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SAR and QSAR in Environmental Research

L Kong, L Zhang
In Gram-negative bacteria, a wide range of proteins are secreted by highly specialized secretion systems. These secreted proteins play essential roles in the response of bacteria to their environment and also in several physiological processes such as adhesion, pathogenicity, adaptation and survival. Therefore, identifying secreted proteins in Gram-negative bacteria may assist in understanding the secretion mechanism and development of new antimicrobial strategies. Considering that a single-feature model is less likely to comprehensively cover this information, three kinds of feature models were used in this paper to represent protein samples by composition analysis, correlation analysis and smoothing encoding method on position-specific scoring matrix profiles...
February 11, 2019: SAR and QSAR in Environmental Research
A M Al-Fakih, Z Y Algamal, M H Lee, M Aziz, H T M Ali
An improved binary differential search (improved BDS) algorithm is proposed for QSAR classification of diverse series of antimicrobial compounds against Candida albicans inhibitors. The transfer functions is the most important component of the BDS algorithm, and converts continuous values of the donor into discrete values. In this paper, the eight types of transfer functions are investigated to verify their efficiency in improving BDS algorithm performance in QSAR classification. The performance was evaluated using three metrics: classification accuracy (CA), geometric mean of sensitivity and specificity (G-mean), and area under the curve...
February 8, 2019: SAR and QSAR in Environmental Research
S Lata, Vikas
Carbon nanotubes (CNTs) have taken precedence over activated carbon in various applications where adsorption is the primary process. The adsorption of chemical compounds by CNTs and activated carbon is most often predicted through linear free energy/solvation energy relationships (LFERs/LSERs). This work proposes quantum-mechanical LSER models based on a combination of quantum-mechanical descriptors and solvatochromic descriptors of LSERs for predicting the adsorption of aromatic organic compounds by activated carbon at varying adsorbate concentrations...
February 7, 2019: SAR and QSAR in Environmental Research
X Yu, Y Wang, H Yang, X Huang
Thousands of investigations on quantitative structure-activity/property relationships (QSARs/QSPRs) have been reported. However, few publications can be found that deal with QSARs for aptamers, because calculating two-dimensional and three-dimensional descriptors directly from aptamers (typically with 15-45 nucleotides) is difficult. This paper describes calculating molecular descriptors from amino acid sequences that are translated from DNA aptamer sequences with DNAMAN software, and developing QSAR models for the aptamers' binding affinity to the influenza virus...
January 14, 2019: SAR and QSAR in Environmental Research
B Sepehri, R Ghavami
In this study, based on molecular docking analysis and comparative molecular field analysis (CoMFA) modelling of a series of 71 CD38 inhibitors including 4‑amino-8-quinoline carboxamides and 2,4-diamino-8-quinazoline carboxamides, new CD38 inhibitors were designed. The interactions of the molecules with the greatest and the lowest activities with the nicotinamide mononucleotide (NMN) binding site were investigated by molecular docking analysis. A CoMFA model with four partial least squares regression (PLSR) components was developed to predict the CD38 inhibitory activity of the molecules...
November 29, 2018: SAR and QSAR in Environmental Research
F Ding, Z Wang, X Yang, L Shi, J Liu, G Chen
Both the acute toxicity and chronic toxicity data on aquatic organisms are indispensable parameters in the ecological risk assessment priority chemical screening process (e.g. persistent, bioaccumulative and toxic chemicals). However, most of the present modelling actions are focused on developing predictive models for the acute toxicity of chemicals to aquatic organisms. As regards chronic aquatic toxicity, considerable work is needed. The major objective of the present study was to construct in silico models for predicting chronic toxicity data for Daphnia magna and Pseudokirchneriella subcapitata...
November 27, 2018: SAR and QSAR in Environmental Research
L Dang, S Zhang
A four-descriptor quantitative structure-property relationship model was constructed to predict 65 intrinsic viscosities [η] of polymer solutions. Four quantum chemical descriptors, the traceless quadrupole moment θ(R) , the hydrogen bond or electrostatic attraction descriptor QH , the partition function QBOT(R) and the frontier orbital descriptor EHOMO , were calculated with density functional theory at the B3LYP/6-31G(d) level and used to develop the model by multivariate linear regression (MLR) analysis...
