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1
Li, Ju-Yun. "Quantitative structure-activity relationship studies in medicinal chemistry." Case Western Reserve University School of Graduate Studies / OhioLINK, 1995. http://rave.ohiolink.edu/etdc/view?acc_num=case1062596938.
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Reddy, Badinehal Asrith. "COMMERCIALIZATION OF A QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP TOOL - SARCHITECT." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1295637833.
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Ren, Xin. "Quantitative structure-activity relationship based virtual screening for novel androgen receptor antagonists." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/43293.
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Androgen receptor (AR) plays a critical role in prostate cancer development and progression. All
current therapeutic AR inhibitors modulate the receptor via direct binding to its Hormone
Binding Site (HBS). Despite the identification of other small molecule binding areas on the AR
surface including Activation Function 2 (AF2), binding function 3 (BF3), and N-terminal domain
(NTD), HBS continues to be the major target site for AR antagonists (even though this site is
prone to resistant mutations). Thus, there is a high need for the identification and development of
novel antagonists targeting HBS of the AR.
In this study, an effective QSAR modeling pipeline was set up and proved to be capable of
identifying new AR antagonists from a large ZINC collection of purchasable chemicals. In
particular, we have utilized DRAGON, INDUCTIVE and MOE descriptors to create various
binary QSAR models of anti-AR activity. When we have applied the developed QSAR solutions
to screen more than 2 million chemicals from the ZINC database, we were able to identify 39
potential candidate AR HBS binders. When they were tested in the DHT displacement assay, 9
chemicals demonstrated the corresponding IC₅₀ values in efficient low-micromole range. Of
those, 9 compounds later exhibited ability to inhibit AR in the eGFP transcriptional assay with
the IC₅₀ values established at 1.04-16.18 μM level. Notably, 6 discovered chemicals
demonstrated concentration-dependent suppression of survival of LNCaP prostate cancer cell
lines.
The results of this study set a ground for the development of an entire novel chemical class of
AR antagonists that are distinct for the currently marketed drugs such as Nitalutamide,
Flutomide, Cassodex, and MDV3100 that all share significant structural similarity.
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Smith, Mark David. "A quantitative structure-activity relationship (QSAR) study of the Ames mutagenicity assay." Thesis, University of Portsmouth, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343333.
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In-vitro mutagenicity assays have traditionally been used for first line identification of potential genotoxic hazard, purporting to chemical carcinogenesis and heritable genetic damage. The recent advances m combinatorial chemistry and high throughput screening technologies have led to a massive explosion in numbers of possible therapeutic candidates being produced at the early stages of drug discovery. This rapid increase in the number of chemicals to be classified results in a greater need for to acquire alternative methods for the prediction of toxicity. Quantitative StructureActivity Relationships (QSAR) can till this need for early hazard identifications by elucidating the physicochemical basis of biological activity. The assumption with predictive QSARs for toxicity is that "biological activity may be described as a function of chemical constitution". This thesis focuses on the Ames mutagenicity assay data for two compound sets; one of 90 compounds, with limited structural flexibility, comprising a range of chemical classes (non-congeneric series), the second, a set of 30 flavonoid compounds. Three physicochemical descriptor sets were generated: EV A, a theoretical molecular descriptor based on the normal co-ordinate modes of vibration; WHIM, derived from weighting functions applied to the 3D-structural molecular co-ordinates; and TSAR, a series of hydrophobic, electronic and steric parameters traditionally associated with the production of biological QSARs. Various "unsupervised" data pre-treatment methods were adopted, to reduce the level of degeneracy within the individual descriptor sets, prior to the calculation of stepwise linear discriminant classification functions. Good predictive models for Ames mutagenicity, as determined by leave-one-out (jackknife) cross-validation, were obtained with each of the three physicochemical descriptor sets. An increase in the predictive ability was observed following the combination of variables from the individual descriptor sets, inferring that some unique information associated with mutagenic activity is contained within each descriptor set. The predictive stability of the models produced was assessed via independent compound predictions, with a poor overall success rate determined. This failure in external prediction was investigated and fundamental differences in physicochemical data space occupancy revealed. Conclusions on training set composition and general model applicability are made with consideration to individual model physicochemical data space coverage.
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Lanevskij, Kiril. "Absorption and Tissue Distribution of Drug-Like Compounds: Quantitative Structure-Activity Relationship Analysis." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2011. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20111003_114235-89858.
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The objective of this work was to develop mechanistic quantitative structure activity relationship models that would facilitate the assessment of drug properties related to their absorption and distribution in the body. The analysis involved several parameters reflecting the rate of passive diffusion across brain endothelium and intestinal epithelium, and thermodynamic constants related to drug distribution between plasma and tissues. Permeation through cellular transport barriers was modeled by nonlinear equations relating the passive diffusion rate to physicochemical properties of drugs: lipophilicity, ionization, hydrogen bonding potential and molecular size. It was demonstrated that brain endothelium and intestinal epithelium exhibit a quantitatively similar pattern of permeability-ionization dependence – ionized species permeate 2-3 orders of magnitude slower than neutral molecules. Analysis of tissue to plasma partitioning data revealed the necessity to split original experimental values into separate terms reflecting plasma and tissue binding strength. Drugs’ affinity to tissues could then be described by their lipophilicity, whereas detrimental effect of ionization was only observed for acidic drugs. Finally, it was shown that a linear combination of quantitative blood-brain barrier transport parameters allows classifying drugs according to their access to central nervous system with 94% overall accuracy.Šiame darbe pristatomi mechanistiniai kiekybinio struktūros ir aktyvumo ryšio modeliai, skirti vaistinių junginių savybių, charakterizuojančių jų absorbciją ir pasiskirstymą organizme prognozavimui. Nagrinėjama keletas parametrų, apibūdinančių paprastos difuzijos per biologines membranas greitį, taip pat termodinaminės konstantos, aprašančios vaistų pasiskirstymą tarp kraujo plazmos ir audinių. Ląstelinių pernašos barjerų pralaidumas buvo modeliuojamas netiesinėmis lygtimis, siejančiomis paprastos difuzijos greitį su vaistų fizikocheminėmis savybėmis, tokiomis kaip lipofiliškumas, jonizacija, vandenilinių ryšių sudarymo potencialas ir molekulių dydis. Nustatyta, kad smegenų endotelyje ir žarnyno epitelyje stebima panašaus pobūdžio difuzijos greičio priklausomybė nuo jonizacijos – katijonai ir anijonai difunduoja atitinkamai 2 ir 3 eilėmis lėčiau už neutralias molekules. Pademonstruota, kad analizuojant vaistų pasiskirstymo tarp audinių ir kraujo duomenis, būtina paversti pradines eksperimentines vertes kitais dydžiais, atspindinčiais vaistų jungimosi prie plazmos ir audinių komponentų stiprumą. Vaistų giminingumas audiniams gali būti aprašytas jų lipofiliškumu, o neigiama jonizacijos įtaka stebima tik rūgštiniams junginiams. Taip pat parodyta, kad vaistų pernašos per hematoencefalinę užtvarą kiekybinių parametrų tiesinė kombinacija leidžia 94% tikslumu klasifikuoti vaistus pagal jų prieinamumą centrinei nervų sistemai.
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Ruark, Christopher Daniel. "Quantitative Structure-Activity Relationships for Organophosphates Binding to Trypsin and Chymotrypsin." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1278010674.
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Diaz-Perez, Maria-Jose. "Quantitative structure-activity relationship (QSAR) study of the effect of steroids on DNA replication." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ50291.pdf.
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Peron, Jean-Marie. "Quantitative structure activity relationship analysis of anti-oxidants with central nervous system therapeutic potential." Thesis, King's College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271327.
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Jaafar, Mohd Zuli. "Chemometrics and pattern recognition methods with applications to environmental and quantitative structure-activity relationship studies." Thesis, University of Bristol, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541608.
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Marsden-Jones, Siân Catherine. "The application of quantitative structure activity relationship models to the method development of countercurrent chromatography." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12598.
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A fundamental challenge for liquid-liquid separation techniques such as countercurrent chromatography (CCC)and centrifugal partition chromatography (CPC), is the swift, efficient selection of the two phase solvent system containing more than two solvents, for the purification of pharmaceuticals and other molecules. A purely computational model that could predict the optimal solvent systems for separation using just molecular structure would be ideal for this task. The experimental value being predicted is the partition coefficient (Kd), which is the concentration of the compound in one phase divided by the concentration in the other. Using this approach, Quantitative Structure Activity Relationship (QSAR) models have been developed to predict the partitioning of compounds in two phase systems from the molecular structure of the compound using molecular descriptors. A Kd value in the range of 0.5 to 2 will give optimal separation. Molecular descriptors are varied, examples include logP values, hydrogen bond donor values and the number of oxygen atoms. This work describes how the QSAR models were developed and tested. A dataset of experimental logKd values for 54 compounds in six different combinations of four solvents (heptane, ethyl acetate, methanol and water) was used to train the QSAR models. A set of 196 possible molecular descriptors was generated for the 54 compounds and a partial least squares regression was used to identify which of these was significant in the relationship between logKd and molecular structure. The resulting models were used to predict the logKd values of four test compounds that had not been used to build the QSAR models. When these predictions were compared to the experimental logKd values, the root mean squared error for four of the six models was less than 0.5 and less than 0.7 for the remaining two. These models were used to successfully separate a range of structurally diverse pharmaceutical compounds by predicting the best solvent systems to carry out the separation on the CCC/CPC using nothing but their molecular structure.
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Ahlberg, Helgee Ernst. "Improving drug discovery decision making using machine learning and graph theory in QSAR modeling." Göteborg : Dept. of Chemistry, University of Gothenburg, 2010. http://gupea.ub.gu.se/dspace/handle/2077/21838.
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Wang, Fang. "Chlorine Contribution to Quantitative Structure and Activity Relationship Models of Disinfection By-Products' Quantum Chemical Descriptors and Toxicities." FIU Digital Commons, 2009. http://digitalcommons.fiu.edu/etd/174.
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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.
