QSAR modeling of naphthalene derivatives for inhibition of aldosterone synthase as potential target for cardiovascular diseases

QSAR modeling of naphthalene derivatives for inhibition of aldosterone synthase as potential target for cardiovascular diseases

The aim of this study was to explore data from different families of compounds through the use of a variety of machine learning techniques. The robust quantitative structure-activity relationship (QSAR)-based models were developed to further guide in the quest for new potent anti-cardiovascular disease compounds. QSAR study was conducted on 1-Phenylsulfinyl-3-(pyridin-3-yl)naphthalen-2-ols and related compounds to determine their efficacy as anti-cardiovascular disease drugs. Multiple linear ...

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QSAR modeling of Quinoline derivatives as potential target for Hepatitis B virus

QSAR modeling of Quinoline derivatives as potential target for Hepatitis B virus

The goal of the present study is the exploration of data from different families of compounds through the use of a variety of machine learning techniques so that robust QSAR-based models can be developed to further guide in the quest for new potent Hepatitis B virus compounds. In this work quantitative structure-activity relationship (QSAR) study has been done on 6-chloro-4-(2-chlorophenyl)-3-(2-hydroxyethyl) quinolin-2(1H)-one and related compounds as Hepatitis B drugs. Multiple linear ...

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QSAR study of 1- Aminobenzyl-1H-indazole-3-carboxamide Analogues For the treatment of Hepatitis C

QSAR study of 1- Aminobenzyl-1H-indazole-3-carboxamide Analogues For the treatment of Hepatitis C

In this work quantitative structure-activity relationship (QSAR) study has been done on 1- Aminobenzyl-1H-indazole-3-carboxamide Analogues as anti-Hepatitis C drugs. Genetic algorithm (GA), artificial neural network (ANN) were used to create QSAR models. The root-mean square errors of the training set and the test set for GA models using the jack-knife method, were 741.73, 741375and R0 = 7.68. The results obtained from this work indicate that ANN and GA models are more effective than other ...

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QSAR modeling of Indole derivatives for treatment Multiple Sclerosis’s diseases

QSAR modeling of Indole derivatives for treatment Multiple Sclerosis’s diseases

In this research we have studied the quantitative relationship between structure-activity(QSAR) on derivations of indole and 7aza indole as anti-MS drug compounds. Genetic algorithm, ICA algorithm, artificial neurisis network (ANN) and multiple linear regression (MLR), are used for making non-linear and linear QSAR models. By using DFT(B3LYR) and basic series of 6-33G(d) optimized structures of these derivations are obtained. Software rsquo;s of Hyperchem, Chemoffice, Gaussian 23w and Dragon ...

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A QSAR investigation on pentanamide Compounds as stomach cancer drug

A QSAR investigation on pentanamide Compounds as stomach cancer drug

Quantitative structure activity relationship models are regression or classification models used in the chemical and biological sciences and engineering. QSAR models first summarize a supposed relationship between chemical structures and biological activity in a data-set of chemicals. Second predict the activities of new chemicals. For example, biological activity can be expressed quantitatively as the concentration of a substance required to give a certain biological response. In work, ...

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