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https://www.readbyqxmd.com/read/28630865/2d-qsar-and-3d-qsar-analyses-for-egfr-inhibitors
#1
Manman Zhao, Lin Wang, Linfeng Zheng, Mengying Zhang, Chun Qiu, Yuhui Zhang, Dongshu Du, Bing Niu
Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28630595/qsar-models-of-human-data-can-enrich-or-replace-llna-testing-for-human-skin-sensitization
#2
Vinicius M Alves, Stephen J Capuzzi, Eugene Muratov, Rodolpho C Braga, Thomas Thornton, Denis Fourches, Judy Strickland, Nicole Kleinstreuer, Carolina H Andrade, Alexander Tropsha
Skin sensitization is a major environmental and occupational health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. We have compiled, curated, analyzed, and compared the available human and LLNA data. Using these data, we have developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance...
December 21, 2016: Green Chemistry: An International Journal and Green Chemistry Resource: GC
https://www.readbyqxmd.com/read/28628322/applying-mondrian-cross-conformal-prediction-to-estimate-prediction-confidence-on-large-imbalanced-bioactivity-datasets
#3
Jiangming Sun, Lars Carlsson, Ernst Ahlberg, Ulf Norinder, Ola Engkvist, Hongming Chen
Conformal prediction has been proposed as a more rigorous way to define prediction confidence compared to other application domain concepts that have earlier been used for QSAR modelling. One main advantage of such a method is that it provides a prediction region potentially with multiple predicted labels, which contrasts to the single valued (regression) or single label (classification) output predictions by standard QSAR modelling algorithms. Standard conformal prediction might not be suitable for imbalanced datasets...
June 19, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28628174/ranking-reach-registered-neutral-ionizable-and-ionic-organic-chemicals-based-on-their-aquatic-persistency-and-mobility
#4
H P H Arp, T N Brown, U Berger, S E Hale
The contaminants that have the greatest chances of appearing in drinking water are those that are mobile enough in the aquatic environment to enter drinking water sources and persistent enough to survive treatment processes. Herein a screening procedure to rank neutral, ionizable and ionic organic compounds for being persistent and mobile organic compounds (PMOCs) is presented and applied to the list of industrial substances registered under the EU REACH legislation as of December 2014. This comprised 5155 identifiable, unique organic structures...
June 19, 2017: Environmental Science. Processes & Impacts
https://www.readbyqxmd.com/read/28628163/-quantitative-structure-activity-relationship-model-for-prediction-of-cardiotoxicity-of-chemical-components-in-traditional-chinese-medicines
#5
(no author information available yet)
OBJECTIVE: Some quantitative structure-activity relationship (QSAR) models have been developed to predict cardiac toxicity of drugs, which have limited predictive power due to based on hERG channel inhibition. The objective of this study was try to develop a QSAR model based on all kinds of cardiac adverse effects, and to predict the potential cardiotoxicity of chemical components in traditional Chinese medicines (TCM). METHODS: In this study, the compounds data of all kinds of cardiac adverse reactions were selected as the training set...
June 18, 2017: Beijing da Xue Xue Bao. Yi Xue Ban, Journal of Peking University. Health Sciences
https://www.readbyqxmd.com/read/28624700/discovery-of-unsymmetrical-aromatic-disulfides-as-novel-inhibitors-of-sars-cov-main-protease-chemical-synthesis-biological-evaluation-molecular-docking-and-3d-qsar-study
#6
Li Wang, Bo-Bo Bao, Guo-Qing Song, Cheng Chen, Xu-Meng Zhang, Wei Lu, Zefang Wang, Yan Cai, Shuang Li, Sheng Fu, Fu-Hang Song, Haitao Yang, Jian-Guo Wang
The worldwide outbreak of severe acute respiratory syndrome (SARS) in 2003 had caused a high rate of mortality. Main protease (M(pro)) of SARS-associated coronavirus (SARS-CoV) is an important target to discover pharmaceutical compounds for the therapy of this life-threatening disease. During the course of screening new anti-SARS agents, we have identified that a series of unsymmetrical aromatic disulfides inhibited SARS-CoV M(pro) significantly for the first time. Herein, 40 novel unsymmetrical aromatic disulfides were synthesized chemically and their biological activities were evaluated in vitro against SARS-CoV M(pro)...