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Chen, Rena Zhanglei. "Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by-products." FIU Digital Commons, 2009. http://digitalcommons.fiu.edu/etd/2145.
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Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital ( ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R2 by approximately 2% to 13% for different DBP classes.
The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.
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Wang, Shaomeng. "Quantitative structure activity relationship study of anti-Mycobacterium avium agents and the calculation of some physico-chemical properties of organic compounds." Case Western Reserve University School of Graduate Studies / OhioLINK, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=case1056656561.
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Baldasare, Corey Adam. "Quantum Chemical pKa Estimation of Carbon Acids, Saturated Alcohols, and Ketones via Quantitative Structure-Activity Relationships." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1598550823525731.
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Girschick, Tobias [Verfasser], Burkhard [Akademischer Betreuer] Rost, and Stefan [Akademischer Betreuer] Kramer. "Enhanced Small Molecule Similarity for Quantitative Structure-Activity Relationship Modeling and Cheminformatics Applications / Tobias Girschick. Gutachter: Burkhard Rost ; Stefan Kramer. Betreuer: Burkhard Rost." München : Universitätsbibliothek der TU München, 2014. http://d-nb.info/1052995357/34.
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Magdziarz, Tomasz. "Sektorowy formalizm porównawczej analizy powierzchni cząsteczkowej (s-CoMSA) - zastosowanie do modelowania zależności struktura-aktywność." Doctoral thesis, Katowice : Uniwersytet Śląski, 2007. http://hdl.handle.net/20.500.12128/5132.
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Celem pracy jest: Opracowanie nowej metody obliczania deskryptorów cząsteczkowych s-CoMSA
(ang. sector-comparative molecular surface analysis); w metodzie tej przestrzeń
cząsteczkowa jest dzielona za zbiór sześciennych sektorów,
● Szeroko rozumiana optymalizacja metody s-CoMSA,
● Analiza QSAR oraz SAR wybranych szeregów związków aktywnych biologicznie z
wykorzystaniem metody s-CoMSA oraz innych metod 3D-QSAR.
W zakres pracy wchodzi: Opracowanie formalizmu metody s-CoMSA,
● Zaprogramowanie procedur analizy s-CoMSA,
● Badanie modeli s-CoMSA aktywności biologicznej wybranych szeregów związków
organicznych, w tym:
• szeregu steroidów o powinowactwie do globuliny wiążącej kortykosteroidy
(ang. corticosteroid-binding globulin – CBG),
• inhibitorów wirusa HIV,
• inhibitorów reduktazy kwasu dihydrofoliowego.
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Buss, Joan L. "Mechanism of hydrolysis-activation of the cardioprotective antioxidant dexrazoxane and identification of more effective analogs by development of a quantitative structure-activity relationship describing imide hydrolysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ31967.pdf.
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Cardon, Sébastien. "Étude quantitative du rôle spécifique de glycosaminoglycanes dans le mécanisme d'internalisation de l'homéoprotéine engrailed 2." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEE041.
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Les homéoprotéines sont des facteurs de transcription importants au cours du développement des organismes vivants, capables notamment de voyager de cellule en cellule. Ces protéines comportent une longue extrémité N-terminale désordonnée, suivie de trois hélices α séparées par une boucle et un tour. Des études de relations structure-activité ont montré que des domaines cationiques (riches en K et R) particuliers dans ces protéines sont responsables de ces propriétés de transfert cellulaire leur permettant d’être secrétées et internalisées dans les cellules. Ces processus impliquent que ces protéines hydrophiles soient capables de franchir la membrane plasmique composée d'un coeur hydrophobe. La membrane plasmique est en effet composée d’une bicouche lipidique, dans laquelle sont insérées de nombreuses protéines, telles que les protéoglycanes portant des ramifications de glycosaminoglycanes (GAG), polysaccharides anioniques. Dans le but de comprendre au niveau moléculaire le processus d'entrée des homéoprotéines dans des cellules eucaryotes, différentes constructions protéiques ont été produites et étudiées : le peptide pénétrant les cellules correspondant à l'hélice 3 (H3), la séquence correspondant à l'homéodomaine (HD), l'homéodomaine étendu d'une séquence putative de liaison aux GAG (NLS-HD) et la protéine entière (En2). La quantification absolue de l’entrée de ces constructions dans des cellules CHO-K1 par spectrométrie de masse a mis en évidence une efficacité d'entrée meilleure pour H3 > NLS-HD > HD, ainsi que l’importance des GAG de surface dans le processus et plus particulièrement celui des héparanes sulfates (HS). Des expériences complémentaires d’ITC, de dichroïsme circulaire et de RMN ont permis d'identifier deux sites d’interaction avec l’héparine (un site principal de haute affinité et un site secondaire de plus basse affinité), interagissant principalement avec le polysaccharide par interactions électrostatiques. In fine, ces études conduisent à une meilleure compréhension moléculaire du processus d'internalisation des homéoprotéines dans des cellules eucaryotesHomeoproteins are important transcription factors during the development of living organisms, and are able to travel from cell to cell. These proteins contain a long N-terminal extremity structurally disordered, followed by three α helices separated by a U-turn. Structure-activity relation studies have shown that in these proteins, some cationic domains (rich in K and R) confer them the cellular transfer properties, allowing them to be secreted by and internalized into cells. These processes imply that the hydrophilic proteins are able to cross plasma membrane. Indeed, the plasma membrane possess a hydrophobic heart and is composed by a lipidic bilayer, in which numerous proteins are inserted, such as proteoglycans carrying glycosaminoglycan (GAG) ramifications, that belong to anionic polysaccharids. In order to understand the entry process of homeoproteins into eukaryotic cells at a molecular level, different proteic constructions have been produced and studied: the cell penetrating peptide corresponding to the third α helix (H3), the sequence corresponding to its homeodomain (HD), the homeodomain with an added putative GAG-binding domain (NLS-HD), and the wild-type protein Engrailed 2 (En2). The absolute mass spectrometry quantification of the peptide and proteins in cells shows a range of internalization efficiency as follows: H3 > NLS - HD > HD. It also highlights the importance of cell-surface GAGs in the internalization and more particularly that of heparan sulfates (HS). Complementary experiments of ITC, circular dichroism and NMR have shown two interaction sites for the heparin (one principal site of high affinity and a secondary site showing a lower affinity) both interacting mainly with polysaccharidic residues using electrostatic interactions. In fine, these studies lead to a better molecular understanding of homeoproteins internalization process in eukaryotic cells
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Andersson, Karl. "Characterization of Biomolecular Interactions Using a Multivariate Approach." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4322.
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Bonano, Julie S. "Structural Determinants of Abuse-Related Neurochemical and Behavioral Effects of Para-Substituted Methcathinone Analogs in Rats." VCU Scholars Compass, 2015. http://scholarscompass.vcu.edu/etd/3911.
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Methcathinone (MCAT) is the β-ketone analog of methamphetamine, and like its amphetamine analog, MCAT functions as a monoamine releaser that selectively promotes the release of dopamine (DA) and norepinephrine (NE) over serotonin (5-HT). MCAT produces amphetamine-like psychostimulant effects and is classified as a Schedule I drug of abuse by the United States Drug Enforcement Administration (DEA). Recently, synthetic MCAT analogs have emerged as designer drugs of abuse in Europe and the United States and have been marketed under deceptively benign names like “bath salts” in an attempt to evade legal restriction. These dangerous, recently emergent and novel drugs of abuse display varying selectivity to promote release of DA/NE vs. 5-HT, and selectivity for DA neurotransmission is believed to correlate with abuse liability. The goal of this dissertation was to conduct preclinical research to examine structural determinants of abuse-related behavioral and neurochemical effects produced by a series of synthetic MCAT analogs. Specifically, this project focused on one feature of the methcathinone scaffold: the para substituent of the benzene ring. A series of six novel MCAT analogs will be examined to evaluate how physicochemical parameters (steric, Es; electronic, σp; lipophilic, πp) of the para substituent influence in vitro monoamine transporter selectivity as well as in vivo neurochemical and behavioral effects. Results from this body of work implicate steric factors as being particularly important in determining a compound’s abuse-related neurochemical and behavioral effects. Thus, these data not only offer an improved understanding of the mechanism of abuse-related drug effects produced by synthetic MCAT analogs, but also help in the generation of homology models of the human DA and 5-HT transporters (DAT and SERT, respectively).
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Da, Chenxiao. "The Development and Applications of the HINT Scoring Function: Exploring Colchicine-Site Anticancer Agents and Tautomerism." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3002.
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The overall aim of this work was to apply HINT, an empirical scoring function based on the understanding of hydrophobicity, to analyze and predict the binding affinities and biological activities of colchicine-site anticancer agents. The second, concurrent aim was to improve the scoring function by incorporating tautomerism within the modeling process. Our belief is that proper evaluation of tautomeric forms for small molecules will improve performance of virtual screening. The novel pyrrole-based compounds targeting the colchicine site were docked into the receptor using HINT as a rescoring function. Two distinct binding modes dictated by the size and shape of a subpocket were predicted to differentiate the highly active compounds from the weak ones. Of the residues predicted to participate in binding for the active binding mode, Cys241β was revealed to form a weak but critical hydrogen bond with the ligand. A larger collection of colchicine-site agents, biologically tested in the same laboratory including our pyrrole-based compounds were subject to 3D quantitative structure-activity relationship (QSAR) study. Using results on docking the pyrrole compounds as a guide, relative binding poses and QSAR models were built to facilitate ligand design and optimization. A new 3D modeling approach was introduced to visually highlight the unique features of highly active compounds and the commonality of all compounds in the dataset using HINT maps and successfully tested on the colchicine-site agents. These results will provide valuable guidance in the future design and development of new colchicine-site agents. To incorporate tautomerism within HINT, we proposed and developed two workflow approaches: a general search tool using a simple and intuitive algorithm analyzing hydrogen shift patterns to identify and enumerate tautomeric structures, and a database that contains commonly observed tautomeric structures. The first approach was designed for small-scale docking studies and the second approach was designed for large-scale virtual screening. The tautomer module in HINT will give more accurate modeling results when the compound encountered is able to tautomerize.
