM- and manually-defined structures (both 0.95 for structures in healthy children and children with medulloblastoma) were higher than the volumetric agreement for SPM2 (0.90 and 0.80, respectively). The similarity measurements (kappa) between KAM- and manually-defined structures (0.95 and 0.93, respectively) were higher than those for SPM2 (both 0.86). We have developed a novel automatic algorithm, KAM, for segmentation of cortical structures on MR images of pediatric patients. Our preliminary results indicated that when segmenting cortical structures, KAM was in better agreement with manually-delineated structures than SPM2. KAM can potentially be used to segment cortical structures for conformal radiation therapy planning and for quantitative evaluation of changes in disease or abnormality. Copyright (c) 2006 Wiley-Liss, Inc.

[Time-organization of EEG patterns' structure in anxiety and phobic disorders].

PubMed

Sviatogor, I A; Mokhovikova, I A

2005-01-01

Thirty-five patients, aged 19-48 years (mean age 38 years) with anxiety and phobic disorders were examined. According to ICD-10 criteria--social phobia (F40.1), panic disorder (F41.0), somatoform autonomic dysfunction (F45.3) were diagnosed. Using electroencephalography data, qualitative and quantitative characteristics of the time- and spatial-organization of brain EEG activity in anxiety and phobic disorders of different severity were established. It were determined 4 types of wave interactions between EEG components, which reflected a different extent of the regulatory mechanisms lesions: 2 structures with one core component (alpha or beta), a structure with two core components and a non-organized structure.

Quantitative structure-activity relationship studies of threo-methylphenidate analogs.

PubMed

Misra, Milind; Shi, Qing; Ye, Xiaocong; Gruszecka-Kowalik, Ewa; Bu, Wei; Liu, Zhanzhu; Schweri, Margaret M; Deutsch, Howard M; Venanzi, Carol A

2010-10-15

Complementary two-dimensional (2D) and three-dimensional (3D) Quantitative Structure-Activity Relationship (QSAR) techniques were used to derive a preliminary model for the dopamine transporter (DAT) binding affinity of 80 racemic threo-methylphenidate (MP) analogs. A novel approach based on using the atom-level E-state indices of the 14 common scaffold atoms in a sphere exclusion protocol was used to identify a test set for 2D- and 3D-QSAR model validation. Comparative Molecular Field Analysis (CoMFA) contour maps based on the structure-activity data of the training set indicate that the 2' position of the phenyl ring cannot tolerate much steric bulk and that addition of electron-withdrawing groups to the 3' or 4' positions of the phenyl ring leads to improved DAT binding affinity. In particular, the optimal substituents were found to be those whose bulk is mainly in the plane of the phenyl ring. Substituents with significant bulk above or below the plane of the ring led to decreased binding affinity. Suggested alterations to be explored in the design of new compounds are the placement at the 3' and 4' position of the phenyl ring of electron-withdrawing groups that lie chiefly in the plane of the ring, for example, halogen substituents on the 3',4'-benzo analog, 79. A complementary 2D-QSAR approach-partial least squares analysis using a reduced set of Molconn-Z descriptors-supports the CoMFA structure-activity interpretation that phenyl ring substitution is a major determinant of DAT binding affinity. The potential usefulness of the CoMFA models was demonstrated by the prediction of the binding affinity of methyl 2-(naphthalen-1-yl)-2-(piperidin-2-yl)acetate, an analog not in the original data set, to be in good agreement with the experimental value. Copyright © 2010 Elsevier Ltd. All rights reserved.

Production and characterization of a broad-specificity polyclonal antibody for O,O-diethyl organophosphorus pesticides and a quantitative structure-activity relationship study of antibody recognition

USDA-ARS?s Scientific Manuscript database

Polyclonal antibody (PAb) with broad-specificity for O,O-diethyl organophosphorus pesticides (OPs) against a generic hapten, 4-(diethoxyphosphoro thioyloxy) benzoic acid, was produced. The obtained PAb showed high sensitivity to seven commonly used O,O-diethyl OPs in a competitive indirect enzyme-l...

Bioelectrochemical Systems Workshop:Standardized Analyses, Design Benchmarks, and Reporting

DTIC Science & Technology

2012-01-01

related to the exoelectrogenic biofilm activity, and to investigate whether the community structure is a function of design and operational parameters...where should biofilm samples be collected? The most prevalent methods of community characterization in BES studies have entailed phylogenetic ...of function associated with this genetic marker, and in methods that involve polymerase chain reaction (PCR) amplification the quantitative

Quantitative structure-activity relationships of the antimalarial agent artemisinin and some of its derivatives - a DFT approach.

PubMed

Rajkhowa, Sanchaita; Hussain, Iftikar; Hazarika, Kalyan K; Sarmah, Pubalee; Deka, Ramesh Chandra

2013-09-01

Artemisinin form the most important class of antimalarial agents currently available, and is a unique sesquiterpene peroxide occurring as a constituent of Artemisia annua. Artemisinin is effectively used in the treatment of drug-resistant Plasmodium falciparum and because of its rapid clearance of cerebral malaria, many clinically useful semisynthetic drugs for severe and complicated malaria have been developed. However, one of the major disadvantages of using artemisinins is their poor solubility either in oil or water and therefore, in order to overcome this difficulty many derivatives of artemisinin were prepared. A comparative study on the chemical reactivity of artemisinin and some of its derivatives is performed using density functional theory (DFT) calculations. DFT based global and local reactivity descriptors, such as hardness, chemical potential, electrophilicity index, Fukui function, and local philicity calculated at the optimized geometries are used to investigate the usefulness of these descriptors for understanding the reactive nature and reactive sites of the molecules. Multiple regression analysis is applied to build up a quantitative structure-activity relationship (QSAR) model based on the DFT based descriptors against the chloroquine-resistant, mefloquine-sensitive Plasmodium falciparum W-2 clone.

Quantitative Phase Composition of TiO 2-Coated Nanoporous-Au Monoliths by X-ray Absorption Spectroscopy and Correlations to Catalytic

DOE PAGES

Bagge-Hansen, Michael; Wichmann, Andre; Wittstock, Arne; ...

2014-02-03

Porous titania/metal composite materials have many potential applications in the fields of green catalysis, energy harvesting, and storage in which both the overall morphology of the nanoporous host material and the crystallographic phase of the titania (TiO 2) guest determine the material’s performance. New insights into the structure–function relationships of these materials were obtained by near-edge X-ray absorption fine structure (NEXAFS) spectroscopy that, for example, provides quantitative crystallographic phase composition from ultrathin, nanostructured titania films, including sensitivity to amorphous components. We demonstrate that crystallographic phase, morphology, and catalytic activity of TiO 2-functionalized nanoporous gold (np-Au) can be controlled by amore » simple annealing procedure (T < 1300 K). The material was prepared by atomic layer deposition of ~2 nm thick TiO 2 on millimeter-sized samples of np-Au (40–50 nm mean ligament size) and catalytically investigated with respect to aerobic CO oxidation. Moreover, the annealing-induced changes in catalytic activity are correlated with concurrent morphology and phase changes as provided by cross-sectional scanning electron microscopy, transmission electron microscopy, and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy.« less

Designer drugs: the evolving science of drug discovery.

PubMed

Wanke, L A; DuBose, R F

1998-07-01

Drug discovery and design are fundamental to drug development. Until recently, most drugs were discovered through random screening or developed through molecular modification. New technologies are revolutionizing this phase of drug development. Rational drug design, using powerful computers and computational chemistry and employing X-ray crystallography, nuclear magnetic resonance spectroscopy, and three-dimensional quantitative structure activity relationship analysis, is creating highly specific, biologically active molecules by virtual reality modeling. Sophisticated screening technologies are eliminating all but the most active lead compounds. These new technologies promise more efficacious, safe, and cost-effective medications, while minimizing drug development time and maximizing profits.

Accurate Assessment of the Oxygen Reduction Electrocatalytic Activity of Mn/Polypyrrole Nanocomposites Based on Rotating Disk Electrode Measurements, Complemented with Multitechnique Structural Characterizations

PubMed Central

Sánchez, Carolina Ramírez; Taurino, Antonietta; Bozzini, Benedetto

2016-01-01

This paper reports on the quantitative assessment of the oxygen reduction reaction (ORR) electrocatalytic activity of electrodeposited Mn/polypyrrole (PPy) nanocomposites for alkaline aqueous solutions, based on the Rotating Disk Electrode (RDE) method and accompanied by structural characterizations relevant to the establishment of structure-function relationships. The characterization of Mn/PPy films is addressed to the following: (i) morphology, as assessed by Field-Emission Scanning Electron Microscopy (FE-SEM) and Atomic Force Microscope (AFM); (ii) local electrical conductivity, as measured by Scanning Probe Microscopy (SPM); and (iii) molecular structure, accessed by Raman Spectroscopy; these data provide the background against which the electrocatalytic activity can be rationalised. For comparison, the properties of Mn/PPy are gauged against those of graphite, PPy, and polycrystalline-Pt (poly-Pt). Due to the literature lack of accepted protocols for precise catalytic activity measurement at poly-Pt electrode in alkaline solution using the RDE methodology, we have also worked on the obtainment of an intralaboratory benchmark by evidencing some of the time-consuming parameters which drastically affect the reliability and repeatability of the measurement. PMID:28042491

Structure–activity relationships study of mTOR kinase inhibition using QSAR and structure-based drug design approaches

PubMed Central

Lakhlili, Wiame; Yasri, Abdelaziz; Ibrahimi, Azeddine

2016-01-01

The discovery of clinically relevant inhibitors of mammalian target of rapamycin (mTOR) for anticancer therapy has proved to be a challenging task. The quantitative structure–activity relationship (QSAR) approach is a very useful and widespread technique for ligand-based drug design, which can be used to identify novel and potent mTOR inhibitors. In this study, we performed two-dimensional QSAR tests, and molecular docking validation tests of a series of mTOR ATP-competitive inhibitors to elucidate their structural properties associated with their activity. The QSAR tests were performed using partial least square method with a correlation coefficient of r2=0.799 and a cross-validation of q2=0.714. The chemical library screening was done by associating ligand-based to structure-based approach using the three-dimensional structure of mTOR developed by homology modeling. We were able to select 22 compounds from two databases as inhibitors of the mTOR kinase active site. We believe that the method and applications highlighted in this study will help future efforts toward the design of selective ATP-competitive inhibitors. PMID:27980424

A mechanism-mediated model for carcinogenicity: Model content and prediction of the outcome of rodent carcinogenicity bioassays currently being conducted on 25 organic chemicals

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

Purdy, R.

A hierarchical model consisting of quantitative structure-activity relationships based mainly on chemical reactivity was developed to predict the carcinogenicity of organic chemicals to rodents. The model is comprised of quantitative structure-activity relationships, QSARs based on hypothesized mechanisms of action, metabolism, and partitioning. Predictors included octanol/water partition coefficient, molecular size, atomic partial charge, bond angle strain, atomic acceptor delocalizibility, atomic radical superdelocalizibility, the lowest unoccupied molecular orbital (LUMO) energy of hypothesized intermediate nitrenium ion of primary aromatic amines, difference in charge of ionized and unionized carbon-chlorine bonds, substituent size and pattern on polynuclear aromatic hydrocarbons, the distance between lone electron pairsmore » over a rigid structure, and the presence of functionalities such as nitroso and hydrazine. The model correctly classified 96% of the carcinogens in the training set of 306 chemicals, and 90% of the carcinogens in the test set of 301 chemicals. The test set by chance contained 84% of the positive thiocontaining chemicals. A QSAR for these chemicals was developed. This posttest set modified model correctly predicted 94% of the carcinogens in the test set. This model was used to predict the carcinogenicity of the 25 organic chemicals the U.S. National Toxicology Program was testing at the writing of this article. 12 refs., 3 tabs.« less

Kinetics of nif Gene Expression in a Nitrogen-Fixing Bacterium

PubMed Central

Poza-Carrión, César; Jiménez-Vicente, Emilio; Navarro-Rodríguez, Mónica; Echavarri-Erasun, Carlos

2014-01-01

Nitrogen fixation is a tightly regulated trait. Switching from N2 fixation-repressing conditions to the N2-fixing state is carefully controlled in diazotrophic bacteria mainly because of the high energy demand that it imposes. By using quantitative real-time PCR and quantitative immunoblotting, we show here how nitrogen fixation (nif) gene expression develops in Azotobacter vinelandii upon derepression. Transient expression of the transcriptional activator-encoding gene, nifA, was followed by subsequent, longer-duration waves of expression of the nitrogenase biosynthetic and structural genes. Importantly, expression timing, expression levels, and NifA dependence varied greatly among the nif operons. Moreover, the exact concentrations of Nif proteins and their changes over time were determined for the first time. Nif protein concentrations were exquisitely balanced, with FeMo cofactor biosynthetic proteins accumulating at levels 50- to 100-fold lower than those of the structural proteins. Mutants lacking nitrogenase structural genes or impaired in FeMo cofactor biosynthesis showed overenhanced responses to derepression that were proportional to the degree of nitrogenase activity impairment, consistent with the existence of at least two negative-feedback regulatory mechanisms. The first such mechanism responded to the levels of fixed nitrogen, whereas the second mechanism appeared to respond to the levels of the mature NifDK component. Altogether, these findings provide a framework to engineer N2 fixation in nondiazotrophs. PMID:24244007

Kinetics of Nif gene expression in a nitrogen-fixing bacterium.

PubMed

Poza-Carrión, César; Jiménez-Vicente, Emilio; Navarro-Rodríguez, Mónica; Echavarri-Erasun, Carlos; Rubio, Luis M

2014-02-01

Nitrogen fixation is a tightly regulated trait. Switching from N2 fixation-repressing conditions to the N2-fixing state is carefully controlled in diazotrophic bacteria mainly because of the high energy demand that it imposes. By using quantitative real-time PCR and quantitative immunoblotting, we show here how nitrogen fixation (nif) gene expression develops in Azotobacter vinelandii upon derepression. Transient expression of the transcriptional activator-encoding gene, nifA, was followed by subsequent, longer-duration waves of expression of the nitrogenase biosynthetic and structural genes. Importantly, expression timing, expression levels, and NifA dependence varied greatly among the nif operons. Moreover, the exact concentrations of Nif proteins and their changes over time were determined for the first time. Nif protein concentrations were exquisitely balanced, with FeMo cofactor biosynthetic proteins accumulating at levels 50- to 100-fold lower than those of the structural proteins. Mutants lacking nitrogenase structural genes or impaired in FeMo cofactor biosynthesis showed overenhanced responses to derepression that were proportional to the degree of nitrogenase activity impairment, consistent with the existence of at least two negative-feedback regulatory mechanisms. The first such mechanism responded to the levels of fixed nitrogen, whereas the second mechanism appeared to respond to the levels of the mature NifDK component. Altogether, these findings provide a framework to engineer N2 fixation in nondiazotrophs.

The Effect of Concept Mapping on Student Understanding and Correlation with Student Learning Styles

NASA Astrophysics Data System (ADS)

Mosley, William G.

This study investigated the use of concept mapping as a pedagogical strategy to promote change in the learning styles of pre-nursing students. Students' individual learning styles revealed two subsets of students; those who demonstrated a learning style that favors abstract conceptualization and those who demonstrated a learning style that favors concrete experience. Students in the experimental groups performed concept mapping activities designed to facilitate an integrative understanding of interactions between various organ systems of the body while the control group received a traditional didactic instruction without performing concept mapping activities. Both qualitative and quantitative data were collected in order to measure differences in student achievement. Analysis of the quantitative data revealed no significant change in the learning styles of students in either the control or experimental groups. Learning style groups were analyzed qualitatively for recurring or emergent themes that students identified as facilitating their learning. An analysis of qualitative data revealed that most students in the pre-nursing program were able to identify concepts within the class based upon visual cues, and a majority of these students exhibited the learning style of abstract conceptualization. As the laboratory experience for the course involves an examination of the anatomical structures of the human body, a visual identification of these structures seemed to be the most logical method to measure students' ability to identify anatomical structures.

Quantitative Structure--Activity Relationship (QSAR) for the Oxidation of Trace Organic Contaminants by Sulfate Radical.

PubMed

Xiao, Ruiyang; Ye, Tiantian; Wei, Zongsu; Luo, Shuang; Yang, Zhihui; Spinney, Richard

2015-11-17

The sulfate radical anion (SO4•–) based oxidation of trace organic contaminants (TrOCs) has recently received great attention due to its high reactivity and low selectivity. In this study, a meta-analysis was conducted to better understand the role of functional groups on the reactivity between SO4•– and TrOCs. The results indicate that compounds in which electron transfer and addition channels dominate tend to exhibit a faster second-order rate constants (kSO4•–) than that of H–atom abstraction, corroborating the SO4•– reactivity and mechanisms observed in the individual studies. Then, a quantitative structure activity relationship (QSAR) model was developed using a sequential approach with constitutional, geometrical, electrostatic, and quantum chemical descriptors. Two descriptors, ELUMO and EHOMO energy gap (ELUMO–EHOMO) and the ratio of oxygen atoms to carbon atoms (#O:C), were found to mechanistically and statistically affect kSO4•– to a great extent with the standardized QSAR model: ln kSO4•– = 26.8–3.97 × #O:C – 0.746 × (ELUMO–EHOMO). In addition, the correlation analysis indicates that there is no dominant reaction channel for SO4•– reactions with various structurally diverse compounds. Our QSAR model provides a robust predictive tool for estimating emerging micropollutants removal using SO4•– during wastewater treatment processes.

Chemical function based pharmacophore generation of endothelin-A selective receptor antagonists.

PubMed

Funk, Oliver F; Kettmann, Viktor; Drimal, Jan; Langer, Thierry

2004-05-20

Both quantitative and qualitative chemical function based pharmacophore models of endothelin-A (ET(A)) selective receptor antagonists were generated by using the two algorithms HypoGen and HipHop, respectively, which are implemented in the Catalyst molecular modeling software. The input for HypoGen is a training set of 18 ET(A) antagonists exhibiting IC(50) values ranging between 0.19 nM and 67 microM. The best output hypothesis consists of five features: two hydrophobic (HY), one ring aromatic (RA), one hydrogen bond acceptor (HBA), and one negative ionizable (NI) function. The highest scoring Hip Hop model consists of six features: three hydrophobic (HY), one ring aromatic (RA), one hydrogen bond acceptor (HBA), and one negative ionizable (NI). It is the result of an input of three highly active, selective, and structurally diverse ET(A) antagonists. The predictive power of the quantitative model could be approved by using a test set of 30 compounds, whose activity values spread over 6 orders of magnitude. The two pharmacophores were tested according to their ability to extract known endothelin antagonists from the 3D molecular structure database of Derwent's World Drug Index. Thereby the main part of selective ET(A) antagonistic entries was detected by the two hypotheses. Furthermore, the pharmacophores were used to screen the Maybridge database. Six compounds were chosen from the output hit lists for in vitro testing of their ability to displace endothelin-1 from its receptor. Two of these are new potential lead compounds because they are structurally novel and exhibit satisfactory activity in the binding assay.

Quantitation of Permethylated N-Glycans through Multiple-Reaction Monitoring (MRM) LC-MS/MS

PubMed Central

Zhou, Shiyue; Hu, Yunli; DeSantos-Garcia, Janie L.; Mechref, Yehia

2015-01-01

The important biological roles of glycans and their implications in disease development and progression have created a demand for the development of sensitive quantitative glycomics methods. Quantitation of glycans existing at low abundance is still analytically challenging. In this study, an N-linked glycans quantitation method using multiple reaction monitoring (MRM) on a triple quadrupole instrument was developed. Optimum normalized collision energy (CE) for both sialylated and fucosylated N-glycan structures was determined to be 30% while it was found to be 35% for either fucosylated or sialylated structures The optimum CE for mannose and complex type N-glycan structures was determined to be 35%. Additionally, the use of three transitions was shown to facilitate reliable quantitation. A total of 88 N-glycan structures in human blood serum were quantified using this MRM approach. Reliable detection and quantitation of these structures was achieved when the equivalence of 0.005 μL of blood serum was analyzed. Accordingly, N-glycans down to the 100th of a μL level can be reliably quantified in pooled human blood serum, spanning a dynamic concentration range of three orders of magnitudes. MRM was also effectively utilized to quantitatively compare the expression of N-glycans derived from brain-targeting breast carcinoma cells (MDA-MB-231BR) and metastatic breast cancer cells (MDA-MB-231). Thus, the described MRM method of permethylated N-glycan structures enables a rapid and reliable identification and quantitation of glycans derived from glycoproteins purified or present in complex biological samples. PMID:25698222

Optimal descriptor as a translator of eclectic information into the prediction of membrane damage by means of various TiO(2) nanoparticles.

PubMed

Toropova, Alla P; Toropov, Andrey A

2013-11-01

The increasing use of nanomaterials incorporated into consumer products leads to the need for developing approaches to establish "quantitative structure-activity relationships" (QSARs) for various nanomaterials. However, the molecular structure as rule is not available for nanomaterials at least in its classic meaning. An possible alternative of classic QSAR (based on the molecular structure) is the using of data on physicochemical features of TiO(2) nanoparticles. The damage to cellular membranes (units L(-1)) by means of various TiO(2) nanoparticles is examined as the endpoint. Copyright © 2013 Elsevier Ltd. All rights reserved.

Aromatase inhibitory activity of 1,4-naphthoquinone derivatives and QSAR study

PubMed Central

Prachayasittikul, Veda; Pingaew, Ratchanok; Worachartcheewan, Apilak; Sitthimonchai, Somkid; Nantasenamat, Chanin; Prachayasittikul, Supaluk; Ruchirawat, Somsak; Prachayasittikul, Virapong

2017-01-01

A series of 2-amino(chloro)-3-chloro-1,4-naphthoquinone derivatives (1-11) were investigated for their aromatase inhibitory activities. 1,4-Naphthoquinones 1 and 4 were found to be the most potent compounds affording IC50 values 5.2 times lower than the reference drug, ketoconazole. A quantitative structure-activity relationship (QSAR) model provided good predictive performance (R2CV = 0.9783 and RMSECV = 0.0748) and indicated mass (Mor04m and H8m), electronegativity (Mor08e), van der Waals volume (G1v) and structural information content index (SIC2) descriptors as key descriptors governing the activity. To investigate the effects of structural modifications on aromatase inhibitory activity, the model was employed to predict the activities of an additional set of 39 structurally modified compounds constructed in silico. The prediction suggested that the 2,3-disubstitution of 1,4-naphthoquinone ring with halogen atoms (i.e., Br, I and F) is the most effective modification for potent activity (1a, 1b and 1c). Importantly, compound 1b was predicted to be more potent than its parent compound 1 (11.90-fold) and the reference drug, letrozole (1.03-fold). The study suggests the 1,4-naphthoquinone derivatives as promising compounds to be further developed as a novel class of aromatase inhibitors. PMID:28827987

Quantitative magneto-optical analysis of the role of finite temperatures on the critical state in YBCO thin films

NASA Astrophysics Data System (ADS)

Albrecht, Joachim; Brück, Sebastian; Stahl, Claudia; Ruoß, Stephen

2016-11-01

We use quantitative magneto-optical microscopy to investigate the influence of finite temperatures on the critical state of thin YBCO films. In particular, temperature and time dependence of supercurrents in inhomogeneous and anisotropic films are analyzed to extract the role of temperature on the supercurrents themselves and the influence of thermally activated relaxation. We find that inhomogeneities and anisotropies of the current density distribution correspond to a different temperature dependence of local supercurrents. In addition, the thermally activated decay of supercurrents can be used to extract local vortex pinning energies. With these results the modification of vortex pinning introduced by substrate structures is studied. In summary the local investigation of supercurrent densities allows the full description of the vortex pinning landscape with respect to pinning forces and energies in superconducting films with complex properties under the influence of finite temperatures.

Quantitative super-resolution imaging of Bruchpilot distinguishes active zone states

NASA Astrophysics Data System (ADS)

Ehmann, Nadine; van de Linde, Sebastian; Alon, Amit; Ljaschenko, Dmitrij; Keung, Xi Zhen; Holm, Thorge; Rings, Annika; Diantonio, Aaron; Hallermann, Stefan; Ashery, Uri; Heckmann, Manfred; Sauer, Markus; Kittel, Robert J.

2014-08-01

The precise molecular architecture of synaptic active zones (AZs) gives rise to different structural and functional AZ states that fundamentally shape chemical neurotransmission. However, elucidating the nanoscopic protein arrangement at AZs is impeded by the diffraction-limited resolution of conventional light microscopy. Here we introduce new approaches to quantify endogenous protein organization at single-molecule resolution in situ with super-resolution imaging by direct stochastic optical reconstruction microscopy (dSTORM). Focusing on the Drosophila neuromuscular junction (NMJ), we find that the AZ cytomatrix (CAZ) is composed of units containing ~137 Bruchpilot (Brp) proteins, three quarters of which are organized into about 15 heptameric clusters. We test for a quantitative relationship between CAZ ultrastructure and neurotransmitter release properties by engaging Drosophila mutants and electrophysiology. Our results indicate that the precise nanoscopic organization of Brp distinguishes different physiological AZ states and link functional diversification to a heretofore unrecognized neuronal gradient of the CAZ ultrastructure.