December 2018: SAR and QSAR in Environmental Research
M Salahinejad, E Zolfonoun
The Quantitative Ion Character-Activity Relationship (QICAR) method was used for correlating metal ionic characteristics with the maximum adsorption capacity (qmax ) of multi-walled carbon for heavy metals. The experimental values of qmax for 25 heavy metal ions, estimated by the Langmuir isotherm model, were used to construct a QICAR model. The genetic algorithm, enhanced replacement method and successive projection algorithm procedures were applied as variable selection algorithms to choose the optimal subsets of descriptors...
December 2018: SAR and QSAR in Environmental Research
R Tumdam, A Kumar, N Subbarao, B S Balaji
Bromodomain-containing protein 4 (BRD4) is a member of the bromodomain and extra-terminal domain (BET) family of proteins. It epigentically regulates the transcription of growth-promoting genes and has become an attractive target for the development of anticancer and anti-inflammatory agents. In the current study, we performed an in silico screening of a small-molecule chemical library against the acetyl-lysine binding site of the first bromodomain (BD1) in BRD4 protein. Potential inhibitors identified through virtual screening were further studied through molecular dynamics simulations, water entrapment analysis and Molecular Mechanics (MM)/Poisson-Boltzmann surface area (PBSA) binding free energy calculations...
December 2018: SAR and QSAR in Environmental Research
M A Azam, S Jupudi, N Saha, R K Paul
The ATP-dependent bacterial MurD enzyme catalyses the formation of the peptide bond between cytoplasmic intermediate UDP-N-acetylmuramoyl-L-alanine and D-glutamic acid. This is essential for bacterial cell wall peptidoglycan synthesis in both Gram-positive and Gram-negative bacteria. MurD is recognized as an important target for the development of new antibacterial agents. In the present study we prepared the 3D-stucture of the catalytic pocket of the Staphylococcus aureus MurD enzyme by homology modelling...
November 8, 2018: SAR and QSAR in Environmental Research
P M Khan, K Roy
The glass transition temperature is a vital property of polymers with a direct impact on their stability. In the present study, we built quantitative structure-property relationship models for the prediction of the glass transition temperatures of polymers using a data set of 206 diverse polymers. Various 2D molecular descriptors were computed from the single repeating units of polymers. We derived five models from different combinations of six descriptors in each case by employing the double cross-validation technique followed by partial least squares regression...
November 5, 2018: SAR and QSAR in Environmental Research
K Inthajak, P Toochinda, L Lawtrakul
A series of antifolate compounds, i.e. 1-(4-chlorophenyl)-6,6-dimethyl-1,3,5-triazine-2,4-diamine, or cycloguanil analogues, have shown effective inhibiting properties against Plasmodium falciparum dihydrofolate reductase (PfDHFR). In this work, the stereoselectivity of PfDHFR to the R and S enantiomer of cycloguanil analogues was obtained from molecular docking calculations and integrated into QSAR study to obtain a more accurate prediction model. Results indicate that PfDHFR can bind to cycloguanil analogues in the R and S enantiomers...
November 1, 2018: SAR and QSAR in Environmental Research
S Ahmadi, A Akbari
In this investigation, quantitative structure-property relationship (QSPR) modelling of adsorption coefficients of 69 aromatic compounds on multi-wall carbon nanotubes (MWCNTs) was studied using the Monte Carlo method. QSPR models were calculated with CORAL software, and optimal descriptors were calculated with the simplified molecular input line entry system (SMILES) and hydrogen-suppressed molecular graphs (HSGs). The aromatic compound data set was randomly split into training, invisible training, calibration and validation sets...
November 2018: SAR and QSAR in Environmental Research
A K Halder
Multiple Quantitative Structure-Activity Relationship (QSAR) analysis is widely used in drug discovery for lead identification. Human Immunodeficiency Virus (HIV) protease is one of the key targets for the treatment of Acquired Immunodeficiency Syndrome (AIDS). One of the major challenges for the design of HIV-1 protease inhibitors (HIV PRIs) is to increase the inhibitory activities against the enzyme to a level where the problem associated to drug resistance may be considerably delayed. Herein, chemometric analyses were performed with 346 structurally diverse HIV PRIs with experimental bioactivities against a sub-type B mutant to develop highly predictable QSAR models and also to identify the effective structural determinants for higher affinity against HIV PR...