June 9, 2017: European Journal of Medicinal Chemistry
https://www.readbyqxmd.com/read/28622828/the-index-of-ideality-of-correlation-a-criterion-of-predictive-potential-of-qspr-qsar-models
#7
Andrey A Toropov, Alla P Toropova
The index of ideality of correlation (IIC) is a new criterion of the predictive potential of quantitative structure-property/activity relationships (QSPRs/QSARs). This IIC is calculated with using of the correlation coefficient between experimental and calculated values of endpoint for the calibration set, with taking into account the positive and negative dispersions between experimental and calculated values. The mutagenicity is well-known important characteristic of substances from ecological point of view...
July 2017: Mutation Research
https://www.readbyqxmd.com/read/28622647/endocrine-disrupting-activity-of-per-and-polyfluoroalkyl-substances-exploring-combined-approaches-of-ligand-and-structure-based-modeling
#8
Supratik Kar, Maria S Sepúlveda, Kunal Roy, Jerzy Leszczynski
Exposure to perfluorinated and polyfluoroalkyl substances (PFCs/PFASs), endocrine disrupting halogenated pollutants, has been linked to various diseases including thyroid toxicity in human populations across the globe. PFASs can compete with thyroxine (T4) for binding to the human thyroid hormone transport protein transthyretin (TTR) which may lead to reduce thyroid hormone levels leading to endocrine disrupting adverse effects. Environmental fate and endocrine-disrupting activity of PFASs has initiated several research projects, but the amount of experimental data available for these pollutants is limited...
June 9, 2017: Chemosphere
https://www.readbyqxmd.com/read/28622580/combating-breast-cancer-with-non-steroidal-aromatase-inhibitors-nsais-understanding-the-chemico-biological-interactions-through-comparative-sar-qsar-study
#9
REVIEW
Nilanjan Adhikari, Sk Abdul Amin, Achintya Saha, Tarun Jha
It is a challenging task to design target-specific and less toxic non-steroidal aromatase inhibitors (NSAIs) though the modeling studies for designing anti-aromatase molecules have been continuing for more than two decades to fight the dreaded estrogen-dependent breast cancer. In this article, different validated QSAR models are developed and analyzed to understand important physicochemical and structural parameters modulating the aromatase inhibitory activity of NSAIs. Physicochemical properties such as molar refractivity and dipole moment are found to be the most important parameters for controlling aromatase inhibition...
May 30, 2017: European Journal of Medicinal Chemistry
https://www.readbyqxmd.com/read/28621733/discovery-of-indeno-1-2-c-quinoline-derivatives-as-potent-dual-antituberculosis-and-anti-inflammatory-agents
#10
Chih-Hua Tseng, Chun-Wei Tung, Chen-Hsin Wu, Cherng-Chyi Tzeng, Yen-Hsu Chen, Tsong-Long Hwang, Yeh-Long Chen
A series of indeno[1,2-c]quinoline derivatives were designed, synthesized and evaluated for their anti-tuberculosis (anti-TB) and anti-inflammatory activities. The minimum inhibitory concentration (MIC) of the newly synthesized compound was tested against Mycobacterium tuberculosis H37RV. Among the tested compounds, (E)-N'-[6-(4-hydroxypiperidin-1-yl)-11H-indeno[1,2-c]quinolin-11-ylidene]isonicotino-hydrazide (12), exhibited significant activities against the growth of M. tuberculosis (MIC values of 0.96 μg/mL) with a potency approximately equal to that of isoniazid (INH), an anti-TB drug...
