Quantitative structure-property relationship (correlation analysis) of phosphonic acid-based chelates in design of MRI contrast agent.

PubMed

Tiwari, Anjani K; Ojha, Himanshu; Kaul, Ankur; Dutta, Anupama; Srivastava, Pooja; Shukla, Gauri; Srivastava, Rakesh; Mishra, Anil K

2009-07-01

Nuclear magnetic resonance imaging is a very useful tool in modern medical diagnostics, especially when gadolinium (III)-based contrast agents are administered to the patient with the aim of increasing the image contrast between normal and diseased tissues. With the use of soft modelling techniques such as quantitative structure-activity relationship/quantitative structure-property relationship after a suitable description of their molecular structure, we have studied a series of phosphonic acid for designing new MRI contrast agent. Quantitative structure-property relationship studies with multiple linear regression analysis were applied to find correlation between different calculated molecular descriptors of the phosphonic acid-based chelating agent and their stability constants. The final quantitative structure-property relationship mathematical models were found as--quantitative structure-property relationship Model for phosphonic acid series (Model 1)--log K(ML) = {5.00243(+/-0.7102)}- MR {0.0263(+/-0.540)}n = 12 l r l = 0.942 s = 0.183 F = 99.165 quantitative structure-property relationship Model for phosphonic acid series (Model 2)--log K(ML) = {5.06280(+/-0.3418)}- MR {0.0252(+/- .198)}n = 12 l r l = 0.956 s = 0.186 F = 99.256.

Prediction of Environmental Impact of High-Energy Materials with Atomistic Computer Simulations

DTIC Science & Technology

2010-11-01

from a training set of compounds. Other methods include Quantitative Struc- ture-Activity Relationship ( QSAR ) and Quantitative Structure-Property...26 28 the development of QSPR/ QSAR models, in contrast to boiling points and critical parameters derived from empirical correlations, to improve...Quadratic Configuration Interaction Singles Doubles QSAR Quantitative Structure-Activity Relationship QSPR Quantitative Structure-Property

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.

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.

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.

Peptide inhibitors of botulinum neurotoxin serotype A: design, inhibition, cocrystal structures, structure-activity relationship and pharmacophore modeling

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

Kumar G.; Swaminathan S.; Kumaran, D.

Clostridium botulinum neurotoxins are classified as Category A bioterrorism agents by the Centers for Disease Control and Prevention (CDC). The seven serotypes (A-G) of the botulinum neurotoxin, the causative agent of the disease botulism, block neurotransmitter release by specifically cleaving one of the three SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins and induce flaccid paralysis. Using a structure-based drug-design approach, a number of peptide inhibitors were designed and their inhibitory activity against botulinum serotype A (BoNT/A) protease was determined. The most potent peptide, RRGF, inhibited BoNT/A protease with an IC{sub 50} of 0.9 {micro}M and a K{sub i} ofmore » 358 nM. High-resolution crystal structures of various peptide inhibitors in complex with the BoNT/A protease domain were also determined. Based on the inhibitory activities and the atomic interactions deduced from the cocrystal structures, the structure-activity relationship was analyzed and a pharmacophore model was developed. Unlike the currently available models, this pharmacophore model is based on a number of enzyme-inhibitor peptide cocrystal structures and improved the existing models significantly, incorporating new features.« less

Peptide inhibitors of botulinum neurotoxin serotype A: design, inhibition, cocrystal structures, structure-activity relationship and pharmacophore modeling.

PubMed

Kumar, Gyanendra; Kumaran, Desigan; Ahmed, S Ashraf; Swaminathan, Subramanyam

2012-05-01

Clostridium botulinum neurotoxins are classified as Category A bioterrorism agents by the Centers for Disease Control and Prevention (CDC). The seven serotypes (A-G) of the botulinum neurotoxin, the causative agent of the disease botulism, block neurotransmitter release by specifically cleaving one of the three SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins and induce flaccid paralysis. Using a structure-based drug-design approach, a number of peptide inhibitors were designed and their inhibitory activity against botulinum serotype A (BoNT/A) protease was determined. The most potent peptide, RRGF, inhibited BoNT/A protease with an IC(50) of 0.9 µM and a K(i) of 358 nM. High-resolution crystal structures of various peptide inhibitors in complex with the BoNT/A protease domain were also determined. Based on the inhibitory activities and the atomic interactions deduced from the cocrystal structures, the structure-activity relationship was analyzed and a pharmacophore model was developed. Unlike the currently available models, this pharmacophore model is based on a number of enzyme-inhibitor peptide cocrystal structures and improved the existing models significantly, incorporating new features. © 2012 International Union of Crystallography

The Moderating Effect of Health-Improving Workplace Environment on Promoting Physical Activity in White-Collar Employees: A Multi-Site Longitudinal Study Using Multi-Level Structural Equation Modeling.

PubMed

Watanabe, Kazuhiro; Otsuka, Yasumasa; Shimazu, Akihito; Kawakami, Norito

2016-02-01

This longitudinal study aimed to investigate the moderating effect of health-improving workplace environment on relationships between physical activity, self-efficacy, and psychological distress. Data were collected from 16 worksites and 129 employees at two time-points. Health-improving workplace environment was measured using the Japanese version of the Environmental Assessment Tool. Physical activity, self-efficacy, and psychological distress were also measured. Multi-level structural equation modeling was used to investigate the moderating effect of health-improving workplace environment on relationships between psychological distress, self-efficacy, and physical activity. Psychological distress was negatively associated with physical activity via low self-efficacy. Physical activity was negatively related to psychological distress. Physical activity/fitness facilities in the work environment exaggerated the positive relationship between self-efficacy and physical activity. Physical activity/fitness facilities in the workplace may promote employees' physical activity.

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, synthesis and exploring the quantitative structure-activity relationship of some antioxidant flavonoid analogues.

PubMed

Das, Sreeparna; Mitra, Indrani; Batuta, Shaikh; Niharul Alam, Md; Roy, Kunal; Begum, Naznin Ara

2014-11-01

A series of flavonoid analogues were synthesized and screened for the in vitro antioxidant activity through their ability to quench 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical. The activity of these compounds, measured in comparison to the well-known standard antioxidants (29-32), their precursors (38-42) and other bioactive moieties (38-42) resembling partially the flavone skeleton was analyzed further to develop Quantitative Structure-Activity Relationship (QSAR) models using the Genetic Function Approximation (GFA) technique. Based on the essential structural requirements predicted by the QSAR models, some analogues were designed, synthesized and tested for activity. The predicted and experimental activities of these compounds were well correlated. Flavone analogue 20 was found to be the most potent antioxidant. Copyright © 2014 Elsevier Ltd. All rights reserved.

Discovery and structure-activity relationships of a series of pyroglutamic acid amide antagonists of the P2X7 receptor.

PubMed

Abdi, Muna H; Beswick, Paul J; Billinton, Andy; Chambers, Laura J; Charlton, Andrew; Collins, Sue D; Collis, Katharine L; Dean, David K; Fonfria, Elena; Gleave, Robert J; Lejeune, Clarisse L; Livermore, David G; Medhurst, Stephen J; Michel, Anton D; Moses, Andrew P; Page, Lee; Patel, Sadhana; Roman, Shilina A; Senger, Stefan; Slingsby, Brian; Steadman, Jon G A; Stevens, Alexander J; Walter, Daryl S

2010-09-01

A computational lead-hopping exercise identified compound 4 as a structurally distinct P2X(7) receptor antagonist. Structure-activity relationships (SAR) of a series of pyroglutamic acid amide analogues of 4 were investigated and compound 31 was identified as a potent P2X(7) antagonist with excellent in vivo activity in animal models of pain, and a profile suitable for progression to clinical studies. Copyright 2010 Elsevier 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.

Modeling of the relationship between dipeptide structure and dipeptide stability, permeability, and ACE inhibitory activity.

PubMed

Foltz, Martin; van Buren, Leo; Klaffke, Werner; Duchateau, Guus S M J E

2009-09-01

Selected di- and tripeptides exhibit angiotensin-I converting enzyme (ACE) inhibitory activity in vitro. However, the efficacy in vivo is most likely limited for most peptides due to low bioavailability. The purpose of this study was to identify descriptors of intestinal stability, permeability, and ACE inhibitory activity of dipeptides. A total of 228 dipeptides were synthesized; intestinal stability was obtained by in vitro digestion, intestinal permeability using Caco-2 cells and ACE inhibitory activity by an in vitro assay. Databases were constructed to study the relationship between structure and activity, permeability, and stability. Quantitative structure-activity relationship (QSAR) modeling was performed based on computed models using partial least squares regression based on 400 molecular descriptors. QSAR modeling of dipeptide stability revealed high correlation coefficients (R > 0.65) for models based on Z and X scales. However, amino acid (AA) clustering showed the best results in describing stability of dipeptides. The N-terminal AA residues Asp, Gly, and Pro as well as the C-terminal residues Pro, Ser, Thr, and Asp stabilize dipeptides toward luminal enzymatic peptide hydrolysis. QSAR modeling did not reveal significant correlation models for intestinal permeability. 2D-fingerprint models were identified describing ACE inhibitory activity of dipeptides. The intestinal stability of 12 peptides was predicted. Peptides were synthesized and stability was confirmed in simulated digestion experiments. Based on the results, specific dipeptides can be designed to meet both stability and activity criteria. However, postabsorptive ACE inhibitory activities of dipeptides in vivo are most likely limited due to the very low intestinal permeability of dipeptides.

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.

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.

Proximal and Distal Outcomes of Organizational Socialization among New Teachers: A Mediation Analysis

ERIC Educational Resources Information Center

Tengku Ariffin, Tengku Faekah; Awang Hashim, Rosna; Yusof, Norhafezah

2014-01-01

This study was designed to examine the relationship between socialization experience and the task performance of new teachers. It proposed to do this by testing a structural model. In explicating the relationship between the two constructs, teacher engagement in workplace learning activities and wellbeing were included in the structural model as…

Distributed Structure Searchable Toxicity

EPA Pesticide Factsheets

The Distributed Structure Searchable Toxicity (DSSTox) online resource provides high quality chemical structures and annotations in association with toxicity data. It helps to build a data foundation for improved structure-activity relationships and predictive toxicology. DSSTox publishes summarized chemical activity representations for structure-activity modeling and provides a structure browser. This tool also houses the chemical inventories for the ToxCast and Tox21 projects.

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

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.

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.

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.

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.

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.

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.

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.

Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

PubMed Central

Kheirollahpour, Maryam; Shohaimi, Shamarina

2014-01-01

The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI) of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA) was applied to reveal the hidden (secondary) effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model. PMID:25097878

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.

Selective CB2 receptor agonists. Part 2: Structure-activity relationship studies and optimization of proline-based compounds.

PubMed

Riether, Doris; Zindell, Renee; Wu, Lifen; Betageri, Raj; Jenkins, James E; Khor, Someina; Berry, Angela K; Hickey, Eugene R; Ermann, Monika; Albrecht, Claudia; Ceci, Angelo; Gemkow, Mark J; Nagaraja, Nelamangala V; Romig, Helmut; Sauer, Achim; Thomson, David S

2015-02-01

Through a ligand-based pharmacophore model (S)-proline based compounds were identified as potent cannabinoid receptor 2 (CB2) agonists with high selectivity over the cannabinoid receptor 1 (CB1). Structure-activity relationship investigations for this compound class lead to oxo-proline compounds 21 and 22 which combine an impressive CB1 selectivity profile with good pharmacokinetic properties. In a streptozotocin induced diabetic neuropathy model, 22 demonstrated a dose-dependent reversal of mechanical hyperalgesia. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluating a Model of Youth Physical Activity

PubMed Central

Heitzler, Carrie D.; Lytle, Leslie A.; Erickson, Darin J.; Barr-Anderson, Daheia; Sirard, John R.; Story, Mary

2011-01-01

Objective To explore the relationship between social influences, self-efficacy, enjoyment, and barriers and physical activity. Methods Structural equation modeling examined relationships between parent and peer support, parent physical activity, individual perceptions, and objectively measured physical activity using accelerometers among a sample of youth aged 10–17 years (N=720). Results Peer support, parent physical activity, and perceived barriers were directly related to youth activity. The proposed model accounted for 14.7% of the variance in physical activity. Conclusions The results demonstrate a need to further explore additional individual, social, and environmental factors that may influence youth’s regular participation in physical activity. PMID:20524889

SOD activity of carboxyfullerenes predicts their neuroprotective efficacy: A structure-activity study

PubMed Central

Ali, Sameh Saad; Hardt, Joshua I.; Dugan, Laura L.

2008-01-01

Superoxide radical anion is a biologically important oxidant that has been linked to tissue injury and inflammation in several diseases. Here we carried out a structure-activity study on 6 different carboxyfullerene superoxide dismutase (SOD) mimetics with distinct electronic and biophysical characteristics. Neurotoxicity via NMDA receptors, which involves intracellular superoxide, was used as a model to evaluate structure-activity relationships between reactivity towards superoxide and neuronal rescue by these drugs. A significant correlation between neuroprotection by carboxyfullerenes and their ki towards superoxide radical was observed. Computer-assistant molecular modeling demonstrated that the reactivity towards superoxide is sensitive to changes in dipole moment which are dictated not only by the number of carboxyl groups, but also by their distribution on the fullerene ball. These results indicate that the SOD activity of these cell-permeable compounds predicts neuroprotection, and establishes a structure-activity relationship to aid in future studies on the biology of superoxide across disciplines. PMID:18656425

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.

Representing Heterogeneity in Structural Relationships Among Multiple Choice Variables Using a Latent Segmentation Approach

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

Garikapati, Venu; Astroza, Sebastian; Pendyala, Ram M.

Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to depict relationships among activity-travel choices in travel demand model systems ignores the possibility that some choices are made jointly as a bundle as well as the possible presence of structural heterogeneity in the population with respect to decision-making processes. As different segments in the population may adopt and follow different causalmore » decision-making mechanisms when making selected choices jointly, it would be of value to develop simultaneous equations model systems relating multiple endogenous choice variables that are able to identify population subgroups following alternative causal decision structures. Because the segments are not known a priori, they are considered latent and determined endogenously within a joint modeling framework proposed in this paper. The methodology is applied to a national mobility survey data set to identify population segments that follow different causal structures relating residential location choice, vehicle ownership, and car-share and mobility service usage. It is found that the model revealing three distinct latent segments best describes the data, confirming the efficacy of the modeling approach and the existence of structural heterogeneity in decision-making in the population. Future versions of activity-travel model systems should strive to incorporate such structural heterogeneity to better reflect varying decision processes across population subgroups.« less

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.

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.

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

Analysis of the relationship between end-to-end distance and activity of single-chain antibody against colorectal carcinoma.

PubMed

Zhang, Jianhua; Liu, Shanhong; Shang, Zhigang; Shi, Li; Yun, Jun

2012-08-22

We investigated the relationship of End-to-end distance between VH and VL with different peptide linkers and the activity of single-chain antibodies by computer-aided simulation. First, we developed (G4S)n (where n = 1-9) as the linker to connect VH and VL, and estimated the 3D structure of single-chain Fv antibody (scFv) by homologous modeling. After molecular models were evaluated and optimized, the coordinate system of every protein was built and unified into one coordinate system, and End-to-end distances calculated using 3D space coordinates. After expression and purification of scFv-n with (G4S)n as n = 1, 3, 5, 7 or 9, the immunoreactivity of purified ND-1 scFv-n was determined by ELISA. A multi-factorial relationship model was employed to analyze the structural factors affecting scFv: rn=ABn-ABO2+CDn-CDO2+BCn-BCst2. The relationship between immunoreactivity and r-values revealed that fusion protein structure approached the desired state when the r-value = 3. The immunoreactivity declined as the r-value increased, but when the r-value exceeded a certain threshold, it stabilized. We used a linear relationship to analyze structural factors affecting scFv immunoreactivity.

PLS-based quantitative structure-activity relationship for substituted benzamides of clebopride type. Application of experimental design in drug design.

PubMed

Norinder, U; Högberg, T

1992-04-01

The advantageous approach of using an experimentally designed training set as the basis for establishing a quantitative structure-activity relationship with good predictive capability is described. The training set was selected from a fractional factorial design scheme based on a principal component description of physico-chemical parameters of aromatic substituents. The derived model successfully predicts the activities of additional substituted benzamides of 6-methoxy-N-(4-piperidyl)salicylamide type. The major influence on activity of the 3-substituent is demonstrated.

Discovery of imidazo[1,2-b]pyridazine derivatives as IKKbeta inhibitors. Part 1: Hit-to-lead study and structure-activity relationship.

PubMed

Shimizu, Hiroki; Tanaka, Shinji; Toki, Tadashi; Yasumatsu, Isao; Akimoto, Toshihiko; Morishita, Kaoru; Yamasaki, Tomonori; Yasukochi, Takanori; Iimura, Shin

2010-09-01

Imidazo[1,2-b]pyridazine derivatives from high-throughput screening were developed as IKKbeta inhibitors. By the optimization of the 3- and 6-position of imidazo[1,2-b]pyridazine scaffold, cell-free IKKbeta inhibitory activity and TNFalpha inhibitory activity in THP-1 cell increased. Also, these compounds showed high kinase selectivity. The structure-activity relationship was revealed and the interaction model of imidazo[1,2-b]pyridazine compounds with IKKbeta was constructed. Copyright 2010. Published by Elsevier Ltd.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

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).

Structure-Activity Relationships for the Antifungal Activity of Selective Estrogen Receptor Antagonists Related to Tamoxifen

PubMed Central

Butts, Arielle; Martin, Jennifer A.; DiDone, Louis; Bradley, Erin K.; Mutz, Mitchell; Krysan, Damian J.

2015-01-01

Cryptococcosis is one of the most important invasive fungal infections and is a significant contributor to the mortality associated with HIV/AIDS. As part of our program to repurpose molecules related to the selective estrogen receptor modulator (SERM) tamoxifen as anti-cryptococcal agents, we have explored the structure-activity relationships of a set of structurally diverse SERMs and tamoxifen derivatives. Our data provide the first insights into the structural requirements for the antifungal activity of this scaffold. Three key molecular characteristics affecting anti-cryptococcal activity emerged from our studies: 1) the presence of an alkylamino group tethered to one of the aromatic rings of the triphenylethylene core; 2) an appropriately sized aliphatic substituent at the 2 position of the ethylene moiety; and 3) electronegative substituents on the aromatic rings modestly improved activity. Using a cell-based assay of calmodulin antagonism, we found that the anti-cryptococcal activity of the scaffold correlates with calmodulin inhibition. Finally, we developed a homology model of C. neoformans calmodulin and used it to rationalize the structural basis for the activity of these molecules. Taken together, these data and models provide a basis for the further optimization of this promising anti-cryptococcal scaffold. PMID:26016941

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.

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.

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

PubMed

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 q (2) values of 0.753 and 0.770, and r (2) 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.

Molecular surface area based predictive models for the adsorption and diffusion of disperse dyes in polylactic acid matrix.

PubMed

Xu, Suxin; Chen, Jiangang; Wang, Bijia; Yang, Yiqi

2015-11-15

Two predictive models were presented for the adsorption affinities and diffusion coefficients of disperse dyes in polylactic acid matrix. Quantitative structure-sorption behavior relationship would not only provide insights into sorption process, but also enable rational engineering for desired properties. The thermodynamic and kinetic parameters for three disperse dyes were measured. The predictive model for adsorption affinity was based on two linear relationships derived by interpreting the experimental measurements with molecular structural parameters and compensation effect: ΔH° vs. dye size and ΔS° vs. ΔH°. Similarly, the predictive model for diffusion coefficient was based on two derived linear relationships: activation energy of diffusion vs. dye size and logarithm of pre-exponential factor vs. activation energy of diffusion. The only required parameters for both models are temperature and solvent accessible surface area of the dye molecule. These two predictive models were validated by testing the adsorption and diffusion properties of new disperse dyes. The models offer fairly good predictive ability. The linkage between structural parameter of disperse dyes and sorption behaviors might be generalized and extended to other similar polymer-penetrant systems. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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

CALCULATING PHYSICAL PROPERTIES OF ORGANIC COMPOUNDS FOR ENVIRONMENTAL MODELING FROM MOLECULAR STRUCTURE

EPA Science Inventory

Mathematical models for predicting the transport and fate of pollutants in the environment require reactivity parameter values-- that is value of the physical and chemical constants that govern reactivity. Although empirical structure activity relationships have been developed t...

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.

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...

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.

DSSTox and Chemical Information Technologies in Support of PredictiveToxicology

EPA Science Inventory

The EPA NCCT Distributed Structure-Searchable Toxicity (DSSTox) Database project initially focused on the curation and publication of high-quality, standardized, chemical structure-annotated toxicity databases for use in structure-activity relationship (SAR) modeling. In recent y...

Quantitative Structure-Antifungal Activity Relationships for cinnamate derivatives.

PubMed

Saavedra, Laura M; Ruiz, Diego; Romanelli, Gustavo P; Duchowicz, Pablo R

2015-12-01

Quantitative Structure-Activity Relationships (QSAR) are established with the aim of analyzing the fungicidal activities of a set of 27 active cinnamate derivatives. The exploration of more than a thousand of constitutional, topological, geometrical and electronic molecular descriptors, which are calculated with Dragon software, leads to predictions of the growth inhibition on Pythium sp and Corticium rolfsii fungi species, in close agreement to the experimental values extracted from the literature. A set containing 21 new structurally related cinnamate compounds is prepared. The developed QSAR models are applied to predict the unknown fungicidal activity of this set, showing that cinnamates like 38, 28 and 42 are expected to be highly active for Pythium sp, while this is also predicted for 28 and 34 in C. rolfsii. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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.

Bio-mimicking galactose oxidase and hemocyanin, two dioxygen-processing copper proteins.

PubMed

Gamez, Patrick; Koval, Iryna A; Reedijk, Jan

2004-12-21

The modelling of the active sites of metalloproteins is one of the most challenging tasks in bio-inorganic chemistry. Copper proteins form part of this stimulating field of research as copper enzymes are mainly involved in oxidation bio-reactions. Thus, the understanding of the structure-function relationship of their active sites will allow the design of effective and environmental friendly oxidation catalysts. This perspective illustrates some outstanding structural and functional synthetic models of the active site of copper proteins, with special attention given to models of galactose oxidase and hemocyanin.

Development of Novel p16INK4a Mimetics as Anticancer Therapy

DTIC Science & Technology

2015-10-01

peptide (or substituted peptide) or the crystal structure of the relevant sequence from p16INK4 ( PDB 1BI7) was used as the starting structure . Model...small peptides that interact with CDK4/6. The specific aims are as follows. (1) Determine structure -function relationships of overlapping peptides...Determine structure -function relationships of overlapping peptides derived from p16 INK4a that inhibit the activity of CDK4/6 and identify stabilized

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

NASA Astrophysics Data System (ADS)

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

2010-09-01

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

Synthesis, structure-activity relationships, and in vivo evaluation of N3-phenylpyrazinones as novel corticotropin-releasing factor-1 (CRF1) receptor antagonists.

PubMed

Hartz, Richard A; Ahuja, Vijay T; Arvanitis, Argyrios G; Rafalski, Maria; Yue, Eddy W; Denhart, Derek J; Schmitz, William D; Ditta, Jonathan L; Deskus, Jeffrey A; Brenner, Allison B; Hobbs, Frank W; Payne, Joseph; Lelas, Snjezana; Li, Yu-Wen; Molski, Thaddeus F; Mattson, Gail K; Peng, Yong; Wong, Harvey; Grace, James E; Lentz, Kimberley A; Qian-Cutrone, Jingfang; Zhuo, Xiaoliang; Shu, Yue-Zhong; Lodge, Nicholas J; Zaczek, Robert; Combs, Andrew P; Olson, Richard E; Bronson, Joanne J; Mattson, Ronald J; Macor, John E

2009-07-23

Evidence suggests that corticotropin-releasing factor-1 (CRF(1)) receptor antagonists may offer therapeutic potential for the treatment of diseases associated with elevated levels of CRF such as anxiety and depression. A pyrazinone-based chemotype of CRF(1) receptor antagonists was discovered. Structure-activity relationship studies led to the identification of numerous potent analogues including 12p, a highly potent and selective CRF(1) receptor antagonist with an IC(50) value of 0.26 nM. The pharmacokinetic properties of 12p were assessed in rats and Cynomolgus monkeys. Compound 12p was efficacious in the defensive withdrawal test (an animal model of anxiety) in rats. The synthesis, structure-activity relationships and in vivo properties of compounds within the pyrazinone chemotype are described.

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.

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.

New model framework and structure and the commonality evaluation model. [concerning unmanned spacecraft projects

NASA Technical Reports Server (NTRS)

1977-01-01

The development of a framework and structure for shuttle era unmanned spacecraft projects and the development of a commonality evaluation model is documented. The methodology developed for model utilization in performing cost trades and comparative evaluations for commonality studies is discussed. The model framework consists of categories of activities associated with the spacecraft system's development process. The model structure describes the physical elements to be treated as separate identifiable entities. Cost estimating relationships for subsystem and program-level components were calculated.

The role of Patient Health Engagement Model (PHE-model) in affecting patient activation and medication adherence: A structural equation model

PubMed Central

Graffigna, Guendalina; Bonanomi, Andrea

2017-01-01

Background Increasing bodies of scientific research today examines the factors and interventions affecting patients’ ability to self-manage and adhere to treatment. Patient activation is considered the most reliable indicator of patients’ ability to manage health autonomously. Only a few studies have tried to assess the role of psychosocial factors in promoting patient activation. A more systematic modeling of the psychosocial factors explaining the variance of patient activation is needed. Objective To test the hypothesized effect of patient activation on medication adherence; to test the the hypothesized effects of positive emotions and of the quality of the patient/doctor relationship on patient activation; and to test the hypothesized mediating effect of Patient Health Engagement (PHE-model) in this pathway. Material and methods This cross-sectional study involved 352 Italian-speaking adult chronic patients. The survey included measures of i) patient activation (Patient Activation Measure 13 –short form); ii) Patient Health Engagement model (Patient Health Engagement Scale); iii) patient adherence (4 item-Morinsky Medication Adherence Scale); iv) the quality of the patients’ emotional feelings (Manikin Self Assessment Scale); v) the quality of the patient/doctor relationship (Health Care Climate Questionnaire). Structural equation modeling was used to test the hypotheses proposed. Results According to the theoretical model we hypothesized, research results confirmed that patients’ activation significantly affects their reported medication adherence. Moreover, psychosocial factors, such as the patients’ quality of the emotional feelings and the quality of the patient/doctor relationship were demonstrated to be factors affecting the level of patient activation. Finally, the mediation effect of the Patient Health Engagement model was confirmed by the analysis. Conclusions Consistently with the results of previous studies, these findings demonstrate that the Patient Health Engagement Model is a critical factor in enhancing the quality of care. The Patient Health Engagement Model might acts as a mechanism to increase patient activation and adherence. PMID:28654686

The role of Patient Health Engagement Model (PHE-model) in affecting patient activation and medication adherence: A structural equation model.

PubMed

Graffigna, Guendalina; Barello, Serena; Bonanomi, Andrea

2017-01-01

Increasing bodies of scientific research today examines the factors and interventions affecting patients' ability to self-manage and adhere to treatment. Patient activation is considered the most reliable indicator of patients' ability to manage health autonomously. Only a few studies have tried to assess the role of psychosocial factors in promoting patient activation. A more systematic modeling of the psychosocial factors explaining the variance of patient activation is needed. To test the hypothesized effect of patient activation on medication adherence; to test the the hypothesized effects of positive emotions and of the quality of the patient/doctor relationship on patient activation; and to test the hypothesized mediating effect of Patient Health Engagement (PHE-model) in this pathway. This cross-sectional study involved 352 Italian-speaking adult chronic patients. The survey included measures of i) patient activation (Patient Activation Measure 13 -short form); ii) Patient Health Engagement model (Patient Health Engagement Scale); iii) patient adherence (4 item-Morinsky Medication Adherence Scale); iv) the quality of the patients' emotional feelings (Manikin Self Assessment Scale); v) the quality of the patient/doctor relationship (Health Care Climate Questionnaire). Structural equation modeling was used to test the hypotheses proposed. According to the theoretical model we hypothesized, research results confirmed that patients' activation significantly affects their reported medication adherence. Moreover, psychosocial factors, such as the patients' quality of the emotional feelings and the quality of the patient/doctor relationship were demonstrated to be factors affecting the level of patient activation. Finally, the mediation effect of the Patient Health Engagement model was confirmed by the analysis. Consistently with the results of previous studies, these findings demonstrate that the Patient Health Engagement Model is a critical factor in enhancing the quality of care. The Patient Health Engagement Model might acts as a mechanism to increase patient activation and adherence.

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...

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.

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).

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

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.

Structure-Activity Relationship and Molecular Mechanics Reveal the Importance of Ring Entropy in the Biosynthesis and Activity of a Natural Product.

PubMed

Tran, Hai L; Lexa, Katrina W; Julien, Olivier; Young, Travis S; Walsh, Christopher T; Jacobson, Matthew P; Wells, James A

2017-02-22

Macrocycles are appealing drug candidates due to their high affinity, specificity, and favorable pharmacological properties. In this study, we explored the effects of chemical modifications to a natural product macrocycle upon its activity, 3D geometry, and conformational entropy. We chose thiocillin as a model system, a thiopeptide in the ribosomally encoded family of natural products that exhibits potent antimicrobial effects against Gram-positive bacteria. Since thiocillin is derived from a genetically encoded peptide scaffold, site-directed mutagenesis allows for rapid generation of analogues. To understand thiocillin's structure-activity relationship, we generated a site-saturation mutagenesis library covering each position along thiocillin's macrocyclic ring. We report the identification of eight unique compounds more potent than wild-type thiocillin, the best having an 8-fold improvement in potency. Computational modeling of thiocillin's macrocyclic structure revealed a striking requirement for a low-entropy macrocycle for activity. The populated ensembles of the active mutants showed a rigid structure with few adoptable conformations while inactive mutants showed a more flexible macrocycle which is unfavorable for binding. This finding highlights the importance of macrocyclization in combination with rigidifying post-translational modifications to achieve high-potency binding.

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.

Development of a Conceptual Model for Smoking Cessation: Physical Activity, Neurocognition, and Executive Functioning.

PubMed

Loprinzi, Paul D; Herod, Skyla M; Walker, Jerome F; Cardinal, Bradley J; Mahoney, Sara E; Kane, Christy

2015-01-01

Considerable research has shown adverse neurobiological effects of chronic alcohol use, including long-term and potentially permanent changes in the structure and function of the brain; however, much less is known about the neurobiological consequences of chronic smoking, as it has largely been ignored until recently. In this article, we present a conceptual model proposing the effects of smoking on neurocognition and the role that physical activity may play in this relationship as well as its role in smoking cessation. Pertinent published peer-reviewed articles deposited in PubMed delineating the pathways in the proposed model were reviewed. The proposed model, which is supported by emerging research, demonstrates a bidirectional relationship between smoking and executive functioning. In support of our conceptual model, physical activity may moderate this relationship and indirectly influence smoking behavior through physical activity-induced changes in executive functioning. Our model may have implications for aiding smoking cessation efforts through the promotion of physical activity as a mechanism for preventing smoking-induced deficits in neurocognition and executive function.

Computational & experimental evaluation of the structure/activity relationship of β-carbolines as DYRK1A inhibitors.

PubMed

Drung, Binia; Scholz, Christoph; Barbosa, Valéria A; Nazari, Azadeh; Sarragiotto, Maria H; Schmidt, Boris

2014-10-15

DYRK1A has been associated with Down's syndrome and neurodegenerative diseases, therefore it is an important target for novel pharmacological interventions. We combined a ligand-based pharmacophore design with a structure-based protein/ligand docking using the software MOE in order to evaluate the underlying structure/activity relationship. Based on this knowledge we synthesized several novel β-carboline derivatives to validate the theoretical model. Furthermore we identified a modified lead structure as a potent DYRK1A inhibitor (IC50=130 nM) with significant selectivity against MAO-A, DYRK2, DYRK3, DYRK4 & CLK2. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

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-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.

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.

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...

Retro-binding thrombin active site inhibitors: identification of an orally active inhibitor of thrombin catalytic activity.

PubMed

Iwanowicz, Edwin J; Kimball, S David; Lin, James; Lau, Wan; Han, W-C; Wang, Tammy C; Roberts, Daniel G M; Schumacher, W A; Ogletree, Martin L; Seiler, Steven M

2002-11-04

A series of retro-binding inhibitors of human alpha-thrombin was prepared to elucidate structure-activity relationships (SAR) and optimize in vivo performance. Compounds 9 and 11, orally active inhibitors of thrombin catalytic activity, were identified to be efficacious in a thrombin-induced lethality model in mice.

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.

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

Varic acid analogues from fungus as PTP1B inhibitors: Biological evaluation and structure-activity relationships.

PubMed

Sun, Wenlong; Zhuang, Chunlin; Li, Xia; Zhang, Bowei; Lu, Xinhua; Zheng, Zhihui; Dong, Yuesheng

2017-08-01

Protein tyrosine phosphatase 1B (PTP1B) inhibitors as potential therapies for diabetes and obesity have attracted much attention in recent years. Six varic acid analogues were isolated from two strains of fungi and evaluated for PTP1B inhibition activities. The structure-activity relationships were also characterized and predicted by molecular modeling. Further kinetic studies indicated the reversible and competitive inhibition manner of varic acid analogues. Trivaric acid showed insulin-sensitizing effect not only in vitro but also in vivo, representing a promising lead compound for further optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

Development of an in Silico Model of DPPH• Free Radical Scavenging Capacity: Prediction of Antioxidant Activity of Coumarin Type Compounds.

PubMed

Goya Jorge, Elizabeth; Rayar, Anita Maria; Barigye, Stephen J; Jorge Rodríguez, María Elisa; Sylla-Iyarreta Veitía, Maité

2016-06-07

A quantitative structure-activity relationship (QSAR) study of the 2,2-diphenyl-l-picrylhydrazyl (DPPH•) radical scavenging ability of 1373 chemical compounds, using DRAGON molecular descriptors (MD) and the neural network technique, a technique based on the multilayer multilayer perceptron (MLP), was developed. The built model demonstrated a satisfactory performance for the training ( R 2 = 0.713 ) and test set ( Q ext 2 = 0.654 ) , respectively. To gain greater insight on the relevance of the MD contained in the MLP model, sensitivity and principal component analyses were performed. Moreover, structural and mechanistic interpretation was carried out to comprehend the relationship of the variables in the model with the modeled property. The constructed MLP model was employed to predict the radical scavenging ability for a group of coumarin-type compounds. Finally, in order to validate the model's predictions, an in vitro assay for one of the compounds (4-hydroxycoumarin) was performed, showing a satisfactory proximity between the experimental and predicted pIC50 values.

TOWARDS REFINED USE OF TOXICITY DATA IN STATISTICALLY BASED SAR MODELS FOR DEVELOPMENTAL TOXICITY.

EPA Science Inventory

In 2003, an International Life Sciences Institute (ILSI) Working Group examined the potential of statistically based structure-activity relationship (SAR) models for use in screening environmental contaminants for possible developmental toxicants.

VERIFICATION AND VALIDATION OF THE SPARC MODEL

EPA Science Inventory

Mathematical models for predicting the transport and fate of pollutants in the environment require reactivity parameter values--that is, the physical and chemical constants that govern reactivity. Although empirical structure-activity relationships that allow estimation of some ...

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...

Toward the identification of a reliable 3D-QSAR model for the protein tyrosine phosphatase 1B inhibitors

NASA Astrophysics Data System (ADS)

Wang, Fangfang; Zhou, Bo

2018-04-01

Protein tyrosine phosphatase 1B (PTP1B) is an intracellular non-receptor phosphatase that is implicated in signal transduction of insulin and leptin pathways, thus PTP1B is considered as potential target for treating type II diabetes and obesity. The present article is an attempt to formulate the three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling of a series of compounds possessing PTP1B inhibitory activities using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The optimum template ligand-based models are statistically significant with great CoMFA (R2cv = 0.600, R2pred = 0.6760) and CoMSIA (R2cv = 0.624, R2pred = 0.8068) values. Molecular docking was employed to elucidate the inhibitory mechanisms of this series of compounds against PTP1B. In addition, the CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of PTP1B active site. The knowledge of structure-activity relationship and ligand-receptor interactions from 3D-QSAR model and molecular docking will be useful for better understanding the mechanism of ligand-receptor interaction and facilitating development of novel compounds as potent PTP1B inhibitors.

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.

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.

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.

STRUCTURE-ACTIVITY RELATIONSHIP STUIDES AND THEIR ROLE IN PREDICTING AND INVESTIGATING CHEMICAL TOXICITY

EPA Science Inventory

Structure-Activity Relationship Studies and their Role in Predicting and Investigating Chemical Toxicity

Structure-activity relationships (SAR) represent attempts to generalize chemical information relative to biological activity for the twin purposes of generating insigh...

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations

PubMed Central

Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua

2015-01-01

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q2 (cross-validated correlation coefficient) = 0.557, R2ncv (non-cross-validated correlation coefficient) = 0.740, R2pre (predicted correlation coefficient) = 0.749 and Q2 = 0.598, R2ncv = 0.767, R2pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors. PMID:26307982

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations.

PubMed

Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua

2015-08-25

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q(2) (cross-validated correlation coefficient) = 0.557, R(2)ncv (non-cross-validated correlation coefficient) = 0.740, R(2)pre (predicted correlation coefficient) = 0.749 and Q(2) = 0.598, R(2)ncv = 0.767, R(2)pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors.

Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization

PubMed Central

Huang, Ruili; Xia, Menghang; Sakamuru, Srilatha; Zhao, Jinghua; Shahane, Sampada A.; Attene-Ramos, Matias; Zhao, Tongan; Austin, Christopher P.; Simeonov, Anton

2016-01-01

Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure–activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing. PMID:26811972

Using Case Studies as a Semester-Long Tool to Teach Neuroanatomy and Structure-Function Relationships to Undergraduates

PubMed Central

Kennedy, Susan

2013-01-01

In addition to being inherently interesting to students, case studies can serve as useful tools to teach neuroanatomy and demonstrate important relationships between brain structure and function. In most undergraduate courses, however, neuroanatomy is presented to students as a “unit” or chapter, much like other topics (e.g., receptors, pharmacology) covered in the course, over a period of a week or two. In this article, a relatively simple model of teaching neuroanatomy is described in which students are actively engaged in the presentation and discussion of case studies throughout the semester, following a general introduction to the structure of the nervous system. In this way, the teaching of neuroanatomy is “distributed” throughout the semester and put into a more user-friendly context for students as additional topics are introduced. Generally, students report enjoying learning brain structure using this method, and commented positively on the class activities associated with learning brain anatomy. Advantages and disadvantages of such a model are presented, as are suggestions for implementing similar models of undergraduate neuroanatomy education. PMID:24319386

CONSIDERATION OF REACTION INTERMEDIATES IN STRUCTURE-ACTIVITY RELATIONSHIPS: A KEY TO UNDERSTANDING AND PREDICTION

EPA Science Inventory

Consideration of Reaction Intermediates in Structure- Activity Relationships: A Key to Understanding and Prediction

A structure-activity relationship (SAR) represents an empirical means for generalizing chemical information relative to biological activity, and is frequent...

Influence of lipophilicity in O-acyl and O-alkyl derivatives of juglone and lawsone: a structure-activity relationship study in the search for natural herbicide models.

PubMed

Durán, Alexandra G; Chinchilla, Nuria; Molinillo, José Mg; Macías, Francisco A

2018-03-01

Naphthoquinones are known for their broad range of biological activities. Given the increasing demands of consumers in relation to food quality and growing concerns about the impact of synthetic herbicides, it is necessary to search for new agrochemicals. Natural products and allelopathy provide new alternatives for the development of pesticides with lower toxicity and greater environmental compatibility. A structure-activity relationship to evaluate the effect of bioavailability was performed. A total of 44 O-acyl and O-alkyl derivatives of juglone and lawsone with different linear chain lengths were prepared. These compounds were tested on etiolated wheat coleoptiles, standard target species (STS) and four weeds, Echinochloa crus-galli L., Lolium rigidum Gaud., Lolium perenne L. and Avena fatua L. The results showed a strong influence of lipophilicity and, in most cases, the data fitted a logP-dependent quadratic mathematical model. The effects produced were mostly stunting and necrosis caused by growth inhibition. The potential structure and activity behaviour is described. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

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.

Depressive symptoms, lifestyle structure, and ART adherence among HIV-infected individuals: a longitudinal mediation analysis.

