Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "QSAR modeling" wg kryterium: Wszystkie pola

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-8 z 8
    Tytuł:
    Self-organizing neural network for modeling 3D QSAR of colchicinoids.
    Autorzy:
    Polański, Jarosław
    Powiązania:
    https://bibliotekanauki.pl/articles/1044388.pdf
    Data publikacji:
    2000
    Wydawca:
    Polskie Towarzystwo Biochemiczne
    Tematy:
    neural networks
    3D QSAR
    colchicinoids
    Opis:
    A novel scheme for modeling 3D QSAR has been developed. A method involving multiple self-organizing neural network adjusted to be analyzed by the PLS (partial least squares) analysis was used to model 3D QSAR of the selected colchicinoids. The model obtained allows the identification of some structural determinants of the biological activity of compounds.
    Źródło:
    Acta Biochimica Polonica; 2000, 47, 1; 37-45
    0001-527X
    Pojawia się w:
    Acta Biochimica Polonica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Badania in silico w przewidywaniu zdolności przenikania leków przez barierę krew-mózg
    In silico prediction of blood-brain barrier penetration of drugs
    Autorzy:
    Brzezińska, Elżbieta
    Powiązania:
    https://bibliotekanauki.pl/articles/1032909.pdf
    Data publikacji:
    2011
    Wydawca:
    Łódzkie Towarzystwo Naukowe
    Tematy:
    modelowanie qsar
    deskryptory
    molekularne
    blood-brain barrier (bbb)
    qsar modeling
    molecular descriptors
    bariera krew-mózg
    Opis:
    Blood-brain barrier (BBB) is a complex cellular system, which separates the brain and central nervous system (CNS) from the bloodstream. BBB permeability (BBBp) is one of the most important pharmacokinetic properties not only for CNS-active drugs. The brain penetration of CNS-nonactive drugs should be very low to minimize the unwanted CNS side effects. Determination of BBBp of therapeutic compounds is an important component in the design of drugs. Usually the blood-brain partition coefficient (log BB) is used to determine BBB permeability of chemical compounds. Quantitative structure-activity relationship (QSAR) models offer predicting log BB from the molecular structure of a compound. Experimental determination of log BB of the compound is difficult, labour-consuming and time-consuming. It is desirable to predict the blood-brain partition coefficient of compounds from their molecular structures or from physicochemical properties. Various descriptors have been revealed in many studies to be important for predicting BBBp of small molecules via passive diffusion. The most important descriptors usually used to build QSAR models and the QSAR modeling methods were presented in this work. The in silico models based on QSAR are frequently used, but are limited by the restricted accessibility of in vivo data during the early drug discovery phase.
    Bariera krew-mózg (ang. Blood-brain barrier - BBB) jest złożonym systemem, który oddziela ośrodkowy układ nerwowy (OUN) od krwioobiegu. Zdolność przenikania bariery krew-mózg (ang. Blood-brain barrier permeability – BBBp) stanowi jedną z najważniejszych właściwości farmakokinetycznych dla leków działających ośrodkowo. Równocześnie, poziom przenikania do mózgu leków działających poza OUN powinien być niski, dla uniknięcia ośrodkowych działań niepożądanych. Ustalenie BBBp substancji leczniczej jest ważnym elementem projektowania leków. Najczęściej używanym wskaźnikiem poziomu przenikania jest współczynnik rozdziału pomiędzy mózg i krew (log BB). Modele matematyczne ilościowej zależności pomiędzy strukturą i aktywnością (ang. quantitative structure-activity relationship - QSAR) dają możliwość przewidywania parametru log BB na podstawie badania struktury związku chemicznego. Doświadczalne ustalanie wartości log BB jest trudne, czasochłonne i pracochłonne. Bardzo przydatna jest więc możliwość przewidywania współczynnika rozdziału związku pomiędzy mózg i krew, na podstawie właściwości fizykochemicznych lub ich struktury. Znacząca rola różnych deskryptorów molekularnych w przewidywaniu log BB została udowodniona w wielu doświadczeniach. W niniejszej pracy opisano najważniejsze z parametrów, często używanych do tworzenia modeli QSAR oraz popularne metody modelowania QSAR. Stosowanie modeli in silico, opartych na metodach QSAR, jest bardzo rozpowszechnione. We wstępnej fazie poszukiwania leku użyteczność tych metod jest ograniczona brakiem dostępu do danych z badań in vivo.
    Źródło:
    Folia Medica Lodziensia; 2011, 38, 2; 117-144
    0071-6731
    Pojawia się w:
    Folia Medica Lodziensia
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Molecular modelling techniques in environmental research
    Autorzy:
    Urniaż, R. D.
    Rutkowska, E.
    Jastrzębski, J. P.
    Książek, P.
