Property representations and molecular fragmentation of chemical compounds in QSAR modeling

2020 ◽  
Vol 206 ◽  
pp. 104146
Author(s):  
Jaroslaw Polanski ◽  
Roksana Duszkiewicz
Keyword(s):  
Chemical Compounds ◽  
Qsar Modeling ◽  
Molecular Fragmentation

Ensemble-Based Modeling of Chemical Compounds with Antimalarial Activity

2019 ◽  
Vol 19 (11) ◽  
pp. 957-969 ◽  
Author(s):  
Ana Yisel Caballero-Alfonso ◽  
Maykel Cruz-Monteagudo ◽  
Eduardo Tejera ◽  
Emilio Benfenati ◽  
Fernanda Borges ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Computational Models ◽  
Antimalarial Activity ◽  
Majority Vote ◽  
Chemical Compounds ◽  
Quantitative Structure Activity Relationship ◽  
Qsar Modeling ◽  
Design Work ◽  
Data Set ◽  
Selection Of

Background: Malaria or Paludism is a tropical disease caused by parasites of the Plasmodium genre and transmitted to humans through the bite of infected mosquitos of the Anopheles genre. This pathology is considered one of the first causes of death in tropical countries and, despite several existing therapies, they have a high toxicity. Computational methods based on Quantitative Structure- Activity Relationship studies have been widely used in drug design work flows. Objective: The main goal of the current research is to develop computational models for the identification of antimalarial hit compounds. Materials and Methods: For this, a data set suitable for the modeling of the antimalarial activity of chemical compounds was compiled from the literature and subjected to a thorough curation process. In addition, the performance of a diverse set of ensemble-based classification methodologies was evaluated and one of these ensembles was selected as the most suitable for the identification of antimalarial hits based on its virtual screening performance. Data curation was conducted to minimize noise. Among the explored ensemble-based methods, the one combining Genetic Algorithms for the selection of the base classifiers and Majority Vote for their aggregation showed the best performance. Results: Our results also show that ensemble modeling is an effective strategy for the QSAR modeling of highly heterogeneous datasets in the discovery of potential antimalarial compounds. Conclusion: It was determined that the best performing ensembles were those that use Genetic Algorithms as a method of selection of base models and Majority Vote as the aggregation method.

scholarly journals Deep Learning Approach for Discovery of In Silico Drugs for Combating COVID-19

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Nishant Jha ◽  
Deepak Prashar ◽  
Mamoon Rashid ◽  
Mohammad Shafiq ◽  
Razaullah Khan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Drug Targets ◽  
Molecular Descriptor ◽  
Chemical Compounds ◽  
Learning Approach ◽  
Binding Affinities ◽  
Qsar Modeling ◽  
Learning Techniques ◽  
Speed Up ◽  
Difficult Situations

Early diagnosis of pandemic diseases such as COVID-19 can prove beneficial in dealing with difficult situations and helping radiologists and other experts manage staffing more effectively. The application of deep learning techniques for genetics, microscopy, and drug discovery has created a global impact. It can enhance and speed up the process of medical research and development of vaccines, which is required for pandemics such as COVID-19. However, current drugs such as remdesivir and clinical trials of other chemical compounds have not shown many impressive results. Therefore, it can take more time to provide effective treatment or drugs. In this paper, a deep learning approach based on logistic regression, SVM, Random Forest, and QSAR modeling is suggested. QSAR modeling is done to find the drug targets with protein interaction along with the calculation of binding affinities. Then deep learning models were used for training the molecular descriptor dataset for the robust discovery of drugs and feature extraction for combating COVID-19. Results have shown more significant binding affinities (greater than −18) for many molecules that can be used to block the multiplication of SARS-CoV-2, responsible for COVID-19.

scholarly journals QSAR modeling growth inhibitors Pasteurella multocida

2019 ◽  
pp. 30-36
Author(s):  
В ВАЖЕВ ◽  
V. Vazhev ◽  
Б МУНАРБАЕВА ◽  
B. Munarbaeva ◽  
Н ВАЖЕВА ◽  
...  
Keyword(s):  
Computer Program ◽  
Correlation Coefficient ◽  
Pasteurella Multocida ◽  
Control Sample ◽  
Chemical Compounds ◽  
Quantitative Structure Activity Relationship ◽  
Farm Animals ◽  
Economic Damage ◽  
Qsar Modeling ◽  
Bacterial Drug Resistance

