QSPR analysis of some agonists and antagonists of α-adrenergic receptors

Kawczak, Piotr; Bober, Leszek; Bączek, Tomasz

doi:10.1007/s00044-014-1130-x

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…On the other hand, the significance of the parameters available from quantum-chemical calculations in relation to a structure-biological activity for different groups of compounds was as well already confirmed in the previous series of publications (Belka et al 2012(Belka et al , 2013Bober et al 2012a, b;Stasiak et al 2013;Kawczak et al 2014Kawczak et al , 2015Kawczak et al , 2018aKawczak et al , b, c, 2019Ciura et al 2017). In view of the above, it was decided to check how the physicochemical descriptors obtained as a result of quantum-chemical methods are influencing the classification of sulfonamides, while all the performed calculations were possible on standard-class principal components.…”

Section: Introductionsupporting

confidence: 59%

The comparison of semiempirical and ab initio molecular modeling methods in activity and property evaluation of selected antimicrobial sulfonamides

2019

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A group of sulfonamides exhibiting antimicrobial activity was analyzed with the application of quantitative structureactivity/property relationships method. The purpose of this study was to show the common and differentiating characteristics of the analyzed chemical structures alike physicochemically as well as pharmacologically based on the quantum-chemical calculations both in vacuo and in the aquatic environment together with their microbiological activity and chromatographic retention data. The semiempirical and ab initio level of in silico molecular modeling was performed for calculations of statistically significant molecular descriptors to compare obtained results. The relationship between the structure and biological activity and physicochemical parameters data was able to class and describe analyzed molecules and the applied chemometric approaches (principal component analysis, factor analysis, and multiple regression analysis) revealed the influential features of the tested structures responsible for the antimicrobial activity.

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Section: Introductionsupporting

confidence: 59%

The comparison of semiempirical and ab initio molecular modeling methods in activity and property evaluation of selected antimicrobial sulfonamides

2019

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“…For the property prediction task, we report the prediction accuracy for novel candidates as the mean absolute error ( MAE ) between the true and predicted values. We chose to predict the isotropic polarizability as it is been shown to be a key property in determining molecular and materials functionality , and is commonly used as a target in other studies. Converged loss curves for each model type as a function of this metric can be found in Figure S5.…”

Section: Methodsmentioning

confidence: 99%

Efficient 3D Molecular Design with an E(3) Invariant Transformer VAE

Dollar,

Joshi,

Pfaendtner

et al. 2023

J. Phys. Chem. A

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This work introduces a three-dimensional (3D) invariant graph-to-string transformer variational autoencoders (VAE) (Vagrant) for generating molecules with accurate density functional theory (DFT)-level properties. Vagrant learns to model the joint probability distribution of a 3D molecular structure and its properties by encoding molecular structures into a 3D-aware latent space. Directed navigation through this latent space implicitly optimizes the 3D structure of a molecule, and the latent embedding can be used to condition a generative transformer to predict the candidate structure as a one-dimensional (1D) sequence. Additionally, we introduce two novel sampling methods that exploit the latent characteristics of a VAE to improve performance. We show that our method outperforms comparable 3D autoregressive and diffusion methods for predicting quantum chemical property values of novel molecules in terms of both sample quality and computational efficiency.

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Activity Evaluation and Selection of Some Classes of Antibiotics with the use of Semi-Empirical Quantum Mechanics and Quantitative Structure- Activity Relationships Approach

Kawczak

Bober

Bączek

2019

CCHTS

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Background: A set of β-lactam antibiotics, aminoglycoside antibiotics, and tetracycline antibiotics were proposed and analyzed with the use of Quantitative Structure-Activity Relationships (QSAR) method. Objective: The characterization of selected antimicrobial compounds in terms of both physicochemical and pharmacological on the basis of calculations of quantum mechanics and possessed biological activity data. Methods: During the study, Multiple Linear Regression (MLR) supported with Factor Analysis (FA) and Principal Component Analysis (PCA) was made, as the types of proposed chemometric approach; the semi-empirical level of in silico molecular modeling was used for calculations and comparison of molecular descriptors both in a vacuum and in the aquatic environment. Results: The relationships between structure and microbiological activity enabled the characterization and description of the analyzed molecules using statistically significant descriptors belonging in most cases to different structural, geometric and electronic elements defining at the same time the properties of the studied three different classes of examined antibiotics. Conclusion: The chemometric methods used revealed the influence of some of the elements of structures examined molecules belonging to main antibiotics classes and responsible for the antimicrobial activity.

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QSPR analysis of some agonists and antagonists of α-adrenergic receptors

Cited by 4 publications

References 17 publications

The comparison of semiempirical and ab initio molecular modeling methods in activity and property evaluation of selected antimicrobial sulfonamides

The comparison of semiempirical and ab initio molecular modeling methods in activity and property evaluation of selected antimicrobial sulfonamides

Efficient 3D Molecular Design with an E(3) Invariant Transformer VAE

Activity Evaluation and Selection of Some Classes of Antibiotics with the use of Semi-Empirical Quantum Mechanics and Quantitative Structure- Activity Relationships Approach

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