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Stenberg, Mia. "In silico tools in risk assessment : of industrial chemicals in general and non-dioxin-like PCBs in particular." Doctoral thesis, Umeå universitet, Kemiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-50609.
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Industrial chemicals in European Union produced or imported in volumes above 1 tonne annually, necessitate a registration within REACH. A common problem, concerning these chemicals, is deficient information and lack of data for assessing the hazards posed to human health and the environment. Animal studies for the type of toxicological information needed are both expensive and time consuming, and to that an ethical aspect is added. Alternative methods to animal testing are thereby requested. REACH have called for an increased use of in silico tools for non-testing data as structure-activity relationships (SARs), quantitative structure-activity relationships (QSARs), and read-across. The main objective of the studies underlying this thesis is related to explore and refine the use of in silico tools in a risk assessment context of industrial chemicals. In particular, try to relate properties of the molecular structure to the toxic effect of the chemical substance, by using principles and methods of computational chemistry. The initial study was a survey of all industrial chemicals; the Industrial chemical map was created. A part of this map was identified including chemicals of potential concern. Secondly, the environmental pollutants, polychlorinated biphenyls (PCBs) were examined and in particular the non-dioxin-like PCBs (NDL-PCBs). A set of 20 NDL-PCBs was selected to represent the 178 PCB congeners with three to seven chlorine substituents. The selection procedure was a combined process including statistical molecular design for a representative selection and expert judgements to be able to include congeners of specific interest. The 20 selected congeners were tested in vitro in as much as 17 different assays. The data from the screening process was turned into interpretable toxicity profiles with multivariate methods, used for investigation of potential classes of NDL-PCBs. It was shown that NDL-PCBs cannot be treated as one group of substances with similar mechanisms of action. Two groups of congeners were identified. A group including in general lower chlorinated congeners with a higher degree of ortho substitution showed a higher potency in more assays (including all neurotoxic assays). A second group included abundant congeners with a similar toxic profile that might contribute to a common toxic burden. To investigate the structure-activity pattern of PCBs effect on DAT in rat striatal synaptosomes, ten additional congeners were selected and tested in vitro. NDL-PCBs were shown to be potent inhibitors of DAT binding. The congeners with highest DAT inhibiting potency were tetra- and penta-chlorinated with 2-3 chlorine atoms in ortho-position. The model was not able to distinguish the congeners with activities in the lower μM range, which could be explained by a relatively unspecific response for the lower ortho chlorinated PCBs.Den europeiska kemikalielagstiftningen REACH har fastställt att kemikalier som produceras eller importeras i en mängd över 1 ton per år, måste registreras och riskbedömmas. En uppskattad siffra är att detta gäller för 30 000 kemikalier. Problemet är dock att data och information ofta är otillräcklig för en riskbedömning. Till stor del har djurförsök använts för effektdata, men djurförsök är både kostsamt och tidskrävande, dessutom kommer den etiska aspekten in. REACH har därför efterfrågat en undersökning av möjligheten att använda in silico verktyg för att bidra med efterfrågad data och information. In silico har en ungefärlig betydelse av i datorn, och innebär beräkningsmodeller och metoder som används för att få information om kemikaliers egenskaper och toxicitet. Avhandlingens syfte är att utforska möjligheten och förfina användningen av in silico verktyg för att skapa information för riskbedömning av industrikemikalier. Avhandlingen beskriver kvantitativa modeller framtagna med kemometriska metoder för att prediktera, dvs förutsäga specifika kemikaliers toxiska effekt. I den första studien (I) undersöktes 56 072 organiska industrikemikalier. Med multivariata metoder skapades en karta över industrikemikalierna som beskrev dess kemiska och fysikaliska egenskaper. Kartan användes för jämförelser med kända och potentiella miljöfarliga kemikalier. De mest kända miljöföroreningarna visade sig ha liknande principal egenskaper och grupperade i kartan. Genom att specialstudera den delen av kartan skulle man kunna identifiera fler potentiellt farliga kemiska substanser. I studie två till fyra (II-IV) specialstuderades miljögiftet PCB. Tjugo PCBs valdes ut så att de strukturellt och fysiokemiskt representerade de 178 PCB kongenerna med tre till sju klorsubstituenter. Den toxikologiska effekten hos dessa 20 PCBs undersöktes i 17 olika in vitro assays. De toxikologiska profilerna för de 20 testade kongenerna fastställdes, dvs vilka som har liknande skadliga effekter och vilka som skiljer sig åt. De toxicologiska profilerna användes för klassificering av PCBs. Kvantitativa modeller utvecklades för prediktioner, dvs att förutbestämma effekter hos ännu icke testade PCBs, och för att få ytterligare kunskap om strukturella egenskaper som ger icke önskvärda effekter i människa och natur. Information som kan användas vid en framtida riskbedömning av icke-dioxinlika PCBs. Den sista studien (IV) är en struktur-aktivitets studie som undersöker de icke-dioxinlika PCBernas hämmande effekt av signalsubstansen dopamin i hjärnan.
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Gbeddy, Gustav Kudjoe Seyram. "Transformation and degradation of organic pollutants on urban road surfaces." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/203905/15/9514791_gustav_gbeddy_thesis.pdf.
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This thesis is an important milestone in understanding the transformation and degradation processes of polycyclic aromatic hydrocarbons (PAHs). PAHs are indicator organic pollutants in urban road dust and some of their transformed products are extremely hazardous. Analytical methods were developed and optimized to comprehensively measure PAHs and their transformed products. The optimized method and relevant statistical techniques were used to assess the ultraviolet photon driven processes of the pollutants. A novel risk assessment approach was developed to evaluate the carcinogenic health risk posed by the pollutants. The new knowledge gained is vital in addressing the challenges posed by these pollutants.
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Madi, Moussa Désiré. "Caractérisation de l’activité contre les bactéries à Gram-négatif, expression hétérologue et étude de la relation structure activité des bactériocines produites par Lacticaseibacillus paracasei CNCM I-5369." Electronic Thesis or Diss., Université de Lille (2018-2021), 2021. http://www.theses.fr/2021LILUR060.
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L’usage abusif et excessif des antibiotiques a exacerbé le phénomène d’antibiorésistance, à travers la planète. Aujourd’hui, la lutte contre l’antibiorésistance est devenue une priorité mondiale en matière de santé publique. En effet, chaque année, elle est responsable de plus de 700,000 décès dans le monde et d'ici 2050, elle causera plus de 10 millions de décès par an, si des actions concrètes ne sont pas mises en place afin de freiner le développement de ce phénomène. En plus des pertes humaines, le coût financier des soins afférents à l’antibiorésistance pourra atteindre 100,000 milliards de dollars dans le monde. Pour faire face à cette crise annoncée, plusieurs stratégies innovantes, parmi lesquelles l’usage des peptides antimicrobiens (PAMs), ont été proposées. Dans cette perspective, les bactériocines, qui sont des PAMs synthétisés par voie ribosomique pourraient contribuer à la solution thérapeutique. Récemment, la souche Lacticaseibacillus paracasei CNCM I-5369 s’est particulièrement distinguée pour son activité contre des germes pathogènes à Gram-négatif. Cette activité est due à 5 nouvelles bactériocines codées par des gènes chromosomiques orf010, orf012, orf023, orf030 et orf038. Toutefois, l’activité est pH-dépendante, c’est-à-dire qu’elle est exercée, uniquement à une valeur de pH ≤ 5. Dans le cadre de cette thèse, nous avons dans un premier temps, vérifiée l’expression de ces gènes lors de la croissance de la bactérie, en utilisant la technique de qPCR. Ainsi, nous avons observé que ces 5 gènes sont exprimés après 24 h de croissance, de façon concomitante à l’apparition de l’activité antimicrobienne indiquant ainsi un lien entre l’expression génique et la production des cinq bactériocines. Ces 5 bactériocines ont été exprimées en système hétérologue chez Escherichia coli Rosetta. Seule la bactériocine codée par orf030, appelée lacticaséicine 30, a pu être produite en grande quantité, contrairement aux autres bactériocines qui ont été produites mais demeurent piégées dans la fraction insoluble. Dans un deuxième temps, nous avons étudié la relation entre la structure de la lacticaséicine 30 et son activité contre les bactéries à Gram-négatif. Les prédictions de structure ont suggéré une organisation en 5 hélices de la lacticaséicine 30. La proportion d’hélice-α était plus importante à pH 5 qu’à pH 7. Pour identifier les régions impliquées dans l’activité contre les bactéries à Gram-négatif, nous avons produit des peptides dérivés de la lacticaséicine 30 par une approche de biologie moléculaire. Ces peptides dérivés sont obtenus en réduisant leurs tailles, ou en insérant des mutations ciblées dans différentes régions. Ainsi, nous avons généré des formes plus courtes de la lacticaséicine 30, contenant soit sa région N-terminale (acides aminés 1 à 39), soit les régions centrale et C-terminale (acides aminés 40 à 111). De la même manière, un peptide dérivé contenant uniquement la première hélice de la région N-terminale a été également produite. Les mutations introduisant des substitutions des acides aminés ont été introduites au sein des hélices-α. Au regard de leurs activités, ces peptides dérivés ont permis de localiser l’activité antibactérienne essentiellement dans la région N-terminale, et nécessite à minima deux hélices-α. Par ailleurs, l’activité de ces variants peptidiques E32G, T33P, T52P et D57G reste sensiblement identique, contrairement à celles des variants E6G, T7P, D57G T52P, A74P, Y78S, Y93S et A97P qui ont été significativement altérées. Dans la dernière partie, nous avons testé l’activité de la lacticaséicine 30 contre un panel de souches cliniques à Gram-négatif et portant des résistances à la colistine. Les résultats obtenus ont mis en lumière une synergie entre la lacticaséicine 30 et la colistine et la réduction significative de l’expression des gènes mcr-1 et mcr-9, responsables de la