PubMed

Magidson, Jessica F; Blashill, Aaron J; Safren, Steven A; Wagner, Glenn J

2015-01-01

Despite the well-documented relationship between depression and antiretroviral therapy (ART) nonadherence, few studies have identified explanatory pathways through which depression affects adherence. The current study tested lifestyle structure-the degree of organization and routinization of daily activities-as a mediator of this relationship, given previous evidence of lifestyle structure being associated with both depression and ART nonadherence. HIV-infected individuals starting or re-starting ART in the California Collaborative Treatment Group 578 study (n = 199) were assessed over 48 weeks. Adherence was measured using electronic monitoring caps to determine dose timing and doses taken, and viral load was assessed. The mediating role of lifestyle structure was tested using generalized linear mixed-effects modeling and bootstrapping. Lifestyle significantly mediated the relationship between depression and both measures of ART adherence behavior. Interventions that minimize disruptions to lifestyle structure and link adherence to daily activities may be useful for individuals with depression and ART nonadherence.

Sexual risk behavior among youth: modeling the influence of prosocial activities and socioeconomic factors.

PubMed

Ramirez-Valles, J; Zimmerman, M A; Newcomb, M D

1998-09-01

Sexual activity among high-school-aged youths has steadily increased since the 1970s, emerging as a significant public health concern. Yet, patterns of youth sexual risk behavior are shaped by social class, race, and gender. Based on sociological theories of financial deprivation and collective socialization, we develop and test a model of the relationships among neighborhood poverty; family structure and social class position; parental involvement; prosocial activities; race; and gender as they predict youth sexual risk behavior. We employ structural equation modeling to test this model on a cross-sectional sample of 370 sexually active high-school students from a midwestern city; 57 percent (n = 209) are males and 86 percent are African American. We find that family structure indirectly predicts sexual risk behavior through neighborhood poverty, parental involvement, and prosocial activities. In addition, family class position indirectly predicts sexual risk behavior through neighborhood poverty and prosocial activities. We address implications for theory and health promotion.

Departmental Contexts and Faculty Research Activity in Norway

ERIC Educational Resources Information Center

Smeby, Jens-Christian; Try, Sverre

2005-01-01

The aim of the paper is to examine the relationship between departmental attributes and university faculty research activity. Since individual and departmental factors are highly interrelated, individual attributes are included in a hierarchical linear model taking into consideration the nested structure of the data. Research activity is measured…

Ecological Structure Activity Relationships

EPA Science Inventory

Ecological Structure Activity Relationships, v1.00a, February 2009
ECOSAR (Ecological Structure Activity Relationships) is a personal computer software program that is used to estimate the toxicity of chemicals used in industry and discharged into water. The program predicts...

Novel approaches to determine contractile function of the isolated adult zebrafish ventricular cardiac myocyte.

PubMed

Dvornikov, Alexey V; Dewan, Sukriti; Alekhina, Olga V; Pickett, F Bryan; de Tombe, Pieter P

2014-05-01

The zebrafish (Danio rerio) has been used extensively in cardiovascular biology, but mainly in the study of heart development. The relative ease of its genetic manipulation may indicate the suitability of this species as a cost-effective model system for the study of cardiac contractile biology. However, whether the zebrafish heart is an appropriate model system for investigations pertaining to mammalian cardiac contractile structure-function relationships remains to be resolved. Myocytes were isolated from adult zebrafish hearts by enzymatic digestion, attached to carbon rods, and twitch force and intracellular Ca(2+) were measured. We observed the modulation of twitch force, but not of intracellular Ca(2+), by both extracellular [Ca(2+)] and sarcomere length. In permeabilized cells/myofibrils, we found robust myofilament length-dependent activation. Moreover, modulation of myofilament activation-relaxation and force redevelopment kinetics by varied Ca(2+) activation levels resembled that found previously in mammalian myofilaments. We conclude that the zebrafish is a valid model system for the study of cardiac contractile structure-function relationships.

Integrated Modeling for Watershed Ecosystem Services Assessment and Forecasting

EPA Science Inventory

Regional scale watershed management decisions must be informed by the science-based relationship between anthropogenic activities on the landscape and the change in ecosystem structure, function, and services that occur as a result. We applied process-based models that represent...

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.

Exploring the relationships between International Classification of Functioning, Disability and Health (ICF) constructs of Impairment, Activity Limitation and Participation Restriction in people with osteoarthritis prior to joint replacement.

PubMed

Pollard, Beth; Johnston, Marie; Dieppe, Paul

2011-05-16

The International Classification of Functioning, Disability and Health (ICF) proposes three main constructs, impairment (I), activity limitation (A) and participation restriction (P). The ICF model allows for all paths between the constructs to be explored, with significant paths likely to vary for different conditions. The relationships between I, A and P have been explored in some conditions but not previously in people with osteoarthritis prior to joint replacement. The aim of this paper is to examine these relationships using separate measures of each construct and structural equation modelling. A geographical cohort of 413 patients with osteoarthritis about to undergo hip and knee joint replacement completed the Aberdeen measures of Impairment, Activity Limitation and Participation Restriction (Ab-IAP). Confirmatory factor analysis was used to test the three factor (I, A, P) measurement model. Structural equation modelling was used to explore the I, A and P pathways in the ICF model. There was support from confirmatory factor analysis for the three factor I, A, P measurement model. The structural equation model had good fit [S-B Chi-square = 439.45, df = 149, CFI robust = 0.91, RMSEA robust = 0.07] and indicated significant pathways between I and A (standardised coefficient = 0.76 p < 0.0001) and between A and P (standardised coefficient = 0.75 p < 0.0001). However, the path between I and P was not significant (standardised coefficient = 0.01). The significant pathways suggest that treatments and interventions aimed at reducing impairment, such as joint replacement, may only affect P indirectly, through A, however, longitudinal data would be needed to establish this.

Simplified molecular input line entry system-based: QSAR modelling for MAP kinase-interacting protein kinase (MNK1).

PubMed

Begum, S; Achary, P Ganga Raju

2015-01-01

Quantitative structure-activity relationship (QSAR) models were built for the prediction of inhibition (pIC50, i.e. negative logarithm of the 50% effective concentration) of MAP kinase-interacting protein kinase (MNK1) by 43 potent inhibitors. The pIC50 values were modelled with five random splits, with the representations of the molecular structures by simplified molecular input line entry system (SMILES). QSAR model building was performed by the Monte Carlo optimisation using three methods: classic scheme; balance of correlations; and balance correlation with ideal slopes. The robustness of these models were checked by parameters as rm(2), r(*)m(2), [Formula: see text] and randomisation technique. The best QSAR model based on single optimal descriptors was applied to study in vitro structure-activity relationships of 6-(4-(2-(piperidin-1-yl) ethoxy) phenyl)-3-(pyridin-4-yl) pyrazolo [1,5-a] pyrimidine derivatives as a screening tool for the development of novel potent MNK1 inhibitors. The effects of alkyl group, -OH, -NO2, F, Cl, Br, I, etc. on the IC50 values towards the inhibition of MNK1 were also reported.

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).

THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY: AN EXPANDED VIEW OF CHEMICAL TOXICITY

EPA Science Inventory

A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. T...

The Mediating Effect of Innovation between Total Quality Management (TQM) and Business Performance

NASA Astrophysics Data System (ADS)

Shan, Ang Wei; Fauzi Ahmad, Mohd; Hisyamudin Muhd Nor, Nik

2016-11-01

Both TQM and Innovation are the competitive key factors that intensely embedded into organizational products, service and process. In order to achieve higher business performance, organizations are needed to adopt both quality and innovation. Therefore, the main objective of this paper is to identify the relationship between TQM and business performance with a mediator's effect of Innovation. After detailed review the extensive literature, a new TQM model is presented. The proposed model integrates the TQM practices and different type of innovation attempt to develop a theoretical knowledge to help academician and manufacturer to understand the relationship that design quality in product and service and engaging innovation in the activities. To this end, the SEM-PLS (Structural Equation Modelling - Partial Least Squares Structural) is used to identify and evaluate the relationship among TQM, Innovation and business performance in establishing a new TQM model.

Arylazolyl(azinyl)thioacetanilides. Part 16: Structure-based bioisosterism design, synthesis and biological evaluation of novel pyrimidinylthioacetanilides as potent HIV-1 inhibitors.

PubMed

Li, Xiao; Lu, Xueyi; Chen, Wenmin; Liu, Huiqing; Zhan, Peng; Pannecouque, Christophe; Balzarini, Jan; De Clercq, Erik; Liu, Xinyong

2014-10-01

A series of novel pyrimidinylthioacetanilides were designed, synthesized, and evaluated for their biological activity as potent HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs). Most of the tested compounds were proved to be effective in inhibiting HIV-1 (IIIB) replication with EC50 ranging from 0.15 μM to 24.2 μM, thereinto compound 15 was the most active lead with favorable inhibitory activity against HIV-1 (IIIB) (EC50=0.15 μM, SI=684). Besides, compound 6 displayed moderate inhibition against the double-mutated HIV-1 strain (K103N/Y181C) (EC50=3.9 μM). Preliminary structure-activity relationships (SARs), structure-cytotoxicity relationships (SCRs) data, and molecular modeling studies were discussed as well, which may provide valuable insights for further optimizations. Copyright © 2014 Elsevier Ltd. All rights reserved.

First structure of full-length mammalian phenylalanine hydroxylase reveals the architecture of an autoinhibited tetramer

PubMed Central

Arturo, Emilia C.; Gupta, Kushol; Héroux, Annie; Stith, Linda; Cross, Penelope J.; Parker, Emily J.; Loll, Patrick J.; Jaffe, Eileen K.

2016-01-01

Improved understanding of the relationship among structure, dynamics, and function for the enzyme phenylalanine hydroxylase (PAH) can lead to needed new therapies for phenylketonuria, the most common inborn error of amino acid metabolism. PAH is a multidomain homo-multimeric protein whose conformation and multimerization properties respond to allosteric activation by the substrate phenylalanine (Phe); the allosteric regulation is necessary to maintain Phe below neurotoxic levels. A recently introduced model for allosteric regulation of PAH involves major domain motions and architecturally distinct PAH tetramers [Jaffe EK, Stith L, Lawrence SH, Andrake M, Dunbrack RL, Jr (2013) Arch Biochem Biophys 530(2):73–82]. Herein, we present, to our knowledge, the first X-ray crystal structure for a full-length mammalian (rat) PAH in an autoinhibited conformation. Chromatographic isolation of a monodisperse tetrameric PAH, in the absence of Phe, facilitated determination of the 2.9 Å crystal structure. The structure of full-length PAH supersedes a composite homology model that had been used extensively to rationalize phenylketonuria genotype–phenotype relationships. Small-angle X-ray scattering (SAXS) confirms that this tetramer, which dominates in the absence of Phe, is different from a Phe-stabilized allosterically activated PAH tetramer. The lack of structural detail for activated PAH remains a barrier to complete understanding of phenylketonuria genotype–phenotype relationships. Nevertheless, the use of SAXS and X-ray crystallography together to inspect PAH structure provides, to our knowledge, the first complete view of the enzyme in a tetrameric form that was not possible with prior partial crystal structures, and facilitates interpretation of a wealth of biochemical and structural data that was hitherto impossible to evaluate. PMID:26884182

Small molecule non-peptide inhibitors of botulinum neurotoxin serotype E: Structure-activity relationship and a pharmacophore model.

PubMed

Kumar, Gyanendra; Agarwal, Rakhi; Swaminathan, Subramanyam

2016-09-15

Botulinum neurotoxins (BoNTs) are the most poisonous biological substance known to humans. They cause flaccid paralysis by blocking the release of acetylcholine at the neuromuscular junction. Here, we report a number of small molecule non-peptide inhibitors of BoNT serotype E. The structure-activity relationship and a pharmacophore model are presented. Although non-peptidic in nature, these inhibitors mimic key features of the uncleavable substrate peptide Arg-Ile-Met-Glu (RIME) of the SNAP-25 protein. Among the compounds tested, most of the potent inhibitors bear a zinc-chelating moiety connected to a hydrophobic and aromatic moiety through a carboxyl or amide linker. All of them show low micromolar IC50 values. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.

Structure-affinity relationship of the interaction between phenolic acids and their derivatives and β-lactoglobulin and effect on antioxidant activity.

PubMed

Wu, Simin; Zhang, Yunyue; Ren, Fazheng; Qin, Yinghui; Liu, Jiaxin; Liu, Jingwen; Wang, Qingyu; Zhang, Hao

2018-04-15

In this study, 71 phenolic acids and their derivatives were used to investigate the structure-affinity relationship of β-lactoglobulin binding, and the effect of this interaction on antioxidant activity. Based on a fluorescence quenching method, an improved mathematical model was adopted to calculate the binding constants, with a correction for the inner-filter effect. Hydroxylation at the 3-position increased the affinity of the phenolic acids for β-lactoglobulin, while hydroxylation at the 2- or 4-positions had a negative effect. Complete methylation of all hydroxy groups, except at the 3-position, enhanced the binding affinity. Replacing the hydroxy groups with methyl groups at the 2-position also had a positive effect. Hydrogen bonding was one of the binding forces for the interaction. The antioxidant activity of phenolic acid-β-lactoglobulin complexes was higher than that of phenolic acids alone. These findings provide an understanding of the structure-activity relationship of the interaction between β-lactoglobulin and phenolic acids. Copyright © 2017 Elsevier Ltd. All rights reserved.

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...

MOAtox: A Comprehensive Mode of Action and Acute Aquatic Toxicity Database for Predictive Model Development

EPA Science Inventory

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

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.

Structural diversity in the dandelion (Taraxacum officinale) polyphenol oxidase family results in different responses to model substrates.

PubMed

Dirks-Hofmeister, Mareike E; Singh, Ratna; Leufken, Christine M; Inlow, Jennifer K; Moerschbacher, Bruno M

2014-01-01

Polyphenol oxidases (PPOs) are ubiquitous type-3 copper enzymes that catalyze the oxygen-dependent conversion of o-diphenols to the corresponding quinones. In most plants, PPOs are present as multiple isoenzymes that probably serve distinct functions, although the precise relationship between sequence, structure and function has not been addressed in detail. We therefore compared the characteristics and activities of recombinant dandelion PPOs to gain insight into the structure-function relationships within the plant PPO family. Phylogenetic analysis resolved the 11 isoenzymes of dandelion into two evolutionary groups. More detailed in silico and in vitro analyses of four representative PPOs covering both phylogenetic groups were performed. Molecular modeling and docking predicted differences in enzyme-substrate interactions, providing a structure-based explanation for grouping. One amino acid side chain positioned at the entrance to the active site (position HB2+1) potentially acts as a "selector" for substrate binding. In vitro activity measurements with the recombinant, purified enzymes also revealed group-specific differences in kinetic parameters when the selected PPOs were presented with five model substrates. The combination of our enzyme kinetic measurements and the in silico docking studies therefore indicate that the physiological functions of individual PPOs might be defined by their specific interactions with different natural substrates.

Homology Models of Melatonin Receptors: Challenges and Recent Advances

PubMed Central

Pala, Daniele; Lodola, Alessio; Bedini, Annalida; Spadoni, Gilberto; Rivara, Silvia

2013-01-01

Melatonin exerts many of its actions through the activation of two G protein-coupled receptors (GPCRs), named MT1 and MT2. So far, a number of different MT1 and MT2 receptor homology models, built either from the prototypic structure of rhodopsin or from recently solved X-ray structures of druggable GPCRs, have been proposed. These receptor models differ in the binding modes hypothesized for melatonin and melatonergic ligands, with distinct patterns of ligand-receptor interactions and putative bioactive conformations of ligands. The receptor models will be described, and they will be discussed in light of the available information from mutagenesis experiments and ligand-based pharmacophore models. The ability of these ligand-receptor complexes to rationalize structure-activity relationships of known series of melatonergic compounds will be commented upon. PMID:23584026

SAR STUDY OF NASAL TOXICITY: LESSONS FOR MODELING SMALL TOXICITY DATASETS

EPA Science Inventory

Most toxicity data, particularly from whole animal bioassays, are generated without the needs or capabilities of structure-activity relationship (SAR) modeling in mind. Some toxicity endpoints have been of sufficient regulatory concern to warrant large scale testing efforts (e.g....

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

Mechanistic Insights into the Specificity of Human Cytosolic Sulfotransferase 2A1 (hSULT2A1) for Hydroxylated Polychlorinated Biphenyls Through the Use of Fluoro-tagged Probes

PubMed Central

Ekuase, E.J.; van ’t Erve, T.J.; Rahaman, A.; Robertson, L.W.; Duffel, M.W.; Luthe, G.

2015-01-01

Determining the relationships between the structures of substrates and inhibitors and their interactions with drug-metabolizing enzymes is of prime importance in predicting the toxic potential of new and legacy xenobiotics. Traditionally, quantitative structure activity relationship (QSAR) studies are performed with many distinct compounds. Based on the chemical properties of the tested compounds, complex relationships can be established so that models can be developed to predict toxicity of novel compounds. In this study, the use of fluorinated analogues as supplemental QSAR compounds was investigated. Substituting fluorine induces changes in electronic and steric properties of the substrate without substantially changing the chemical backbone of the substrate. In vitro assays were performed using purified human cytosolic sulfotransferase hSULT2A1 as a model enzyme. A mono-hydroxylated polychlorinated biphenyl (4-OH PCB 14) and its four possible mono-fluoro analogues were used as test compounds. Remarkable similarities were found between this approach and previously published QSAR studies for hSULT2A1. Both studies implicate the importance of dipole moment and dihedral angle as being important to PCB structure in respect to being substrates for hSULT2A1. We conclude that mono-fluorinated analogues of a target substrate can be a useful tool to study the structure activity relationships for enzyme specificity. PMID:26165989

Progress in the Visualization and Mining of Chemical and Target Spaces.

PubMed

Medina-Franco, José L; Aguayo-Ortiz, Rodrigo

2013-12-01

Chemogenomics is a growing field that aims to integrate the chemical and target spaces. As part of a multi-disciplinary effort to achieve this goal, computational methods initially developed to visualize the chemical space of compound collections and mine single-target structure-activity relationships, are being adapted to visualize and mine complex relationships in chemogenomics data sets. Similarly, the growing evidence that clinical effects are many times due to the interaction of single or multiple drugs with multiple targets, is encouraging the development of novel methodologies that are integrated in multi-target drug discovery endeavors. Herein we review advances in the development and application of approaches to generate visual representations of chemical space with particular emphasis on methods that aim to explore and uncover relationships between chemical and target spaces. Also, progress in the data mining of the structure-activity relationships of sets of compounds screened across multiple targets are discussed in light of the concept of activity landscape modeling. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

New potent and selective cytochrome P450 2B6 (CYP2B6) inhibitors based on three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis

PubMed Central

Korhonen, L E; Turpeinen, M; Rahnasto, M; Wittekindt, C; Poso, A; Pelkonen, O; Raunio, H; Juvonen, R O

2007-01-01

Background and purpose: The cytochrome P450 2B6 (CYP2B6) enzyme metabolises a number of clinically important drugs. Drug-drug interactions resulting from inhibition or induction of CYP2B6 activity may cause serious adverse effects. The aims of this study were to construct a three-dimensional structure-activity relationship (3D-QSAR) model of the CYP2B6 protein and to identify novel potent and selective inhibitors of CYP2B6 for in vitro research purposes. Experimental approach: The inhibition potencies (IC50 values) of structurally diverse chemicals were determined with recombinant human CYP2B6 enzyme. Two successive models were constructed using Comparative Molecular Field Analysis (CoMFA). Key results: Three compounds proved to be very potent and selective competitive inhibitors of CYP2B6 in vitro (IC50<1 μM): 4-(4-chlorobenzyl)pyridine (CBP), 4-(4-nitrobenzyl)pyridine (NBP), and 4-benzylpyridine (BP). A complete inhibition of CYP2B6 activity was achieved with 0.1 μM CBP, whereas other CYP-related activities were not affected. Forty-one compounds were selected for further testing and construction of the final CoMFA model. The created CoMFA model was of high quality and predicted accurately the inhibition potency of a test set (n=7) of structurally diverse compounds. Conclusions and implications: Two CoMFA models were created which revealed the key molecular characteristics of inhibitors of the CYP2B6 enzyme. The final model accurately predicted the inhibitory potencies of several structurally unrelated compounds. CBP, BP and NBP were identified as novel potent and selective inhibitors of CYP2B6 and CBP especially is a suitable inhibitor for in vitro screening studies. PMID:17325652

Testing Theory of Planned Behavior and Neo-Socioanalytic Theory models of trait activity, industriousness, exercise social cognitions, exercise intentions, and physical activity in a representative U.S. sample.

PubMed

Vo, Phuong T; Bogg, Tim

2015-01-01

Prior research identified assorted relations between trait and social cognition models of personality and engagement in physical activity. Using a representative U.S. sample (N = 957), the goal of the present study was to test two alternative structural models of the relationships among the extraversion-related facet of activity, the conscientiousness-related facet of industriousness, social cognitions from the Theory of Planned Behavior (perceived behavioral control, affective attitudes, subjective norms, intentions), Social Cognitive Theory (self-efficacy, outcome expectancies), and the Transtheoretical Model (behavioral processes of change), and engagement in physical activity. Path analyses with bootstrapping procedures were used to model direct and indirect effects of trait and social cognition constructs on physical activity through two distinct frameworks - the Theory of Planned Behavior and Neo-Socioanalytic Theory. While both models showed good internal fit, comparative model information criteria showed the Theory-of-Planned-Behavior-informed model provided a better fit. In the model, social cognitions fully mediated the relationships from the activity facet and industriousness to intentions for and engagement in physical activity, such that the relationships were primarily maintained by positive affective evaluations, positive expected outcomes, and confidence in overcoming barriers related to physical activity engagement. The resultant model - termed the Disposition-Belief-Motivation model- is proposed as a useful framework for organizing and integrating personality trait facets and social cognitions from various theoretical perspectives to investigate the expression of health-related behaviors, such as physical activity. Moreover, the results are discussed in terms of extending the application of the Disposition-Belief-Motivation model to longitudinal and intervention designs for physical activity engagement.

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.

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.

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.

The Significance of G Protein-Coupled Receptor Crystallography for Drug Discovery

PubMed Central

Salon, John A.; Lodowski, David T.

2011-01-01

Crucial as molecular sensors for many vital physiological processes, seven-transmembrane domain G protein-coupled receptors (GPCRs) comprise the largest family of proteins targeted by drug discovery. Together with structures of the prototypical GPCR rhodopsin, solved structures of other liganded GPCRs promise to provide insights into the structural basis of the superfamily's biochemical functions and assist in the development of new therapeutic modalities and drugs. One of the greatest technical and theoretical challenges to elucidating and exploiting structure-function relationships in these systems is the emerging concept of GPCR conformational flexibility and its cause-effect relationship for receptor-receptor and receptor-effector interactions. Such conformational changes can be subtle and triggered by relatively small binding energy effects, leading to full or partial efficacy in the activation or inactivation of the receptor system at large. Pharmacological dogma generally dictates that these changes manifest themselves through kinetic modulation of the receptor's G protein partners. Atomic resolution information derived from increasingly available receptor structures provides an entrée to the understanding of these events and practically applying it to drug design. Supported by structure-activity relationship information arising from empirical screening, a unified structural model of GPCR activation/inactivation promises to both accelerate drug discovery in this field and improve our fundamental understanding of structure-based drug design in general. This review discusses fundamental problems that persist in drug design and GPCR structural determination. PMID:21969326

Testing Theory of Planned Behavior and Neo-Socioanalytic Theory models of trait activity, industriousness, exercise social cognitions, exercise intentions, and physical activity in a representative U.S. sample

PubMed Central

Vo, Phuong T.; Bogg, Tim

2015-01-01

Prior research identified assorted relations between trait and social cognition models of personality and engagement in physical activity. Using a representative U.S. sample (N = 957), the goal of the present study was to test two alternative structural models of the relationships among the extraversion-related facet of activity, the conscientiousness-related facet of industriousness, social cognitions from the Theory of Planned Behavior (perceived behavioral control, affective attitudes, subjective norms, intentions), Social Cognitive Theory (self-efficacy, outcome expectancies), and the Transtheoretical Model (behavioral processes of change), and engagement in physical activity. Path analyses with bootstrapping procedures were used to model direct and indirect effects of trait and social cognition constructs on physical activity through two distinct frameworks – the Theory of Planned Behavior and Neo-Socioanalytic Theory. While both models showed good internal fit, comparative model information criteria showed the Theory-of-Planned-Behavior-informed model provided a better fit. In the model, social cognitions fully mediated the relationships from the activity facet and industriousness to intentions for and engagement in physical activity, such that the relationships were primarily maintained by positive affective evaluations, positive expected outcomes, and confidence in overcoming barriers related to physical activity engagement. The resultant model – termed the Disposition-Belief-Motivation model– is proposed as a useful framework for organizing and integrating personality trait facets and social cognitions from various theoretical perspectives to investigate the expression of health-related behaviors, such as physical activity. Moreover, the results are discussed in terms of extending the application of the Disposition-Belief-Motivation model to longitudinal and intervention designs for physical activity engagement. PMID:26300811

Structure-activity relationship of antiparasitic and cytotoxic indoloquinoline alkaloids, and their tricyclic and bicyclic analogues.

PubMed

Van Baelen, Gitte; Hostyn, Steven; Dhooghe, Liene; Tapolcsányi, Pál; Mátyus, Péter; Lemière, Guy; Dommisse, Roger; Kaiser, Marcel; Brun, Reto; Cos, Paul; Maes, Louis; Hajós, György; Riedl, Zsuzsanna; Nagy, Ildikó; Maes, Bert U W; Pieters, Luc

2009-10-15

Based on the indoloquinoline alkaloids cryptolepine (1), neocryptolepine (2), isocryptolepine (3) and isoneocryptolepine (4), used as lead compounds for new antimalarial agents, a series of tricyclic and bicyclic analogues, including carbolines, azaindoles, pyrroloquinolines and pyrroloisoquinolines was synthesized and biologically evaluated. None of the bicyclic compounds was significantly active against the chloroquine-resistant strain Plasmodium falciparum K1, in contrast to the tricyclic derivatives. The tricyclic compound 2-methyl-2H-pyrido[3,4-b]indole (9), or 2-methyl-beta-carboline, showed the best in vitro activity, with an IC(50) value of 0.45 microM against P. falciparum K1, without apparent cytotoxicity against L6 cells (SI>1000). However, this compound was not active in the Plasmodium berghei mouse model. Structure-activity relationships are discussed and compared with related naturally occurring compounds.

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.

Reverse engineering the gap gene network of Drosophila melanogaster.

PubMed

Perkins, Theodore J; Jaeger, Johannes; Reinitz, John; Glass, Leon

2006-05-01

A fundamental problem in functional genomics is to determine the structure and dynamics of genetic networks based on expression data. We describe a new strategy for solving this problem and apply it to recently published data on early Drosophila melanogaster development. Our method is orders of magnitude faster than current fitting methods and allows us to fit different types of rules for expressing regulatory relationships. Specifically, we use our approach to fit models using a smooth nonlinear formalism for modeling gene regulation (gene circuits) as well as models using logical rules based on activation and repression thresholds for transcription factors. Our technique also allows us to infer regulatory relationships de novo or to test network structures suggested by the literature. We fit a series of models to test several outstanding questions about gap gene regulation, including regulation of and by hunchback and the role of autoactivation. Based on our modeling results and validation against the experimental literature, we propose a revised network structure for the gap gene system. Interestingly, some relationships in standard textbook models of gap gene regulation appear to be unnecessary for or even inconsistent with the details of gap gene expression during wild-type development.

Use it or lose it: engaged lifestyle as a buffer of cognitive decline in aging?

PubMed

Hultsch, D F; Hertzog, C; Small, B J; Dixon, R A

1999-06-01

Data from the Victoria Longitudinal Study were used to examine the hypothesis that maintaining intellectual engagement through participation in everyday activities buffers individuals against cognitive decline in later life. The sample consisted of 250 middle-aged and older adults tested 3 times over 6 years. Structural equation modeling techniques were used to examine the relationships among changes in lifestyle variables and an array of cognitive variables. There was a relationship between changes in intellectually related activities and changes in cognitive functioning. These results are consistent with the hypothesis that intellectually engaging activities serve to buffer individuals against decline. However, an alternative model suggested the findings were also consistent with the hypothesis that high-ability individuals lead intellectually active lives until cognitive decline in old age limits their activities.

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...

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.

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 role of general system theory for functional neuroimaging.

PubMed

Stephan, Klaas Enno

2004-12-01

One of the most important goals of neuroscience is to establish precise structure-function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure-function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure-function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples.

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.

A Comparative Study of Successful Central Nervous System Drugs Using Molecular Modeling

ERIC Educational Resources Information Center

Kim, Hyosub; Sulaimon, Segun; Menezes, Sandra; Son, Anne; Menezes, Warren J. C.

2011-01-01

Molecular modeling is a powerful tool used for three-dimensional visualization and for exploring electrostatic forces involved in drug transport. This tool enhances student understanding of structure-property relationships, as well as actively engaging them in class. Molecular modeling of several central nervous system (CNS) drugs is used to…

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

THE USE OF STRUCTURE-ACTIVITY RELATIONSHIPS IN INTEGRATING THE CHEMISTRY AND TOXICOLOGY OF ENDOCRINE DISRUPTING CHEMICALS

EPA Science Inventory

Structure activity relationships (SARs) are based on the principle that structurally similar chemicals should have similar biological activity. SARs relate specifically-defined toxicological activity of chemicals to their molecular structure and physico-chemical properties. To de...

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.

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.

STRUCTURE-ACTIVITY RELATIONSHIPS--COMPUTERIZED SYSTEMS

EPA Science Inventory

This report discusses some important general strategies and issuesrelative to the application of computational SAR techniques formodeling genotoxicity and carcinogenicity endpoints. roblemsparticular to the SAR modeling of such endpoints pertain to: hecomplexity of the carcinogen...

A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts

PubMed Central

Pizzo, Fabiola; Lombardo, Anna; Manganaro, Alberto; Benfenati, Emilio

2016-01-01

The prompt identification of chemical molecules with potential effects on liver may help in drug discovery and in raising the levels of protection for human health. Besides in vitro approaches, computational methods in toxicology are drawing attention. We built a structure-activity relationship (SAR) model for evaluating hepatotoxicity. After compiling a data set of 950 compounds using data from the literature, we randomly split it into training (80%) and test sets (20%). We also compiled an external validation set (101 compounds) for evaluating the performance of the model. To extract structural alerts (SAs) related to hepatotoxicity and non-hepatotoxicity we used SARpy, a statistical application that automatically identifies and extracts chemical fragments related to a specific activity. We also applied the chemical grouping approach for manually identifying other SAs. We calculated accuracy, specificity, sensitivity and Matthews correlation coefficient (MCC) on the training, test and external validation sets. Considering the complexity of the endpoint, the model performed well. In the training, test and external validation sets the accuracy was respectively 81, 63, and 68%, specificity 89, 33, and 33%, sensitivity 93, 88, and 80% and MCC 0.63, 0.27, and 0.13. Since it is preferable to overestimate hepatotoxicity rather than not to recognize unsafe compounds, the model's architecture followed a conservative approach. As it was built using human data, it might be applied without any need for extrapolation from other species. This model will be freely available in the VEGA platform. PMID:27920722

Departments of Defense and Agriculture Team Up to Develop New Insecticides for Mosquito Control

DTIC Science & Technology

2010-01-01

archives of insecticide data by quantita- tive structure-activity relationship ( QSAR ) modeling to predict and synthesize new insecticides. This...blood- sucking arthropods. The key thrust of IIBBL’s approach involves QSAR -based modeling of fast-acting pyrethroid insecticides to predict and

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 ...

Estimation of Physical Properties and Chemical Reactivity Parameters of Organic Compounds for Environmental Modeling by SPARC

EPA Science Inventory

Mathematical models for predicting the transport and fate of pollutants in the environment require reactivity parameter values that is value of the physical and chemical constants that govern reactivity. Although empirical structure activity relationships have been developed th...

The mechanics of fault-bend folding and tear-fault systems in the Niger Delta

NASA Astrophysics Data System (ADS)

Benesh, Nathan Philip

This dissertation investigates the mechanics of fault-bend folding using the discrete element method (DEM) and explores the nature of tear-fault systems in the deep-water Niger Delta fold-and-thrust belt. In Chapter 1, we employ the DEM to investigate the development of growth structures in anticlinal fault-bend folds. This work was inspired by observations that growth strata in active folds show a pronounced upward decrease in bed dip, in contrast to traditional kinematic fault-bend fold models. Our analysis shows that the modeled folds grow largely by parallel folding as specified by the kinematic theory; however, the process of folding over a broad axial surface zone yields a component of fold growth by limb rotation that is consistent with the patterns observed in natural folds. This result has important implications for how growth structures can he used to constrain slip and paleo-earthquake ages on active blind-thrust faults. In Chapter 2, we expand our DEM study to investigate the development of a wider range of fault-bend folds. We examine the influence of mechanical stratigraphy and quantitatively compare our models with the relationships between fold and fault shape prescribed by the kinematic theory. While the synclinal fault-bend models closely match the kinematic theory, the modeled anticlinal fault-bend folds show robust behavior that is distinct from the kinematic theory. Specifically, we observe that modeled structures maintain a linear relationship between fold shape (gamma) and fault-horizon cutoff angle (theta), rather than expressing the non-linear relationship with two distinct modes of anticlinal folding that is prescribed by the kinematic theory. These observations lead to a revised quantitative relationship for fault-bend folds that can serve as a useful interpretation tool. Finally, in Chapter 3, we examine the 3D relationships of tear- and thrust-fault systems in the western, deep-water Niger Delta. Using 3D seismic reflection data and new map-based structural restoration techniques, we find that the tear faults have distinct displacement patterns that distinguish them from conventional strike-slip faults and reflect their roles in accommodating displacement gradients within the fold-and-thrust belt.

Selection of appropriate training and validation set chemicals for modelling dermal permeability by U-optimal design.

PubMed

Xu, G; Hughes-Oliver, J M; Brooks, J D; Yeatts, J L; Baynes, R E

2013-01-01

Quantitative structure-activity relationship (QSAR) models are being used increasingly in skin permeation studies. The main idea of QSAR modelling is to quantify the relationship between biological activities and chemical properties, and thus to predict the activity of chemical solutes. As a key step, the selection of a representative and structurally diverse training set is critical to the prediction power of a QSAR model. Early QSAR models selected training sets in a subjective way and solutes in the training set were relatively homogenous. More recently, statistical methods such as D-optimal design or space-filling design have been applied but such methods are not always ideal. This paper describes a comprehensive procedure to select training sets from a large candidate set of 4534 solutes. A newly proposed 'Baynes' rule', which is a modification of Lipinski's 'rule of five', was used to screen out solutes that were not qualified for the study. U-optimality was used as the selection criterion. A principal component analysis showed that the selected training set was representative of the chemical space. Gas chromatograph amenability was verified. A model built using the training set was shown to have greater predictive power than a model built using a previous dataset [1].

A novel two-step hierarchical quantitative structure-activity relationship modeling work flow for predicting acute toxicity of chemicals in rodents.

PubMed

Zhu, Hao; Ye, Lin; Richard, Ann; Golbraikh, Alexander; Wright, Fred A; Rusyn, Ivan; Tropsha, Alexander

2009-08-01

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. A wealth of available biological data requires new computational approaches to link chemical structure, in vitro data, and potential adverse health effects. A database containing experimental cytotoxicity values for in vitro half-maximal inhibitory concentration (IC(50)) and in vivo rodent median lethal dose (LD(50)) for more than 300 chemicals was compiled by Zentralstelle zur Erfassung und Bewertung von Ersatz- und Ergaenzungsmethoden zum Tierversuch (ZEBET; National Center for Documentation and Evaluation of Alternative Methods to Animal Experiments). The application of conventional quantitative structure-activity relationship (QSAR) modeling approaches to predict mouse or rat acute LD(50) values from chemical descriptors of ZEBET compounds yielded no statistically significant models. The analysis of these data showed no significant correlation between IC(50) and LD(50). However, a linear IC(50) versus LD(50) correlation could be established for a fraction of compounds. To capitalize on this observation, we developed a novel two-step modeling approach as follows. First, all chemicals are partitioned into two groups based on the relationship between IC(50) and LD(50) values: One group comprises compounds with linear IC(50) versus LD(50) relationships, and another group comprises the remaining compounds. Second, we built conventional binary classification QSAR models to predict the group affiliation based on chemical descriptors only. Third, we developed k-nearest neighbor continuous QSAR models for each subclass to predict LD(50) values from chemical descriptors. All models were extensively validated using special protocols. The novelty of this modeling approach is that it uses the relationships between in vivo and in vitro data only to inform the initial construction of the hierarchical two-step QSAR models. Models resulting from this approach employ chemical descriptors only for external prediction of acute rodent toxicity.

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

INTER-SPECIES COMPARISONS AND SAR MODELLING OF ESTROGENICITY USING RAINBOW TROUT ER BINDING DATA

EPA Science Inventory

The U.S. EPA has been mandated to screen industrial chemicals and pesticides for potential endocrine activity. Structure-activity relationships (SARs) to predict receptor binding are being developed as a first step to rank and prioritize chemicals for testing in bioassays. First ...

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.

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.

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

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.

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.

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.

Structural brain correlates of unconstrained motor activity in people with schizophrenia.

PubMed

Farrow, Tom F D; Hunter, Michael D; Wilkinson, Iain D; Green, Russell D J; Spence, Sean A

2005-11-01

Avolition affects quality of life in chronic schizophrenia. We investigated the relationship between unconstrained motor activity and the volume of key executive brain regions in 16 male patients with schizophrenia. Wristworn actigraphy monitors were used to record motor activity over a 20 h period. Structural magnetic resonance imaging brain scans were parcellated and individual volumes for anterior cingulate cortex and dorsolateral prefrontal cortex extracted. Patients'total activity was positively correlated with volume of left anterior cingulate cortex. These data suggest that the volume of specific executive structures may affect (quantifiable) motor behaviours, having further implications for models of the 'will' and avolition.

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.

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

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...

Structure-activity relationships for novel drug precursor N-substituted-6-acylbenzothiazolon derivatives: A theoretical approach

NASA Astrophysics Data System (ADS)

Sıdır, Yadigar Gülseven; Sıdır, İsa

2013-08-01

In this study, the twelve new modeled N-substituted-6-acylbenzothiazolon derivatives having analgesic analog structure have been investigated by quantum chemical methods using a lot of electronic parameters and structure-activity properties; such as molecular polarizability (α), dipole moment (μ), EHOMO, ELUMO, q-, qH+, molecular volume (Vm), ionization potential (IP), electron affinity (EA), electronegativity (χ), molecular hardness (η), molecular softness (S), electrophilic index (ω), heat of formation (HOF), molar refractivity (MR), octanol-water partition coefficient (log P), thermochemical properties (entropy (S), capacity of heat (Cv)); as to investigate activity relationships with molecular structure. The correlations of log P with Vm, MR, ω, EA, EHOMO - ELUMO (ΔE), HOF in aqueous phase, χ, μ, S, η parameters, respectively are obtained, while the linear relation of log P with IP, Cv, HOF in gas phase are not observed. The log P parameter is obtained to be depending on different properties of compounds due to their complexity.

[Identification of the cumulative eco-environment effect of coal-electricity integration based on interpretative structural model].

PubMed

Han, Lin Wei; Fu, Xiao; Yan, Yan; Wang, Chen Xing; Wu, Gang

2017-05-18

In order to determine the cumulative eco-environmental effect of coal-electricity integration, we selected 29 eco-environmental factors including different development and construction activities of coal-electricity integration, soil, water, atmospheric conditions, biology, landscape, and ecology. Literature survey, expert questionnaire and interview were conducted to analyze the interactive relationships between different factors. The structure and correlations between the eco-environmental factors influenced by coal-electricity integration activities were analyzed using interpretive structural modeling (ISM) and the cumulative eco-environment effect of development and construction activities was determined. A research and evaluation framework for the cumulative eco-environmental effect was introduced in addition to specific evaluation and management needs. The results of this study would provide a theoretical and technical basis for planning and management of coal-electricity integration development activities.

Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

PubMed

Cunningham, Albert R; Carrasquer, C Alex; Qamar, Shahid; Maguire, Jon M; Cunningham, Suzanne L; Trent, John O

2012-10-01

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby's structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity.

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

Structure-Activity Relationship Studies and Molecular Modeling of Naphthalene-Based Sphingosine Kinase 2 Inhibitors.

