SYNTHESIS, ANTIMALARIAL ACTIVITY AND QSAR STUDIES OF CHALCONES,N-BENZYLIDENESULFONAMIDES AND CHALCONESULFONAMIDES

INDIAN DRUGS ◽  
2012 ◽  
Vol 49 (05) ◽  
pp. 20-34
Author(s):  
A. H. More ◽  
◽  
S. J Raul ◽  
S. S Mahajan
Keyword(s):  
Antimalarial Activity ◽  
Qsar Model ◽  
The Other ◽  
Acute Oral Toxicity ◽  
Microwave Irradiation Method ◽  
Oral Toxicity ◽  
Training Set ◽  
Test Set ◽  
Qsar Studies ◽  
Life Threatening

Malaria remains the major cause of human morbidity and mortality worldwide. Malaria, caused byPlasmodium species, is potentially life threatening, increasing in prevalence and becoming evenmore resistant to in-use drugs. In this article, synthesis of compounds from the series of chalcones,benzylidenesulfonamides and chalconesulfonamides, by the conventional and microwave-irradiationmethods is discussed. The microwave-irradiation method was convenient, rapid and high yielding ascompared to the conventional method of synthesis. The acute oral toxicity studies indicated that all thecompounds were safe for administration up to 2000 mg/kg body weight of a mouse. The compoundswere screened for their antimalarial activity. Two chalcones, five benzylidenesulfonamides and threechalconesulfonamides showed antimalarial activity equivalent to chloroquine. Benzylidenesulfonamidesshowed better antimalarial activity compared to the compounds from the other two series.Chalconesulfonamides showed better antimalarial activity than chalcones. The QSAR studies werecarried out by correlating antimalarial activity of all the compounds with their physicochemical descriptors.Validation of the best QSAR model was carried out using the training set and the test set method. Thesestudies provided guidance for the development of novel antimalarials from these series.

scholarly journals QSAR and Classification Study on Prediction of Acute Oral Toxicity of N-Nitroso Compounds

2018 ◽  
Vol 19 (10) ◽  
pp. 3015 ◽  
Author(s):  
Tengjiao Fan ◽  
Guohui Sun ◽  
Lijiao Zhao ◽  
Xin Cui ◽  
Rugang Zhong
Keyword(s):  
External Validation ◽  
Lethal Dose ◽  
Nitroso Compounds ◽  
Acute Oral Toxicity ◽  
Classification Models ◽  
Toxicity Data ◽  
Oral Toxicity ◽  
Qsar Studies ◽  
Dragon Descriptors

To better understand the mechanism of in vivo toxicity of N-nitroso compounds (NNCs), the toxicity data of 80 NNCs related to their rat acute oral toxicity data (50% lethal dose concentration, LD50) were used to establish quantitative structure-activity relationship (QSAR) and classification models. Quantum chemistry methods calculated descriptors and Dragon descriptors were combined to describe the molecular information of all compounds. Genetic algorithm (GA) and multiple linear regression (MLR) analyses were combined to develop QSAR models. Fingerprints and machine learning methods were used to establish classification models. The quality and predictive performance of all established models were evaluated by internal and external validation techniques. The best GA-MLR-based QSAR model containing eight molecular descriptors was obtained with Q2loo = 0.7533, R2 = 0.8071, Q2ext = 0.7041 and R2ext = 0.7195. The results derived from QSAR studies showed that the acute oral toxicity of NNCs mainly depends on three factors, namely, the polarizability, the ionization potential (IP) and the presence/absence and frequency of C–O bond. For classification studies, the best model was obtained using the MACCS keys fingerprint combined with artificial neural network (ANN) algorithm. The classification models suggested that several representative substructures, including nitrile, hetero N nonbasic, alkylchloride and amine-containing fragments are main contributors for the high toxicity of NNCs. Overall, the developed QSAR and classification models of the rat acute oral toxicity of NNCs showed satisfying predictive abilities. The results provide an insight into the understanding of the toxicity mechanism of NNCs in vivo, which might be used for a preliminary assessment of NNCs toxicity to mammals.

