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

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

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.

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

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.

Evaluation of Chemotherapeutic Activity of the Selected Bases' Analogues of Nucleic Acids Supported by ab initio Various Quantum Chemical Calculations

BACKGROUND

Pharmacological and physicochemical classification of bases' selected analogues of nucleic acids is proposed in the study.

OBJECTIVE

Structural parameters received by the PCM (Polarizable Continuum Model) with several types of calculation methods for the structures in vacuo and in the aquatic environment together with the huge set of extra molecular descriptors obtained by the professional software and literature values of biological activity were used to search the relationships.

METHODS

Principal Component Analysis (PCA) together with Factor Analysis (FA) and Multiple Linear Regressions (MLR) as the types of the chemometric approach based on semi-empirical ab initio molecular modeling studies were performed.

RESULTS

The equations with statistically significant descriptors were proposed to demonstrate both the common and differentiating characteristics of the bases' analogues of nucleic acids based on the quantum chemical calculations and biological activity data.

CONCLUSION

The obtained QSAR models can be used for predicting and explaining the activity of studied molecules.