An improved 96-well turbidity assay for T4 lysozyme activity.

PubMed

Toro, Tasha B; Nguyen, Thao P; Watt, Terry J

2015-01-01

T4 lysozyme (T4L) is an important model system for investigating the relationship between protein structure and function. Despite being extensively studied, a reliable, quantitative activity assay for T4L has not been developed. Here, we present an improved T4L turbidity assay as well as an affinity-based T4L expression and purification protocol. This assay is designed for 96-well format and utilizes conditions amenable for both T4L and other lysozymes. This protocol enables easy, efficient, and quantitative characterization of T4L variants and allows comparison between different lysozymes. Our method: •Is applicable for all lysozymes, with enhanced sensitivity for T4 lysozyme compared to other 96-well plate turbidity assays;•Utilizes standardized conditions for comparing T4 lysozyme variants and other lysozymes; and•Incorporates a simplified expression and purification protocol for T4 lysozyme.

An improved 96-well turbidity assay for T4 lysozyme activity

PubMed Central

Toro, Tasha B.; Nguyen, Thao P.; Watt, Terry J.

2015-01-01

T4 lysozyme (T4L) is an important model system for investigating the relationship between protein structure and function. Despite being extensively studied, a reliable, quantitative activity assay for T4L has not been developed. Here, we present an improved T4L turbidity assay as well as an affinity-based T4L expression and purification protocol. This assay is designed for 96-well format and utilizes conditions amenable for both T4L and other lysozymes. This protocol enables easy, efficient, and quantitative characterization of T4L variants and allows comparison between different lysozymes. Our method: • Is applicable for all lysozymes, with enhanced sensitivity for T4 lysozyme compared to other 96-well plate turbidity assays; • Utilizes standardized conditions for comparing T4 lysozyme variants and other lysozymes; and • Incorporates a simplified expression and purification protocol for T4 lysozyme. PMID:26150996

Multi-object segmentation framework using deformable models for medical imaging analysis.

PubMed

Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

2016-08-01

Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed framework has a wide range of applications especially in the presence of adjacent structures of interest or under intra-structure inhomogeneities giving excellent quantitative results.

Automated Inference of Chemical Discriminants of Biological Activity.

PubMed

Raschka, Sebastian; Scott, Anne M; Huertas, Mar; Li, Weiming; Kuhn, Leslie A

2018-01-01

Ligand-based virtual screening has become a standard technique for the efficient discovery of bioactive small molecules. Following assays to determine the activity of compounds selected by virtual screening, or other approaches in which dozens to thousands of molecules have been tested, machine learning techniques make it straightforward to discover the patterns of chemical groups that correlate with the desired biological activity. Defining the chemical features that generate activity can be used to guide the selection of molecules for subsequent rounds of screening and assaying, as well as help design new, more active molecules for organic synthesis.The quantitative structure-activity relationship machine learning protocols we describe here, using decision trees, random forests, and sequential feature selection, take as input the chemical structure of a single, known active small molecule (e.g., an inhibitor, agonist, or substrate) for comparison with the structure of each tested molecule. Knowledge of the atomic structure of the protein target and its interactions with the active compound are not required. These protocols can be modified and applied to any data set that consists of a series of measured structural, chemical, or other features for each tested molecule, along with the experimentally measured value of the response variable you would like to predict or optimize for your project, for instance, inhibitory activity in a biological assay or ΔG binding . To illustrate the use of different machine learning algorithms, we step through the analysis of a dataset of inhibitor candidates from virtual screening that were tested recently for their ability to inhibit GPCR-mediated signaling in a vertebrate.

The influence of HOPE VI neighborhood revitalization on neighborhood-based physical activity: A mixed-methods approach.

PubMed

Dulin-Keita, Akilah; Clay, Olivio; Whittaker, Shannon; Hannon, Lonnie; Adams, Ingrid K; Rogers, Michelle; Gans, Kim

2015-08-01

This study uses a mixed methods approach to 1) identify surrounding residents' perceived expectations for Housing Opportunities for People Everywhere (HOPE VI) policy on physical activity outcomes and to 2) quantitatively examine the odds of neighborhood-based physical activity pre-/post-HOPE VI in a low socioeconomic status, predominantly African American community in Birmingham, Alabama. To address aim one, we used group concept mapping which is a structured approach for data collection and analyses that produces pictures/maps of ideas. Fifty-eight residents developed statements about potential influences of HOPE VI on neighborhood-based physical activity. In the quantitative study, we examined whether these potential influences increased the odds of neighborhood walking/jogging. We computed block entry logistic regression models with a larger cohort of residents at baseline (n = 184) and six-months (n = 142, 77% retention; n = 120 for all informative variables). We examined perceived neighborhood disorder (perceived neighborhood disorder scale), walkability and aesthetics (Neighborhood Environment Walkability Scale) and HOPE VI-related community safety and safety for physical activity as predictors. During concept mapping, residents generated statements that clustered into three distinct concepts, "Increased Leisure Physical Activity," "Safe Play Areas," and "Generating Health Promoting Resources." The quantitative analyses indicated that changes in neighborhood walkability increased the odds of neighborhood-based physical activity (p = 0.04). When HOPE VI-related safety for physical activity was entered into the model, it was associated with increased odds of physical activity (p = 0.04). Walkability was no longer statistically significant. These results suggest that housing policies that create walkable neighborhoods and that improve perceptions of safety for physical activity may increase neighborhood-based physical activity. However, the longer term impacts of neighborhood-level policies on physical activity require more longitudinal evidence to determine whether increased participation in physical activity is sustained. Copyright © 2015 Elsevier Ltd. All rights reserved.

Aortic root segmentation in 4D transesophageal echocardiography

NASA Astrophysics Data System (ADS)

Chechani, Shubham; Suresh, Rahul; Patwardhan, Kedar A.

2018-02-01

The Aortic Valve (AV) is an important anatomical structure which lies on the left side of the human heart. The AV regulates the flow of oxygenated blood from the Left Ventricle (LV) to the rest of the body through aorta. Pathologies associated with the AV manifest themselves in structural and functional abnormalities of the valve. Clinical management of pathologies often requires repair, reconstruction or even replacement of the valve through surgical intervention. Assessment of these pathologies as well as determination of specific intervention procedure requires quantitative evaluation of the valvular anatomy. 4D (3D + t) Transesophageal Echocardiography (TEE) is a widely used imaging technique that clinicians use for quantitative assessment of cardiac structures. However, manual quantification of 3D structures is complex, time consuming and suffers from inter-observer variability. Towards this goal, we present a semiautomated approach for segmentation of the aortic root (AR) structure. Our approach requires user-initialized landmarks in two reference frames to provide AR segmentation for full cardiac cycle. We use `coarse-to-fine' B-spline Explicit Active Surface (BEAS) for AR segmentation and Masked Normalized Cross Correlation (NCC) method for AR tracking. Our method results in approximately 0.51 mm average localization error in comparison with ground truth annotation performed by clinical experts on 10 real patient cases (139 3D volumes).

Structural Basis for Certain Naturally Occurring Bioflavonoids to Function as Reducing Co-Substrates of Cyclooxygenase I and II

PubMed Central

Zhu, Bao Ting

2010-01-01

Background Recent studies showed that some of the dietary bioflavonoids can strongly stimulate the catalytic activity of cyclooxygenase (COX) I and II in vitro and in vivo, presumably by facilitating enzyme re-activation. In this study, we sought to understand the structural basis of COX activation by these dietary compounds. Methodology/Principal Findings A combination of molecular modeling studies, biochemical analysis and site-directed mutagenesis assay was used as research tools. Three-dimensional quantitative structure-activity relationship analysis (QSAR/CoMFA) predicted that the ability of bioflavonoids to activate COX I and II depends heavily on their B-ring structure, a moiety known to be associated with strong antioxidant ability. Using the homology modeling and docking approaches, we identified the peroxidase active site of COX I and II as the binding site for bioflavonoids. Upon binding to this site, bioflavonoid can directly interact with hematin of the COX enzyme and facilitate the electron transfer from bioflavonoid to hematin. The docking results were verified by biochemical analysis, which reveals that when the cyclooxygenase activity of COXs is inhibited by covalent modification, myricetin can still stimulate the conversion of PGG2 to PGE2, a reaction selectively catalyzed by the peroxidase activity. Using the site-directed mutagenesis analysis, we confirmed that Q189 at the peroxidase site of COX II is essential for bioflavonoids to bind and re-activate its catalytic activity. Conclusions/Significance These findings provide the structural basis for bioflavonoids to function as high-affinity reducing co-substrates of COXs through binding to the peroxidase active site, facilitating electron transfer and enzyme re-activation. PMID:20808785

The effect of hydrodynamic conditions on the phenotype of Pseudomonas fluorescens biofilms.

PubMed

Simões, Manuel; Pereira, Maria O; Sillankorva, Sanna; Azeredo, Joana; Vieira, Maria J

2007-01-01

This study investigated the phenotypic characteristics of monoculture P. fluorescens biofilms grown under turbulent and laminar flow, using flow cells reactors with stainless steel substrata. The cellular physiology and the overall biofilm activity, structure and composition were characterized, and compared, within hydrodynamically distinct conditions. The results indicate that turbulent flow-generated biofilm cells were significantly less extensive, with decreased metabolic activity and a lower protein and polysaccharides composition per cell than those from laminar flow-generated biofilms. The effect of flow regime did not cause significantly different outer membrane protein expression. From the analysis of biofilm activity, structure and composition, turbulent flow-generated biofilms were metabolically more active, had twice more mass per cm(2), and higher cellular density and protein content (mainly cellular) than laminar flow-generated biofilms. Conversely, laminar flow-generated biofilms presented higher total and matrix polysaccharide contents. Direct visualisation and scanning electron microscopy analysis showed that these different flows generate structurally different biofilms, corroborating the quantitative results. The combination of applied methods provided useful information regarding a broad spectrum of biofilm parameters, which can contribute to control and model biofilm processes.

The Effects of Structured Physical Activity Program on Social Interaction and Communication for Children with Autism.

PubMed

Zhao, Mengxian; Chen, Shihui

2018-01-01

The purpose of this study was to investigate the effects of structured physical activity program on social interaction and communication of children with autism spectrum disorder (ASD). Fifty children with ASD from a special school were randomly divided into experimental and control groups. 25 children with ASD were placed in the experimental group, and the other 25 children as the control group participated in regular physical activity. A total of forty-one participants completed the study. A 12-week structured physical activity program was implemented with a total of 24 exercise sessions targeting social interaction and communication of children with ASD, and a quasi-experimental design was used for this study. Data were collected using quantitative and qualitative instruments. SSIS and ABLLS-R results showed that an overall improvement in social skills and social interaction for the experimental group across interim and posttests, F = 8.425, p = 0.001 ( p < 0.005), and significant improvements appeared in communication, cooperation, social interaction, and self-control subdomains ( p < 0.005). Conversely, no statistically significant differences were found in the control group ( p > 0.005). The study concluded that the special structured physical activity program positively influenced social interaction and communication skills of children with ASD, especially in social skills, communication, prompt response, and frequency of expression.

TIPdb: a database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan.

PubMed

Lin, Ying-Chi; Wang, Chia-Chi; Chen, Ih-Sheng; Jheng, Jhao-Liang; Li, Jih-Heng; Tung, Chun-Wei

2013-01-01

The unique geographic features of Taiwan are attributed to the rich indigenous and endemic plant species in Taiwan. These plants serve as resourceful bank for biologically active phytochemicals. Given that these plant-derived chemicals are prototypes of potential drugs for diseases, databases connecting the chemical structures and pharmacological activities may facilitate drug development. To enhance the utility of the data, it is desirable to develop a database of chemical compounds and corresponding activities from indigenous plants in Taiwan. A database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan was constructed. The database, TIPdb, is composed of a standardized format of published anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan. A browse function was implemented for users to browse the database in a taxonomy-based manner. Search functions can be utilized to filter records of interest by botanical name, part, chemical class, or compound name. The structured and searchable database TIPdb was constructed to serve as a comprehensive and standardized resource for anticancer, antiplatelet, and antituberculosis compounds search. The manually curated chemical structures and activities provide a great opportunity to develop quantitative structure-activity relationship models for the high-throughput screening of potential anticancer, antiplatelet, and antituberculosis drugs.

TIPdb: A Database of Anticancer, Antiplatelet, and Antituberculosis Phytochemicals from Indigenous Plants in Taiwan

PubMed Central

Lin, Ying-Chi; Wang, Chia-Chi; Chen, Ih-Sheng; Jheng, Jhao-Liang; Li, Jih-Heng; Tung, Chun-Wei

2013-01-01

The unique geographic features of Taiwan are attributed to the rich indigenous and endemic plant species in Taiwan. These plants serve as resourceful bank for biologically active phytochemicals. Given that these plant-derived chemicals are prototypes of potential drugs for diseases, databases connecting the chemical structures and pharmacological activities may facilitate drug development. To enhance the utility of the data, it is desirable to develop a database of chemical compounds and corresponding activities from indigenous plants in Taiwan. A database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan was constructed. The database, TIPdb, is composed of a standardized format of published anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan. A browse function was implemented for users to browse the database in a taxonomy-based manner. Search functions can be utilized to filter records of interest by botanical name, part, chemical class, or compound name. The structured and searchable database TIPdb was constructed to serve as a comprehensive and standardized resource for anticancer, antiplatelet, and antituberculosis compounds search. The manually curated chemical structures and activities provide a great opportunity to develop quantitative structure-activity relationship models for the high-throughput screening of potential anticancer, antiplatelet, and antituberculosis drugs. PMID:23766708

Synthesis, Antifungal Evaluation and In Silico Study of N-(4-Halobenzyl)amides.

PubMed

Montes, Ricardo Carneiro; Perez, Ana Luiza A L; Medeiros, Cássio Ilan S; Araújo, Marianna Oliveira de; Lima, Edeltrudes de Oliveira; Scotti, Marcus Tullius; Sousa, Damião Pergentino de

2016-12-13

A collection of 32 structurally related N -(4-halobenzyl)amides were synthesized from cinnamic and benzoic acids through coupling reactions with 4-halobenzylamines, using (benzotriazol-1-yloxy)tris(dimethylamino)phosphonium hexafluorophosphate (BOP) as a coupling agent. The compounds were identified by spectroscopic methods such as infrared, ¹H- and 13 C- Nuclear Magnetic Resonance (NMR) and high-resolution mass spectrometry. The compounds were then submitted to antimicrobial tests by the minimum inhibitory concentration method (MIC) and nystatin was used as a control in the antifungal assays. The purpose of the tests was to evaluate the influence of structural changes in the cinnamic and benzoic acid substructures on the inhibitory activity against strains of Candida albicans , Candida tropicalis , and Candida krusei . A quantitative structure-activity relationship (QSAR) study with KNIME v. 3.1.0 and Volsurf v. 1.0.7 softwares were realized, showing that descriptors DRDRDR, DRDRAC, L4LgS, IW4 and DD2 influence the antifungal activity of the haloamides. In general, 10 benzamides revealed fungal sensitivity, especially a vanillic amide which enjoyed the lowest MIC. The results demonstrate that a hydroxyl group in the para position, and a methoxyl at the meta position enhance antifungal activity for the amide skeletal structure. In addition, the double bond as a spacer group appears to be important for the activity of amide structures.

Alert-QSAR. Implications for Electrophilic Theory of Chemical Carcinogenesis

PubMed Central

Putz, Mihai V.; Ionaşcu, Cosmin; Putz, Ana-Maria; Ostafe, Vasile

2011-01-01

Given the modeling and predictive abilities of quantitative structure activity relationships (QSARs) for genotoxic carcinogens or mutagens that directly affect DNA, the present research investigates structural alert (SA) intermediate-predicted correlations ASA of electrophilic molecular structures with observed carcinogenic potencies in rats (observed activity, A = Log[1/TD50], i.e., ASA=f(X1SA,X2SA,…)). The present method includes calculation of the recently developed residual correlation of the structural alert models, i.e., ARASA=f(A−ASA,X1SA,X2SA,…). We propose a specific electrophilic ligand-receptor mechanism that combines electronegativity with chemical hardness-associated frontier principles, equality of ligand-reagent electronegativities and ligand maximum chemical hardness for highly diverse toxic molecules against specific receptors in rats. The observed carcinogenic activity is influenced by the induced SA-mutagenic intermediate effect, alongside Hansch indices such as hydrophobicity (LogP), polarizability (POL) and total energy (Etot), which account for molecular membrane diffusion, ionic deformation, and stericity, respectively. A possible QSAR mechanistic interpretation of mutagenicity as the first step in genotoxic carcinogenesis development is discussed using the structural alert chemoinformation and in full accordance with the Organization for Economic Co-operation and Development QSAR guidance principles. PMID:21954348

Discovery of new antimalarial chemotypes through chemical methodology and library development.

PubMed

Brown, Lauren E; Chih-Chien Cheng, Ken; Wei, Wan-Guo; Yuan, Pingwei; Dai, Peng; Trilles, Richard; Ni, Feng; Yuan, Jing; MacArthur, Ryan; Guha, Rajarshi; Johnson, Ronald L; Su, Xin-zhuan; Dominguez, Melissa M; Snyder, John K; Beeler, Aaron B; Schaus, Scott E; Inglese, James; Porco, John A

2011-04-26

In an effort to expand the stereochemical and structural complexity of chemical libraries used in drug discovery, the Center for Chemical Methodology and Library Development at Boston University has established an infrastructure to translate methodologies accessing diverse chemotypes into arrayed libraries for biological evaluation. In a collaborative effort, the NIH Chemical Genomics Center determined IC(50)'s for Plasmodium falciparum viability for each of 2,070 members of the CMLD-BU compound collection using quantitative high-throughput screening across five parasite lines of distinct geographic origin. Three compound classes displaying either differential or comprehensive antimalarial activity across the lines were identified, and the nascent structure activity relationships (SAR) from this experiment used to initiate optimization of these chemotypes for further development.

Biological activity of aldose reductase and lipophilicity of pyrrolyl-acetic acid derivatives

NASA Astrophysics Data System (ADS)

Kumari, A.; Kumari, R.; Kumar, R.; Gupta, M.

2011-12-01

Quantitative Structure-Activity Relationship modeling is a powerful approach for correlating an organic compound to its lipophilicity. In this paper QSAR models are established for estimation of correlation of the lipophilicity of a series of pyrrolyl-acetic acid derivatives, inhibitors of the aldose reductase enzyme, in the n-octanol-water system with biological activity of aldose reductase. Lipophilicity, expressed by the logarithm of n-octnol-water partition coefficient log P and biological activity of aldose reductase inhibitory activity by log it. Result obtained by QSAR modeling of compound series reveal a definite trend in biological activity and a further improvement in quantitative relationships are established if, beside log P, Hammett electronic constant σ and connectivity index chi-3 (3 χ) term included in the regression equation. The tri-parametric model with log P, 3 χ and σ as correlating parameters have been found to be the best which gives a variance of 87% ( R 2 = 0.8743). A compound has been found to be serious outlier and when the same has been excluded the model explains about 94% variance of the data set ( R 2 = 0.9447). The topological index (3 χ) has been found to be a good parameter for modeling the biological activity.

Quantitative morphometric analysis for the tectonic characterisation of northern Tunisia.

NASA Astrophysics Data System (ADS)

Camafort, Miquel; Pérez-Peña, José Vicente; Booth-Rea, Guillermo; Ranero, César R.; Gràcia, Eulàlia; Azañón, José Miguel; Melki, Fetheddine; Ouadday, Mohamed

2016-04-01

Northern Tunisia is characterized by low deformation rates and low to moderate seismicity. Although instrumental seismicity reaches maximum magnitudes of Mw 5.5, some historical earthquakes have occurred with catastrophic consequences in this region. Aiming to improve our knowledge of active tectonics in Tunisia, we carried out both a quantitative morphometric analysis and field study in the north-western region. We applied different morphometric tools, like river profiles, knickpoint analysis, hypsometric curves and integrals and drainage pattern anomalies in order to differentiate between zones with high or low recent tectonic activity. This analysis helps identifying uplift and subsidence zones, which we relate to fault activity. Several active faults in a sparse distribution were identified. A selected sector was studied with a field campaign to test the results obtained with the quantitative analysis. During the fieldwork we identified geological evidence of recent activity and a considerable seismogenic potential along El Alia-Teboursouk (ETF) and Dkhila (DF) faults. The ETF fault could be responsible of one of the most devastating historical earthquakes in northern Tunisia that destroyed Utique in 412 A.D. Geological evidence include fluvial terraces folded by faults, striated and cracked pebbles, clastic dikes, sand volcanoes, coseismic cracks, etc. Although not reflected in the instrumental seismicity, our results support an important seismic hazard, evidenced by the several active tectonic structures identified and the two seismogenic faults described. After obtaining the current active tectonic framework of Tunisia we discuss our results within the western Mediterranean trying to contribute to the understanding of the western Mediterranean tectonic context. With our results, we suggest that the main reason explaining the sparse and scarce seismicity of the area in contrast with the adjacent parts of the Nubia-Eurasia boundary is due to its extended continental platform and its lack of proto-oceanic crust northward.

Linear and non-linear quantitative structure-activity relationship models on indole substitution patterns as inhibitors of HIV-1 attachment.

PubMed

Nirouei, Mahyar; Ghasemi, Ghasem; Abdolmaleki, Parviz; Tavakoli, Abdolreza; Shariati, Shahab

2012-06-01

The antiviral drugs that inhibit human immunodeficiency virus (HIV) entry to the target cells are already in different phases of clinical trials. They prevent viral entry and have a highly specific mechanism of action with a low toxicity profile. Few QSAR studies have been performed on this group of inhibitors. This study was performed to develop a quantitative structure-activity relationship (QSAR) model of the biological activity of indole glyoxamide derivatives as inhibitors of the interaction between HIV glycoprotein gp120 and host cell CD4 receptors. Forty different indole glyoxamide derivatives were selected as a sample set and geometrically optimized using Gaussian 98W. Different combinations of multiple linear regression (MLR), genetic algorithms (GA) and artificial neural networks (ANN) were then utilized to construct the QSAR models. These models were also utilized to select the most efficient subsets of descriptors in a cross-validation procedure for non-linear log (1/EC50) prediction. The results that were obtained using GA-ANN were compared with MLR-MLR and MLR-ANN models. A high predictive ability was observed for the MLR, MLR-ANN and GA-ANN models, with root mean sum square errors (RMSE) of 0.99, 0.91 and 0.67, respectively (N = 40). In summary, machine learning methods were highly effective in designing QSAR models when compared to statistical method.

A quantitative structure-activity relationship to predict efficacy of granular activated carbon adsorption to control emerging contaminants.

PubMed

Kennicutt, A R; Morkowchuk, L; Krein, M; Breneman, C M; Kilduff, J E

2016-08-01

A quantitative structure-activity relationship was developed to predict the efficacy of carbon adsorption as a control technology for endocrine-disrupting compounds, pharmaceuticals, and components of personal care products, as a tool for water quality professionals to protect public health. Here, we expand previous work to investigate a broad spectrum of molecular descriptors including subdivided surface areas, adjacency and distance matrix descriptors, electrostatic partial charges, potential energy descriptors, conformation-dependent charge descriptors, and Transferable Atom Equivalent (TAE) descriptors that characterize the regional electronic properties of molecules. We compare the efficacy of linear (Partial Least Squares) and non-linear (Support Vector Machine) machine learning methods to describe a broad chemical space and produce a user-friendly model. We employ cross-validation, y-scrambling, and external validation for quality control. The recommended Support Vector Machine model trained on 95 compounds having 23 descriptors offered a good balance between good performance statistics, low error, and low probability of over-fitting while describing a wide range of chemical features. The cross-validated model using a log-uptake (qe) response calculated at an aqueous equilibrium concentration (Ce) of 1 μM described the training dataset with an r(2) of 0.932, had a cross-validated r(2) of 0.833, and an average residual of 0.14 log units.

Modulation of Active Site Electronic Structure by the Protein Matrix to Control [NiFe] Hydrogenase Reactivity

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

Smith, Dayle MA; Raugei, Simone; Squier, Thomas C.

2014-09-30

Control of the reactivity of the nickel center of the [NiFe] hydrogenase and other metalloproteins commonly involves outer coordination sphere ligands that act to modify the geometry and physical properties of the active site metal centers. We carried out a combined set of classical molecular dynamics and quantum/classical mechanics calculations to provide quantitative estimates of how dynamic fluctuations of the active site within the protein matrix modulate the electronic structure at the catalytic center. Specifically we focused on the dynamics of the inner and outer coordination spheres of the cysteinate-bound Ni–Fe cluster in the catalytically active Ni-C state. There aremore » correlated movements of the cysteinate ligands and the surrounding hydrogen-bonding network, which modulate the electron affinity at the active site and the proton affinity of a terminal cysteinate. On the basis of these findings, we hypothesize a coupling between protein dynamics and electron and proton transfer reactions critical to dihydrogen production.« less

Modulation of active site electronic structure by the protein matrix to control [NiFe] hydrogenase reactivity.

