The searching for agents for Alzheimer’s disease treatment via the system of self-consistent models

Toropov, Andrey A.; Toropova, Alla P.; Achary, P. Ganga Raju; Rašková, Mária; Raška, Ivan

doi:10.1080/15376516.2022.2053918

Cited by 14 publications

(6 citation statements)

References 42 publications

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“…Apparently, this is the effect of exposure to the vector of the ideality of correlation. Analogical pairs of correlations were observed in computer experiments described in the literature [20,21]. Figure 2 indicates that latent correlations on active and passive training sets are statistically more significant than total correlations on these sets.…”

Section: Third Schemesupporting

confidence: 67%

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QSPR and Nano-QSPR: Which One Is Common? The Case of Fullerenes Solubility

Toropova,

Toropov,

Fjodorova

2023

Inorganics

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Background: The system of self-consistent models is an attempt to develop a tool to assess the predictive potential of various approaches by considering a group of random distributions of available data into training and validation sets. Considering many different splits is more informative than considering a single model. Methods: Models studied here build up for solubility of fullerenes C60 and C70 in different organic solvents using so-called quasi-SMILES, which contain traditional simplified molecular input-line entry systems (SMILES) incorporated with codes that reflect the presence of C60 and C70. In addition, the fragments of local symmetry (FLS) in quasi-SMILES are applied to improve the solubility’s predictive potential (expressed via mole fraction at 298’K) models. Results: Several versions of the Monte Carlo procedure are studied. The use of the fragments of local symmetry along with a special vector of the ideality of correlation improves the predictive potential of the models. The average value of the determination coefficient on the validation sets is equal to 0.9255 ± 0.0163. Conclusions: The comparison of different manners of the Monte Carlo optimization of the correlation weights has shown that the best predictive potential was observed for models where both fragments of local symmetry and the vector of the ideality of correlation were applied.

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Section: Third Schemesupporting

confidence: 67%

“…Can the OECD principles be improved? Latent attempts to do this can be seen in many studies [14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

QSPR and Nano-QSPR: Which One Is Common? The Case of Fullerenes Solubility

Toropova,

Toropov,

Fjodorova

2023

Inorganics

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“…The literature reports also proved that generating the target function with the inclusion of IIC and CII simultaneously can be more efficient than using IIC or CII alone. 61 Finally, models improved with TF 3 outweighed all other models statistically, thus rendering them a significantly trustworthy source of possible future prediction.…”

Section: Resultsmentioning

confidence: 99%

Prediction of second-order rate constants of the sulfate radical anion with aromatic contaminants using the Monte Carlo technique

Lotfi,

Ahmadi,

Azimi

et al. 2023

New J. Chem.

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“…In view of what has been said, the system of self-consistent models looks very attractive from the point of view of justifying the use of an appropriate approach to constructing the models. A test of this scheme for the case of ordinary regression models showed the convenience of using the approach for linear regression models [ 14 , 25 , 26 , 27 , 28 , 29 ]. Since the system of self-consistent models implies the consideration of groups of models with the allocation of average values of statistical parameters, this approach provides more objective information about the statistical significance of the approach used.…”

Section: Discussionmentioning

confidence: 99%

The System of Self-Consistent Models: QSAR Analysis of Drug-Induced Liver Toxicity

Toropova

Toropov

Roncaglioni

et al. 2023

Toxics

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Removing a drug-like substance that can cause drug-induced liver injury from the drug discovery process is a significant task for medicinal chemistry. In silico models can facilitate this process. Semi-correlation is an approach to building in silico models representing the prediction in the active (1)—inactive (0) format. The so-called system of self-consistent models has been suggested as an approach for two tasks: (i) building up a model and (ii) estimating its predictive potential. However, this approach has been tested so far for regression models. Here, the approach is applied to building up and estimating a categorical hepatotoxicity model using the CORAL software. This new process yields good results: sensitivity = 0.77, specificity = 0.75, accuracy = 0.76, and Matthew correlation coefficient = 0.51 (all compounds) and sensitivity = 0.83, specificity = 0.81, accuracy = 0.83 and Matthew correlation coefficient = 0.63 (validation set).

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The searching for agents for Alzheimer’s disease treatment via the system of self-consistent models

Cited by 14 publications

References 42 publications

QSPR and Nano-QSPR: Which One Is Common? The Case of Fullerenes Solubility

QSPR and Nano-QSPR: Which One Is Common? The Case of Fullerenes Solubility

Prediction of second-order rate constants of the sulfate radical anion with aromatic contaminants using the Monte Carlo technique

The System of Self-Consistent Models: QSAR Analysis of Drug-Induced Liver Toxicity

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