QSAR modeling of bis-quinolinium and bis-isoquinolinium compounds as acetylcholine esterase inhibitors based on the Monte Carlo method—the implication for Myasthenia gravis treatment

Sokolović, Dušan; Aleksić, Dragana; Milenković, Vesko; Karaleić, Sladjan; Mitić, Dragana; Kocić, Jadranka; Mekić, Branimir; Veselinović, Jovana B.; Veselinović, Aleksandar M.

doi:10.1007/s00044-016-1720-x

Cited by 8 publications

(3 citation statements)

References 32 publications

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“…One 3D QSAR model developed by PLS for the same dataset has been described by Yu et al [19]. The values for statistical features used to examine the model were n(training) = 35, n(test) = 08, non cross validated R 2 = 0.984, Q 2 cross validated = 0.599 and r 2 ext = 0.728, and r 2 m (overall) = 0.821.…”

Section: Resultsmentioning

confidence: 99%

“…The results are easy to interpret and can be applied in designing of new compounds [5][6][7]. Earlier, CORAL has been used for QSAR studies of various types of compounds like SIRT1 modulators [8,9], anti-neuraminidase agents [10], anticonvulsant agents [11], antimalarial agents [12], NNRTI inhibitors [13], antibacterial agents [14], anticancer agents [15], aromatase inhibitors [16], antihuman serine proteinases [17], acetylcholinesterase inhibitors [18,19], peptidase-4 inhibitors [20], glycogen synthase kinase-3β inhibitors [21], and lipase inhibitors [22] etc.…”

Section: Introductionmentioning

confidence: 99%

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Monte Carlo Method Based QSAR Studies of Mer Kinase Inhibitors in Compliance with OECD Principles

Kumar

2017

Drug Res (Stuttg)

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Monte Carlo method based QSAR studies for inhibitors of Mer kinase, a potential novel target for cancer treatment, has been carried out using balance of correlation technique. The data was divided into three random and dissimilar splits and hybrid optimal descriptors derived from SMILES and hydrogen filled graphs based notations were used for construction of QSAR models. The generated models have good fitting ability, robustness, generalizability and internal predictive ability. The external predictive ability has been tested using multiple criteria and described models exhibited good performance in all of these tests. The values of R, Q, R, Q, R and ∆R for the best model are 0.9502, 0.9388, 0.9469, 0.9083, 0.7534 and 0.0894 respectively. Also, the structural characteristics responsible for enhancement and reduction of activity have been extracted. Further, the agreement with the OECD rules for QSAR model has been discussed.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Monte Carlo Method Based QSAR Studies of Mer Kinase Inhibitors in Compliance with OECD Principles

Kumar

2017

Drug Res (Stuttg)

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“…The parameters & d for compounds used in the QSAR study can be determined by below mentioned equations. Here n is the total number of compounds involved in it [37].…”

Section: Domain Of Applicabilitymentioning

confidence: 99%

Use of Graph Based Descriptors for Determination of Structural Features Causing Modulation of Fructose-1,6-Bisphosphatase

et al. 2020

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Fructose-1,6-bisphosphatase performs a significant function in regulating the blood glucose level in type 2 diabetes by controlling the process gluconeogenesis. In this research work optimal descriptor (graph) based quantitative structural activity relationship studies of a set of 203 fructose-1,6-bisphosphatase has been performed with the help of Monte Carlo optimization. Distribution of compounds into different sets such as training set, invisible training set, calibration set and validation sets resulted in formation of splits. Statistical parameters obtained from quantitative structural activity relationship modeling were good for various designed splits. The statistical parameters such as R2 and Q2 for calibration and validation sets of best split developed were found to be 0.8338, 0.7908 & 0.7920 and 0.7036 respectively. Based on the results obtained for correlation weights, different structural attributes were described as promoters and demoters of the endpoint. Further these structural attributes were used in designing of new fructose-1,6-bisphosphatase inhibitors and molecular docking study was accomplished for the determination of interactions of designed molecules with the enzyme.

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Prediction of Biochemical Endpoints by the CORAL Software: Prejudices, Paradoxes, and Results

Toropov

Toropova

Roncaglioni

et al. 2018

Methods in Molecular Biology

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QSAR modeling of bis-quinolinium and bis-isoquinolinium compounds as acetylcholine esterase inhibitors based on the Monte Carlo method—the implication for Myasthenia gravis treatment

Cited by 8 publications

References 32 publications

Monte Carlo Method Based QSAR Studies of Mer Kinase Inhibitors in Compliance with OECD Principles

Monte Carlo Method Based QSAR Studies of Mer Kinase Inhibitors in Compliance with OECD Principles

Use of Graph Based Descriptors for Determination of Structural Features Causing Modulation of Fructose-1,6-Bisphosphatase

Prediction of Biochemical Endpoints by the CORAL Software: Prejudices, Paradoxes, and Results

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