PubMed

Smith, Dayle M A; Raugei, Simone; Squier, Thomas C

2014-11-21

Control of the reactivity of the nickel center of the [NiFe] hydrogenase and other metalloproteins commonly involves outer coordination sphere ligands that act to modify the geometry and physical properties of the active site metal centers. We carried out a combined set of classical molecular dynamics and quantum/classical mechanics calculations to provide quantitative estimates of how dynamic fluctuations of the active site within the protein matrix modulate the electronic structure at the catalytic center. Specifically we focused on the dynamics of the inner and outer coordination spheres of the cysteinate-bound Ni-Fe cluster in the catalytically active Ni-C state. There are correlated movements of the cysteinate ligands and the surrounding hydrogen-bonding network, which modulate the electron affinity at the active site and the proton affinity of a terminal cysteinate. On the basis of these findings, we hypothesize a coupling between protein dynamics and electron and proton transfer reactions critical to dihydrogen production.

Neural network-based QSAR and insecticide discovery: spinetoram

NASA Astrophysics Data System (ADS)

Sparks, Thomas C.; Crouse, Gary D.; Dripps, James E.; Anzeveno, Peter; Martynow, Jacek; DeAmicis, Carl V.; Gifford, James

2008-06-01

Improvements in the efficacy and spectrum of the spinosyns, novel fermentation derived insecticide, has long been a goal within Dow AgroSciences. As large and complex fermentation products identifying specific modifications to the spinosyns likely to result in improved activity was a difficult process, since most modifications decreased the activity. A variety of approaches were investigated to identify new synthetic directions for the spinosyn chemistry including several explorations of the quantitative structure activity relationships (QSAR) of spinosyns, which initially were unsuccessful. However, application of artificial neural networks (ANN) to the spinosyn QSAR problem identified new directions for improved activity in the chemistry, which subsequent synthesis and testing confirmed. The ANN-based analogs coupled with other information on substitution effects resulting from spinosyn structure activity relationships lead to the discovery of spinetoram (XDE-175). Launched in late 2007, spinetoram provides both improved efficacy and an expanded spectrum while maintaining the exceptional environmental and toxicological profile already established for the spinosyn chemistry.

The importance of psychological and social factors in influencing the uptake and maintenance of physical activity after stroke: a structured review of the empirical literature.

PubMed

Morris, Jacqui; Oliver, Tracey; Kroll, Thilo; Macgillivray, Steve

2012-01-01

Background. People with stroke are not maintaining adequate engagement in physical activity (PA) for health and functional benefit. This paper sought to describe any psychological and social factors that may influence physical activity engagement after stroke. Methods. A structured literature review of studies indexed in MEDLINE, CinAHL, P&BSC, and PsycINFO using search terms relevant to stroke, physical disabilities, and PA. Publications reporting empirical findings (quantitative or qualitative) regarding psychological and/or social factors were included. Results. Twenty studies from 19 publications (9 surveys, 1 RCT, and 10 qualitative studies) were included. Seventeen studies reported findings pertinent to psychological factors and fourteen findings pertinent to social factors. Conclusion. Self-efficacy, physical activity beliefs, and social support appear particularly relevant to physical activity behaviour after stroke and should be included in theoretically based physical interventions. The Transtheoretical Model and the Theory of Planned Behaviour are candidate behavioural models that may support intervention development.

Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.

New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.

PubMed

Hattotuwagama, Channa K; Guan, Pingping; Doytchinova, Irini A; Flower, Darren R

2004-11-21

Quantitative structure-activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide-protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2-D(b), H2-K(b) and H2-K(k). As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred).

Creating Research-Rich Learning Experiences and Quantitative Skills in a 1st Year Earth Systems Course

NASA Astrophysics Data System (ADS)

King, P. L.; Eggins, S.; Jones, S.

2014-12-01

We are creating a 1st year Earth Systems course at the Australian National University that is built around research-rich learning experiences and quantitative skills. The course has top students including ≤20% indigenous/foreign students; nonetheless, students' backgrounds in math and science vary considerably posing challenges for learning. We are addressing this issue and aiming to improve knowledge retention and deep learning by changing our teaching approach. In 2013-2014, we modified the weekly course structure to a 1hr lecture; a 2hr workshop with hands-on activities; a 2hr lab; an assessment piece covering all face-to-face activities; and a 1hr tutorial. Our new approach was aimed at: 1) building student confidence with data analysis and quantitative skills through increasingly difficult tasks in science, math, physics, chemistry, climate science and biology; 2) creating effective learning groups using name tags and a classroom with 8-person tiered tables; 3) requiring students to apply new knowledge to new situations in group activities, two 1-day field trips and assessment items; 4) using pre-lab and pre-workshop exercises to promote prior engagement with key concepts; 5) adding open-ended experiments to foster structured 'scientific play' or enquiry and creativity; and 6) aligning the assessment with the learning outcomes and ensuring that it contains authentic and challenging southern hemisphere problems. Students were asked to design their own ocean current experiment in the lab and we were astounded by their ingenuity: they simulated the ocean currents off Antarctica; varied water density to verify an equation; and examined the effect of wind and seafloor topography on currents. To evaluate changes in student learning, we conducted surveys in 2013 and 2014. In 2014, we found higher levels of student engagement with the course: >~80% attendance rates and >~70% satisfaction (20% neutral). The 2014 cohort felt that they were more competent in writing and data analysis skills, working quantitatively using spreadsheets; deriving equations to describe nature; using the scientific method; and research processes. Assessment strategies are challenging and we plan to test a grading approach based on the "three Cs": content, correctness and creativity.

Grain-boundary-dependent CO2 electroreduction activity.

PubMed

Feng, Xiaofeng; Jiang, Kaili; Fan, Shoushan; Kanan, Matthew W

2015-04-15

Uncovering new structure-activity relationships for metal nanoparticle (NP) electrocatalysts is crucial for advancing many energy conversion technologies. Grain boundaries (GBs) could be used to stabilize unique active surfaces, but a quantitative correlation between GBs and catalytic activity has not been established. Here we use vapor deposition to prepare Au NPs on carbon nanotubes (Au/CNT). As deposited, the Au NPs have a relatively high density of GBs that are readily imaged by transmission electron microscopy (TEM); thermal annealing lowers the density in a controlled manner. We show that the surface-area-normalized activity for CO2 reduction is linearly correlated with GB surface density on Au/CNT, demonstrating that GB engineering is a powerful approach to improving the catalytic activity of metal NPs.

Development of a method for urine bikunin/urinary trypsin inhibitor (UTI) quantitation and structural characterization: Application to type 1 and type 2 diabetes.

PubMed

Lepedda, Antonio Junior; Nieddu, Gabriele; Rocchiccioli, Silvia; Fresu, Pietro; De Muro, Pierina; Formato, Marilena

2013-12-01

Bikunin is a plasma proteinase inhibitor often associated with inflammatory conditions. It has a half-life of few minutes and it is rapidly excreted into urine as urinary trypsin inhibitor (UTI). UTI levels are usually low in healthy individuals but they can increase up to tenfold in both acute and chronic inflammatory diseases. This article describes a sensitive method for both direct UTI quantitation and structural characterization. UTI purification was performed by anion exchange micro-chromatography followed by SDS-PAGE. A calibration curve for protein quantitation was set up by using a purified UTI fraction. UTI identification and structural characterization was performed by Nano-LC-MS/MS analysis. The method was applied on urine samples from 9 patients with type 1 diabetes, 11 patients with type 2 diabetes, and 28 healthy controls, matched for age and sex with patients, evidencing higher UTI levels in both groups of patients with respect to controls (p < 0.001 and p = 0.001, respectively). Spearman's correlation tests highlighted no association between UTI levels and age in each group tested. Owing to the elevated sensitivity and specificity, the described method allows UTI quantitation from very low quantities of specimen. Furthermore, as UTI concentration is normalized for creatinine level, the analysis could be also performed on randomly collected urine samples. Finally, MS/MS analysis prospects the possibility of characterizing PTM sites potentially able to affect UTI localization, function, and pathophysiological activity. Preliminary results suggest that UTI levels could represent a useful marker of chronic inflammatory condition in type 1 and 2 diabetes. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model-based analysis of N-glycosylation in Chinese hamster ovary cells

PubMed Central

Krambeck, Frederick J.; Bennun, Sandra V.; Betenbaugh, Michael J.

2017-01-01

The Chinese hamster ovary (CHO) cell is the gold standard for manufacturing of glycosylated recombinant proteins for production of biotherapeutics. The similarity of its glycosylation patterns to the human versions enable the products of this cell line favorable pharmacokinetic properties and lower likelihood of causing immunogenic responses. Because glycan structures are the product of the concerted action of intracellular enzymes, it is difficult to predict a priori how the effects of genetic manipulations alter glycan structures of cells and therapeutic properties. For that reason, quantitative models able to predict glycosylation have emerged as promising tools to deal with the complexity of glycosylation processing. For example, an earlier version of the same model used in this study was used by others to successfully predict changes in enzyme activities that could produce a desired change in glycan structure. In this study we utilize an updated version of this model to provide a comprehensive analysis of N-glycosylation in ten Chinese hamster ovary (CHO) cell lines that include a wild type parent and nine mutants of CHO, through interpretation of previously published mass spectrometry data. The updated N-glycosylation mathematical model contains up to 50,605 glycan structures. Adjusting the enzyme activities in this model to match N-glycan mass spectra produces detailed predictions of the glycosylation process, enzyme activity profiles and complete glycosylation profiles of each of the cell lines. These profiles are consistent with biochemical and genetic data reported previously. The model-based results also predict glycosylation features of the cell lines not previously published, indicating more complex changes in glycosylation enzyme activities than just those resulting directly from gene mutations. The model predicts that the CHO cell lines possess regulatory mechanisms that allow them to adjust glycosylation enzyme activities to mitigate side effects of the primary loss or gain of glycosylation function known to exist in these mutant cell lines. Quantitative models of CHO cell glycosylation have the potential for predicting how glycoengineering manipulations might affect glycoform distributions to improve the therapeutic performance of glycoprotein products. PMID:28486471

Mass Spectrometry Based Identification of Geometric Isomers during Metabolic Stability Study of a New Cytotoxic Sulfonamide Derivatives Supported by Quantitative Structure-Retention Relationships

PubMed Central

Belka, Mariusz; Hewelt-Belka, Weronika; Sławiński, Jarosław; Bączek, Tomasz

2014-01-01

A set of 15 new sulphonamide derivatives, presenting antitumor activity have been subjected to a metabolic stability study. The results showed that besides products of biotransformation, some additional peaks occurred in chromatograms. Tandem mass spectrometry revealed the same mass and fragmentation pathway, suggesting that geometric isomerization occurred. Thus, to support this hypothesis, quantitative structure-retention relationships were applied. Human liver microsomes were used as an in vitro model of metabolism. The biotransformation reactions were tracked by liquid chromatography assay and additionally, fragmentation mass spectra were recorded. In silico molecular modeling at a semi-empirical level was conducted as a starting point for molecular descriptor calculations. A quantitative structure-retention relationship model was built applying multiple linear regression based on selected three-dimensional descriptors. The studied compounds revealed high metabolic stability, with a tendency to form hydroxylated biotransformation products. However, significant chemical instability in conditions simulating human body fluids was noticed. According to literature and MS data geometrical isomerization was suggested. The developed in sillico model was able to describe the relationship between the geometry of isomer pairs and their chromatographic retention properties, thus it supported the hypothesis that the observed pairs of peaks are most likely geometric isomers. However, extensive structural investigations are needed to fully identify isomers’ geometry. An effort to describe MS fragmentation pathways of novel chemical structures is often not enough to propose structures of potent metabolites and products of other chemical reactions that can be observed in compound solutions at early drug discovery studies. The results indicate that the relatively non-expensive and not time- and labor-consuming in sillico approach could be a good supportive tool assisting the identification of cis-trans isomers based on retention data. This methodology can be helpful during the structural identification of biotransformation and degradation products of new chemical entities - potential new drugs. PMID:24893169

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology.

PubMed

von Bergen, Martin; Jehmlich, Nico; Taubert, Martin; Vogt, Carsten; Bastida, Felipe; Herbst, Florian-Alexander; Schmidt, Frank; Richnow, Hans-Hermann; Seifert, Jana

2013-10-01

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ((13)C, (15)N, (36)S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

Cooperative catalysis for the direct hydrodeoxygenation of vegetable oils into diesel-range alkanes over Pd/NbOPO4.

PubMed

Xia, Qineng; Zhuang, Xiaojing; Li, Molly Meng-Jung; Peng, Yung-Kang; Liu, Guoliang; Wu, Tai-Sing; Soo, Yun-Liang; Gong, Xue-Qing; Wang, Yanqin; Tsang, Shik Chi Edman

2016-04-14

Near quantitative carbon yields of diesel-range alkanes were achieved from the hydrodeoxygenation of triglycerides over Pd/NbOPO4 under mild conditions with no catalyst deactivation: catalyst characterization and theoretical calculations suggest that the high hydrodeoxygenation activity originated from the synergistic effect of Pd and strong Lewis acidity on the unique structure of NbOPO4.

Novel Carboxamides as Potential Mosquito Repellents

DTIC Science & Technology

2010-09-01

effective dosage to prevent Aedes aegypti (L.) (Diptera: Culicidae) bites . One compound, (E)-N-cyclohexyl-N-ethyl-2-hexenamide, was superior to N,N...versus 0.047 mol/cm2). KEY WORDS repellents, carboxamides, quantitative structure-activity relationship, CPT, Aedes aegypti N,N-diethyl-3-methylbenzamide...these were synthe- sized. The model was validated by subsequent bioas- says with female Aedes aegypti (L.) (Diptera: Culici- dae) mosquitoes, wherein

Quantum chemical parameters in QSAR: what do I use when?

USGS Publications Warehouse

Hickey, James P.; Ostrander, Gary K.

1996-01-01

This chapter provides a brief overview of the numerous quantum chemical parameters that have been/are currently being used in quantitative structure activity relationships (QSAR), along with a representative bibliography. The parameters will be grouped according to their mechanistic interpretations, and representative biological and physical chemical applications will be mentioned. Parmater computation methods and the appropriate software are highlighted, as are sources for software.

QSAR Study on the anti-tumor activity of levofloxacin-thiadiazole HDACi conjugates

NASA Astrophysics Data System (ADS)

Tang, Ziqiang; Feng, Hui; Chen, Yan; Yue, Wei; Feng, Changjun

2017-12-01

A molecular electronegativity distance vector(M t) based on 13atomic types is used to describe the structures of 19 conjugates(LHCc) of levofloxacin-thiadiazole HDAC inhibitor(HDACi) and related to the anti-tumor activity (M F and P C) of LHCc against MCF-7 and PC-3. The quantitative structure-activity relationships (QSAR) was established by using leaps-and-bounds regression analysis for the anti-tumor activities (M F and P C) of 19 above compounds to MCF-7and PC-3 along with the M t. The correlation coefficients (R 2) and the leave-one-out (LOO) cross validation R cv 2 for the M F and P C models were 0.792 and 0.679; 0.773 and 0.565, respectively. The QSAR models have favorable correlation, as well as robustness and good prediction capability by R 2, F, R cv 2, A IC F IT V IF tests. The results indicate that the molecular structural units: －CHg－(g=1, 2), －NH2, －NH－,－OH, O=, －O－, －S－ and －X are main factors which can affect the anti-tumor activity M F and PC bioactivities of these compounds directly.

Proximity-activated nanoparticles: in vitro performance of specific structural modification by enzymatic cleavage

PubMed Central

Adam Smith, R; Sewell, Sarah L; Giorgio, Todd D

2008-01-01

The development and in vitro performance of a modular nanoscale system capable of specific structural modification by enzymatic activity is described in this work. Due to its small physical size and adaptable characteristics, this system has the potential for utilization in targeted delivery systems and biosensing. Nanoparticle probes were synthesized containing two distinct fluorescent species including a quantum dot base particle and fluorescently labeled cleavable peptide substrate. Activity of these probes was monitored by gel electrophoresis with quantitative cleavage measurements made by fluorometric analysis. The model proximity-activated nanoparticles studied here exhibit significant susceptibility to cleavage by matrix metalloprotease-7 (MMP-7) at physiologically relevant concentrations, with nearly complete cleavage of available substrate molecules after 24 hours. This response is specific to MMP-7 enzyme activity, as cleavage is completely inhibited with the addition of EDTA. Utilization of enzyme-specific modification is a sensitive approach with broad applications for targeted therapeutics and biosensing. The versatility of this nanoparticle system is highlighted in its modular design, as it has the capability to integrate characteristics for detection, biosensing, targeting, and payload delivery into a single, multifunctional nanoparticle structure. PMID:18488420

[The morphofunctional state of the bone marrow in lead and zinc intoxication].

PubMed

Vladimtseva, T M; Pashkevich, I A; Salmina, A B

2006-01-01

The nucleolus is a compulsory nuclear structure of all cells of eukaryotes. The quantitative and qualitative characteristics of nuclei show the functional activity of a cell, the rate of its synthesis of RNA and portents, and its metabolic state. Heavy metals (zinc chloride and lead acetate) were comparatively investigated for their effects on the nucleolar apparatus of bone marrow cells in in vivo experiments. Zinc chloride and lead acetate were ascertained to damage the nucleolar apparatus of cells, thus decreasing their transcriptional activity or irreversibly damaging them.

Modeling Joint Effects of Mixtures of Chemicals on Microorganisms Using Quantitative Structure Activity Relationships

DTIC Science & Technology

1993-08-22

Cyclohexane Alk 74 133 26 Pentane Alk 70 150 27 Hexane Alk 38 47 28 Heptane Alk 18 58 29 Octane Alk 8 60 30 Bis (2-chloroethyl) ether Alc 1,600 3,025 31...Triethanolarnine Amni 900 741 SAro- aromatic; Hal- balogemmaed aliphatic; Alk - alkanes; Alc- alcohols, este’s, ketones and et Aji- amineL -5- Correlation...chemicals using laboratory grown activated sludge by synthetic feed. They adapted the OECD Method 209, using inhibition of oxygen uptake rate as the measure

Electrodeposition of Highly Porous Pt Nanoparticles Studied by Quantitative 3D Electron Tomography: Influence of Growth Mechanisms and Potential Cycling on the Active Surface Area.

PubMed

Ustarroz, Jon; Geboes, Bart; Vanrompay, Hans; Sentosun, Kadir; Bals, Sara; Breugelmans, Tom; Hubin, Annick

2017-05-17

Nanoporous Pt nanoparticles (NPs) are promising fuel cell catalysts due to their large surface area and increased electrocatalytic activity toward the oxygen reduction reaction (ORR). Herein, we report on the influence of the growth mechanisms on the surface properties of electrodeposited Pt dendritic NPs with large surface areas. The electrochemically active surface was studied by hydrogen underpotential deposition (H UPD) and compared for the first time to high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) quantitative 3D electron tomography of individual nanoparticles. Large nucleation overpotential leads to a large surface coverage of roughened spheroids, which provide a large roughness factor (R f ) but low mass-specific electrochemically active surface area (EASA). Lowering the nucleation overpotential leads to highly porous Pt NPs with pores stretching to the center of the structure. At the expense of smaller R f , the obtained EASA values of these structures are in the range of those of large surface area supported fuel cell catalysts. The active surface area of the Pt dendritic NPs was measured by electron tomography, and it was found that the potential cycling in the H adsorption/desorption and Pt oxidation/reduction region, which is generally performed to determine the EASA, leads to a significant reduction of that surface area due to a partial collapse of their dendritic and porous morphology. Interestingly, the extrapolation of the microscopic tomography results in macroscopic electrochemical parameters indicates that the surface properties measured by H UPD are comparable to the values measured on individual NPs by electron tomography after the degradation caused by the H UPD measurement. These results highlight that the combination of electrochemical and quantitative 3D surface analysis techniques is essential to provide insights into the surface properties, the electrochemical stability, and, hence, the applicability of these materials. Moreover, it indicates that care must be taken with widely used electrochemical methods of surface area determination, especially in the case of large surface area and possibly unstable nanostructures, since the measured surface can be strongly affected by the measurement itself.

Application of 3D-QSAR in the rational design of receptor ligands and enzyme inhibitors.

PubMed

Mor, Marco; Rivara, Silvia; Lodola, Alessio; Lorenzi, Simone; Bordi, Fabrizio; Plazzi, Pier Vincenzo; Spadoni, Gilberto; Bedini, Annalida; Duranti, Andrea; Tontini, Andrea; Tarzia, Giorgio

2005-11-01

Quantitative structure-activity relationships (QSARs) are frequently employed in medicinal chemistry projects, both to rationalize structure-activity relationships (SAR) for known series of compounds and to help in the design of innovative structures endowed with desired pharmacological actions. As a difference from the so-called structure-based drug design tools, they do not require the knowledge of the biological target structure, but are based on the comparison of drug structural features, thus being defined ligand-based drug design tools. In the 3D-QSAR approach, structural descriptors are calculated from molecular models of the ligands, as interaction fields within a three-dimensional (3D) lattice of points surrounding the ligand structure. These descriptors are collected in a large X matrix, which is submitted to multivariate analysis to look for correlations with biological activity. Like for other QSARs, the reliability and usefulness of the correlation models depends on the validity of the assumptions and on the quality of the data. A careful selection of compounds and pharmacological data can improve the application of 3D-QSAR analysis in drug design. Some examples of the application of CoMFA and CoMSIA approaches to the SAR study and design of receptor or enzyme ligands is described, pointing the attention to the fields of melatonin receptor ligands and FAAH inhibitors.

QSAR DataBank - an approach for the digital organization and archiving of QSAR model information

PubMed Central

2014-01-01

Background Research efforts in the field of descriptive and predictive Quantitative Structure-Activity Relationships or Quantitative Structure–Property Relationships produce around one thousand scientific publications annually. All the materials and results are mainly communicated using printed media. The printed media in its present form have obvious limitations when they come to effectively representing mathematical models, including complex and non-linear, and large bodies of associated numerical chemical data. It is not supportive of secondary information extraction or reuse efforts while in silico studies poses additional requirements for accessibility, transparency and reproducibility of the research. This gap can and should be bridged by introducing domain-specific digital data exchange standards and tools. The current publication presents a formal specification of the quantitative structure-activity relationship data organization and archival format called the QSAR DataBank (QsarDB for shorter, or QDB for shortest). Results The article describes QsarDB data schema, which formalizes QSAR concepts (objects and relationships between them) and QsarDB data format, which formalizes their presentation for computer systems. The utility and benefits of QsarDB have been thoroughly tested by solving everyday QSAR and predictive modeling problems, with examples in the field of predictive toxicology, and can be applied for a wide variety of other endpoints. The work is accompanied with open source reference implementation and tools. Conclusions The proposed open data, open source, and open standards design is open to public and proprietary extensions on many levels. Selected use cases exemplify the benefits of the proposed QsarDB data format. General ideas for future development are discussed. PMID:24910716

Management of the aging of critical safety-related concrete structures in light-water reactor plants

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

Naus, D.J.; Oland, C.B.; Arndt, E.G.

1990-01-01

The Structural Aging Program has the overall objective of providing the USNRC with an improved basis for evaluating nuclear power plant safety-related structures for continued service. The program consists of a management task and three technical tasks: materials property data base, structural component assessment/repair technology, and quantitative methodology for continued-service determinations. Objectives, accomplishments, and planned activities under each of these tasks are presented. Major program accomplishments include development of a materials property data base for structural materials as well as an aging assessment methodology for concrete structures in nuclear power plants. Furthermore, a review and assessment of inservice inspection techniquesmore » for concrete materials and structures has been complete, and work on development of a methodology which can be used for performing current as well as reliability-based future condition assessment of concrete structures is well under way. 43 refs., 3 tabs.« less

Biological evaluation and 3D-QSAR studies of curcumin analogues as aldehyde dehydrogenase 1 inhibitors.

PubMed

Wang, Hui; Du, Zhiyun; Zhang, Changyuan; Tang, Zhikai; He, Yan; Zhang, Qiuyan; Zhao, Jun; Zheng, Xi

2014-05-16

Aldehyde dehydrogenase 1 (ALDH1) is reported as a biomarker for identifying some cancer stem cells, and down-regulation or inhibition of the enzyme can be effective in anti-drug resistance and a potent therapeutic for some tumours. In this paper, the inhibitory activity, mechanism mode, molecular docking and 3D-QSAR (three-dimensional quantitative structure activity relationship) of curcumin analogues (CAs) against ALDH1 were studied. Results demonstrated that curcumin and CAs possessed potent inhibitory activity against ALDH1, and the CAs compound with ortho di-hydroxyl groups showed the most potent inhibitory activity. This study indicates that CAs may represent a new class of ALDH1 inhibitor.