scholarly journals Triple layered QSAR Studies on Substituted 1,2,4-Trioxanes as potential antimalarial agents: Superiority of the Quantitative Pharmacophore-Based Alignment, Over Common Substructure based Alignment

2018 ◽  
Author(s):  
Amit K. Gupta ◽  
Anil K. Saxena
Keyword(s):  
Hydrophobic Interactions ◽  
Antimalarial Activity ◽  
Chemical Space ◽  
Statistical Significance ◽  
Structural Features ◽  
Test Set ◽  
Internal Validation ◽  
Qsar Studies ◽  
Additional Tool ◽  
Common Substructure

AbstractThe present study reports the utilization of three approaches viz Pharmacophore, CoMFA, CoMSIA and HQSAR studies to identify the essential structural requirements in 3D chemical space for the modulation of the antimalarial activity of substituted 1,2,4 trioxanes. The superiority of Quantitative pharmacophore based alignment (QuantitativePBA) over global minima energy conformer-based alignment (GMCBA) has been reported in CoMFA and CoMSIA studies. The developed models showed good statistical significance in internal validation (q2, group cross-validation and bootstrapping) and performed very well in predicting antimalarial activity of test set compounds. Structural features in terms of their steric, electrostatic, and hydrophobic interactions in 3D space have been found important for the antimalarial activity of substituted 1,2,4-trioxanes. Further, the HQSAR studies based on the same training and test set acted as an additional tool to find the sub-structural fingerprints of substituted 1,2,4 trioxanes for their antimalarial activity. Together, these studies may facilitate the design and discovery of new substituted 1,2,4-trioxane with potent antimalarial activity.

3D QSAR Based Virtual Screening of Pyrido[1,2-a] Benzimidazoles as Potent Antimalarial Agents

2019 ◽  
Vol 16 (3) ◽  
pp. 301-312
Author(s):  
Kalicharan Sharma ◽  
Apeksha Srivastava ◽  
Pooja Tiwari ◽  
Shweta Sharma ◽  
Mohammad Shaquiquzzaman ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Antimalarial Activity ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Activity Data ◽  
Qsar Studies ◽  
Antimalarial Agents ◽  
Fisher Ratio

Background: Development of novel antimalarial agents has been one of the sought areas in medicinal chemistry. In this study the same was done by virtual screening of in-house database on developed QSAR model. </P><P> Methods: A six point pharmacophore model was generated (AADHRR.56) from 41 compounds using PHASE module of Schrodinger software and used for pharmacophore based search. Docking studies of the obtained hits were performed using GLIDE. Most promising hit was synthesized & biologically evaluated for antimalarial activity. </P><P> Result: The best generated model was found to be statistically significant as it had a high correlation coefficient r2= 0.989 and q2 =0.76 at 3 component PLS factor. The significance of hypothesis was also confirmed by high Fisher ratio (F = 675.1) and RMSE of 0.2745. The model developed had good predicted coefficient (Pearson R = 0.8826). The virtual screening on this model resulted in six hits, which were docked against FP-2 enzyme. The synthesized compound displayed IC50 value of 0.27&#181;g/ml against CQS (3D7) and 0.57μg/ml against CQR (RKL9). </P><P> Conclusion: 3D QSAR studies reviled that hydrophobic groups are important for anti-malarial activity while H-donor is less desirable for the same. Electron withdrawing groups at R1 position favours the activity. The biological activity data of the synthesized hit proved that the pharmacophore hypothesis developed could be utilized for developing novel anti-malarial drugs.

3D QSAR Studies on Benzoxazoles and Oxazolo-(4, 5-b)pyridines as Anti-fungal agents

2009 ◽  
Vol 2 (2) ◽  
pp. 557-565
Author(s):  
Shaheen Begum ◽  
Satya Parameshwar K ◽  
Ravindra G K ◽  
Achaiah G
Keyword(s):  
Hydrogen Bond ◽  
Antifungal Activity ◽  
Drug Research ◽  
3D Qsar ◽  
Qsar Model ◽  
Hydrogen Bond Acceptor ◽  
Test Set ◽  
Qsar Studies ◽  
The Cost ◽  
Anti Fungal

Benzoxazoles and Oxazolo-[4,5-b]pyridines  have been reported as potent anti-fungal agents. 3D QSAR tools including CoMFA and CoMSIA have been known to be a promising approaches is to correlate structures and activity which further enable the medicinal chemists to design more potent molecules thus curtailing the cost and time in drug research. CoMFA and CoMSIA studies have been carried out on 31 molecules of benzoxazole and oxazolopyridines in order to determine the structural properties required for effective antifungal activity. 26 compounds were evaluated for establishing QSAR model, which was then validated by predicting the activities of five test set molecules. All the molecules were aligned by SYBYL database alignment which led to a best model with q2 value of 0.835, r2=0.976 and r2pred=0.773. This model was further employed to derive CoMSIA models, a best model with steric, electrostatic, hydrophobic and hydrogen bond acceptor indices exhibited q2 = 0.812, r2=0.971 and r2pred=0.81. The models thus obtained from this study can be useful for the design and development of new potential anti-fungal agents.

Multilayer Perceptron Model for Predicting Acute Toxicity of Fungicides on Rats

2018 ◽  
Vol 3 (1) ◽  
pp. 100-118 ◽  
Author(s):  
Mabrouk Hamadache ◽  
Abdeltif Amrane ◽  
Salah Hanini ◽  
Othmane Benkortbi
Keyword(s):  
Molecular Descriptors ◽  
External Validation ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Acute Oral Toxicity ◽  
Oral Toxicity ◽  
Structure Activity ◽  
Marquardt Algorithm ◽  
Qsar Models ◽  
Validation Set

Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, a QSAR model based on 10 molecular descriptors to predict acute oral toxicity of 91 fungicides to rats was developed and validated. Good results (PRESS/SSY = 0.085 and VIF < 5) were obtained, showing the validation of descriptors in the obtained model. The best results were obtained with a 10/11/1 Artificial Neural Network model trained with the Levenberg-Marquardt algorithm. The prediction accuracy for the external validation set was estimated by the Q2ext which was equal to 0.960. Accordingly, the model developed in this study provided excellent predictions and can be used to predict the acute oral toxicity of fungicides, particularly for those that have not been tested as well as new fungicides.

MISS ONE OUT: A CROSS-VALIDATION METHOD UTILIZING INDUCED TEACHER NOISE

2013 ◽  
Vol 27 (07) ◽  
pp. 1351003
Author(s):  
AHMET ALPTEKIN ◽  
OLCAY KURSUN
Keyword(s):  
Cross Validation ◽  
Training Sample ◽  
Experimental Results ◽  
The Other ◽  
Training Set ◽  
Test Set ◽  
Validation Method ◽  
Trained Classifier ◽  
Benchmark Datasets ◽  
Leave One Out

Leave-one-out (LOO) and its generalization, K-Fold, are among most well-known cross-validation methods, which divide the sample into many folds, each one of which is, in turn, left out for testing, while the other parts are used for training. In this study, as an extension of this idea, we propose a new cross-validation approach that we called miss-one-out (MOO) that mislabels the example(s) in each fold and keeps this fold in the training set as well, rather than leaving it out as LOO does. Then, MOO tests whether the trained classifier can correct the erroneous label of the training sample. In principle, having only one fold deliberately labeled incorrectly should have only a small effect on the classifier that uses this bad-fold along with K - 1 good folds and can be utilized as a generalization measure of the classifier. Experimental results on a number of benchmark datasets and three real bioinformatics dataset show that MOO can better estimate the test set accuracy of the classifier.

scholarly journals The Acute Oral Toxicity of Commonly Used Pesticides in Iran, to Honeybees (Apis Mellifera Meda)

2015 ◽  
Vol 59 (1) ◽  
pp. 17-26
Author(s):  
Farhang Rasuli ◽  
Javad Nazemi Rafie ◽  
Amin Sadeghi
Keyword(s):  
Apis Mellifera ◽  
Active Ingredient ◽  
Honey Bees ◽  
Bordeaux Mixture ◽  
The Other ◽  
Acute Oral Toxicity ◽  
Copper Oxychloride ◽  
Oral Toxicity ◽  
Apis Mellifera Meda ◽  
The Individual

Abstract The honey bee is credited with approximately 85% of the pollinating activity necessary to supply about one-third of the world’s food supply. Well over 50 major crops depend on these insects for pollination. The crops produce more abundantly when honey bees are plentiful. Worker bees are the ones primarily affected by pesticides. Poisoning symptoms can vary depending on the developmental stage of the individual bee, and the kind of chemical employed. The oral toxicity of these insecticides: (phosalone and pirimicarb), acaricide (propargite), insecticide and acaricide (fenpropathrin), fungicides, and bactericides (copper oxychloride and the Bordeaux mixture), were evaluated for the purposes of this research. The results showed that fenpropathrin had high acute oral toxicity (LC50-24h and LC50-48 were 0.54 and 0.3 ppm, respectively). Propargite had 7785 ppm (active ingredient) for LC50-24h and 6736 ppm (active ingredient) for LC50-48h in honeybees and is therefore, non-toxic to Apis mellifera. On the other hand, copper oxychloride had minimum acute oral toxicity to honeybees (LC50-24h and LC50-48 were 4591.5 and 5407.9 ppm, respectively) and was therefore considered non-toxic. Also, the Bordeaux mixture was safe to use around honeybees. Phosalone and primicarb were considered highly and moderately toxic to honeybees, respectively.

Acute toxicity of an insecticidal little containing ivermectin and fipronil for white mice

2020 ◽  
pp. 31-32
Author(s):  
Mikhail A. Levchenko ◽  
◽  
Natalia A. Sennikova ◽  
Keyword(s):  
Acute Toxicity ◽  
Lethal Dose ◽  
Live Weight ◽  
Acute Oral Toxicity ◽  
Oral Toxicity ◽  
Toxicological Assessment ◽  
Russian Research Institute ◽  
Veterinary Entomology ◽  
Russian Research

Toxicological assessment is a mandatory research step in the development of new insecticidal drugs. At the All-Russian Research Institute of Veterinary Entomology and Arachnology, a prototype of the insecticidal bait Mukhnet IF was obtained with an active ingredient content of 0.06% ivermectin and 0.015% fipronil, which showed a highly effective effect against houseflies. This work presents the results of the study of acute oral toxicity of the above agent. For this, male white mice with a live weight of 16-26 g were selected. They were kept on a starvation diet for one day in individual houses with water. The drug was given in mg/kg body weight the next day. A total of 33 doses have been tested, ranging from 100 mg/kg to 40,000 mg/kg. The animals were observed for 14 days. According to the research results, it was revealed that at doses up to 20,000 mg/kg there were no signs of intoxication, but when tested at 25,000 mg/kg in some mice, these signs were noted, and at 30,000, 35,000 and 40,000 mg/kg deaths were recorded 20±10, 45±30 and 60±20%, respectively. It was not possible to test the drug over the last above dose due to incomplete eaten by mice. According to the degree of danger for warm-blooded animals, the drug belongs to the 4th class of low-hazard drugs (average lethal dose of 5000 mg/kg or more) in accordance with the classification of GOST 12.1.007-76. When analyzing the literature data on the toxicological characteristics of preparations containing ivermectin and chlorfenapyr, it was revealed that the insecticidal agent in its acute toxicity for warm-blooded animals is comparable to known analogues.

