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https://www.readbyqxmd.com/read/28729623/3d-qsar-studies-on-maslinic-acid-analogs-for-anticancer-activity-against-breast-cancer-cell-line-mcf-7
#1
Sarfaraz Alam, Feroz Khan
Global prevalence of breast cancer and its rising frequency makes it a key area of research in drug discovery programs. The research article describes the development of field based 3D-QSAR model based on human breast cancer cell line MCF7 in vitro anticancer activity, which defines the molecular level understanding and regions of structure-activity relationship for triterpene maslinic acid and its analogs. The key features such as average shape, hydrophobic regions and electrostatic patterns of active compounds were mined and mapped to virtually screen potential analogs...
July 20, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28728491/catalogic-301c-model-validation-and-improvement
#2
N H Dimitrova, I A Dermen, N D Todorova, K G Vasilev, S D Dimitrov, O G Mekenyan, Y Ikenaga, T Aoyagi, Y Zaitsu, C Hamaguchi
In Europe, REACH legislation encourages the use of alternative in silico methods such as (Q)SAR models. According to the recent progress of Chemical Substances Control Law (CSCL) in Japan, (Q)SAR predictions are also utilized as supporting evidence for the assessment of bioaccumulation potential of chemicals along with read across. Currently, the effective use of read across and QSARs is examined for other hazards, including biodegradability. This paper describes the results of external validation and improvement of CATALOGIC 301C model based on more than 1000 tested new chemical substances of the publication schedule under CSCL...
June 2017: SAR and QSAR in Environmental Research
https://www.readbyqxmd.com/read/28727421/shallow-representation-learning-via-kernel-pca-improves-qsar-modelability
#3
Stefano E Rensi, Russ B Altman
Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure activity relationships (QSAR), but have been eclipsed in performance by non-linear methods. Support vector machines (SVMs) and neural networks are currently among the most popular and accurate QSAR methods because they learn new representations of the data that greatly improve modelability. In this work we use shallow representation learning to improve the accuracy of L1 regularized logistic regression (LASSO) and meet the performance of Tanimoto SVM...
July 20, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28726171/qsar-modeling-docking-and-admet-studies-for-exploration-of-potential-anti-malarial-compounds-against-plasmodium-falciparum
#4
Tabish Qidwai
Development of resistance in the Plasmodium falciparum to Artemisinin, the most effective anti-malarial compound, threatens malaria elimination tactics. To gain more efficacious Artemisinin derivatives, QSAR modeling and docking was performed. In the present study, 2D-QSAR model and molecular docking were used to evaluate the Artemisinin compounds and to reveal their binding modes and structural basis of inhibitory activity. Moreover, ADMET-related descriptors have been calculated to predict the pharmacokinetic properties of the effective compounds...
December 2016: In Silico Pharmacology
https://www.readbyqxmd.com/read/28723087/developing-collaborative-qsar-models-without-sharing-structures
#5
Peter Gedeck, Suzanne Skolnik, Stephane Rodde
It is widely understood that QSAR models greatly improve if more data are used. However, irrespective of model quality, once chemical structures diverge too far from the initial data set, the predictive performance of a model degrades quickly. To increase the applicability domain we need to increase the diversity of the training set. This can be achieved by combining data from diverse sources. Public data can be easily included, however proprietary data may be more difficult to add due to intellectual property concerns...
July 19, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28722475/ann-qsar-workflow-for-predicting-the-inhibition-of-hiv-1-reverse-transcriptase-by-pyridinone-non-nucleoside-derivatives
#6
Abolfazl Barzegar, Elham Zamani-Gharehchamani, Ali Kadkhodaie-Ilkhchi
AIM: Pyridinone derivatives have high potency against non-nucleoside reverse transcriptase inhibitor (NNRTI)-resistant human immunodeficiency virus type-1 strains. Quantitative structure-activity relationship (QSAR) studies on a series of pyridinone derivatives acting as NNRTIs are very important in designing the next generation of NNRTIs. Methodology & results: The QSAR models were developed using linear (single and forward stepwise) and combined nonlinear artificial neural network (ANN) approaches...