November 2018: SAR and QSAR in Environmental Research
F Zhang, M Bartels, A Clark, T Erskine, T Auernhammer, B Bhhatarai, D Wilson, S Marty
The accurate prediction of toxicokinetic parameters arising from oral, dermal and inhalation routes of chemical exposure is a key element in chemical safety assessments. In this research, the physiologically based pharmacokinetic (PBPK) GastroPlusTM software was evaluated against a series of chemicals for the prediction of toxicokinetic parameters. Overall, 67% of predicted intrinsic clearance (Clint) values were within 1- to 10-fold of empirical data for 463 compounds, and 87% of the predicted fraction unbounded in plasma (Fup) values were 1- to 3-fold of empirical data for 441 compounds...
November 2018: SAR and QSAR in Environmental Research
R Li, Y Du, J Shen
BTK inhibitors have been proved as an effective target for B-cell malignancies. Ibrutinib is the most advanced irreversible BTK inhibitor for treating mantle cell lymphoma/chronic lymphocytic leukaemia but with existing drug resistance and adverse effects. To design novel effective and safety reversible BTK inhibitors, 115 newly cinnoline analogues were selected to perform molecular docking and 3D-QSAR study because of the main scaffold similarity to Ibrutinib. Both established CoMFA and CoMSIA models obtained high predictive and satisfactory value...
November 2018: SAR and QSAR in Environmental Research
Y Xi, Z Qin, A Yan
Cyclooxygenase-1 (COX-1) is one isoform of COX, and it is a main target of nonsteroidal anti-inflammatory drugs (NSAIDs). It is important to develop efficient and selective COX-1 inhibitors. In this work, 12 classification models for 1530 cyclooxygenase-1 (COX-1) inhibitors were built by support vector machine (SVM), decision tree (DT) and random forest (RF) methods. The best classification model (model 1A) was built by SVM with MACCS fingerprints. The classification accuracies for the training and test sets were 99...
October 2018: SAR and QSAR in Environmental Research
O A Raevsky, V Yu Grigorev, D E Polianczyk, O E Raevskaja, J C Dearden
Assessment of the influence of six physicochemical properties used in the multiparameter optimization (MPO) approach for chemical penetration of the blood-brain barrier was carried out by means of application of logistic regression and multiple linear regression, using a data set of 578 diverse chemicals. It was found that use of an aggregation MPO-score descriptor did not give satisfactory results with central nervous system (CNS)/non-CNS classification. Thus an application of the MPO approach for CNS penetration is ambiguous...
October 2018: SAR and QSAR in Environmental Research
C Braeuning, A Braeuning, H Mielke, A Holzwarth, M Peiser
In vivo skin sensitization assays have to be provided by applicants to the competent authorities in the European Union for the approval of active substances (AS) in pesticides. This study aimed to test the practicability of in silico predictions for AS by freely available (Q)SAR tools to evaluate their use as a time- and cost-effective alternative to animal testing in the context of the 3R concept. Predictions of skin sensitization for 48 selected sensitizing and non-sensitizing AS by the software programs CAESAR, Toxtree, OECD (Q)SAR Toolbox, CASE Ultra, Leadscope and SciQSAR were collected and compared...
October 2018: SAR and QSAR in Environmental Research
A Bak, V Kozik, I Malik, J Jampilek, A Smolinski
The current study examines in silico characterization of the structure-inhibitory potency for a set of phenylcarbamic acid derivatives containing an N-arylpiperazine scaffold, considering the electronic, steric and lipophilic properties. The main objective of the ligand-based modelling was the systematic study of classical comparative molecular field analysis (CoMFA)/comparative molecular surface analysis (CoMSA) performance for the modelling of in vitro efficiency observed for these phenylcarbamates, revealing their inhibitory activities against a virulent Mycobacterium tuberculosis H37 Rv strain...
October 2018: SAR and QSAR in Environmental Research
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