Abstract. The search for effective drugs for the treatment of infectious diseases of farm animals is an urgent problem. The article presents the models of antipasteurllosis activity of a vast array of chemical compounds, built using descriptors generated by the Dragon program and the computer program PROGROC developed by us. Pasteurelosis is an infectious disease of many species of animals, caused by bacteria of the genus Pasteurella, has a wide geographical distribution and causes significant economic damage to livestock. Treatment of diseased animals with antibiotics is complicated by the emergence of forms of microorganisms that are resistant to them. To solve the problem of bacterial drug resistance, it is proposed to search for and select compounds with antipasteurellosis activity using QSAR (Quantitative Structure-Activity Relationship) methods. To assess the antipasteurellosis activity, the indicator lgMIC (MIC is the minimum inhibitory concentration of the substance) was used. The prediction quality was characterized by a correlation coefficient R between the predicted and experimental values of lgMIC and the standard deviation s. In the present work, models of inhibitory activity against Pasteurella multocida 362 chemical compounds selected at the ChEMBL site were obtained. The simulation involved 445 molecular structure descriptors calculated by the Dragon 7 program. The calculations were performed using the PROGROC computer program (PROGgram RObustness Calculation). The values of the correlation coefficient reached 0.9360–0.9549 for the control sample, where 55–61 % of the total set of substances are represented. When checking the quality of modeling by means of sliding control, the following indicators were obtained: R = 0.9297 and s = 0.40. Calculations were made for compounds with only threshold estimates (<lgMIC>) in the original database. The obtained estimated lgMIC estimates are in good agreement with the experimental ones, which indicates the possibility of replacing the experiment with less costly calculations.

Cytochemical analysis of mast cell granules after poly-dl-lysine action

1978 ◽  
Vol 36 (2) ◽  
pp. 278-279
Author(s):  
R. Courtoy ◽  
L.J. Simar ◽  
J. Christophe
Keyword(s):  
Mast Cell ◽  
Mast Cells ◽  
Chemical Compounds ◽  
Cellular Membrane ◽  
Thin Sections ◽  
Organic Bases ◽  
Ferric Thiocyanate ◽  
Cytochemical Analysis ◽  
Mast Cell Granule ◽  
Amine Liberation

Several chemical compounds induce amine liberation from mast cells but do not necessarily provoque the granule expulsion. For example, poly-dl-lysine induces modifications of the cellular membrane permeability which promotes ion exchange at the level of mast cell granules. Few of them are expulsed but the majority remains in the cytoplasm and appears less dense to the electrons. A cytochemical analysis has been performed to determine the composition of these granules after the polylysine action.We have previously reported that it was possible to demonstrate polyanions on epon thin sections using a cetylpyridinium ferric thiocyanate method. Organic bases are selectively stained with cobalt thiocyanate and the sulfhydryle groups are characterized with a silver methenamine reaction. These techniques permit to reveal the mast cell granule constituents, i.e. heparin, biogenic amines and basic proteins.

Growth of near noble metal Pd and Pt thin film silicides morphology and structure

1984 ◽  
Vol 42 ◽  
pp. 498-499
Author(s):  
E. I. Alessandrini ◽  
M. O. Aboelfotoh
Keyword(s):  
Noble Metals ◽  
Annealing Temperature ◽  
Chemical Compounds ◽  
Barrier Properties ◽  
Solid State Reactions ◽  
Transmission Electron ◽  
Stable Chemical ◽  
Metal Thickness ◽  
Amorphous Si ◽  
Si Films

Considerable interest has been generated in solid state reactions between thin films of near noble metals and silicon. These metals deposited on Si form numerous stable chemical compounds at low temperatures and have found applications as Schottky barrier contacts to silicon in VLSI devices. Since the very first phase that nucleates in contact with Si determines the barrier properties, the purpose of our study was to investigate the silicide formation of the near noble metals, Pd and Pt, at very thin thickness of the metal films on amorphous silicon.Films of Pd and Pt in the thickness range of 0.5nm to 20nm were made by room temperature evaporation on 40nm thick amorphous Si films, which were first deposited on 30nm thick amorphous Si3N4 membranes in a window configuration. The deposition rate was 0.1 to 0.5nm/sec and the pressure during deposition was 3 x 10 -7 Torr. The samples were annealed at temperatures in the range from 200° to 650°C in a furnace with helium purified by hot (950°C) Ti particles. Transmission electron microscopy and diffraction techniques were used to evaluate changes in structure and morphology of the phases formed as a function of metal thickness and annealing temperature.