Self-organization of local magnetoplasma structures in the upper layers of the solar convection zone

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

Chumak, O. V., E-mail: chuo@yandex.ru

Self-organization and evolution of magnetoplasma structures in the upper layers of the solar convection zone are discussed as a process of diffuse aggregation of magnetic flux tubes. Equations describing the tube motion under the action of magnetic interaction forces, hydrodynamic forces, and random forces are written explicitly. The process of aggregation of magnetic flux tubes into magnetic flux clusters of different shapes and dimensions is simulated numerically. The obtained structures are compared with the observed morphological types of sunspot groups. The quantitative comparison with the observational data was performed by comparing the fractal dimensions of the photospheric magnetic structures observedmore » in solar active regions with those of structures obtained in the numerical experiment. The model has the following free parameters: the numbers of magnetic flux tubes with opposite polarities on the considered area element (Nn and Ns), the average radius of the cross section of the magnetic flux tube (a), its effective length (l), the twist factor of the tube field (k), and the absolute value of the average velocity of chaotic tube displacements (d). Variations in these parameters in physically reasonable limits leads to the formation of structures (tube clusters of different morphological types) having different fractal dimensions. Using the NOAA 10488 active region, which appeared and developed into a complicated configuration near the central meridian, as an example, it is shown that good quantitative agreement between the fractal dimensions is achieved at the following parameters of the model: Nn = Ns = 250 ± 50; a = 150 ± 50 km; l ∼ 5000 km, and d = 80 ± 10 m/s. These results do not contradict the observational data and theoretical estimates obtained in the framework of the Parker “spaghetti” model and provide new information on the physical processes resulting in the origin and evolution of local magnetic plasma structures in the near-photospheric layers of the solar convection zone.« less

1-[(3-Aryloxy-3-aryl)propyl]-1H-imidazoles, new imidazoles with potent activity against Candida albicans and dermatophytes. Synthesis, structure-activity relationship, and molecular modeling studies.

PubMed

La Regina, Giuseppe; D'Auria, Felicia Diodata; Tafi, Andrea; Piscitelli, Francesco; Olla, Stefania; Caporuscio, Fabiana; Nencioni, Lucia; Cirilli, Roberto; La Torre, Francesco; De Melo, Nadja Rodrigues; Kelly, Steven L; Lamb, David C; Artico, Marino; Botta, Maurizio; Palamara, Anna Teresa; Silvestri, Romano

2008-07-10

New 1-[(3-aryloxy-3-aryl)propyl]-1 H-imidazoles were synthesized and evaluated against Candida albicans and dermatophytes in order to develop structure-activity relationships (SARs). Against C. albicans the new imidazoles showed minimal inhibitory concentrations (MICs) comparable to those of ketoconazole, miconazole, and econazole, and were more potent than fluconazole. Several derivatives ( 10, 12, 14, 18- 20, 24, 28, 29, 30, and 34) turned out to be potent inhibitors of C. albicans strains resistant to fluconazole, with MIC values less than 10 microg/mL. Against dermatophytes strains, compounds 20, 25, and 33 (MIC

Molecular docking and QSAR study on steroidal compounds as aromatase inhibitors.

PubMed

Dai, Yujie; Wang, Qiang; Zhang, Xiuli; Jia, Shiru; Zheng, Heng; Feng, Dacheng; Yu, Peng

2010-12-01

In order to develop more potent, selective and less toxic steroidal aromatase (AR) inhibitors, molecular docking, 2D and 3D hybrid quantitative structure-activity relationship (QSAR) study have been conducted using topological, molecular shape, spatial, structural and thermodynamic descriptors on 32 steroidal compounds. The molecular docking study shows that one or more hydrogen bonds with MET374 are one of the essential requirements for the optimum binding of ligands. The QSAR model obtained indicates that the aromatase inhibitory activity can be enhanced by increasing SIC, SC_3_C, Jurs_WNSA_1, Jurs_WPSA_1 and decreasing CDOCKER interaction energy (ECD), IAC_Total and Shadow_XZfrac. The predicted results shows that this model has a comparatively good predictive power which can be used in prediction of activity of new steroidal aromatase inhibitors. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

QSAR studies in substituted 1,2,3,4,6,7,12,12a-octa-hydropyrazino[2',1':6,1]pyrido[3,4-b]indoles--a potent class of neuroleptics.

PubMed

Saxena, Anil K; Ram, Siya; Saxena, Mridula; Singh, Nidhi; Prathipati, Philip; Jain, Padam C; Singh, H K; Anand, Nitya

2003-05-01

A series of nineteen substituted 1,2,3,4,6,7,12,12a-octahydropyrazino[2',1':6,1]pyrido[3, 4-b]indoles analogues of neuroleptic drug, Centbutindole have been studied using quantitative structure-activity relationship analysis. The derived models display good fits to the experimental data (r>or=0.75) having good predictive power (r(cv)>or=0.688). The best model describes a high correlation between predicted and experimental activity data (r=0.967). Statistical analysis of the equation populations indicates that hydrophobicity (as measured by pi(R), logP(o/w) and SlogP_VSA8), dipole y and structural parameters in terms of indicator variable, (In(1)) and globularity are important variables in describing the variation in the neuroleptic activity in the series.

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.

A framework for evaluating the formation, implementation, and performance of accountable care organizations.

PubMed

Fisher, Elliott S; Shortell, Stephen M; Kreindler, Sara A; Van Citters, Aricca D; Larson, Bridget K

2012-11-01

The implementation of accountable care organizations (ACOs), a new health care payment and delivery model designed to improve care and lower costs, is proceeding rapidly. We build on our experience tracking early ACOs to identify the major factors-such as contract characteristics; structure, capabilities, and activities; and local context-that would be likely to influence ACO formation, implementation, and performance. We then propose how an ACO evaluation program could be structured to guide policy makers and payers in improving the design of ACO contracts, while providing insights for providers on approaches to care transformation that are most likely to be successful in different contexts. We also propose key activities to support evaluation of ACOs in the near term, including tracking their formation, developing a set of performance measures across all ACOs and payers, aggregating those performance data, conducting qualitative and quantitative research, and coordinating different evaluation activities.

Farber's Disease

MedlinePlus

... of these disorders. Additional studies will emphasize the quantitative analysis of the central nervous system structure and ... of these disorders. Additional studies will emphasize the quantitative analysis of the central nervous system structure and ...

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

PubMed

Pradeep, Prachi; Povinelli, Richard J; Merrill, Stephen J; Bozdag, Serdar; Sem, Daniel S

2015-04-01

The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal predictors of in vivo carcinogenicity for development of hybrid Quantitative Structure Activity Relationship (QSAR) models. We propose two novel approaches for the use of mechanistically relevant in vitro assay data in the identification of relevant biological descriptors and development of Quantitative Biological Activity Relationship (QBAR) models for carcinogenicity prediction. We demonstrate that in vitro assay data can be used to develop QBAR models for in vivo carcinogenicity prediction via two case studies corroborated with firm scientific rationale. The case studies demonstrate the similarities between QBAR and QSAR modeling in: (i) the selection of relevant descriptors to be used in the machine learning algorithm, and (ii) the development of a computational model that maps chemical or biological descriptors to a toxic endpoint. The results of both the case studies show: (i) improved accuracy and sensitivity which is especially desirable under regulatory requirements, and (ii) overall adherence with the OECD/REACH guidelines. Such mechanism based models can be used along with QSAR models for prediction of mechanistically complex toxic endpoints. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry.

PubMed

Chavez, Juan D; Eng, Jimmy K; Schweppe, Devin K; Cilia, Michelle; Rivera, Keith; Zhong, Xuefei; Wu, Xia; Allen, Terrence; Khurgel, Moshe; Kumar, Akhilesh; Lampropoulos, Athanasios; Larsson, Mårten; Maity, Shuvadeep; Morozov, Yaroslav; Pathmasiri, Wimal; Perez-Neut, Mathew; Pineyro-Ruiz, Coriness; Polina, Elizabeth; Post, Stephanie; Rider, Mark; Tokmina-Roszyk, Dorota; Tyson, Katherine; Vieira Parrine Sant'Ana, Debora; Bruce, James E

2016-01-01

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.

System architectures for telerobotic research

NASA Technical Reports Server (NTRS)

Harrison, F. Wallace

1989-01-01

Several activities are performed related to the definition and creation of telerobotic systems. The effort and investment required to create architectures for these complex systems can be enormous; however, the magnitude of process can be reduced if structured design techniques are applied. A number of informal methodologies supporting certain aspects of the design process are available. More recently, prototypes of integrated tools supporting all phases of system design from requirements analysis to code generation and hardware layout have begun to appear. Activities related to system architecture of telerobots are described, including current activities which are designed to provide a methodology for the comparison and quantitative analysis of alternative system architectures.

Antifreeze (glyco)protein mimetic behavior of poly(vinyl alcohol): detailed structure ice recrystallization inhibition activity study.

PubMed

Congdon, Thomas; Notman, Rebecca; Gibson, Matthew I

2013-05-13

This manuscript reports a detailed study on the ability of poly(vinyl alcohol) to act as a biomimetic surrogate for antifreeze(glyco)proteins, with a focus on the specific property of ice-recrystallization inhibition (IRI). Despite over 40 years of study, the underlying mechanisms that govern the action of biological antifreezes are still poorly understood, which is in part due to their limited availability and challenging synthesis. Poly(vinyl alcohol) (PVA) has been shown to display remarkable ice recrystallization inhibition activity despite its major structural differences to native antifreeze proteins. Here, controlled radical polymerization is used to synthesize well-defined PVA, which has enabled us to obtain the first quantitative structure-activity relationships, to probe the role of molecular weight and comonomers on IRI activity. Crucially, it was found that IRI activity is "switched on" when the polymer chain length increases from 10 and 20 repeat units. Substitution of the polymer side chains with hydrophilic or hydrophobic units was found to diminish activity. Hydrophobic modifications to the backbone were slightly more tolerated than side chain modifications, which implies an unbroken sequence of hydroxyl units is necessary for activity. These results highlight that, although hydrophobic domains are key components of IRI activity, the random inclusion of addition hydrophobic units does not guarantee an increase in activity and that the actual polymer conformation is important.

Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling.

PubMed

Vlot, Anna H C; de Witte, Wilhelmus E A; Danhof, Meindert; van der Graaf, Piet H; van Westen, Gerard J P; de Lange, Elizabeth C M

2017-12-04

Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K D ) and the target dissociation rate constant on target and tissue selectivity. The K D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ 8 -tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K D and k off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K D value is often not the lowest K D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

QSAR models for predicting octanol/water and organic carbon/water partition coefficients of polychlorinated biphenyls.

PubMed

Yu, S; Gao, S; Gan, Y; Zhang, Y; Ruan, X; Wang, Y; Yang, L; Shi, J

2016-04-01

Quantitative structure-property relationship modelling can be a valuable alternative method to replace or reduce experimental testing. In particular, some endpoints such as octanol-water (KOW) and organic carbon-water (KOC) partition coefficients of polychlorinated biphenyls (PCBs) are easier to predict and various models have been already developed. In this paper, two different methods, which are multiple linear regression based on the descriptors generated using Dragon software and hologram quantitative structure-activity relationships, were employed to predict suspended particulate matter (SPM) derived log KOC and generator column, shake flask and slow stirring method derived log KOW values of 209 PCBs. The predictive ability of the derived models was validated using a test set. The performances of all these models were compared with EPI Suite™ software. The results indicated that the proposed models were robust and satisfactory, and could provide feasible and promising tools for the rapid assessment of the SPM derived log KOC and generator column, shake flask and slow stirring method derived log KOW values of PCBs.

Active cell mechanics: Measurement and theory.

PubMed

Ahmed, Wylie W; Fodor, Étienne; Betz, Timo

2015-11-01

Living cells are active mechanical systems that are able to generate forces. Their structure and shape are primarily determined by biopolymer filaments and molecular motors that form the cytoskeleton. Active force generation requires constant consumption of energy to maintain the nonequilibrium activity to drive organization and transport processes necessary for their function. To understand this activity it is necessary to develop new approaches to probe the underlying physical processes. Active cell mechanics incorporates active molecular-scale force generation into the traditional framework of mechanics of materials. This review highlights recent experimental and theoretical developments towards understanding active cell mechanics. We focus primarily on intracellular mechanical measurements and theoretical advances utilizing the Langevin framework. These developing approaches allow a quantitative understanding of nonequilibrium mechanical activity in living cells. This article is part of a Special Issue entitled: Mechanobiology. Copyright © 2015. Published by Elsevier B.V.

Deep Eutectic Solvents as Convenient Media for Synthesis of Novel Coumarinyl Schiff Bases and Their QSAR Studies.

PubMed

Molnar, Maja; Komar, Mario; Brahmbhatt, Harshad; Babić, Jurislav; Jokić, Stela; Rastija, Vesna

2017-09-05

Deep eutectic solvents, as green and environmentally friendly media, were utilized in the synthesis of novel coumarinyl Schiff bases. Novel derivatives were synthesized from 2-((4-methyl-2-oxo-2 H -chromen-7-yl)oxy)acetohydrazide and corresponding aldehyde in choline chloride:malonic acid (1:1) based deep eutectic solvent. In these reactions, deep eutectic solvent acted as a solvent and catalyst as well. Novel Schiff bases were synthesized in high yields (65-75%) with no need for further purification, and their structures were confirmed by mass spectra, ¹H and 13 C NMR. Furthermore, their antioxidant activity was determined and compared to antioxidant activity of previously synthesized derivatives, thus investigating their structure-activity relationship utilizing quantitative structure-activity relationship QSAR studies. Calculation of molecular descriptors has been performed by DRAGON software. The best QSAR model ( R tr = 0.636; R ext = 0.709) obtained with three descriptors ( MATS3m , Mor22u , Hy ) implies that the pairs of atoms higher mass at the path length 3, three-dimensional arrangement of atoms at scattering parameter s = 21 Å - ¹, and higher number of hydrophilic groups (-OH, -NH) enhanced antioxidant activity. Electrostatic potential surface of the most active compounds showed possible regions for donation of electrons to 1,1-diphenyl-2-picryhydrazyl (DPPH) radicals.

Discrete Fourier Transform-Based Multivariate Image Analysis: Application to Modeling of Aromatase Inhibitory Activity.

PubMed

Barigye, Stephen J; Freitas, Matheus P; Ausina, Priscila; Zancan, Patricia; Sola-Penna, Mauro; Castillo-Garit, Juan A

2018-02-12

We recently generalized the formerly alignment-dependent multivariate image analysis applied to quantitative structure-activity relationships (MIA-QSAR) method through the application of the discrete Fourier transform (DFT), allowing for its application to noncongruent and structurally diverse chemical compound data sets. Here we report the first practical application of this method in the screening of molecular entities of therapeutic interest, with human aromatase inhibitory activity as the case study. We developed an ensemble classification model based on the two-dimensional (2D) DFT MIA-QSAR descriptors, with which we screened the NCI Diversity Set V (1593 compounds) and obtained 34 chemical compounds with possible aromatase inhibitory activity. These compounds were docked into the aromatase active site, and the 10 most promising compounds were selected for in vitro experimental validation. Of these compounds, 7419 (nonsteroidal) and 89 201 (steroidal) demonstrated satisfactory antiproliferative and aromatase inhibitory activities. The obtained results suggest that the 2D-DFT MIA-QSAR method may be useful in ligand-based virtual screening of new molecular entities of therapeutic utility.

Understanding Cytokine and Growth Factor Receptor Activation Mechanisms

PubMed Central

Atanasova, Mariya; Whitty, Adrian

2012-01-01

Our understanding of the detailed mechanism of action of cytokine and growth factor receptors – and particularly our quantitative understanding of the link between structure, mechanism and function – lags significantly behind our knowledge of comparable functional protein classes such as enzymes, G protein-coupled receptors, and ion channels. In particular, it remains controversial whether such receptors are activated by a mechanism of ligand-induced oligomerization, versus a mechanism in which the ligand binds to a pre-associated receptor dimer or oligomer that becomes activated through subsequent conformational rearrangement. A major limitation to progress has been the relative paucity of methods for performing quantitative mechanistic experiments on unmodified receptors expressed at endogenous levels on live cells. In this article we review the current state of knowledge on the activation mechanisms of cytokine and growth factor receptors, critically evaluate the evidence for and against the different proposed mechanisms, and highlight other key questions that remain unanswered. New approaches and techniques have led to rapid recent progress in this area, and the field is poised for major advances in the coming years, which promises to revolutionize our understanding of this large and biologically and medically important class of receptors. PMID:23046381

In silico quantitative structure-toxicity relationship study of aromatic nitro compounds.

PubMed

Pasha, Farhan Ahmad; Neaz, Mohammad Morshed; Cho, Seung Joo; Ansari, Mohiuddin; Mishra, Sunil Kumar; Tiwari, Sharvan

2009-05-01

Small molecules often have toxicities that are a function of molecular structural features. Minor variations in structural features can make large difference in such toxicity. Consequently, in silico techniques may be used to correlate such molecular toxicities with their structural features. Relative to nine different sets of aromatic nitro compounds having known observed toxicities against different targets, we developed ligand-based 2D quantitative structure-toxicity relationship models using 20 selected topological descriptors. The topological descriptors have several advantages such as conformational independency, facile and less time-consuming computation to yield good results. Multiple linear regression analysis was used to correlate variations of toxicity with molecular properties. The information index on molecular size, lopping centric index and Kier flexibility index were identified as fundamental descriptors for different kinds of toxicity, and further showed that molecular size, branching and molecular flexibility might be particularly important factors in quantitative structure-toxicity relationship analysis. This study revealed that topological descriptor-guided quantitative structure-toxicity relationship provided a very useful, cost and time-efficient, in silico tool for describing small-molecule toxicities.

History of EPI Suite™ and future perspectives on chemical property estimation in US Toxic Substances Control Act new chemical risk assessments.

PubMed

Card, Marcella L; Gomez-Alvarez, Vicente; Lee, Wen-Hsiung; Lynch, David G; Orentas, Nerija S; Lee, Mari Titcombe; Wong, Edmund M; Boethling, Robert S

2017-03-22

Chemical property estimation is a key component in many industrial, academic, and regulatory activities, including in the risk assessment associated with the approximately 1000 new chemical pre-manufacture notices the United States Environmental Protection Agency (US EPA) receives annually. The US EPA evaluates fate, exposure and toxicity under the 1976 Toxic Substances Control Act (amended by the 2016 Frank R. Lautenberg Chemical Safety for the 21 st Century Act), which does not require test data with new chemical applications. Though the submission of data is not required, the US EPA has, over the past 40 years, occasionally received chemical-specific data with pre-manufacture notices. The US EPA has been actively using this and publicly available data to develop and refine predictive computerized models, most of which are housed in EPI Suite™, to estimate chemical properties used in the risk assessment of new chemicals. The US EPA develops and uses models based on (quantitative) structure-activity relationships ([Q]SARs) to estimate critical parameters. As in any evolving field, (Q)SARs have experienced successes, suffered failures, and responded to emerging trends. Correlations of a chemical structure with its properties or biological activity were first demonstrated in the late 19 th century and today have been encapsulated in a myriad of quantitative and qualitative SARs. The development and proliferation of the personal computer in the late 20 th century gave rise to a quickly increasing number of property estimation models, and continually improved computing power and connectivity among researchers via the internet are enabling the development of increasingly complex models.

Comparison of the applicability domain of a quantitative structure-activity relationship for estrogenicity with a large chemical inventory.

PubMed

Netzeva, Tatiana I; Gallegos Saliner, Ana; Worth, Andrew P

2006-05-01

The aim of the present study was to illustrate that it is possible and relatively straightforward to compare the domain of applicability of a quantitative structure-activity relationship (QSAR) model in terms of its physicochemical descriptors with a large inventory of chemicals. A training set of 105 chemicals with data for relative estrogenic gene activation, obtained in a recombinant yeast assay, was used to develop the QSAR. A binary classification model for predicting active versus inactive chemicals was developed using classification tree analysis and two descriptors with a clear physicochemical meaning (octanol-water partition coefficient, or log Kow, and the number of hydrogen bond donors, or n(Hdon)). The model demonstrated a high overall accuracy (90.5%), with a sensitivity of 95.9% and a specificity of 78.1%. The robustness of the model was evaluated using the leave-many-out cross-validation technique, whereas the predictivity was assessed using an artificial external test set composed of 12 compounds. The domain of the QSAR training set was compared with the chemical space covered by the European Inventory of Existing Commercial Chemical Substances (EINECS), as incorporated in the CDB-EC software, in the log Kow / n(Hdon) plane. The results showed that the training set and, therefore, the applicability domain of the QSAR model covers a small part of the physicochemical domain of the inventory, even though a simple method for defining the applicability domain (ranges in the descriptor space) was used. However, a large number of compounds are located within the narrow descriptor window.

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

PubMed Central

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

2009-01-01

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

Structure- and reactivity-based development of covalent inhibitors of the activating and gatekeeper mutant forms of the epidermal growth factor receptor (EGFR).

PubMed

Ward, Richard A; Anderton, Mark J; Ashton, Susan; Bethel, Paul A; Box, Matthew; Butterworth, Sam; Colclough, Nicola; Chorley, Christopher G; Chuaqui, Claudio; Cross, Darren A E; Dakin, Les A; Debreczeni, Judit É; Eberlein, Cath; Finlay, M Raymond V; Hill, George B; Grist, Matthew; Klinowska, Teresa C M; Lane, Clare; Martin, Scott; Orme, Jonathon P; Smith, Peter; Wang, Fengjiang; Waring, Michael J

2013-09-12

A novel series of small-molecule inhibitors has been developed to target the double mutant form of the epidermal growth factor receptor (EGFR) tyrosine kinase, which is resistant to treatment with gefitinib and erlotinib. Our reported compounds also show selectivity over wild-type EGFR. Guided by molecular modeling, this series was evolved to target a cysteine residue in the ATP binding site via covalent bond formation and demonstrates high levels of activity in cellular models of the double mutant form of EGFR. In addition, these compounds show significant activity against the activating mutations, which gefitinib and erlotinib target and inhibition of which gives rise to their observed clinical efficacy. A glutathione (GSH)-based assay was used to measure thiol reactivity toward the electrophilic functionality of the inhibitor series, enabling both the identification of a suitable reactivity window for their potency and the development of a reactivity quantitative structure-property relationship (QSPR) to support design.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Asymmetric bagging and feature selection for activities prediction of drug molecules.

PubMed

Li, Guo-Zheng; Meng, Hao-Hua; Lu, Wen-Cong; Yang, Jack Y; Yang, Mary Qu

2008-05-28

Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cycle by employing the traditional experimental method. With the fact that the number of drug molecules with positive activity is rather fewer than that of negatives, it is important to predict molecular activities considering such an unbalanced situation. Here, asymmetric bagging and feature selection are introduced into the problem and asymmetric bagging of support vector machines (asBagging) is proposed on predicting drug activities to treat the unbalanced problem. At the same time, the features extracted from the structures of drug molecules affect prediction accuracy of QSAR models. Therefore, a novel algorithm named PRIFEAB is proposed, which applies an embedded feature selection method to remove redundant and irrelevant features for asBagging. Numerical experimental results on a data set of molecular activities show that asBagging improve the AUC and sensitivity values of molecular activities and PRIFEAB with feature selection further helps to improve the prediction ability. Asymmetric bagging can help to improve prediction accuracy of activities of drug molecules, which can be furthermore improved by performing feature selection to select relevant features from the drug molecules data sets.

Applications of High-Nitrogen Energetics in Pyrotechnics: Development of Perchlorate-Free Red Star M126A1 Hand-Held Signal Formulations with Superior Luminous Intensities and Burn Times

DTIC Science & Technology

2011-03-25

short-term administration of 3-amino- triazole. The US Army Public Health Command has stated that quantitative structure activity relationship ( QSAR ...modeling is not a useful tool in determining the toxic nature of high nitrogen salts such as bis-tetrazolate 1. Therefore, no data on the toxicology of

Prediction of Physicochemical Properties of Energetic Materials for Identification of Treatment Technologies for Waste Streams

DTIC Science & Technology

2010-11-01

estimate the pharmacokinetics of potential drugs (Horning and Klamt 2005). QSPR/ QSARs also have potential applications in the fuel science field...group contribution methods, and (2) quantitative structure-property/activity relationships (QSPR/ QSAR ). The group contribution methods are primarily...development of QSPR/ QSARs is the identification of the ap- propriate set of descriptors that allow the desired attribute of the compound to be adequately

Next-Generation Fire Extinguishing Agent. Phase 4. Foundation for New Training Agent Development

DTIC Science & Technology

1989-12-01

Administration PCE perchloroethylene PEL Permissible Exposure Limit QSAR Quantitative Structure Activity Relationship SBUV Solar Backscatter Ultraviolet xi...can pass through the troposphere without destruction to enter the stratosphere. In the stratosphere, they photolyze in the intense solar radiation to...radiation, UV-B, striking the earth. Preliminary data from a Solar Backscatter Ultraviolet (SBUV) instrument aboard NASA’s Nimbus 7 satellite show a

[Synthesis of amino acids of Bacillus subtilis IMV V-7023 in the medium with glycerophosphates].

PubMed

Tserkovniak, L S; Roĭ, A O; Kurdysh, I K

2009-01-01

It was shown that under cultivation of Bacillus subtilis IMVV-7023 in the nutrient medium with glycerophosphate biologically active substances are accumulated in the culture liquid. They influence positively the seeds growth and formation of plant germs. The bacteria synthesize amino acids in this medium, their quantitative structure differs from the type of carbon nutrition and cultivation time of the cells.

Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods.

PubMed

Li, Mengshan; Zhang, Huaijing; Chen, Bingsheng; Wu, Yan; Guan, Lixin

2018-03-05

The pKa value of drugs is an important parameter in drug design and pharmacology. In this paper, an improved particle swarm optimization (PSO) algorithm was proposed based on the population entropy diversity. In the improved algorithm, when the population entropy was higher than the set maximum threshold, the convergence strategy was adopted; when the population entropy was lower than the set minimum threshold the divergence strategy was adopted; when the population entropy was between the maximum and minimum threshold, the self-adaptive adjustment strategy was maintained. The improved PSO algorithm was applied in the training of radial basis function artificial neural network (RBF ANN) model and the selection of molecular descriptors. A quantitative structure-activity relationship model based on RBF ANN trained by the improved PSO algorithm was proposed to predict the pKa values of 74 kinds of neutral and basic drugs and then validated by another database containing 20 molecules. The validation results showed that the model had a good prediction performance. The absolute average relative error, root mean square error, and squared correlation coefficient were 0.3105, 0.0411, and 0.9685, respectively. The model can be used as a reference for exploring other quantitative structure-activity relationships.

From QSAR to QSIIR: Searching for Enhanced Computational Toxicology Models

PubMed Central

Zhu, Hao

2017-01-01

Quantitative Structure Activity Relationship (QSAR) is the most frequently used modeling approach to explore the dependency of biological, toxicological, or other types of activities/properties of chemicals on their molecular features. In the past two decades, QSAR modeling has been used extensively in drug discovery process. However, the predictive models resulted from QSAR studies have limited use for chemical risk assessment, especially for animal and human toxicity evaluations, due to the low predictivity of new compounds. To develop enhanced toxicity models with independently validated external prediction power, novel modeling protocols were pursued by computational toxicologists based on rapidly increasing toxicity testing data in recent years. This chapter reviews the recent effort in our laboratory to incorporate the biological testing results as descriptors in the toxicity modeling process. This effort extended the concept of QSAR to Quantitative Structure In vitro-In vivo Relationship (QSIIR). The QSIIR study examples provided in this chapter indicate that the QSIIR models that based on the hybrid (biological and chemical) descriptors are indeed superior to the conventional QSAR models that only based on chemical descriptors for several animal toxicity endpoints. We believe that the applications introduced in this review will be of interest and value to researchers working in the field of computational drug discovery and environmental chemical risk assessment. PMID:23086837

Designing a Quantitative Structure-Activity Relationship for the ...

EPA Pesticide Factsheets

Toxicokinetic models serve a vital role in risk assessment by bridging the gap between chemical exposure and potentially toxic endpoints. While intrinsic metabolic clearance rates have a strong impact on toxicokinetics, limited data is available for environmentally relevant chemicals including nearly 8000 chemicals tested for in vitro bioactivity in the Tox21 program. To address this gap, a quantitative structure-activity relationship (QSAR) for intrinsic metabolic clearance rate was developed to offer reliable in silico predictions for a diverse array of chemicals. Models were constructed with curated in vitro assay data for both pharmaceutical-like chemicals (ChEMBL database) and environmentally relevant chemicals (ToxCast screening) from human liver microsomes (2176 from ChEMBL) and human hepatocytes (757 from ChEMBL and 332 from ToxCast). Due to variability in the experimental data, a binned approach was utilized to classify metabolic rates. Machine learning algorithms, such as random forest and k-nearest neighbor, were coupled with open source molecular descriptors and fingerprints to provide reasonable estimates of intrinsic metabolic clearance rates. Applicability domains defined the optimal chemical space for predictions, which covered environmental chemicals well. A reduced set of informative descriptors (including relative charge and lipophilicity) and a mixed training set of pharmaceuticals and environmentally relevant chemicals provided the best intr

Functionalization of SBA-15 mesoporous silica by Cu-phosphonate units: Probing of synthesis route

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

Laskowski, Lukasz, E-mail: lukasz.laskowski@kik.pcz.pl; Czestochowa University of Technology, Institute of Physics, Al. Armii Krajowej 19, 42-201 Czestochowa; Laskowska, Magdalena, E-mail: magdalena.laskowska@onet.pl

2014-12-15

Mesoporous silica SBA-15 containing propyl-copper phosphonate units was investigated. The structure of mesoporous samples was tested by N{sub 2} isothermal sorption (BET and BHJ analysis), TEM microscopy and X-Ray scattering. Quantitative analysis EDX has given information about proportions between component atoms in the sample. Quantitative elemental analysis has been carried out to support EDX. To examine bounding between copper atoms and phosphonic units the Raman spectroscopy was carried out. As a support of Raman scattering, the theoretical calculations were made based on density functional theory, with the B3LYP method. By comparison of the calculated vibrational spectra of the molecule withmore » experimental results, distribution of the active units inside silica matrix has been determined. - Graphical abstract: The present study is devoted to mesoporous silica SBA-15 containing propyl-copper phosphonate units. The species were investigated to confirm of synthesis procedure correctness by the micro-Raman technique combined with DFT numerical simulations. Complementary research was carried out to test the structure of mesoporous samples. - Highlights: • SBA-15 silica functionalized with propyl-copper phosphonate units was synthesized. • Synthesis efficiency probed by Raman study supported with DFT simulations. • Homogenous distribution of active units was proved. • Synthesis route enables precise control of distance between copper ions.« less

A Quantitative Structure Activity Relationship for acute oral toxicity of pesticides on rats: Validation, domain of application and prediction.

PubMed

Hamadache, Mabrouk; Benkortbi, Othmane; Hanini, Salah; Amrane, Abdeltif; Khaouane, Latifa; Si Moussa, Cherif

2016-02-13

Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, we developed a validated QSAR model to predict acute oral toxicity of 329 pesticides to rats because a few QSAR models have been devoted to predict the Lethal Dose 50 (LD50) of pesticides on rats. This QSAR model is based on 17 molecular descriptors, and is robust, externally predictive and characterized by a good applicability domain. The best results were obtained with a 17/9/1 Artificial Neural Network model trained with the Quasi Newton back propagation (BFGS) algorithm. The prediction accuracy for the external validation set was estimated by the Q(2)ext and the root mean square error (RMS) which are equal to 0.948 and 0.201, respectively. 98.6% of external validation set is correctly predicted and the present model proved to be superior to models previously published. Accordingly, the model developed in this study provides excellent predictions and can be used to predict the acute oral toxicity of pesticides, particularly for those that have not been tested as well as new pesticides. Copyright © 2015 Elsevier B.V. All rights reserved.

Utilization of quantitative structure-activity relationships (QSARs) in risk assessment: Alkylphenols

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

Beck, B.D.; Toole, A.P.; Callahan, B.G.

1991-12-01

Alkylphenols are a class of environmentally pervasive compounds, found both in natural (e.g., crude oils) and in anthropogenic (e.g., wood tar, coal gasification waste) materials. Despite the frequent environmental occurrence of these chemicals, there is a limited toxicity database on alkylphenols. The authors have therefore developed a 'toxicity equivalence approach' for alkylphenols which is based on their ability to inhibit, in a specific manner, the enzyme cyclooxygenase. Enzyme-inhibiting ability for individual alkylphenols can be estimated based on the quantitative structure-activity relationship developed by Dewhirst (1980) and is a function of the free hydroxyl group, electron-donating ring substituents, and hydrophobic aromaticmore » ring substituents. The authors evaluated the toxicological significance of cyclooxygenase inhibition by comparison of the inhibitory capacity of alkylphenols with the inhibitory capacity of acetylsalicylic acid, or aspirin, a compound whose low-level effects are due to cyclooxygenase inhibition. Since nearly complete absorption for alkylphenols and aspirin is predicted, based on estimates of hydrophobicity and fraction of charged molecules at gastrointestinal pHs, risks from alkylphenols can be expressed directly in terms of 'milligram aspirin equivalence,' without correction for absorption differences. They recommend this method for assessing risks of mixtures of alkylphenols, especially for those compounds with no chronic toxicity data.38 references.« less

Predicting human skin absorption of chemicals: development of a novel quantitative structure activity relationship.

PubMed

Luo, Wen; Medrek, Sarah; Misra, Jatin; Nohynek, Gerhard J

2007-02-01

The objective of this study was to construct and validate a quantitative structure-activity relationship model for skin absorption. Such models are valuable tools for screening and prioritization in safety and efficacy evaluation, and risk assessment of drugs and chemicals. A database of 340 chemicals with percutaneous absorption was assembled. Two models were derived from the training set consisting 306 chemicals (90/10 random split). In addition to the experimental K(ow) values, over 300 2D and 3D atomic and molecular descriptors were analyzed using MDL's QsarIS computer program. Subsequently, the models were validated using both internal (leave-one-out) and external validation (test set) procedures. Using the stepwise regression analysis, three molecular descriptors were determined to have significant statistical correlation with K(p) (R2 = 0.8225): logK(ow), X0 (quantification of both molecular size and the degree of skeletal branching), and SsssCH (count of aromatic carbon groups). In conclusion, two models to estimate skin absorption were developed. When compared to other skin absorption QSAR models in the literature, our model incorporated more chemicals and explored a large number of descriptors. Additionally, our models are reasonably predictive and have met both internal and external statistical validations.

Local structure in LaMnO3 and CaMnO3 perovskites: A quantitative structural refinement of Mn K -edge XANES data

NASA Astrophysics Data System (ADS)

Monesi, C.; Meneghini, C.; Bardelli, F.; Benfatto, M.; Mobilio, S.; Manju, U.; Sarma, D. D.

2005-11-01

Hole-doped perovskites such as La1-xCaxMnO3 present special magnetic and magnetotransport properties, and it is commonly accepted that the local atomic structure around Mn ions plays a crucial role in determining these peculiar features. Therefore experimental techniques directly probing the local atomic structure, like x-ray absorption spectroscopy (XAS), have been widely exploited to deeply understand the physics of these compounds. Quantitative XAS analysis usually concerns the extended region [extended x-ray absorption fine structure (EXAFS)] of the absorption spectra. The near-edge region [x-ray absorption near-edge spectroscopy (XANES)] of XAS spectra can provide detailed complementary information on the electronic structure and local atomic topology around the absorber. However, the complexity of the XANES analysis usually prevents a quantitative understanding of the data. This work exploits the recently developed MXAN code to achieve a quantitative structural refinement of the Mn K -edge XANES of LaMnO3 and CaMnO3 compounds; they are the end compounds of the doped manganite series LaxCa1-xMnO3 . The results derived from the EXAFS and XANES analyses are in good agreement, demonstrating that a quantitative picture of the local structure can be obtained from XANES in these crystalline compounds. Moreover, the quantitative XANES analysis provides topological information not directly achievable from EXAFS data analysis. This work demonstrates that combining the analysis of extended and near-edge regions of Mn K -edge XAS spectra could provide a complete and accurate description of Mn local atomic environment in these compounds.

Assessment and monitoring of forest ecosystem structure

Treesearch

Oscar A. Aguirre Calderón; Javier Jiménez Pérez; Horst Kramer

2006-01-01

Characterization of forest ecosystems structure must be based on quantitative indices that allow objective analysis of human influences or natural succession processes. The objective of this paper is the compilation of diverse quantitative variables to describe structural attributes from the arboreal stratum of the ecosystem, as well as different methods of forest...

The Effects of Structured Physical Activity Program on Social Interaction and Communication for Children with Autism

PubMed Central

Zhao, Mengxian

2018-01-01

The purpose of this study was to investigate the effects of structured physical activity program on social interaction and communication of children with autism spectrum disorder (ASD). Fifty children with ASD from a special school were randomly divided into experimental and control groups. 25 children with ASD were placed in the experimental group, and the other 25 children as the control group participated in regular physical activity. A total of forty-one participants completed the study. A 12-week structured physical activity program was implemented with a total of 24 exercise sessions targeting social interaction and communication of children with ASD, and a quasi-experimental design was used for this study. Data were collected using quantitative and qualitative instruments. SSIS and ABLLS-R results showed that an overall improvement in social skills and social interaction for the experimental group across interim and posttests, F = 8.425, p = 0.001 (p < 0.005), and significant improvements appeared in communication, cooperation, social interaction, and self-control subdomains (p < 0.005). Conversely, no statistically significant differences were found in the control group (p > 0.005). The study concluded that the special structured physical activity program positively influenced social interaction and communication skills of children with ASD, especially in social skills, communication, prompt response, and frequency of expression. PMID:29568743

Structural and functional changes during epileptogenesis in the mouse model of medial temporal lobe epilepsy.

PubMed

Dietrich, Yvan; Eliat, Pierre-Antoine; Dieuset, Gabriel; Saint-Jalmes, Herve; Pineau, Charles; Wendling, Fabrice; Martin, Benoit

2016-08-01

An important issue in epilepsy research is to understand the structural and functional modifications leading to chronic epilepsy, characterized by spontaneous recurrent seizures, after initial brain insult. To address this issue, we recorded and analyzed electroencephalography (EEG) and quantitative magnetic resonance imaging (MRI) data during epileptogenesis in the in vivo mouse model of Medial Temporal Lobe Epilepsy (MTLE, kainate). Besides, this model of epilepsy is a particular form of drug-resistant epilepsy. The results indicate that high-field (4.7T) MRI parameters (T2-weighted; T2-quantitative) allow to detect the gradual neuro-anatomical changes that occur during epileptogenesis while electrophysiological parameters (number and duration of Hippocampal Paroxysmal Discharges) allow to assess the dysfunctional changes through the quantification of epileptiform activity. We found a strong correlation between EEG-based markers (invasive recording) and MRI-based parameters (non-invasive) periodically computed over the `latent period' that spans over two weeks, on average. These results indicated that both structural and functional changes occur in the considered epilepsy model and are considered as biomarkers of the installation of epilepsy. Additionally, such structural and functional changes can also be observed in human temporal lobe epilepsy. Interestingly, MRI imaging parameters could be used to track early (day-7) structural changes (gliosis, cell loss) in the lesioned brain and to quantify the evolution of epileptogenesis after traumatic brain injury.

A Mechanism-based 3D-QSAR Approach for Classification ...

EPA Pesticide Factsheets

Organophosphate (OP) and carbamate esters can inhibit acetylcholinesterase (AChE) by binding covalently to a serine residue in the enzyme active site, and their inhibitory potency depends largely on affinity for the enzyme and the reactivity of the ester. Despite this understanding, there has been no mechanism-based in silico approach for classification and prediction of the inhibitory potency of ether OPs or carbamates. This prompted us to develop a three dimensional prediction framework for OPs, carbamates, and their analogs. Inhibitory structures of a compound that can form the covalent bond were identified through analysis of docked conformations of the compound and its metabolites. Inhibitory potencies of the selected structures were then predicted using a previously developed three dimensional quantitative structure-active relationship. This approach was validated with a large number of structurally diverse OP and carbamate compounds encompassing widely used insecticides and structural analogs including OP flame retardants and thio- and dithiocarbamate pesticides. The modeling revealed that: (1) in addition to classical OP metabolic activation, the toxicity of carbamate compounds can be dependent on biotransformation, (2) OP and carbamate analogs such as OP flame retardants and thiocarbamate herbicides can act as AChEI, (3) hydrogen bonds at the oxyanion hole is critical for AChE inhibition through the covalent bond, and (4) π–π interaction with Trp86

Simultaneous structure-activity studies and arming of natural products by C-H amination reveal cellular targets of eupalmerin acetate.

PubMed

Li, Jing; Cisar, Justin S; Zhou, Cong-Ying; Vera, Brunilda; Williams, Howard; Rodríguez, Abimael D; Cravatt, Benjamin F; Romo, Daniel

2013-06-01

Natural products have a venerable history of, and enduring potential for the discovery of useful biological activity. To fully exploit this, the development of chemical methodology that can functionalize unique sites within these complex structures is highly desirable. Here, we describe the use of rhodium(II)-catalysed C-H amination reactions developed by Du Bois to carry out simultaneous structure-activity relationship studies and arming (alkynylation) of natural products at 'unfunctionalized' positions. Allylic and benzylic C-H bonds in the natural products undergo amination while olefins undergo aziridination, and tertiary amine-containing natural products are converted to amidines by a C-H amination-oxidation sequence or to hydrazine sulfamate zwitterions by an unusual N-amination. The alkynylated derivatives are ready for conversion into cellular probes that can be used for mechanism-of-action studies. Chemo- and site-selectivity was studied with a diverse library of natural products. For one of these-the marine-derived anticancer diterpene, eupalmerin acetate-quantitative proteome profiling led to the identification of several protein targets in HL-60 cells, suggesting a polypharmacological mode of action.

Simultaneous structure-activity studies and arming of natural products by C-H amination reveal cellular targets of eupalmerin acetate

NASA Astrophysics Data System (ADS)

Li, Jing; Cisar, Justin S.; Zhou, Cong-Ying; Vera, Brunilda; Williams, Howard; Rodríguez, Abimael D.; Cravatt, Benjamin F.; Romo, Daniel

2013-06-01

Natural products have a venerable history of, and enduring potential for the discovery of useful biological activity. To fully exploit this, the development of chemical methodology that can functionalize unique sites within these complex structures is highly desirable. Here, we describe the use of rhodium(II)-catalysed C-H amination reactions developed by Du Bois to carry out simultaneous structure-activity relationship studies and arming (alkynylation) of natural products at ‘unfunctionalized’ positions. Allylic and benzylic C-H bonds in the natural products undergo amination while olefins undergo aziridination, and tertiary amine-containing natural products are converted to amidines by a C-H amination-oxidation sequence or to hydrazine sulfamate zwitterions by an unusual N-amination. The alkynylated derivatives are ready for conversion into cellular probes that can be used for mechanism-of-action studies. Chemo- and site-selectivity was studied with a diverse library of natural products. For one of these—the marine-derived anticancer diterpene, eupalmerin acetate—quantitative proteome profiling led to the identification of several protein targets in HL-60 cells, suggesting a polypharmacological mode of action.

Mechanism of Formation of the Major Estradiol Product Ions Following Collisional Activation of the Molecular Anion in a Tandem Quadrupole Mass Spectrometer

NASA Astrophysics Data System (ADS)

Wooding, Kerry M.; Barkley, Robert M.; Hankin, Joseph A.; Johnson, Christopher A.; Bradford, Andrew P.; Santoro, Nanette; Murphy, Robert C.

2013-10-01

The importance of the mass spectral product ion structure is highlighted in quantitative assays, which typically use multiple reaction monitoring (MRM), and in the discovery of novel metabolites. Estradiol is an important sex steroid whose quantitation and metabolite identification using tandem mass spectrometry has been widely employed in numerous clinical studies. Negative electrospray ionization tandem mass spectrometry of estradiol (E2) results in several product ions, including the abundant m/z 183 and 169. Although m/z 183 is one of the most abundant product ions used in many quantitative assays, the structure of m/z 183 has not been rigorously examined. We suggest a structure for m/z 183 and a mechanism of formation consistent with collision induced dissociation (CID) of E2 and several stable isotopes ([D4]-E2, [13C6]-E2, and [D1]-E2). An additional product ion from E2, namely m/z 169, has also been examined. MS3 experiments indicated that both m/z 183 and m/z 169 originate from only E2 [M - H]- m/z 271. These ions, m/z 183 and m/z 169, were also present in the collision induced decomposition mass spectra of other prominent estrogens, estrone (E1) and estriol (E3), indicating that these two product ions could be used to elucidate the estrogenic origin of novel metabolites. We propose two fragmentation schemes to explain the CID data and suggest a structure of m/z 183 and m/z 169 consistent with several isotopic variants and high resolution mass spectrometric measurements.

Chiral monolithic absorbent constructed by optically active helical-substituted polyacetylene and graphene oxide: preparation and chiral absorption capacity.

PubMed

Li, Weifei; Wang, Bo; Yang, Wantai; Deng, Jianping

2015-02-01

Chiral monolithic absorbent is successfully constructed for the first time by using optically active helical-substituted polyacetylene and graphene oxide (GO). The preparative strategy is facile and straightforward, in which chiral-substituted acetylene monomer (Ma), cross-linker (Mb), and alkynylated GO (Mc) undergo copolymerization to form the desired monolithic absorbent in quantitative yield. The resulting monoliths are characterized by circular dichroism, UV-vis absorption, scanning electron microscopy (SEM), FT-IR, Raman, energy-dispersive spectrometer (EDS), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET), XPS, and thermogravimetric analysis (TGA) techniques. The polymer chains derived from Ma form chiral helical structures and thus provide optical activity to the monoliths, while GO sheets contribute to the formation of porous structures. The porous structure enables the monolithic absorbents to demonstrate a large swelling ratio in organic solvents, and more remarkably, the helical polymer chains provide optical activity and further enantio-differentiating absorption ability. The present study establishes an efficient and versatile methodology for preparing novel functional materials, in particular monolithic chiral materials based on substituted polyacetylene and GO. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hyaluronidase Inhibitory Activity of Pentacylic Triterpenoids from Prismatomeris tetrandra (Roxb.) K. Schum: Isolation, Synthesis and QSAR Study

PubMed Central

Abdullah, Nor Hayati; Thomas, Noel Francis; Sivasothy, Yasodha; Lee, Vannajan Sanghiran; Liew, Sook Yee; Noorbatcha, Ibrahim Ali; Awang, Khalijah

2016-01-01

The mammalian hyaluronidase degrades hyaluronic acid by the cleavage of the β-1,4-glycosidic bond furnishing a tetrasaccharide molecule as the main product which is a highly angiogenic and potent inducer of inflammatory cytokines. Ursolic acid 1, isolated from Prismatomeris tetrandra, was identified as having the potential to develop inhibitors of hyaluronidase. A series of ursolic acid analogues were either synthesized via structure modification of ursolic acid 1 or commercially obtained. The evaluation of the inhibitory activity of these compounds on the hyaluronidase enzyme was conducted. Several structural, topological and quantum chemical descriptors for these compounds were calculated using semi empirical quantum chemical methods. A quantitative structure activity relationship study (QSAR) was performed to correlate these descriptors with the hyaluronidase inhibitory activity. The statistical characteristics provided by the best multi linear model (BML) (R2 = 0.9717, R2cv = 0.9506) indicated satisfactory stability and predictive ability of the developed model. The in silico molecular docking study which was used to determine the binding interactions revealed that the ursolic acid analog 22 had a strong affinity towards human hyaluronidase. PMID:26907251

A cellular system for quantitation of vitamin K cycle activity: structure-activity effects on vitamin K antagonism by warfarin metabolites

PubMed Central

Haque, Jamil A.; McDonald, Matthew G.; Kulman, John D.

2014-01-01

Warfarin and other 4-hydroxycoumarins inhibit vitamin K epoxide reductase (VKOR) by depleting reduced vitamin K that is required for posttranslational modification of vitamin K–dependent clotting factors. In vitro prediction of the in vivo potency of vitamin K antagonists is complicated by the complex multicomponent nature of the vitamin K cycle. Here we describe a sensitive assay that enables quantitative analysis of γ-glutamyl carboxylation and its antagonism in live cells. We engineered a human embryonic kidney (HEK) 293–derived cell line (HEK 293-C3) to express a chimeric protein (F9CH) comprising the Gla domain of factor IX fused to the transmembrane and cytoplasmic regions of proline-rich Gla protein 2. Maximal γ-glutamyl carboxylation of F9CH required vitamin K supplementation, and was dose-dependently inhibited by racemic warfarin at a physiologically relevant concentration. Cellular γ-glutamyl carboxylation also exhibited differential VKOR inhibition by warfarin enantiomers (S > R) consistent with their in vivo potencies. We further analyzed the structure-activity relationship for inhibition of γ-glutamyl carboxylation by warfarin metabolites, observing tolerance to phenolic substitution at the C-5 and especially C-6, but not C-7 or C-8, positions on the 4-hydroxycoumarin nucleus. After correction for in vivo concentration and protein binding, 10-hydroxywarfarin and warfarin alcohols were predicted to be the most potent inhibitory metabolites in vivo. PMID:24297869

Measuring the Internal Structure and Physical Conditions in Star and Planet Forming Clouds Cores: Towards a Quantitative Description of Cloud Evolution

NASA Technical Reports Server (NTRS)

Lada, Charles J.