PubMed

Congdon, Molly D; Kharel, Yugesh; Brown, Anne M; Lewis, Stephanie N; Bevan, David R; Lynch, Kevin R; Santos, Webster L

2016-03-10

The two isoforms of sphingosine kinase (SphK1 and SphK2) are the only enzymes that phosphorylate sphingosine to sphingosine-1-phosphate (S1P), which is a pleiotropic lipid mediator involved in a broad range of cellular processes including migration, proliferation, and inflammation. SphKs are targets for various diseases such as cancer, fibrosis, and Alzheimer's and sickle cell disease. Herein, we disclose the structure-activity profile of naphthalene-containing SphK inhibitors and molecular modeling studies that reveal a key molecular switch that controls SphK selectivity.

Chemistry and Structure-Activity Relationships of Psychedelics.

PubMed

Nichols, David E

2018-01-01

This chapter will summarize structure-activity relationships (SAR) that are known for the classic serotonergic hallucinogens (aka psychedelics), focusing on the three chemical types: tryptamines, ergolines, and phenethylamines. In the brain, the serotonin 5-HT 2A receptor plays a key role in regulation of cortical function and cognition, and also appears to be the principal target for hallucinogenic/psychedelic drugs such as LSD. It is one of the most extensively studied of the 14 known types of serotonin receptors. Important structural features will be identified for activity and, where possible, those that the psychedelics have in common will be discussed. Because activation of the 5-HT 2A receptor is the principal mechanism of action for psychedelics, compounds with 5-HT 2A agonist activity generally are quickly discarded by the pharmaceutical industry. Thus, most of the research on psychedelics can be related to activation of 5-HT 2A receptors. Therefore, much of the discussion will include not only clinical or anecdotal studies, but also will consider data from animal models as well as a certain amount of molecular pharmacology where it is known.

Antitumor potential of crown ethers: structure-activity relationships, cell cycle disturbances, and cell death studies of a series of ionophores.

PubMed

Marjanović, Marko; Kralj, Marijeta; Supek, Fran; Frkanec, Leo; Piantanida, Ivo; Smuc, Tomislav; Tusek-Bozić, Ljerka

2007-03-08

The present paper demonstrates the antiproliferative ability and structure-activity relationships (SAR) of 14 crown and aza-crown ether analogues on five tumor-cell types. The most active compounds were di-tert-butyldicyclohexano-18-crown-6 (3), which exhibited cytotoxicity in the submicromolar range, and di-tert-butyldibenzo-18-crown-6 (5) (IC50 values of approximately 2 microM). Also, 3 and 5 induced marked influence on the cell cycle phase distribution--strong G1 arrest, followed by the induction of apoptosis. A computational SAR modeling effort offers insight into possible mechanisms of crown ether biological activity, presumably involving penetration into cell membranes, and points out structural features of molecules important for this activity. The results reveal that crown ethers possess marked tumor-cell growth inhibitory activity, the extent of which depends on the characteristics of the hydrophilic macrocylic cavity and the surrounding hydrophobic ring. Our work supports the hypothesis that crown ether compounds inhibit tumor-cell growth by disrupting potassium ion homeostasis, which in turn leads to cell cycle perturbations and apoptosis.

Modeling the relationship between family home environment factors and parental health.

PubMed

Didericksen, Katharine Wickel; Berge, Jerica M

2015-06-01

Understanding parental health is an important part of understanding family health. Previous research suggests that family meals, familial relationship satisfaction, and family physical activity may separately be related to physical health. The current study aims to combine these variables into a structural equation model to determine the collective relationship they have with adult health within a sample of parents (n = 1,435). Most parents were married, White, and highly educated. The relationship between family meals and parental health was significant (β = -.07, t = -2.29, p < .05), with the full model having adequate fit and accounting for some of the overall variance in parental health. Familial relationship satisfaction and family physical activity were not found to be associated with parental health. Exploratory findings of the sample stratified by biological sex are described. Findings from the current study were consistent with a systemic perspective in that parents may have health benefits when they participate in family-level behavior (e.g., family meals). Additional areas for research and limitations to the current study are also discussed. (c) 2015 APA, all rights reserved).

Structural Diversity in the Dandelion (Taraxacum officinale) Polyphenol Oxidase Family Results in Different Responses to Model Substrates

PubMed Central

Dirks-Hofmeister, Mareike E.; Singh, Ratna; Leufken, Christine M.; Inlow, Jennifer K.; Moerschbacher, Bruno M.

2014-01-01

Polyphenol oxidases (PPOs) are ubiquitous type-3 copper enzymes that catalyze the oxygen-dependent conversion of o-diphenols to the corresponding quinones. In most plants, PPOs are present as multiple isoenzymes that probably serve distinct functions, although the precise relationship between sequence, structure and function has not been addressed in detail. We therefore compared the characteristics and activities of recombinant dandelion PPOs to gain insight into the structure–function relationships within the plant PPO family. Phylogenetic analysis resolved the 11 isoenzymes of dandelion into two evolutionary groups. More detailed in silico and in vitro analyses of four representative PPOs covering both phylogenetic groups were performed. Molecular modeling and docking predicted differences in enzyme-substrate interactions, providing a structure-based explanation for grouping. One amino acid side chain positioned at the entrance to the active site (position HB2+1) potentially acts as a “selector” for substrate binding. In vitro activity measurements with the recombinant, purified enzymes also revealed group-specific differences in kinetic parameters when the selected PPOs were presented with five model substrates. The combination of our enzyme kinetic measurements and the in silico docking studies therefore indicate that the physiological functions of individual PPOs might be defined by their specific interactions with different natural substrates. PMID:24918587

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.

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

Influence of perceived sport competence and body attractiveness on physical activity and other healthy lifestyle habits in adolescents.

PubMed

Moreno-Murcia, Juan Antonio; Hellín, Pedro; González-Cutre, David; Martínez-Galindo, Celestina

2011-05-01

The purpose of this study was to test an explanatory model of the relationships between physical self-concept and some healthy habits. A sample of 472 adolescents aged 16 to 20 answered different questionnaires assessing physical self-concept, physical activity, intention to be physically active and consumption of alcohol and tobacco. The results of the structural equation model showed that perceived sport competence positively correlated with current physical activity. Body attractiveness positively correlated with physical activity in boys and negatively in girls. Current physical activity positively correlated with the intention to be physically active in the future and negatively with the consumption of alcohol and tobacco. Nevertheless, this last relationship was only significant in boys. The results are discussed in connection with the promotion of healthy lifestyle guidelines among adolescents. This model shows the importance of physical self-concept for engaging in physical activity in adolescence. It also suggests that physical activity is associated with the intention to continue being physically active and with healthy lifestyle habits.

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.

Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study on acetylcholinesterase

NASA Astrophysics Data System (ADS)

Andersson, C. David; Hillgren, J. Mikael; Lindgren, Cecilia; Qian, Weixing; Akfur, Christine; Berg, Lotta; Ekström, Fredrik; Linusson, Anna

2015-03-01

Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to illustrate benefits of performing a statistical molecular design (SMD) and proper statistical analysis of the molecules' properties before SAR and quantitative structure-activity relationship (QSAR) analysis. Our SMD followed by synthesis yielded a set of inhibitors of the enzyme acetylcholinesterase (AChE) that had very few inherent dependencies between the substructures in the molecules. If such dependencies exist, they cause severe errors in SAR interpretation and predictions by QSAR-models, and leave a set of molecules less suitable for future decision-making. In our study, SAR- and QSAR models could show which molecular sub-structures and physicochemical features that were advantageous for the AChE inhibition. Finally, the QSAR model was used for the prediction of the inhibition of AChE by an external prediction set of molecules. The accuracy of these predictions was asserted by statistical significance tests and by comparisons to simple but relevant reference models.

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.

Molecular Docking, Molecular Dynamics, and Structure-Activity Relationship Explorations of 14-Oxygenated N-Methylmorphinan-6-ones as Potent μ-Opioid Receptor Agonists.

PubMed

Noha, Stefan M; Schmidhammer, Helmut; Spetea, Mariana

2017-06-21

Among opioids, morphinans are of major importance as the most effective analgesic drugs acting primarily via μ-opioid receptor (μ-OR) activation. Our long-standing efforts in the field of opioid analgesics from the class of morphinans led to N-methylmorphinan-6-ones differently substituted at positions 5 and 14 as μ-OR agonists inducing potent analgesia and fewer undesirable effects. Herein we present the first thorough molecular modeling study and structure-activity relationship (SAR) explorations aided by docking and molecular dynamics (MD) simulations of 14-oxygenated N-methylmorphinan-6-ones to gain insights into their mode of binding to the μ-OR and interaction mechanisms. The structure of activated μ-OR provides an essential model for how ligand/μ-OR binding is encoded within small chemical differences in otherwise structurally similar morphinans. We reveal important molecular interactions that these μ-agonists share and distinguish them. The molecular docking outcomes indicate the crucial role of the relative orientation of the ligand in the μ-OR binding site, influencing the propensity of critical non-covalent interactions that are required to facilitate ligand/μ-OR interactions and receptor activation. The MD simulations point out minor differences in the tendency to form hydrogen bonds by the 4,5α-epoxy group, along with the tendency to affect the 3-7 lock switch. The emerged SARs reveal the subtle interplay between the substituents at positions 5 and 14 in the morphinan scaffold by enabling the identification of key structural elements that determine the distinct pharmacological profiles. This study provides a significant structural basis for understanding ligand binding and μ-OR activation by the 14-oxygenated N-methylmorphinan-6-ones, which should be useful for guiding drug design.

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.

Physical activity, self-efficacy, and quality of life in older Czech adults.

PubMed

Mudrak, Jiri; Stochl, Jan; Slepicka, Pavel; Elavsky, Steriani

2016-03-01

Despite efforts to expand global physical activity (PA) surveillance data to include both low- and high-income countries worldwide, our understanding of the relationship between PA and quality of life (QOL) in older adults from culturally diverse backgrounds is limited. We tested McAuley's social-cognitive model of the PA-QOL relationship in the cultural context of the Czech Republic, a post-communist central European country. A total of 546 older Czech adults (mean age 68 years) completed a battery of questionnaires assessing indicators of PA, self-efficacy, health status, and global QOL. A structural equation model was used to test the relationship between PA and QOL. The model hypothesized an indirect relationship between PA and QOL: PA predicted self-efficacy, which in turn predicted global QOL through mental and physical health status. The analyses indicated an acceptable fit of the proposed model, albeit with different emphases than those of studies from Western countries. Above all, we observed a stronger effect of PA on self-efficacy and a weaker mediating effect of health status on the PA-QOL relationship. Our findings supported the validity of McAuley's PA-QOL social-cognitive model for a non-Western cultural context. However, it seems that self-efficacy and health status may influence the PA-QOL relationship in this population in a manner different from that proposed in McAuley's model.

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.

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...

The NMR Structure of Human Obestatin in Membrane-Like Environments: Insights into the Structure-Bioactivity Relationship of Obestatin

PubMed Central

Gurriarán-Rodríguez, Uxía; Mosteiro, Carlos S.; Álvarez-Pérez, Juan C.; Otero-Alén, María; Camiña, Jesús P.; Gallego, Rosalía; García-Caballero, Tomás; Martín-Pastor, Manuel; Casanueva, Felipe F.; Jiménez-Barbero, Jesús; Pazos, Yolanda

2012-01-01

The quest for therapeutic applications of obestatin involves, as a first step, the determination of its 3D solution structure and the relationship between this structure and the biological activity of obestatin. On this basis, we have employed a combination of circular dichroism (CD), nuclear magnetic resonance (NMR) spectroscopy, and modeling techniques to determine the solution structure of human obestatin (1). Other analogues, including human non-amidated obestatin (2) and the fragment peptides (6–23)-obestatin (3), (11–23)-obestatin (4), and (16–23)-obestatin (5) have also been scrutinized. These studies have been performed in a micellar environment to mimic the cell membrane (sodium dodecyl sulfate, SDS). Furthermore, structural-activity relationship studies have been performed by assessing the in vitro proliferative capabilities of these peptides in the human retinal pigmented epithelial cell line ARPE-19 (ERK1/2 and Akt phosphorylation, Ki67 expression, and cellular proliferation). Our findings emphasize the importance of both the primary structure (composition and size) and particular segments of the obestatin molecule that posses significant α-helical characteristics. Additionally, details of a species-specific role for obestatin have also been hypothesized by comparing human and mouse obestatins (1 and 6, respectively) at both the structural and bioactivity levels. PMID:23056203

The NMR structure of human obestatin in membrane-like environments: insights into the structure-bioactivity relationship of obestatin.

PubMed

Alén, Begoña O; Nieto, Lidia; Gurriarán-Rodríguez, Uxía; Mosteiro, Carlos S; Álvarez-Pérez, Juan C; Otero-Alén, María; Camiña, Jesús P; Gallego, Rosalía; García-Caballero, Tomás; Martín-Pastor, Manuel; Casanueva, Felipe F; Jiménez-Barbero, Jesús; Pazos, Yolanda

2012-01-01

The quest for therapeutic applications of obestatin involves, as a first step, the determination of its 3D solution structure and the relationship between this structure and the biological activity of obestatin. On this basis, we have employed a combination of circular dichroism (CD), nuclear magnetic resonance (NMR) spectroscopy, and modeling techniques to determine the solution structure of human obestatin (1). Other analogues, including human non-amidated obestatin (2) and the fragment peptides (6-23)-obestatin (3), (11-23)-obestatin (4), and (16-23)-obestatin (5) have also been scrutinized. These studies have been performed in a micellar environment to mimic the cell membrane (sodium dodecyl sulfate, SDS). Furthermore, structural-activity relationship studies have been performed by assessing the in vitro proliferative capabilities of these peptides in the human retinal pigmented epithelial cell line ARPE-19 (ERK1/2 and Akt phosphorylation, Ki67 expression, and cellular proliferation). Our findings emphasize the importance of both the primary structure (composition and size) and particular segments of the obestatin molecule that posses significant α-helical characteristics. Additionally, details of a species-specific role for obestatin have also been hypothesized by comparing human and mouse obestatins (1 and 6, respectively) at both the structural and bioactivity levels.

The Influence of Race-Ethnicity and Physical Activity Levels on Elementary School Achievement

ERIC Educational Resources Information Center

Caldas, Stephen J.; Reilly, Monique S.

2018-01-01

The authors used structural equation modeling to map the relationships between student race-ethnicity via the mediating variable physical activity on English language arts (ELA) and mathematics achievement among 964 fourth- and fifth-grade students. The students attended a New York City Metropolitan area school district and completed the Physical…

Design of Aminobenzothiazole Inhibitors of Rho Kinases 1 and 2 by Using Protein Kinase A as a Structure Surrogate.

PubMed

Judge, Russell A; Vasudevan, Anil; Scott, Victoria E; Simler, Gricelda H; Pratt, Steve D; Namovic, Marian T; Putman, C Brent; Aguirre, Ana; Stoll, Vincent S; Mamo, Mulugeta; Swann, Steven I; Cassar, Steven C; Faltynek, Connie R; Kage, Karen L; Boyce-Rustay, Janel M; Hobson, Adrian D

2018-03-16

We describe the design, synthesis, and structure-activity relationships (SARs) of a series of 2-aminobenzothiazole inhibitors of Rho kinases (ROCKs) 1 and 2, which were optimized to low nanomolar potencies by use of protein kinase A (PKA) as a structure surrogate to guide compound design. A subset of these molecules also showed robust activity in a cell-based myosin phosphatase assay and in a mechanical hyperalgesia in vivo pain model. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The power of social networks and social support in promotion of physical activity and body mass index among African American adults.

PubMed

Flórez, Karen R; Richardson, Andrea S; Ghosh-Dastidar, Madhumita Bonnie; Troxel, Wendy; DeSantis, Amy; Colabianchi, Natalie; Dubowitz, Tamara

2018-04-01

Social support and social networks can elucidate important structural and functional aspects of social relationships that are associated with health-promoting behaviors, including Physical Activity (PA) and weight. A growing number of studies have investigated the relationship between social support, social networks, PA and obesity specifically among African Americans; however, the evidence is mixed and many studies focus exclusively on African American women. Most studies have also focused on either functional or structural aspects of social relationships (but not both) and few have objectively measured moderate-to-vigorous physical activity (MVPA) and body mass index (BMI). Cross-sectional surveys of adult African American men and women living in two low-income predominantly African American neighborhoods in Pittsburgh, PA (N = 799) measured numerous structural features as well as functional aspects of social relationships. Specifically, structural features included social isolation, and social network size and diversity. Functional aspects included perceptions of social support for physical activity from the social network in general as well as from family and friends specifically. Height, weight, and PA were objectively measured. From these, we derived Body Mass Index (BMI) and moderate-to-vigorous physical activity (MVPA). All regression models were stratified by gender, and included age, income, education, employment, marital status, physical limitations, and a neighborhood indicator. Greater social isolation was a significant predictor of lower BMI among men only. Among women only, social isolation was significantly associated with increased MVPA whereas, network diversity was significantly associated with reduced MVPA. Future research would benefit from in-depth qualitative investigations to understand how social networks may act to influence different types of physical activity among African Americans, as well as understand how they can be possible levers for health promotion and prevention.

Database Technology Activities and Assessment for Defense Modeling and Simulation Office (DMSO) (August 1991-November 1992). A Documented Briefing

DTIC Science & Technology

1994-01-01

databases and identifying new data entities, data elements, and relationships . - Standard data naming conventions, schema, and definition processes...management system. The use of such a tool could offer: (1) structured support for representation of objects and their relationships to each other (and...their relationships to related multimedia objects such as an engineering drawing of the tank object or a satellite image that contains the installation

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

Structure-Antimicrobial Activity Relationship for a New Class of Antimicrobials, Silanols, in Comparison to Alcohols and Phenols

DTIC Science & Technology

2006-08-01

equations for the antimicrobial activities and the structural properties of the silanols, the alcohols, and the phenols against four bacteria.........59 4... equations in Table 4-3. ...................................69 ix 4-6 Comparison data of PRESS and RMSPE of different classes of external compounds against...manner as shown in Equation 1-1. Hansch and Fujita derived a correlation model Equation 1-2 based on the linear free energy approach using

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.

[Physical activity, obesity and self-esteem in chilean schoolchildren].

PubMed

Zurita-Ortega, Félix; Castro-Sánchez, Manuel; Rodríguez-Fernández, Sonia; Cofré-Boladós, Cristian; Chacón-Cuberos, Ramón; Martínez-Martínez, Asunción; Muros-Molina, José Joaquín

2017-03-01

Obesity is a worldwide epidemic disease and a problem for the Chilean society. To analyze the relationship between physical condition, body mass index (BMI), level of physical activity and self-esteem. Material ad Methods: Questionnaires to assess self-esteem (Rosemberg scale) and levels of physical activity (Physical Activity Questionnaire for older Children, PAQ-C) were answered by 515 children aged 10.5 ± 0.5 years from 27 schools of Santiago de Chile. BMI was calculated. Course-Navette test was carried out, vertical jump and hand dynamometry were measured. For statistical analysis, structural equations were used. An acceptable goodness of fit for the models was found. There was a positive relationship between BMI and hand dynamometry, as well as a negative relationship between BMI and maximal oxygen consumption, jumping ability, physical activity and self-esteem. Finally, self-esteem was positively related to physical activity engagement. In these children, self-esteem was related to physical activity variables.

Protective activity of (1S,2E,4R,6R,7E,11E)-2,7,11-cembratriene-4,6-diol analogues against diisopropylfluorophosphate neurotoxicity: preliminary structure-activity relationship and pharmacophore modeling.

PubMed

Eterović, Vesna A; Del Valle-Rodriguez, Angelie; Pérez, Dinely; Carrasco, Marimée; Khanfar, Mohammad A; El Sayed, Khalid A; Ferchmin, Pedro A

2013-08-01

Diisopropylfluorophosphate (DFP) is an organophosphorous insecticide used as a surrogate for the more toxic chemical warfare nerve agent sarin. DFP produces neurotoxicity in vivo and irreversibly decreases the area of population spikes recorded from the CA1 region of acute hippocampal slices. (1S,2E,4R,6R,7E,11E)-2,7,11-Cembratriene-4,6-diol (1) is a neuroprotective natural cembranoid that reverses DFP-induced damage both in vivo and in the hippocampal slice. Cembranoid 1 acts by noncompetitive inhibition of the α7 nicotinic acetylcholine receptor. This study aims at establishing a preliminary structure-activity relationship to define the neuroprotective cembranoid pharmacophores using the hippocampal slice assay and pharmacophore modeling. Fourteen natural, semisynthetic, or biocatalytic cembranoid analogues 2-15 related to 1 were tested for their capacity to protect the population spikes from DFP-induced damage and intrinsic toxicity. Twelve cembranoids caused significant reversal of DFP toxicity; only 3 active analogues displayed minor intrinsic toxicity at 10 μM. The C-4 epimer of 1 (2) and the 4-O-methyl ether analogue of 1 (3), were totally devoid of neuroprotective activity. The results suggested a model for cembranoid binding where the hydrophobic ring surface binds to a hydrophobic (Hbic) patch on the receptor molecule and an electronegative atom (oxygen or sulfur) in proper spatial relationship to the ring surface interacts with an electropositive group in the receptor binding site. A pharmacophore model consisting of 1 hydrogen bond acceptor (HBA), 2 Hbic, and 10 exclusion spheres was established using HipHop-REFINE and supported the above mentioned pharmacophoric hypothesis. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Medicinal Chemistry and Molecular Modeling: An Integration to Teach Drug Structure-Activity Relationship and the Molecular Basis of Drug Action

ERIC Educational Resources Information Center

Carvalho, Ivone; Borges, Aurea D. L.; Bernardes, Lilian S. C.

2005-01-01

The use of computational chemistry and the protein data bank (PDB) to understand and predict the chemical and molecular basis involved in the drug-receptor interactions is discussed. A geometrical and chemical overview of the great structural similarity in the substrate and inhibitor is provided.

Highlighting the Structure-Function Relationship of the Brain with the Ising Model and Graph Theory

PubMed Central

Das, T. K.; Abeyasinghe, P. M.; Crone, J. S.; Sosnowski, A.; Laureys, S.; Owen, A. M.; Soddu, A.

2014-01-01

With the advent of neuroimaging techniques, it becomes feasible to explore the structure-function relationships in the brain. When the brain is not involved in any cognitive task or stimulated by any external output, it preserves important activities which follow well-defined spatial distribution patterns. Understanding the self-organization of the brain from its anatomical structure, it has been recently suggested to model the observed functional pattern from the structure of white matter fiber bundles. Different models which study synchronization (e.g., the Kuramoto model) or global dynamics (e.g., the Ising model) have shown success in capturing fundamental properties of the brain. In particular, these models can explain the competition between modularity and specialization and the need for integration in the brain. Graphing the functional and structural brain organization supports the model and can also highlight the strategy used to process and organize large amount of information traveling between the different modules. How the flow of information can be prevented or partially destroyed in pathological states, like in severe brain injured patients with disorders of consciousness or by pharmacological induction like in anaesthesia, will also help us to better understand how global or integrated behavior can emerge from local and modular interactions. PMID:25276772

G Protein-Coupled Estrogen Receptor (GPER) Agonist Dual Binding Mode Analyses toward Understanding of its Activation Mechanism: A Comparative Homology Modeling Approach.

PubMed

Arnatt, Christopher K; Zhang, Yan

2013-07-01

G protein-coupled estrogen receptor (GPER) has been shown to be important in several disease states such as estrogen sensitive cancers. While several selective ligands have been identified for the receptor, little is known about how they interact with GPER and how their structures influence their activity. Specifically, within one series of ligands, whose structure varied only at one position, the replacement of a hydrogen atom with an acetyl group changed a potent antagonist into a potent agonist. In this study, two GPER homology models were constructed based on the x-ray crystal structures of both the active and inactive β 2 -adrenergic receptors (β 2 AR) in an effort to characterize the differences of binding modes between agonists and antagonists to the receptor, and to understand their activity in relation to their structures. The knowledge attained in this study is expected to provide valuable information on GPER ligands structure activity relationship to benefit future rational design of potent agonists and antagonists of the receptor for potential therapeutic applications.

G Protein-Coupled Estrogen Receptor (GPER) Agonist Dual Binding Mode Analyses toward Understanding of its Activation Mechanism: A Comparative Homology Modeling Approach

PubMed Central

Arnatt, Christopher K.; Zhang, Yan

2015-01-01

G protein-coupled estrogen receptor (GPER) has been shown to be important in several disease states such as estrogen sensitive cancers. While several selective ligands have been identified for the receptor, little is known about how they interact with GPER and how their structures influence their activity. Specifically, within one series of ligands, whose structure varied only at one position, the replacement of a hydrogen atom with an acetyl group changed a potent antagonist into a potent agonist. In this study, two GPER homology models were constructed based on the x-ray crystal structures of both the active and inactive β2-adrenergic receptors (β2AR) in an effort to characterize the differences of binding modes between agonists and antagonists to the receptor, and to understand their activity in relation to their structures. The knowledge attained in this study is expected to provide valuable information on GPER ligands structure activity relationship to benefit future rational design of potent agonists and antagonists of the receptor for potential therapeutic applications. PMID:26229572

The ISO Edi Conceptual Model Activity and Its Relationship to OSI.

ERIC Educational Resources Information Center

Fincher, Judith A.

1990-01-01

The edi conceptual model is being developed to define common structures, services, and processes that syntax-specific standards like X12 and EDIFACT could adopt. Open Systems Interconnection (OSI) is of interest to edi because of its potential to help enable global interoperability across Electronic Data Interchange (EDI) functional groups. A…

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...

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...

Structure-activity relationship of cyanine tau aggregation inhibitors

PubMed Central

Chang, Edward; Congdon, Erin E.; Honson, Nicolette S.; Duff, Karen E.; Kuret, Jeff

2009-01-01

A structure-activity relationship for symmetrical cyanine inhibitors of human tau aggregation was elaborated using a filter trap assay. Antagonist activity depended on cyanine heterocycle, polymethine bridge length, and the nature of meso- and N-substituents. One potent member of the series, 3,3’-diethyl-9-methylthiacarbocyanine iodide (compound 11), retained submicromolar potency and had calculated physical properties consistent with blood-brain barrier and cell membrane penetration. Exposure of organotypic slices prepared from JNPL3 transgenic mice (which express human tau harboring the aggregation prone P301L tauopathy mutation) to compound 11 for one week revealed a biphasic dose response relationship. Low nanomolar concentrations decreased insoluble tau aggregates to half those observed in slices treated with vehicle alone. In contrast, high concentrations (≥300 nM) augmented tau aggregation and produced abnormalities in tissue tubulin levels. These data suggest that certain symmetrical carbocyanine dyes can modulate tau aggregation in the slice biological model at concentrations well below those associated with toxicity. PMID:19432420

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.

Molecular modeling studies of novel retro-binding tripeptide active-site inhibitors of thrombin.

PubMed

Lau, W F; Tabernero, L; Sack, J S; Iwanowicz, E J

1995-08-01

A novel series of retro-binding tripeptide thrombin active-site inhibitors was recently developed (Iwanowicz, E. I. et al. J. Med. Chem. 1994, 37, 2111(1)). It was hypothesized that the binding mode for these inhibitors is similar to that of the first three N-terminal residues of hirudin. This binding hypothesis was subsequently verified when the crystal structure of a member of this series, BMS-183,507 (N-[N-[N-[4-(Aminoiminomethyl)amino[-1-oxobutyl]-L- phenylalanyl]-L-allo-threonyl]-L-phenylalanine, methyl ester), was determined (Taberno, L.J. Mol. Biol. 1995, 246, 14). The methodology for developing the binding models of these inhibitors, the structure-activity relationships (SAR) and modeling studies that led to the elucidation of the proposed binding mode is described. The crystal structure of BMS-183,507/human alpha-thrombin is compared with the crystal structure of hirudin/human alpha-thrombin (Rydel, T.J. et al. Science 1990, 249,227; Rydel, T.J. et al. J. Mol Biol. 1991, 221, 583; Grutter, M.G. et al. EMBO J. 1990, 9, 2361) and with the computational binding model of BMS-183,507.

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.

Self-efficacy and pain acceptance as mediators of the relationship between pain and performance of valued life activities in women and men with rheumatoid arthritis.

PubMed

Ahlstrand, Inger; Vaz, Sharmila; Falkmer, Torbjörn; Thyberg, Ingrid; Björk, Mathilda

2017-06-01

To study whether personal factors (self-efficacy and pain acceptance) mediate the relationship between pain and performance of valued life activities in persons with rheumatoid arthritis. Persons with rheumatoid arthritis for at least four years ( n = 737; 73% women) answered a questionnaire measuring self-efficacy, pain acceptance, performance of valued life activities, and self-rated pain. Relationships among these constructs were explored using univariate and multivariate analyses. Structural equation modelling was then used to examine the mediational role of personal factors on the relationship between pain and performance of valued life activities. A direct negative association between pain and performance of valued life activities was identified ( Beta = .34, P < .001). This suggests that people with rheumatoid arthritis who had higher levels of pain has increased difficulties in performing valued life activities. Self-efficacy and activity engagement component of pain acceptance mediated the relationship between pain and performance of valued life activities, however the pain willingness component of pain acceptance did not influence participation in valued life activities. These findings highlight the importance of considering personal factors, such as pain acceptance and self-efficacy, in facilitating participation in valued life activities.

Social Relationships, Leisure Activity, and Health in Older Adults

PubMed Central

Chang, Po-Ju; Wray, Linda; Lin, Yeqiang

2015-01-01

Objective Although the link between enhanced social relationships and better health has generally been well established, few studies have examined the role of leisure activity in this link. This study examined how leisure influences the link between social relationships and health in older age. Methods Using data from the 2006 and 2010 waves of the nationally representative U.S. Health and Retirement Study and structural equation modelling analyses, we examined data on 2,965 older participants to determine if leisure activities mediated the link between social relationships and health in 2010, controlling for race, education level, and health in 2006. Results The results demonstrated that leisure activities mediate the link between social relationships and health in these age groups. Perceptions of positive social relationships were associated with greater involvement in leisure activities, and greater involvement in leisure activities was associated with better health in older age. Discussion & Conclusions The contribution of leisure to health in these age groups is receiving increasing attention, and the results of this study add to the literature on this topic, by identifying the mediating effect of leisure activity on the link between social relationships and health. Future studies aimed at increasing leisure activity may contribute to improved health outcomes in older adults. PMID:24884905

Social relationships, leisure activity, and health in older adults.

PubMed

Chang, Po-Ju; Wray, Linda; Lin, Yeqiang

2014-06-01

Although the link between enhanced social relationships and better health has generally been well established, few studies have examined the role of leisure activity in this link. This study examined how leisure influences the link between social relationships and health in older age. Using data from the 2006 and 2010 waves of the nationally representative U.S. Health and Retirement Study and structural equation modeling analyses, we examined data on 2,965 older participants to determine if leisure activities mediated the link between social relationships and health in 2010, controlling for race, education level, and health in 2006. The results demonstrated that leisure activities mediate the link between social relationships and health in these age groups. Perceptions of positive social relationships were associated with greater involvement in leisure activities, and greater involvement in leisure activities was associated with better health in older age. The contribution of leisure to health in these age groups is receiving increasing attention, and the results of this study add to the literature on this topic, by identifying the mediating effect of leisure activity on the link between social relationships and health. Future studies aimed at increasing leisure activity may contribute to improved health outcomes in older adults. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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.

An examination on the influence of small and medium enterprise (SME) stakeholder on green supply chain management practices

NASA Astrophysics Data System (ADS)

Shahlan, M. Z.; Sidek, A. A.; Suffian, S. A.; Hazza, M. H. F. A.; Daud, M. R. C.

2018-01-01

In this paper, climate change and global warming are the biggest current issues in the industrial sectors. The green supply chain managements (GSCM) is one of the crucial input to these issues. Effective GSCM can potentially secure the organization’s competitive advantage and improve the environmental performance of the network activities. In this study, the aim is to investigate and examine how a small and medium enterprises (SMEs) stakeholder pressure and top management influence green supply chain management practices. The study is further advance green supply chain management research in Malaysia focusing on SMEs manufacturing sector using structural equation modelling. Structural equation modelling is a multivariate statistical analysis technique used to examine structural relationship. It is the combination of factor analysis and multi regression analysis and used to analyse structural relationship between measure variable and latent factor. This research found that top management support and stakeholder pressure is the major influence for SMEs to adopt green supply chain management. The research also found that top management is fully mediate with the relationship between stakeholder pressure and monitoring supplier environmental performance.

Leisure activities are linked to mental health benefits by providing time structure: comparing employed, unemployed and homemakers

PubMed Central

Goodman, William K; Geiger, Ashley M; Wolf, Jutta M

2017-01-01

Background Unemployment has consistently been linked to negative mental health outcomes, emphasising the need to characterise the underlying mechanisms. The current study aimed at testing whether compared with other employment groups, fewer leisure activities observed in unemployment may contribute to elevated risk for negative mental health via loss of time structure. Methods Depressive symptoms (Center for Epidemiologic Studies Depression), leisure activities (exercise, self-focused, social), and time structure (Time Structure Questionnaire (TSQ)) were assessed cross-sectionally in 406 participants (unemployed=155, employed=140, homemakers=111) recruited through Amazon Mechanical Turk. Results Controlling for gender and age, structural equation modelling revealed time structure partially (employed, homemakers) and fully (unemployed) mediated the relationship between leisure activities and depressive symptoms. With the exception of differential effects for structured routines, all other TSQ factors (sense of purpose, present orientation, effective organisation and persistence) contributed significantly to all models. Conclusions These findings support the idea that especially for the unemployed, leisure activities impose their mental health benefits through increasing individuals’ perception of spending their time effectively. Social leisure activities that provide a sense of daily structure may thereby be a particularly promising low-cost intervention to improve mental health in this population. PMID:27298424

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

Relationship between Mind and Brain: A Proposal of Solution Based on Forms of Intra- and Extra-Individual Negentropy

ERIC Educational Resources Information Center

Alegre, Alberto A.; Zumaeta, Pablo A.

2015-01-01

It is proposed that the problem of the mind-brain relationship can be overcome by a non-classical materialistic model of personality based on the information defined as a special form of negentropy with a structure and activity, which in five intra-individual categories, organizes all and each of the levels of the personality, and, in an…

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.

The influence of corporate structure and quality improvement activities on outcome improvement in residential care homes.

PubMed

Winters, S; Kool, R B; Klazinga, N S; Huijsman, R

2014-08-01

To examine the impact of corporate structure and quality improvement (QI) activities on improvements in client-reported and professional indicators between 2007 and 2009. A cross-sectional study using organizational survey and indicator multilevel modelling to test relationships between corporate structure, QI activities and performance improvements on indicators. In total, 169 residential care homes for the elderly in the Netherlands. Change between 2007 and 2009 in client-reported and professional indicators. A middle-size corporate structure was associated with QI. The QI activity 'multidisciplinary team meetings' was positively correlated with the indicator 'safety environment' for somatic and psycho-geriatric care. The QI activities 'educational material' and 'direct work instructions' were associated negatively with the indicator 'availability of personnel' for somatic clients, but positively for psycho-geriatric clients. QI activities such as 'health plan activities', 'clinical lessons' and 'financial activities' had no relationship to improved performance. For psycho-geriatric clients mainly organizational QI activities were positively associated with QI. The mediating role of the corporate structure for performing QI activities appeared stronger for the change in client-reported than for professional indicators. This study reveals associations between QI activities and corporate structure and changes in indicator performance. A corporate structure was associated with improvement in client-reported indicators, but less on professional indicators, which assumes a central policy at corporate level with impact on client-reported indicators, in contrast to a more local level approach towards activities that result in QI on professional indicators. Tailoring QI activities at the right managerial level may be important to achieve improvement. © The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

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.

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.

Computer-assisted determination of minimum energy conformations. 7: A pharmacophore model of the active region of the alpha2-adrenoceptor

NASA Astrophysics Data System (ADS)

Ashman, William P.; Mickiewicz, A. P.; Nelson, Todd M.

1992-09-01

Molecular modeling and computational chemistry techniques are used to analyze compounds in developing pharmacophores of biological receptors to use as templates in structure activity relationship studies and to design new chemicals having physiological activity of interest. In this study, the results of x-ray crystal analyses and PM3 semi-empirical molecular orbital conformational analyses are used to determine the three-dimensional representations of selected adrenergic compounds known to be agonists with the alpha2-adrenoceptor in achieving optimized geometries and electrostatic parameters. The alpha2-adrenergic agonists interact with the adrenergic system receptors to produce various increases or decreases in hemodynamic responses (i.e., hypertension, hypotension, and bradycardia) and sedation. A pharmacophore model of the active region of the alpha2-adrenoceptor is described based on the superimposition of common structural, electrostatic, and physicochemical features of the compounds. Using the model to predict compound adrenergic activity and to design alpha2-adrenergic compounds is discussed.

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.

Youth participation in organized and informal sports activities across childhood and adolescence: exploring the relationships of motivational beliefs, developmental stage and gender.

PubMed

Dawes, Nickki Pearce; Vest, Andrea; Simpkins, Sandra

2014-08-01

Involvement in physically active pursuits, such as sports, contributes to achieving and maintaining good emotional and physical health. The central goal of this article was to examine the longitudinal relationships between participation (i.e., time spent in the activities) in organized and informal sports contexts and motivational beliefs, and factors that might impact these relationships, such as developmental stage and gender. The data for the current study were drawn from the childhood and beyond longitudinal study, which utilized a cohort sequential design with data collected on three cohorts across four waves. The current study sample included 986 European American youth (51 % female), who t were mostly from working- and middle-class families. Self-report questionnaires were used to collect data from the youth about their participation in sports and their motivational beliefs (i.e., value and perceptions of competence) about this activity. Structural equation modeling was used to examine the relationships between participation and motivational beliefs across childhood and adolescence. The results provide some support for a model of reciprocal relationships between participation and motivational beliefs in organized and informal sports activities. These relationships between participation and motivational beliefs did not vary significantly based on developmental stage or by gender. Overall, the findings suggest that participation in organized and informal sports contexts may be fostered by supporting the development of positive motivational beliefs about the activities across developmental periods.

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.

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

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

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.

A comprehensive analysis of the thermodynamic events involved in ligand receptor binding using CoRIA and its variants

NASA Astrophysics Data System (ADS)

Verma, Jitender; Khedkar, Vijay M.; Prabhu, Arati S.; Khedkar, Santosh A.; Malde, Alpeshkumar K.; Coutinho, Evans C.

2008-02-01

Quantitative Structure-Activity Relationships (QSAR) are being used since decades for prediction of biological activity, lead optimization, classification, identification and explanation of the mechanisms of drug action, and prediction of novel structural leads in drug discovery. Though the technique has lived up to its expectations in many aspects, much work still needs to be done in relation to problems related to the rational design of peptides. Peptides are the drugs of choice in many situations, however, designing them rationally is a complicated task and the complexity increases with the length of their sequence. In order to deal with the problem of peptide optimization, one of our recently developed QSAR formalisms CoRIA (Comparative Residue Interaction Analysis) is being expanded and modified as: reverse-CoRIA ( rCoRIA) and mixed-CoRIA ( mCoRIA) approaches. In these methodologies, the peptide is fragmented into individual units and the interaction energies (van der Waals, Coulombic and hydrophobic) of each amino acid in the peptide with the receptor as a whole ( rCoRIA) and with individual active site residues in the receptor ( mCoRIA) are calculated, which along with other thermodynamic descriptors, are used as independent variables that are correlated to the biological activity by chemometric methods. As a test case, the three CoRIA methodologies have been validated on a dataset of diverse nonamer peptides that bind to the Class I major histocompatibility complex molecule HLA-A*0201, and for which some structure activity relationships have already been reported. The different models developed, and validated both internally as well as externally, were found to be robust with statistically significant values of r 2 (correlation coefficient) and r 2 pred (predictive r 2). These models were able to identify all the structure activity relationships known for this class of peptides, as well uncover some new relationships. This means that these methodologies will perform well for other peptide datasets too. The major advantage of these approaches is that they explicitly utilize the 3D structures of small molecules or peptides as well as their macromolecular targets, to extract position-specific information about important interactions between the ligand and receptor, which can assist the medicinal and computational chemists in designing new molecules, and biologists in studying the influence of mutations in the target receptor on ligand binding.

Peers' Perceived Support, Student Engagement in Academic Activities and Life Satisfaction: A Structural Equation Modeling Approach

ERIC Educational Resources Information Center

Hakimzadeh, Rezvan; Besharat, Mohammad-Ali; Khaleghinezhad, Seyed Ali; Ghorban Jahromi, Reza

2016-01-01

This study investigates the relationships among peers' perceived support, life satisfaction, and student engagement in academic activities. Three hundred and fifteen Iranian students (172 boys and 143 girls) who were studying in one suburb of Tehran participated in this study. All participants were asked to complete Peers' Perceived Support scale…

Modeling a Neural Network as a Teaching Tool for the Learning of the Structure-Function Relationship

ERIC Educational Resources Information Center

Salinas, Dino G.; Acevedo, Cristian; Gomez, Christian R.