résistance à la colistineThe excessive use of antibiotics has exacerbated the phenomenon of antibiotic resistance throughout the world. Today, the fight against antibiotic resistance has become a global public health priority. Indeed, every year, it is responsible for more than 700,000 deaths in the world and by 2050, it will cause more than 10 million deaths per year, if concrete actions are not implemented to curb the development of this phenomenon. In addition to the human losses, the financial cost of antibiotic resistance-related care could reach 100,000 billion dollars worldwide. To face this crisis, several innovative strategies, including the use of antimicrobial peptides (AMPs), have been proposed. In this perspective, bacteriocins, which are ribosomally APMs, could contribute to the therapeutic solution. Recently, the Lacticaseibacillus paracasei CNCM I-5369 strain has been particularly distinguished for its activity against Gram-negative pathogens. This activity is due to 5 new bacteriocins encoded by chromosomal genes orf010, orf012, orf023, orf030 and orf038. However, the activity is pH-dependent, i.e., it is exerted, only at a pH value ≤ 5. In the framework of this thesis, we first verified the expression of these genes during the growth of the bacteria, using the qPCR technique. Thus, we observed that these 5 genes were expressed after 24 h of growth, concomitantly with the appearance of antimicrobial activity indicating a possible link between gene expression and the production of the five bacteriocins. These 5 bacteriocins were expressed in a heterologous system in Escherichia coli Rosetta. It should be noted that only the bacteriocin encoded by orf030, called lacticaseicin 30, could be produced in large quantities, in contrast to the other bacteriocins which were produced but remain trapped in the insoluble fraction. In a second step, we investigated the relationship between the structure of lacticaseicin 30 and its activity against Gram-negative bacteria. Structural predictions suggested a 5-helix organization of lacticaseicin 30. The proportion of helix-α was greater at pH 5 than at pH 7. To identify the regions involved in the activity against Gram-negative bacteria, we produced lacticaseicin 30-derived peptides by a molecular biology approach. These derived peptides are obtained by reducing their sizes, or by inserting targeted mutations in different regions. Thus, we generated shorter forms of lacticaseicin 30, containing either its N-terminal region (amino acids 1 to 39), or the central and C-terminal regions (amino acids 40 to 111). Similarly, a derivative peptide containing only the first helix of the N-terminal region was also produced. Mutations introducing amino acid substitutions were introduced within the α-helices. With regard to their activities, these derived peptides localized antibacterial activity mainly in the N-terminal region, and requires at least two helix-αs. Furthermore, the activity of these peptide variants E32G, T33P, T52P, and D57G remained essentially the same, unlike to those of the variants E6G, T7P, D57G T52P, A74P, Y78S, Y93S, and A97P, which were significantly impaired. In the last part, we tested the activity of lacticaseicin 30 against a panel of Gram-negative clinical strains with colistin resistance. The results obtained highlighted a synergy between lacticase 30 and colistin and a significant reduction of the expression of the mcr-1 and mcr-9 genes, responsible for colistin resistance
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Larsson, Malin. "Computational methods for analyzing dioxin-like compounds and identifying potential aryl hydrocarbon receptor ligands : multivariate studies based on human and rodent in vitro data." Doctoral thesis, Umeå universitet, Kemiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-139487.
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Polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) are omnipresent and persistent environmental pollutants. In particular, 29 congeners are of special concern, and these are usually referred to as dioxin-like compounds (DLCs). In the European Union, the risks associated with DLCs in food products are estimated by a weighted sum of the DLCs’ concentrations. These weights, also called toxic equivalency factors (TEFs), compare the DLCs’ potencies to the most toxic congener, 2,3,7,8-tetrachloro-dibenzo-p-dioxin (2378- TCDD). The toxicological effects of PCDD/Fs and PCBs are diverse, ranging from chloracne and immunological effects in humans to severe weight loss, thymic atrophy, hepatotoxicity, immunotoxicity, endocrine disruption, and carcinogenesis in rodents. Here, the molecular structures of DLCs were used as the basis to study the congeneric differences in in vitro data from both human and rodent cell responses related to the aryl hydrocarbon receptor (AhR). Based on molecular orbital densities and partial charges, we developed new ways to describe DLCs, which proved to be useful in quantitative structure-activity relationship modeling. This thesis also provides a new approach, the calculation of the consensus toxicity factor (CTF), to condense information from a battery of screening tests. The current TEFs used to estimate the risk of DLCs in food are primarily based on in vivo information from rat and mouse experiments. Our CTFs, based on human cell responses, show clear differences compared to the current TEFs. For instance, the CTF of 23478-PeCDF is as high as the CTF for 2378-TCDD, and the CTF of PCB 126 is 30 times lower than the corresponding TEF. Both of these DLCs are common congeners in fish in the Baltic Sea. Due to the severe effects of DLCs and their impact on environmental and human health, it is crucial to determine if other compounds have similar effects. To find such compounds, we developed a virtual screening protocol and applied it to a set of 6,445 industrial chemicals. This protocol included a presumed 3D representation of AhR and the structural and chemical properties of known AhR ligands. This screening resulted in a priority list of 28 chemicals that we identified as potential AhR ligands.
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Alencar, Filho Edilson Beserra de. "Estudos da relação quantitativa estrutura-atividade (QSAR) de adutos de Morita-Baylis-Hillman bioativos contra Leishmania amazonensis." Universidade Federal da Paraíba, 2012. http://tede.biblioteca.ufpb.br:8080/handle/tede/7163.
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The Morita-Baylis-Hillman Adducts (MBHA) is a class of molecules studied by our research group on synthetic, theoretical and bioactivity aspects. In this work, we present Quantitative Structure-Activity Relationship (QSAR) models involving 32 aromatic MBHA. Initially, the most stable conformations of thirty-two MBHA were investigated by theoretical methods, which were used to construct models. For this study, were obtained potential energy curves using AM1 semi-empirical method, considering rotational degrees of freedom (sigma bonds). From these curves, the less energy conformation to each molecule was selected and optimized at B3LYP/6- 31+G(d) level, considering solvent effects through Polarizable Continuum Model (PCM). Proton Nuclear Magnetic Ressonance data are in agreement with the conformational study. Intramolecular Hydrogen Bonds (IHB) are presents in the most of the studied compounds, according to structural characterization and QTAIM calculations. Curiously, compounds that showed hydrogen bonds involving the nitro and hydroxyl groups have the best values of biological activity (IC50). An explanation is based on redox mechanism of action of nitrocompounds. NBO (Natural Bond Orbital) charges and LUKO (Lowest Unoccupied Kohn-Sham Orbitals) analysis at the ortho-nitro group are in agreement with these analyses. Considering quantum calculations and structural observations, four descriptors were selected a priori and submitted to a QSAR study using PLS (Partial Least Squares) and MLR (Multiple Linear Regression) modeling. A second QSAR approach was made from the another set of descriptors obtained through the online platform E-DRAGON, which were submitted to a variable selection method. The quality parameters obtained for models indicate that both are robust and predictive.
Os Adutos de Morita-Baylis-Hillman (AMBH) compreendem uma classe de moléculas investigadas por nosso grupo de pesquisas nos aspectos sintéticos, teóricos e de bioatividade. Neste trabalho, apresentamos modelos de Relação Quantitativa entre a Estrutura Química e a Atividade Leishmanicida (QSAR) envolvendo 32 AMBH aromáticos. Deste modo, inicialmente foram investigadas as conformações mais estáveis de cada composto através de métodos teóricos, as quais foram utilizadas na construção dos modelos. Foram obtidas curvas de energia potencial utilizando o método semi-empírico AM1, considerando graus de liberdade rotacionais (ligações sigma). A partir destas curvas, a conformação de menor energia para cada molécula foi selecionada e otimizada ao nível B3LYP/6-31+G(d), considerando os efeitos do solvente aquoso usando PCM ( Polarizable Continuum Model ). Dados espectroscópicos de Ressonância Magnética Nuclear de prótons corroboraram o estudo conformacional. Ligações de Hidrogênio Intramoleculares (LHI) se mostraram presentes na maioria das moléculas estudadas, conforme caracterização estrutural e cálculos QTAIM ( Quantum Theory Atoms in Molecules ). Curiosamente, os compostos que apresentaram Ligações de Hidrogênio envolvendo o grupo nitro (NO2) e a hidroxila (OH) possuem melhores valores de atividade biológica (menor IC50). Uma explicação está baseada no mecanismo de ação redox de nitrocompostos. Observação das cargas NBO ( Natural Bond Orbitals ) e análise dos orbitais de fronteira LUKO ( Lowest Unoccupied Kohn-Sham Orbitals ) ao nível do grupo orto-nitro estão de acordo com estas análises. Considerando os cálculos quânticos, bem como observações estruturais, quatro descritores foram selecionados a priori e submetidos a um estudo QSAR ( Quantitative Structure- Activity Relationships ) utilizando modelagem PLS ( Partial Least Squares ) e MLR ( Multiple Linear Regression ). Uma segunda abordagem QSAR foi realizada a partir de outro conjunto de descritores obtidos através da plataforma online E-DRAGON, os quais foram submetidos ao método de seleção de variáveis OPS ( Ordered Predictor Selection ). Os parâmetros de qualidade obtidos para os modelos indicam que ambos são robustos e preditivos.
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Chen, Jonathan Jun Feng. "Data Mining/Machine Learning Techniques for Drug Discovery: Computational and Experimental Pipeline Development." University of Akron / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=akron1524661027035591.
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Ribeiro, Taisa Pereira Piacentini. "Estudo teórico (modelagem molecular e QSAR) de compostos quinolínicos com atividade herbicida." Universidade Estadual do Oeste do Paraná, 2017. http://tede.unioeste.br/handle/tede/2964.