    Rudnicka, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/363208.pdf
    Data publikacji:
    2013
    Wydawca:
    Uniwersytet Warmińsko-Mazurski w Olsztynie
    Tematy:
    molecular dynamics
    molecular modeling
    pharmacokinetics
    pharmacophore modeling
    QSAR
    dynamika molekularna
    modelowanie molekularne
    farmakokinetyka
    modelowanie farmakoforowe
    Opis:
    Over the last few decades significant increase in computational methods (in silico) was annotated. Novel methods have been developed and applied for hypothesis improvement and testing in regions of industrial, pharmaceutical and environmental research. The term in silico methods include variety of approaches. Considerable attention has been attracted to databases, data analysis tools, quantitative structure-activity relationships (QSAR), pharmacophore models, molecular docking and dynamics, pharmacokinetics and other molecular modelling techniques. In silico methods are often accompanied by experimental data, both to create the model and to test it. Such models are frequently used in the discovery and optimization of novel molecules with expected affinity to a target, the estimation of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The review summarizes briefly the applications of most common molecular modelling techniques and evaluates their application in environmental research. Additionally, this study considers computer aided methods as potential and complex tools that may serve as valuable partnership with wet-lab experiments and may provide a rational aid to minimize the cost and time of research.
    Źródło:
    Environmental Biotechnology; 2013, 9, 2; 39-51
    1734-4964
    Pojawia się w:
    Environmental Biotechnology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Structure Activity Relationships, QSAR Modeling and Drug-like calculations of TP inhibition of 1,3,4-oxadiazoline-2-thione Derivatives
    Autorzy:
    Almi, Z.
    Belaidi, S.
    Lanez, T.
    Tchouar, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/971332.pdf
    Data publikacji:
    2014
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    SAR
    QSAR
    drug-like
    TP inhibitory
    MLR
    1,3,4-oxadiazoline-2-thione derivatives
    Opis:
    QSAR studies have been performed on twenty-one molecules of 1,3,4-oxadiazoline-2-thiones. The compounds used are among the most thymidine phosphorylase (TP) inhibitors. A multiple linear regression (MLR) procedure was used to design the relationships between molecular descriptor and TP inhibition of the 1,3,4-oxadiazoline-2-thione derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based of the following descriptors: logP, HE, Pol, MR, MV, and MW, qO1, SAG, for the TP inhibitory activity. To confirm the predictive power of the models, an external set of molecules was used. High correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR models.
    Źródło:
    International Letters of Chemistry, Physics and Astronomy; 2014, 18; 113-124
    2299-3843
    Pojawia się w:
    International Letters of Chemistry, Physics and Astronomy
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Computational predictive mutagenicity of similar chemicals for anthraquinone, β-sitosterol and quercetin found in Alternanthera tenella by using QSAR modeling software
    Autorzy:
    Haque, Mahmudul
    Bhakat, Ram Kumar
    Bhattacharjee, Aloke
    Talapatra, Soumendra Nath
    Powiązania:
    https://bibliotekanauki.pl/articles/1182926.pdf
    Data publikacji:
    2016
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Allelopathy; Allelochemicals; Alternanthera tenella; Invasive species; Terrestrial ecosystem; Predictive Ames mutagenicity; QSAR modeling; T.E.S.T. software
    Opis:
    The present study aims to evaluate the mutagenic potential of secondary metabolites viz. anthraquinone, β-sitosterol and quercetin present in Alternanthera tenella and their related analogus compounds similar in their molecular structure. Nine similar putative allelochemicals analogus to each of anthraquninone, β-sitosterol and quercetin respectively were selected, a total of twenty seven similar chemicals were studied for mutagenicity prediction. Ames mutagenicity prediction was carried out by using T.E.S.T. (Toxicity Estimation Software Tool) of USEPA. All experimental metadata were obtained from Toxicity Benchmark and T.E.S.T. The results clearly indicated that the allelochemicals, anthraquinone and its related eight compounds were mutagenic positive except benzanthrone (mutagenic negative) but all experimental data were found mutagenic positive. β-sitosterol showed mutagenic negative in both experimental and predicted value. It’s three related compounds were mutagenic positive but rest six related compounds mutagenic negative in predicted value while in experimental data, seven compounds were found mutagenic positive and rest two mutagenic negative. In case of quercetin, both data were obtained mutagenic positive while in related compounds, seven compounds were found to be mutagenic positive and two compounds mutagenic negative in predicted value. All were found to be mutagenic positive in experimental metadata. Such findings poses a curiosity that are there any possibilities of conversion or substitution in the position of aromatic ring of allelochemicals when present in soil? Because allelopathy depends upon several environmental stressors and mutagenicity may be induced by allelochemicals. It is suggesting for future research to detect metabolic pathway and mechanism of allelochemicals formation in A. tenella in presence of toxins in soil and to validate with other available 2D and 3D softwares.