2010-01-01

The authors describe an activity they have created in which students can visualize a theoretical neural network whose states evolve according to a well-known simple law. This activity provided an uncomplicated approach to a paradigm commonly represented through complex mathematical formulation. From their observations, students learned many basic…

Predicting Adolescents' Organized Activity Involvement: The Role of Maternal Depression History, Family Relationship Quality, and Adolescent Cognitions

ERIC Educational Resources Information Center

Bohnert, Amy M.; Martin, Nina C.; Garber, Judy

2007-01-01

Although the potential benefits of organized activity involvement during high school have been documented, little is known about what familial and individual characteristics are associated with higher levels of participation. Using structural equation modeling, this longitudinal study examined the extent to which maternal depression history (i.e.,…

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.

The changing strength and nature of fire-climate relationships in the northern Rocky Mountains, U.S.A., 1902-2008

USGS Publications Warehouse

Littell, Jeremy

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008

PubMed Central

Higuera, Philip E.; Abatzoglou, John T.; Littell, Jeremy S.; Morgan, Penelope

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity. PMID:26114580

The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008.

PubMed

Higuera, Philip E; Abatzoglou, John T; Littell, Jeremy S; Morgan, Penelope

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

Validation of clay modeling as a learning tool for the periventricular structures of the human brain.

PubMed

Akle, Veronica; Peña-Silva, Ricardo A; Valencia, Diego M; Rincón-Perez, Carlos W

2018-03-01

Visualizing anatomical structures and functional processes in three dimensions (3D) are important skills for medical students. However, contemplating 3D structures mentally and interpreting biomedical images can be challenging. This study examines the impact of a new pedagogical approach to teaching neuroanatomy, specifically how building a 3D-model from oil-based modeling clay affects learners' understanding of periventricular structures of the brain among undergraduate medical students in Colombia. Students were provided with an instructional video before building the models of the structures, and thereafter took a computer-based quiz. They then brought their clay models to class where they answered questions about the structures via interactive response cards. Their knowledge of periventricular structures was assessed with a paper-based quiz. Afterward, a focus group was conducted and a survey was distributed to understand students' perceptions of the activity, as well as the impact of the intervention on their understanding of anatomical structures in 3D. Quiz scores of students that constructed the models were significantly higher than those taught the material in a more traditional manner (P < 0.05). Moreover, the modeling activity reduced time spent studying the topic and increased understanding of spatial relationships between structures in the brain. The results demonstrated a significant difference between genders in their self-perception of their ability to contemplate and rotate structures mentally (P < 0.05). The study demonstrated that the construction of 3D clay models in combination with autonomous learning activities was a valuable and efficient learning tool in the anatomy course, and that additional models could be designed to promote deeper learning of other neuroanatomy topics. Anat Sci Educ 11: 137-145. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

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.

Structure-Activity Relationships Based on 3D-QSAR CoMFA/CoMSIA and Design of Aryloxypropanol-Amine Agonists with Selectivity for the Human β3-Adrenergic Receptor and Anti-Obesity and Anti-Diabetic Profiles.

PubMed

Lorca, Marcos; Morales-Verdejo, Cesar; Vásquez-Velásquez, David; Andrades-Lagos, Juan; Campanini-Salinas, Javier; Soto-Delgado, Jorge; Recabarren-Gajardo, Gonzalo; Mella, Jaime

2018-05-16

The wide tissue distribution of the adrenergic β3 receptor makes it a potential target for the treatment of multiple pathologies such as diabetes, obesity, depression, overactive bladder (OAB), and cancer. Currently, there is only one drug on the market, mirabegron, approved for the treatment of OAB. In the present study, we have carried out an extensive structure-activity relationship analysis of a series of 41 aryloxypropanolamine compounds based on three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques. This is the first combined comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) study in a series of selective aryloxypropanolamines displaying anti-diabetes and anti-obesity pharmacological profiles. The best CoMFA and CoMSIA models presented values of r ² ncv = 0.993 and 0.984 and values of r ² test = 0.865 and 0.918, respectively. The results obtained were subjected to extensive external validation ( q ², r ², r ² m , etc.) and a final series of compounds was designed and their biological activity was predicted (best pEC 50 = 8.561).

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.

Analysis of structural relationship among the occupational dysfunction on the psychological problem in healthcare workers: a study using structural equation modeling

PubMed Central

Kyougoku, Makoto

2015-01-01

Purpose. The purpose of this study is to demonstrate the hypothetical model based on structural relationship with the occupational dysfunction on psychological problems (stress response, burnout syndrome, and depression) in healthcare workers. Method. Three cross sectional studies were conducted to assess the following relations: (1) occupational dysfunction on stress response (n = 468), (2) occupational dysfunction on burnout syndrome (n = 1,142), and (3) occupational dysfunction on depression (n = 687). Personal characteristics were collected through a questionnaire (such as age, gender, and job category, opportunities for refreshment, time spent on leisure activities, and work relationships) as well as the Classification and Assessment of Occupational Dysfunction (CAOD). Furthermore, study 1 included the Stress Response Scale-18 (SRS-18), study 2 used the Japanese Burnout Scale (JBS), and study 3 employed the Center for Epidemiological Studies Depression Scale (CES-D). The Kolmogorov–Smirnov test, confirmatory factor analysis (CFA), exploratory factor analysis (EFA), and path analysis of structural equation modeling (SEM) analysis were used in all of the studies. EFA and CFA were used to measure structural validity of four assessments; CAOD, SRS-18, JBS, and CES-D. For examination of a potential covariate, we assessed the correlation of the total and factor score of CAOD and personal factors in all studies. Moreover, direct and indirect effects of occupational dysfunction on stress response (Study 1), burnout syndrome (Study 2), and depression (Study 3) were also analyzed. Results. In study 1, CAOD had 16 items and 4 factors. In Study 2 and 3, CAOD had 16 items and 5 factors. SRS-18 had 18 items and 3 factors, JBS had 17 items and 3 factors, and CES-D had 20 items and 4 factors. All studies found that there were significant correlations between the CAOD total score and the personal factor that included opportunities for refreshment, time spent on leisure activities, and work relationships (p < 0.01). The hypothesis model results suggest that the classification of occupational dysfunction had good fit on the stress response (RMSEA = 0.061, CFI = 0.947, and TLI = 0.943), burnout syndrome (RMSEA = 0.076, CFI = 0.919, and TLI = 0.913), and depression (RMSEA = 0.060, CFI = 0.922, TLI = 0.917). Moreover, the detected covariates include opportunities for refreshment, time spent on leisure activities, and work relationships on occupational dysfunction. Conclusion. Our findings indicate that psychological problems are associated with occupational dysfunction in healthcare workers. Reduction of occupational dysfunction might be a strategy of better preventive occupational therapies for healthcare workers with psychological problems. However, longitudinal studies will be needed to determine a causal relationship. PMID:26618078

Analysis of structural relationship among the occupational dysfunction on the psychological problem in healthcare workers: a study using structural equation modeling.

PubMed

Teraoka, Mutsumi; Kyougoku, Makoto

2015-01-01

Purpose. The purpose of this study is to demonstrate the hypothetical model based on structural relationship with the occupational dysfunction on psychological problems (stress response, burnout syndrome, and depression) in healthcare workers. Method. Three cross sectional studies were conducted to assess the following relations: (1) occupational dysfunction on stress response (n = 468), (2) occupational dysfunction on burnout syndrome (n = 1,142), and (3) occupational dysfunction on depression (n = 687). Personal characteristics were collected through a questionnaire (such as age, gender, and job category, opportunities for refreshment, time spent on leisure activities, and work relationships) as well as the Classification and Assessment of Occupational Dysfunction (CAOD). Furthermore, study 1 included the Stress Response Scale-18 (SRS-18), study 2 used the Japanese Burnout Scale (JBS), and study 3 employed the Center for Epidemiological Studies Depression Scale (CES-D). The Kolmogorov-Smirnov test, confirmatory factor analysis (CFA), exploratory factor analysis (EFA), and path analysis of structural equation modeling (SEM) analysis were used in all of the studies. EFA and CFA were used to measure structural validity of four assessments; CAOD, SRS-18, JBS, and CES-D. For examination of a potential covariate, we assessed the correlation of the total and factor score of CAOD and personal factors in all studies. Moreover, direct and indirect effects of occupational dysfunction on stress response (Study 1), burnout syndrome (Study 2), and depression (Study 3) were also analyzed. Results. In study 1, CAOD had 16 items and 4 factors. In Study 2 and 3, CAOD had 16 items and 5 factors. SRS-18 had 18 items and 3 factors, JBS had 17 items and 3 factors, and CES-D had 20 items and 4 factors. All studies found that there were significant correlations between the CAOD total score and the personal factor that included opportunities for refreshment, time spent on leisure activities, and work relationships (p < 0.01). The hypothesis model results suggest that the classification of occupational dysfunction had good fit on the stress response (RMSEA = 0.061, CFI = 0.947, and TLI = 0.943), burnout syndrome (RMSEA = 0.076, CFI = 0.919, and TLI = 0.913), and depression (RMSEA = 0.060, CFI = 0.922, TLI = 0.917). Moreover, the detected covariates include opportunities for refreshment, time spent on leisure activities, and work relationships on occupational dysfunction. Conclusion. Our findings indicate that psychological problems are associated with occupational dysfunction in healthcare workers. Reduction of occupational dysfunction might be a strategy of better preventive occupational therapies for healthcare workers with psychological problems. However, longitudinal studies will be needed to determine a causal relationship.

In vitro and in vivo structure and activity relationship analysis of polymethoxylated flavonoids: identifying sinensetin as a novel antiangiogenesis agent.

PubMed

Lam, In Kei; Alex, Deepa; Wang, You-Hua; Liu, Ping; Liu, Ai-Lin; Du, Guan-Hua; Lee, Simon Ming Yuen

2012-06-01

Polymethoxylated flavonoids are present in citrus fruit in a range of chemical structures and abundance. These compounds have potential for anticarcinogenesis, antitumor, and cardiovascular protective activity, but the effect on angiogenesis has not been well studied. Human umbilical vein endothelial cells (HUVECs) in vitro and zebrafish (Danio rerio) in vivo models were used to screen and identify the antiangiogenesis activity of seven polymethoxylated flavonoids; namely, hesperetin, naringin, neohesperidin, nobiletin, scutellarein, scutellarein tetramethylether, and sinensetin. Five, excluding naringin and neohesperidin, showed different degrees of potency of antiangiogenesis activity. Sinensetin, which had the most potent antiangiogenesis activity and the lowest toxicity, inhibited angiogenesis by inducing cell cycle arrest in the G0/G1 phase in HUVEC culture and downregulating the mRNA expressions of angiogenesis genes flt1, kdrl, and hras in zebrafish. The in vivo structure-activity relationship (SAR) analysis indicated that a flavonoid with a methoxylated group at the C3' position offers a stronger antiangiogenesis activity, whereas the absence of a methoxylated group at the C8 position offers lower lethal toxicity in addition to enhancing the antiangiogenesis activity. This study provides new insight into how modification of the chemical structure of polymethoxylated flavonoids affects this newly identified antiangiogenesis activity. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

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-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.

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.

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...

Alignment-independent technique for 3D QSAR analysis

NASA Astrophysics Data System (ADS)

Wilkes, Jon G.; Stoyanova-Slavova, Iva B.; Buzatu, Dan A.

2016-04-01

Molecular biochemistry is controlled by 3D phenomena but structure-activity models based on 3D descriptors are infrequently used for large data sets because of the computational overhead for determining molecular conformations. A diverse dataset of 146 androgen receptor binders was used to investigate how different methods for defining molecular conformations affect the performance of 3D-quantitative spectral data activity relationship models. Molecular conformations tested: (1) global minimum of molecules' potential energy surface; (2) alignment-to-templates using equal electronic and steric force field contributions; (3) alignment using contributions "Best-for-Each" template; (4) non-energy optimized, non-aligned (2D > 3D). Aggregate predictions from models were compared. Highest average coefficients of determination ranged from R Test 2 = 0.56 to 0.61. The best model using 2D > 3D (imported directly from ChemSpider) produced R Test 2 = 0.61. It was superior to energy-minimized and conformation-aligned models and was achieved in only 3-7 % of the time required using the other conformation strategies. Predictions averaged from models built on different conformations achieved a consensus R Test 2 = 0.65. The best 2D > 3D model was analyzed for underlying structure-activity relationships. For the compound strongest binding to the androgen receptor, 10 substructural features contributing to binding were flagged. Utility of 2D > 3D was compared for two other activity endpoints, each modeling a medium sized data set. Results suggested that large scale, accurate predictions using 2D > 3D SDAR descriptors may be produced for interactions involving endocrine system nuclear receptors and other data sets in which strongest activities are produced by fairly inflexible substrates.

Cause-and-effect relationships in tandem swimmer models using transfer entropy

NASA Astrophysics Data System (ADS)

Peterson, Sean; Rosen, Maxwell; Gementzopoulos, Antonios; Zhang, Peng; Porfiri, Maurizio

2017-11-01

Swimming in a group affords a number of advantages to fish, including an enhanced ability to escape from predators, search for food, and mate. To study coordinated movements of fish, principled approaches are needed to unravel cause-and-effect relationships from raw-time series of multiple bodies moving in an encompassing fluid. In this work, we aim at demonstrating the validity of transfer entropy to elucidate cause-and-effect relationships in a fluid-structure interaction problem. Specifically, we consider two tandem airfoils in a uniform flow, wherein the pitching angle of one airfoil is actively controlled while the other is allowed to passively rotate. The active control alternates the pitch angle based upon an underlying two-state ergodic Markov process. We monitor the pitch angle of both the active and passive airfoils in time and demonstrate that transfer entropy can detect causality independent of which airfoil is actuated. The influence estimated by transfer entropy is found to be modulated by the distance between the two airfoils. The proposed data-driven technique offers a model-free perspective on fluid-structure interactions that can help illuminate the mechanisms of swimming in coordination. This work was supported by the National Science Foundation under Grant Numbers CBET-1332204 and CMMI-1433670.

Reduced density gradient as a novel approach for estimating QSAR descriptors, and its application to 1, 4-dihydropyridine derivatives with potential antihypertensive effects.

PubMed

Jardínez, Christiaan; Vela, Alberto; Cruz-Borbolla, Julián; Alvarez-Mendez, Rodrigo J; Alvarado-Rodríguez, José G

2016-12-01

The relationship between the chemical structure and biological activity (log IC 50 ) of 40 derivatives of 1,4-dihydropyridines (DHPs) was studied using density functional theory (DFT) and multiple linear regression analysis methods. With the aim of improving the quantitative structure-activity relationship (QSAR) model, the reduced density gradient s( r) of the optimized equilibrium geometries was used as a descriptor to include weak non-covalent interactions. The QSAR model highlights the correlation between the log IC 50 with highest molecular orbital energy (E HOMO ), molecular volume (V), partition coefficient (log P), non-covalent interactions NCI(H4-G) and the dual descriptor [Δf(r)]. The model yielded values of R 2 =79.57 and Q 2 =69.67 that were validated with the next four internal analytical validations DK=0.076, DQ=-0.006, R P =0.056, and R N =0.000, and the external validation Q 2 boot =64.26. The QSAR model found can be used to estimate biological activity with high reliability in new compounds based on a DHP series. Graphical abstract The good correlation between the log IC 50 with the NCI (H4-G) estimated by the reduced density gradient approach of the DHP derivatives.

Molecular characterization of the receptor binding structure-activity relationships of influenza B virus hemagglutinin.

PubMed

Carbone, V; Kim, H; Huang, J X; Baker, M A; Ong, C; Cooper, M A; Li, J; Rockman, S; Velkov, T

2013-01-01

Selectivity of α2,6-linked human-like receptors by B hemagglutinin (HA) is yet to be fully understood. This study integrates binding data with structure-recognition models to examine the impact of regional-specific sequence variations within the receptor-binding pocket on selectivity and structure activity relationships (SAR). The receptor-binding selectivity of influenza B HAs corresponding to either B/Victoria/2/1987 or the B/Yamagata/16/88 lineages was examined using surface plasmon resonance, solid-phase ELISA and gel-capture assays. Our SAR data showed that the presence of asialyl sugar units is the main determinant of receptor preference of α2,6 versus α2,3 receptor binding. Changes to the type of sialyl-glycan linkage present on receptors exhibit only a minor effect upon binding affinity. Homology-based structural models revealed that structural properties within the HA pocket, such as a glyco-conjugate at Asn194 on the 190-helix, sterically interfere with binding to avian receptor analogs by blocking the exit path of the asialyl sugars. Similarly, naturally occurring substitutions in the C-terminal region of the 190-helix and near the N-terminal end of the 140-loop narrows the horizontal borders of the binding pocket, which restricts access of the avian receptor analog LSTa. This study helps bridge the gap between ligand structure and receptor recognition for influenza B HA; and provides a consensus SAR model for the binding of human and avian receptor analogs to influenza B HA.

Synthesis-atomic structure-properties relationships in metallic nanoparticles by total scattering experiments and 3D computer simulations: case of Pt-Ru nanoalloy catalysts

NASA Astrophysics Data System (ADS)

Prasai, Binay; Ren, Yang; Shan, Shiyao; Zhao, Yinguang; Cronk, Hannah; Luo, Jin; Zhong, Chuan-Jian; Petkov, Valeri

2015-04-01

An approach to determining the 3D atomic structure of metallic nanoparticles (NPs) in fine detail and using the unique knowledge obtained for rationalizing their synthesis and properties targeted for optimization is described and exemplified on Pt-Ru alloy NPs of importance to the development of devices for clean energy conversion such as fuel cells. In particular, PtxRu100-x alloy NPs, where x = 31, 49 and 75, are synthesized by wet chemistry and activated catalytically by a post-synthesis treatment involving heating under controlled N2-H2 atmosphere. So-activated NPs are evaluated as catalysts for gas-phase CO oxidation and ethanol electro-oxidation reactions taking place in fuel cells. Both as-synthesized and activated NPs are characterized structurally by total scattering experiments involving high-energy synchrotron X-ray diffraction coupled to atomic pair distribution functions (PDFs) analysis. 3D structure models both for as-synthesized and activated NPs are built by molecular dynamics simulations based on the archetypal for current theoretical modelling Sutton-Chen method. Models are refined against the experimental PDF data by reverse Monte Carlo simulations and analysed in terms of prime structural characteristics such as metal-to-metal bond lengths, bond angles and first coordination numbers for Pt and Ru atoms. Analysis indicates that, though of a similar type, the atomic structure of as-synthesized and respective activated NPs differ in several details of importance to NP catalytic properties. Structural characteristics of activated NPs and data for their catalytic activity are compared side by side and strong evidence found that electronic effects, indicated by significant changes in Pt-Pt and Ru-Ru metal bond lengths at NP surface, and practically unrecognized so far atomic ensemble effects, indicated by distinct stacking of atomic layers near NP surface and prevalence of particular configurations of Pt and Ru atoms in these layers, contribute to the observed enhancement of the catalytic activity of PtxRu100-x alloy NPs at x ~ 50. Implications of so-established relationships between the atomic structure and catalytic activity of Pt-Ru alloy NPs on efforts aimed at improving further the latter by tuning-up the former are discussed and the usefulness of detailed NP structure studies to advancing science and technology of metallic NPs - exemplified.An approach to determining the 3D atomic structure of metallic nanoparticles (NPs) in fine detail and using the unique knowledge obtained for rationalizing their synthesis and properties targeted for optimization is described and exemplified on Pt-Ru alloy NPs of importance to the development of devices for clean energy conversion such as fuel cells. In particular, PtxRu100-x alloy NPs, where x = 31, 49 and 75, are synthesized by wet chemistry and activated catalytically by a post-synthesis treatment involving heating under controlled N2-H2 atmosphere. So-activated NPs are evaluated as catalysts for gas-phase CO oxidation and ethanol electro-oxidation reactions taking place in fuel cells. Both as-synthesized and activated NPs are characterized structurally by total scattering experiments involving high-energy synchrotron X-ray diffraction coupled to atomic pair distribution functions (PDFs) analysis. 3D structure models both for as-synthesized and activated NPs are built by molecular dynamics simulations based on the archetypal for current theoretical modelling Sutton-Chen method. Models are refined against the experimental PDF data by reverse Monte Carlo simulations and analysed in terms of prime structural characteristics such as metal-to-metal bond lengths, bond angles and first coordination numbers for Pt and Ru atoms. Analysis indicates that, though of a similar type, the atomic structure of as-synthesized and respective activated NPs differ in several details of importance to NP catalytic properties. Structural characteristics of activated NPs and data for their catalytic activity are compared side by side and strong evidence found that electronic effects, indicated by significant changes in Pt-Pt and Ru-Ru metal bond lengths at NP surface, and practically unrecognized so far atomic ensemble effects, indicated by distinct stacking of atomic layers near NP surface and prevalence of particular configurations of Pt and Ru atoms in these layers, contribute to the observed enhancement of the catalytic activity of PtxRu100-x alloy NPs at x ~ 50. Implications of so-established relationships between the atomic structure and catalytic activity of Pt-Ru alloy NPs on efforts aimed at improving further the latter by tuning-up the former are discussed and the usefulness of detailed NP structure studies to advancing science and technology of metallic NPs - exemplified. Electronic supplementary information (ESI) available: XRD patterns, TEM and 3D structure modelling methodology. See DOI: 10.1039/c5nr00800j

Decoding the Semantic Content of Natural Movies from Human Brain Activity

PubMed Central

Huth, Alexander G.; Lee, Tyler; Nishimoto, Shinji; Bilenko, Natalia Y.; Vu, An T.; Gallant, Jack L.

2016-01-01

One crucial test for any quantitative model of the brain is to show that the model can be used to accurately decode information from evoked brain activity. Several recent neuroimaging studies have decoded the structure or semantic content of static visual images from human brain activity. Here we present a decoding algorithm that makes it possible to decode detailed information about the object and action categories present in natural movies from human brain activity signals measured by functional MRI. Decoding is accomplished using a hierarchical logistic regression (HLR) model that is based on labels that were manually assigned from the WordNet semantic taxonomy. This model makes it possible to simultaneously decode information about both specific and general categories, while respecting the relationships between them. Our results show that we can decode the presence of many object and action categories from averaged blood-oxygen level-dependent (BOLD) responses with a high degree of accuracy (area under the ROC curve > 0.9). Furthermore, we used this framework to test whether semantic relationships defined in the WordNet taxonomy are represented the same way in the human brain. This analysis showed that hierarchical relationships between general categories and atypical examples, such as organism and plant, did not seem to be reflected in representations measured by BOLD fMRI. PMID:27781035

Towards a physics-based multiscale modelling of the electro-mechanical coupling in electro-active polymers.

PubMed

Cohen, Noy; Menzel, Andreas; deBotton, Gal

2016-02-01

Owing to the increasing number of industrial applications of electro-active polymers (EAPs), there is a growing need for electromechanical models which accurately capture their behaviour. To this end, we compare the predicted behaviour of EAPs undergoing homogeneous deformations according to three electromechanical models. The first model is a phenomenological continuum-based model composed of the mechanical Gent model and a linear relationship between the electric field and the polarization. The electrical and the mechanical responses according to the second model are based on the physical structure of the polymer chain network. The third model incorporates a neo-Hookean mechanical response and a physically motivated microstructurally based long-chains model for the electrical behaviour. In the microstructural-motivated models, the integration from the microscopic to the macroscopic levels is accomplished by the micro-sphere technique. Four types of homogeneous boundary conditions are considered and the behaviours determined according to the three models are compared. For the microstructurally motivated models, these analyses are performed and compared with the widely used phenomenological model for the first time. Some of the aspects revealed in this investigation, such as the dependence of the intensity of the polarization field on the deformation, highlight the need for an in-depth investigation of the relationships between the structure and the behaviours of the EAPs at the microscopic level and their overall macroscopic response.

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.

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

2D-QSAR study of fullerene nanostructure derivatives as potent HIV-1 protease inhibitors

NASA Astrophysics Data System (ADS)

Barzegar, Abolfazl; Jafari Mousavi, Somaye; Hamidi, Hossein; Sadeghi, Mehdi

2017-09-01

The protease of human immunodeficiency virus1 (HIV-PR) is an essential enzyme for antiviral treatments. Carbon nanostructures of fullerene derivatives, have nanoscale dimension with a diameter comparable to the diameter of the active site of HIV-PR which would in turn inhibit HIV. In this research, two dimensional quantitative structure-activity relationships (2D-QSAR) of fullerene derivatives against HIV-PR activity were employed as a powerful tool for elucidation the relationships between structure and experimental observations. QSAR study of 49 fullerene derivatives was performed by employing stepwise-MLR, GAPLS-MLR, and PCA-MLR models for variable (descriptor) selection and model construction. QSAR models were obtained with higher ability to predict the activity of the fullerene derivatives against HIV-PR by a correlation coefficient (R2training) of 0.942, 0.89, and 0.87 as well as R2test values of 0.791, 0.67and 0.674 for stepwise-MLR, GAPLS-MLR, and PCA -MLR models, respectively. Leave-one-out cross-validated correlation coefficient (R2CV) and Y-randomization methods confirmed the models robustness. The descriptors indicated that the HIV-PR inhibition depends on the van der Waals volumes, polarizability, bond order between two atoms and electronegativities of fullerenes derivatives. 2D-QSAR simulation without needing receptor's active site geometry, resulted in useful descriptors mainly denoting ;C60 backbone-functional groups; and ;C60 functional groups; properties. Both properties in fullerene refer to the ligand fitness and improvement van der Waals interactions with HIV-PR active site. Therefore, the QSAR models can be used in the search for novel HIV-PR inhibitors based on fullerene derivatives.

ADVANCED COMPUTATIONAL METHODS IN DOSE MODELING: APPLICATION OF COMPUTATIONAL BIOPHYSICAL TRANSPORT, COMPUTATIONAL CHEMISTRY, AND COMPUTATIONAL BIOLOGY

EPA Science Inventory

Computational toxicology (CompTox) leverages the significant gains in computing power and computational techniques (e.g., numerical approaches, structure-activity relationships, bioinformatics) realized over the last few years, thereby reducing costs and increasing efficiency i...

Intraplate deformation on north-dipping basement structures in the Northern Gawler Craton, Australia: reactivation of original terrane boundaries or later intra-cratonic thrusts?

NASA Astrophysics Data System (ADS)

Baines, G.; Giles, D.; Betts, P. G.; Backé, G.

2007-12-01

Multiple intraplate orogenic events have deformed Neoproterozoic to Carboniferous sedimentary sequences that cover the Archean to Mesoproterozoic basement of the northern Gawler Craton, Australia. These intraplate orogenies reactivated north-dipping basement penetrating faults that are imaged on seismic reflection profiles. These north-dipping structures pre-date Neoproterozoic deposition but their relationships to significant linear magnetic and gravity anomalies that delineate unexposed Archean to Early Mesoproterozoic basement terranes are unclear. The north-dipping structures are either terrane boundaries that formed during continental amalgamation or later faults, which formed during a mid- to late-Mesoproterozoic transpressional orogeny and cross-cut the original lithological terrane boundaries. We model magnetic and gravity data to determine the 3D structure of the unexposed basement of the northern Gawler Craton. These models are constrained by drill hole and surface observations, seismic reflection profiles and petrophysical data, such that geologically reasonable models that can satisfy the data are limited. The basement structures revealed by this modelling approach constrain the origin and significance of the north-dipping structures that were active during the later intraplate Petermann, Delamerian and Alice Springs Orogenies. These results have bearing on which structures are likely to be active during present-day intraplate deformation in other areas, including, for example, current seismic activity along similar basement structures in the Adelaide "Geosyncline".

Pyrrole-Based Antitubulin Agents: Two Distinct Binding Modalities are Predicted for C-2 Analogs in the Colchicine Site.

PubMed

Da, Chenxiao; Telang, Nakul; Barelli, Peter; Jia, Xin; Gupton, John T; Mooberry, Susan L; Kellogg, Glen E

2012-01-12

3,5-dibromo-4-(3,4-dimethoxyphenyl)-1H-pyrrole-2-carboxylic acid ethyl ester is a promising antitubulin lead agent that targets the colchicine site of tubulin. C-2 analogs were synthesized and tested for microtubule depolymerizing and antiproliferative activity. Molecular modeling studies using both GOLD docking and HINT (Hydropathic INTeraction) scoring revealed two distinct binding modes that explain the structural-activity relationships and are in accord with the structural basis of colchicine binding to tubulin. The binding mode of higher activity compounds is buried deeper in the site and overlaps well with rings A and C of colchicine, while the lower activity binding mode shows fewer critical contacts with tubulin. The model distinguishes highly active compounds from those with weaker activities and provides novel insights into the colchicine site and compound design.

QSAR modeling of GPCR ligands: methodologies and examples of applications.

PubMed

Tropsha, A; Wang, S X

2006-01-01

GPCR ligands represent not only one of the major classes of current drugs but the major continuing source of novel potent pharmaceutical agents. Because 3D structures of GPCRs as determined by experimental techniques are still unavailable, ligand-based drug discovery methods remain the major computational molecular modeling approaches to the analysis of growing data sets of tested GPCR ligands. This paper presents an overview of modern Quantitative Structure Activity Relationship (QSAR) modeling. We discuss the critical issue of model validation and the strategy for applying the successfully validated QSAR models to virtual screening of available chemical databases. We present several examples of applications of validated QSAR modeling approaches to GPCR ligands. We conclude with the comments on exciting developments in the QSAR modeling of GPCR ligands that focus on the study of emerging data sets of compounds with dual or even multiple activities against two or more of GPCRs.

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.

The relationship between physical activity, meaning in life, and subjective vitality in community-dwelling older adults.

PubMed

Ju, Haewon

2017-11-01

The present study examined the potential contribution of meaning in life to the relationship between physical activity and subjective vitality in older adults. Two-hundred and fifty community-dwelling elders completed the instruments assessing physical activity, meaning in life, and subjective vitality. Results from structural equation modeling indicated that physical activity was positively associated with both meaning in life and subjective vitality. Further, the relationship between physical activity and vitality was partially mediated by meaning in life. Although previous studies have consistently found a positive impact of physical activity on vitality, the current study suggested that it is more productive to focus not only on physical activity, but also on meaning in life, in order to vitalize elders. Further, a focus on meaning in life can be a productive way to continue to vitalize older adults who are unable to engage in regular physical activity. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Large structural modification with conserved conformation: analysis of delta(3)-fused aryl prolines in model beta-turns.

PubMed

Jeannotte, Guillaume; Lubell, William D

2004-11-10

For the first time, the influence of a fused Delta3-arylproline on peptide conformation has been studied by the synthesis and comparison of the conformations of peptides containing proline and pyrrolo-proline, 3 (PyPro). Pyrrolo-proline was demonstrated to be a conservative replacement for Pro in model beta-turns, 4 and 5, as shown by their similar DMSO titration curves, cis/trans-isomer populations, and NOESY spectral data. Pyrrolo-proline may thus be used for studying the structure activity relationships of Pro-containing peptides with minimal modification of secondary structures.

3-aminopyridazine derivatives with atypical antidepressant, serotonergic, and dopaminergic activities.

PubMed

Wermuth, C G; Schlewer, G; Bourguignon, J J; Maghioros, G; Bouchet, M J; Moire, C; Kan, J P; Worms, P; Biziere, K

1989-03-01

Minaprine [3-[(beta-morpholinoethyl)amino]-4-methyl-6-phenylpyridazine dihydrochloride] is active in most animal models of depression and exhibits in vivo a dual dopaminomimetic and serotoninomimetic activity profile. In an attempt to dissociate these two effects and to characterize the responsible structural requirements, a series of 47 diversely substituted analogues of minaprine were synthesized and tested for their potential antidepressant, serotonergic, and dopaminergic activities. The structure-activity relationships show that dopaminergic and serotonergic activities can be dissociated. Serotonergic activity appears to be correlated mainly with the substituent in the 4-position of the pyridazine ring whereas the dopaminergic activity appears to be dependent on the presence, or in the formation, of a para-hydroxylated aryl ring in the 6-position of the pyridazine ring.

Do Perceptions of Competence Mediate The Relationship Between Fundamental Motor Skill Proficiency and Physical Activity Levels of Children in Kindergarten?

PubMed

Crane, Jeff R; Naylor, Patti J; Cook, Ryan; Temple, Viviene A

2015-07-01

Perceptions of competence mediate the relationship between motor skill proficiency and physical activity among older children and adolescents. This study examined kindergarten children's perceptions of physical competence as a mediator of the relationship between motor skill proficiency as a predictor variable and physical activity levels as the outcome variable; and also with physical activity as a predictor and motor skill proficiency as the outcome. Participants were 116 children (mean age = 5 years 7 months, 58% boys) from 10 schools. Motor skills were measured using the Test of Gross Motor Development-2 and physical activity was monitored through accelerometry. Perceptions of physical competence were measured using The Pictorial Scale of Perceived Competence and Social Acceptance for Young Children, and the relationships between these variables were examined using a model of mediation. The direct path between object control skills and moderate-vigorous physical activity (MVPA) was significant and object control skills predicted perceived physical competence. However, perceived competence did not mediate the relationship between object control skills and MVPA. The significant relationship between motor proficiency and perceptions of competence did not in turn influence kindergarten children's participation in physical activity. These findings support concepts of developmental differences in the structure of the self-perception system.

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

Leisure activities are linked to mental health benefits by providing time structure: comparing employed, unemployed and homemakers.

PubMed

Goodman, William K; Geiger, Ashley M; Wolf, Jutta M

2017-01-01

Unemployment has consistently been linked to negative mental health outcomes, emphasising the need to characterise the underlying mechanisms. The current study aimed at testing whether compared with other employment groups, fewer leisure activities observed in unemployment may contribute to elevated risk for negative mental health via loss of time structure. Depressive symptoms (Center for Epidemiologic Studies Depression), leisure activities (exercise, self-focused, social), and time structure (Time Structure Questionnaire (TSQ)) were assessed cross-sectionally in 406 participants (unemployed=155, employed=140, homemakers=111) recruited through Amazon Mechanical Turk. Controlling for gender and age, structural equation modelling revealed time structure partially (employed, homemakers) and fully (unemployed) mediated the relationship between leisure activities and depressive symptoms. With the exception of differential effects for structured routines, all other TSQ factors (sense of purpose, present orientation, effective organisation and persistence) contributed significantly to all models. These findings support the idea that especially for the unemployed, leisure activities impose their mental health benefits through increasing individuals' perception of spending their time effectively. Social leisure activities that provide a sense of daily structure may thereby be a particularly promising low-cost intervention to improve mental health in this population. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

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

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

Synthesis, biological evaluation, and structure-activity relationship of clonazepam, meclonazepam, and 1,4-benzodiazepine compounds with schistosomicidal activity.

PubMed

Menezes, Carla M S; Rivera, Gildardo; Alves, Marina A; do Amaral, Daniel N; Thibaut, Jean Pierre B; Noël, François; Barreiro, Eliezer J; Lima, Lídia M

2012-06-01

The inherent morbidity and mortality caused by schistosomiasis is a serious public health problem in developing countries. Praziquantel is the only drug in therapeutic use, leading to a permanent risk of parasite resistance. In search for new schistosomicidal drugs, meclonazepam, the 3-methyl-derivative of clonazepam, is still considered an interesting lead-candidate because it has a proven schistosomicidal effect in humans but adverse effects on the central nervous system did not allow its clinical use. Herein, the synthesis, in vitro biological evaluation, and molecular modeling of clonazepam, meclonazepam, and analogues are reported to establish the first structure-activity relationship for schistosomicidal benzodiazepines. Our findings indicate that the amide moiety [N(1) H-C(2) (=O)] is the principal pharmacophoric unit of 1,4-benzodiazepine schistosomicidal compounds and that substitution on the amide nitrogen atom (N(1) position) is not tolerated. © 2012 John Wiley & Sons A/S.

Molecular modeling and snake venom phospholipase A2 inhibition by phenolic compounds: Structure-activity relationship.

PubMed

Alam, Md Iqbal; Alam, Mohammed A; Alam, Ozair; Nargotra, Amit; Taneja, Subhash Chandra; Koul, Surrinder

2016-05-23

In our earlier study, we have reported that a phenolic compound 2-hydroxy-4-methoxybenzaldehyde from Janakia arayalpatra root extract was active against Viper and Cobra envenomations. Based on the structure of this natural product, libraries of synthetic structurally variant phenolic compounds were studied through molecular docking on the venom protein. To validate the activity of eight selected compounds, we have tested them in in vivo and in vitro models. The compound 21 (2-hydroxy-3-methoxy benzaldehyde), 22 (2-hydroxy-4-methoxybenzaldehyde) and 35 (2-hydroxy-3-methoxybenzylalcohol) were found to be active against venom-induced pathophysiological changes. The compounds 20, 15 and 35 displayed maximum anti-hemorrhagic, anti-lethal and PLA2 inhibitory activity respectively. In terms of SAR, the presence of a formyl group in conjunction with a phenolic group was seen as a significant contributor towards increasing the antivenom activity. The above observations confirmed the anti-venom activity of the phenolic compounds which needs to be further investigated for the development of new anti-snake venom leads. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

The Relation of Story Structure to a Model of Conceptual Change in Science Learning

NASA Astrophysics Data System (ADS)

Klassen, Stephen

2010-03-01

Although various reasons have been proposed to explain the potential effectiveness of science stories to promote learning, no explicit relationship of stories to learning theory in science has been propounded. In this paper, two structurally analogous models are developed and compared: a structural model of stories and a temporal conceptual change model of learning. On the basis of the similarity of the models, as elaborated, it is proposed that the structure of science stories may promote a re-enactment of the learning process, and, thereby, such stories serve to encourage active learning through the generation of hypotheses and explanations. The practical implications of this theoretical analogy can be applied to the classroom in that the utilization of stories provides the opportunity for a type of re-enactment of the learning process that may encourage both engagement with the material and the development of long-term memory structures.

Antimalarial Pyrido[1,2-a]benzimidazoles: Lead Optimization, Parasite Life Cycle Stage Profile, Mechanistic Evaluation, Killing Kinetics, and in Vivo Oral Efficacy in a Mouse Model.

PubMed

Singh, Kawaljit; Okombo, John; Brunschwig, Christel; Ndubi, Ferdinand; Barnard, Linley; Wilkinson, Chad; Njogu, Peter M; Njoroge, Mathew; Laing, Lizahn; Machado, Marta; Prudêncio, Miguel; Reader, Janette; Botha, Mariette; Nondaba, Sindisiwe; Birkholtz, Lyn-Marie; Lauterbach, Sonja; Churchyard, Alisje; Coetzer, Theresa L; Burrows, Jeremy N; Yeates, Clive; Denti, Paolo; Wiesner, Lubbe; Egan, Timothy J; Wittlin, Sergio; Chibale, Kelly

2017-02-23

Further structure-activity relationship (SAR) studies on the recently identified pyrido[1,2-a]benzimidazole (PBI) antimalarials have led to the identification of potent, metabolically stable compounds with improved in vivo oral efficacy in the P. berghei mouse model and additional activity against parasite liver and gametocyte stages, making them potential candidates for preclinical development. Inhibition of hemozoin formation possibly contributes to the mechanism of action.

Structure-reactivity relationships between fluorescent chromophores and antioxidant activity of grain and sweet sorghum seeds

USDA-ARS?s Scientific Manuscript database

Polyphenolic structures, such as tannins, are the putative cause of a variety of seed functions including bird/insect resistance and antioxidant activity. Structure-reactivity relationships are necessary to understand the influence of polyphenolic chromophore structures on the tannin content and fr...

PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

EPA Science Inventory

Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...

Constructing inquiry: One school's journey to develop an inquiry-based school for teachers and students

NASA Astrophysics Data System (ADS)

Sisk-Hilton, Stephanie Lee

This study examines the two way relationship between an inquiry-based professional development model and teacher enactors. The two year study follows a group of teachers enacting the emergent Supporting Knowledge Integration for Inquiry Practice (SKIIP) professional development model. This study seeks to: (a) identify activity structures in the model that interact with teachers' underlying assumptions regarding professional development and inquiry learning; (b) explain key decision points during implementation in terms of these underlying assumptions; and (c) examine the impact of key activity structures on individual teachers' stated belief structures regarding inquiry learning. Linn's knowledge integration framework facilitates description and analysis of teacher development. Three sets of tensions emerge as themes that describe and constrain participants' interaction with and learning through the model. These are: learning from the group vs. learning on one's own; choosing and evaluating evidence based on impressions vs. specific criteria; and acquiring new knowledge vs. maintaining feelings of autonomy and efficacy. In each of these tensions, existing group goals and operating assumptions initially fell at one end of the tension, while the professional development goals and forms fell at the other. Changes to the model occurred as participants reacted to and negotiated these points of tension. As the group engaged in and modified the SKIIP model, they had repeated opportunities to articulate goals and to make connections between goals and model activity structures. Over time, decisions to modify the model took into consideration an increasingly complex set of underlying assumptions and goals. Teachers identified and sought to balance these tensions. This led to more complex and nuanced decision making, which reflected growing capacity to consider multiple goals in choosing activity structures to enact. The study identifies key activity structures that scaffolded this process for teachers, and which ultimately promoted knowledge integration at both the group and individual levels. This study is an "extreme case" which examines implementation of the SKIIP model under very favorable conditions. Lessons learned regarding appropriate levels of model responsiveness, likely areas of conflict between model form and teacher underlying assumptions, and activity structures that scaffold knowledge integration provide a starting point for future, larger scale implementation.