July 19, 2017: Future Medicinal Chemistry
https://www.readbyqxmd.com/read/28720328/design-synthesis-molecular-modeling-and-anti-hyperglycemic-evaluation-of-quinazolin-4-3h-one-derivatives-as-potential-ppar%C3%AE-and-sur-agonists
#7
Mohamed K Ibrahim, Ibrahim H Eissa, Mohamed S Alesawy, Ahmed M Metwaly, Mohamed M Radwan, Mahmoud A ElSohly
Peroxisome proliferator-activated receptor gamma (PPARγ) and sulfonylurea receptor (SUR) play crucial roles in management of type-2 diabetes mellitus. In this study, a series of novel quinazoline-4(3H)-one-sulfonylurea hybrids were designed and synthesized as dual PPARγ and SUR agonists. The synthesized compounds were evaluated for their in vivo anti-hyperglycemic activities against STZ-induced hyperglycemic rats. Four compounds (19a, 19d, 19f and 25g) demonstrated potent activities with reduction in blood glucose levels of 40...
July 8, 2017: Bioorganic & Medicinal Chemistry
https://www.readbyqxmd.com/read/28715707/design-synthesis-and-2d-qsar-study-of-novel-pyridine-and-quinolone-hydrazone-derivatives-as-potential-antimicrobial-and-antitubercular-agents
#8
Mohamed A Abdelrahman, Ismail Salama, Mohamed S Gomaa, Mahmoud M Elaasser, Marwa M Abdel-Aziz, Dalia H Soliman
The increased development of highly resistant bacterial strains and tuberculosis, constitute a serious public health threat, highlighting the urgent need of novel antibacterial agents. In this work, two novel series of nicotinic acid hydrazone derivatives (6a-r) and quinolone hydrazide derivatives (12a-l) were synthesized and evaluated as antimicrobial and antitubercular agents. The synthesized compounds were evaluated in vitro for their antibacterial, antifungal and antimycobacterial activities. Compounds 6f and 6p bearing the 3,4,5- (OCH3)3 and 2,5-(OCH3)2 benzylidene motifs were the most potent and as antibacterial, antifungal (MIC: 0...
July 4, 2017: European Journal of Medicinal Chemistry
https://www.readbyqxmd.com/read/28715209/comparison-of-the-predictive-performance-and-interpretability-of-random-forest-and-linear-models-on-benchmark-datasets
#9
Richard Liam Marchese Robinson, Anna Palczewska, Jan Palczewski, Nathan Kidley
The ability to interpret the predictions made by quantitative structure activity relationships (QSARs) offers a number of advantages. Whilst QSARs built using non-linear modelling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modelling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting non-linear QSAR models in general and Random Forest in particular...
July 17, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28714799/in-silico-approaches-to-identify-novel-myeloid-cell-leukemia-1-mcl-1-inhibitors-for-treatment-of-cancer
#10
Ji-Xia Ren, Cheng-Ping Li, Xiu-Ling Zhou, Xue-Song Cao, Yong Xie
Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using "Receptor-Ligand Pharmacophore Generation" method and manual build feature method, and then carefully validated by a test database...
July 17, 2017: Journal of Biomolecular Structure & Dynamics
https://www.readbyqxmd.com/read/28713276/structure-activity-relationships-of-pentacyclic-triterpenoids-as-potent-and-selective-inhibitors-against-human-carboxylesterase-1
#11
Li-Wei Zou, Tong-Yi Dou, Ping Wang, Wei Lei, Zi-Miao Weng, Jie Hou, Dan-Dan Wang, Yi-Ming Fan, Wei-Dong Zhang, Guang-Bo Ge, Ling Yang
Human carboxylesterase 1 (hCE1), one of the most important serine hydrolases distributed in liver and adipocytes, plays key roles in endobiotic homeostasis and xenobiotic metabolism. This study aimed to find potent and selective inhibitors against hCE1 from phytochemicals and their derivatives. To this end, a series of natural triterpenoids were collected and their inhibitory effects against human carboxylesterases (hCEs) were assayed using D-Luciferin methyl ester (DME) and 6,8-dichloro-9,9-dimethyl-7-oxo-7,9-dihydroacridin-2-yl benzoate (DDAB) as specific optical substrate for hCE1, and hCE2, respectively...