2004-01-01

This grant funds a research program to use infrared extinction measurements to probe the detailed structure of dark molecular cloud cores and investigate the physical conditions which give rise to star and planet formation. The goals of this program are to acquire, reduce and analyze deep infrared and molecular-line observations of a carefully selected sample of nearby dark clouds in order to determine the detailed initial conditions for star formation from quantitative measurements of the internal structure of starless cloud cores and to quantitatively investigate the evolution of such structure through the star and planet formation process.

CLICK: The new USGS center for LIDAR information coordination and knowledge

USGS Publications Warehouse

Stoker, Jason M.; Greenlee, Susan K.; Gesch, Dean B.; Menig, Jordan C.

2006-01-01

Elevation data is rapidly becoming an important tool for the visualization and analysis of geographic information. The creation and display of three-dimensional models representing bare earth, vegetation, and structures have become major requirements for geographic research in the past few years. Light Detection and Ranging (lidar) has been increasingly accepted as an effective and accurate technology for acquiring high-resolution elevation data for bare earth, vegetation, and structures. Lidar is an active remote sensing system that records the distance, or range, of a laser fi red from an airborne or space borne platform such as an airplane, helicopter or satellite to objects or features on the Earth’s surface. By converting lidar data into bare ground topography and vegetation or structural morphologic information, extremely accurate, high-resolution elevation models can be derived to visualize and quantitatively represent scenes in three dimensions. In addition to high-resolution digital elevation models (Evans et al., 2001), other lidar-derived products include quantitative estimates of vegetative features such as canopy height, canopy closure, and biomass (Lefsky et al., 2002), and models of urban areas such as building footprints and three-dimensional city models (Maas, 2001).

Interactions of Indole Derivatives with β-Cyclodextrin: A Quantitative Structure-Property Relationship Study

PubMed Central

Šoškić, Milan; Porobić, Ivana

2016-01-01

Retention factors for 31 indole derivatives, most of them with auxin activity, were determined by high-performance liquid chromatography, using bonded β-cyclodextrin as a stationary phase. A three-parameter QSPR (quantitative structure-property relationship) model, based on physico-chemical and structural descriptors was derived, which accounted for about 98% variations in the retention factors. The model suggests that the indole nucleus occupies the relatively apolar cavity of β-cyclodextrin while the carboxyl group of the indole -3-carboxylic acids makes hydrogen bonds with the hydroxyl groups of β-cyclodextrin. The length and flexibility of the side chain containing carboxyl group strongly affect the binding of these compounds to β-cyclodextrin. Non-acidic derivatives, unlike the indole-3-carboxylic acids, are poorly retained on the column. A reasonably well correlation was found between the retention factors of the indole-3-acetic acids and their relative binding affinities for human serum albumin, a carrier protein in the blood plasma. A less satisfactory correlation was obtained when the retention factors of the indole derivatives were compared with their affinities for auxin-binding protein 1, a plant auxin receptor. PMID:27124734

A novel structure-based multimode QSAR method affords predictive models for phosphodiesterase inhibitors.

PubMed

Dong, Xialan; Ebalunode, Jerry O; Cho, Sung Jin; Zheng, Weifan

2010-02-22

Quantitative structure-activity relationship (QSAR) methods aim to build quantitatively predictive models for the discovery of new molecules. It has been widely used in medicinal chemistry for drug discovery. Many QSAR techniques have been developed since Hansch's seminal work, and more are still being developed. Motivated by Hopfinger's receptor-dependent QSAR (RD-QSAR) formalism and the Lukacova-Balaz scheme to treat multimode issues, we have initiated studies that focus on a structure-based multimode QSAR (SBMM QSAR) method, where the structure of the target protein is used in characterizing the ligand, and the multimode issue of ligand binding is systematically treated with a modified Lukacova-Balaz scheme. All ligand molecules are first docked to the target binding pocket to obtain a set of aligned ligand poses. A structure-based pharmacophore concept is adopted to characterize the binding pocket. Specifically, we represent the binding pocket as a geometric grid labeled by pharmacophoric features. Each pose of the ligand is also represented as a labeled grid, where each grid point is labeled according to the atom types of nearby ligand atoms. These labeled grids or three-dimensional (3D) maps (both the receptor map (R-map) and the ligand map (L-map)) are compared to each other to derive descriptors for each pose of the ligand, resulting in a multimode structure-activity relationship (SAR) table. Iterative partial least-squares (PLS) is employed to build the QSAR models. When we applied this method to analyze PDE-4 inhibitors, predictive models have been developed, obtaining models with excellent training correlation (r(2) = 0.65-0.66), as well as test correlation (R(2) = 0.64-0.65). A comparative analysis with 4 other QSAR techniques demonstrates that this new method affords better models, in terms of the prediction power for the test set.

An Extended Structure-Activity Relationship of Nondioxin-Like PCBs Evaluates and Supports Modeling Predictions and Identifies Picomolar Potency of PCB 202 Towards Ryanodine Receptors.

PubMed

Holland, Erika B; Feng, Wei; Zheng, Jing; Dong, Yao; Li, Xueshu; Lehmler, Hans-Joachim; Pessah, Isaac N

2017-01-01

Nondioxin-like polychlorinated biphenyls (NDL PCBs) activate ryanodine-sensitive Ca 2+  channels (RyRs) and this activation has been associated with neurotoxicity in exposed animals. RyR-active congeners follow a distinct structure-activity relationship and a quantitative structure-activity relationship (QSAR) predicts that a large number of PCBs likely activate the receptor, which requires validation. Additionally, previous structural based conclusions have been established using receptor ligand binding assays but the impact of varying PCB structures on ion channel gating behavior is not understood. We used [ 3 H]Ryanodine ([ 3 H]Ry) binding to assess the RyR-activity of 14 previously untested PCB congeners evaluating the predictability of the QSAR. Congeners determined to display widely varying potency were then assayed with single channel voltage clamp analysis to assess direct influences on channel gating kinetics. The RyR-activity of individual PCBs assessed in in vitro assays followed the general pattern predicted by the QSAR but binding and lipid bilayer experiments demonstrated higher potency than predicted. Of the 49 congeners tested to date, tetra-ortho PCB 202 was found to be the most potent RyR-active congener increasing channel open probability at 200 pM. Shifting meta-substitutions to the para-position resulted in a > 100-fold reduction in potency as seen with PCB 197. Non-ortho PCB 11 was found to lack activity at the receptor supporting a minimum mono-ortho substitution for PCB RyR activity. These findings expand and support previous SAR assessments; where out of the 49 congeners tested to date 42 activate the receptor demonstrating that the RyR is a sensitive and common target of PCBs. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

17 CFR Appendix A to Part 255 - Reporting and Recordkeeping Requirements for Covered Trading Activities

Code of Federal Regulations, 2014 CFR

2014-04-01

... regarding a variety of quantitative measurements of their covered trading activities, which vary depending... entity's covered trading activities. c. The quantitative measurements that must be furnished pursuant to... prior to September 30, 2015. e. In addition to the quantitative measurements required in this appendix...

Using NMR chemical shifts to calculate the propensity for structural order and disorder in proteins.

PubMed

Tamiola, Kamil; Mulder, Frans A A

2012-10-01

NMR spectroscopy offers the unique possibility to relate the structural propensities of disordered proteins and loop segments of folded peptides to biological function and aggregation behaviour. Backbone chemical shifts are ideally suited for this task, provided that appropriate reference data are available and idiosyncratic sensitivity of backbone chemical shifts to structural information is treated in a sensible manner. In the present paper, we describe methods to detect structural protein changes from chemical shifts, and present an online tool [ncSPC (neighbour-corrected Structural Propensity Calculator)], which unites aspects of several current approaches. Examples of structural propensity calculations are given for two well-characterized systems, namely the binding of α-synuclein to micelles and light activation of photoactive yellow protein. These examples spotlight the great power of NMR chemical shift analysis for the quantitative assessment of protein disorder at the atomic level, and further our understanding of biologically important problems.

Multi-wavelength Raman spectroscopy study of supported vanadia catalysts: Structure identification and quantification

DOE PAGES

Wu, Zili

2014-10-20

Revealing the structure of supported metal oxide catalysts is a prerequisite for establishing the structure - catalysis relationship. Among a variety of characterization techniques, multi-wavelength Raman spectroscopy, combining resonance Raman and non-resonance Raman with different excitation wavelengths, has recently emerged as a particularly powerful tool in not only identifying but also quantifying the structure of supported metal oxide clusters. In our review, we make use of two supported vanadia systems, VO x/SiO 2 and VO x/CeO 2, as examples to showcase how one can employ this technique to investigate the heterogeneous structure of active oxide clusters and to understand themore » complex interaction between the oxide clusters and the support. Moreover, the qualitative and quantitative structural information gained from the multi-wavelength Raman spectroscopy can be utilized to provide fundamental insights for designing more efficient supported metal oxide catalysts.« less

Molecular docking, 3D-QSAR and structural optimization on imidazo-pyridine derivatives dually targeting AT1 and PPARγ

PubMed Central

Zhang, Jun; Hao, Qing-Qing; Liu, Xin; Jing, Zhi; Jia, Wen-Qing; Wang, Shu-Qing; Xu, Wei-Ren; Cheng, Xian-Chao; Wang, Run-Ling

2017-01-01

Telmisartan, a bifunctional agent of blood pressure lowering and glycemia reduction, was previously reported to antagonize angiotensin II type 1 (AT1) receptor and partially activate peroxisome proliferator-activated receptor γ (PPARγ) simultaneously. Through the modification to telmisartan, researchers designed and obtained imidazo-\\pyridine derivatives with the IC50s of 0.49∼94.1 nM against AT1 and EC50s of 20∼3640 nM towards PPARγ partial activation. For minutely inquiring the interaction modes with the relevant receptor and analyzing the structure-activity relationships, molecular docking and 3D-QSAR (Quantitative structure-activity relationships) analysis of these imidazo-\\pyridines on dual targets were conducted in this work. Docking approaches of these derivatives with both receptors provided explicit interaction behaviors and excellent matching degree with the binding pockets. The best CoMFA (Comparative Molecular Field Analysis) models exhibited predictive results of q2=0.553, r2=0.954, SEE=0.127, r2pred=0.779 for AT1 and q2=0.503, r2=1.00, SEE=0.019, r2pred=0.604 for PPARγ, respectively. The contour maps from the optimal model showed detailed information of structural features (steric and electrostatic fields) towards the biological activity. Combining the bioisosterism with the valuable information from above studies, we designed six molecules with better predicted activities towards AT1 and PPARγ partial activation. Overall, these results could be useful for designing potential dual AT1 antagonists and partial PPARγ agonists. PMID:28445965

Molecular docking, 3D-QSAR and structural optimization on imidazo-pyridine derivatives dually targeting AT1 and PPARg.

PubMed

Zhang, Jun; Hao, Qing-Qing; Liu, Xin; Jing, Zhi; Jia, Wen-Qing; Wang, Shu-Qing; Xu, Wei-Ren; Cheng, Xian-Chao; Wang, Run-Ling

2017-04-11

Telmisartan, a bifunctional agent of blood pressure lowering and glycemia reduction, was previously reported to antagonize angiotensin II type 1 (AT1) receptor and partially activate peroxisome proliferator-activated receptor γ (PPARγ) simultaneously. Through the modification to telmisartan, researchers designed and obtained imidazo-\\pyridine derivatives with the IC50s of 0.49~94.1 nM against AT1 and EC50s of 20~3640 nM towards PPARγ partial activation. For minutely inquiring the interaction modes with the relevant receptor and analyzing the structure-activity relationships, molecular docking and 3D-QSAR (Quantitative structure-activity relationships) analysis of these imidazo-\\pyridines on dual targets were conducted in this work. Docking approaches of these derivatives with both receptors provided explicit interaction behaviors and excellent matching degree with the binding pockets. The best CoMFA (Comparative Molecular Field Analysis) models exhibited predictive results of q2=0.553, r2=0.954, SEE=0.127, r2pred=0.779 for AT1 and q2=0.503, r2=1.00, SEE=0.019, r2pred=0.604 for PPARγ, respectively. The contour maps from the optimal model showed detailed information of structural features (steric and electrostatic fields) towards the biological activity. Combining the bioisosterism with the valuable information from above studies, we designed six molecules with better predicted activities towards AT1 and PPARγ partial activation. Overall, these results could be useful for designing potential dual AT1 antagonists and partial PPARγ agonists.

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.

Syringe Injectable Electronics: Precise Targeted Delivery with Quantitative Input/Output Connectivity.

PubMed

Hong, Guosong; Fu, Tian-Ming; Zhou, Tao; Schuhmann, Thomas G; Huang, Jinlin; Lieber, Charles M

2015-10-14

Syringe-injectable mesh electronics with tissue-like mechanical properties and open macroporous structures is an emerging powerful paradigm for mapping and modulating brain activity. Indeed, the ultraflexible macroporous structure has exhibited unprecedented minimal/noninvasiveness and the promotion of attractive interactions with neurons in chronic studies. These same structural features also pose new challenges and opportunities for precise targeted delivery in specific brain regions and quantitative input/output (I/O) connectivity needed for reliable electrical measurements. Here, we describe new results that address in a flexible manner both of these points. First, we have developed a controlled injection approach that maintains the extended mesh structure during the "blind" injection process, while also achieving targeted delivery with ca. 20 μm spatial precision. Optical and microcomputed tomography results from injections into tissue-like hydrogel, ex vivo brain tissue, and in vivo brains validate our basic approach and demonstrate its generality. Second, we present a general strategy to achieve up to 100% multichannel I/O connectivity using an automated conductive ink printing methodology to connect the mesh electronics and a flexible flat cable, which serves as the standard "plug-in" interface to measurement electronics. Studies of resistance versus printed line width were used to identify optimal conditions, and moreover, frequency-dependent noise measurements show that the flexible printing process yields values comparable to commercial flip-chip bonding technology. Our results address two key challenges faced by syringe-injectable electronics and thereby pave the way for facile in vivo applications of injectable mesh electronics as a general and powerful tool for long-term mapping and modulation of brain activity in fundamental neuroscience through therapeutic biomedical studies.

Biological and analytical characterization of two extracts from Valeriana officinalis.

PubMed

Circosta, Clara; De Pasquale, Rita; Samperi, Stefania; Pino, Annalisa; Occhiuto, Francesco

2007-06-13

The anticoronaryspastic and antibronchospastic activities of ethanolic and aqueous extracts of Valeriana officinalis L. roots were investigated in anaesthetized guinea-pigs and the results were correlated with the qualitative/quantitative chemical composition of the extracts in order to account for some of the common uses of this plant. The protective effects of orally administered ethanolic and aqueous extracts (50, 100 and 200 mg/kg) were evaluated against pitressin-induced coronary spasm and pressor response in guinea-pigs and were compared with those of nifedipine. Furthermore, the protective effects against histamine-induced and Oleaceae antigen challenge-induced bronchospasm were evaluated. Finally, the two valerian extracts were analytically characterized by qualitative and quantitative chromatographic analysis. The results showed that the two valeriana extracts possessed significant anticoronaryspastic, antihypertensive and antibronchospastic properties. These were similar to those exhibited by nifedipine and are due to the structural features of the active principles they contain. This study justifies the traditional use of this plant in the treatment of some respiratory and cardiovascular disorders.

Habitat occupancy and detection of the pacific sheath-tailed bat (emballonura semicaudata) on aguiguan, commonwealth of the northern Mariana Islands

USGS Publications Warehouse

Gorresen, P.M.; Bonaccorso, F.J.; Pinzari, C.A.

2009-01-01

Occupancy analysis was used to quantify Pacific sheath-tailed bat (Emballonura semicaudata) foraging activity and its relationship to forest structure and proximity to cave roosts on Aguiguan Island in the Commonwealth of the Northern Mariana Islands. Bat occurrence was most closely associated with canopy cover, vegetation stature and distance to known roosts. The metrics generated by this study can serve as a quantitative baseline for future assessments of the status of this endangered species following changes in habitat due to management activities (e.g., feral goat control) or other factors (e.g., typhoon impacts). Additionally, we provide quantitative descriptions of the echolocation calls of E. semicaudata. Search-phase calls were characterized by a relatively narrow bandwidth and short pulse duration typical of insectivores that forage within vegetative clutter. Two distinctly characteristic frequencies were recorded: 30.97 ?? 1.08 kHz and 63.15 ?? 2.20 kHz ?? Museum and Institute of Zoology PAS.

QSAR Study of p56lck Protein Tyrosine Kinase Inhibitory Activity of Flavonoid Derivatives Using MLR and GA-PLS

PubMed Central

Fassihi, Afshin; Sabet, Razieh

2008-01-01

Quantitative relationships between molecular structure and p56lck protein tyrosine kinase inhibitory activity of 50 flavonoid derivatives are discovered by MLR and GA-PLS methods. Different QSAR models revealed that substituent electronic descriptors (SED) parameters have significant impact on protein tyrosine kinase inhibitory activity of the compounds. Between the two statistical methods employed, GA-PLS gave superior results. The resultant GA-PLS model had a high statistical quality (R2 = 0.74 and Q2 = 0.61) for predicting the activity of the inhibitors. The models proposed in the present work are more useful in describing QSAR of flavonoid derivatives as p56lck protein tyrosine kinase inhibitors than those provided previously. PMID:19325836

Ligand-Induced Modulation of the Free-Energy Landscape of G Protein-Coupled Receptors Explored by Adaptive Biasing Techniques

PubMed Central

Provasi, Davide; Artacho, Marta Camacho; Negri, Ana; Mobarec, Juan Carlos; Filizola, Marta

2011-01-01

Extensive experimental information supports the formation of ligand-specific conformations of G protein-coupled receptors (GPCRs) as a possible molecular basis for their functional selectivity for signaling pathways. Taking advantage of the recently published inactive and active crystal structures of GPCRs, we have implemented an all-atom computational strategy that combines different adaptive biasing techniques to identify ligand-specific conformations along pre-determined activation pathways. Using the prototypic GPCR β2-adrenergic receptor as a suitable test case for validation, we show that ligands with different efficacies (either inverse agonists, neutral antagonists, or agonists) modulate the free-energy landscape of the receptor by shifting the conformational equilibrium towards active or inactive conformations depending on their elicited physiological response. Notably, we provide for the first time a quantitative description of the thermodynamics of the receptor in an explicit atomistic environment, which accounts for the receptor basal activity and the stabilization of different active-like states by differently potent agonists. Structural inspection of these metastable states reveals unique conformations of the receptor that may have been difficult to retrieve experimentally. PMID:22022248

Lipophilicity-related inhibition of blood platelet aggregation by nipecotic acid anilides.

PubMed

De Marco, Agostino; De Candia, Modesto; Carotti, Andrea; Cellamare, Saverio; De Candia, Erica; Altomare, Cosimo

2004-06-01

Using N-[4-(hexyloxy)phenyl]piperidine-3-carboxamide (17c) as a structural lead, a number of isomers, derivatives, and ring-opened analogs were synthesized and tested for their ability to block the in vitro aggregation of human platelets induced by adenosine 5'-diphosphate (ADP). For the most active compounds, inhibition of the platelet aggregation triggered by arachidonic acid (AA) and ADP-induced intraplatelet calcium mobilization was also demonstrated. Based on quantitative structure-activity relationships (QSARs), we proved the impact of hydrophobicity on antiplatelet activity by a nonlinear (parabolic or bilinear) relationship between pIC(50) and lipophilicity, as assessed by RP-HPLC capacity factors and ClogP (i.e. calculated 1-octanol-water partition coefficients). This study highlighted the following additional SARs: quasi-isolipophilic isomers of 17c (isonipecotanilides and pipecolinanilides) and ring-opened analogs (e.g. anilide of beta-alanine) exhibited lower antiplatelet activity; methylation of the piperidine nitrogen of 17c has no effect, whereas alkylation with an n-propyl group decreases the activity by a factor of approximately 2, most likely due to a conformation-dependent decrease in lipophilicity.

Fluvial drainage networks: the fractal approach as an improvement of quantitative geomorphic analyses

NASA Astrophysics Data System (ADS)

Melelli, Laura; Liucci, Luisa; Vergari, Francesca; Ciccacci, Sirio; Del Monte, Maurizio

2014-05-01

Drainage basins are primary landscape units for geomorphological investigations. Both hillslopes and river drainage system are fundamental components in drainage basins analysis. As other geomorphological systems, also the drainage basins aim to an equilibrium condition where the sequence of erosion, transport and sedimentation approach to a condition of minimum energy effort. This state is revealed by a typical geometry of landforms and of drainage net. Several morphometric indexes can measure how much a drainage basin is far from the theoretical equilibrium configuration, revealing possible external disarray. In active tectonic areas, the drainage basins have a primary importance in order to highlight style, amount and rate of tectonic impulses, and morphometric indexes allow to estimate the tectonic activity classes of different sectors in a study area. Moreover, drainage rivers are characterized by a self-similarity structure; this promotes the use of fractals theory to investigate the system. In this study, fractals techniques are employed together with quantitative geomorphological analysis to study the Upper Tiber Valley (UTV), a tectonic intermontane basin located in northern Apennines (Umbria, central Italy). The area is the result of different tectonic phases. From Late Pliocene until present time the UTV is strongly controlled by a regional uplift and by an extensional phase with different sets of normal faults playing a fundamental role in basin morphology. Thirty-four basins are taken into account for the quantitative analysis, twenty on the left side of the basin, the others on the right side. Using fractals dimension of drainage networks, Horton's laws results, concavity and steepness indexes, and hypsometric curves, this study aims to obtain an evolutionary model of the UTV, where the uplift is compared to local subsidence induced by normal fault activity. The results highlight a well defined difference between western and eastern tributary basins, suggesting a greater disequilibrium in the last ones. The quantitative analysis points out the segments of the basin boundaries where the fault activity is more efficient and the resulting geomorphological implications.

Synthesis and quantitative structure activity relationship (QSAR) of arylidene (benzimidazol-1-yl)acetohydrazones as potential antibacterial agents.

PubMed

El-Kilany, Yeldez; Nahas, Nariman M; Al-Ghamdi, Mariam A; Badawy, Mohamed E I; El Ashry, El Sayed H

2015-01-01

Ethyl (benzimidazol-1-yl)acetate was subjected to hydrazinolysis with hydrazine hydrate to give (benzimidazol-1-yl)acetohydrazide. The latter was reacted with various aromatic aldehydes to give the respective arylidene (1H-benzimidazol-1-yl)acetohydrazones. Solutions of the prepared hydrazones were found to contain two geometric isomers. Similarly (2-methyl-benzimidazol-1-yl)acetohydrazide was reacted with various aldehydes to give the corresponding hydrazones. The antibacterial activity was evaluated in vitro by minimum inhibitory concentration (MIC) against Agrobacterium tumefaciens (A. tumefaciens), Erwinia carotovora (E. carotovora), Corynebacterium fascians (C. fascians) and Pseudomonas solanacearum (P. solanacearum). MIC result demonstrated that salicylaldehyde(1H-benzimidazol-1-yl)acetohydrazone (4) was the most active compound (MIC = 20, 35, 25 and 30 mg/L against A. tumefaciens, C. fascians, E. carotovora and P. solanacearum, respectively). Quantitative structure activity relationship (QSAR) investigation using Hansch analysis was applied to find out the correlation between antibacterial activity and physicochemical properties. Various physicochemical descriptors and experimentally determined MIC values for different microorganisms were used as independent and dependent variables, respectively. pMICs of the compounds exhibited good correlation (r = 0.983, 0.914, 0.960 and 0.958 for A. tumefaciens, C. fascians, E. carotovora and P. solanacearum, respectively) with the prediction made by the model. QSAR study revealed that the hydrophobic parameter (ClogP), the aqueous solubility (LogS), calculated molar refractivity, topological polar surface area and hydrogen bond acceptor were found to have overall significant correlation with antibacterial activity. The statistical results of training set, correlation coefficient (r and r (2)), the ratio between regression and residual variances (f, Fisher's statistic), the standard error of estimates and significant (s) gave reliability to the prediction of molecules with activity using QSAR models. However, QSAR equations derived for the MIC values against the tested bacteria showed negative contribution of molecular mass.

Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action.

PubMed

Papamokos, George; Silins, Ilona

2016-01-01

There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens.

Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action

PubMed Central

Papamokos, George; Silins, Ilona

2016-01-01

There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens. PMID:27625608

Is the structural diversity of tripeptides sufficient for developing functional food additives with satisfactory multiple bioactivities?