Synthesis, biological evaluation, QSAR study and molecular docking of novel N-(4-amino carbonylpiperazinyl) (thio)phosphoramide derivatives as cholinesterase inhibitors.

PubMed

Gholivand, Khodayar; Ebrahimi Valmoozi, Ali Asghar; Bonsaii, Mahyar

2014-06-01

Novel (thio)phosphoramidate derivatives based on piperidincarboxamide with the general formula of (NH2-C(O)-C5H9N)-P(X=O,S)R1R2 (1-5) and (NH2-C(O)-C5H9N)2-P(O)R (6-9) were synthesized and characterized by (31)P, (13)C, (1)H NMR, IR spectroscopy. Furthermore, the crystal structure of compound (NH2-C(O)-C5H9N)2-P(O)(OC6H5) (6) was investigated. The activities of derivatives on cholinesterases (ChE) were determined using a modified Ellman's method. Also the mixed-type mechanisms of these compounds were evaluated by Lineweaver-Burk plots. Molecular docking and quantitative structure-activity relationship (QSAR) were used to understand the relationship between molecular structural features and anti-ChE activity, and to predict the binding affinity of phosphoramido-piperidinecarboxamides (PAPCAs) to ChE receptors. From molecular docking analysis, noncovalent interactions especially hydrogen bonding as well as hydrophobic was found between PAPCAs and ChE. Based on the docking results, appropriate molecular structural parameters were adopted to develop a QSAR model. DFT-QSAR models for ChE enzymes demonstrated the importance of electrophilicity parameter in describing the anti-AChE and anti-BChE activities of the synthesized compounds. The correlation matrix of QSAR models and docking analysis confirmed that electrophilicity descriptor can control the influence of the hydrophobic properties of P=(O, S) and CO functional groups of PAPCA derivatives in the inhibition of human ChE enzymes. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Riccardin C derivatives as anti-MRSA agents: structure-activity relationship of a series of hydroxylated bis(bibenzyl)s.

PubMed

Sawada, Hiromi; Okazaki, Miki; Morita, Daichi; Kuroda, Teruo; Matsuno, Kenji; Hashimoto, Yuichi; Miyachi, Hiroyuki

2012-12-15

Members of a series of macrocyclic bis(bibenzyl) riccardin-class derivatives were found to exhibit antibacterial activity towards methicillin-resistant Staphylococcus aureus (anti-MRSA activity). Structure-activity relationship (SAR) studies were conducted, focusing on the number and position of the hydroxyl groups. The minimum essential structure for anti-MRSA activity was also investigated. Copyright © 2012 Elsevier Ltd. All rights reserved.

Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.

PUBLIC SOURCES OF MUTAGENICITY AND CARCINOGENICITY DATA: USE IN STRUCTURE-ACTIVITY RELATIONSHIP MODELS

EPA Science Inventory

No Abstract - first paragraph of INTRODUCTION

Publicly supported compilations of mutagenicity and carcinogenicity data are available
for a significant number and variety of environmental and industrial chemicals and, to a lesser
extent, pharmaceutical chemicals. T...

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

An information driven strategy to support multidisciplinary design

NASA Technical Reports Server (NTRS)

Rangan, Ravi M.; Fulton, Robert E.

1990-01-01

The design of complex engineering systems such as aircraft, automobiles, and computers is primarily a cooperative multidisciplinary design process involving interactions between several design agents. The common thread underlying this multidisciplinary design activity is the information exchange between the various groups and disciplines. The integrating component in such environments is the common data and the dependencies that exist between such data. This may be contrasted to classical multidisciplinary analyses problems where there is coupling between distinct design parameters. For example, they may be expressed as mathematically coupled relationships between aerodynamic and structural interactions in aircraft structures, between thermal and structural interactions in nuclear plants, and between control considerations and structural interactions in flexible robots. These relationships provide analytical based frameworks leading to optimization problem formulations. However, in multidisciplinary design problems, information based interactions become more critical. Many times, the relationships between different design parameters are not amenable to analytical characterization. Under such circumstances, information based interactions will provide the best integration paradigm, i.e., there is a need to model the data entities and their dependencies between design parameters originating from different design agents. The modeling of such data interactions and dependencies forms the basis for integrating the various design agents.

Effects of risk factors for and components of metabolic syndrome on the quality of life of patients with systemic lupus erythematosus: a structural equation modeling approach.

PubMed

Lee, Jeong-Won; Kang, Ji-Hyoun; Lee, Kyung-Eun; Park, Dong-Jin; Kang, Seong Wook; Kwok, Seung-Ki; Kim, Seong-Kyu; Choe, Jung-Yoon; Kim, Hyoun-Ah; Sung, Yoon-Kyoung; Shin, Kichul; Lee, Sang-Il; Lee, Chang Hoon; Choi, Sung Jae; Lee, Shin-Seok

2018-01-01

This study assessed the relationships among the risk factors for and components of metabolic syndrome (MetS) and health-related quality of life (HRQOL) in a hypothesized causal model using structural equation modeling (SEM) in patients with systemic lupus erythematosus (SLE). Of the 505 SLE patients enrolled in the Korean Lupus Network (KORNET registry), 244 had sufficient data to assess the components of MetS at enrollment. Education level, monthly income, corticosteroid dose, Systemic Lupus Erythematosus Disease Activity Index, Physicians' Global Assessment, Beck Depression Inventory, MetS components, and the Short Form-36 at the time of cohort entry were determined. SEM was used to test the causal relationship based on the Analysis of Moment Structure. The average age of the 244 patients was 40.7 ± 11.8 years. The SEM results supported the good fit of the model (χ 2  = 71.629, p = 0.078, RMSEA 0.034, CFI 0.972). The final model showed a direct negative effect of higher socioeconomic status and a positive indirect effect of higher disease activity on MetS, the latter through corticosteroid dose. MetS did not directly impact HRQOL but had an indirect negative impact on it, through depression. In our causal model, MetS risk factors were related to MetS components. The latter had a negative indirect impact on HRQOL, through depression. Clinicians should consider socioeconomic status and medication and seek to modify disease activity, MetS, and depression to improve the HRQOL of SLE patients.

Predicting physical activity and fruit and vegetable intake in adolescents: a test of the information, motivation, behavioral skills model.

PubMed

Kelly, Stephanie; Melnyk, Bernadette Mazurek; Belyea, Michael

2012-04-01

Most adolescents do not meet national recommendations regarding physical activity and/or the intake of fruits and vegetables. The purpose of this study was to explore whether variables in the information, motivation, behavioral skills (IMB) model of health promotion predicted physical activity and fruit and vegetable intake in 404 adolescents from 2 high schools in the Southwest United States using structural equation modeling (SEM). The SEM models included theoretical constructs, contextual variables, and moderators. The theoretical relationships in the IMB model were confirmed and were moderated by gender and race. Interventions that incorporate cognitive-behavioral skills building may be a key factor for promoting physical activity as well as fruit and vegetable intake in adolescents. Copyright © 2012 Wiley Periodicals, Inc.

The Structural Basis of IKs Ion-Channel Activation: Mechanistic Insights from Molecular Simulations.

PubMed

Ramasubramanian, Smiruthi; Rudy, Yoram

2018-06-05

Relating ion channel (iCh) structural dynamics to physiological function remains a challenge. Current experimental and computational techniques have limited ability to explore this relationship in atomistic detail over physiological timescales. A framework associating iCh structure to function is necessary for elucidating normal and disease mechanisms. We formulated a modeling schema that overcomes the limitations of current methods through applications of artificial intelligence machine learning. Using this approach, we studied molecular processes that underlie human IKs voltage-mediated gating. IKs malfunction underlies many debilitating and life-threatening diseases. Molecular components of IKs that underlie its electrophysiological function include KCNQ1 (a pore-forming tetramer) and KCNE1 (an auxiliary subunit). Simulations, using the IKs structure-function model, reproduced experimentally recorded saturation of gating-charge displacement at positive membrane voltages, two-step voltage sensor (VS) movement shown by fluorescence, iCh gating statistics, and current-voltage relationship. Mechanistic insights include the following: 1) pore energy profile determines iCh subconductance; 2) the entire protein structure, not limited to the pore, contributes to pore energy and channel subconductance; 3) interactions with KCNE1 result in two distinct VS movements, causing gating-charge saturation at positive membrane voltages and current activation delay; and 4) flexible coupling between VS and pore permits pore opening at lower VS positions, resulting in sequential gating. The new modeling approach is applicable to atomistic scale studies of other proteins on timescales of physiological function. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Recent advances in the in silico modelling of UDP glucuronosyltransferase substrates.

PubMed

Sorich, Michael J; Smith, Paul A; Miners, John O; Mackenzie, Peter I; McKinnon, Ross A

2008-01-01

UDP glucurononosyltransferases (UGT) are a superfamily of enzymes that catalyse the conjugation of a range of structurally diverse drugs, environmental and endogenous chemicals with glucuronic acid. This process plays a significant role in the clearance and detoxification of many chemicals. Over the last decade the regulation and substrate profiles of UGT isoforms have been increasingly characterised. The resulting data has facilitated the prototyping of ligand based in silico models capable of predicting, and gaining insights into, binding affinity and the substrate- and regio- selectivity of glucuronidation by UGT isoforms. Pharmacophore modelling has produced particularly insightful models and quantitative structure-activity relationships based on machine learning algorithms result in accurate predictions. Simple structural chemical descriptors were found to capture much of the chemical information relevant to UGT metabolism. However, quantum chemical properties of molecules and the nucleophilic atoms in the molecule can enhance both the predictivity and chemical intuitiveness of structure-activity models. Chemical diversity analysis of known substrates has shown some bias towards chemicals with aromatic and aliphatic hydroxyl groups. Future progress in in silico development will depend on larger and more diverse high quality metabolic datasets. Furthermore, improved protein structure data on UGTs will enable the application of structural modelling techniques likely leading to greater insight into the binding and reactive processes of UGT catalysed glucuronidation.

Structural Analysis of Chemokine Receptor–Ligand Interactions

PubMed Central

2017-01-01

This review focuses on the construction and application of structural chemokine receptor models for the elucidation of molecular determinants of chemokine receptor modulation and the structure-based discovery and design of chemokine receptor ligands. A comparative analysis of ligand binding pockets in chemokine receptors is presented, including a detailed description of the CXCR4, CCR2, CCR5, CCR9, and US28 X-ray structures, and their implication for modeling molecular interactions of chemokine receptors with small-molecule ligands, peptide ligands, and large antibodies and chemokines. These studies demonstrate how the integration of new structural information on chemokine receptors with extensive structure–activity relationship and site-directed mutagenesis data facilitates the prediction of the structure of chemokine receptor–ligand complexes that have not been crystallized. Finally, a review of structure-based ligand discovery and design studies based on chemokine receptor crystal structures and homology models illustrates the possibilities and challenges to find novel ligands for chemokine receptors. PMID:28165741

Aconitum and Delphinium sp. Alkaloids as Antagonist Modulators of Voltage-Gated Na+ Channels. AM1/DFT Electronic Structure Investigations and QSAR Studies

PubMed Central

Turabekova, Malakhat A.; Rasulev, Bakhtiyor F.; Levkovich, Mikhail G.; Abdullaev, Nasrulla D.; Leszczynski, Jerzy

2015-01-01

Early pharmacological studies of Aconitum and Delphinium sp. alkaloids suggested that these neurotoxins act at site 2 of voltage-gated Na+ channel and allosterically modulate its function. Understanding structural requirements for these compounds to exhibit binding activity at voltage-gated Na+ channel has been important in various fields. This paper reports quantum-chemical studies and quantitative structure-activity relationships (QSARs) based on a total of 65 natural alkaloids from two plant species, which includes both blockers and openers of sodium ion channel. A series of 18 antagonist alkaloids (9 blockers and 9 openers) have been studied using AM1 and DFT computational methods in order to reveal their structure-activity (structure-toxicity) relationship at electronic level. An examination of frontier orbitals obtained for ground and protonated forms of the compounds revealed that HOMOs and LUMOs were mainly represented by nitrogen atom and benzyl/benzoylester orbitals with –OH and –OCOCH3 contributions. The results obtained from this research have confirmed the experimental findings suggesting that neurotoxins acting at type 2 receptor site of voltage-dependent sodium channel are activators and blockers with common structural features and differ only in efficacy. The energetic tendency of HOMO-LUMO energy gap can probably distinguish activators and blockers that have been observed. Genetic Algorithm with Multiple Linear Regression Analysis (GA-MLRA) technique was also applied for the generation of two-descriptor QSAR models for the set of 65 blockers. Additionally to the computational studies, the HOMO-LUMO gap descriptor in each obtained QSAR model has confirmed the crucial role of charge transfer in receptor-ligand interactions. A number of other descriptors such as logP, IBEG, nNH2, nHDon, nCO have been selected as complementary ones to LUMO and their role in activity alteration has also been discussed. PMID:18201930

Efficient heterologous expression, functional characterization and molecular modeling of annular seabream digestive phospholipase A2.

PubMed

Smichi, Nabil; Othman, Houcemeddine; Achouri, Neila; Noiriel, Alexandre; Triki, Soumaya; Arondel, Vincent; Srairi-Abid, Najet; Abousalham, Abdelkarim; Gargouri, Youssef; Miled, Nabil; Fendri, Ahmed

2018-03-01

Here we report the cDNA cloning of a phospholipase A 2 (PLA 2 ) from five Sparidae species. The deduced amino acid sequences show high similarity with pancreatic PLA 2 . In addition, a phylogenetic tree derived from alignment of various available sequences revealed that Sparidae PLA 2 are closer to avian PLA 2 group IB than to mammals' ones. In order to understand the structure-function relationships of these enzymes, we report here the recombinant expression in E.coli, the refolding and characterization of His-tagged annular seabream PLA 2 (AsPLA 2 ). A single Ni-affinity chromatography step was used to obtain a highly purified recombinant AsPLA 2 with a molecular mass of 15kDa as attested by gel electrophoresis and MALDI-TOF mass spectrometry data. The enzyme has a specific activity of 400U.mg -1 measured on phosphatidylcholine at pH 8.5 and 50°C. The enzyme high thermo-activity and thermo-stability make it a potential candidate in various biological applications. The 3D structure models of these enzymes were compared with structures of phylogenetically related pancreatic PLA 2 . By following these models and utilizing molecular dynamics simulations, the resistance of the AsPLA 2 at high temperatures was explained. Using the monomolecular film technique, AsPLA 2 was found to be active on various phospholipids spread at the air/water interface at a surface pressure between 12 and 25dyncm -1 . Interestingly, this enzyme was shown to be mostly active on dilauroyl-phosphatidylglycerol monolayers and this behavior was confirmed by molecular docking and dynamics simulations analysis. The discovery of a thermo-active new member of Sparidae PLA 2 , provides new insights on structure-activity relationships of fish PLA 2 . Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular Docking, Molecular Dynamics, and Structure–Activity Relationship Explorations of 14-Oxygenated N-Methylmorphinan-6-ones as Potent μ-Opioid Receptor Agonists

PubMed Central

2017-01-01

Among opioids, morphinans are of major importance as the most effective analgesic drugs acting primarily via μ-opioid receptor (μ-OR) activation. Our long-standing efforts in the field of opioid analgesics from the class of morphinans led to N-methylmorphinan-6-ones differently substituted at positions 5 and 14 as μ-OR agonists inducing potent analgesia and fewer undesirable effects. Herein we present the first thorough molecular modeling study and structure–activity relationship (SAR) explorations aided by docking and molecular dynamics (MD) simulations of 14-oxygenated N-methylmorphinan-6-ones to gain insights into their mode of binding to the μ-OR and interaction mechanisms. The structure of activated μ-OR provides an essential model for how ligand/μ-OR binding is encoded within small chemical differences in otherwise structurally similar morphinans. We reveal important molecular interactions that these μ-agonists share and distinguish them. The molecular docking outcomes indicate the crucial role of the relative orientation of the ligand in the μ-OR binding site, influencing the propensity of critical non-covalent interactions that are required to facilitate ligand/μ-OR interactions and receptor activation. The MD simulations point out minor differences in the tendency to form hydrogen bonds by the 4,5α-epoxy group, along with the tendency to affect the 3–7 lock switch. The emerged SARs reveal the subtle interplay between the substituents at positions 5 and 14 in the morphinan scaffold by enabling the identification of key structural elements that determine the distinct pharmacological profiles. This study provides a significant structural basis for understanding ligand binding and μ-OR activation by the 14-oxygenated N-methylmorphinan-6-ones, which should be useful for guiding drug design. PMID:28125215

Quantitative structure activity relationship studies of piperazinyl phenylalanine derivatives as VLA-4/VCAM-1 inhibitors.

PubMed

Bhargava, Dinesh; Karthikeyan, C; Moorthy, N S H N; Trivedi, Piyush

2009-09-01

QSAR study was carried out for a series of piperazinyl phenylalanine derivatives exhibiting VLA-4/VCAM-1 inhibitory activity to find out the structural features responsible for the biological activity. The QSAR study was carried out on V-life Molecular Design Suite software and the derived best QSAR model by partial least square (forward) regression method showed 85.67% variation in biological activity. The statistically significant model with high correlation coefficient (r2=0.85) was selected for further study and the resulted validation parameters of the model, crossed squared correlation coefficient (q2=0.76 and pred_r2=0.42) show the model has good predictive ability. The model showed that the parameters SaaNEindex, SsClcount slogP,and 4PathCount are highly correlated with VLA-4/VCAM-1 inhibitory activity of piperazinyl phenylalanine derivatives. The result of the study suggests that the chlorine atoms in the molecule and fourth order fragmentation patterns in the molecular skeleton favour VLA-4/VCAM-1 inhibition shown by the title compounds whereas lipophilicity and nitrogen bonded to aromatic bond are not conducive for VLA-4/VCAM-1 inhibitory activity.

Selective kappa-opioid agonists: synthesis and structure-activity relationships of piperidines incorporating on oxo-containing acyl group.

PubMed

Giardina, G; Clarke, G D; Dondio, G; Petrone, G; Sbacchi, M; Vecchietti, V

1994-10-14

This study describes the synthesis and the structure-activity relationships (SARs) of the (S)-(-)-enantiomers of a novel class of 2-(aminomethyl)piperidine derivatives, using kappa-opioid binding affinity and antinociceptive potency as the indices of biological activity. Compounds incorporating the 1-tetralon-6-ylacetyl residue (30 and 34-45) demonstrated an in vivo antinociceptive activity greater than predicted on the basis of their kappa-binding affinities. In particular, (2S)-2-[(dimethylamino)methyl]-1-[(5,6,7,8-tetrahydro-5-oxo-2- naphthyl)acetyl]piperidine (34) was found to have a potency similar to spiradoline in animal models of antinociception after subcutaneous administration, with ED50s of 0.47 and 0.73 mumol/kg in the mouse and in the rat abdominal constriction tests, respectively. Further in vivo studies in mice and/or rats revealed that compound 34, compared to other selective kappa-agonists, has a reduced propensity to cause a number of kappa-related side effects, including locomotor impairment/sedation and diuresis, at antinociceptive doses. For example, it has an ED50 of 26.5 mumol/kg sc in the rat rotarod model, exhibiting a ratio of locomotor impairment/sedation vs analgesia of 36. Possible reasons for this differential activity and its clinical consequence are discussed.

Structure-Activity Relationships of Nitro-Substituted Aroylhydrazone Iron Chelators with Antioxidant and Antiproliferative Activities.

PubMed

Hrušková, Kateřina; Potůčková, Eliška; Opálka, Lukáš; Hergeselová, Tereza; Hašková, Pavlína; Kovaříková, Petra; Šimůnek, Tomáš; Vávrová, Kateřina

2018-05-23

Aroylhydrazone iron chelators such as salicylaldehyde isonicotinoyl hydrazone (SIH) protect various cells against oxidative injury and display antineoplastic activities. Previous studies have shown that a nitro-substituted hydrazone, namely, NHAPI, displayed markedly improved plasma stability, selective antitumor activity, and moderate antioxidant properties. In this study, we prepared four series of novel NHAPI derivatives and explored their iron chelation activities, anti- or pro-oxidant effects, protection against model oxidative injury in the H9c2 cell line derived from rat embryonic cardiac myoblasts, cytotoxicities to the corresponding noncancerous H9c2 cells, and antiproliferative activities against the MCF-7 human breast adenocarcinoma and HL-60 human promyelocytic leukemia cell lines. Nitro substitution had both negative and positive effects on the examined properties, and we identified new structure-activity relationships. Naphthyl and biphenyl derivatives showed selective antiproliferative action, particularly in the breast adenocarcinoma MCF-7 cell line, where they exceeded the selectivity of the parent compound NHAPI. Of particular interest is a compound prepared from 2-hydroxy-5-methyl-3-nitroacetophenone and biphenyl-4-carbohydrazide, which protected cardiomyoblasts against oxidative injury at 1.8 ± 1.2 μM with 24-fold higher selectivity than SIH. These compounds will serve as leads for further structural optimization and mechanistic studies.

μ Opioid receptor: novel antagonists and structural modeling

NASA Astrophysics Data System (ADS)

Kaserer, Teresa; Lantero, Aquilino; Schmidhammer, Helmut; Spetea, Mariana; Schuster, Daniela

2016-02-01

The μ opioid receptor (MOR) is a prominent member of the G protein-coupled receptor family and the molecular target of morphine and other opioid drugs. Despite the long tradition of MOR-targeting drugs, still little is known about the ligand-receptor interactions and structure-function relationships underlying the distinct biological effects upon receptor activation or inhibition. With the resolved crystal structure of the β-funaltrexamine-MOR complex, we aimed at the discovery of novel agonists and antagonists using virtual screening tools, i.e. docking, pharmacophore- and shape-based modeling. We suggest important molecular interactions, which active molecules share and distinguish agonists and antagonists. These results allowed for the generation of theoretically validated in silico workflows that were employed for prospective virtual screening. Out of 18 virtual hits evaluated in in vitro pharmacological assays, three displayed antagonist activity and the most active compound significantly inhibited morphine-induced antinociception. The new identified chemotypes hold promise for further development into neurochemical tools for studying the MOR or as potential therapeutic lead candidates.

Structure-based design and biological evaluation of novel 2-(indol-2-yl) thiazole derivatives as xanthine oxidase inhibitors.

PubMed

Song, Jeong Uk; Jang, Jae Wan; Kim, Tae Hun; Park, Heuisul; Park, Wan Su; Jung, Sang-Hun; Kim, Geun Tae

2016-02-01

Inhibition of xanthine oxidase (XO) has obviously been a central concept for controlling hyperuricemia, which causes serious and painful inflammatory arthritis disease such as gout. We discovered a series of novel 2-(indol-2-yl)thiazole derivatives as XO inhibitors at the level of nanomolar activity. Structure-guided design using molecular modeling program (Accelrys Software program) provided an excellent basis for optimization of 2-(indol-2-yl)thiazole compounds. Structure-activity relationship indicated that hydrophobic alkoxy group (isopropoxy, cyclopentoxy) at 5-position and hydrogen binding acceptor (NO2, CN) at 7-position of indole ring appear as critical functional groups. Among the compounds, 2-(7-nitro-5-isopropoxy-indol-2-yl)-4-methylthiazole-5-carboxylic acid (9m) exhibits the most potent XO inhibitory activity (IC50 value: 5.1 nM) and the excellent uric acid lowering activity in potassium oxonate induced hyperuricemic rat model. Copyright © 2016. Published by Elsevier Ltd.

A review of the global relationship among freshwater fish, autotrophic activity, and regional climate

USGS Publications Warehouse

Deines, Andrew M.; Bunnell, David B.; Rogers, Mark W.; Beard, T. Douglas; Taylor, William W.

2015-01-01

The relationship between autotrophic activity and freshwater fish populations is an important consideration for ecologists describing trophic structure in aquatic communities, fisheries managers tasked with increasing sustainable fisheries development, and fish farmers seeking to maximize production. Previous studies of the empirical relationships of autotrophic activity and freshwater fish yield have found positive relationships but were limited by small sample sizes, small geographic scopes, and the inability to compare patterns among many types of measurement techniques. Individual studies and reviews have also lacked consistent consideration of regional climate factors which may inform relationships between fisheries and autotrophic activity. We compiled data from over 700 freshwater systems worldwide and used meta-analysis and linear models to develop a comprehensive global synthesis between multiple metrics of autotrophic activity, fisheries, and climate indicators. Our results demonstrate that multiple metrics of fish (i.e., catch per unit effort, yield, and production) increase with autotrophic activity across a variety of fisheries. At the global scale additional variation in this positive relationship can be ascribed to regional climate differences (i.e., temperature and precipitation) across systems. Our results provide a method and proof-of-concept for assessing inland fisheries production at the global scale, where current estimates are highly uncertain, and may therefore inform the continued sustainable use of global inland fishery resources.

A categorical structure-activity relationship analysis of the developmental toxicity of antithyroid drugs.

PubMed

Cunningham, Albert R; Carrasquer, C Alex; Mattison, Donald R

2009-01-01

The choice of therapeutic strategies for hyperthyroidism during pregnancy is limited. Surgery and radioiodine are typically avoided, leaving propylthiouracil and methimazole in the US. Carbimazole, a metabolic precursor of methimazole, is available in some countries outside of the US. In the US propylthiouracil is recommended because of concern about developmental toxicity from methimazole and carbimazole. Despite this recommendation, the data on developmental toxicity of all three agents are extremely limited and insufficient to support a policy given the broad use of methimazole and carbimazole around the world. In the absence of new human or animal data we describe the development of a new structure-activity relationship (SAR) model for developmental toxicity using the cat-SAR expert system. The SAR model was developed from data for 323 compounds evaluated for human developmental toxicity with 130 categorized as developmental toxicants and 193 as nontoxicants. Model cross-validation yielded a concordance between observed and predicted results between 79% to 81%. Based on this model, propylthiouracil, methimazole, and carbimazole were observed to share some structural features relating to human developmental toxicity. Thus given the need to treat women with Graves's disease during pregnancy, new molecules with minimized risk for developmental toxicity are needed. To help meet this challenge, the cat-SAR method would be a useful in screening new drug candidates for developmental toxicity as well as for investigating their mechanism of action.

Automatically updating predictive modeling workflows support decision-making in drug design.

PubMed

Muegge, Ingo; Bentzien, Jörg; Mukherjee, Prasenjit; Hughes, Robert O

2016-09-01

Using predictive models for early decision-making in drug discovery has become standard practice. We suggest that model building needs to be automated with minimum input and low technical maintenance requirements. Models perform best when tailored to answering specific compound optimization related questions. If qualitative answers are required, 2-bin classification models are preferred. Integrating predictive modeling results with structural information stimulates better decision making. For in silico models supporting rapid structure-activity relationship cycles the performance deteriorates within weeks. Frequent automated updates of predictive models ensure best predictions. Consensus between multiple modeling approaches increases the prediction confidence. Combining qualified and nonqualified data optimally uses all available information. Dose predictions provide a holistic alternative to multiple individual property predictions for reaching complex decisions.

Perovskite oxides: Oxygen electrocatalysis and bulk structure

NASA Technical Reports Server (NTRS)

Carbonio, R. E.; Fierro, C.; Tryk, D.; Scherson, D.; Yeager, Ernest

1987-01-01

Perovskite type oxides were considered for use as oxygen reduction and generation electrocatalysts in alkaline electrolytes. Perovskite stability and electrocatalytic activity are studied along with possible relationships of the latter with the bulk solid state properties. A series of compounds of the type LaFe(x)Ni1(-x)O3 was used as a model system to gain information on the possible relationships between surface catalytic activity and bulk structure. Hydrogen peroxide decomposition rate constants were measured for these compounds. Ex situ Mossbauer effect spectroscopy (MES), and magnetic susceptibility measurements were used to study the solid state properties. X ray photoelectron spectroscopy (XPS) was used to examine the surface. MES has indicated the presence of a paramagnetic to magnetically ordered phase transition for values of x between 0.4 and 0.5. A correlation was found between the values of the MES isomer shift and the catalytic activity for peroxide decomposition. Thus, the catalytic activity can be correlated to the d-electron density for the transition metal cations.

Perovskite-type oxides - Oxygen electrocatalysis and bulk structure

NASA Technical Reports Server (NTRS)

Carbonio, R. E.; Fierro, C.; Tryk, D.; Scherson, D.; Yeager, E.

1988-01-01

Perovskite type oxides were considered for use as oxygen reduction and generation electrocatalysts in alkaline electrolytes. Perovskite stability and electrocatalytic activity are studied along with possible relationships of the latter with the bulk solid state properties. A series of compounds of the type LaFe(x)Ni1(-x)O3 was used as a model system to gain information on the possible relationships between surface catalytic activity and bulk structure. Hydrogen peroxide decomposition rate constants were measured for these compounds. Ex situ Mossbauer effect spectroscopy (MES), and magnetic susceptibility measurements were used to study the solid state properties. X ray photoelectron spectroscopy (XPS) was used to examine the surface. MES has indicated the presence of a paramagnetic to magnetically ordered phase transition for values of x between 0.4 and 0.5. A correlation was found between the values of the MES isomer shift and the catalytic activity for peroxide decomposition. Thus, the catalytic activity can be correlated to the d-electron density for the transition metal cations.

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

DEVELOPMENT OF STRUCTURE ACTIVITY RELATIONSHIPS FOR ASSESSING ECOLOGICAL RISKS

EPA Science Inventory

In the field of environmental toxicology, structure activity relationships (SARs) have developed as scientifically-credible tools for predicting the effects of chemicals when little or no empirical data are available.

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...

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...

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...

Prediction of enzyme activity with neural network models based on electronic and geometrical features of substrates.

PubMed

Szaleniec, Maciej

2012-01-01

Artificial Neural Networks (ANNs) are introduced as robust and versatile tools in quantitative structure-activity relationship (QSAR) modeling. Their application to the modeling of enzyme reactivity is discussed, along with methodological issues. Methods of input variable selection, optimization of network internal structure, data set division and model validation are discussed. The application of ANNs in the modeling of enzyme activity over the last 20 years is briefly recounted. The discussed methodology is exemplified by the case of ethylbenzene dehydrogenase (EBDH). Intelligent Problem Solver and genetic algorithms are applied for input vector selection, whereas k-means clustering is used to partition the data into training and test cases. The obtained models exhibit high correlation between the predicted and experimental values (R(2) > 0.9). Sensitivity analyses and study of the response curves are used as tools for the physicochemical interpretation of the models in terms of the EBDH reaction mechanism. Neural networks are shown to be a versatile tool for the construction of robust QSAR models that can be applied to a range of aspects important in drug design and the prediction of biological activity.

Discovery, synthesis, and structure-activity relationships of 20(S)-protopanaxadiol (PPD) derivatives as a novel class of AMPKα2β1γ1 activators.

PubMed

Liu, Junhua; Chen, Dakai; Liu, Peng; He, Mengna; Li, Jia; Li, Jingya; Hu, Lihong

2014-05-22

Adenosine 5'-monophosphate-activated protein kinase (AMPK) has been demonstrated as a promising drug target due to its regulatory function in glucose and lipid metabolism. 20(S)-protopanoxadiol (PPD) was firstly identified from high throughput screening as a small molecule activator of AMPK subtype α2β1γ1. In order to enhance its potency on AMPK, a series of PPD derivatives were synthesized and evaluated. Structure-activity relationship study showed that the amine derivatives at the 24-position (groups I-VI) can improve the potency (EC50: 0.7-2.3 μM) and efficacy (fold: 2.5-3.8). Among them, compounds 12 and 13 exhibited the best potency (EC50: 1.2 and 0.7 μM) and efficacy (fold: 3.7 and 3.8). Further study suggested the mechanism of AMPK activation may functioned at the allosteric position, resulting the inhibition of the lipid synthesis in HepG2 cell model. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Predicting Monoamine Oxidase Inhibitory Activity through Ligand-Based Models

PubMed Central

Vilar, Santiago; Ferino, Giulio; Quezada, Elias; Santana, Lourdes; Friedman, Carol

2013-01-01

The evolution of bio- and cheminformatics associated with the development of specialized software and increasing computer power has produced a great interest in theoretical in silico methods applied in drug rational design. These techniques apply the concept that “similar molecules have similar biological properties” that has been exploited in Medicinal Chemistry for years to design new molecules with desirable pharmacological profiles. Ligand-based methods are not dependent on receptor structural data and take into account two and three-dimensional molecular properties to assess similarity of new compounds in regards to the set of molecules with the biological property under study. Depending on the complexity of the calculation, there are different types of ligand-based methods, such as QSAR (Quantitative Structure-Activity Relationship) with 2D and 3D descriptors, CoMFA (Comparative Molecular Field Analysis) or pharmacophoric approaches. This work provides a description of a series of ligand-based models applied in the prediction of the inhibitory activity of monoamine oxidase (MAO) enzymes. The controlled regulation of the enzymes’ function through the use of MAO inhibitors is used as a treatment in many psychiatric and neurological disorders, such as depression, anxiety, Alzheimer’s and Parkinson’s disease. For this reason, multiple scaffolds, such as substituted coumarins, indolylmethylamine or pyridazine derivatives were synthesized and assayed toward MAO-A and MAO-B inhibition. Our intention is to focus on the description of ligand-based models to provide new insights in the relationship between the MAO inhibitory activity and the molecular structure of the different inhibitors, and further study enzyme selectivity and possible mechanisms of action. PMID:23231398

The Role of Self-Efficacy and Referent Specific Social Support in Promoting Rural Adolescent Girls' Physical Activity

ERIC Educational Resources Information Center

Beets, Michael W.; Pitetti, Kenneth H.; Forlaw, Loretta

2007-01-01

Objective: To examine the role of social support (SS) and self-efficacy (SE) for physical activity (PA) in rural high school girls (N = 259, 15.5+1.2yrs). Methods: Using structural equation modeling, the relationships among PA, SS for PA from mother, father, and peers, and SE for overcoming barriers, seeking support, and resisting competing…

Longitudinal relationships between resources, motivation, and functioning.

PubMed

Hess, Thomas M; Emery, Lisa; Neupert, Shevaun D

2012-05-01

We investigated how fluctuations and linear changes in health and cognitive resources influence the motivation to engage in complex cognitive activity and the extent to which motivation mediated the relationship between changing resources and cognitively demanding activities. Longitudinal data from 332 adults aged 20-85 years were examined. Motivation was assessed using a composite of Need for Cognition and Personal Need for Structure and additional measures of health, sensory functioning, cognitive ability, and self-reported activity engagement. Multilevel modeling revealed that age-typical changes in health, sensory functions, and ability were associated with changes in motivation, with the impact of declining health on motivation being particularly strong in older adulthood. Changes in motivation, in turn, predicted involvement in cognitive and social activities as well as changes in cognitive ability. Finally, motivation was observed to partially mediate the relationship between changes in resources and cognitively demanding activities. Our results suggest that motivation may play an important role in determining the course of cognitive change and involvement in cognitively demanding everyday activities in adulthood.

Toxicity Evaluation of Engineered Nanomaterials: Risk Evaluation Tools (Phase 3 Studies)

DTIC Science & Technology

2012-01-01

report. The second modeling approach was on quantitative structure activity relationships ( QSARs ). A manuscript entitled “Connecting the dots: Towards...expands rapidly. We proposed two types of mechanisms of toxic action supported by the nano- QSAR model , which collectively govern the toxicity of the...interpretative nano- QSAR model describing toxicity of 18 nano-metal oxides to a HaCaT cell line as a model for dermal exposure. In result, by the comparison of

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.

Computer aided drug design

NASA Astrophysics Data System (ADS)

Jain, A.

2017-08-01

Computer based method can help in discovery of leads and can potentially eliminate chemical synthesis and screening of many irrelevant compounds, and in this way, it save time as well as cost. Molecular modeling systems are powerful tools for building, visualizing, analyzing and storing models of complex molecular structure that can help to interpretate structure activity relationship. The use of various techniques of molecular mechanics and dynamics and software in Computer aided drug design along with statistics analysis is powerful tool for the medicinal chemistry to synthesis therapeutic and effective drugs with minimum side effect.

Effect of inhibitory feedback on correlated firing of spiking neural network.

PubMed

Xie, Jinli; Wang, Zhijie

2013-08-01

Understanding the properties and mechanisms that generate different forms of correlation is critical for determining their role in cortical processing. Researches on retina, visual cortex, sensory cortex, and computational model have suggested that fast correlation with high temporal precision appears consistent with common input, and correlation on a slow time scale likely involves feedback. Based on feedback spiking neural network model, we investigate the role of inhibitory feedback in shaping correlations on a time scale of 100 ms. Notably, the relationship between the correlation coefficient and inhibitory feedback strength is non-monotonic. Further, computational simulations show how firing rate and oscillatory activity form the basis of the mechanisms underlying this relationship. When the mean firing rate holds unvaried, the correlation coefficient increases monotonically with inhibitory feedback, but the correlation coefficient keeps decreasing when the network has no oscillatory activity. Our findings reveal that two opposing effects of the inhibitory feedback on the firing activity of the network contribute to the non-monotonic relationship between the correlation coefficient and the strength of the inhibitory feedback. The inhibitory feedback affects the correlated firing activity by modulating the intensity and regularity of the spike trains. Finally, the non-monotonic relationship is replicated with varying transmission delay and different spatial network structure, demonstrating the universality of the results.

Trainable structure-activity relationship model for virtual screening of CYP3A4 inhibition.

PubMed

Didziapetris, Remigijus; Dapkunas, Justas; Sazonovas, Andrius; Japertas, Pranas

2010-11-01

A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for >800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. For compounds within this domain the statistical results of the final model approach the data consistency between experimental data from literature and PubChem datasets with the overall accuracy of 89%. However, the original model is applicable only for less than a half of PubChem database. Since the similarity correction procedure of GALAS modeling method allows straightforward model training, the possibility to expand the applicability domain has been investigated. Experimental data from PubChem dataset served as an example of in-house high-throughput screening data. The model successfully adapted itself to both data classified using the same and different IC₅₀ threshold compared with the training set. In addition, adjustment of the CYP3A4 inhibition model to compounds with a novel chemical scaffold has been demonstrated. The reported GALAS model is proposed as a useful tool for virtual screening of compounds for possible drug-drug interactions even prior to the actual synthesis.

Structure-activity relationships for chloro- and nitrophenol toxicity in the pollen tube growth test

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

Schueuermann, G.; Somashekar, R.K.; Kristen, U.

