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SAR and QSAR in Environmental Research

E Nazarshodeh, R Sheikhpour, S Gharaghani, M A Sarram
Carbonic anhydrases (CAs) are essential enzymes in biological processes. Prediction of the activity of compounds towards CA isoforms could be evaluated by computational techniques to discover a novel therapeutic inhibitor. Studies such as quantitative structure-activity relationships (QSARs), molecular docking and pharmacophore modelling have been carried out to design potent inhibitors. Unfortunately, QSAR does not consider the information of target space in the model. We successfully developed an in silico proteochemometrics model that simultaneously uses target and ligand descriptors to predict the activities of CA inhibitors...
June 2018: SAR and QSAR in Environmental Research
K Kranthi Kumar, B Uma Devi, P Neeraja
In this study, cholesterol biotransformation gene-set of human steroidogenic acute regulatory protein-related lipid transfer (START) domains were evaluated from high-throughput gene screening approaches. It was shown that STARD1, STARD3 and STARD4 proteins are better effective transporters of cholesterol than STARD5 and STARD6 domains. Docking studies show a strong agreement with gene ontology enrichment data. According to both complementary strategies, it was found that only STARD1, STARD3 and STARD4 are potentially involved in cholesterol biotransformation in mitochondria through Ω1-loop of C-terminal α4-helical domain...
June 2018: SAR and QSAR in Environmental Research
Y Liang, S Zhang, S Ding
Gram-negative bacterial secreted proteins play different roles in invaded eukaryotic cells and cause various diseases. Prediction of Gram-negative bacterial secreted protein types is a meaningful and challenging task. In this paper, we develop a multiple statistical features extraction model based on the dipeptide composition (DPC) descriptor and the detrended moving-average auto-cross-correlation analysis (DMACA) descriptor by PSI-BLAST profile. A 610-dimensional feature vector was constructed on the training set, and the feature extraction model was denoted DPC-DMACA-PSSM...
June 2018: SAR and QSAR in Environmental Research
J M Fitzpatrick, D W Roberts, G Patlewicz
Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives, such as expert systems software. Here we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge-based) and TIMES-SS (hybrid), and evaluated their performance using two large sets of animal data: one set of 1249 substances from eChemportal and a second set of 515 substances from NICEATM...
June 2018: SAR and QSAR in Environmental Research
A A Elfiky, A M Ismail
A new Zika virus (ZIKV) outbreak started in 2015. According to the World Health Organization, 84 countries confirmed ZIKV infection. RNA-dependent RNA polymerase (RdRp) was an appealing target for drug designers during the last two decades. Through molecular docking, we screened 16 nucleotide/side inhibitors against ZIKV RdRp. While the mode of interaction with ZIKV is different from that in the hepatitis C virus (HCV), nucleotide/side inhibitors in this study (mostly anti-HCV) showed promising binding affinities (-6...
May 2018: SAR and QSAR in Environmental Research
S A Amin, N Adhikari, S Bhargava, T Jha, S Gayen
The current study deals with chemometric modelling strategies (Naïve Bayes classification, hologram-based quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)) to explore the important features of hydroxylamine derivatives for exerting potent human immunodeficiency virus-1 (HIV-1) protease inhibition. Depending on the statistically validated reliable and robust quantitative structure-activity relationship (QSAR) models, important and crucial structural features have been identified that may be responsible for enhancing the activity profile of these hydroxylamine compounds...
May 2018: SAR and QSAR in Environmental Research
I Luque Ruiz, M Á Gómez-Nieto
The development of robust QSAR models to predict the activity of molecules of β-secretase inhibitors is an area of interest due to the increase of Alzheimer's disease in patients in the global population. In this paper, we present a proposal based on the use of relative distance matrices as input data to the QSAR algorithms. These matrices store measurements of distances between the structural characteristics of pairs of molecules and between the molecules and a structural pattern extracted from the whole data set, thus efficiently representing a correlation between structural changes and activity...
May 2018: SAR and QSAR in Environmental Research
A M Al-Fakih, Z Y Algamal, M H Lee, M Aziz
A penalized quantitative structure-property relationship (QSPR) model with adaptive bridge penalty for predicting the melting points of 92 energetic carbocyclic nitroaromatic compounds is proposed. To ensure the consistency of the descriptor selection of the proposed penalized adaptive bridge (PBridge), we proposed a ridge estimator ([Formula: see text]) as an initial weight in the adaptive bridge penalty. The Bayesian information criterion was applied to ensure the accurate selection of the tuning parameter ([Formula: see text])...
May 2018: SAR and QSAR in Environmental Research
P De, K Roy
Persistent, bioaccumulative and toxic (PBT) chemicals symbolize a group of substances that are not easily degraded; instead, they accumulate in different organisms and exhibit an acute or chronic toxicity. The limited empirical data on PBT chemicals, the high cost of testing together with the regulatory constraints and the international push for reduced animal testing motivate a greater reliance on predictive computational methods like quantitative structure-activity relationship (QSAR) models in PBT assessment...
April 2018: SAR and QSAR in Environmental Research
U Saqib, M S Baig
Toll/IL1 receptor (TIR) adaptor proteins continue to be an integral part of Toll-like receptors' (TLR) signalling involved in inflammation. Signalling is likely to be initiated by these TIR adaptors when they are recruited to a TIR-TIR interface formed by TLR dimerization. Among these, myeloid differentiation factor-88 (MyD88), MyD88 adapter-like protein (Mal), TIR domain-containing adaptor protein inducing interferon-β (TRIF) and TRIF-related adaptor molecule (TRAM) play pivotal roles at many steps in the signalling events leading to inflammation...
April 2018: SAR and QSAR in Environmental Research
S Chauhan, A Kumar
Hierarchical QSAR technology (HiT QSAR) was used for consensus QSAR modelling of 65 SIRT1 activators. Simplex representation of molecular structure (SiRMS) has been used for descriptor generation. The predictive QSAR models were developed using the partial least squares (PLS) method. The QSAR models were built up according to OECD principles. One hundred rounds of Y-scrambling were performed for each selected model to exclude chance correlations. A successful consensus model (r2 = 0.830, [Formula: see text] = 0...
April 2018: SAR and QSAR in Environmental Research
R Sheikhpour, M A Sarram, M Rezaeian, E Sheikhpour
The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors...
April 2018: SAR and QSAR in Environmental Research
S Bitam, M Hamadache, S Hanini
Numerous studies show that tacrine derivatives exhibit increased inhibitory activity against butyrylcholinesterase (BuChE) and acetylcholinesterase (AChE). However, the screening assays for currently available BuChE inhibitors are expensive, time consuming and dependent on the inhibitory compound. It is therefore desirable to develop alternative methods to facilitate the screening of these derivatives in the early phase of drug discovery. In order to develop robust predictive models, three regression methods were chosen in this study: multiple linear regression (MLR), support vector regression (SVR) and multilayer perceptron network (MLP)...
March 2018: SAR and QSAR in Environmental Research
G Cerruela García, N García-Pedrajas, I Luque Ruiz, M Á Gómez-Nieto
This paper proposes a method for molecular activity prediction in QSAR studies using ensembles of classifiers constructed by means of two supervised subspace projection methods, namely nonparametric discriminant analysis (NDA) and hybrid discriminant analysis (HDA). We studied the performance of the proposed ensembles compared to classical ensemble methods using four molecular datasets and eight different models for the representation of the molecular structure. Using several measures and statistical tests for classifier comparison, we observe that our proposal improves the classification results with respect to classical ensemble methods...
March 2018: SAR and QSAR in Environmental Research
B P Repsold, S F Malan, J Joubert, D W Oliver
Alzheimer's Disease (AD) is a neurodegenerative disease characterized by central nervous system insults with progressive cognitive (memory, attention) and non-cognitive (anxiety, depression) impairments. Pathophysiological events affect predominantly cholinergic neuronal loss and dysfunctions of the dopaminergic system. The aim of the current study was to design multi-targeted directed lead structures based on the coumarin scaffold with inhibitory properties at two key enzymes in disease relevant systems, i...
March 2018: SAR and QSAR in Environmental Research
C A Ganou, P Th Eleftheriou, P Theodosis-Nobelos, M Fesatidou, A A Geronikaki, T Lialiaris, E A Rekka
PTP1b is a protein tyrosine phosphatase involved in the inactivation of insulin receptor. Since inhibition of PTP1b may prolong the action of the receptor, PTP1b has become a drug target for the treatment of type II diabetes. In the present study, prediction of inhibition using docking analysis targeted specifically to the active or allosteric site was performed on 87 compounds structurally belonging to 10 different groups. Two groups, consisting of 15 thiomorpholine and 10 thiazolyl derivatives exhibiting the best prediction results, were selected for in vitro evaluation...
February 2018: SAR and QSAR in Environmental Research
S Nandi, S Ahmed, A K Saxena
The virulence of tuberculosis infections resistant to conventional combination drug regimens cries for the design of potent fluoroquinolone compounds to be used as second line antimycobacterial chemotherapeutics. One of the most effective in silico methods is combinatorial design and high throughput screening by a ligand-based pharmacophore prior to experiment. The combinatorial design of a series of 3850 fluoroquinolone and isothiazoloquinolone compounds was then screened virtually by applying a topological descriptor based quantitative structure activity relationship (QSAR) for predicting highly active congeneric quinolone leads against Mycobacterium fortuitum and Mycobacterium smegmatis...
February 2018: SAR and QSAR in Environmental Research
A D Şahin, M T Saçan
Toxic potencies of xenobiotics such as halogenated aromatic hydrocarbons inducing 2,3,7,8-tetrachlorodibenzo-p-dioxin/2,3,7,8-tetrachlorodibenzofuran (TCDD/TCDF)-like effects were investigated by quantitative structure-toxicity relationships (QSTR) using their aryl hydrocarbon receptor (AhR) binding affinity data. A descriptor pool was created using the SPARTAN 10, DRAGON 6.0 and ADMET 8.0 software packages, and the descriptors were selected using QSARINS (v.2.2.1) software. The QSTR models generated for AhR binding affinities of chemicals with TCDD/TCDF-like effects were internally and externally validated in line with the Organization of Economic Co-operation and Development (OECD) principles...
February 2018: SAR and QSAR in Environmental Research
O Kouatly, Ph Eleftheriou, A Petrou, D Hadjipavlou-Litina, A Geronikaki
Docking analysis was used to predict the effectiveness of adamantanyl insertion in improving cycloxygenase/lipoxygenase (COX/LOX) inhibitory action of previously tested 2-thiazolylimino-5-arylidene-4-thiazolidinones. The crystal structure data of human 5-LOX (3O8Y), ovine COX-1 (1EQH) and mouse COX-2 (3ln1) were used for docking analysis. All docking calculations were carried out using AutoDock 4.2 software. Following prediction results, 11 adamantanyl derivatives were synthesized and evaluated for biological action...
February 2018: SAR and QSAR in Environmental Research
J Devillers
Zika virus (ZIKV) is a mosquito-borne flavivirus for which there are no vaccines or specific therapeutics. To find drugs active on the virus is a complex, expensive and time-consuming process. The prospect of drug repurposing, which consists of finding new indications for existing drugs, is an interesting alternative to expedite drug development for specific diseases. In theory, drug repurposing is also able to respond much more rapidly to a crisis than a classical drug discovery process. Consequently, the methodology is attractive for vector-borne diseases that can emerge or re-emerge worldwide with the risk to become pandemic quickly...
February 2018: SAR and QSAR in Environmental Research
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