QSAR modeling for predicting carcinogenic potency of nitroso-compounds using 0D-2D molecular descriptors

2007 ◽  
Author(s):  
Maykel González ◽  
Aliuska Helguera ◽  
M. Natália Cordeiro ◽  
Miguel Cabrera Pérez ◽  
Reinaldo Ruiz ◽  
...  
Keyword(s):  
Molecular Descriptors ◽  
Nitroso Compounds ◽  
Qsar Modeling ◽  
Carcinogenic Potency

Analysis of Bioactive Chemical Compounds of Trogoderma granarium (Insecta: Coleoptera: Dermestidae) Using Gas Chromatography – Mass Spectrometry

2017 ◽  
Vol 9 (03) ◽  
Author(s):  
Jenan Mohammed Ubaid ◽  
Abeer Fauzi Al-Rubaye ◽  
Imad Hadi Hameed
Keyword(s):  
Acetic Acid ◽  
Benzoyl Chloride ◽  
Methanolic Extract ◽  
Biological Activities ◽  
Chemical Compounds ◽  
Gas Chromatography Mass Spectrometry ◽  
Pentanoic Acid ◽  
Trogoderma Granarium ◽  
Trans Methyl ◽  
Phenacyl Thiocyanate

Methanolic extract of bioactive compounds of Trogoderma granarium was assayed. GC-MS analysis of Trogoderma granarium revealed the existence of the Pentanoic acid , 1,1-dimethylpropyl ester , (1H)-Pyrimidinone , 5-chloro-4,6- diphenyl, Cyclobutanemethanol , α-methyl- , Nitro-2-methyl-1,3-propanediol , Hydroxylamine ,O-(2-methylpropyl)- , Uridine , 2',3'-O-(phenylmethylene)- ,Acetic acid ,2-benzoylthio-,2-oxo-2-phenylethyl ester , methylpropyl)- , Uridine , 2',3'-O-(phenylmethylene)- , 5'-(4-methylbenzenesulfo , Indolinol , 1-benzoyl-, Benzeneethanol , β-methyl-,(s)- , Acetic acid ,2-benzoylthio-,2-oxo-2-phenylethyl ester , Phenacyl thiocyanate , Deoxy-L-ribose-2,5-dibenzoate , Methenamine , Alanine , N-methyl-n-propargyloxycarbonyl-, decyl ester , Benzoyl chloride , Thiophene-2-ol , benzoate , Ethanone , -(5- nitrotetrazol-2-yl)-1-phenyl- , 2,5-Dimethylhexane-2,5-dihydroperoxide , Benzamide , N-(3-benzylthio-1,2,4-thiadiazol- 5-yl)- , Methyl p-(2-phenyl-1-benzimidazolyl)benzoate , Methyl-2-phenoxyethylamine , Pentaborane(11) , cis-Methoxy- 5-trans-methyl-1R-cyclohexanol , Nitro-1-phenyl-3-(tetrahydropyran-2-yloxy)propan-1-one , cis-Methoxy-5-transmethyl-1R-cyclohexanol. Trogoderma granarium produce many important secondary metabolites with high biological activities.

Study effect of crude extracts of Hibiscus sabdarifa L. on some Enterobacteriaceae

2018 ◽  
Vol 9 (SPL1) ◽  
Author(s):  
Sabreen A Kamal ◽  
Ishraq A Salih ◽  
Hawraa Jawad Kadhim ◽  
Zainab A Tolaifeh
Keyword(s):  
Escherichia Coli ◽  
Ethyl Acetate ◽  
Bacterial Growth ◽  
Chemical Compounds ◽  
Inhibition Zone ◽  
Crude Extracts ◽  
And Control

Red rose or roselle (beauty rose ) is natively known as red tea belong to Malvaceae, it is flowers use traditionally for antihypertensive hepato protective, anticancer,antidiabetic,antibacterial, cytotoxicity and antidiarreal, By preparing red tea from it's flower. In this study, we extract chemical compounds by using two solvent which are Ethanol, Ethyl acetate. so we can extract Anthocyanin which is responsible for red colour of flower with many chemical compounds. then study the effect of these extracts on 5 genera from Enterobacteriacaea which can cause diarrheae (Shigella, Salmonella, Escherichia coli, Proteus and Klebsiella ) by preparing 3 concentrations for each solvent (250, 500, 750 ) mg/ml, and control then compare with two antibiotic (Azereonam 30 mg/ml and Bacitracin 10 mg/ml ) these extracts revealed obvious inhibition zone in bacterial growth.

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