Acute toxicity of 10 chlorophenols and 10 nitrophenols with identical substitution patterns is analyzed with the pollen tube growth (PTG) test. Concentration values of 50% growth inhibition (IC50) between 0.1 and 300 mg/L indicate that the absolute sensitivity of this alternative biotest is comparable to conventional aquatic test systems. Analysis of quantitative structure-activity relationships using lipophilicity (log K{sub ow}), acidity (pK{sub a}), and quantum chemical parameters to model intrinsic acidity, solvation interactions, and nucleophilicity reveals substantial differences between the intraseries trends of log IC50. With chlorophenols, a narcotic-type relationship is derived, which, however, shows marked differences in slope and interceptmore » when compared to reference regression equations for polar narcosis. Regression analysis of nitrophenol toxicity suggests interpretation in terms of two modes of action: oxidative uncoupling activity is associated with a pK{sub a} window from 3.8 to 8.5, and more acidic congeners with diortho-substitution show a transition from uncoupling to a narcotic mode of action with decreasing pK{sub a} and log K{sub ow}. Model calculations for phenol nucleophilicity suggest that differences in the phenol readiness for glucuronic acid conjugation as a major phase-II detoxication pathway have no direct influence on acute PTG toxicity of the compounds.« less

A Comparative Structural Equation Modeling Investigation of the Relationships among Teaching, Cognitive and Social Presence

ERIC Educational Resources Information Center

Kozan, Kadir

2016-01-01

The present study investigated the relationships among teaching, cognitive, and social presence through several structural equation models to see which model would better fit the data. To this end, the present study employed and compared several different structural equation models because different models could fit the data equally well. Among…

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

PubMed

Fang, Xingang; Bagui, Sikha; Bagui, Subhash

2017-08-01

The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

A mechanistic stress model of protein evolution accounts for site-specific evolutionary rates and their relationship with packing density and flexibility

PubMed Central

2014-01-01

Background Protein sites evolve at different rates due to functional and biophysical constraints. It is usually considered that the main structural determinant of a site’s rate of evolution is its Relative Solvent Accessibility (RSA). However, a recent comparative study has shown that the main structural determinant is the site’s Local Packing Density (LPD). LPD is related with dynamical flexibility, which has also been shown to correlate with sequence variability. Our purpose is to investigate the mechanism that connects a site’s LPD with its rate of evolution. Results We consider two models: an empirical Flexibility Model and a mechanistic Stress Model. The Flexibility Model postulates a linear increase of site-specific rate of evolution with dynamical flexibility. The Stress Model, introduced here, models mutations as random perturbations of the protein’s potential energy landscape, for which we use simple Elastic Network Models (ENMs). To account for natural selection we assume a single active conformation and use basic statistical physics to derive a linear relationship between site-specific evolutionary rates and the local stress of the mutant’s active conformation. We compare both models on a large and diverse dataset of enzymes. In a protein-by-protein study we found that the Stress Model outperforms the Flexibility Model for most proteins. Pooling all proteins together we show that the Stress Model is strongly supported by the total weight of evidence. Moreover, it accounts for the observed nonlinear dependence of sequence variability on flexibility. Finally, when mutational stress is controlled for, there is very little remaining correlation between sequence variability and dynamical flexibility. Conclusions We developed a mechanistic Stress Model of evolution according to which the rate of evolution of a site is predicted to depend linearly on the local mutational stress of the active conformation. Such local stress is proportional to LPD, so that this model explains the relationship between LPD and evolutionary rate. Moreover, the model also accounts for the nonlinear dependence between evolutionary rate and dynamical flexibility. PMID:24716445

Synthesis, Structure-Activity Relationships (SAR) and in Silico Studies of Coumarin Derivatives with Antifungal Activity

PubMed Central

de Araújo, Rodrigo S. A.; Guerra, Felipe Q. S.; de O. Lima, Edeltrudes; de Simone, Carlos A.; Tavares, Josean F.; Scotti, Luciana; Scotti, Marcus T.; de Aquino, Thiago M.; de Moura, Ricardo O.; Mendonça, Francisco J. B.; Barbosa-Filho, José M.

2013-01-01

The increased incidence of opportunistic fungal infections, associated with greater resistance to the antifungal drugs currently in use has highlighted the need for new solutions. In this study twenty four coumarin derivatives were screened in vitro for antifungal activity against strains of Aspergillus. Some of the compounds exhibited significant antifungal activity with MICs values ranging between 16 and 32 μg/mL. The structure-activity relationships (SAR) study demonstrated that O-substitutions are essential for antifungal activity. It also showed that the presence of a short aliphatic chain and/or electron withdrawing groups (NO2 and/or acetate) favor activity. These findings were confirmed using density functional theory (DFT), when calculating the LUMO density. In Principal Component Analysis (PCA), two significant principal components (PCs) explained more than 60% of the total variance. The best Partial Least Squares Regression (PLS) model showed an r2 of 0.86 and q2cv of 0.64 corroborating the SAR observations as well as demonstrating a greater probe N1 interaction for active compounds. Descriptors generated by TIP correlogram demonstrated the importance of the molecular shape for antifungal activity. PMID:23306152

A Systematic Review of Music Therapy Practice and Outcomes with Acute Adult Psychiatric In-Patients

PubMed Central

Carr, Catherine; Odell-Miller, Helen; Priebe, Stefan

2013-01-01

Background and Objectives There is an emerging evidence base for the use of music therapy in the treatment of severe mental illness. Whilst different models of music therapy have been developed in mental health care, none have specifically accounted for the features and context of acute in-patient settings. This review aimed to identify how music therapy is provided for acute adult psychiatric in-patients and what outcomes have been reported. Review Methods A systematic review using medical, psychological and music therapy databases. Papers describing music therapy with acute adult psychiatric in-patients were included. Analysis utilised narrative synthesis. Results 98 papers were identified, of which 35 reported research findings. Open group work and active music making for nonverbal expression alongside verbal reflection was emphasised. Aims were engagement, communication and interpersonal relationships focusing upon immediate areas of need rather than longer term insight. The short stay, patient diversity and institutional structure influenced delivery and resulted in a focus on single sessions, high session frequency, more therapist direction, flexible use of musical activities, predictable musical structures, and clear realistic goals. Outcome studies suggested effectiveness in addressing a range of symptoms, but were limited by methodological shortcomings and small sample sizes. Studies with significant positive effects all used active musical participation with a degree of structure and were delivered in four or more sessions. Conclusions No single clearly defined model exists for music therapy with adults in acute psychiatric in-patient settings, and described models are not conclusive. Greater frequency of therapy, active structured music making with verbal discussion, consistency of contact and boundaries, an emphasis on building a therapeutic relationship and building patient resources may be of particular importance. Further research is required to develop specific music therapy models for this patient group that can be tested in experimental studies. PMID:23936399

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.

Clustering of 3D-Structure Similarity Based Network of Secondary Metabolites Reveals Their Relationships with Biological Activities.

PubMed

Ohtana, Yuki; Abdullah, Azian Azamimi; Altaf-Ul-Amin, Md; Huang, Ming; Ono, Naoaki; Sato, Tetsuo; Sugiura, Tadao; Horai, Hisayuki; Nakamura, Yukiko; Morita Hirai, Aki; Lange, Klaus W; Kibinge, Nelson K; Katsuragi, Tetsuo; Shirai, Tsuyoshi; Kanaya, Shigehiko

2014-12-01

Developing database systems connecting diverse species based on omics is the most important theme in big data biology. To attain this purpose, we have developed KNApSAcK Family Databases, which are utilized in a number of researches in metabolomics. In the present study, we have developed a network-based approach to analyze relationships between 3D structure and biological activity of metabolites consisting of four steps as follows: construction of a network of metabolites based on structural similarity (Step 1), classification of metabolites into structure groups (Step 2), assessment of statistically significant relations between structure groups and biological activities (Step 3), and 2-dimensional clustering of the constructed data matrix based on statistically significant relations between structure groups and biological activities (Step 4). Applying this method to a data set consisting of 2072 secondary metabolites and 140 biological activities reported in KNApSAcK Metabolite Activity DB, we obtained 983 statistically significant structure group-biological activity pairs. As a whole, we systematically analyzed the relationship between 3D-chemical structures of metabolites and biological activities. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-Efficacy, Depression, and Self-Care Activities in Adult Jordanians with Type 2 Diabetes: The Role of Illness Perception.

PubMed

Al-Amer, Rasmieh; Ramjan, Lucie; Glew, Paul; Randall, Sue; Salamonson, Yenna

2016-10-01

Diabetes mellitus is reaching epidemic levels worldwide. In a developing country like Jordan, type 2 diabetes mellitus (T2DM) has reached a prevalence rate of 17.1%. This cross-sectional study examined the relationship between self-care activities and: illness perception, depression, social support, religiosity and spiritual coping, and self-efficacy among patients with T2DM. A random sample of 220 patients with T2DM, who attended Jordan University Hospital in Jordan were enrolled. The data were collected through a structured interview and the medical files. The instruments consisted of a sociodemographic and clinical standardised questionnaires: Brief Illness Perception Questionnaire, Patients' Health Questionnaire-9; ENRICH Social Support Instrument; Religious and Spiritual Coping Subscale; Diabetes Management Self-Efficacy Scale; and Summary of Diabetes Self-Care Activities. Bivariate analysis investigated the relationship between variables. Structure Equation Modelling (SEM) was performed to test the proposed conceptual model. The study found that approximately 70% of the respondents suffered some form of depressive symptoms. The SEM showed a direct relationship between self-efficacy and self-care activities (β = 0.40; p < 0.001). Depression was indirectly related to self-care activities through self-efficacy (β = -0.20; p = 0.003); nevertheless, it was directly related to perception of: treatment control, consequences, and emotional representations. Overall, the sequence between illness perception and self-efficacy was mediated by depression. Strategies to promote self-efficacy and illness perception are vital in customising a diabetes health plan to meet Arabic cultural expectations.

CERAPP: Collaborative Estrogen Receptor Activity Prediction ...

EPA Pesticide Factsheets

Humans potentially are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Many of these chemicals never have been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for assessment in costly in vivo tests, for instance, within the EPA Endocrine Disruptor Screening Program. Here, we describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating the efficacy of using predictive computational models on high-throughput screening data to screen thousands of chemicals against the ER. CERAPP combined multiple models developed in collaboration among 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1677 compounds provided by EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were tested using an evaluation set of 7522 chemicals collected from the literature. To overcome the limitations of single models, a consensus was built weighting models using a scoring function (0 to 1) based on their accuracies. Individual model scores ranged from 0.69 to 0.85, showing

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

Field, Kevin G.; Univ. of Wisconsin, Madison, WI; Miller, Brandon D.

Ferritic/Martensitic (F/M) steels with high Cr content posses the high temperature strength and low swelling rates required for advanced nuclear reactor designs. Radiation induced segregation (RIS) occurs in F/M steels due to solute atoms preferentially coupling to point defect fluxes which migrate to defect sinks, such as grain boundaries (GBs). The RIS response of F/M steels and austenitic steels has been shown to be dependent on the local structure of GBs where low energy structures have suppressed RIS responses. This relationship between local GB structure and RIS has been demonstrated primarily in ion-irradiated specimens. A 9 wt.% Cr model alloymore » steel was irradiated to 3 dpa using neutrons at the Advanced Test Reactor (ATR) to determine the effect of a neutron radiation environment on the RIS response at different GB structures. This investigation found the relationship between GB structure and RIS is also active for F/M steels irradiated using neutrons. The data generated from the neutron irradiation is also compared to RIS data generated using proton irradiations on the same heat of model alloy.« less

QSPR models for predicting generator-column-derived octanol/water and octanol/air partition coefficients of polychlorinated biphenyls.

PubMed

Yuan, Jintao; Yu, Shuling; Zhang, Ting; Yuan, Xuejie; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

2016-06-01

Octanol/water (K(OW)) and octanol/air (K(OA)) partition coefficients are two important physicochemical properties of organic substances. In current practice, K(OW) and K(OA) values of some polychlorinated biphenyls (PCBs) are measured using generator column method. Quantitative structure-property relationship (QSPR) models can serve as a valuable alternative method of replacing or reducing experimental steps in the determination of K(OW) and K(OA). In this paper, two different methods, i.e., multiple linear regression based on dragon descriptors and hologram quantitative structure-activity relationship, were used to predict generator-column-derived log K(OW) and log K(OA) values of PCBs. The predictive ability of the developed models was validated using a test set, and the performances of all generated models were compared with those of three previously reported models. All results indicated that the proposed models were robust and satisfactory and can thus be used as alternative models for the rapid assessment of the K(OW) and K(OA) of PCBs. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Derivatives of Ergot-alkaloids: Molecular structure, physical properties, and structure-activity relationships

NASA Astrophysics Data System (ADS)

Ivanova, Bojidarka B.; Spiteller, Michael

2012-09-01

A comprehensive screening of fifteen functionalized Ergot-alkaloids, containing bulk aliphatic cyclic substituents at D-ring of the ergoline molecular skeleton was performed, studying their structure-active relationships and model interactions with α2A-adreno-, serotonin (5HT2A) and dopamine D3 (D3A) receptors. The accounted high affinity to the receptors binding loops and unusual bonding situations, joined with the molecular flexibility of the substituents and the presence of proton accepting/donating functional groups in the studied alkaloids, may contribute to further understanding the mechanisms of biological activity in vivo and in predicting their therapeutic potential in central nervous system (CNS), including those related the Schizophrenia. Since the presented correlation between the molecular structure and properties, was based on the comprehensively theoretical computational and experimental physical study on the successfully isolated derivatives, through using routine synthetic pathways in a relatively high yields, marked these derivatives as 'treasure' for further experimental and theoretical studied in areas such as: (a) pharmacological and clinical testing; (b) molecular-drugs design of novel psychoactive substances; (c) development of the analytical protocols for determination of Ergot-alkaloids through a functionalization of the ergoline-skeleton, and more.

Organophosphorus (OP) Pesticide Degradation in the Presence of Chlorinated Oxidants: Kinetics, Modeling, and Structure-Activity Relationships

EPA Science Inventory

The rates and pathways for pesticide transformation during drinking water treatment are known for only a few pesticides and under limited conditions. The resulting oxons are more toxic than the parent pesticides. The transformation rates and pathways for chlorpyrifos, an OP pest...

Need Support, Need Satisfaction, Intrinsic Motivation, and Physical Activity Participation among Middle School Students

ERIC Educational Resources Information Center

Zhang, Tao; Solmon, Melinda A.; Kosma, Maria; Carson, Russell L.; Gu, Xiangli

2011-01-01

Using self-determination theory as a framework, the purpose of this study was to test a structural model of hypothesized relationships among perceived need support from physical education teachers (autonomy support, competence support, and relatedness support), psychological need satisfaction (autonomy, competence, and relatedness), intrinsic…

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...

An Undergraduate Laboratory Activity on Molecular Dynamics Simulations

ERIC Educational Resources Information Center

Spitznagel, Benjamin; Pritchett, Paige R.; Messina, Troy C.; Goadrich, Mark; Rodriguez, Juan

2016-01-01

Vision and Change [AAAS, 2011] outlines a blueprint for modernizing biology education by addressing conceptual understanding of key concepts, such as the relationship between structure and function. The document also highlights skills necessary for student success in 21st century Biology, such as the use of modeling and simulation. Here we…

The Relationship of Freshmen's Physics Achievement and Their Related Affective Characteristics

ERIC Educational Resources Information Center

Gungor, Almer (Abak); Eryilmaz, Ali; Fakioglu, Turgut

2007-01-01

The purpose of this study was to determine the best-fitting structural equation model between the freshmen's physics achievement and selected affective characteristics related to physics. These characteristics are students' situational interest in physics, personal interest in physics, aspiring extra activities related to physics, importance of…

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.

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).

Protein model discrimination using mutational sensitivity derived from deep sequencing.

PubMed

Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

2012-02-08

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

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

Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome

PubMed Central

Low, Yen S; Caster, Ola; Bergvall, Tomas; Fourches, Denis; Zang, Xiaoling; Norén, G Niklas; Rusyn, Ivan; Edwards, Ralph

2016-01-01

Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%–81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations. PMID:26499102

Dihydro-β-agarofuran sesquiterpenes from celastraceae species as anti-tumour-promoting agents: Structure-activity relationship.

PubMed

Núñez, Marvin J; Jiménez, Ignacio A; Mendoza, Cristina R; Chavez-Sifontes, Marvin; Martinez, Morena L; Ichiishi, Eiichiro; Tokuda, Ryo; Tokuda, Harukuni; Bazzocchi, Isabel L

2016-03-23

Inhibition of tumour promotion in multistage chemical carcinogenesis is considered a promising strategy for cancer chemoprevention. In an ongoing investigation of bioactive secondary metabolites from Celastraceae species, five new dihydro-β-agarofuran sesquiterpenes (1-5), named Chiapens A-E, and seventeen known ones, were isolated from Maytenus chiapensis. Their structures were elucidated by extensive NMR spectroscopic and mass spectrometric techniques, and their absolute configurations were determined by circular dichroism studies, chemical correlations and biogenic means. The isolated compounds, along with twenty known sesquiterpenes, previously isolated from Zinowiewia costaricensis, have been tested for their inhibitory effects on Epstein-Barr virus early antigen (EBV-EA) activation induced by 12-O-tetradecanoylphorpol-13-acetate (TPA). Thirty three compounds from this series showed stronger effects than that of β-carotene, the reference inhibitor. The structure-activity relationship (SAR) analysis revealed that the type of substituent, in particular at the C-1 position of the sesquiterpene scaffold, was able to modulate the anti-tumour promoting activity. Compounds 3, 6, and 33 showed significant effects in an in vivo two-stage mouse-skin carcinogenesis model. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

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.

Discovery of a Manduca sexta Allatotropin Antagonist from a Manduca sexta Allatotropin Receptor Homology Model.

PubMed

Kai, Zhen-Peng; Zhu, Jing-Jing; Deng, Xi-Le; Yang, Xin-Ling; Chen, Shan-Shan

2018-04-03

Insect G protein coupled receptors (GPCRs) have important roles in modulating biology, physiology and behavior. They have been identified as candidate targets for next-generation insecticides, yet these targets have been relatively poorly exploited for insect control. In this study, we present a pipeline of novel Manduca sexta allatotropin (Manse-AT) antagonist discovery with homology modeling, docking, molecular dynamics simulation and structure-activity relationship. A series of truncated and alanine-replacement analogs of Manse-AT were assayed for the stimulation of juvenile hormone biosynthesis. The minimum sequence required to retain potent biological activity is the C -terminal amidated octapeptide Manse-AT (6-13). We identified three residues essential for bioactivity (Thr⁴, Arg6 and Phe⁸) by assaying alanine-replacement analogs of Manse-AT (6-13). Alanine replacement of other residues resulted in reduced potency but bioactivity was retained. The 3D structure of the receptor (Manse-ATR) was built and the binding pocket was identified. The binding affinities of all the analogs were estimated by calculating the free energy of binding. The calculated binding affinities corresponded to the biological activities of the analogs, which supporting our localization of the binding pocket. Then, based on the docking and molecular dynamics studies of Manse-AT (10-13), we described it can act as a potent Manse-AT antagonist. The antagonistic effect on JH biosynthesis of Manse-AT (10-13) validated our hypothesis. The IC 50 value of antagonist Manse-AT (10-13) is 0.9 nM. The structure-activity relationship of antagonist Manse-AT (10-13) was also studied for the further purpose of investigating theoretically the structure factors influencing activity. These data will be useful for the design of new Manse-AT agonist and antagonist as potential pest control agents.

Electronic Structures of Anti-Ferromagnetic Tetraradicals: Ab Initio and Semi-Empirical Studies.

PubMed

Zhang, Dawei; Liu, Chungen

2016-04-12

The energy relationships and electronic structures of the lowest-lying spin states in several anti-ferromagnetic tetraradical model systems are studied with high-level ab initio and semi-empirical methods. The Full-CI method (FCI), the complete active space second-order perturbation theory (CASPT2), and the n-electron valence state perturbation theory (NEVPT2) are employed to obtain reference results. By comparing the energy relationships predicted from the Heisenberg and Hubbard models with ab initio benchmarks, the accuracy of the widely used Heisenberg model for anti-ferromagnetic spin-coupling in low-spin polyradicals is cautiously tested in this work. It is found that the strength of electron correlation (|U/t|) concerning anti-ferromagnetically coupled radical centers could range widely from strong to moderate correlation regimes and could become another degree of freedom besides the spin multiplicity. Accordingly, the Heisenberg-type model works well in the regime of strong correlation, which reproduces well the energy relationships along with the wave functions of all the spin states. In moderately spin-correlated tetraradicals, the results of the prototype Heisenberg model deviate severely from those of multi-reference electron correlation ab initio methods, while the extended Heisenberg model, containing four-body terms, can introduce reasonable corrections and maintains its accuracy in this condition. In the weak correlation regime, both the prototype Heisenberg model and its extended forms containing higher-order correction terms will encounter difficulties. Meanwhile, the Hubbard model shows balanced accuracy from strong to weak correlation cases and can reproduce qualitatively correct electronic structures, which makes it more suitable for the study of anti-ferromagnetic coupling in polyradical systems.

Structure-activity relationship of indoloquinoline analogs anti-MRSA.

PubMed

Zhao, Min; Kamada, Tomonori; Takeuchi, Aya; Nishioka, Hiromi; Kuroda, Teruo; Takeuchi, Yasuo

2015-12-01

Indolo[3,2-b]quinoline analogs (3a-3s), 4-(acridin-9-ylamino) phenol hydrochloride (4), benzofuro[3,2-b]quinoline (3t), indeno[1,2-b]quinolines (3u and 3v) have been synthesized. Those compounds were found to exhibit anti-bacterial activity towards Methicillin-resistant Staphylococcus aureus (anti-MRSA activity). Structure-activity relationship studies were conducted that indoloquinoline ring, benzofuroquinoline ring and 4-aminophenol group are essential structure for anti-MRSA activity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors

PubMed Central

Zhou, Nannan; Xu, Yuan; Liu, Xian; Wang, Yulan; Peng, Jianlong; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

2015-01-01

The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC50 units from measured inhibition affinities and a Pearson’s correlation coefficient R2 of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors. PMID:26110383

The Structure-Activity Relationship of the 3-Oxy Site in the Anticonvulsant (R)-N-Benzyl 2-Acetamido-3-methoxypropionamide

PubMed Central

Morieux, Pierre; Salomé, Christophe; Park, Ki Duk; Stables, James P.; Kohn, Harold

2010-01-01

Lacosamide ((R)-N-benzyl 2-acetamido-3-methoxypropionamide, (R)-1) is a low molecular weight anticonvulsant recently introduced in the United States and Europe for adjuvant treatment of partial-onset seizures in adults. In this study, we define the structure-activity relationship (SAR) for the compound's 3-oxy site. Placement of small non-polar, non-bulky substituents at the 3-oxy site provided compounds with pronounced seizure protection in the maximal electroshock (MES) seizure test with activities similar to (R)-1. The anticonvulsant activity loss that accompanied introduction of larger moieties at the 3-oxy site in (R)-1 was offset, in part, by including unsaturated groups at this position. Our findings were similar to a recently reported SAR study of the 4′-benzylamide site in (R)-1 (J. Med. Chem.2010, 53, 1288–1305). Together, these results indicate that both the 3-oxy and 4′-benzylamide positions in (R)-1 can accommodate non-bulky, hydrophobic groups and still retain pronounced anticonvulsant activities in rodents in the MES seizure model. PMID:20614888

The effects of physically active leisure on stress-health relationships.

PubMed

Iwasaki, Y; Zuzanek, J; Mannell, R C

2001-01-01

In this article, the effects of physically active leisure on the relationships between stress and health are examined using structural equation modeling (SEM). The analyses are based on data from Canada's 1994 National Population Health Survey (n = 17,626). Overall, physically active leisure was found to directly contribute to higher levels of physical health and wellbeing, and lower levels of mental ill-health among Canadians. When the respondents experienced higher levels of chronic stress, life event stress, and/or work stress, involvement in physically active leisure appeared to help them maintain good health and wellbeing. Also, higher levels of participation in physically active leisure helped paid workers suppress levels of work stress. Agencies involved in health promotion and lifestyle intervention should give greater consideration to physically active leisure. As a significant component of an active lifestyle, physically active leisure can contribute to better health, and provide a valuable resource for coping with stress.

Establishing a relationship between maximum torque production of isolated joints to simulate EVA ratchet push-pull maneuver: A case study

NASA Technical Reports Server (NTRS)

Pandya, Abhilash; Maida, James; Hasson, Scott; Greenisen, Michael; Woolford, Barbara

1993-01-01

As manned exploration of space continues, analytical evaluation of human strength characteristics is critical. These extraterrestrial environments will spawn issues of human performance which will impact the designs of tools, work spaces, and space vehicles. Computer modeling is an effective method of correlating human biomechanical and anthropometric data with models of space structures and human work spaces. The aim of this study is to provide biomechanical data from isolated joints to be utilized in a computer modeling system for calculating torque resulting from any upper extremity motions: in this study, the ratchet wrench push-pull operation (a typical extravehicular activity task). Established here are mathematical relationships used to calculate maximum torque production of isolated upper extremity joints. These relationships are a function of joint angle and joint velocity.

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%.

Exploring Solid-State Structure and Physical Properties: A Molecular and Crystal Model Exercise

ERIC Educational Resources Information Center

Bindel, Thomas H.

2008-01-01

A crystal model laboratory exercise is presented that allows students to examine relations among the microscopic-macroscopic-symbolic levels, using crystalline mineral samples and corresponding crystal models. Students explore the relationship between solid-state structure and crystal form. Other structure-property relationships are explored. The…

Predicting Rat and Human Pregnane X Receptor Activators Using Bayesian Classification Models.

PubMed

AbdulHameed, Mohamed Diwan M; Ippolito, Danielle L; Wallqvist, Anders

2016-10-17

The pregnane X receptor (PXR) is a ligand-activated transcription factor that acts as a master regulator of metabolizing enzymes and transporters. To avoid adverse drug-drug interactions and diseases such as steatosis and cancers associated with PXR activation, identifying drugs and chemicals that activate PXR is of crucial importance. In this work, we developed ligand-based predictive computational models for both rat and human PXR activation, which allowed us to identify potentially harmful chemicals and evaluate species-specific effects of a given compound. We utilized a large publicly available data set of nearly 2000 compounds screened in cell-based reporter gene assays to develop Bayesian quantitative structure-activity relationship models using physicochemical properties and structural descriptors. Our analysis showed that PXR activators tend to be hydrophobic and significantly different from nonactivators in terms of their physicochemical properties such as molecular weight, logP, number of rings, and solubility. Our Bayesian models, evaluated by using 5-fold cross-validation, displayed a sensitivity of 75% (76%), specificity of 76% (75%), and accuracy of 89% (89%) for human (rat) PXR activation. We identified structural features shared by rat and human PXR activators as well as those unique to each species. We compared rat in vitro PXR activation data to in vivo data by using DrugMatrix, a large toxicogenomics database with gene expression data obtained from rats after exposure to diverse chemicals. Although in vivo gene expression data pointed to cross-talk between nuclear receptor activators that is captured only by in vivo assays, overall we found broad agreement between in vitro and in vivo PXR activation. Thus, the models developed here serve primarily as efficient initial high-throughput in silico screens of in vitro activity.

Atom and receptor based 3D QSAR models for generating new conformations from pyrazolopyrimidine as IL-2 inducible tyrosine kinase inhibitors.

PubMed

Ul-Haq, Zaheer; Effendi, Juweria Shahrukh; Ashraf, Sajda; Bkhaitan, Majdi M

2017-06-01

In the current study, quantitative three-dimensional structure-activity-relationship (3D-QSAR) method was performed to design a model for new chemical entities by utilizing pyrazolopyrimidines. Their inhibiting activity on receptor IL-2 Itk correlates descriptors based on topology and hydrophobicity. The best model developed by ligand-based (atom-based) approach has correlation-coefficient of r 2 : 0.987 and cross-validated squared correlation-coefficient of q 2 : 0.541 with an external prediction capability of r 2 : 0.944. Whereas the best selected model developed by structured-based (receptor-based) approach has correlation-coefficient of r 2 : 0.987, cross-validated squared correlation-coefficient of q 2 : 0.637 with an external predictive ability of r 2 : 0.941. The statistical parameters prove that structure-based gave a better model to design new chemical scaffolds. The results achieved indicated that hydrophobicity at R 1 location play a vital role in the inhibitory activity and introduction of appropriately bulky and strongly hydrophobic-groups at position 3 of the terminal phenyl-group which is highly significant to enhance the activity. Six new pyrazolopyrimidine derivatives were designed. Docking simulation study was carried out and their inhibitory activity was predicted by the best structure based model with predictive activity of ranging from 8.43 to 8.85 log unit. The interacting residues PHE435, ASP500, LYS391, GLU436, MET438, CYS442, ILE369, VAL377 of PDB 4HCT were studied with respect to type of bonding with the new compounds. This study was aimed to search out more potent inhibitors of IL-2 Itk. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Modeling ready biodegradability of fragrance materials.

PubMed

Ceriani, Lidia; Papa, Ester; Kovarich, Simona; Boethling, Robert; Gramatica, Paola

2015-06-01

In the present study, quantitative structure activity relationships were developed for predicting ready biodegradability of approximately 200 heterogeneous fragrance materials. Two classification methods, classification and regression tree (CART) and k-nearest neighbors (kNN), were applied to perform the modeling. The models were validated with multiple external prediction sets, and the structural applicability domain was verified by the leverage approach. The best models had good sensitivity (internal ≥80%; external ≥68%), specificity (internal ≥80%; external 73%), and overall accuracy (≥75%). Results from the comparison with BIOWIN global models, based on group contribution method, show that specific models developed in the present study perform better in prediction than BIOWIN6, in particular for the correct classification of not readily biodegradable fragrance materials. © 2015 SETAC.

In vitro-in vivo activity relationship of substituted benzimidazole cell division inhibitors with activity against Mycobacteria tuberculosis

PubMed Central

Knudson, Susan E.; Kumar, Kunal; Awasthi, Divya; Ojima, Iwao; Slayden, Richard A.

2014-01-01

Structure based drug design was used to develop a compound library of novel 2,5,6- and 2,5,7-trisubstituted benzimidazoles. Three structural analogs, SB-P1G10, SB-P8B2 and SB-P3G2 were selected from this library based on previous studies for advanced study. In vitro studies revealed that SB-P8B2 and SB-P3G2 had sigmoidal kill-curves while in contrast SB-P1G10 showed a narrow zonal susceptibility. The in vitro studies also demonstrated that exposure to SB-P8B2 or SB-P3G2 was bactericidal, while SB-P1G10 treatment never resulted in complete killing. The dose curves for the three compounds against clinical isolates were comparable to their respective dose curves in the laboratory strain of M. tuberculosis. SB-P8B2 and SB-P3G2 exhibited antibacterial activity against non-replicating bacilli under low oxygen conditions. SB-P3G2 and SB-P1G10 were assessed in acute short-term animal models of tuberculosis, which showed that SB-P3G2 treatment demonstrated activity against M. tuberculosis. Together, these studies reveal an in vitro- in vivo relationship of the 2,5,6-trisubstituted benzimidazoles that serves as a criterion for advancing this class of cell division inhibitors into more resource intensive in vivo efficacy models such as the long-term murine model of tuberculosis and Pre-IND PK/PD studies. Specifically, these studies are the first demonstration of efficacy and an in vitro–in vivo activity relationship for 2,5,6-trisubstituted benzimidazoles. The in vivo activity presented in this manuscript substantiates this class of cell division inhibitors as having potency and efficacy against M. tuberculosis. PMID:24746463

Sedentary Screen Time and Left Ventricular Structure and Function: the CARDIA Study

PubMed Central

Gibbs, Bethany Barone; Reis, Jared P.; Schelbert, Erik B.; Craft, Lynette L.; Sidney, Steve; Lima, Joao; Lewis, Cora E.

2013-01-01

Sedentary screen time (watching TV or using a computer) predicts cardiovascular outcomes independently from moderate and vigorous physical activity and could impact left ventricular structure and function through the adverse consequences of sedentary behavior. Purpose To determine whether sedentary screen time is associated with measures of left ventricular structure and function. Methods The Coronary Artery Risk Development in Young Adults (CARDIA) Study measured screen time by questionnaire and left ventricular structure and function by echocardiography in 2,854 black and white participants, aged 43–55 years, in 2010–2011. Generalized linear models evaluated cross-sectional trends for echocardiography measures across higher categories of screen time and adjusting for demographics, smoking, alcohol, and physical activity. Further models adjusted for potential intermediate factors (blood pressure, antihypertensive medication use, diabetes, and body mass index (BMI). Results The relationship between screen time and left ventricular mass(LVM) differed in blacks vs. whites. Among whites, higher screen time was associated with larger LVM (P<0.001), after adjustment for height, demographics, and lifestyle variables. Associations between screen time and LVM persisted when adjusting for blood pressure, antihypertensive medication use, and diabetes (P=0.008) but not with additional adjustment for BMI (P=0.503). Similar relationships were observed for screen time with LVM indexed to height2.7, relative wall thickness, and mass-to-volume ratio. Screen time was not associated with left ventricular structure among blacks or left ventricular function in either race group. Conclusions Sedentary screen time is associated with greater LVM in white adults and this relationship was largely explained by higher overall adiposity. The lack of association in blacks supports a potential qualitative difference in the cardiovascular consequences of sedentary screen-based behavior. PMID:23863618

Detailed Anatomical and Electrophysiological Models of Human Atria and Torso for the Simulation of Atrial Activation

PubMed Central

Ferrer, Ana; Sebastián, Rafael; Sánchez-Quintana, Damián; Rodríguez, José F.; Godoy, Eduardo J.; Martínez, Laura; Saiz, Javier

2015-01-01

Atrial arrhythmias, and specifically atrial fibrillation (AF), induce rapid and irregular activation patterns that appear on the torso surface as abnormal P-waves in electrocardiograms and body surface potential maps (BSPM). In recent years both P-waves and the BSPM have been used to identify the mechanisms underlying AF, such as localizing ectopic foci or high-frequency rotors. However, the relationship between the activation of the different areas of the atria and the characteristics of the BSPM and P-wave signals are still far from being completely understood. In this work we developed a multi-scale framework, which combines a highly-detailed 3D atrial model and a torso model to study the relationship between atrial activation and surface signals in sinus rhythm. Using this multi scale model, it was revealed that the best places for recording P-waves are the frontal upper right and the frontal and rear left quadrants of the torso. Our results also suggest that only nine regions (of the twenty-one structures in which the atrial surface was divided) make a significant contribution to the BSPM and determine the main P-wave characteristics. PMID:26523732

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

The contributions of human factors on human error in Malaysia aviation maintenance industries

NASA Astrophysics Data System (ADS)

Padil, H.; Said, M. N.; Azizan, A.

2018-05-01

Aviation maintenance is a multitasking activity in which individuals perform varied tasks under constant pressure to meet deadlines as well as challenging work conditions. These situational characteristics combined with human factors can lead to various types of human related errors. The primary objective of this research is to develop a structural relationship model that incorporates human factors, organizational factors, and their impact on human errors in aviation maintenance. Towards that end, a questionnaire was developed which was administered to Malaysian aviation maintenance professionals. Structural Equation Modelling (SEM) approach was used in this study utilizing AMOS software. Results showed that there were a significant relationship of human factors on human errors and were tested in the model. Human factors had a partial effect on organizational factors while organizational factors had a direct and positive impact on human errors. It was also revealed that organizational factors contributed to human errors when coupled with human factors construct. This study has contributed to the advancement of knowledge on human factors effecting safety and has provided guidelines for improving human factors performance relating to aviation maintenance activities and could be used as a reference for improving safety performance in the Malaysian aviation maintenance companies.

Structure-activity relationships of seco-prezizaane and picrotoxane/picrodendrane terpenoids by Quasar receptor-surface modeling.

PubMed

Schmidt, Thomas J; Gurrath, Marion; Ozoe, Yoshihisa

2004-08-01

The seco-prezizaane-type sesquiterpenes pseudoanisatin and parviflorolide from Illicium are noncompetitive antagonists at housefly (Musca domestica) gamma-aminobutyric acid (GABA) receptors. They show selectivity toward the insect receptor and thus represent new leads toward selective insecticides. Based on the binding data for 13 seco-prezizaane terpenoids and 17 picrotoxane and picrodendrane-type terpenoids to housefly and rat GABA receptors, a QSAR study was conducted by quasi-atomistic receptor-surface modeling (Quasar). The resulting models provide insight into the structural basis of selectivity and properties of the binding sites at GABA receptor-coupled chloride channels of insects and mammals.

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.

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.

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

EPA Science Inventory

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

Discovery of novel DAPY-IAS hybrid derivatives as potential HIV-1 inhibitors using molecular hybridization based on crystallographic overlays.

PubMed

Huang, Boshi; Wang, Xueshun; Liu, Xinhao; Chen, Zihui; Li, Wanzhuo; Sun, Songkai; Liu, Huiqing; Daelemans, Dirk; De Clercq, Erik; Pannecouque, Christophe; Zhan, Peng; Liu, Xinyong

2017-08-15

Crystallographic overlap studies and pharmacophoric analysis indicated that diarylpyrimidine (DAPY)-based HIV-1 NNRTIs showed a similar binding mode and pharmacophoric features as indolylarylsulfones (IASs), another class of potent NNRTIs. Thus, a novel series of DAPY-IAS hybrid derivatives were identified as newer NNRTIs using structure-based molecular hybridization. Some target compounds exhibited moderate activities against HIV-1 IIIB strain, among which the two most potent inhibitors possessed EC 50 values of 1.48μM and 1.61μM, respectively. They were much potent than the reference drug ddI (EC 50 =76.0μM) and comparable to 3TC (EC 50 =2.54μM). Compound 7a also exhibited the favorable selectivity index (SI=80). Preliminary structure-activity relationships (SARs), structure-cytotoxicity relationships, molecular modeling studies, and in silico calculation of physicochemical properties of these new inhibitors were also discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development, Optimization and Structure-Activity Relationships of Covalent-Reversible JAK3 Inhibitors Based on a Tricyclic Imidazo[5,4-d]pyrrolo[2,3-b]pyridine Scaffold.

PubMed

Forster, Michael; Chaikuad, Apirat; Dimitrov, Teodor; Döring, Eva; Holstein, Julia; Berger, Benedict-Tilman; Gehringer, Matthias; Ghoreschi, Kamran; Müller, Susanne; Knapp, Stefan; Laufer, Stefan A

2018-05-31

Janus kinases are major drivers of immune signaling and have been the focus of anti-inflammatory drug discovery for more than a decade. Because of the invariable co-localization of JAK1 and JAK3 at cytokine receptors, the question if selective JAK3 inhibition is sufficient to effectively block downstream signaling has been highly controversial. Recently, we discovered the covalent-reversible JAK3 inhibitor FM-381 (23) featuring high isoform and kinome selectivity. Crystallography revealed that this inhibitor induces an unprecedented binding pocket by interactions of a nitrile substituent with arginine residues in JAK3. Herein we describe detailed structure activity relationships necessary for induction of the arginine pocket and the impact of this structural change on potency, isoform selectivity and efficacy in cellular models. Furthermore, we evaluated the stability of this novel inhibitor class in in vitro metabolic assays and were able to demonstrate an adequate stability of key compound 23 for in vivo use.

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

PubMed

Kumar, Ashwani; Chauhan, Shilpi

2017-01-01

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

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.

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.

Phenylquinoxalinone CFTR activator as potential prosecretory therapy for constipation

PubMed Central

CIL, ONUR; PHUAN, PUAY-WAH; SON, JUNG-HO; ZHU, JIE S.; KU, COLTON K.; TABIB, NILOUFAR AKHAVAN; TEUTHORN, ANDREW P.; FERRERA, LORETTA; ZACHOS, NICHOLAS C.; LIN, RUXIAN; GALIETTA, LUIS J. V.; DONOWITZ, MARK; KURTH, MARK J.; VERKMAN, ALAN S.

2017-01-01

Constipation is a common condition for which current treatments can have limited efficacy. By high-throughput screening, we recently identified a phenylquinoxalinone activator of the cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel that stimulated intestinal fluid secretion and normalized stool output in a mouse model of opioid-induced constipation. Here, we report phenylquinoxalinone structure-activity analysis, mechanism of action, animal efficacy data in acute and chronic models of constipation, and functional data in ex vivo primary cultured human enterocytes. Structure-activity analysis was done on 175 phenylquinoxalinone analogs, including 15 synthesized compounds. The most potent compound, CFTRact-J027, activated CFTR with EC50 ~ 200 nM, with patch-clamp analysis showing a linear CFTR current-voltage relationship with direct CFTR activation. CFTRact-J027 corrected reduced stool output and hydration in a mouse model of acute constipation produced by scopolamine and in a chronically constipated mouse strain (C3H/HeJ). Direct comparison with the approved prosecretory drugs lubiprostone and linaclotide showed substantially greater intestinal fluid secretion with CFTRact-J027, as well as greater efficacy in a constipation model. As evidence to support efficacy in human constipation, CFTRact-J027 increased transepithelial fluid transport in enteroids generated from normal human small intestine. Also, CFTRact-J027 was rapidly metabolized in vitro in human hepatic microsomes, suggesting minimal systemic exposure upon oral administration. These data establish structure-activity and mechanistic data for phenylquinoxalinone CFTR activators, and support their potential efficacy in human constipation. PMID:27815136

Structural approaches to knowledge exchange: comparing practices across five centres of excellence in public health.

PubMed

Van der Graaf, P; Francis, O; Doe, E; Barrett, E; O'Rorke, M; Docherty, G

2018-03-01

In 2008, five UKCRC Public Health Research Centres of Excellence were created to develop a coordinated approach to policy and practice engagement and knowledge exchange. The five Centres have developed their own models and practices for achieving these aims, which have not been compared in detail to date. We applied an extended version of Saner's model for the interface between science and policy to compare five case studies of knowledge exchanges, one from each centre. We compared these practices on three dimensions within our model (focus, function and type/scale) to identify barriers and facilitators for knowledge exchange. The case studies shared commonalities in their range of activities (type) but illustrated different ways of linking these activities (function). The Centres' approaches ranged from structural to more organic, and varied in the extent that they engaged internal audiences (focus). Each centre addressed policymakers at different geographical levels and scale. This article emphasizes the importance of linking a range of activities that engage policymakers at different levels, intensities and points in their decision-making processes to build relationships. Developing a structural approach to knowledge exchange activities in different contexts presents challenges of resource, implementation and evaluation.