NASA Astrophysics Data System (ADS)

Wang, Jian-Hui; Liu, Yong-Le; Ning, Jing-Heng; Yu, Jian; Li, Xiang-Hong; Wang, Fa-Xiang

2013-05-01

Multifunctional peptides have attracted increasing attention in the food science community because of their therapeutic potential, low toxicity and rapid intestinal absorption. However, previous study demonstrated that the limited structural variations make it difficult to optimize dipeptide molecules in a good balance between desirable and undesirable properties (F. Tian, P. Zhou, F. Lv, R. Song, Z. Li, J. Pept. Sci. 13 (2007) 549-566). In the present work, we attempt to answer whether the structural diversity is sufficient for a tripeptide to have satisfactory multiple bioactivities. Statistical test, structural examination and energetic analysis confirm that peptides of three amino acids long can bind tightly to human angiotensin converting enzyme (ACE) and thus exert significant antihypertensive efficacy. Further quantitative structure-activity relationship (QSAR) modeling and prediction of all 8000 possible tripeptides reveal that their ACE-inhibitory potency exhibits a good (positive) relationship to antioxidative activity, but has only a quite modest correlation with bitterness. This means that it is possible to find certain tripeptide entities possessing the optimal combination of strong ACE-inhibitory potency, high antioxidative activity and weak bitter taste, which are the promising candidates for developing multifunctional food additives with satisfactory multiple bioactivities. The marked difference between dipeptide and tripeptide can be attributed to the fact that the structural diversity of peptides increases dramatically with a slight change in sequence length.

Spectroscopic characteristic (FT-IR, FT-Raman, UV, 1H and 13C NMR), theoretical calculations and biological activity of alkali metal homovanillates

NASA Astrophysics Data System (ADS)

Samsonowicz, M.; Kowczyk-Sadowy, M.; Piekut, J.; Regulska, E.; Lewandowski, W.

2016-04-01

The structural and vibrational properties of lithium, sodium, potassium, rubidium and cesium homovanillates were investigated in this paper. Supplementary molecular spectroscopic methods such as: FT-IR, FT-Raman in the solid phase, UV and NMR were applied. The geometrical parameters and energies were obtained from density functional theory (DFT) B3LYP method with 6-311++G** basis set calculations. The geometry of the molecule was fully optimized, vibrational spectra were calculated and fundamental vibrations were assigned. Geometric and magnetic aromaticity indices, atomic charges, dipole moments, HOMO and LUMO energies were also calculated. The microbial activity of investigated compounds was tested against Bacillus subtilis (BS), Pseudomonas aeruginosa (PA), Escherichia coli (EC), Staphylococcus aureus (SA) and Candida albicans (CA). The relationship between the molecular structure of tested compounds and their antimicrobial activity was studied. The principal component analysis (PCA) was applied in order to attempt to distinguish the biological activities of these compounds according to selected band wavenumbers. Obtained data show that the FT-IR spectra can be a rapid and reliable analytical tool and a good source of information for the quantitative analysis of the relationship between the molecular structure of the compound and its biological activity.

Design and synthesis of novel insecticides based on the serotonergic ligand 1-[(4-aminophenyl)ethyl]-4-[3-(trifluoromethyl)phenyl]piperazine (PAPP).

PubMed

Cai, Mingyi; Li, Zhong; Fan, Feng; Huang, Qingchun; Shao, Xusheng; Song, Gonghua

2010-03-10

1-[(4-Aminophenyl)ethyl]-4-[3-(trifluoromethyl)phenyl]piperazine (PAPP) is a 5-HT(1A) agonist and was reported to display high affinity for serotonin (5-HT) receptor from the parasitic nematode Haemonchus contortus . The present investigation explored the possibility of using PAPP as a lead compound of new insecticides with novel mode of action. On the basis of the PAPP scaffold, a series of 1-arylmethyl-4-[(trifluoromethyl)pyridin-2-yl]piperazine derivatives were designed, synthesized, and evaluated for biological activities against the armyworm Pseudaletia separata (Walker). Bioassays showed that most of the target compounds displayed certain growth-inhibiting activities or larvicidal activities against armyworm. The quantitative structure-activity relationship (QSAR) for growth-inhibiting activities was also analyzed and established.

3D-QSAR Studies on a Series of Dihydroorotate Dehydrogenase Inhibitors: Analogues of the Active Metabolite of Leflunomide

PubMed Central

Li, Shun-Lai; He, Mao-Yu; Du, Hong-Guang

2011-01-01

The active metabolite of the novel immunosuppressive agent leflunomide has been shown to inhibit the enzyme dihydroorotate dehydrogenase (DHODH). This enzyme catalyzes the fourth step in de novo pyrimidine biosynthesis. Self-organizing molecular field analysis (SOMFA), a simple three-dimensional quantitative structure-activity relationship (3D-QSAR) method is used to study the correlation between the molecular properties and the biological activities of a series of analogues of the active metabolite. The statistical results, cross-validated rCV2 (0.664) and non cross-validated r2 (0.687), show a good predictive ability. The final SOMFA model provides a better understanding of DHODH inhibitor-enzyme interactions, and may be useful for further modification and improvement of inhibitors of this important enzyme. PMID:21686163

3D-Quantitative structure-activity relationships of synthetic antileishmanial ring-substituted ether phospholipids.

PubMed

Kapou, Agnes; Benetis, Nikolas P; Avlonitis, Nikos; Calogeropoulou, Theodora; Koufaki, Maria; Scoulica, Efi; Nikolaropoulos, Sotiris S; Mavromoustakos, Thomas

2007-02-01

The application of 2D-NMR spectroscopy and Molecular Modeling in determining the active conformation of flexible molecules in 3D-QSAR was demonstrated in the present study. In particular, a series of 33 flexible synthetic phospholipids, either 2-(4-alkylidene-cyclohexyloxy)ethyl- or omega-cycloalkylidene-substituted ether phospholipids were systematically evaluated for their in vitro antileishmanial activity against the promastigote forms of Leishmania infantum and Leishmania donovani by CoMFA and CoMSIA 3D-QSAR studies. Steric and hydrophobic properties of the phospholipids under study appear to govern their antileishmanial activity against both strains, while the electrostatic properties have no significant contribution. The acknowledgment of these important properties of the pharmacophore will aid in the rational design of new analogues with higher activity.

The Potential of Micro Electro Mechanical Systems and Nanotechnology for the U.S. Army

DTIC Science & Technology

2001-05-01

Quantitative Structure Activity Relationship ( QSAR ) model . The QSAR model calculates the proper composition of the polymer-carbon black matrix...example, the BEI Gyrochip Model QRS11 from Systron Donner Inertial Division has a startup time of less than 1 second, a Mean Time Between Failure (MTBF... modeling from many equations per atom to a few lines of code. This approach is amenable to parallel processing. Nevertheless, their programs require

Drug interaction study of flavonoids toward CYP3A4 and their quantitative structure activity relationship (QSAR) analysis for predicting potential effects.

PubMed

Li, Yannan; Ning, Jing; Wang, Yan; Wang, Chao; Sun, Chengpeng; Huo, Xiaokui; Yu, Zhenlong; Feng, Lei; Zhang, Baojing; Tian, Xiangge; Ma, Xiaochi

2018-05-09

The high risk of herb-drug interactions (HDIs) mediated by the herbal medicines and dietary supplements which containing abundant flavonoids had become more and more frequent in our daily life. In our study, the inhibition activities of 44 different structures of flavonoids toward human CYPs were systemically evaluated for the first time. According to our results, a remarkable structure-dependent inhibition behavior toward CYP3A4 was observed in vitro. Some flavonoids such as licoflavone (12) and irilone (30) exhibited the selective inhibition toward CYP3 A4 rather than other major human CYPs. To illustrate the interaction mechanism, the inhibition kinetics of various compounds was further performed. Sophoranone (1), apigenin (10), baicalein (11), 5,4'-dihydroxy-3,6,7,8,3'-pentamethoxyflavone (15), myricetin (23) and kushenol K (38) remarkably inhibited the CYP3 A4-catalyzed bufalin 5'-hydroxylation reaction, with K i values of 2.17 ± 0.29, 6.15 ± 0.39, 9.18 ± 3.40, 2.30 ± 0.36, 5.00 ± 2.77 and 1.35 ± 0.25 μM, respectively. Importantly, compounds 1, 11, 15, 23 and 38 could significantly inhibit the metabolism of some clinical drugs in vitro, and these drug-drug interactions (DDIs) of myricetin (23) or kushenol K (38) with clinical drug diazepam were further verified in human primary hepatocytes, respectively. Finally, a quantitative structure-activity relationship (QSAR) of flavonoids with their inhibitory effects toward CYP3 A4 was established using computational methods. Our findings illustrated the high risk of herb-drug interactions (HDIs) caused by flavonoids and revealed the vital structures requirement of natural flavonoids for the HDIs with clinical drugs eliminated by CYP3 A4. Our research provided the useful guidance to safely and rationally use herbal medicines and dietary supplements containing rich natural flavonoids components. Copyright © 2018 Elsevier B.V. All rights reserved.

UPLC-MS/MS quantitative analysis and structural fragmentation study of five Parmotrema lichens from the Eastern Ghats.

PubMed

Kumar, K; Siva, Bandi; Sarma, V U M; Mohabe, Satish; Reddy, A Madhusudana; Boustie, Joel; Tiwari, Ashok K; Rao, N Rama; Babu, K Suresh

2018-07-15

Comparative phytochemical analysis of five lichen species [Parmotrema tinctorum (Delise ex Nyl.) Hale, P. andinum (Mull. Arg.) Hale, P. praesorediosum (Nyl.) Hale, P. grayanum (Hue) Hale, P. austrosinense (Zahlbr.) Hale] of Parmotrema genus were performed using two complementary UPLC-MS systems. The first system consists of high resolution UPLC-QToF-MS/MS spectrometer and the second system consisted of UPLC-MS/MS in Multiple Reaction Monitoring (MRM) mode for quantitative analysis of major constituents in the selected lichen species. The individual compounds (47 compounds) were identified using Q-ToF-MS/MS, via comparison of the exact molecular masses from their MS/MS spectra, the comparison of literature data and retention times to those of standard compounds which were isolated from crude extract of abundant lichen, P. tinctorum. The analysis also allowed us to identify unknown peaks/compounds, which were further characterized by their mass fragmentation studies. The quantitative MRM analysis was useful to have a better discrimination of species according to their chemical profile. Moreover, the determination of antioxidant activities (ABTS + inhibition) and Advance Glycation Endproducts (AGEs) inhibition carried out for the crude extracts revealed a potential antiglycaemic activity to be confirmed for P. austrosinense. Copyright © 2018 Elsevier B.V. All rights reserved.

Effects of finite spatial resolution on quantitative CBF images from dynamic PET

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

Phelps, M.E.; Huang, S.C.; Mahoney, D.K.

1985-05-01

The finite spatial resolution of PET causes the time-activity responses on pixels around the boundaries between gray and white matter regions to contain kinetic components from tissues of different CBF's. CBF values estimated from kinetics of such mixtures are underestimated because of the nonlinear relationship between the time-activity response and the estimated CBF. Computer simulation is used to investigate these effects on phantoms of circular structures and realistic brain slice in terms of object size and quantitative CBF values. The CBF image calculated is compared to the case of having resolution loss alone. Results show that the size of amore » high flow region in the CBF image is decreased while that of a low flow region is increased. For brain phantoms, the qualitative appearance of CBF images is not seriously affected, but the estimated CBF's are underestimated by 11 to 16 percent in local gray matter regions (of size 1 cm/sup 2/) with about 14 percent reduction in global CBF over the whole slice. It is concluded that the combined effect of finite spatial resolution and the nonlinearity in estimating CBF from dynamic PET is quite significant and must be considered in processing and interpreting quantitative CBF images.« less

Comparison of ultrastructural and nanomechanical signature of platelets from acute myocardial infarction and platelet activation

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

Li, Aiqun; Chen, Jianwei; Liang, Zhi-Hong

Acute myocardial infarction (AMI) initiation and progression follow complex molecular and structural changes in the nanoarchitecture of platelets. However, it remains poorly understood how the transformation from health to AMI alters the ultrastructural and biomechanical properties of platelets within the platelet activation microenvironment. Here, we show using an atomic force microscope (AFM) that platelet samples, including living human platelets from the healthy and AMI patient, activated platelets from collagen-stimulated model, show distinct ultrastructural imaging and stiffness profiles. Correlative morphology obtained on AMI platelets and collagen-activated platelets display distinct pseudopodia structure and nanoclusters on membrane. In contrast to normal platelets, AMImore » platelets have a stiffer distribution resulting from complicated pathogenesis, with a prominent high-stiffness peak representative of platelet activation using AFM-based force spectroscopy. Similar findings are seen in specific stages of platelet activation in collagen-stimulated model. Further evidence obtained from different force measurement region with activated platelets shows that platelet migration is correlated to the more elasticity of pseudopodia while high stiffness at the center region. Overall, ultrastructural and nanomechanical profiling by AFM provides quantitative indicators in the clinical diagnostics of AMI with mechanobiological significance.« less

Application of Quantitative Structure–Activity Relationship Models of 5-HT1A Receptor Binding to Virtual Screening Identifies Novel and Potent 5-HT1A Ligands

PubMed Central

2015-01-01

The 5-hydroxytryptamine 1A (5-HT1A) serotonin receptor has been an attractive target for treating mood and anxiety disorders such as schizophrenia. We have developed binary classification quantitative structure–activity relationship (QSAR) models of 5-HT1A receptor binding activity using data retrieved from the PDSP Ki database. The prediction accuracy of these models was estimated by external 5-fold cross-validation as well as using an additional validation set comprising 66 structurally distinct compounds from the World of Molecular Bioactivity database. These validated models were then used to mine three major types of chemical screening libraries, i.e., drug-like libraries, GPCR targeted libraries, and diversity libraries, to identify novel computational hits. The five best hits from each class of libraries were chosen for further experimental testing in radioligand binding assays, and nine of the 15 hits were confirmed to be active experimentally with binding affinity better than 10 μM. The most active compound, Lysergol, from the diversity library showed very high binding affinity (Ki) of 2.3 nM against 5-HT1A receptor. The novel 5-HT1A actives identified with the QSAR-based virtual screening approach could be potentially developed as novel anxiolytics or potential antischizophrenic drugs. PMID:24410373

Two quantitative trait loci affect ACE activities in Mexican-Americans.

PubMed

Kammerer, Candace M; Gouin, Nicolas; Samollow, Paul B; VandeBerg, Jane F; Hixson, James E; Cole, Shelley A; MacCluer, Jean W; Atwood, Larry D

2004-02-01

Angiotensin-converting enzyme (ACE) activity is highly heritable and has been associated with cardiovascular disease. We are studying the effects of genes and environmental factors on hypertension and related phenotypes, such as ACE activity, in Mexican-American families. In the current study, we performed multipoint linkage analysis to search for quantitative trait loci (QTLs) that affect ACE activities on data from 793 individuals from 29 pedigrees from the San Antonio Family Heart Study. As expected, we obtained strong evidence (maximum log of the odds [LOD]=4.57, genomic P=0.003) that a QTL for ACE activity is located on chromosome 17 near the ACE structural locus. We subsequently performed linkage analyses conditional on the effect of this QTL and obtained strong evidence (LOD=3.34) for a second QTL on chromosome 4 near D4S1548. We next incorporated the ACEIns/Del genotypes in our analyses and removed the evidence for the chromosome 17 QTL (maximum LOD=0.60); however, we retained our evidence for the QTL on chromosome 4q. We conclude that the QTL on chromosome 17 is tightly linked to ACE and is in strong disequilibrium with the insertion/deletion polymorphism, which is consistent with other reports. We also have evidence that an additional QTL affects ACE activity. Identification of this additional QTL might lead to alternate means of prophylaxis.

QSAR and molecular graphics analysis of N2-phenylguanines as inhibitors of herpes simplex virus thymidine kinases.

PubMed

Gaudio, A C; Richards, W G; Takahata, Y

2000-02-01

A quantitative structure-activity relationship study of N2-(substituted)-phenylguanines (PHG) as inhibitors of herpes simplex virus thymidine kinase (HSV TK) was performed. The activity of a set of PHG derivatives were analyzed against the thymidine kinase of herpes simplex virus types 1 (HSV1 TK) and 2 (HSV2 TK). Classic and calculated physicochemical parameters were included in the analysis. The results showed that there is an important difference in the activity of the meta substituted PHG derivatives against HSV1 TK and HSV2 TK. The activity of the meta derivatives against HSV2 TK is influenced by a steric effect, which is not observed against HSV1 TK. The superposition of the three-dimensional structures of the active sites of HSV1 TK (crystal structure) and HSV2 TK (homology model) revealed that the amino acid Ile97 is located near the meta position in the HSV1 TK active site, whereas the amino acid Leu97 is located near the meta position in the HSV2 TK active site. This single difference in the active sites of both enzymes can explain the source of the steric effect and serves as an indication that our previously proposed binding mode for the PHG derivatives is plausible. However, another observed mutation in the active site region, Ala168 by Ser168, suggests that an alternative binding mode, similar to that of ganciclovir, could be possible.

Nanoscale visualization of redox activity at lithium-ion battery cathodes.

PubMed

Takahashi, Yasufumi; Kumatani, Akichika; Munakata, Hirokazu; Inomata, Hirotaka; Ito, Komachi; Ino, Kosuke; Shiku, Hitoshi; Unwin, Patrick R; Korchev, Yuri E; Kanamura, Kiyoshi; Matsue, Tomokazu

2014-11-17

Intercalation and deintercalation of lithium ions at electrode surfaces are central to the operation of lithium-ion batteries. Yet, on the most important composite cathode surfaces, this is a rather complex process involving spatially heterogeneous reactions that have proved difficult to resolve with existing techniques. Here we report a scanning electrochemical cell microscope based approach to define a mobile electrochemical cell that is used to quantitatively visualize electrochemical phenomena at the battery cathode material LiFePO4, with resolution of ~100 nm. The technique measures electrode topography and different electrochemical properties simultaneously, and the information can be combined with complementary microscopic techniques to reveal new perspectives on structure and activity. These electrodes exhibit highly spatially heterogeneous electrochemistry at the nanoscale, both within secondary particles and at individual primary nanoparticles, which is highly dependent on the local structure and composition.

Analysis of Mammalian Sphingolipids by Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) and Tissue Imaging Mass Spectrometry (TIMS)

PubMed Central

Sullards, M. Cameron; Liu, Ying; Chen, Yanfeng; Merrill, Alfred H.

2011-01-01

Sphingolipids are a highly diverse category of molecules that serve not only as components of biological structures but also as regulators of numerous cell functions. Because so many of the structural features of sphingolipids give rise to their biological activity, there is a need for comprehensive or “sphingolipidomic” methods for identification and quantitation of as many individual subspecies as possible. This review defines sphingolipids as a class, briefly discusses classical methods for their analysis, and focuses primarily on liquid chromatography tandem mass spectrometry (LC-MS/MS) and tissue imaging mass spectrometry (TIMS). Recently, a set of evolving and expanding methods have been developed and rigorously validated for the extraction, identification, separation, and quantitation of sphingolipids by LC-MS/MS. Quantitation of these biomolecules is made possible via the use of an internal standard cocktail. The compounds that can be readily analyzed are free long-chain (sphingoid) bases, sphingoid base 1-phosphates, and more complex species such as ceramides, ceramide 1-phosphates, sphingomyelins, mono- and di-hexosylceramides sulfatides, and novel compounds such as the 1-deoxy- and 1-(deoxymethyl)-sphingoid bases and their N-acyl-derivatives. These methods can be altered slightly to separate and quantitate isomeric species such as glucosyl/galactosylceramide. Because these techniques require the extraction of sphingolipids from their native environment, any information regarding their localization in histological slices is lost. Therefore, this review also describes methods for TIMS. This technique has been shown to be a powerful tool to determine the localization of individual molecular species of sphingolipids directly from tissue slices. PMID:21749933

Molecular pathways to parallel evolution: I. Gene nexuses and their morphological correlates.

PubMed

Zuckerkandl, E

1994-12-01

Aspects of the regulatory interactions among genes are probably as old as most genes are themselves. Correspondingly, similar predispositions to changes in such interactions must have existed for long evolutionary periods. Features of the structure and the evolution of the system of gene regulation furnish the background necessary for a molecular understanding of parallel evolution. Patently "unrelated" organs, such as the fat body of a fly and the liver of a mammal, can exhibit fractional homology, a fraction expected to become subject to quantitation. This also seems to hold for different organs in the same organism, such as wings and legs of a fly. In informational macromolecules, on the other hand, homology is indeed all or none. In the quite different case of organs, analogy is expected usually to represent attenuated homology. Many instances of putative convergence are likely to turn out to be predominantly parallel evolution, presumably including the case of the vertebrate and cephalopod eyes. Homology in morphological features reflects a similarity in networks of active genes. Similar nexuses of active genes can be established in cells of different embryological origins. Thus, parallel development can be considered a counterpart to parallel evolution. Specific macromolecular interactions leading to the regulation of the c-fos gene are given as an example of a "controller node" defined as a regulatory unit. Quantitative changes in gene control are distinguished from relational changes, and frequent parallelism in quantitative changes is noted in Drosophila enzymes. Evolutionary reversions in quantitative gene expression are also expected. The evolution of relational patterns is attributed to several distinct mechanisms, notably the shuffling of protein domains. The growth of such patterns may in part be brought about by a particular process of compensation for "controller gene diseases," a process that would spontaneously tend to lead to increased regulatory and organismal complexity. Despite the inferred increase in gene interaction complexity, whose course over evolutionary time is unknown, the number of homology groups for the functional and structural protein units designated as domains has probably remained rather constant, even as, in some of its branches, evolution moved toward "higher" organisms. In connection with this process, the question is raised of parallel evolution within the purview of activating and repressing master switches and in regard to the number of levels into which the hierarchies of genic master switches will eventually be resolved.

Synthesis, biological evaluation, and 3D QSAR study of 2-methyl-4-oxo-3-oxetanylcarbamic acid esters as N-acylethanolamine acid amidase (NAAA) inhibitors.

PubMed

Ponzano, Stefano; Berteotti, Anna; Petracca, Rita; Vitale, Romina; Mengatto, Luisa; Bandiera, Tiziano; Cavalli, Andrea; Piomelli, Daniele; Bertozzi, Fabio; Bottegoni, Giovanni

2014-12-11

N-(2-Oxo-3-oxetanyl)carbamic acid esters have recently been reported to be noncompetitive inhibitors of the N-acylethanolamine acid amidase (NAAA) potentially useful for the treatment of pain and inflammation. In the present study, we further explored the structure-activity relationships of the carbamic acid ester side chain of 2-methyl-4-oxo-3-oxetanylcarbamic acid ester derivatives. Additional favorable features in the design of potent NAAA inhibitors have been found together with the identification of a single digit nanomolar inhibitor. In addition, we devised a 3D QSAR using the atomic property field method. The model turned out to be able to account for the structural variability and was prospectively validated by designing, synthesizing, and testing novel inhibitors. The fairly good agreement between predictions and experimental potency values points to this 3D QSAR model as the first example of quantitative structure-activity relationships in the field of NAAA inhibitors.

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

Specification and estimation of sources of bias affecting neurological studies in PET/MR with an anatomical brain phantom

NASA Astrophysics Data System (ADS)

Teuho, J.; Johansson, J.; Linden, J.; Saunavaara, V.; Tolvanen, T.; Teräs, M.

2014-01-01

Selection of reconstruction parameters has an effect on the image quantification in PET, with an additional contribution from a scanner-specific attenuation correction method. For achieving comparable results in inter- and intra-center comparisons, any existing quantitative differences should be identified and compensated for. In this study, a comparison between PET, PET/CT and PET/MR is performed by using an anatomical brain phantom, to identify and measure the amount of bias caused due to differences in reconstruction and attenuation correction methods especially in PET/MR. Differences were estimated by using visual, qualitative and quantitative analysis. The qualitative analysis consisted of a line profile analysis for measuring the reproduction of anatomical structures and the contribution of the amount of iterations to image contrast. The quantitative analysis consisted of measurement and comparison of 10 anatomical VOIs, where the HRRT was considered as the reference. All scanners reproduced the main anatomical structures of the phantom adequately, although the image contrast on the PET/MR was inferior when using a default clinical brain protocol. Image contrast was improved by increasing the amount of iterations from 2 to 5 while using 33 subsets. Furthermore, a PET/MR-specific bias was detected, which resulted in underestimation of the activity values in anatomical structures closest to the skull, due to the MR-derived attenuation map that ignores the bone. Thus, further improvements for the PET/MR reconstruction and attenuation correction could be achieved by optimization of RAMLA-specific reconstruction parameters and implementation of bone to the attenuation template.

26th National Medicinal Chemistry Symposium--Developments in chemokines, carbohydrates, p53 and drug metabolism. 14-18 June 1998, Richmond, Virginia, USA.

PubMed

Swords, B

1998-08-01

This symposium, organized by the American Chemical Society, is held every two years. This year's meeting, sponsored by the ACS and The Virginia Commonwealth University, was attended by approximately 300 delegates and covered developments in chemokines, carbohydrates, p53, drug metabolism, prodrugs, structure-based design and molecular modeling. At the opening ceremony, John Topliss began by paying tribute to the distinguished medicinal chemistry career of Alfred Burger (University of Virginia, USA). He then reviewed the application of physicochemical principles to drug design, including the development and application of quantitative structure-activity relationship methodology.