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The search for new herbicides to control herbicides-resistant weeds is necessary to attend the rising demand of food from the world’s population. This work was divided into two parts. The first aimed to obtain a model of QSAR-2D, 3D and hybrid to predict compounds with activity to the inhibition of photosynthesis. For this, was used a data set of 44 quinoline analogues described in the literature as PET inhibitors, and all tested in the same bioassay method. For construction of models were used the programs QSAR Modeling and Pentacle. The obtained models A, C and D, were approved in the validation tests (internal and external), they are robust and with good predictive capacity. The second part of studie aimed to identify a pharmacophore model, for select compounds from the data set of first part, aiming to use as a tool for virtual screening. The research resulted in 86,560 compounds, and thus several screening filters were applied according to Briggs rule of three, in silico toxicity analyzes, unsupervised pattern recognition (PCA), and docking studies. As a result, 28 compounds remained, all of which showed potential to be herbicides, through the prediction using the obtained QSAR models, however, only the model D proved to be reliable for prediction the virtual screening. Finally, we selected the ten compounds that presented the highest predictive value of PET inhibition activity, using the model D.
A busca de novos herbicidas para o controle de ervas daninhas resistentes é necessária para atender à crescente demanda alimentar da população mundial. Este trabalho foi dividido em duas partes. A primeira teve por objetivo a obtenção de modelos de QSAR-2D, 3D e híbrido para previsão de compostos com atividade de inibição da fotossíntese. Para isso, foi utilizado um conjunto de dados formado por 44 análogos de quinolina descritos na literatura como inibidores do PET e todos testados pela mesma metodologia de ensaio biológico. Para construção dos modelos foram utilizados os programas QSAR Modeling e Pentacle. Os modelos A, C e D obtidos foram aprovados nos testes de validação (interna e externa), são robustos e com boa capacidade de previsão. A segunda parte do estudo teve como objetivo a identificação de um modelo farmacofórico, para compostos selecionados do conjunto de dados da primeira parte, visando o uso do mesmo como ferramenta para triagem virtual. A pesquisa resultou em 86.560 compostos, e assim foram aplicados diversos filtros de seleção de acordo com a regra de três de Briggs, análises “in silico” de toxicidade, técnica de reconhecimento de padrões não supervisionados (PCA), e estudos e ancoramento molecular. Como resultado, restaram 28 compostos, sendo que todos mostraram potencial para serem herbicidas, através da previsão utilizando os modelos de QSAR obtidos, porém apenas o modelo D mostrou-se confiável para previsão da triagem virtual. Por fim, foram selecionados os dez compostos que apresentaram maior valor de previsão de atividade de inibição do PET, utilizando o modelo D.
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Jelena, Ćurčić. "In silico određivanje fizičko-hemijskih, farmakokinetskih i toksikoloških parametara i in vitro ispitivanje antiproliferativne aktivnosti novosintetisanih derivata N-sukcinimida." Phd thesis, Univerzitet u Novom Sadu, Medicinski fakultet u Novom Sadu, 2020. https://www.cris.uns.ac.rs/record.jsf?recordId=113945&source=NDLTD&language=en.
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Sukcinimidi su jedinjenja koja pokazuju višestruke farmakološke efekte uključujući i antiproliferativnu aktivnost, zahvaljujući prisustvu farmakofore sa dva hidrofobna regiona i dva regiona bogata elektronima. Savremeni dizajn lekova ima za cilj da se modifikacijama u strukturi (promena vrste, položaja i orijentacije supstituenata) i in silico računarskim metodama predvide i optimizuju farmakokinetske osobine i bezbednosni profil kandidata za lek. U ranoj fazi razvoja lekova se koriste postojeće baze podataka o molekulskim, farmakokinetskim i toksikološkim parametrima već ispitanih jedinjenja i pomoću matematičkih modela i algoritama predviđaju se osobine novih molekula, eliminišu se neodgovarajući kandidati i postiže se ušteda u vremenu i materijalnim sredstvima. Da se ispitaju fizičko-hemijske karakteristike 11 novosintetisanih metil-etil-N-aril-sukcinimida na osnovu strukture, primenom različitih softverskih paketa; da se na osnovu strukture odrede farmakokinetski i toksikološki parametri, primenom različitih softverskih paketa; da se ispita retenciono ponašanje, odnosno odrede retencione konstante za svako jedinjenje primenom visokoefikasne hromatografije na tankom sloju (HP-TLC) i ispita mogućnost primene retencionih konstanti kao mere lipofilnosti ispitivanih jedinjenja; da se ispita antiproliferativna aktivnost na odabranim kulturama ćelija karcinoma i na zdravim ćelijama fibroblasta pluća; da se analizom molekulskog dokinga ustanovi vezivanje za estrogene receptore. Ispitano je retenciono ponašanje 11 novosintetisanih derivata sukcinimida primenom visokoefikasne hromatografije na tankom sloju (HP-TLC) obrnute faze uz primenu dvokomponentne smeše vode i organskog rastvarača (metanola, acetonitrila ili acetona), sa odgovarajućim zapreminskim udelom organskog rastvarača kao mobilne faze. Iz razvijenih hromatograma su izračunate retencione konstante RM0 i S. Logaritam podeonog koeficijenta (logP) određen je in silico, korišćenjem različitih računarskih programa. In silico su određene fizičko-hemijske karakteristike, farmakokinetski parametri, toksikološki parametri, akvatična toksičnosti i afinitet vezivanja za estrogene receptore. Izračunate su vrednosti afiniteta za 4 vrste receptora (G-protein spregnuti receptori, jonski kanali, inhibitori kinaza, nuklearni receptori). Antiproliferativna aktivnost ispitivanih derivata sukcinimida određena je primenom kolorimetrijskog testa sa tetrazolijum solima (MTT testa) na komercijalnim kulturama ćelija (MRC-5, A549, HeLa, MDA-MB-231, MCF-7, HT-29) i izračunate su IC50 vrednosti. Urađena je i doking analiza sukcinimida prema ERA (estrogen receptor alfa) i ERB (estrogen receptor beta) i dobijene su vrednosti energije formiranja kompleksa sa posmatranim receptorima (MolDock Score). Statistički najznačajnije linearne korelacije dobijene su između eksperimentalno određenih hromatografskih parametara (RM0 i S) i in silico parametara lipofilnosti MlogP i ClogP. Ispitivanjem uticaja promene RM0 i S na farmakokinetske karakteristike dobijeni su rezultati koji pokazuju paraboličnu zavisnost konstante apsorpcije (Ka) i procenta vezivanja za proteine plazme (PPB) od posmatranih retencionih konstanti, dok je zavisnost sa volumenom distribucije (Vd) i sposobnošću prolaska kroz krvno-moždanu barijeru (logBBB) bila linearnog tipa. Toksičnost ispitivanih jedinjenja, procenjena na osnovu in silico dobijenih LD50 vrednosti, nije bila viša od toksičnosti već registrovanih lekova sa strukturom sukcinimida, i dala je parabolične zavisnosti u odnosu na RM0 i S vrednosti. Eksperimentalno nijedno od ispitivanih jedinjenja nije pokazalo aktivnost u odnosu na zdrave fibroblaste pluća. Najznačajniju antiproliferativnu aktivnost (najniže IC50) su pokazala jedinjenja 6 i 7 u odnosu na ćelije linije MCF-7 i jedinjenje 11 u odnosu na A549 ćelijsku liniju. Doking analiza je pokazala niže energije formiranja kompleksa sa ERA, u odnosu na ERB. Eksperimentalno određeni parametri RM0 i S se mogu koristiti kao alternativne i pouzdane mere lipofilnosti analiziranih sukcinimida. Ispitivana jedinjenja pokazuju povoljne fizičko-hemijske karakteristike, predviđene in silico metodama i povoljne farmakokinetske karakteristike: male vrednosti konstante apsorpcije, umeren volumen distribucije, povoljan afinitet vezivanja za proteine plazme, favorizovan prolazak kroz krvno-moždanu barijeru za lipofilnija jedinjenja. Procenjuje se da sva ispitivana jedinjenja, izuzev derivata sa –CN supstituentom, imaju zahtevani nizak stepen toksičnosti. Po antiproliferativnoj aktivnosti u odnosu na ćelije ER-zavisnog karcinoma dojke (MCF-7) izdvajaju se jedinjenja sa metil i nitro supstituentom u para položaju. Na osnovu malih energija formiranja kompleksa sa ERA, koji su eksprimirani na ćelijama MCF-7 linije, pretpostavlja se da bi mehanizam njihovog delovanja delimično mogao biti objašnjen uticajem na ERA, ali su potrebna dodatna istraživanja na tom polju.Succinimides have exhibited various pharmaceutical effects including antiproliferative activity due to an important structural fragment (a pharmacophore) presented in form of two hydrophobic regions and two electron-rich centers. Current development of new drugs involves modifications in structure (type, position and orientation of substituents) and usage of in silico computational programs to predict and optimize pharmacokinetic and safety profile of drug candidates. In early phase of drug development, databases regarding the molecular, pharmacokinetic and toxicological parameters of already tested compounds are used, mathematical models and algorithms are applied for predicting the properties of new molecules and inadequate candidates are eliminated saving time and resources. Determination of physico-chemical properties of the analyzed methyl-ethyl-N-phenilsuccinimide derivatives by software packages; virtual pharmacokinetic and toxicology screening; investigation of retention behavior of the compounds by the reversed-phase HPTLC analysis and calculation of retention constants and their correlation with lipophilicity; in vitro evaluation of antiproliferative activity toward five carcinoma cell lines and normal fetal lung cell line; molecular behavior study on target estrogen receptors by molecular docking and correlation of antiproliferative activity toward ER+ breast carcinoma cell lines and in silico estrogen receptor affinity binding. Retention behavior of 11 newly synthesized succinimide derivatives was determined by reversed phase high performance thin layer chromatography (RP HPTLC) with the application of two-component mixtures water - organic solvent (methanol, acetonitrile or acetone) with adequate volume fractions of the organic modifier. After chromatographic development RM0 and S parameters were calculated. The logarithm of partition coefficient, logP for the analyzed compounds were calculated by different softwares. Physico-chemical properties, pharmacokinetic and toxicological parameters, aquatic toxicity and relative affinity to estrogen receptors were predicted in silico. The affinity toward 4 types of receptors (G-proteine coupled receptors, ion channels, kinase inhibitors, nuclear receptors) were calculated as well. Standard MTT assay was applied to evaluate cytotoxic activities of the analyzed succinimides after cells were exposed. Antiproliferative activity were investigated toward commercial MRC-5, A549, HeLa, MDA-MB-231, MCF-7, HT-29 cell lines and IC50 values were calculated for each compound. MolDock Score that represents energy of binding to estrogen alfa and estrogen beta receptors was determined by molecular docking. Statistically significant linear correlations were determined between the chromatographic retention constants (RM0 and S) and calculated logP, and the best two were obtained in correlation of retention constants with MlogP and ClogP. The examination of RM0 and S influence on pharmacokinetics indicated parabolic dependence of the absorption constant (Ka) and plasma protein binding predictor (PPB) from the observed constants while the volume of distribution (Vd) and the ability to cross the brain blood barrier (logBBB) had linear association with the retention parameters. The toxicity of the analysed compounds evaluated in silico as LD50 on rodents was lower in comparison with the drugs with succinimide structure that are on the market and had parabolic correlation with the RM0 and S values. The experiments indicated that none of the compounds examined had cytotoxic activity toward the healthy lung fibroblast cells. The results of the in vitro assay shown that none of the investigated compounds demonstrated antiproliferative activity toward fetal lung cells. The most potent antiproliferative agents were compounds 6 and 7 toward MCF-7 cell line, and compound 11 toward A549 cell line. Molecular docking shown lower energy for binding to ERA in comparison to ERB.