2017: Frontiers in Pharmacology
https://www.readbyqxmd.com/read/28710924/identification-of-new-bace1-inhibitors-using-pharmacophore-and-molecular-dynamics-simulations-approach
#12
Anantha Krishnan Dhanabalan, Manish Kesherwani, Devadasan Velmurugan, Krishnasamy Gunasekaran
Inhibition of β-Secretase (BACE1) is crucial for the treatment of Alzheimer's disease (AD). Availability of BACE1 crystal structures in both apo and complexed forms enables to find structure-based BACE1 inhibitors for controlling AD. There are two catalytic aspartates (ASP32 and ASP228) presents in the active domain of BACE1. In order to understand the binding mechanism and structure-activity relationship of amidine-containing BACE1 inhibitors, molecular docking, and pharmacophore and 3D-QSAR studies have been carried out with 34 amidine derivatives to develop a pharmacophore model...
June 8, 2017: Journal of Molecular Graphics & Modelling
https://www.readbyqxmd.com/read/28708269/heme-oxygenase-database-hemeoxdb-and-qsar-analysis-of-isoform-1-inhibitors
#13
Emanuele Amata, Agostino Marrazzo, Maria Dichiara, Maria N Modica, Loredana Salerno, Orazio Prezzavento, Giovanni Nastasi, Antonio Rescifina, Giuseppe Romeo, Valeria Pittalà
Due to the increasing interest in the field of heme oxygenases (HOs), we have built a ligand database named HemeOxDB that includes the entire set of known HO-1 and HO-2 inhibitors, resulting in more than 400 compounds. The HemeOxDB is available online at http://www.researchdsf.unict.it/hemeoxdb/, and having a robust search engine allows the end-users to build complex queries, sort tabulated results, generate color coded 2D (two dimension) and 3D (three dimension) graphs, and is will grow to be a tool for the design of potent and selective HO-1 or HO-2 inhibitors...
July 14, 2017: ChemMedChem
https://www.readbyqxmd.com/read/28707599/designing-of-selective-%C3%AE-secretase-inhibitory-benzenesulfonamides-through-comparative-in-vitro-and-in-silico-analysis
#14
Neeraj Masand, Satya P Gupta, Ratan Lal Khosa
BACKGROUND: In Alzheimer's disease (AD), the gene mutations have been identified in the amyloid precursor protein (APP), the presenilin-1 (PS1) and -2 (PS2) genes. APP is a transmembrane protein which gets cleaved by α- and β-secretase enzymes and releases Aβ peptides which forms senile plaques in brain tissue. It contributes for local inflammatory response, subsequent oxidative stress, biochemical changes and neuronal death. Targeting the development of Aβ aggregates in the senile plaques is an important strategy in the treatment of AD...
July 13, 2017: Current Drug Discovery Technologies
https://www.readbyqxmd.com/read/28707592/rational-drug-design-of-antineoplastic-agents-using-3d-qsar-cheminformatic-and-virtual-screening-approaches
#15
Jelica Vucicevic, Katarina Nikolic, John B O Mitchell
BACKGROUND: Computer-Aided Drug Design has strongly accelerated the development of novel antineoplastic agents by helping in the hit identification, optimization, and evaluation. RESULTS: Computational approaches such as cheminformatic search, virtual screening, pharmacophore modeling, molecular docking and dynamics have been developed and applied to explain the activity of bioactive molecules, design novel agents, increase the success rate of drug research, and decrease the total costs of drug discovery...