Consideration of the Aluminum Distribution in Zeolites in Theoretical and Experimental Catalysis Research

DOE PAGES

Knott, Brandon C.; Nimlos, Claire T.; Robichaud, David J.; ...

2017-12-11

Research efforts in zeolite catalysis have become increasingly cognizant of the diversity in structure and function resulting from the distribution of framework aluminum atoms, through emerging reports of catalytic phenomena that fall outside those recognizable as the shape-selective ones emblematic of its earlier history. Molecular-level descriptions of how active-site distributions affect catalysis are an aspirational goal articulated frequently in experimental and theoretical research, yet they are limited by imprecise knowledge of the structure and behavior of the zeolite materials under interrogation. In experimental research, higher precision can result from more reliable control of structure during synthesis and from more robustmore » and quantitative structural and kinetic characterization probes. In theoretical research, construction of models with specific aluminum locations and distributions seldom capture the heterogeneity inherent to the materials studied by experiment. In this Perspective, we discuss research findings that appropriately frame the challenges in developing more predictive synthesis-structure-function relations for zeolites, highlighting studies on ZSM-5 zeolites that are among the most structurally complex molecular sieve frameworks and the most widely studied because of their versatility in commercial applications. We discuss research directions to address these challenges and forge stronger connections between zeolite structure, composition, and active sites to catalytic function. Such connections promise to aid in bridging the findings of theoretical and experimental catalysis research, and transforming zeolite active site design from an empirical endeavor into a more predictable science founded on validated models.« less

Consideration of the Aluminum Distribution in Zeolites in Theoretical and Experimental Catalysis Research

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

Knott, Brandon C.; Nimlos, Claire T.; Robichaud, David J.

Research efforts in zeolite catalysis have become increasingly cognizant of the diversity in structure and function resulting from the distribution of framework aluminum atoms, through emerging reports of catalytic phenomena that fall outside those recognizable as the shape-selective ones emblematic of its earlier history. Molecular-level descriptions of how active-site distributions affect catalysis are an aspirational goal articulated frequently in experimental and theoretical research, yet they are limited by imprecise knowledge of the structure and behavior of the zeolite materials under interrogation. In experimental research, higher precision can result from more reliable control of structure during synthesis and from more robustmore » and quantitative structural and kinetic characterization probes. In theoretical research, construction of models with specific aluminum locations and distributions seldom capture the heterogeneity inherent to the materials studied by experiment. In this Perspective, we discuss research findings that appropriately frame the challenges in developing more predictive synthesis-structure-function relations for zeolites, highlighting studies on ZSM-5 zeolites that are among the most structurally complex molecular sieve frameworks and the most widely studied because of their versatility in commercial applications. We discuss research directions to address these challenges and forge stronger connections between zeolite structure, composition, and active sites to catalytic function. Such connections promise to aid in bridging the findings of theoretical and experimental catalysis research, and transforming zeolite active site design from an empirical endeavor into a more predictable science founded on validated models.« less

Characterizing structure connectivity correlation with the default mode network in Alzheimer's patients and normal controls

NASA Astrophysics Data System (ADS)

Guo, Jia; Xu, Peng; Song, Chao; Yao, Li; Zhao, Xiaojie

2012-03-01

Magnetic resonance diffusion tensor imaging (DTI) is a kind of effective measure to do non-invasive investigation on brain fiber structure at present. Studies of fiber tracking based on DTI showed that there was structural connection of white matter fiber among the nodes of resting-state functional network, denoting that the connection of white matter was the basis of gray matter regions in functional network. Nevertheless, relationship between these structure connectivity regions and functional network has not been clearly indicated. Moreover, research of fMRI found that activation of default mode network (DMN) in Alzheimer's disease (AD) was significantly descended, especially in hippocampus and posterior cingulated cortex (PCC). The relationship between this change of DMN activity and structural connection among functional networks needs further research. In this study, fast marching tractography (FMT) algorithm was adopted to quantitative calculate fiber connectivity value between regions, and hippocampus and PCC which were two important regions in DMN related with AD were selected to compute white matter connection region between them in elderly normal control (NC) and AD patient. The fiber connectivity value was extracted to do the correlation analysis with activity intensity of DMN. Results showed that, between PCC and hippocampus of NC, there exited region with significant high connectivity value of white matter fiber whose performance has relatively strong correlation with the activity of DMN, while there was no significant white matter connection region between them for AD patient which might be related with reduced network activation in these two regions of AD.

In silico study of in vitro GPCR assays by QSAR modeling ...

EPA Pesticide Factsheets

The U.S. EPA is screening thousands of chemicals of environmental interest in hundreds of in vitro high-throughput screening (HTS) assays (the ToxCast program). One goal is to prioritize chemicals for more detailed analyses based on activity in molecular initiating events (MIE) of adverse outcome pathways (AOPs). However, the chemical space of interest for environmental exposure is much wider than this set of chemicals. Thus, there is a need to fill data gaps with in silico methods, and quantitative structure-activity relationships (QSARs) are a proven and cost effective approach to predict biological activity. ToxCast in turn provides relatively large datasets that are ideal for training and testing QSAR models. The overall goal of the study described here was to develop QSAR models to fill the data gaps in a larger environmental database of ~32k structures. The specific aim of the current work was to build QSAR models for 18 G-Protein Coupled Receptor (GPCR) assays, part of the aminergic category. Two QSAR modeling strategies were adopted: classification models were developed to separate chemicals into active/non-active classes, and then regression models were built to predict the potency values of the bioassays for the active chemicals. Multiple software programs were used to calculate constitutional, topological and substructural molecular descriptors from two-dimensional (2D) chemical structures. Model-fitting methods included PLSDA (partial least squares d

Quantitative structure-activity relationship and molecular docking of artemisinin derivatives to vascular endothelial growth factor receptor 1.

PubMed

Saeed, Mohamed E M; Kadioglu, Onat; Seo, Ean-Jeong; Greten, Henry Johannes; Brenk, Ruth; Efferth, Thomas

2015-04-01

The antimalarial drug artemisinin has been shown to exert anticancer activity through anti-angiogenic effects. For further drug development, it may be useful to have derivatives with improved anti-angiogenic properties. We performed molecular docking of 52 artemisinin derivatives to vascular endothelial growth factor receptors (VEGFR1, VEGFR2), and VEGFA ligand using Autodock4 and AutodockTools-1.5.7.rc1 using the Lamarckian genetic algorithm. Quantitative structure-activity relationship (QSAR) analyses of the compounds prepared by Corina Molecular Networks were performed using the Molecular Operating Environment MOE 2012.10. A statistically significant inverse relationship was obtained between in silico binding energies to VEGFR1 and anti-angiogenic activity in vivo of a test-set of artemisinin derivatives (R=-0.843; p=0.035). This served as a control experiment to validate molecular docking predicting anti-angiogenc effects. Furthermore, 52 artemisinin derivatives were docked to VEGFR1 and in selected examples also to VEGFR2 and VEGFA. Higher binding affinities were calculated for receptors than for the ligand. The best binding affinities to VEGFR1 were found for an artemisinin dimer, 10-dihydroartemisinyl-2-propylpentanoate, and dihydroartemisinin α-hemisuccinate sodium salt. QSAR analyses revealed significant relationships between VEGFR1 binding energies and defined molecular descriptors of 35 artemisinins assigned to the training set (R=0.0848, p<0.0001) and 17 derivatives assigned to the test set (R=0.761, p<0.001). Molecular docking and QSAR calculations can be used to identify novel artemisinin derivatives with anti-angiogenic effects. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Quantitative structure-activity relationship for the oxidation of aromatic organic contaminants in water by TAML/H2O2.

PubMed

Su, Hanrui; Yu, Chunyang; Zhou, Yongfeng; Gong, Lidong; Li, Qilin; Alvarez, Pedro J J; Long, Mingce

2018-05-02

Tetra-amido macrocyclic ligand (TAML) activator is a functional analog of peroxidase enzymes, which activates hydrogen peroxide (H 2 O 2 ) to form high valence iron-oxo complexes that selectively degrade persistent aromatic organic contaminants (ACs) in water. Here, we develop quantitative structure-activity relationship (QSAR) models based on measured pseudo first-order kinetic rate coefficients (k obs ) of 29 ACs (e.g., phenols and pharmaceuticals) oxidized by TAML/H 2 O 2 at neutral and basic pH values to gain mechanistic insight on the selectivity and pH dependence of TAML/H 2 O 2 systems. These QSAR models infer that electron donating ability (E HOMO ) is the most important AC characteristic for TAML/H 2 O 2 oxidation, pointing to a rate-limiting single-electron transfer (SET) mechanism. Oxidation rates at pH 7 also depend on AC reactive indices such as f min - and qH + , which respectively represent propensity for electrophilic attack and the most positive net atomic charge on hydrogen atoms. At pH 10, TAML/H 2 O 2 is more reactive towards ACs with a lower hydrogen to carbon atoms ratio (#H:C), suggesting the significance of hydrogen atom abstraction. In addition, lnk obs of 14 monosubstituted phenols is negatively correlated with Hammett constants (σ) and exhibits similar sensitivity to substituent effects as horseradish peroxidase. Although accurately predicting degradation rates of specific ACs in complex wastewater matrices could be difficult, these QSAR models are statistically robust and help predict both relative degradability and reaction mechanism for TAML/H 2 O 2 -based treatment processes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Hippocampal coupling with cortical and subcortical structures in the context of memory consolidation.

PubMed

Skelin, Ivan; Kilianski, Scott; McNaughton, Bruce L

2018-04-13

Memory consolidation is a gradual process through which episodic memories become incorporated into long-term 'semantic' representations. It likely involves reactivation of neural activity encoding the recent experience during non-REM sleep. A critical prerequisite for memory consolidation is precise coordination of reactivation events between the hippocampus and cortical/subcortical structures, facilitated by the coupling of local field potential (LFP) oscillations (slow oscillations, sleep spindles and sharp wave/ripples) between these structures. We review the rapidly expanding literature on the qualitative and quantitative aspects of hippocampal oscillatory and neuronal coupling with cortical/subcortical structures in the context of memory reactivation. Reactivation in the hippocampus and cortical/subcortical structures is tightly coupled with sharp wave/ripples. Hippocampal-cortical/subcortical coupling is rich in dimensionality and this dimensionality is likely underestimated due to the limitations of the current methodology. Copyright © 2018 Elsevier Inc. All rights reserved.

A Quantitative Measure of Conformational Changes in Apo, Holo and Ligand-Bound Forms of Enzymes.

PubMed

Singh, Satendra; Singh, Atul Kumar; Wadhwa, Gulshan; Singh, Dev Bukhsh; Dwivedi, Seema; Gautam, Budhayash; Ramteke, Pramod W

2016-06-01

Determination of the native geometry of the enzymes and ligand complexes is a key step in the process of structure-based drug designing. Enzymes and ligands show flexibility in structural behavior as they come in contact with each other. When ligand binds with active site of the enzyme, in the presence of cofactor some structural changes are expected to occur in the active site. Motivation behind this study is to determine the nature of conformational changes as well as regions where such changes are more pronounced. To measure the structural changes due to cofactor and ligand complex, enzyme in apo, holo and ligand-bound forms is selected. Enzyme data set was retrieved from protein data bank. Fifteen triplet groups were selected for the analysis of structural changes based on selection criteria. Structural features for selected enzymes were compared at the global as well as local region. Accessible surface area for the enzymes in entire triplet set was calculated, which describes the change in accessible surface area upon binding of cofactor and ligand with the enzyme. It was observed that some structural changes take place during binding of ligand in the presence of cofactor. This study will helps in understanding the level of flexibility in protein-ligand interaction for computer-aided drug designing.

An analysis of fracture trace patterns in areas of flat-lying sedimentary rocks for the detection of buried geologic structure. [Kansas and Texas

NASA Technical Reports Server (NTRS)

Podwysocki, M. H.

1974-01-01

Two study areas in a cratonic platform underlain by flat-lying sedimentary rocks were analyzed to determine if a quantitative relationship exists between fracture trace patterns and their frequency distributions and subsurface structural closures which might contain petroleum. Fracture trace lengths and frequency (number of fracture traces per unit area) were analyzed by trend surface analysis and length frequency distributions also were compared to a standard Gaussian distribution. Composite rose diagrams of fracture traces were analyzed using a multivariate analysis method which grouped or clustered the rose diagrams and their respective areas on the basis of the behavior of the rays of the rose diagram. Analysis indicates that the lengths of fracture traces are log-normally distributed according to the mapping technique used. Fracture trace frequency appeared higher on the flanks of active structures and lower around passive reef structures. Fracture trace log-mean lengths were shorter over several types of structures, perhaps due to increased fracturing and subsequent erosion. Analysis of rose diagrams using a multivariate technique indicated lithology as the primary control for the lower grouping levels. Groupings at higher levels indicated that areas overlying active structures may be isolated from their neighbors by this technique while passive structures showed no differences which could be isolated.

Developing Geoscience Students' Quantitative Skills

NASA Astrophysics Data System (ADS)

Manduca, C. A.; Hancock, G. S.

2005-12-01

Sophisticated quantitative skills are an essential tool for the professional geoscientist. While students learn many of these sophisticated skills in graduate school, it is increasingly important that they have a strong grounding in quantitative geoscience as undergraduates. Faculty have developed many strong approaches to teaching these skills in a wide variety of geoscience courses. A workshop in June 2005 brought together eight faculty teaching surface processes and climate change to discuss and refine activities they use and to publish them on the Teaching Quantitative Skills in the Geosciences website (serc.Carleton.edu/quantskills) for broader use. Workshop participants in consultation with two mathematics faculty who have expertise in math education developed six review criteria to guide discussion: 1) Are the quantitative and geologic goals central and important? (e.g. problem solving, mastery of important skill, modeling, relating theory to observation); 2) Does the activity lead to better problem solving? 3) Are the quantitative skills integrated with geoscience concepts in a way that makes sense for the learning environment and supports learning both quantitative skills and geoscience? 4) Does the methodology support learning? (e.g. motivate and engage students; use multiple representations, incorporate reflection, discussion and synthesis) 5) Are the materials complete and helpful to students? 6) How well has the activity worked when used? Workshop participants found that reviewing each others activities was very productive because they thought about new ways to teach and the experience of reviewing helped them think about their own activity from a different point of view. The review criteria focused their thinking about the activity and would be equally helpful in the design of a new activity. We invite a broad international discussion of the criteria(serc.Carleton.edu/quantskills/workshop05/review.html).The Teaching activities can be found on the Teaching Quantitative Skills in the Geosciences website (serc.Carleton.edu/quantskills/). In addition to the teaching activity collection (85 activites), this site contains a variety of resources to assist faculty with the methods they use to teach quantitative skills at both the introductory and advanced levels; information about broader efforts in quantitative literacy involving other science disciplines, and a special section of resources for students who are struggling with their quantitative skills. The site is part of the Digital Library for Earth Science Education and has been developed by geoscience faculty in collaboration with mathematicians and mathematics educators with funding from the National Science Foundation.

Molecular determinants of ligand binding modes in the histamine H(4) receptor: linking ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR) models to in silico guided receptor mutagenesis studies.

PubMed

Istyastono, Enade P; Nijmeijer, Saskia; Lim, Herman D; van de Stolpe, Andrea; Roumen, Luc; Kooistra, Albert J; Vischer, Henry F; de Esch, Iwan J P; Leurs, Rob; de Graaf, Chris

2011-12-08

The histamine H(4) receptor (H(4)R) is a G protein-coupled receptor (GPCR) that plays an important role in inflammation. Similar to the homologous histamine H(3) receptor (H(3)R), two acidic residues in the H(4)R binding pocket, D(3.32) and E(5.46), act as essential hydrogen bond acceptors of positively ionizable hydrogen bond donors in H(4)R ligands. Given the symmetric distribution of these complementary pharmacophore features in H(4)R and its ligands, different alternative ligand binding mode hypotheses have been proposed. The current study focuses on the elucidation of the molecular determinants of H(4)R-ligand binding modes by combining (3D) quantitative structure-activity relationship (QSAR), protein homology modeling, molecular dynamics simulations, and site-directed mutagenesis studies. We have designed and synthesized a series of clobenpropit (N-(4-chlorobenzyl)-S-[3-(4(5)-imidazolyl)propyl]isothiourea) derivatives to investigate H(4)R-ligand interactions and ligand binding orientations. Interestingly, our studies indicate that clobenpropit (2) itself can bind to H(4)R in two distinct binding modes, while the addition of a cyclohexyl group to the clobenpropit isothiourea moiety allows VUF5228 (5) to adopt only one specific binding mode in the H(4)R binding pocket. Our ligand-steered, experimentally supported protein modeling method gives new insights into ligand recognition by H(4)R and can be used as a general approach to elucidate the structure of protein-ligand complexes.

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. Copyright © 2016 Elsevier B.V. All rights reserved.

ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains

PubMed Central

Canova, Carlos; Denker, Michael; Gerstein, George; Helias, Moritz

2016-01-01

With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing. Previous work introduced a method for visualization of SSEs in massively parallel spike trains, based on an intersection matrix that contains in each entry the degree of overlap of active neurons in two corresponding time bins. Repeated SSEs are reflected in the matrix as diagonal structures of high overlap values. The method as such, however, leaves the task of identifying these diagonal structures to visual inspection rather than to a quantitative analysis. Here we present ASSET (Analysis of Sequences of Synchronous EvenTs), an improved, fully automated method which determines diagonal structures in the intersection matrix by a robust mathematical procedure. The method consists of a sequence of steps that i) assess which entries in the matrix potentially belong to a diagonal structure, ii) cluster these entries into individual diagonal structures and iii) determine the neurons composing the associated SSEs. We employ parallel point processes generated by stochastic simulations as test data to demonstrate the performance of the method under a wide range of realistic scenarios, including different types of non-stationarity of the spiking activity and different correlation structures. Finally, the ability of the method to discover SSEs is demonstrated on complex data from large network simulations with embedded synfire chains. Thus, ASSET represents an effective and efficient tool to analyze massively parallel spike data for temporal sequences of synchronous activity. PMID:27420734

Novel 1,4-naphthoquinone-based sulfonamides: Synthesis, QSAR, anticancer and antimalarial studies.

PubMed

Pingaew, Ratchanok; Prachayasittikul, Veda; Worachartcheewan, Apilak; Nantasenamat, Chanin; Prachayasittikul, Supaluk; Ruchirawat, Somsak; Prachayasittikul, Virapong

2015-10-20

A novel series of 1,4-naphthoquinones (33-44) tethered by open and closed chain sulfonamide moieties were designed, synthesized and evaluated for their cytotoxic and antimalarial activities. All quinone-sulfonamide derivatives displayed a broad spectrum of cytotoxic activities against all of the tested cancer cell lines including HuCCA-1, HepG2, A549 and MOLT-3. Most quinones (33-36 and 38-43) exerted higher anticancer activity against HepG2 cell than that of the etoposide. The open chain analogs 36 and 42 were shown to be the most potent compounds. Notably, the restricted sulfonamide analog 38 with 6,7-dimethoxy groups exhibited the most potent antimalarial activity (IC₅₀ = 2.8 μM). Quantitative structure-activity relationships (QSAR) study was performed to reveal important chemical features governing the biological activities. Five constructed QSAR models provided acceptable predictive performance (Rcv 0.5647-0.9317 and RMSEcv 0.1231-0.2825). Four additional sets of structurally modified compounds were generated in silico (34a-34d, 36a-36k, 40a-40d and 42a-42k) in which their activities were predicted using the constructed QSAR models. A comprehensive discussion of the structure-activity relationships was made and a set of promising compounds (i.e., 33, 36, 38, 42, 36d, 36f, 42e, 42g and 42f) was suggested for further development as anticancer and antimalarial agents. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

An anthropomorphic phantom for quantitative evaluation of breast MRI.

PubMed

Freed, Melanie; de Zwart, Jacco A; Loud, Jennifer T; El Khouli, Riham H; Myers, Kyle J; Greene, Mark H; Duyn, Jeff H; Badano, Aldo

2011-02-01

In this study, the authors aim to develop a physical, tissue-mimicking phantom for quantitative evaluation of breast MRI protocols. The objective of this phantom is to address the need for improved standardization in breast MRI and provide a platform for evaluating the influence of image protocol parameters on lesion detection and discrimination. Quantitative comparisons between patient and phantom image properties are presented. The phantom is constructed using a mixture of lard and egg whites, resulting in a random structure with separate adipose- and glandular-mimicking components. T1 and T2 relaxation times of the lard and egg components of the phantom were estimated at 1.5 T from inversion recovery and spin-echo scans, respectively, using maximum-likelihood methods. The image structure was examined quantitatively by calculating and comparing spatial covariance matrices of phantom and patient images. A static, enhancing lesion was introduced by creating a hollow mold with stereolithography and filling it with a gadolinium-doped water solution. Measured phantom relaxation values fall within 2 standard errors of human values from the literature and are reasonably stable over 9 months of testing. Comparison of the covariance matrices of phantom and patient data demonstrates that the phantom and patient data have similar image structure. Their covariance matrices are the same to within error bars in the anterior-posterior direction and to within about two error bars in the right-left direction. The signal from the phantom's adipose-mimicking material can be suppressed using active fat-suppression protocols. A static, enhancing lesion can also be included with the ability to change morphology and contrast agent concentration. The authors have constructed a phantom and demonstrated its ability to mimic human breast images in terms of key physical properties that are relevant to breast MRI. This phantom provides a platform for the optimization and standardization of breast MRI imaging protocols for lesion detection and characterization.

Structure Detection of Nonlinear Aeroelastic Systems with Application to Aeroelastic Flight Test Data. Part 2

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Brenner, martin J.

2006-01-01

This viewgraph presentation reviews the 1. Motivation for the study 2. Nonlinear Model Form 3. Structure Detection 4. Least Absolute Shrinkage and Selection Operator (LASSO) 5. Objectives 6. Results 7. Assess LASSO as a Structure Detection Tool: Simulated Nonlinear Models 8. Applicability to Complex Systems: F/A-18 Active Aeroelastic Wing Flight Test Data. The authors conclude that 1. this is a novel approach for detecting the structure of highly over-parameterised nonlinear models in situations where other methods may be inadequate 2. that it is a practical significance in the analysis of aircraft dynamics during envelope expansion and could lead to more efficient control strategies and 3. this could allow greater insight into the functionality of various systems dynamics, by providing a quantitative model which is easily interpretable

Using Weighted Entropy to Rank Chemicals in Quantitative High Throughput Screening Experiments

PubMed Central

Shockley, Keith R.

2014-01-01

Quantitative high throughput screening (qHTS) experiments can simultaneously produce concentration-response profiles for thousands of chemicals. In a typical qHTS study, a large chemical library is subjected to a primary screen in order to identify candidate hits for secondary screening, validation studies or prediction modeling. Different algorithms, usually based on the Hill equation logistic model, have been used to classify compounds as active or inactive (or inconclusive). However, observed concentration-response activity relationships may not adequately fit a sigmoidal curve. Furthermore, it is unclear how to prioritize chemicals for follow-up studies given the large uncertainties that often accompany parameter estimates from nonlinear models. Weighted Shannon entropy can address these concerns by ranking compounds according to profile-specific statistics derived from estimates of the probability mass distribution of response at the tested concentration levels. This strategy can be used to rank all tested chemicals in the absence of a pre-specified model structure or the approach can complement existing activity call algorithms by ranking the returned candidate hits. The weighted entropy approach was evaluated here using data simulated from the Hill equation model. The procedure was then applied to a chemical genomics profiling data set interrogating compounds for androgen receptor agonist activity. PMID:24056003

Using Active Learning to Teach Concepts and Methods in Quantitative Biology.

PubMed

Waldrop, Lindsay D; Adolph, Stephen C; Diniz Behn, Cecilia G; Braley, Emily; Drew, Joshua A; Full, Robert J; Gross, Louis J; Jungck, John A; Kohler, Brynja; Prairie, Jennifer C; Shtylla, Blerta; Miller, Laura A

2015-11-01

This article provides a summary of the ideas discussed at the 2015 Annual Meeting of the Society for Integrative and Comparative Biology society-wide symposium on Leading Students and Faculty to Quantitative Biology through Active Learning. It also includes a brief review of the recent advancements in incorporating active learning approaches into quantitative biology classrooms. We begin with an overview of recent literature that shows that active learning can improve students' outcomes in Science, Technology, Engineering and Math Education disciplines. We then discuss how this approach can be particularly useful when teaching topics in quantitative biology. Next, we describe some of the recent initiatives to develop hands-on activities in quantitative biology at both the graduate and the undergraduate levels. Throughout the article we provide resources for educators who wish to integrate active learning and technology into their classrooms. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.