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Durán, Alcaide Ángel. "Development of high-performance algorithms for a new generation of versatile molecular descriptors. The Pentacle software." Doctoral thesis, Universitat Pompeu Fabra, 2010. http://hdl.handle.net/10803/7201.
Full textAbstract:
The work of this thesis was focused on the development of high-performance algorithms for a new generation of molecular descriptors, with many advantages with respect to its predecessors, suitable for diverse applications in the field of drug design, as well as its implementation in commercial grade scientific software (Pentacle). As a first step, we developed a new algorithm (AMANDA) for discretizing molecular interaction fields which allows extracting from them the most interesting regions in an efficient way. This algorithm was incorporated into a new generation of alignmentindependent molecular descriptors, named GRIND-2. The computing speed and efficiency of the new algorithm allow the application of these descriptors in virtual screening. In addition, we developed a new alignment-independent encoding algorithm (CLACC) producing quantitative structure-activity relationship models which have better predictive ability and are easier to interpret than those obtained with other methods.El trabajo que se presenta en esta tesis se ha centrado en el desarrollo de algoritmos de altas prestaciones para la obtención de una nueva generación de descriptores moleculares, con numerosas ventajas con respecto a sus predecesores, adecuados para diversas aplicaciones en el área del diseño de fármacos, y en su implementación en un programa científico de calidad comercial (Pentacle). Inicialmente se desarrolló un nuevo algoritmo de discretización de campos de interacción molecular (AMANDA) que permite extraer eficientemente las regiones de máximo interés. Este algoritmo fue incorporado en una nueva generación de descriptores moleculares independientes del alineamiento, denominados GRIND-2. La rapidez y eficiencia del nuevo algoritmo permitieron aplicar estos descriptores en cribados virtuales. Por último, se puso a punto un nuevo algoritmo de codificación independiente de alineamiento (CLACC) que permite obtener modelos cuantitativos de relación estructura-actividad con mejor capacidad predictiva y mucho más fáciles de interpretar que los obtenidos con otros métodos.
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Chang, Yeong-Sheng, and 張詠昇. "Quantitative Structure-Activity Relationship of Flavonoid Antioxidants." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/15526659025148038238.
Full textAbstract:
碩士淡江大學
化學學系碩士班
93
Because of the large cost of people, materials, and money in the drug design process, a new investigation – Quantitative Structure-Activity Relationship ( QSAR ) , was used in this study. Recently, computer-aided drug design has emerged as a powerful technique in drug discovery process. Modern QSAR analysis developed using molecular structure descriptors and regression analysis techniques have found wide utility and acceptance. It was our aim to reduce the time of discovering process as well as help us to design better structures of flavonoids and more efficient antioxidants. A series of 118 flavonoid molecules were employed in all the calculations. All molecular structures were optimized at semi-empirical ( PM3 ) level. By use of structural , electronic energy, electrostatic energy, and bond energy as descriptors, the regression analysis was performed using. As the result, we suggested that the substituent position of the hydroxy group on the position 5 and 8 of the A ring could make an important role in the antioxidant property. Another key point might be the hydroxy group on the position 3 and 4 of the C ring. Besides, it had been shown good correlation between bond energy and antioxidant property. All the three energies ( electronic energy, electrostatic energy, and bond energy ) also affected the activity and helped us to construct the final QSAR model. It was clear from our QSAR analysis that all the descriptors involved encode very specific information about what factors affect the antioxidant properties of the flavonoids. Thus we could design more efficient antioxidants by using this model.
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"Quantitative structure activity relationship (QSAR) of platinum drugs." 2006. http://library.cuhk.edu.hk/record=b5896517.
Full textAbstract:
Leung Chung Wai.Thesis (M.Phil.)--Chinese University of Hong Kong, 2006.
Includes bibliographical references (leaves 142-146).
Abstracts in English and Chinese.
ABSTRACT (ENGISH) --- p.iii
ABSTRACT (CHINESS) --- p.v
ACHKNOWLEDGEMENTS --- p.vii
TABLE OF CONTENTS --- p.viii
Chapter CHAPTER 1 --- Introduction and Background
Chapter 1.1 --- Introduction of Platinum Drugs --- p.1
Chapter 1.2 --- Mechanism of Action of Cisplatin --- p.3
Chapter 1.3 --- Structure-Activity Relationships of the Platinum Drug 、 --- p.4
Chapter 1.4 --- QS AR Parameters --- p.9
Chapter 1.4.1 --- Chemical Hardness: Descriptor of Chemical Reactivity --- p.9
Chapter 1.4.2 --- Possible Reaction Pathway of Platinum Drugs --- p.12
Chapter 1.4.2.1 --- Proposed DNA Binding Pathway of Platinum Drugs --- p.13
Chapter 1.4.2.1.1 --- Hydrolysis Pathway --- p.13
Chapter 1.4.2.1.2 --- DNA Binding Pathway Involving the S-containing Biomolecules (Methionine Pathways) --- p.16
Chapter 1.4.2.1.3 --- Conclusion --- p.21
Chapter 1.5 --- Thesis Scope --- p.22
Chapter CHAPTER 2 --- Theory and Methodology
Chapter 2.1 --- Introduction --- p.24
Chapter 2.2 --- Density Functional Theory (DFT) --- p.24
Chapter 2.2.1 --- Kohn-Sham Theorem --- p.25
Chapter 2.2.2 --- Exchange-Correlation Energy Functional --- p.27
Chapter 2.3 --- Basis Set --- p.27
Chapter 2.3.1 --- Relativistic Effective Core Potential --- p.27
Chapter 2.3.2 --- Double-Zeta --- p.28
Chapter 2.3.3 --- Polarized Basis Set --- p.29
Chapter 2.4 --- Solvation Model --- p.30
Chapter 2.4.1 --- Continuum Model --- p.30
Chapter 2.4.1.1 --- Simple Solvation Model --- p.31
Chapter 2.4.1.1.1 --- Electrostatic Component --- p.31
Chapter 2.4.1.1.2 --- Dispersion-Repulsion Interaction --- p.33
Chapter 2.4.1.1.3 --- Cavitatoin Energy --- p.35
Chapter 2.4.1.2 --- Polarized Continuum Model --- p.36
Chapter 2.5 --- Methodology --- p.39
Chapter 2.5.1 --- Calculation of DFT Global Reactivity Index --- p.39
Chapter 2.5.1.1 --- Calculation for the Reaction Intermediates --- p.41
Chapter 2.5.2 --- Calculation of the Reaction Pathways --- p.42
Chapter CHAPTER 3 --- Results and Discussion
Chapter 3.1 --- Introduction --- p.49
Chapter 3.2 --- Optimized Structure against Experimental Geometry --- p.49
Chapter 3.3 --- Kohn-Sham Orbitals --- p.54
Chapter 3.3.1 --- Location of the HOMO and LUMO --- p.55
Chapter 3.4 --- Results of the DFT Reactivity Parameter --- p.57
Chapter 3.5 --- Chemical Structure of the Drugs in the QSAR --- p.64
Chapter 3.6 --- QSAR Analysis --- p.67
Chapter 3.6.1 --- The Overall QSAR Plot of the Platinum Drugs --- p.68
Chapter 3.6.1.1 --- Empirical Applicability of the QSAR on the Platinum(IV) Drugs --- p.70
Chapter 3.6.1.2 --- Detail QASR Study According to the Type of Platinum Drug --- p.71
Chapter 3.6.1.2.1 --- QSAR Study of the non-“trans-DACH´ح Platinum Drugs --- p.72
Chapter 3.6.1.2.1.1 --- "QSAR Equation of the non-""trαns-DACH"" Platinum Drugs" --- p.75
Chapter 3.6.1.2.2 --- QSAR Analysis for the Pt-trαns-DACH Drugs --- p.77
Chapter 3.6.1.2.2.1 --- "QSAR Study of trans-S,S-DACH Platinum Drugs" --- p.79
Chapter 3.6.1.2.2.2 --- "QSAR Study of trans-R,R-DACH Platinum Drugs" --- p.80
Chapter 3.6.1.3 --- Summary --- p.81
Chapter 3.7 --- QSAR Study of the Important Intermediates Using Chemical Hardness --- p.82
Chapter 3.7.1 --- Optimized Structure for the Intermediates --- p.84
Chapter 3.7.2 --- QSAR of the Dichloride Pt-Drugs Using Chemical Hardness of Parent Compounds --- p.90
Chapter 3.7.3 --- QSAR of the Dichloride Pt-Drugs Using Chemical Hardness of Hydrolysis Intermediates --- p.91
Chapter 3.7.4 --- QSAR of the Dichloride Pt-Drugs Using Chemical Hardness of Cyclic-Methionine Intermediates --- p.93
Chapter 3.7.5 --- Conclusion --- p.95
Chapter CHAPTER 4 --- Results and Discussion
Chapter 4.1 --- Introduction --- p.96
Chapter 4.2 --- Study Scheme --- p.97
Chapter 4.3 --- Optimized Structures --- p.98
Chapter 4.4 --- Comments on the Reliability of the Calculation Model --- p.103
Chapter 4.4.1 --- Reaction Profile in the Gas Phase --- p.104
Chapter 4.4.2 --- Reaction Profiles Using Simple Solvation Model --- p.105
Chapter 4.4.2.1 --- Defects of the Simple Solvation Model --- p.107
Chapter 4.4.3 --- Reaction Profile Using PCM-UAHF Solvation Model --- p.109
Chapter 4.4.3.1 --- Selection of the Reaction Parameters for the QSAR Study --- p.112
Chapter 4.5 --- QSAR Study of Platinum Drugs Using the Reaction Parameters (AG and ΔG+) --- p.121
Chapter 4.5.1 --- QSAR Analysis Using ΔG+(hydrolysis) --- p.121
Chapter 4.5.2 --- QSAR Analysis Using ΔG(hydrolysis) --- p.123
Chapter 4.5.3 --- QSAR Analysis Using ΔG+(guanine) --- p.125
Chapter 4.5.4 --- QSAR Analysis Using ΔG(guanine) --- p.127
Chapter 4.5.5 --- Further investigation of the Bidentate Pt-drugs DNA Binding --- p.129
Chapter 4.5.5.1 --- Calculation Model --- p.129
Chapter 4.5.5.2 --- Bidentate Pt-Drugs Reactions --- p.130
Chapter 4.5.5.3 --- Selection of the Calculated Model for the QSAR Study --- p.133
Chapter 4.5.5.4 --- QSAR Analysis Using ΔG+(guanine) for the Platinum Drugs with Bidentate Caboxylate Ligands --- p.136
Chapter 4.5.5.5 --- QSAR Analysis Using ΔG(guanine) for the Platinum Drugs with Bidentate Carboxylate Ligands --- p.137
Chapter 4.5.6 --- Conclusion --- p.138
Chapter CHAPTER 5 --- Conclusion Remarks and Future Works
Chapter 5.1 --- Conclusion --- p.140
Chapter 5.2 --- Future Works --- p.141
REFERENCES --- p.142
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Kana, Angela Robyn. "Quantitative structure-activity relationship prediction of anaerobic transformation of chloroacetanilide herbicides /." 2007. http://digital.library.okstate.edu/etd/umi-okstate-2359.pdf.