3D-QSAR and molecular docking studies on designing inhibitors of the hepatitis C virus NS5B polymerase

NASA Astrophysics Data System (ADS)

Li, Wenlian; Si, Hongzong; Li, Yang; Ge, Cuizhu; Song, Fucheng; Ma, Xiuting; Duan, Yunbo; Zhai, Honglin

2016-08-01

Viral hepatitis C infection is one of the main causes of the hepatitis after blood transfusion and hepatitis C virus (HCV) infection is a global health threat. The HCV NS5B polymerase, an RNA dependent RNA polymerase (RdRp) and an essential role in the replication of the virus, has no functional equivalent in mammalian cells. So the research and development of efficient NS5B polymerase inhibitors provides a great strategy for antiviral therapy against HCV. A combined three-dimensional quantitative structure-activity relationship (QSAR) modeling was accomplished to profoundly understand the structure-activity correlation of a train of indole-based inhibitors of the HCV NS5B polymerase to against HCV. A comparative molecular similarity indices analysis (COMSIA) model as the foundation of the maximum common substructure alignment was developed. The optimum model exhibited statistically significant results: the cross-validated correlation coefficient q2 was 0.627 and non-cross-validated r2 value was 0.943. In addition, the results of internal validations of bootstrapping and Y-randomization confirmed the rationality and good predictive ability of the model, as well as external validation (the external predictive correlation coefficient rext2 = 0.629). The information obtained from the COMSIA contour maps enables the interpretation of their structure-activity relationship. Furthermore, the molecular docking study of the compounds for 3TYV as the protein target revealed important interactions between active compounds and amino acids, and several new potential inhibitors with higher activity predicted were designed basis on our analyses and supported by the simulation of molecular docking. Meanwhile, the OSIRIS Property Explorer was introduced to help select more satisfactory compounds. The satisfactory results from this study may lay a reliable theoretical base for drug development of hepatitis C virus NS5B polymerase inhibitors.

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

Evaluation of analgesic and anti-inflammatory activities of Rubia cordifolia L. by spectrum-effect relationships.

PubMed

Shen, Cai-Hong; Liu, Cui-Ting; Song, Xiao-Juan; Zeng, Wei-Ya; Lu, Xiao-Ying; Zheng, Zuo-Liang; Jie-Pan; Zhan, Ruo-Ting; Ping-Yan

2018-07-15

The objective of the current work was to evaluate the spectrum-effect relationships between high-performance liquid chromatography fingerprints and analgesic and anti-inflammatory effects of Rubia cordifolia L. extract (RCE), and to identify active components of RCE. Chemical fingerprints of ten batches of RC from various sources were obtained by HPLC, and similarity and hierarchical clustering analyses were carried out. Pharmacodynamic assays were performed in adjuvant-induced arthritis rat model to assess the analgesic and anti-inflammatory properties of RCE. The spectrum-effect relationships between chemical fingerprints and the analgesic and anti-inflammatory effects of RCE were established by gray correlation analysis. UPLC-ESI-MS was used to identify the structures of potential active components, by reference standards comparison. The results showed that a close correlation existed between chemical fingerprints with analgesic and anti-inflammatory activities, and alizarin, 6-hydroxyrubiadin, purpurin and rubiadin might be the active constituents of RCE. In addition, RCE attenuated pathological changes in adjuvant-induced arthritis. The current findings provide a strong basis for combining chemical fingerprints with analgesic and anti-inflammatory activities in assessing the spectrum-effect relationships of RCE. Copyright © 2018. Published by Elsevier B.V.

TOPICAL REVIEW: Protein stability and enzyme activity at extreme biological temperatures

NASA Astrophysics Data System (ADS)

Feller, Georges

2010-08-01

Psychrophilic microorganisms thrive in permanently cold environments, even at subzero temperatures. To maintain metabolic rates compatible with sustained life, they have improved the dynamics of their protein structures, thereby enabling appropriate molecular motions required for biological activity at low temperatures. As a consequence of this structural flexibility, psychrophilic proteins are unstable and heat-labile. In the upper range of biological temperatures, thermophiles and hyperthermophiles grow at temperatures > 100 °C and synthesize ultra-stable proteins. However, thermophilic enzymes are nearly inactive at room temperature as a result of their compactness and rigidity. At the molecular level, both types of extremophilic proteins have adapted the same structural factors, but in opposite directions, to address either activity at low temperatures or stability in hot environments. A model based on folding funnels is proposed accounting for the stability-activity relationships in extremophilic proteins.

Representation of molecular structure using quantum topology with inductive logic programming in structure-activity relationships.

PubMed

Buttingsrud, Bård; Ryeng, Einar; King, Ross D; Alsberg, Bjørn K

2006-06-01

The requirement of aligning each individual molecule in a data set severely limits the type of molecules which can be analysed with traditional structure activity relationship (SAR) methods. A method which solves this problem by using relations between objects is inductive logic programming (ILP). Another advantage of this methodology is its ability to include background knowledge as 1st-order logic. However, previous molecular ILP representations have not been effective in describing the electronic structure of molecules. We present a more unified and comprehensive representation based on Richard Bader's quantum topological atoms in molecules (AIM) theory where critical points in the electron density are connected through a network. AIM theory provides a wealth of chemical information about individual atoms and their bond connections enabling a more flexible and chemically relevant representation. To obtain even more relevant rules with higher coverage, we apply manual postprocessing and interpretation of ILP rules. We have tested the usefulness of the new representation in SAR modelling on classifying compounds of low/high mutagenicity and on a set of factor Xa inhibitors of high and low affinity.

Relationships between structure, process and outcome to assess quality of integrated chronic disease management in a rural South African setting: applying a structural equation model.

PubMed

Ameh, Soter; Gómez-Olivé, Francesc Xavier; Kahn, Kathleen; Tollman, Stephen M; Klipstein-Grobusch, Kerstin

2017-03-23

South Africa faces a complex dual burden of chronic communicable and non-communicable diseases (NCDs). In response, the Integrated Chronic Disease Management (ICDM) model was initiated in primary health care (PHC) facilities in 2011 to leverage the HIV/ART programme to scale-up services for NCDs, achieve optimal patient health outcomes and improve the quality of medical care. However, little is known about the quality of care in the ICDM model. The objectives of this study were to: i) assess patients' and operational managers' satisfaction with the dimensions of ICDM services; and ii) evaluate the quality of care in the ICDM model using Avedis Donabedian's theory of relationships between structure (resources), process (clinical activities) and outcome (desired result of healthcare) constructs as a measure of quality of care. A cross-sectional study was conducted in 2013 in seven PHC facilities in the Bushbuckridge municipality of Mpumalanga Province, north-east South Africa - an area underpinned by a robust Health and Demographic Surveillance System (HDSS). The patient satisfaction questionnaire (PSQ-18), with measures reflecting structure/process/outcome (SPO) constructs, was adapted and administered to 435 chronic disease patients and the operational managers of all seven PHC facilities. The adapted questionnaire contained 17 dimensions of care, including eight dimensions identified as priority areas in the ICDM model - critical drugs, equipment, referral, defaulter tracing, prepacking of medicines, clinic appointments, waiting time, and coherence. A structural equation model was fit to operationalise Donabedian's theory, using unidirectional, mediation, and reciprocal pathways. The mediation pathway showed that the relationships between structure, process and outcome represented quality systems in the ICDM model. Structure correlated with process (0.40) and outcome (0.75). Given structure, process correlated with outcome (0.88). Of the 17 dimensions of care in the ICDM model, three structure (equipment, critical drugs, accessibility), three process (professionalism, friendliness and attendance to patients) and three outcome (competence, confidence and coherence) dimensions reflected their intended constructs. Of the priority dimensions, referrals, defaulter tracing, prepacking of medicines, appointments, and patient waiting time did not reflect their intended constructs. Donabedian's theoretical framework can be used to provide evidence of quality systems in the ICDM model.

Modeling the Prospective Relationships of Impairment, Injury Severity, and Participation to Quality of Life Following Traumatic Brain Injury

PubMed Central

Kalpinski, Ryan J.; Williamson, Meredith L. C.; Elliott, Timothy R.; Berry, Jack W.; Underhill, Andrea T.; Fine, Philip R.

2013-01-01

Identifying reliable predictors of positive adjustment following traumatic brain injury (TBI) remains an important area of inquiry. Unfortunately, much of available research examines direct relationships between predictor variables and outcomes without attending to the contextual relationships that can exist between predictor variables. Relying on theoretical models of well-being, we examined a theoretical model of adjustment in which the capacity to engage in intentional activities would be prospectively associated with greater participation, which in turn would predict subsequent life satisfaction and perceived health assessed at a later time. Structural equation modeling of data collected from 312 individuals (226 men, 86 women) with TBI revealed that two elements of participation—mobility and occupational activities—mediated the prospective influence of functional independence and injury severity to optimal adjustment 60 months following medical discharge for TBI. The model accounted for 21% of the variance in life satisfaction and 23% of the variance in self-rated health. Results indicate that the effects of functional independence and injury severity to optimal adjustment over time may be best understood in the context of participation in meaningful, productive activities. Implications for theoretical models of well-being and for clinical interventions that promote adjustmentafter TBI are discussed. PMID:24199186

QSAR and docking studies on xanthone derivatives for anticancer activity targeting DNA topoisomerase IIα

PubMed Central

Alam, Sarfaraz; Khan, Feroz

2014-01-01

Due to the high mortality rate in India, the identification of novel molecules is important in the development of novel and potent anticancer drugs. Xanthones are natural constituents of plants in the families Bonnetiaceae and Clusiaceae, and comprise oxygenated heterocycles with a variety of biological activities along with an anticancer effect. To explore the anticancer compounds from xanthone derivatives, a quantitative structure activity relationship (QSAR) model was developed by the multiple linear regression method. The structure–activity relationship represented by the QSAR model yielded a high activity–descriptors relationship accuracy (84%) referred by regression coefficient (r2=0.84) and a high activity prediction accuracy (82%). Five molecular descriptors – dielectric energy, group count (hydroxyl), LogP (the logarithm of the partition coefficient between n-octanol and water), shape index basic (order 3), and the solvent-accessible surface area – were significantly correlated with anticancer activity. Using this QSAR model, a set of virtually designed xanthone derivatives was screened out. A molecular docking study was also carried out to predict the molecular interaction between proposed compounds and deoxyribonucleic acid (DNA) topoisomerase IIα. The pharmacokinetics parameters, such as absorption, distribution, metabolism, excretion, and toxicity, were also calculated, and later an appraisal of synthetic accessibility of organic compounds was carried out. The strategy used in this study may provide understanding in designing novel DNA topoisomerase IIα inhibitors, as well as for other cancer targets. PMID:24516330

Using Theoretical Descriptions in Structure Activity Relations. 3. Electronic Descriptors

DTIC Science & Technology

1988-08-01

Activity Relationships (QSAR) have been used successfully in the past to develop predictive equations for several biological and physical properties...Linear Free Energy Relationships (,FF.3) and is based on work by Hammet in which he derived electronic descriptors for the dissociation of substituted...structure of a compound and its activity in a system. Several different structural descriptors have been used in QSAR equations . These range from

Structure-activity models of oral clearance, cytotoxicity, and LD50: a screen for promising anticancer compounds

PubMed Central

Boik, John C; Newman, Robert A

2008-01-01

Background Quantitative structure-activity relationship (QSAR) models have become popular tools to help identify promising lead compounds in anticancer drug development. Few QSAR studies have investigated multitask learning, however. Multitask learning is an approach that allows distinct but related data sets to be used in training. In this paper, a suite of three QSAR models is developed to identify compounds that are likely to (a) exhibit cytotoxic behavior against cancer cells, (b) exhibit high rat LD50 values (low systemic toxicity), and (c) exhibit low to modest human oral clearance (favorable pharmacokinetic characteristics). Models were constructed using Kernel Multitask Latent Analysis (KMLA), an approach that can effectively handle a large number of correlated data features, nonlinear relationships between features and responses, and multitask learning. Multitask learning is particularly useful when the number of available training records is small relative to the number of features, as was the case with the oral clearance data. Results Multitask learning modestly but significantly improved the classification precision for the oral clearance model. For the cytotoxicity model, which was constructed using a large number of records, multitask learning did not affect precision but did reduce computation time. The models developed here were used to predict activities for 115,000 natural compounds. Hundreds of natural compounds, particularly in the anthraquinone and flavonoids groups, were predicted to be cytotoxic, have high LD50 values, and have low to moderate oral clearance. Conclusion Multitask learning can be useful in some QSAR models. A suite of QSAR models was constructed and used to screen a large drug library for compounds likely to be cytotoxic to multiple cancer cell lines in vitro, have low systemic toxicity in rats, and have favorable pharmacokinetic properties in humans. PMID:18554402

Structure-activity models of oral clearance, cytotoxicity, and LD50: a screen for promising anticancer compounds.

PubMed

Boik, John C; Newman, Robert A

2008-06-13

Quantitative structure-activity relationship (QSAR) models have become popular tools to help identify promising lead compounds in anticancer drug development. Few QSAR studies have investigated multitask learning, however. Multitask learning is an approach that allows distinct but related data sets to be used in training. In this paper, a suite of three QSAR models is developed to identify compounds that are likely to (a) exhibit cytotoxic behavior against cancer cells, (b) exhibit high rat LD50 values (low systemic toxicity), and (c) exhibit low to modest human oral clearance (favorable pharmacokinetic characteristics). Models were constructed using Kernel Multitask Latent Analysis (KMLA), an approach that can effectively handle a large number of correlated data features, nonlinear relationships between features and responses, and multitask learning. Multitask learning is particularly useful when the number of available training records is small relative to the number of features, as was the case with the oral clearance data. Multitask learning modestly but significantly improved the classification precision for the oral clearance model. For the cytotoxicity model, which was constructed using a large number of records, multitask learning did not affect precision but did reduce computation time. The models developed here were used to predict activities for 115,000 natural compounds. Hundreds of natural compounds, particularly in the anthraquinone and flavonoids groups, were predicted to be cytotoxic, have high LD50 values, and have low to moderate oral clearance. Multitask learning can be useful in some QSAR models. A suite of QSAR models was constructed and used to screen a large drug library for compounds likely to be cytotoxic to multiple cancer cell lines in vitro, have low systemic toxicity in rats, and have favorable pharmacokinetic properties in humans.

Connectome Signatures of Neurocognitive Abnormalities in Euthymic Bipolar I Disorder

PubMed Central

Ajilore, Olusola; Vizueta, Nathalie; Walshaw, Patricia; Zhan, Liang; Leow, Alex; Altshuler, Lori L.

2015-01-01

Objectives Connectomics have allowed researchers to study integrative patterns of neural connectivity in humans. Yet, it is unclear how connectomics may elucidate structure-function relationships in bipolar I disorder (BPI). Expanding on our previous structural connectome study, here we used an overlapping sample with additional psychometric and fMRI data to relate structural connectome properties to both fMRI signals and cognitive performance. Methods 42 subjects completed a neuropsychological (NP) battery covering domains of processing speed, verbal memory, working memory, and cognitive flexibility. 32 subjects also had fMRI data performing a Go/NoGo task. Results Bipolar participants had lower NP performance across all domains, but only working memory reached statistical significance. In BPI participants, processing speed was significantly associated with both white matter integrity (WMI) in the corpus callosum and interhemispheric network integration. Mediation models further revealed that the relationship between interhemispheric integration and processing speed was mediated by WMI, and processing speed mediated the relationship between WMI and working memory. Bipolar subjects had significantly decreased BA47 activation during NoGo vs. Go. Significant predictors of BA47 fMRI activations during the Go/NoGo task were its nodal path length (left hemisphere) and its nodal clustering coefficient (right hemisphere). Conclusions This study suggests that structural connectome changes underlie abnormalities in fMRI activation and cognitive performance in euthymic BPI subjects. Results support that BA47 structural connectome changes may be a trait marker for BPI. Future studies are needed to determine if these “connectome signatures” may also confer a biological risk and/or serve as predictors of relapse. PMID:26228398

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.

Space-time evolution of a growth fold (Betic Cordillera, Spain). Evidences from 3D geometrical modelling

NASA Astrophysics Data System (ADS)

Martin-Rojas, Ivan; Alfaro, Pedro; Estévez, Antonio

2014-05-01

We present a study that encompasses several software tools (iGIS©, ArcGIS©, Autocad©, etc.) and data (geological mapping, high resolution digital topographic data, high resolution aerial photographs, etc.) to create a detailed 3D geometric model of an active fault propagation growth fold. This 3D model clearly shows structural features of the analysed fold, as well as growth relationships and sedimentary patterns. The results obtained permit us to discuss the kinematics and structural evolution of the fold and the fault in time and space. The study fault propagation fold is the Crevillente syncline. This fold represents the northern limit of the Bajo Segura Basin, an intermontane basin in the Eastern Betic Cordillera (SE Spain) developed from upper Miocene on. 3D features of the Crevillente syncline, including growth pattern, indicate that limb rotation and, consequently, fault activity was higher during Messinian than during Tortonian; consequently, fault activity was also higher. From Pliocene on our data point that limb rotation and fault activity steadies or probably decreases. This in time evolution of the Crevillente syncline is not the same all along the structure; actually the 3D geometric model indicates that observed lateral heterogeneity is related to along strike variation of fault displacement.

From surprise to cognition: Some effects of the structure of C.A.L. simulation programs on the cognitive and scientific activities of young adults

NASA Astrophysics Data System (ADS)

Dicker, R. J.

The main objective of this thesis is to describe the effect on cognition of the structure of CAL simulation programs used, in science teaching. Four programs simulating a pond ecosystem were written so as to present a simulation model and to assist in cognition in different ways. Various clinically detailed methods of describing learning were developed and tried including concept maps which were found to be sammative rather than formative descriptions of learning, and to be ambiguous) and hierarchical structures (which were found to be difficult to produce). Fran these concept maps and hierarchical structures I developed my Interaction Model of Learning which can be used to describe the chronological events concerned with cognition. Using the Interaction Model, the nature of cognition and the effect that CAL program structure has on this process is described. Various scenarios are presented as a means of showing the possible effects of program structure on learning. Four forms of concept learning activity and their relationship to learning valid and alternative conceptions are described. The findings from the study are particularly related to the work of Driver (1983), Marton (1976) and Entwistle (1981).

MOLECULAR INTERACTION POTENTIALS FOR THE DEVELOPMENT OF STRUCTURE-ACTIVITY RELATIONSHIPS

EPA Science Inventory

Abstract
One reasonable approach to the analysis of the relationships between molecular structure and toxic activity is through the investigation of the forces and intermolecular interactions responsible for chemical toxicity. The interaction between the xenobiotic and the bio...

Upper extremity function in stroke subjects: relationships between the international classification of functioning, disability, and health domains.

PubMed

Faria-Fortini, Iza; Michaelsen, Stella Maris; Cassiano, Janine Gomes; Teixeira-Salmela, Luci Fuscaldi

2011-01-01

Upper limb (UL) impairments are the most common disabling deficits after stroke and have complex relationships with activity and participation domains. However, relatively few studies have applied the ICF model to identify the contributions of specific UL impairments, such as muscular weakness, pain, and sensory loss, as predictors of activity and participation. The purposes of this predictive study were to evaluate the relationships between UL variables related to body functions/structures, activity, and participation domains and to determine which would best explain activity and participation with 55 subjects with chronic stroke. Body functions/structures were assessed by measures of grip, pinch, and UL strength, finger tactile sensations, shoulder pain, and cognition (MMSE); activity domain by measures of observed performance (BBT, NHPT, and TEMPA); and participation by measures of quality of life (SSQOL). Upper-limb and grip strength were related to all activity measures (0.52

Interaction of phenolic acids and their derivatives with human serum albumin: Structure-affinity relationships and effects on antioxidant activity.

PubMed

Zhang, Yunyue; Wu, Simin; Qin, Yinghui; Liu, Jiaxin; Liu, Jingwen; Wang, Qingyu; Ren, Fazheng; Zhang, Hao

2018-02-01

In this study, 111 phenolic acids and their derivatives were chosen to investigate their structure-affinity relationships when binding to human serum albumin (HSA), and effects on their antioxidant activity. A comprehensive mathematical model was employed to calculate the binding constants, using a fluorescence quenching method, and this was corrected for the inner-filter effect to improve accuracy. We found that a hydroxy group at the 2-position of the benzene ring exerted a positive effect on the affinities, while a 4-hydroxy substituent had a negative influence. Both methylation of the hydroxy groups and replacing the hydroxy groups with methyl groups at the 3- and 4-positions of the benzene ring enhanced the binding affinities. Hydrophobic force and hydrogen bonding were binding forces for the phenolic acids, and their methyl esters, respectively. The antioxidant activity of the HSA-phenolic acid interaction compounds was higher than that of the phenolic acids alone. Copyright © 2017. Published by Elsevier Ltd.

A measurement error model for physical activity level as measured by a questionnaire with application to the 1999-2006 NHANES questionnaire.

PubMed

Tooze, Janet A; Troiano, Richard P; Carroll, Raymond J; Moshfegh, Alanna J; Freedman, Laurence S

2013-06-01

Systematic investigations into the structure of measurement error of physical activity questionnaires are lacking. We propose a measurement error model for a physical activity questionnaire that uses physical activity level (the ratio of total energy expenditure to basal energy expenditure) to relate questionnaire-based reports of physical activity level to true physical activity levels. The 1999-2006 National Health and Nutrition Examination Survey physical activity questionnaire was administered to 433 participants aged 40-69 years in the Observing Protein and Energy Nutrition (OPEN) Study (Maryland, 1999-2000). Valid estimates of participants' total energy expenditure were also available from doubly labeled water, and basal energy expenditure was estimated from an equation; the ratio of those measures estimated true physical activity level ("truth"). We present a measurement error model that accommodates the mixture of errors that arise from assuming a classical measurement error model for doubly labeled water and a Berkson error model for the equation used to estimate basal energy expenditure. The method was then applied to the OPEN Study. Correlations between the questionnaire-based physical activity level and truth were modest (r = 0.32-0.41); attenuation factors (0.43-0.73) indicate that the use of questionnaire-based physical activity level would lead to attenuated estimates of effect size. Results suggest that sample sizes for estimating relationships between physical activity level and disease should be inflated, and that regression calibration can be used to provide measurement error-adjusted estimates of relationships between physical activity and disease.

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.

Sport Participation and Metabolic Risk During Adolescent Years: A Structured Equation Model.

PubMed

Werneck, AndréOliveira; da Silva, Danilo Rodrigues Pereira; Fernandes, Rômulo Araújo; Ronque, EnioRicardoVaz; Coelho-E-Silva, Manuel J; Cyrino, Edilson Serpeloni

2018-06-21

Sports practice during childhood can influence health indicators in later ages through direct and indirect pathways. Thus, this study aimed to test direct and indirect pathways to the association between sports practice in childhood and metabolic risk in adolescence, adopting physical activity, adiposity, and cardiorespiratory fitness at adolescence as potential mediators. This cross-sectional study with retrospective information was conducted with 991 adolescents (579 girls, 412 boys) aged 10 to 16 y. Sports activity was self-reported in childhood (retrospective data) and physical activity evaluated in adolescence through questionnaires. Somatic maturation (Mirwald method), cardiorespiratory fitness (20-m shuttle-run test), body fat (skinfolds), waist circumference, blood pressure (automatic instrument) and blood variables (fasting glucose, HDL cholesterol, and triglycerides) were measured at adolescence. Waist circumference, blood pressure and blood variables composed the metabolic risk score. Structured equation modeling was adopted. In both sexes, the relationship between sports practice at childhood and metabolic risk was fully mediated by habitual physical activity, which is related to the obesity construct and cardiorespiratory fitness. Obesity was associated with metabolic risk in boys (β=0.062; p<0.001) and girls (β=0.047; p<0.001). The relationship between sports practice in childhood and metabolic risk in adolescence was mediated by physical activity, obesity, and cardiorespiratory fitness. © Georg Thieme Verlag KG Stuttgart · New York.

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...

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...

In-silico structure activity relationship study of toxicity endpoints by QSAR modeling (SOT)

EPA Science Inventory

Several thousand chemicals were tested in 700 toxicity-related in-vitro HTS bioassays through the EPA’s ToxCast and Tox21 projects. This chemical set only covers a portion of the chemical space of interest for environmental exposure, leading to a need to fill data gaps with alter...

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.

Perceived sports competence mediates the relationship between childhood motor skill proficiency and adolescent physical activity and fitness: a longitudinal assessment.

PubMed

Barnett, Lisa M; Morgan, Philip J; van Beurden, Eric; Beard, John R

2008-08-08

The purpose of this paper was to investigate whether perceived sports competence mediates the relationship between childhood motor skill proficiency and subsequent adolescent physical activity and fitness. In 2000, children's motor skill proficiency was assessed as part of a school-based physical activity intervention. In 2006/07, participants were followed up as part of the Physical Activity and Skills Study and completed assessments for perceived sports competence (Physical Self-Perception Profile), physical activity (Adolescent Physical Activity Recall Questionnaire) and cardiorespiratory fitness (Multistage Fitness Test). Structural equation modelling techniques were used to determine whether perceived sports competence mediated between childhood object control skill proficiency (composite score of kick, catch and overhand throw), and subsequent adolescent self-reported time in moderate-to-vigorous physical activity and cardiorespiratory fitness. Of 928 original intervention participants, 481 were located in 28 schools and 276 (57%) were assessed with at least one follow-up measure. Slightly more than half were female (52.4%) with a mean age of 16.4 years (range 14.2 to 18.3 yrs). Relevant assessments were completed by 250 (90.6%) students for the Physical Activity Model and 227 (82.3%) for the Fitness Model. Both hypothesised mediation models had a good fit to the observed data, with the Physical Activity Model accounting for 18% (R2 = 0.18) of physical activity variance and the Fitness Model accounting for 30% (R2 = 0.30) of fitness variance. Sex did not act as a moderator in either model. Developing a high perceived sports competence through object control skill development in childhood is important for both boys and girls in determining adolescent physical activity participation and fitness. Our findings highlight the need for interventions to target and improve the perceived sports competence of youth.

A structural model of treatment program and individual counselor leadership in innovation transfer.

PubMed

Joe, George W; Becan, Jennifer E; Knight, Danica K; Flynn, Patrick M

2017-03-23

A number of program-level and counselor-level factors are known to impact the adoption of treatment innovations. While program leadership is considered a primary factor, the importance of leadership among clinical staff to innovation transfer is less known. Objectives included explore (1) the influence of two leadership roles, program director and individual counselor, on recent training activity and (2) the relationship of counselor attributes on training endorsement. The sample included 301 clinical staff in 49 treatment programs. A structural equation model was evaluated for key hypothesized relationships between exogenous and endogenous variables related to the two leadership roles. The importance of organizational leadership, climate, and counselor attributes (particularly counseling innovation interest and influence) to recent training activity was supported. In a subset of 68 counselors who attended a developer-led training on a new intervention, it was found that training endorsement was higher among those with high innovation interest and influence. The findings suggest that each leadership level impacts the organization in different ways, yet both can promote or impede technology transfer.

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.

Synthetic polyester-hydrolyzing enzymes from thermophilic actinomycetes.

PubMed

Wei, Ren; Oeser, Thorsten; Zimmermann, Wolfgang

2014-01-01

Thermophilic actinomycetes produce enzymes capable of hydrolyzing synthetic polyesters such as polyethylene terephthalate (PET). In addition to carboxylesterases, which have hydrolytic activity predominantly against PET oligomers, esterases related to cutinases also hydrolyze synthetic polymers. The production of these enzymes by actinomycetes as well as their recombinant expression in heterologous hosts is described and their catalytic activity against polyester substrates is compared. Assays to analyze the enzymatic hydrolysis of synthetic polyesters are evaluated, and a kinetic model describing the enzymatic heterogeneous hydrolysis process is discussed. Structure-function and structure-stability relationships of actinomycete polyester hydrolases are compared based on molecular dynamics simulations and recently solved protein structures. In addition, recent progress in enhancing their activity and thermal stability by random or site-directed mutagenesis is presented. © 2014 Elsevier Inc. All rights reserved.

Topological pattern for the search of new active drugs against methicillin resistant Staphylococcus aureus.

PubMed

Bueso-Bordils, Jose I; Perez-Gracia, Maria T; Suay-Garcia, Beatriz; Duart, Maria J; Martin Algarra, Rafael V; Lahuerta Zamora, Luis; Anton-Fos, Gerardo M; Aleman Lopez, Pedro A

2017-09-29

Molecular topology was used to develop a mathematical model capable of classifying compounds according to antimicrobial activity against methicillin resistant Staphylococcus aureus (MRSA). Topological indices were used as structural descriptors and their relation to antimicrobial activity was determined by using linear discriminant analysis. This topological model establishes new structure activity relationships which show that the presence of cyclopropyl, chlorine and ramification pairs at a distance of two bonds favor this activity, while the presence of tertiary amines decreases it. This model was applied to a combinatorial library of a thousand and one 6-fluoroquinolones, from which 117 theoretical active molecules were obtained. The compound 10 and five new quinolones were tested against MRSA. They all showed some activity against MRSA, although compounds 6, 8 and 9 showed anti-MRSA activity similar to ciprofloxacin. This model was also applied to 263 theoretical antibacterial agents described by us in a previous work, from which 34 were predicted as theoretically active. Anti-MRSA activity was found bibliographically in 9 of them (ensuring at least 26% of success), and from the rest, 3 compounds were randomly chosen and tested, finding mitomycin C to be more active than ciprofloxacin. The results demonstrate the utility of the molecular topology approaches for identifying new drugs active against MRSA. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

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.

Investigating Supervisory Relationships and Therapeutic Alliances Using Structural Equation Modeling

ERIC Educational Resources Information Center

DePue, Mary Kristina; Lambie, Glenn W.; Liu, Ren; Gonzalez, Jessica

2016-01-01

The authors used structural equation modeling to examine the contribution of supervisees' supervisory relationship levels to therapeutic alliance (TA) scores with their clients in practicum. Results showed that supervisory relationship scores positively contributed to the TA. Client and counselor ratings of the TA also differed.

Small Molecule Anticonvulsant Agents with Potent In Vitro Neuroprotection

PubMed Central

Smith, Garry R.; Zhang, Yan; Du, Yanming; Kondaveeti, Sandeep K.; Zdilla, Michael J.; Reitz, Allen B.

2012-01-01

Severe seizure activity is associated with recurring cycles of excitotoxicity and oxidative stress that result in progressive neuronal damage and death. Intervention to halt these pathological processes is a compelling disease-modifying strategy for the treatment of seizure disorders. In the present study, a core small molecule with anticonvulsant activity has been structurally optimized for neuroprotection. Phenotypic screening of rat hippocampal cultures with nutrient medium depleted of antioxidants was utilized as a disease model. Increased cell death and decreased neuronal viability produced by acute treatment with glutamate or hydrogen peroxide were prevented by our novel molecules. The neuroprotection associated with this chemical series has marked structure activity relationships that focus on modification of the benzylic position of a 2-phenyl-2-hydroxyethyl sulfamide core structure. Complete separation between anticonvulsant activity and neuroprotective action was dependent on substitution at the benzylic carbon. Chiral selectivity was evident in that the S-enantiomer of the benzylic hydroxy group had neither neuroprotective nor anticonvulsant activity, while the R-enantiomer of the lead compound had full neuroprotective action at ≤40 nM and antiseizure activity in three animal models. These studies indicate that potent, multifunctional neuroprotective anticonvulsants are feasible within a single molecular entity. PMID:22535312

Noscapinoids with anti-cancer activity against human acute lymphoblastic leukemia cells (CEM): a three dimensional chemical space pharmacophore modeling and electronic feature analysis.

PubMed

Naik, Pradeep K; Santoshi, Seneha; Joshi, Harish C

2012-01-01

We have identified a new class of microtubule-binding compounds-noscapinoids-that alter microtubule dynamics at stoichiometric concentrations without affecting tubulin polymer mass. Noscapinoids show great promise as chemotherapeutic agents for the treatment of human cancers. To investigate the structural determinants of noscapinoids responsible for anti-cancer activity, we tested 36 structurally diverse noscapinoids in human acute lymphoblastic leukemia cells (CEM). The IC(50) values of these noscapinoids vary from 1.2 to 56.0 μM. Pharmacophore models of anti-cancer activity were generated that identify two hydrogen bond acceptors, two aromatic rings, two hydrophobic groups, and one positively charged group as essential structural features. Additionally, an atom-based quantitative structure-activity relationship (QSAR) model was developed that gave a statistically satisfying result (R(2) = 0.912, Q(2) = 0.908, Pearson R = 0.951) and effectively predicts the anti-cancer activity of training and test set compounds. The pharmacophore model presented here is well supported by electronic property analysis using density functional theory at B3LYP/3-21*G level. Molecular electrostatic potential, particularly localization of negative potential near oxygen atoms of the dimethoxy isobenzofuranone ring of active compounds, matched the hydrogen bond acceptor feature of the generated pharmacophore. Our results further reveal that all active compounds have smaller lowest unoccupied molecular orbital (LUMO) energies concentrated over the dimethoxy isobenzofuranone ring, azido group, and nitro group, which is indicative of the electron acceptor capacity of the compounds. Results obtained from this study will be useful in the efficient design and development of more active noscapinoids.

STRUCTURE-ACTIVITY RELATIONSHIPS (SARS) AMONG MUTAGENS AND CARCINOGENS: A REVIEW

EPA Science Inventory

The review is an introduction to methods for evaluating structure-activity relationships (SARs), and, in particular, to those methods that have been applied to study mutagenicity and carcinogenicity. A brief history and some background material on the earliest attempts to correla...

QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS FOR CHEMICAL REDUCTIONS OF ORGANIC CONTAMINANTS

EPA Science Inventory

Sufficient kinetic data on abiotic reduction reactions involving organic contaminants are now available that quantitative structure-activity relationships (QSARs) for these reactions can be developed. Over 50 QSARs have been reported, most in just the last few years, and they ar...

Clustered multistate models with observation level random effects, mover-stayer effects and dynamic covariates: modelling transition intensities and sojourn times in a study of psoriatic arthritis.

PubMed

Yiu, Sean; Farewell, Vernon T; Tom, Brian D M

2018-02-01

In psoriatic arthritis, it is important to understand the joint activity (represented by swelling and pain) and damage processes because both are related to severe physical disability. The paper aims to provide a comprehensive investigation into both processes occurring over time, in particular their relationship, by specifying a joint multistate model at the individual hand joint level, which also accounts for many of their important features. As there are multiple hand joints, such an analysis will be based on the use of clustered multistate models. Here we consider an observation level random-effects structure with dynamic covariates and allow for the possibility that a subpopulation of patients is at minimal risk of damage. Such an analysis is found to provide further understanding of the activity-damage relationship beyond that provided by previous analyses. Consideration is also given to the modelling of mean sojourn times and jump probabilities. In particular, a novel model parameterization which allows easily interpretable covariate effects to act on these quantities is proposed.

Modeling Liver-Related Adverse Effects of Drugs Using kNN QSAR Method

PubMed Central

Rodgers, Amie D.; Zhu, Hao; Fourches, Dennis; Rusyn, Ivan; Tropsha, Alexander

2010-01-01

Adverse effects of drugs (AEDs) continue to be a major cause of drug withdrawals both in development and post-marketing. While liver-related AEDs are a major concern for drug safety, there are few in silico models for predicting human liver toxicity for drug candidates. We have applied the Quantitative Structure Activity Relationship (QSAR) approach to model liver AEDs. In this study, we aimed to construct a QSAR model capable of binary classification (active vs. inactive) of drugs for liver AEDs based on chemical structure. To build QSAR models, we have employed an FDA spontaneous reporting database of human liver AEDs (elevations in activity of serum liver enzymes), which contains data on approximately 500 approved drugs. Approximately 200 compounds with wide clinical data coverage, structural similarity and balanced (40/60) active/inactive ratio were selected for modeling and divided into multiple training/test and external validation sets. QSAR models were developed using the k nearest neighbor method and validated using external datasets. Models with high sensitivity (>73%) and specificity (>94%) for prediction of liver AEDs in external validation sets were developed. To test applicability of the models, three chemical databases (World Drug Index, Prestwick Chemical Library, and Biowisdom Liver Intelligence Module) were screened in silico and the validity of predictions was determined, where possible, by comparing model-based classification with assertions in publicly available literature. Validated QSAR models of liver AEDs based on the data from the FDA spontaneous reporting system can be employed as sensitive and specific predictors of AEDs in pre-clinical screening of drug candidates for potential hepatotoxicity in humans. PMID:20192250

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

NASA Astrophysics Data System (ADS)

Krein, Michael

After decades of development and use in a variety of application areas, Quantitative Structure Property Relationships (QSPRs) and related descriptor-based statistical learning methods have achieved a level of infamy due to their misuse. The field is rife with past examples of overtrained models, overoptimistic performance assessment, and outright cheating in the form of explicitly removing data to fit models. These actions do not serve the community well, nor are they beneficial to future predictions based on established models. In practice, in order to select combinations of descriptors and machine learning methods that might work best, one must consider the nature and size of the training and test datasets, be aware of existing hypotheses about the data, and resist the temptation to bias structure representation and modeling to explicitly fit the hypotheses. The definition and application of these best practices is important for obtaining actionable modeling outcomes, and for setting user expectations of modeling accuracy when predicting the endpoint values of unknowns. A wide variety of statistical learning approaches, descriptor types, and model validation strategies are explored herein, with the goals of helping end users understand the factors involved in creating and using QSPR models effectively, and to better understand relationships within the data, especially by looking at the problem space from multiple perspectives. Molecular relationships are commonly envisioned in a continuous high-dimensional space of numerical descriptors, referred to as chemistry space. Descriptor and similarity metric choice influence the partitioning of this space into regions corresponding to local structural similarity. These regions, known as domains of applicability, are most likely to be successfully modeled by a QSPR. In Chapter 2, the network topology and scaling relationships of several chemistry spaces are thoroughly investigated. Chemistry spaces studied include the ZINC data set, a qHTS PubChem bioassay, as well as the protein binding sites from the PDB. The characteristics of these networks are compared and contrasted with those of the bioassay Structure Activity Landscape Index (SALI) subnetwork, which maps discontinuities or cliffs in the structure activity landscape. Mapping this newly generated information over underlying chemistry space networks generated using different descriptors demonstrates local modeling capacity and can guide the choice of better local representations of chemistry space. Chapter 2 introduces and demonstrates this novel concept, which also enables future work in visualization and interpretation of chemical spaces. Initially, it was discovered that there were no community-available tools to leverage best-practice ideas to comprehensively build, compare, and interpret QSPRs. The Yet Another Modeling System (YAMS) tool performs a series of balanced, rational decisions in dataset preprocessing and parameter/feature selection over a choice of modeling methods. To date, YAMS is the only community-available informatics tool that performs such decisions consistently between methods while also providing multiple model performance comparisons and detailed descriptor importance information. The focus of the tool is thus to convey rich information about model quality and predictions that help to "close the loop" between modeling and experimental efforts, for example, in tailoring nanocomposite properties. Polymer nanocomposites (PNC) are complex material systems encompassing many potential structures, chemistries, and self assembled morphologies that could significantly impact commercial and military applications. There is a strong desire to characterize and understand the tradespace of nanocomposites, to identify the important factors relating nanostructure to materials properties and determine an effective way to control materials properties at the manufacturing scale. Due to the complexity of the systems, existing design approaches rely heavily on trial-and-error learning. By leveraging existing experimental data, Materials Quantitative Structure-Property Relationships (MQSPRs) relate molecular structures to the polar and dispersive components of corresponding surface tensions. In turn, existing theories relate polymer and nanofiller polar and dispersive surface tension components to the dispersion state and interfacial polymer relaxation times. These quantities may, in the future, be used as input to continuum mechanics approaches shown able to predict the thermomechanical response of nanocomposites. For a polymer dataset and a particle dataset, multiple structural representations and descriptor sets are benchmarked, including a set of high performance surface-property descriptors developed as part of this work. The systematic variation of structural representations as part of the informatics approach reveals important insight in modeling polymers, and should become common practice when defining new problem spaces.