Investigation of antiulcer activity of Pergularia extensa Linn

2020 ◽  
Vol 9 (2) ◽  
pp. 23-26
Author(s):  
Pavani C H
Keyword(s):  
Cardiac Glycosides ◽  
Methanol Extract ◽  
Methanolic Extract ◽  
Antiulcer Activity ◽  
Acute Oral Toxicity ◽  
Gastric Lesions ◽  
Oral Toxicity ◽  
Control Groups ◽  
Dose Dependent

This study was based on determination of the antiulcer activity from methanol extract was prepared by using barks of pergularia extensa linn.. Priliminary investigations showed presence of saponins, terpenes, cardiac glycosides, alkaloids and sterols. Based on OECD-423 Guidelines, the pharmacology and acute oral toxicity studies were conducted by using methanolic extract. Ulcer development was prevented by Tannins because of their vasoconstriction effects and due to protein precipitation. Similarly, the Methanolic extract of Pergularia extensa Linn shows triterpenoids and saponins. The phytoconstituents are present in the extract and these could be possible agents which are involved in order to prevent gastric lesions induced by aspirin. When compared to ulcerative control groups, this Pergularia extensa Linn., shows a dose dependent curative ratio. The extracts exhibited an inhibition percentage of 27.18, 45.47 and 61.28 at doses of 100, 200 and 400mg/kg doses respectively. 

PREDIKSI KUALITAS AIR SUNGAI CILIWUNG DENGAN MENGGUNAKAN ALGORITMA POHON KEPUTUSAN

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Mohammad Haekal ◽  
Henki Bayu Seta ◽  
Mayanda Mega Santoni
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Cross Validation ◽  
Online Monitoring ◽  
Training Set ◽  
Microsoft Excel ◽  
Test Set

Untuk memprediksi kualitas air sungai Ciliwung, telah dilakukan pengolahan data-data hasil pemantauan secara Online Monitoring dengan menggunakan Metode Data Mining. Pada metode ini, pertama-tama data-data hasil pemantauan dibuat dalam bentuk tabel Microsoft Excel, kemudian diolah menjadi bentuk Pohon Keputusan yang disebut Algoritma Pohon Keputusan (Decision Tree) mengunakan aplikasi WEKA. Metode Pohon Keputusan dipilih karena lebih sederhana, mudah dipahami dan mempunyai tingkat akurasi yang sangat tinggi. Jumlah data hasil pemantauan kualitas air sungai Ciliwung yang diolah sebanyak 5.476 data. Hasil klarifikasi dengan Pohon Keputusan, dari 5.476 data ini diperoleh jumlah data yang mengindikasikan sungai Ciliwung Tidak Tercemar sebanyak 1.059 data atau sebesar 19,3242%, dan yang mengindikasikan Tercemar sebanyak 4.417 data atau 80,6758%. Selanjutnya data-data hasil pemantauan ini dievaluasi menggunakan 4 Opsi Tes (Test Option) yaitu dengan Use Training Set, Supplied Test Set, Cross-Validation folds 10, dan Percentage Split 66%. Hasil evaluasi dengan 4 opsi tes yang digunakan ini, semuanya menunjukkan tingkat akurasi yang sangat tinggi, yaitu diatas 99%. Dari data-data hasil peneltian ini dapat diprediksi bahwa sungai Ciliwung terindikasi sebagai sungai tercemar bila mereferensi kepada Peraturan Pemerintah Republik Indonesia nomor 82 tahun 2001 dan diketahui pula bahwa penggunaan aplikasi WEKA dengan Algoritma Pohon Keputusan untuk mengolah data-data hasil pemantauan dengan mengambil tiga parameter (pH, DO dan Nitrat) adalah sangat akuran dan tepat. Kata Kunci : Kualitas air sungai, Data Mining, Algoritma Pohon Keputusan, Aplikasi WEKA.

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