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Wu, Tong-Jung, and 吳東潤. "4D-Quantitative Structure-Activity Relationship Analysis on a Series of TW01 Analogues." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/81894918346305640242.
Full textAbstract:
碩士國立臺灣大學
資訊工程學研究所
97
Receptor-independent 4D-quantitative structure-activity relationships analyses were carried out on TW01 analogues, the possible tyrosine kinase inhibitors, to construct 4D-QSAR models for four human cancer cell lines, MDA-MB-231, PC-3, Hep3B and HUVEC, for which the -logIC50 values were measured. Total of 42 TW01 analogues were included in the training sets. It is divided into four subsets, 24 compounds for MDA-MB-231 and PC-3, eight compounds for Hep3B and 13 compounds for HUVEC. Distinct 4D-QSAR models were identified for MDA-MB-231 (three models with Q2 value of 0.716 to 0.795), PC-3 (three models with Q2 value of 0.827 to 0.844), Hep3B (two models with Q2 value of 0.839 and 0.884) and HUVEC training sets (three models with Q2 value of 0.742 to 0.812). Four sets of models yielded statistical significance (Q2 value larger than 0.7). After outlier removed from training set with Chauvenet''s criterion, more statistically significant models were available for MDA-MB-231 (one model with Q2 value of 0.824) and PC-3 training sets (four models with Q2 value of 0.839 to 0.882). Two methods of genetic algorithm (WOLF, and MIT-GA) for model construction were used and compared in 4D-QSAR analysis. MIT-GA package was alternatively applied for MDA-MB-231 as well as PC-3 training sets and one 4D-QSAR model was identified for either of both two training sets (Q2 value of 0.807 for MDA-MB-231 and 0.772 for PC-3). The models constructed using PC-3 training set were also utilized to predict TW01 analogues not in the training set. Consequently, a constructed model yielded absolute value of residuals between observed and predicted -logIC50 values less than 0.5 for the compounds already assayed. Furthermore, PC-3 training set was extended by adding more TW01 analogues and yielded a significant model with R2 value of 0.811 and Q2 value of 0.734 after outliers were removed from the extended PC-3 training set. In the optimized 4DQSAR models, steric and hydrophobic sites were generally embedded in these models. Compared our 4D-QSAR models with McGregor’s work on pharmacophore analysis with series of ATP binding site of tyrosince kinases, the possible targets of TW01 analogues seem to fit into the ATP binding sites of protein kinases. The distinct optimized 4DQSAR models for each cancer cell line are feedback to TW01 synthetic team for designing and can be used for virtual high throughput screening for more potent TW01 analogues.
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Sheu, Jong Rong, and 許中榮. "Quantitative-Structure Activity Relationship of Halogenated Aromatics and Toxic Organophosphorus Toxic Compounds." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/35925665904189229376.
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Xu, Zhong-Rong, and 許中榮. "Quantitative-Structure Activity Relationship of Halogenated Aromatics and Toxic Organophosphorus Toxic Compounds." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/23546659227774256979.
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Chang, Po-Lun, and 張栢綸. "3D quantitative structure-activity relationship studies of carbamates as inhibitors of acetylcholinesterase." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/57814229433566189963.
Full textAbstract:
碩士國立中興大學
化學系所
103
Acetylcholinesterase enzyme is the main topic of the treatment of Alzheimer''s disease. In this study, I used a three-dimensional quantitative structure-activity relationship (3D QSAR) , to calculate the computer simulation models of 50 carbamate inhibitors inhibition constant (KI). The results presented a very high degree of similarity, and the R2 value results were all greater than 0.9, with statistical significance. Consequently, the results from the simulation of carbamate inhibitors presented that some long chains and phenyl F2 substituents got better inhibitory effect of the acetylcholinesterase enzyme. The results of this study provide a useful information in the future design of carbamate inhibitors, which could both save more time and reduce the costs it wasted.
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Wang, Chien-Chih, and 王建智. "Quantitative Structure Activity Relationship for Inhibition Effects of Toluenes to Pseudomonas putida." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/15647349670663572342.
Full textAbstract:
碩士國立成功大學
化學系專班
91
Acute toxicity of toluene series to Pseudomonas putida(ATCC 23973)was estimated by an initial oxygen uptake method. Inhibition studies of these compounds on the oxidation of benzoate by Pseudomonas putida were expressed as oxygen uptake rates.Double reciprocal plots for the inhibition by these compounds of oxygen uptake in Pseudomonas,a physical constant(Ki) was obtained. Pseudomonas putida can degrade Benzaldehyde and Benzoic acid series compound. In toluene series,compound with NH2- and OH-substituent were found less toxicity than other substituted toluenes. In this study,in correlation of log(1/Ki) with logP(logarithm of 1-octanol-water partition coefficient ) and LUMO(lowest unoccupied molecular orbital),the following one equation were obtained. log1/Ki =－0.36 (±0.032 )ELUMO+0.37 (±0.030) MlogP -2.04 (±0.08) n = 42，R2 = 0.8889，s = 0.15，F = 152.09
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Huang, Chia-Wen, and 黃佳雯. "Quantitative Structure-Activity Relationship for Dermal Median Lethal Dose and Influential Molecular Characteristics." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/866x3e.
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Chen, Hsu-fang, and 陳許芳. "The Self-Reactivity Model for N-O Compounds Using Quantitative Structure Activity Relationship Approach." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/59237201689726059762.
Full textAbstract:
碩士國立高雄第一科技大學
環境與安全衛生工程研究所
104
Chemical Reactivity hazard has been reported as one of the main causes of fire and explosion in the industries. The reactivity distributes self-reactivity and compatibility. According to EU-REACH regulation, the self-reactivity is categorized into explosive properties which is Physical and chemical properties. Exothermic onset temperature ( T o ) and decomposition energy (Hd) are important self-reactivity parameters. Although many Exothermic onset temperature ( T o ) and decomposition energy (Hd) prediction models are put forward, but most of them are only for small groups and a small amount of data which make the prediction range very limited. However, certain quantities of samples are used in experiments. when chemicals have unknown toxicity or at high prices, it’s difficult to get their To and Hd through experiments. In this regard, taking reliable methods to estimate the To and Hd of compounds is indispensable. Quantitative structure activity relationship (QSAR) approach has been validated to be an effective method for predicting properties of chemical compounds, and it also has been acknowledged worldwide to be one of the predictive methods for providing hazardous information of chemical substances. EU takes this mode of testing as an alternative in REACH regulation.In this work, the To 137 of N-O compounds and Hd 138 of N-O compounds are collected to build up and validate a QSAR model for predicting the To of N-O compounds. Dragon and CODESSA PRO software are adopted to calculate molecular descriptors for each compound. A modified stepwise regression algorithm is applied to find out molecular descriptors that are highly correlated with the To and Hd of N-O compounds.
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Chen, Yen-Chih. "A New Quantitative Structure-Activity Relationship Model for Practical Applications using Hierarchical Clustering Genetic Algorithms." 2004. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-2707200402254400.
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Chen, Yen-Chih, and 陳彥志. "A New Quantitative Structure-Activity Relationship Model for Practical Applications using Hierarchical Clustering Genetic Algorithms." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/63533061833801756887.
Full textAbstract:
碩士國立臺灣大學
資訊工程學研究所
92
The purpose of quantitative structure-activity relationship (QSAR) is to formulate mathematical relationships between physico-chemical properties of compounds and their experimentally determined in vitro biological activities. The derived QSAR model can be subsequently applied to many practical applications, such as compound classification, diagnosis of drug mechanism, prediction of biological activity, and lead optimization. QSAR are commonly regarded as the best approaches to computational molecular design. To develop a reliable and versatile QSAR model, genetic algorithm-based partial least squares (GA-PLS) and hierarchical clustering-based partial least squares (HC-PLS) are employed in this thesis. According to a series of studies, the results have been successfully validated by Selwood and Holloway data sets. The benefits of our model can be summarized as follow. First, GA-PLS is capable of selecting the significant molecular descriptors that play an important role in determining biological activity. By means of encoding the latent variable of PLS into chromosome and combining biased mutation with uniform mutation, GA-PLS can further improve the efficiency and accuracy of QSAR model. Second, HC-PLS is able to discriminate the representative compounds in the data set to facilitate molecular property prediction or to further analyze the subsets. Based on the comparison between molecular descriptors and biological activities (actual values for the training data and predicted values for the test data), the similar compounds have more potential to exhibit similar physicochemical and biological properties. With the encouraging achievements, the highly predicted QSAR model derived by GA-PLS and HC-PLS not only enhances our understanding of the specifics of drug action, but also provides a theoretical foundation for future lead optimization.
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Wadhwaniya, Noureen. "2d quantitative structure activity relationship modeling of methylphenidate analogues using algorithm and partial least square regression." Thesis, 2005. http://library1.njit.edu/etd/fromwebvoyage.cfm?id=njit-etd2005-043.
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Chang, Ming, and 張茗. "Photodegradation of emerging contaminants with TiO2 nanoparticles in the presence of electrolytes and quantitative structure-activity relationship." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/bk62j4.
Full textAbstract:
碩士國立臺灣大學
農業化學研究所
107
Tris (1,3-dichloropropyl) phosphate (TDCPP), one of phosphorus flame retardants, gradually replaces brominated flame retardants. Due to increasing usage of TDCPP, it is detected in the environment, and TDCPP has adverse effects on animals’ reproductive and neurological system. Therefore, TDCPP has to be removed from the environment. Photocatalytic reactions can efficiently remove contaminants in aquatic environments since it takes short time and contaminants are able to be efficiently degraded or even mineralized by photocatalytic reactions. TiO2 nanoparticles (NPs) are one of common photocatalysts and Degussa P25 TiO2 NP was chosen. Several factors might influence photocatalytic reactions, such as solution pH, temperatures, and halide ions like Cl- and Br-, which are likely from seawater, leachate or salty marshes. Hence, the effects of these factors on the photocatalytic reactions have to be investigated. Most previous studies showed that halide ions would inhibit degradation of pollutants by photocatalysts, while according to our previous study, the presence of halide ions enhanced photodegradation efficiency by TiO2 instead. Since the chemicals utilized in above experiments were different, it is necessary to explore the effects of chemical structures on the photocatalytic degradation rates of chemicals by P25 NPs in the presence of halide ions. The surface of P25 contained positive charges in acid conditions, and the positive charges on P25 surface reduced with Cl- or Br-, indicating that they were neutralized by Cl- or Br-. In addition, the results analyzed by Fourier-transform infrared spectroscopy showed that hydroxyl groups possessed on the surface of P25 decreased after the addition of Cl- or Br-, which further suggested that Cl- or Br- would form bonds with the surface of P25. P25 successfully degraded TDCPP in 60 min irradiated with UV light. Furthermore, TDCPP was almost mineralized during the process of photodegradation by P25, and Cl- released was also detected. The photodegradation rate constants of TDCPP with P25 decreased with increasing the initial TDCPP concentrations, but increased with the increase of P25 dosages. Photodegradation rates of TDCPP decreased when pH increased, and they did not be influenced obviously by different temperatures. The decrease of degradation kinetics of TDCPP in the presence of 10-500 mM NaCl or NaBr was observed. In order to further investigate the relationships between chemical structures and rate constants, rate constants of 4-chlorophenol (4-CP)、phenol、bisphenol A (BPA)、ethinyl estradiol (EE2), and trimethoprim (TMP) by P25 were measured. In the presence of Cl-, the degradation rate constants of 4-CP, phenol, BPA, EE2, and TMP all decelerated; while the photodegradation rates of 4-CP, phenol, BPA, EE2, and TMP increased with over 50 mM NaBr. Without NaBr, HO● formed by P25 NPs, while no HO● detected with NaBr. However, the formation of Br● through the reactions of HO● or hVB+ with Br- from P25 was detected. Thus, the dominant radicals reacting with chemicals were Br● in the presence of Br-. The results from quantitative structure-activity relationship showed that the rate constants of chemicals with negative values of Hammett σ constant was larger, indicating that Br● was more likely to react with chemicals possessing electron-donating substituents. It also confirmed that Br● could attack selectively with electron-rich compounds. This study understood the effects of environmental factors on the photodegradation of contaminants, developed the method of detecting Br●, and investigated the relationships between chemical structures and rate constants.
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Pletsas, Dimitrios, Elrashied A. E. Garelnabi, Li Li, Roger M. Phillips, and Richard T. Wheelhouse. "Synthesis and quantitative structure-activity relationship of imidazotetrazine prodrugs with activity independent of O6-methylguanine-DNA-methyltransferase, DNA mismatch repair, and p53." 2013. http://hdl.handle.net/10454/6135.
Full textAbstract:
YesThe antitumor prodrug temozolomide is compromised by its dependence for activity on DNA mismatch repair (MMR) and the repair of the chemosensitive DNA lesion, O6-methylguanine (O6-MeG), by O6-methylguanine-DNA-methyltransferase (E.C. 2.1.1.63, MGMT). Tumor response is also dependent on wild-type p53. Novel 3-(2-anilinoethyl)-substituted imidazotetrazines are reported that have activity independent of MGMT, MMR, and p53. This is achieved through a switch of mechanism so that bioactivity derives from imidazotetrazine-generated arylaziridinium ions that principally modify guanine-N7 sites on DNA. Mono- and bifunctional analogues are reported, and a quantitative structure-activity relationship (QSAR) study identified the p-tolyl-substituted bifunctional congener as optimized for potency, MGMT-independence, and MMR-independence. NCI60 data show the tumor cell response is distinct from other imidazotetrazines and DNA-guanine-N7 active agents such as nitrogen mustards and cisplatin. The new imidazotetrazine compounds are promising agents for further development, and their improved in vitro activity validates the principles on which they were designed.
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Wang, James, and 王焰增. "Using Three Dimenson Quantitative Structure Activity Relationship to Predict and Analyze The Activities of Matrix metalloproteinases-1’s Inhibitors." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/94628025864324291841.
Full textAbstract:
碩士國立清華大學
生物技術研究所
90
The human matrix metalloproteinases (MMPs) are the products of a growing gene family of at least 20 members of structurally related Zn - and Ca -containing neutral endopeptidases。These enzymes play important roles in extracellular matrix turnover during homeostatic physiological processes such as embryonic development， morphogenesis, tissue resorption and remodelling，nerve growth, reproduction, hair follicle development，platelet aggregation， macrophage and neutrophil function，cell migration，and angiogenesis. Nevertheless，the important role of MMPs in many pathological processes such as rheumatoid arthritis，osteoarthritis，cancer invasion，cancer metastasis，ulcerations， periodontal diseases，fibrotic diseases，atherosclerosis，epidermolysis bullosa，and aortic aneurysm is also well known。 Using the sortware named “SpartanTM” to build Matrix metalloproteinases－1 inhibitors。 Using the descriptors，CoMFA （Comparative Molecular Field Analysis）and CoMSIA（Comparative Molecular Shape Indices Analysis），to research the QSAR (Structure-Activity Relationship) of MMP1’s inhibitors。The CoMFA model give q2＝0.533 when using the atom “I” as probe。The CoMSIA models had q2＝0.514，0.503 and include steric，electronic fields。
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Chung, Ying, and 鍾瑩. "Research on Quantitative Structure Activity Relationship for Inhibition of Acetylcholinesterase,Butyrylcholinseterase and Cholesterol Esterase by 1-Acyloxy-3-methanesulfonyloxybenzenes." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/50617993052120591497.
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Tsai, Din-Yu, and 蔡定裕. "The Study of Toxicity Assessment of Aromatic Aldehydes(Benzaldehydes) Using a Closed-System Algal Test and The Quantitative Structure-Activity Relationship." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/83548615052654470341.
Full textAbstract:
碩士國立交通大學
環境工程系所
94
The objective of this study is to study the toxic effect of aromatic aldehydes (benzaldehyde) on Pseudokirchneriella subcapitata using a closed system test. The effects of benzaldehydes were evaluated by three kinds of response endpoints, i.e., cell density, algal growth rate, and the dissolved oxygen production. Median effective concentratons (EC50s) were estimated using the Probit model with a test duration of 48hr. The quantitative structure-activity relationships (QSARs) were established based on the 1-octanol/water partition coefficient (logKow) and an electronic parameters-Lowest unoccupied molecular orbit (ELUMO). The result shows that the algae would make three types of benzaldehydes (benzaldehdye、vanillin and 3,4-dihydroxybenzaldehyde) into benzoic acid, and this reaction is called the dismutation. Special attention should be paid to that the oxygen produced by algae and toxicity of benzaldehydes will be decreased in the dismutation. The highest toxicity in different kinds of hydroxyl- benzaldehydes is 5-bromo-2-hydroxybenzaldehyde. In addition, the toxicity of para-hydroxy-benzaldehydes is lower than that of ortho-hydroxy- benzalde- hydes, exept 3-bromo-4-hydroxybenzaldehyde. The results also reveal that the value of the lower effect concentration (EC10、LOEC、NOEC and NEC) of the benzaldehydes is NOEC
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Jhan, Jyun-Siang, and 詹竣翔. "Novel Non-Steroidal Anti-Inflammatory Drugs Design Based on Quantitative-Structure Activity Relationship for Inhibitions of Naja mossambica mossambica, Bee Venom, and Porcine Pancreatic Phospholipase A2s by 3-Acyloxy-1-N-n-Octylcarbanyl Benzenes." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/28133819181975801434.
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