Perceived Social Relationships and Science Learning Outcomes for Taiwanese Eighth Graders: Structural Equation Modeling with a Complex Sampling Consideration

ERIC Educational Resources Information Center

Jen, Tsung-Hau; Lee, Che-Di; Chien, Chin-Lung; Hsu, Ying-Shao; Chen, Kuan-Ming

2013-01-01

Based on the Trends in International Mathematics and Science Study 2007 study and a follow-up national survey, data for 3,901 Taiwanese grade 8 students were analyzed using structural equation modeling to confirm a social-relation-based affection-driven model (SRAM). SRAM hypothesized relationships among students' perceived social relationships in…

Design and optimisation of orally active TLR7 agonists for the treatment of hepatitis C virus infection.

PubMed

Tran, Thien-Duc; Pryde, David C; Jones, Peter; Adam, Fiona M; Benson, Neil; Bish, Gerwyn; Calo, Frederick; Ciaramella, Guiseppe; Dixon, Rachel; Duckworth, Jonathan; Fox, David N A; Hay, Duncan A; Hitchin, James; Horscroft, Nigel; Howard, Martin; Gardner, Iain; Jones, Hannah M; Laxton, Carl; Parkinson, Tanya; Parsons, Gemma; Proctor, Katie; Smith, Mya C; Smith, Nicholas; Thomas, Amy

2011-04-15

The synthesis and structure-activity relationships of a series of novel interferon inducers are described. Pharmacokinetic studies and efficacy assessment of a series of 8-oxo-3-deazapurine analogues led to the identification of compound 33, a potent and selective agonist of the TLR7 receptor with an excellent in vivo efficacy profile in a mouse model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantitative structure-activity relationship for the partition coefficient of hydrophobic compounds between silicone oil and air.

PubMed

Qu, Yanfei; Ma, Yongwen; Wan, Jinquan; Wang, Yan

2018-06-01

The silicon oil-air partition coefficients (K SiO/A ) of hydrophobic compounds are vital parameters for applying silicone oil as non-aqueous-phase liquid in partitioning bioreactors. Due to the limited number of K SiO/A values determined by experiment for hydrophobic compounds, there is an urgent need to model the K SiO/A values for unknown chemicals. In the present study, we developed a universal quantitative structure-activity relationship (QSAR) model using a sequential approach with macro-constitutional and micromolecular descriptors for silicone oil-air partition coefficients (K SiO/A ) of hydrophobic compounds with large structural variance. The geometry optimization and vibrational frequencies of each chemical were calculated using the hybrid density functional theory at the B3LYP/6-311G** level. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates that a regression model derived from logK SiO/A , the number of non-hydrogen atoms (#nonHatoms) and energy gap of E LUMO and E HOMO (E LUMO -E HOMO ) could explain the partitioning mechanism of hydrophobic compounds between silicone oil and air. The correlation coefficient R 2 of the model is 0.922, and the internal and external validation coefficient, Q 2 LOO and Q 2 ext , are 0.91 and 0.89 respectively, implying that the model has satisfactory goodness-of-fit, robustness, and predictive ability and thus provides a robust predictive tool to estimate the logK SiO/A values for chemicals in application domain. The applicability domain of the model was visualized by the Williams plot.

Collaborative development of predictive toxicology applications

PubMed Central

2010-01-01

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals. The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation. Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way. PMID:20807436

Collaborative development of predictive toxicology applications.

PubMed

Hardy, Barry; Douglas, Nicki; Helma, Christoph; Rautenberg, Micha; Jeliazkova, Nina; Jeliazkov, Vedrin; Nikolova, Ivelina; Benigni, Romualdo; Tcheremenskaia, Olga; Kramer, Stefan; Girschick, Tobias; Buchwald, Fabian; Wicker, Joerg; Karwath, Andreas; Gütlein, Martin; Maunz, Andreas; Sarimveis, Haralambos; Melagraki, Georgia; Afantitis, Antreas; Sopasakis, Pantelis; Gallagher, David; Poroikov, Vladimir; Filimonov, Dmitry; Zakharov, Alexey; Lagunin, Alexey; Gloriozova, Tatyana; Novikov, Sergey; Skvortsova, Natalia; Druzhilovsky, Dmitry; Chawla, Sunil; Ghosh, Indira; Ray, Surajit; Patel, Hitesh; Escher, Sylvia

2010-08-31

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals.The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation.Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way.

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.

Insights into the structural/conformational requirements of cytotoxic oxadiazoles as potential chemotherapeutic target binding agents

NASA Astrophysics Data System (ADS)

Alikhani, Radin; Razzaghi-Asl, Nima; Ramazani, Ali; Hosseinzadeh, Zahra

2018-07-01

A few novel previously synthesized 2,5-disubstituted 1,3,4-oxadiazoles with cytotoxic activity (1-17) were subjected to combined docking/quantum mechanical studies against chemotherapeutic targets. Selected macromolecular targets were those that were previously known to be inhibited by 1,3,4-oxadiazoles. Within this work, favorable binding modes/affinities of the oxadiazoles toward validated cancer targets were elucidated. Some oxadiazole structures exhibited ΔGbs comparable to or stronger than crystallographic ligands that were previously demonstrated to inhibit such targets. On the basis of obtained results, a general structure activity/binding relationship (SAR/SBR) was developed and a few 2,5-disubstituted 1,3,4-oxadiazole structures were proposed and virtually validated as potential cytotoxic candidates. To get more insight into structure binding relationship of candidate molecules within best correlated targets, docked conformation of the best in silico in vitro correlated oxadiazole structure was analyzed in terms of intermolecular binding energy components by functional B3LYP in association with split valence basis set using polarization functions (Def2-SVP). We believe that such modeling studies may be complementary to our previous results on the synthesis and cytotoxicity assessment of novel 1,3,4-oxadiazole derivatives through extending the scope of privileged structures toward designing new potential anti-tumor compounds.

Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis

PubMed Central

Lizandra, Jorge; Devís-Devís, José; Pérez-Gimeno, Esther; Valencia-Peris, Alexandra; Peiró-Velert, Carmen

2016-01-01

This study examined whether adolescents’ time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely to succeed academically three years later. Moreover, adolescents who spent more time in the three different types of sedentary behaviors were more likely to engage longer in those sedentary behaviors after the three-year period. The better the adolescents performed academically, the less time they devoted to social-based activities and more to academic activities. An inverse relationship emerged between time dedicated to technological-based activities and academic sedentary activities. A moderating auto-regressive effect by gender indicated that boys were more likely to spend more time on technological-based activities three years later than girls. To conclude, previous academic performance predicts better sedentary behaviors three years later than the reverse. The positive longitudinal auto-regressive effects on the four variables under study reinforce the ‘success breeds success’ hypothesis, with academic performance and social-based activities emerging as the strongest ones. Technological-based activities showed a moderating effect by gender and a negative longitudinal association with academic activities that supports a displacement hypothesis. Other longitudinal and covariate effects reflect the complex relationships among sedentary behaviors and academic performance and the need to explore these relationships in depth. Theoretical and practical implications for school health are outlined. PMID:27055121

Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis.

PubMed

Lizandra, Jorge; Devís-Devís, José; Pérez-Gimeno, Esther; Valencia-Peris, Alexandra; Peiró-Velert, Carmen

2016-01-01

This study examined whether adolescents' time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely to succeed academically three years later. Moreover, adolescents who spent more time in the three different types of sedentary behaviors were more likely to engage longer in those sedentary behaviors after the three-year period. The better the adolescents performed academically, the less time they devoted to social-based activities and more to academic activities. An inverse relationship emerged between time dedicated to technological-based activities and academic sedentary activities. A moderating auto-regressive effect by gender indicated that boys were more likely to spend more time on technological-based activities three years later than girls. To conclude, previous academic performance predicts better sedentary behaviors three years later than the reverse. The positive longitudinal auto-regressive effects on the four variables under study reinforce the 'success breeds success' hypothesis, with academic performance and social-based activities emerging as the strongest ones. Technological-based activities showed a moderating effect by gender and a negative longitudinal association with academic activities that supports a displacement hypothesis. Other longitudinal and covariate effects reflect the complex relationships among sedentary behaviors and academic performance and the need to explore these relationships in depth. Theoretical and practical implications for school health are outlined.

Longitudinal Relationships Between Resources, Motivation, and Functioning

PubMed Central

Emery, Lisa; Neupert, Shevaun D.

2012-01-01

Objectives. We investigated how fluctuations and linear changes in health and cognitive resources influence the motivation to engage in complex cognitive activity and the extent to which motivation mediated the relationship between changing resources and cognitively demanding activities. Method. Longitudinal data from 332 adults aged 20–85 years were examined. Motivation was assessed using a composite of Need for Cognition and Personal Need for Structure and additional measures of health, sensory functioning, cognitive ability, and self-reported activity engagement. Results. Multilevel modeling revealed that age-typical changes in health, sensory functions, and ability were associated with changes in motivation, with the impact of declining health on motivation being particularly strong in older adulthood. Changes in motivation, in turn, predicted involvement in cognitive and social activities as well as changes in cognitive ability. Finally, motivation was observed to partially mediate the relationship between changes in resources and cognitively demanding activities. Discussion. Our results suggest that motivation may play an important role in determining the course of cognitive change and involvement in cognitively demanding everyday activities in adulthood. PMID:21926400

Control pole placement relationships

NASA Technical Reports Server (NTRS)

Ainsworth, O. R.

1982-01-01

Using a simplified Large Space Structure (LSS) model, a technique was developed which gives algebraic relationships for the unconstrained poles. The relationships, which were obtained by this technique, are functions of the structural characteristics and the control gains. Extremely interesting relationships evolve for the case when the structural damping is zero. If the damping is zero, the constrained poles are uncoupled from the structural mode shapes. These relationships, which are derived for structural damping and without structural damping, provide new insight into the migration of the unconstrained poles for the CFPPS.

Structural Relationships between Social Activities and Longitudinal Trajectories of Depression among Older Adults

ERIC Educational Resources Information Center

Hong, Song-Iee; Hasche, Leslie; Bowland, Sharon

2009-01-01

Purpose: This study examines the structural relationships between social activities and trajectories of late-life depression. Design and Methods: Latent class analysis was used with a nationally representative sample of older adults (N = 5,294) from the Longitudinal Study on Aging II to classify patterns of social activities. A latent growth curve…

Motivation Mediates the Perfectionism-Burnout Relationship: A Three-Wave Longitudinal Study With Junior Athletes.

PubMed

Madigan, Daniel J; Stoeber, Joachim; Passfield, Louis

2016-08-01

Perfectionism in sports has been shown to predict longitudinal changes in athlete burnout. What mediates these changes over time, however, is still unclear. Adopting a self-determination theory perspective and using a three-wave longitudinal design, the current study examined perfectionistic strivings, perfectionistic concerns, autonomous motivation, controlled motivation, and athlete burnout in 141 junior athletes (mean age = 17.3 years) over 6 months of active training. When multilevel structural equation modeling was employed to test a mediational model, a differential pattern of between- and within-person relationships emerged. Whereas autonomous motivation mediated the negative relationship that perfectionistic strivings had with burnout at the between- and within-person level, controlled motivation mediated the positive relationship that perfectionistic concerns had with burnout at the between-persons level only. The present findings suggest that differences in autonomous and controlled motivation explain why perfectionism predicts changes in athlete burnout over time.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.

PubMed

Zhu, Zhenyu; Wang, Rubin; Zhu, Fengyun

2018-01-01

Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.

Evolution of fractality in space plasmas of interest to geomagnetic activity

NASA Astrophysics Data System (ADS)

Muñoz, Víctor; Domínguez, Macarena; Alejandro Valdivia, Juan; Good, Simon; Nigro, Giuseppina; Carbone, Vincenzo

2018-03-01

We studied the temporal evolution of fractality for geomagnetic activity, by calculating fractal dimensions from the Dst data and from a magnetohydrodynamic shell model for turbulent magnetized plasma, which may be a useful model to study geomagnetic activity under solar wind forcing. We show that the shell model is able to reproduce the relationship between the fractal dimension and the occurrence of dissipative events, but only in a certain region of viscosity and resistivity values. We also present preliminary results of the application of these ideas to the study of the magnetic field time series in the solar wind during magnetic clouds, which suggest that it is possible, by means of the fractal dimension, to characterize the complexity of the magnetic cloud structure.

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

NASA Astrophysics Data System (ADS)

Zhi, Hui; Zheng, Junxia; Chang, Yiqun; Li, Qingguo; Liao, Guochao; Wang, Qi; Sun, Pinghua

2015-10-01

Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q2 value of 0.792 and an r2 value of 0.985. The best CoMSIA model predicted a q2 value of 0.633 and an r2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients (rpred2) of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted.

Development and Application of Computational/In Vitro Toxicological Methods for Chemical Hazard Risk Reduction of New Materials for Advanced Weapon Systems

NASA Technical Reports Server (NTRS)

Frazier, John M.; Mattie, D. R.; Hussain, Saber; Pachter, Ruth; Boatz, Jerry; Hawkins, T. W.

2000-01-01

The development of quantitative structure-activity relationship (QSAR) is essential for reducing the chemical hazards of new weapon systems. The current collaboration between HEST (toxicology research and testing), MLPJ (computational chemistry) and PRS (computational chemistry, new propellant synthesis) is focusing R&D efforts on basic research goals that will rapidly transition to useful products for propellant development. Computational methods are being investigated that will assist in forecasting cellular toxicological end-points. Models developed from these chemical structure-toxicity relationships are useful for the prediction of the toxicological endpoints of new related compounds. Research is focusing on the evaluation tools to be used for the discovery of such relationships and the development of models of the mechanisms of action. Combinations of computational chemistry techniques, in vitro toxicity methods, and statistical correlations, will be employed to develop and explore potential predictive relationships; results for series of molecular systems that demonstrate the viability of this approach are reported. A number of hydrazine salts have been synthesized for evaluation. Computational chemistry methods are being used to elucidate the mechanism of action of these salts. Toxicity endpoints such as viability (LDH) and changes in enzyme activity (glutahoione peroxidase and catalase) are being experimentally measured as indicators of cellular damage. Extrapolation from computational/in vitro studies to human toxicity, is the ultimate goal. The product of this program will be a predictive tool to assist in the development of new, less toxic propellants.

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

Correlates of male cohabiting partner's involvement in child-rearing tasks in low-income urban Black stepfamilies.

PubMed

Forehand, Rex; Parent, Justin; Golub, Andrew; Reid, Megan

2014-06-01

Cohabitation is a family structure experienced by many Black children. This study examines the link between family relationships (child relationship with mother and the cohabiting partner; parent and cohabiting partner relationship) and involvement of biologically unrelated male cohabiting partners (MCP) in child rearing. The participants were 121 low-income urban Black families consisting of a single mother, MCP, and an adolescent (56% female, M age = 13.7). Assessments were conducted individually with mothers, MCPs, and adolescents via measures administered by interview. MCPs were involved in both domains of child rearing assessed (daily child-related tasks and setting limits) and those identified as coparents by the mother were more involved in child-rearing tasks than those not identified as coparents. Using structural equation modeling (SEM), the mother-MCP relationship (both support and conflict) and the adolescent-MCP relationship were related to MCP's involvement in both domains of child rearing. The findings indicate that MCPs are actively involved in child rearing and family relationship variables are associated with their involvement in these tasks. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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.

Transmembrane Helices Tilt, Bend, Slide, Torque, and Unwind between Functional States of Rhodopsin

PubMed Central

Ren, Zhong; Ren, Peter X.; Balusu, Rohith; Yang, Xiaojing

2016-01-01

The seven-helical bundle of rhodopsin and other G-protein coupled receptors undergoes structural rearrangements as the transmembrane receptor protein is activated. These structural changes are known to involve tilting and bending of various transmembrane helices. However, the cause and effect relationship among structural events leading to a cytoplasmic crevasse for G-protein binding is less well defined. Here we present a mathematical model of the protein helix and a simple procedure to determine multiple parameters that offer precise depiction of a helical conformation. A comprehensive survey of bovine rhodopsin structures shows that the helical rearrangements during the activation of rhodopsin involve a variety of angular and linear motions such as torsion, unwinding, and sliding in addition to the previously reported tilting and bending. These hitherto undefined motion components unify the results obtained from different experimental approaches, and demonstrate conformational similarity between the active opsin structure and the photoactivated structures in crystallo near the retinal anchor despite their marked differences. PMID:27658480

On the role of general system theory for functional neuroimaging

PubMed Central

Stephan, Klaas Enno

2004-01-01

One of the most important goals of neuroscience is to establish precise structure–function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure–function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure–function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples. PMID:15610393

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.

Investigation on quantitative structure activity relationships and pharmacophore modeling of a series of mGluR2 antagonists.

PubMed

Zhang, Meng-Qi; Zhang, Xiao-Le; Li, Yan; Fan, Wen-Jia; Wang, Yong-Hua; Hao, Ming; Zhang, Shu-Wei; Ai, Chun-Zhi

2011-01-01

MGluR2 is G protein-coupled receptor that is targeted for diseases like anxiety, depression, Parkinson's disease and schizophrenia. Herein, we report the three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of a series of 1,3-dihydrobenzo[ b][1,4]diazepin-2-one derivatives as mGluR2 antagonists. Two series of models using two different activities of the antagonists against rat mGluR2, which has been shown to be very similar to the human mGluR2, (activity I: inhibition of [(3)H]-LY354740; activity II: mGluR2 (1S,3R)-ACPD inhibition of forskolin stimulated cAMP.) were derived from datasets composed of 137 and 69 molecules respectively. For activity I study, the best predictive model obtained from CoMFA analysis yielded a Q(2) of 0.513, R(2) (ncv) of 0.868, R(2) (pred) = 0.876, while the CoMSIA model yielded a Q(2) of 0.450, R(2) (ncv) = 0.899, R(2) (pred) = 0.735. For activity II study, CoMFA model yielded statistics of Q(2) = 0.5, R(2) (ncv) = 0.715, R(2) (pred) = 0.723. These results prove the high predictability of the models. Furthermore, a combined analysis between the CoMFA, CoMSIA contour maps shows that: (1) Bulky substituents in R(7), R(3) and position A benefit activity I of the antagonists, but decrease it when projected in R(8) and position B; (2) Hydrophilic groups at position A and B increase both antagonistic activity I and II; (3) Electrostatic field plays an essential rule in the variance of activity II. In search for more potent mGluR2 antagonists, two pharmacophore models were developed separately for the two activities. The first model reveals six pharmacophoric features, namely an aromatic center, two hydrophobic centers, an H-donor atom, an H-acceptor atom and an H-donor site. The second model shares all features of the first one and has an additional acceptor site, a positive N and an aromatic center. These models can be used as guidance for the development of new mGluR2 antagonists of high activity and selectivity. This work is the first report on 3D-QSAR modeling of these mGluR2 antagonists. All the conclusions may lead to a better understanding of the mechanism of antagonism and be helpful in the design of new potent mGluR2 antagonists.

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.

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.

The Junior Faculty Laboratory: An Innovative Model of Peer Mentoring

PubMed Central

Johnson, Kimberly S.; Hastings, S. Nicole; Purser, Jama L; Whitson, Heather E

2013-01-01

Mentoring in academic medicine has been shown to contribute to the success of junior faculty, resulting in increased productivity, career satisfaction, and opportunities for networking. Although traditional dyadic mentoring, involving one senior faculty member and one junior protégé, is the dominant model for mentoring in the academic environment, there is increasing recognition that the sharing of knowledge, skills, and experiences among peers may also contribute to the career development of junior faculty. The authors describe the structure, activities, and outcomes of the Junior Faculty Laboratory (JFL), a self-organized, flexible, and dynamic peer mentoring model within the Duke University Center for the Study of Aging and Human Development. As an innovative mentoring model, JFL is entirely peer-driven and its activities are determined by the real-time needs of members. In contrast to some other peer mentoring models, JFL lacks senior faculty input or a structured curriculum, members are multidisciplinary, meeting times are project-driven rather than preset, and participation in collaborative projects is optional based on the interests and needs of group members. Additionally, JFL was not formed as a substitute for, but as a complement to the dyadic mentoring relationships enjoyed by its members. The model, now in its fifth year, has demonstrated success and sustainability. The authors present the JFL as an innovative, mentoring model that can be reproduced by other junior faculty seeking to foster collegial relationships with peers while simultaneously enhancing their career development. PMID:22030756

The Junior Faculty Laboratory: an innovative model of peer mentoring.

PubMed

Johnson, Kimberly S; Hastings, S Nicole; Purser, Jama L; Whitson, Heather E

2011-12-01

Mentoring in academic medicine has been shown to contribute to the success of junior faculty, resulting in increased productivity, career satisfaction, and opportunities for networking. Although traditional dyadic mentoring, involving one senior faculty member and one junior protégé, is the dominant model for mentoring in the academic environment, there is increasing recognition that the sharing of knowledge, skills, and experiences among peers may also contribute to the career development of junior faculty. The authors describe the structure, activities, and outcomes of the Junior Faculty Laboratory (JFL), a self-organized, flexible, and dynamic peer-mentoring model within the Duke University Center for the Study of Aging and Human Development. As an innovative mentoring model, JFL is entirely peer driven, and its activities are determined by the real-time needs of members. In contrast to some other peer-mentoring models, JFL lacks senior faculty input or a structured curriculum, members are multidisciplinary, meeting times are project driven rather than preset, and participation in collaborative projects is optional based on the interests and needs of group members. Additionally, JFL was not formed as a substitute for, but as a complement to, the dyadic mentoring relationships enjoyed by its members. The model, now in its fifth year, has demonstrated success and sustainability. The authors present the JFL as an innovative, mentoring model that can be reproduced by other junior faculty seeking to foster collegial relationships with peers while simultaneously enhancing their career development.

An examination of the structure of posttraumatic stress disorder in relation to the anxiety and depressive disorders.

PubMed

Forbes, David; Lockwood, Emma; Elhai, Jon D; Creamer, Mark; O'Donnell, Meaghan; Bryant, Richard; McFarlane, Alexander; Silove, Derrick

2011-07-01

The nature and structure of posttraumatic stress disorder (PTSD) has been the subject of much interest in recent times. This research has been represented by two streams, the first representing a substantive body of work which focuses specifically on the factor structure of PTSD and the second exploring PTSD's relationship with other mood and anxiety disorders. The present study attempted to bring these two streams together by examining structural models of PTSD and their relationship with dimensions underlying other mood and anxiety disorders. PTSD, anxiety and mood disorder data from 989 injury survivors interviewed 3-months following their injury were analyzed using a series of confirmatory factor analyses (CFA) to identify the optimal structural model. CFA analyses indicated that the best fitting model included PTSD's re-experiencing (B1-5), active avoidance (C1-2), and hypervigilance and startle (D4-5) loading onto a Fear factor (represented by panic disorder, agoraphobia and social phobia) and the PTSD dysphoria symptoms (numbing symptoms C3-7 and hyperarousal symptoms D1-3) loading onto an Anxious Misery/Distress factor (represented by depression, generalized anxiety disorder and obsessive compulsive disorder). The findings have implications for informing potential revisions to the structure of the diagnosis of PTSD and the diagnostic algorithm to be applied, with the aim of enhancing diagnostic specificity. Copyright © 2011 Elsevier B.V. All rights reserved.

Exploring model based engineering for large telescopes: getting started with descriptive models

NASA Astrophysics Data System (ADS)

Karban, R.; Zamparelli, M.; Bauvir, B.; Koehler, B.; Noethe, L.; Balestra, A.

2008-07-01

Large telescopes pose a continuous challenge to systems engineering due to their complexity in terms of requirements, operational modes, long duty lifetime, interfaces and number of components. A multitude of decisions must be taken throughout the life cycle of a new system, and a prime means of coping with complexity and uncertainty is using models as one decision aid. The potential of descriptive models based on the OMG Systems Modeling Language (OMG SysMLTM) is examined in different areas: building a comprehensive model serves as the basis for subsequent activities of soliciting and review for requirements, analysis and design alike. Furthermore a model is an effective communication instrument against misinterpretation pitfalls which are typical of cross disciplinary activities when using natural language only or free-format diagrams. Modeling the essential characteristics of the system, like interfaces, system structure and its behavior, are important system level issues which are addressed. Also shown is how to use a model as an analysis tool to describe the relationships among disturbances, opto-mechanical effects and control decisions and to refine the control use cases. Considerations on the scalability of the model structure and organization, its impact on the development process, the relation to document-centric structures, style and usage guidelines and the required tool chain are presented.

OPERA models for predicting physicochemical properties and environmental fate endpoints.

PubMed

Mansouri, Kamel; Grulke, Chris M; Judson, Richard S; Williams, Antony J

2018-03-08

The collection of chemical structure information and associated experimental data for quantitative structure-activity/property relationship (QSAR/QSPR) modeling is facilitated by an increasing number of public databases containing large amounts of useful data. However, the performance of QSAR models highly depends on the quality of the data and modeling methodology used. This study aims to develop robust QSAR/QSPR models for chemical properties of environmental interest that can be used for regulatory purposes. This study primarily uses data from the publicly available PHYSPROP database consisting of a set of 13 common physicochemical and environmental fate properties. These datasets have undergone extensive curation using an automated workflow to select only high-quality data, and the chemical structures were standardized prior to calculation of the molecular descriptors. The modeling procedure was developed based on the five Organization for Economic Cooperation and Development (OECD) principles for QSAR models. A weighted k-nearest neighbor approach was adopted using a minimum number of required descriptors calculated using PaDEL, an open-source software. The genetic algorithms selected only the most pertinent and mechanistically interpretable descriptors (2-15, with an average of 11 descriptors). The sizes of the modeled datasets varied from 150 chemicals for biodegradability half-life to 14,050 chemicals for logP, with an average of 3222 chemicals across all endpoints. The optimal models were built on randomly selected training sets (75%) and validated using fivefold cross-validation (CV) and test sets (25%). The CV Q 2 of the models varied from 0.72 to 0.95, with an average of 0.86 and an R 2 test value from 0.71 to 0.96, with an average of 0.82. Modeling and performance details are described in QSAR model reporting format and were validated by the European Commission's Joint Research Center to be OECD compliant. All models are freely available as an open-source, command-line application called OPEn structure-activity/property Relationship App (OPERA). OPERA models were applied to more than 750,000 chemicals to produce freely available predicted data on the U.S. Environmental Protection Agency's CompTox Chemistry Dashboard.

Prediction of local proximal tibial subchondral bone structural stiffness using subject-specific finite element modeling: Effect of selected density-modulus relationship.

PubMed

Nazemi, S Majid; Amini, Morteza; Kontulainen, Saija A; Milner, Jaques S; Holdsworth, David W; Masri, Bassam A; Wilson, David R; Johnston, James D

2015-08-01

Quantitative computed tomography based subject-specific finite element modeling has potential to clarify the role of subchondral bone alterations in knee osteoarthritis initiation, progression, and pain initiation. Calculation of bone elastic moduli from image data is a basic step when constructing finite element models. However, different relationships between elastic moduli and imaged density (known as density-modulus relationships) have been reported in the literature. The objective of this study was to apply seven different trabecular-specific and two cortical-specific density-modulus relationships from the literature to finite element models of proximal tibia subchondral bone, and identify the relationship(s) that best predicted experimentally measured local subchondral structural stiffness with highest explained variance and least error. Thirteen proximal tibial compartments were imaged via quantitative computed tomography. Imaged bone mineral density was converted to elastic moduli using published density-modulus relationships and mapped to corresponding finite element models. Proximal tibial structural stiffness values were compared to experimentally measured stiffness values from in-situ macro-indentation testing directly on the subchondral bone surface (47 indentation points). Regression lines between experimentally measured and finite element calculated stiffness had R(2) values ranging from 0.56 to 0.77. Normalized root mean squared error varied from 16.6% to 337.6%. Of the 21 evaluated density-modulus relationships in this study, Goulet combined with Snyder and Schneider or Rho appeared most appropriate for finite element modeling of local subchondral bone structural stiffness. Though, further studies are needed to optimize density-modulus relationships and improve finite element estimates of local subchondral bone structural stiffness. Copyright © 2015 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

Structure-activity studies and therapeutic potential of host defense peptides of human thrombin.

PubMed

Kasetty, Gopinath; Papareddy, Praveen; Kalle, Martina; Rydengård, Victoria; Mörgelin, Matthias; Albiger, Barbara; Malmsten, Martin; Schmidtchen, Artur

2011-06-01

Peptides of the C-terminal region of human thrombin are released upon proteolysis and identified in human wounds. In this study, we wanted to investigate minimal determinants, as well as structural features, governing the antimicrobial and immunomodulating activity of this peptide region. Sequential amino acid deletions of the peptide GKYGFYTHVFRLKKWIQKVIDQFGE (GKY25), as well as substitutions at strategic and structurally relevant positions, were followed by analyses of antimicrobial activity against the Gram-negative bacteria Escherichia coli and Pseudomonas aeruginosa, the Gram-positive bacterium Staphylococcus aureus, and the fungus Candida albicans. Furthermore, peptide effects on lipopolysaccharide (LPS)-, lipoteichoic acid-, or zymosan-induced macrophage activation were studied. The thrombin-derived peptides displayed length- and sequence-dependent antimicrobial as well as immunomodulating effects. A peptide length of at least 20 amino acids was required for effective anti-inflammatory effects in macrophage models, as well as optimal antimicrobial activity as judged by MIC assays. However, shorter (>12 amino acids) variants also displayed significant antimicrobial effects. A central K14 residue was important for optimal antimicrobial activity. Finally, one peptide variant, GKYGFYTHVFRLKKWIQKVI (GKY20) exhibiting improved selectivity, i.e., low toxicity and a preserved antimicrobial as well as anti-inflammatory effect, showed efficiency in mouse models of LPS shock and P. aeruginosa sepsis. The work defines structure-activity relationships of C-terminal host defense peptides of thrombin and delineates a strategy for selecting peptide epitopes of therapeutic interest.

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

Understanding Substrate Selectivity of Human UDP-glucuronosyltransferases through QSAR modeling and analysis of homologous enzymes

PubMed Central

Dong, Dong; Ako, Roland; Hu, Ming; Wu, Baojian

2015-01-01

The UDP-glucuronosyltransferase (UGT) enzyme catalyzes the glucuronidation reaction which is a major metabolic and detoxification pathway in humans. Understanding the mechanisms for substrate recognition by UGT assumes great importance in an attempt to predict its contribution to xenobiotic/drug disposition in vivo. Spurred on by this interest, 2D/3D-quantitative structure activity relationships (QSAR) and pharmacophore models have been established in the absence of a complete mammalian UGT crystal structure. This review discusses the recent progress in modeling human UGT substrates including those with multiple sites of glucuronidation. A better understanding of UGT active site contributing to substrate selectivity (and regioselectivity) from the homologous enzymes (i.e., plant and bacterial UGTs, all belong to family 1 of glycosyltransferase (GT1)) is also highlighted, as these enzymes share a common catalytic mechanism and/or overlapping substrate selectivity. PMID:22385482

Assessment of Cognitively Stimulating Activity in a Spanish Population.

PubMed

Morales Ortiz, Manuel; Fernández, Aaron

2018-05-01

Theoretical models of active ageing and cognitive reserve emphasize the importance of leading an active life to delay age-related cognitive deterioration and maintain good levels of well-being and personal satisfaction in the elderly. The objective of this research was to construct a scale to measure cognitively stimulating activities (CSA) in the Spanish language. The sample consisted of a total of 453 older persons. The scale was constructed from a list of 28 items and validated using structural equation models. The scale obtained showed a negative correlation with age and a positive correlation with education and physical activity. Using hierarchical regression models, CSAs were found to have a significant effect on attention when controlling for the effect of age and education. Likewise, a significant interaction between age and CSA was found on the measure of episodic memory. The validated CSA scale will enable the relationships between changes in cognitive functions and stimulating activities to be studied.

Mobility impairment, social engagement, and life satisfaction among the older population in China: a structural equation modeling analysis.

PubMed

Li, Linna; Loo, Becky P Y

2017-05-01

Revealing the relationship between mobility impairment and life satisfaction can help to propose effective interventions to secure mobility and life satisfaction. However, the relationship remains unclear and lacks quantitative evidence in China. This study therefore assesses the association of mobility impairment, social engagement, and life satisfaction among the older population in China. Based on the sample of China Health and Retirement Longitudinal Survey database in 2013, a structural equation modeling is established. The sample size is 4245 with 55.9% with mobility impairment. The model shows that the length of suffering from disability is significantly related to mobility impairment (β = 0.058, p < 0.001). Mobility impairment is inversely related to social engagement (β = -0.300, p < 0.001) and life satisfaction (β = -0.311, p < 0.001). Social engagement is positively related to life satisfaction (β = 0.211, p < 0.001). Moreover, the relationships have some differences for the seniors with different sociodemographic characteristics and living in different residential areas. As seniors get older, they tend to have more severe mobility impairment and participate less in social activities. Those with higher mobility impairment are more likely to report lower life satisfaction partly because they usually participate less in social activities. Different strategies are suggested to be adopted to improve the life satisfaction of the older population from the aspects of promoting mobility and social engagement, including improving the design of transport facilitates, providing assistive facilities for the seniors with severe mobility impairment, promoting the accessibility of community leisure and healthcare services, and constructing more community senior activity centers.

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

NASA Astrophysics Data System (ADS)

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

2008-06-01

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

Critical patch-size for two-sex populations.

PubMed

Andreguetto Maciel, Gabriel; Mendes Coutinho, Renato; André Kraenkel, Roberto

2018-06-01

As environments become increasingly degraded, mainly due to human activities, species are often subject to isolated habitats surrounded by unfavorable regions. Since the pioneering work by Skellam [25] mathematical models have provided useful insights into the population persistence in such cases. Most of these models, however, neglect the sex structure of populations and the differences between males and females. In this work we investigate, through a reaction-diffusion system, the dynamics of a sex-structured population in a single semipermeable patch. The critical patch size for persistence is determined from implicit relationships between model parameters. The effects of the various growth and movement parameters are also investigated. Copyright © 2018 Elsevier Inc. All rights reserved.

The Developmental Pathway From Pubertal Timing to Delinquency and Sexual Activity From Early to Late Adolescence

PubMed Central

Negriff, Sonya; Elizabeth, J. Susman; Trickett, Penelope K.

2013-01-01

There is strong evidence that early pubertal timing is associated with adolescent problem behaviors. However, there has been limited investigation of the mechanisms or developmental relationships. The present study examined longitudinal models incorporating pubertal timing, delinquency, and sexual activity in a sample of 454 adolescents (9–13 years old at enrollment; 47% females). Participants were seen for three assessments approximately 1 year apart. Characteristics of friendship networks (older friends, male friends, older male friends) were examined as mediators. Structural equation modeling was used to test these associations as well as temporal relationships between sexual activity and delinquency. Results showed that early pubertal timing at Time 1 was related to more sexual activity at Time 2, which was related to higher delinquency at Time 3, a trend mediation effect. None of the friendship variables mediated these associations. Gender or maltreatment status did not moderate the meditational pathways. The results also supported the temporal sequence of sexual activity preceding increases in delinquency. These findings reveal that early maturing adolescents may actively seek out opportunities to engage in sexual activity which appears to be risk for subsequent delinquency. PMID:21191640

The developmental pathway from pubertal timing to delinquency and sexual activity from early to late adolescence.

PubMed

Negriff, Sonya; Susman, Elizabeth J; Trickett, Penelope K

2011-10-01

There is strong evidence that early pubertal timing is associated with adolescent problem behaviors. However, there has been limited investigation of the mechanisms or developmental relationships. The present study examined longitudinal models incorporating pubertal timing, delinquency, and sexual activity in a sample of 454 adolescents (9-13 years old at enrollment; 47% females). Participants were seen for three assessments approximately 1 year apart. Characteristics of friendship networks (older friends, male friends, older male friends) were examined as mediators. Structural equation modeling was used to test these associations as well as temporal relationships between sexual activity and delinquency. Results showed that early pubertal timing at Time 1 was related to more sexual activity at Time 2, which was related to higher delinquency at Time 3, a trend mediation effect. None of the friendship variables mediated these associations. Gender or maltreatment status did not moderate the meditational pathways. The results also supported the temporal sequence of sexual activity preceding increases in delinquency. These findings reveal that early maturing adolescents may actively seek out opportunities to engage in sexual activity which appears to be risk for subsequent delinquency.

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

PubMed Central

Wang, Zhanggen; Su, Jiyan; Jiao, Chunwei; Xie, Yizhen; Yang, Burton B.

2017-01-01

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. PMID:28052025

Northeastern Brazilian margin: Regional tectonic evolution based on integrated analysis of seismic reflection and potential field data and modelling

NASA Astrophysics Data System (ADS)

Blaich, Olav A.; Tsikalas, Filippos; Faleide, Jan Inge

2008-10-01

Integration of regional seismic reflection and potential field data along the northeastern Brazilian margin, complemented by crustal-scale gravity modelling, is used to reveal and illustrate onshore-offshore crustal structure correlation, the character of the continent-ocean boundary, and the relationship of crustal structure to regional variation of potential field anomalies. The study reveals distinct along-margin structural and magmatic changes that are spatially related to a number of conjugate Brazil-West Africa transfer systems, governing the margin segmentation and evolution. Several conceptual tectonic models are invoked to explain the structural evolution of the different margin segments in a conjugate margin context. Furthermore, the constructed transects, the observed and modelled Moho relief, and the potential field anomalies indicate that the Recôncavo, Tucano and Jatobá rift system may reflect a polyphase deformation rifting-mode associated with a complex time-dependent thermal structure of the lithosphere. The constructed transects and available seismic reflection profiles, indicate that the northern part of the study area lacks major breakup-related magmatic activity, suggesting a rifted non-volcanic margin affinity. In contrast, the southern part of the study area is characterized by abrupt crustal thinning and evidence for breakup magmatic activity, suggesting that this region evolved, partially, with a rifted volcanic margin affinity and character.

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....

STRUCTURE-ACTIVITY RELATIONSHIP AMONG ORGANOTINS IN AN IN VITRO MODEL OF NEURONAL DIFFERENTIATION AND PROGRAMMED CELL DEATH.

EPA Science Inventory

The organotins are used as heat stabilizers in PVC pipes and as marine biocides. Human exposure to monomethyltin (MMT) and dimethyltin (DMT) can occur in the water supply as a result of leaching from PVC pipes. Developmental exposure of rats to MMT and the known neurotoxicant t...

Work Engagement Accumulation of Task, Social, Personal Resources: A Three-Wave Structural Equation Model

ERIC Educational Resources Information Center

Weigl, Matthias; Hornung, Severin; Parker, Sharon K.; Petru, Raluca; Glaser, Jurgen; Angerer, Peter

2010-01-01

Drawing on Conservation of Resources Theory and previous research on work engagement, the present study investigates gain spirals between employees' engagement and their task, social, and personal resources. It focuses on the key resources of job control, positive work relationships, and active coping behavior. In a three-wave design, work…

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.

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

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 Central

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 Ca2+ 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 [3H]Ryanodine ([3H]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. PMID:27655348

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

PubMed

Lymperopoulos, Ilias N

2017-10-01

The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

Structure-Function Perturbation and Dissociation of Tetrameric Urate Oxidase by High Hydrostatic Pressure

PubMed Central

Girard, Eric; Marchal, Stéphane; Perez, Javier; Finet, Stéphanie; Kahn, Richard; Fourme, Roger; Marassio, Guillaume; Dhaussy, Anne-Claire; Prangé, Thierry; Giffard, Marion; Dulin, Fabienne; Bonneté, Françoise; Lange, Reinhard; Abraini, Jacques H.; Mezouar, Mohamed; Colloc'h, Nathalie

2010-01-01

Abstract Structure-function relationships in the tetrameric enzyme urate oxidase were investigated using pressure perturbation. As the active sites are located at the interfaces between monomers, enzyme activity is directly related to the integrity of the tetramer. The effect of hydrostatic pressure on the enzyme was investigated by x-ray crystallography, small-angle x-ray scattering, and fluorescence spectroscopy. Enzymatic activity was also measured under pressure and after decompression. A global model, consistent with all measurements, discloses structural and functional details of the pressure-induced dissociation of the tetramer. Before dissociating, the pressurized protein adopts a conformational substate characterized by an expansion of its substrate binding pocket at the expense of a large neighboring hydrophobic cavity. This substate should be adopted by the enzyme during its catalytic mechanism, where the active site has to accommodate larger intermediates and product. The approach, combining several high-pressure techniques, offers a new (to our knowledge) means of exploring structural and functional properties of transient states relevant to protein mechanisms. PMID:20483346

Phyto-fungicides: Structure activity relationships of the thymol derivatives against Rhizoctonia solani

USDA-ARS?s Scientific Manuscript database

Thymol, the key component of thyme oil and its derivatives were evaluated for their structure activity relationship as fungicide against Rhizoctonia solani. Since plant based chemicals are considered as “Generally Recognized as Safe” (GRAS) chemicals, there is a great potential to use phytochemicals...