    Źródło:
    World Scientific News; 2016, 49, 2; 162-191
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Predictive acute toxicity comparison in Daphnia magna for common organic chemicals present in cosmetics by using two QSAR modeling softwares
    Autorzy:
    Talapatra, Soumendra Nath
    Konar, Sarnali
    Powiązania:
    https://bibliotekanauki.pl/articles/1190143.pdf
    Data publikacji:
    2016
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    QSAR modelling
    Cosmetic organic chemicals
    T.E.S.T. and ECOSAR software
    Predictive acute toxicity
    Daphnia magna
    Opis:
    Different types of organic compounds, which are used in cosmetics from decades. The usage of cosmetic products are mainly by people in office, culture, festival, recreation etc. All of these chemicals are of synthetic origin. The present study aims to predict comparative acute toxicity as LC50 (median lethal concentration) values in Daphnia magna for common types of cosmetic compounds. The predictions of LC50 values were determined by using two QSAR modeling softwares, T.E.S.T. or Toxicity Estimation Software Tool and ECOSAR (Ecological Structure Activity Relationship), for established 23 types of chemicals commonly present in cosmetics. These two softwares help to predict of LC50 values by easy screening. In present result, predictive data with statistical interpretation (R2 or correlation coefficient values) were obtained easily in T.E.S.T. but not in ECOSAR and the statistical data interpretation was not found. Among all these chemicals, it was observed that major compounds are not toxic to D. magna except few chemicals viz. ascorbyl palmitate, triclosan, methyl triclosan and triclocarbon. Further researches are suggested to compare these predicted data with other available 2-dimentional and 3-dimentional softwares and these chemicals should be studied in combinations of cosmetic chemicals with this test model in vivo because they are major food sources for fish in freshwater ecosystem.
    Źródło:
    World Scientific News; 2016, 42; 101-118
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    QSAR modeling for acute toxicity prediction in rat by common painkiller drugs
    Autorzy:
    Roy, J.S.
    Gupta, K.
    Talapatra, S.N.
    Powiązania:
    https://bibliotekanauki.pl/articles/11550.pdf
    Data publikacji:
    2016
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Opis:
    Painkiller drugs or analgesics are potent pain reliever chemical agents, which are commonly used in pain therapy. Mathematical modeling by QSAR (quantitative structure activity relationship) methods are well known practices to determine predictive toxicity in biota. Now-adays, an easy screening of chemicals, QSAR can be done by using several recommended softwares. The present study was carried out by using software namely T.E.S.T. (Toxicity estimation software tool) for rat oral LD50 (median lethal dose) predictive toxicity for common painkiller drugs. These painkiller drugs were selected as 35 compounds and tabulated on the basis characteristics of one non-narcotic viz. acetaminophen, twenty non-steroidal anti-inflammatory such as bromofenac, diclofenac, diflunsial, etodolac, fenoprofen, flurbiprofen, ibuprofen, indomethacin, ketoprofen, ketorolac, maclofenamate sodium, mefenamic acid, meloxicam, nabumetone, naproxen, oxaprozin, phenylbutazone, piroxicam, sulindac and tolmetin as well as fourteen narcotic viz. buprenorphine, butorphanol, codeine, hydrocodone, hydromorphone, levorphanol, meperidine, methadone, morphine, nalbuphine, oxycodone, pentazocine, dextropropoxyphene and tapentadol. The data were tabulated on experimental (bioassay) from ChemIDPlus and T.E.S.T. and predictive toxicity of 30 compounds out of 35 compounds by using T.E.S.T. The predictive data were found by T.E.S.T. that 20 and 10 compounds were very toxic and moderately toxic respectively but not extremely, super toxic and non-toxic in rat model after acute oral exposure. It is suggested to evaluate the predicted data further with other available recommended softwares with different test models like daphnia, fish etc. to know aquatic toxicity when these compounds may discharge into waterbodies.
    Źródło:
    International Letters of Natural Sciences; 2016, 52
    2300-9675
    Pojawia się w:
    International Letters of Natural Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    QSAR modeling for prediction of acute toxicity and mutagenicity in different test models by established common phytochemicals present in Phyllanthus niruri
    Autorzy:
    Dhar, Shrinjana
    Gupta, Kaushik
    Talapatra, Soumendra Nath
    Powiązania:
    https://bibliotekanauki.pl/articles/1192089.pdf
    Data publikacji:
    2016
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    QSAR modeling
    Common phytochemicals
    Phyllanthus niruri
    T.E.S.T. software
    Predictive toxicity and mutagenicity
    Opis:
    In globe, Pyllanthus niruri is a well-established medicinal herb studied by many researchers, grown widely in many parts of West Bengal. The present study was aimed to predict the acute toxicity as LC50 in Daphnia magna and Pimephales promelas and rat oral LD50 value as well as Ames mutagenicity by using QSAR modeling software, T.E.S.T. (Toxicity Estimation Software Tool) for commonly found phytochemicals in Pyllanthus niruri. In present works, the data were obtained for LC50, few phytochemicals were toxic to D. magna and P. promelas and also mutagenic but rat oral LD50 determined less toxic. The present QSAR modeling work is suggesting that more researches should be required through experimental as well as predictive study with other prescribed software to know the mechanisms of toxicity and mutagenicity for these combined form of phytochemicals after separating each natural chemical from extract prior to drugs development for therapeutic usage.
    Źródło:
    World Scientific News; 2016, 37; 202-219
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies