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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...
March 7, 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])...
March 1, 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...
February 15, 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...
February 1, 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...
January 26, 2018: SAR and QSAR in Environmental Research
S Gupta, S Mallick
In this study, a support vector machine (SVM) based multi-species QSAR (quantitative structure-activity relationship) model was developed for predicting the water-plant cuticular polymer matrix membrane (MX) partition coefficient, KMXw of diverse chemicals using two simple molecular descriptors derived from the chemical structures and following the OECD guidelines. Accordingly, the Lycopersicon esculentum Mill. data were used to construct the QSAR model that was externally validated using three other plant species data...
January 18, 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...
January 8, 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...
January 4, 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...
January 4, 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
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
R K Goel, D Y Gawande, A A Lagunin, V V Poroikov
Traditional knowledge guides the use of plants for restricted therapeutic indications, but their pharmacological actions may be found beyond their ethnic therapeutic indications employing emerging computational tools. In this context, the present study was envisaged to explore the novel pharmacological effect of Achyranthes aspera (A. aspera) using PASS and PharmaExpert software tools. Based on the predicted mechanisms of the antidepressant effect for all analysed phytoconstituents of A. aspera, one may suggest its significant antidepressant action...
December 19, 2017: SAR and QSAR in Environmental Research
D A Shulga, O I Titov, S A Pisarev, V A Palyulin
Nowadays, as computing has become much more available, a fresh momentum has been observed in the field of re-visioning and re-parameterizing the usual tools, as well as estimating for the incorporation of new qualitative capabilities, aimed at making more accurate and reliable predictions in drug discovery processes. Inspired by the success of modelling the electrostatic part of the halogen bonding (XB) by means of the distributed multipole expansion, a study is presented which attempts to extend this approach to a tougher case of σ-hole interaction: sulphur-based chalcogen bonding...
December 19, 2017: SAR and QSAR in Environmental Research
T Jha, N Adhikari, A Saha, S A Amin
Matrix metalloproteinase-2 (MMP-2) is a potential target in anticancer drug discovery due to its association with angiogenesis, metastasis and tumour progression. In this study, 67 glutamic acid derivatives, synthesized and evaluated as MMP-2 inhibitors, were taken into account for multi-QSAR modelling study (regression-based 2D-QSAR, classification-based LDA-QSAR, Bayesian classification QSAR, HQSAR, 3D-QSAR CoMFA and CoMSIA as well as Open3DQSAR). All these QSAR studies were statistically validated individually...
December 19, 2017: SAR and QSAR in Environmental Research
P Kumar, R Kaalia, A Srinivasan, I Ghosh
Health care systems have benefitted from rational drug discovery processes like vHTS, virtual high throughput screening pharmacophores and quantitative structure-activity relationships, and many challenges have been explored using such techniques: decisions on specificity and selectivity are made after screening millions of molecules for multiple targets. Recent challenges in drug research emphasize the design of drugs that bind with more than one target of interest (multi-target) and do not bind with undesirable targets...
December 15, 2017: SAR and QSAR in Environmental Research
B Sepehri, R Ghavami
Ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches were used to identify new inhibitors for ATAD2 bromodomain. The LBVS approach was used to search 23,129,083 clean compounds to identify compounds similar to an active compound with reported pIC50 equal to 7.2. Based on LBVS results, 19 compounds were selected. To perform SBVS, by applying nine filters on 23,129,083 clean compounds, 1,057,060 compounds were selected. After performing SBVS on these selected compounds with idock software, 16 compounds with the lowest binding energies were selected...
December 2017: SAR and QSAR in Environmental Research
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