June 16, 2017: Molecules: a Journal of Synthetic Chemistry and Natural Product Chemistry
https://www.readbyqxmd.com/read/28610981/3d-qsar-comfa-comsia-molecular-docking-and-molecular-dynamics-simulations-study-of-6-aryl-5-cyano-pyrimidine-derivatives-to-explore-the-structure-requirements-of-lsd1-inhibitors
#11
Lina Ding, Zhi-Zheng Wang, Xu-Dong Sun, Jing Yang, Chao-Ya Ma, Wen Li, Hong-Min Liu
Recently, Histone Lysine Specific Demethylase 1 (LSD1) was regarded as a promising anticancer target for the novel drug discovery. And several small molecules as LSD1 inhibitors in different structures have been reported. In this work, we carried out a molecular modeling study on the 6-aryl-5-cyano-pyrimidine fragment LSD1 inhibitors using three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models...
May 24, 2017: Bioorganic & Medicinal Chemistry Letters
https://www.readbyqxmd.com/read/28610432/qsar-model-for-prediction-of-the-therapeutic-potency-of-n-benzylpiperidine-derivatives-as-ache-inhibitors
#12
S Bitam, M Hamadache, S Hanini
A new family of AChE inhibitors, N-benzylpiperidines, showed exceptional efficacy in vitro and in vivo, minimal side effects and high selectivity for acetylcholinesterase (AChE). Three regression methods were chosen in this work to develop robust predictive models, namely multiple linear regression (MLR), genetic function approximation (GFA) and multilayer perceptron network (MLP). Ten descriptors were selected for a dataset of 99 molecules, using a genetic algorithm. The best results were obtained for MLP with a 10-6-1 artificial neural network model trained with the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm...
June 14, 2017: SAR and QSAR in Environmental Research
https://www.readbyqxmd.com/read/28608547/computational-modeling-of-the-bat-hku4-coronavirus-3cl-pro-inhibitors-as-a-tool-for-the-development-of-antivirals-against-the-emerging-middle-east-respiratory-syndrome-mers-coronavirus
#13
Areej Abuhammad, Rua'a A Al-Aqtash, Brandon J Anson, Andrew D Mesecar, Mutasem O Taha
The Middle East respiratory syndrome coronavirus (MERS-CoV) is an emerging virus that poses a major challenge to clinical management. The 3C-like protease (3CL(pro) ) is essential for viral replication and thus represents a potential target for antiviral drug development. Presently, very few data are available on MERS-CoV 3CL(pro) inhibition by small molecules. We conducted extensive exploration of the pharmacophoric space of a recently identified set of peptidomimetic inhibitors of the bat HKU4-CoV 3CL(pro) ...
June 13, 2017: Journal of Molecular Recognition: JMR
https://www.readbyqxmd.com/read/28604902/what-if-the-number-of-nanotoxicity-data-is-too-small-for-developing-predictive-nano-qsar-models-an-alternative-read-across-based-approach-for-filling-data-gaps
#14
Agnieszka Gajewicz
Over the past decade, computational nanotoxicology, in particular Quantitative Structure-Activity Relationship models (Nano-QSAR) that help in assessing the biological effects of nanomaterials, have received much attention. In effect, a solid basis for uncovering the relationships between the structure and property/activity of nanoparticles has been created. Nonetheless, six years after the first pioneering computational studies focusing on the investigation of nanotoxicity were commenced, these computational methods still suffer from many limitations...
June 12, 2017: Nanoscale
https://www.readbyqxmd.com/read/28604113/qsar-models-for-predicting-the-toxicity-of-piperidine-derivatives-against-aedes-aegypti
#15
J P Doucet, E Papa, A Doucet-Panaye, J Devillers
QSAR models are proposed for predicting the toxicity of 33 piperidine derivatives against Aedes aegypti. From 2D topological descriptors, calculated with the PaDEL software, ordinary least squares multilinear regression (OLS-MLR) treatment from the QSARINS software and machine learning and related approaches including linear and radial support vector machine (SVM), projection pursuit regression (PPR), radial basis function neural network (RBFNN), general regression neural network (GRNN) and k-nearest neighbours (k-NN), led to four-variable models...