July 12, 2017: Current Medicinal Chemistry
https://www.readbyqxmd.com/read/28705120/qsar-docking-admet-system-pharmacology-studies-on-tormentic-acid-derivatives-for-anticancer-activity
#16
Sarfaraz Alam, Feroz Khan
To explore the anticancer compounds from tormentic acid derivatives, a quantitative structure-activity relationship (QSAR) model was developed by the multiple linear regression methods. The developed QSAR model yielded a high activity-descriptors relationship accuracy of 94% referred by regression coefficient (r(2)= 0.94) and a high activity prediction accuracy of 91%. The QSAR study indicates that chemical descriptors, chiV5, T_T_Cl_7, T_2_T_4, SsCH3count, and Epsilon3 are significantly correlated with anticancer activity...
July 14, 2017: Journal of Biomolecular Structure & Dynamics
https://www.readbyqxmd.com/read/28705027/tensor-algebra-based-geometric-methodology-to-codify-central-chirality-on-organic-molecules
#17
C R García-Jacas, Y Marrero-Ponce, T Hernández-Ortega, K Martinez-Mayorga, L Cabrera-Leyva, J C Ledesma-Romero, I Aguilera-Fernández, A R Rodríguez-León
A novel mathematical procedure to codify chiral features of organic molecules in the QuBiLS-MIDAS framework is introduced. This procedure constitutes a generalization to that commonly used to date, where the values 1 and -1 (correction factor) are employed to weight the molecular vectors when each atom is labelled as R (rectus) or S (sinister) according to the Cahn-Ingold-Prelog rules. Therefore, values in the range [Formula: see text] with steps equal to 0.25 may be accounted for. The atoms labelled R or S can have negative and positive values assigned (e...
July 14, 2017: SAR and QSAR in Environmental Research
https://www.readbyqxmd.com/read/28705017/impact-of-geometry-optimization-methods-on-qsar-modelling-a-case-study-for-predicting-human-serum-albumin-binding-affinity
#18
S Önlü, M Türker Saçan
Quantitative structure-activity relationship (QSAR) modelling is a major tool employed in the prediction of various endpoints. However, current QSAR literature is missing a full understanding of the impact of quantum chemical calculation methods on the estimation of molecular descriptors and model performance. Here, we provide a comprehensive analysis of the quantitative effects of different geometry optimization methods (semi-empirical, ab initio Hartee-Fock and density functional theory) on the molecular descriptors...
July 14, 2017: SAR and QSAR in Environmental Research
https://www.readbyqxmd.com/read/28703021/prediction-of-pesticide-acute-toxicity-using-two-dimensional-chemical-descriptors-and-target-species-classification
#19
T M Martin, C R Lilavois, M G Barron
Previous modelling of the median lethal dose (oral rat LD50) has indicated that local class-based models yield better correlations than global models. We evaluated the hypothesis that dividing the dataset by pesticidal mechanisms would improve prediction accuracy. A linear discriminant analysis (LDA) based-approach was utilized to assign indicators such as the pesticide target species, mode of action, or target species - mode of action combination. LDA models were able to predict these indicators with about 87% accuracy...
July 13, 2017: SAR and QSAR in Environmental Research
https://www.readbyqxmd.com/read/28702798/the-differential-absorption-of-a-series-of-p-glycoprotein-substrates-in-isolated-perfused-lungs-from-mdr1a-1b-genetic-knockout-mice-can-be-attributed-to-distinct-physico-chemical-properties-an-insight-into-predicting-transporter-mediated-pulmonary-specific
#20
Daniel F Price, Chris N Luscombe, Peter J Eddershaw, Chris D Edwards, Mark Gumbleton
PURPOSE: To examine if pulmonary P-glycoprotein (P-gp) is functional in an intact lung; impeding the pulmonary absorption and increasing lung retention of P-gp substrates administered into the airways. Using calculated physico-chemical properties alone build a predictive Quantitative Structure-Activity Relationship (QSAR) model distinguishing whether a substrate's pulmonary absorption would be limited by P-gp or not. METHODS: A panel of 18 P-gp substrates were administered into the airways of an isolated perfused mouse lung (IPML) model derived from Mdr1a/Mdr1b knockout mice...
July 12, 2017: Pharmaceutical Research
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