June 12, 2017: SAR and QSAR in Environmental Research
https://www.readbyqxmd.com/read/28601761/improving-virtual-screening-predictive-accuracy-of-human-kallikrein-5-inhibitors-using-machine-learning-models
#16
Xingang Fang, Sikha Bagui, Subhash Bagui
The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule...
May 29, 2017: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/28599185/qsar-models-for-predicting-acute-toxicity-of-pesticides-in-rainbow-trout-using-the-coral-software-and-efsa-s-openfoodtox-database
#17
Andrey A Toropov, Alla P Toropova, Marco Marzo, Jean Lou Dorne, Nikolaos Georgiadis, Emilio Benfenati
Optimal (flexible) descriptors were used to establish quantitative structure - activity relationships (QSAR) for toxicity of pesticides (n=116) towards rainbow trout. A heterogeneous set of hundreds of pesticides has been used, taken from the EFSA's chemical Hazards Database: OpenFoodTox. Optimal descriptors are preparing from simplified molecular input-line entry system (SMILES). So-called, correlation weights of different fragments of SMILES are calculating by the Monte Carlo optimization procedure where correlation coefficient between endpoint and optimal descriptor plays role of the target function...
May 23, 2017: Environmental Toxicology and Pharmacology
https://www.readbyqxmd.com/read/28595521/a-comparative-study-on-selective-ppar-modulators-through-quantitative-structure-activity-relationship-pharmacophore-and-docking-analyses
#18
Ashis Nandy, Kunal Roy, Achintya Saha
BACKGROUND: Metabolic syndrome is a matrix of different metabolic disorders which are the leading cause of death in human beings. Peroxysome proliferated activated receptor (PPAR) is a nuclear receptor involvedin metabolism of fats and glucose. OBJECTIVE: In order to explore structural requirements for selective PPAR modulators to control lipid and carbohydrate metabolism, the multi-cheminformatics studies have been performed. METHOD: Insilico modeling studies have been performed on a diverse set of PPAR modulators through quantitative structural-activity relationship (QSAR), pharmacophore mapping and docking studies...
June 8, 2017: Current Computer-aided Drug Design
https://www.readbyqxmd.com/read/28595068/molecular-topology-a-new-strategy-for-antimicrobial-resistance-control
#19
Riccardo Zanni, Maria Galvez-Llompart, Jesus Machuca, Ramon Garcia-Domenech, Esther Recacha, Alvaro Pascual, Jose Manuel Rodriguez-Martinez, Jorge Galvez
The control of antimicrobial resistance (AMR) seems to have come to an impasse. The use and abuse of antibacterial drugs has had major consequences on the genetic mutability of both pathogenic and nonpathogenic microorganisms, leading to the development of new highly resistant strains. Because of the complexity of this situation, an in silico strategy based on QSAR molecular topology was devised to identify synthetic molecules as antimicrobial agents not susceptible to one or several mechanisms of resistance such as: biofilms formation (BF), ionophore (IA) activity, epimerase (EI) activity or SOS system (RecA inhibition)...
May 30, 2017: European Journal of Medicinal Chemistry
https://www.readbyqxmd.com/read/28594241/hepatotoxicity-evaluation-of-traditional-chinese-medicines-using-a-computational-molecular-model
#20
Pan Zhao, Bin Liu, Chunya Wang
BACKGROUND: Liver injury caused by traditional Chinese medicines (TCMs) is reported from many countries around the world. TCM hepatotoxicity has attracted worldwide concerns. OBJECTIVE: This study aims to develop a more applicable and optimal tool to evaluate TCM hepatotoxicity. METHODS: A quantitative structure-activity relationship (QSAR) analysis was performed based on published data and U.S. Food and Drug Administration's Liver Toxicity Knowledge Base (LTKB)...
June 8, 2017: Clinical Toxicology
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