The nature of the interaction of dimethylselenide with IIIA group element compounds

The first systematic theoretical study of the nature of intermolecular bonding of dimethylselenide as donor and IIIA group element halides as acceptors was made with the help of the approach of Quantum Theory of Atoms in Molecules. Density Functional Theory with "old" Sapporo triple-ζ basis sets was used to calculate geometry, thermodynamics, and wave function of Me 2Se···AX3 complexes. The analysis of the electron density distribution and the Laplacian of the electron density allowed us to reveal and explain the tendencies in the influence of the central atom (A = B, Al, Ga, In) and halogen (X = F, Cl, Br, I) on the nature of Se···A bonding. Significant changes in properties of the selenium lone pair upon complexation were described by means of the analysis of the Laplacian of the charge density. Charge transfer characteristics and the contributions to it from electron localization and delocalization were analyzed in terms of localization and delocalization indexes. Common features of the complexation and differences in the nature of bonding were revealed. Performed analysis evidenced that gallium and indium halide complexes can be attributed to charge transfer-driven complexes; aluminum halides complexes seem to be mainly of an electrostatic nature. The nature of bonding in different boron halides essentially varies; these complexes are stabilized mainly by covalent Se···B interaction. In all the complexes under study covalence of the Se···A interaction is rather high. © 2013 American Chemical Society

Dimethyl selenide complexes with compounds of Group IIIA elements: Electron density redistribution and interaction energy partitioning

Molecular structures of dimethyl selenide complexes with AX3 (A = B, Al, Ga, In; X = H, Me) compounds of Group IIIA elements were calculated by the PBE1PBE/SapporoTZ method. A complex approach to study the nature of interactions is proposed, which involves analysis of electron localization/delocalization characteristics and their influence on charge transfer and energy effects of complexation. It is shown that electron sharing is more important for stabiliza tion of the complexes under study than electrostatic interaction between their fragments. It is demonstrated that analysis of local (topological) characteristics of the electron density distribu tion is insufficient to discover similarity/dissimilarity in the nature of some complexes. The energies of interaction in the complexes under study are mainly composed of the contributions of Se atom as active center of the donor molecule and the entire acceptor molecule. Energy characteristics of local interaction between Se atom and Group IIIA element atom are not representative. © 2014 Springer Science+Business Media, Inc

Quantum-chemical investigation of structure and reactivity of pyrazol-5-ones and their thio- and seleno-analogs: X. Solvent effect on the chemical shifts of nuclei in the molecules of 3-methylpyrazol-5-ones and 1-phenyl-3-methylchalcogenepyrazol-5-ones and characteristics of tautomeric equilibrium in these compounds

By quantum-chemical DFT/GIAO method chemical shifts of all nuclei in the NMR spectra of 3-methylpyrazol-5-one and 1-phenyl-3-methylchalcogenopyrazol-5- ones in chloroform and dimethyl sulfoxide were calculated and analyzed using various solvation models. Low sensitivity to solvent of the chemical shfts of 13C and 1H nuclei (except for "acidic" protons) calculated in the framework of various continuum models is revealed. Discrete and discrete-continuum models reflect well deshielding of the active centers of H-complexation and chemical shifts of "acidic" protons of the studied pyrazolones in solutions. Optimization of geometry of pyrazolones in solutions only slightly improves the agreement between the theoretically calculated and the experimental values. Shielding of nitrogen, oxygen, sulfur, and selenium atoms is more sensitive to the nature of solvent and to the nature of tautomeric forms. The methods of NMR spectroscopy allow to identify reliably the dominating tautomeric form but they are insufficient for the quantitative characterization of tautomeric equilibria. © 2009 Pleiades Publishing, Ltd

Estimation of the size of drug-like chemical space based on GDB-17 data

The goal of this paper is to estimate the number of realistic drug-like molecules which could ever be synthesized. Unlike previous studies based on exhaustive enumeration of molecular graphs or on combinatorial enumeration preselected fragments, we used results of constrained graphs enumeration by Reymond to establish a correlation between the number of generated structures (M) and the number of heavy atoms (N): logM = 0.584 × N × logN + 0.356. The number of atoms limiting drug-like chemical space of molecules which follow Lipinsky's rules (N = 36) has been obtained from the analysis of the PubChem database. This results in M ≈ 1033 which is in between the numbers estimated by Ertl (1023) and by Bohacek (1060). © 2013 Springer Science+Business Media Dordrecht

MOLECULE REPRESENTATION AND DATABASING OF MOLECULES AND REACTIONS

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Generative Topographic Mapping Approach to Modeling and Chemical Space Visualization of Human Intestinal Transporters

© 2016, Springer Science+Business Media New York.The generative topographic mapping (GTM) approach has been used both to build predictive models linking chemical structure of molecules and their ability to bind some membrane transport proteins (transporters) and to visualize a chemical space of transporters’ binders on two-dimensional maps. For this purpose, experimental data on 2958 molecules active against up to 11 transporters have been used. It has been shown that GTM-based classification (active/inactive) models display reasonable predictive performance, comparable with that of such popular machine-learning methods as Random Forest, SVM, or k-NN. Moreover, GTM offers its own models applicability domain definition which may significantly improve the models performance. GTM maps themselves represent an interesting tool of the chemical space analysis of the transporters’ ligands. Thus, with the help of class landscapes, they identify distinct zones populated by active or inactive molecules with respect to a given transporter. As demonstrated in this paper, the superposition of class landscapes describing different activities delineates the areas mostly populated by the compounds of desired pharmacological profile

Ligand-based pharmacophore modeling using novel 3D pharmacophore signatures

© 2018 by the authors. Pharmacophore modeling is a widely used strategy for finding new hit molecules. Since not all protein targets have available 3D structures, ligand-based approaches are still useful. Currently, there are just a few free ligand-based pharmacophore modeling tools, and these have a lot of restrictions, e.g., using a template molecule for alignment. We developed a new approach to 3D pharmacophore representation and matching which does not require pharmacophore alignment. This representation can be used to quickly find identical pharmacophores in a given set. Based on this representation, a 3D pharmacophore ligand-based modeling approach to search for pharmacophores which preferably match active compounds and do not match inactive ones was developed. The approach searches for 3D pharmacophore models starting from 2D structures of available active and inactive compounds. The implemented approach was successfully applied for several retrospective studies. The results were compared to a 2D similarity search, demonstrating some of the advantages of the developed 3D pharmacophore models. Also, the generated 3D pharmacophore models were able to match the 3D poses of known ligands from their protein-ligand complexes, confirming the validity of the models. The developed approach is available as an open-source software tool: http://www.qsar4u.com/pages/pmapper.php and https://github.com/meddwl/psearch

Artificial intelligence in synthetic chemistry: Achievements and prospects

The review is devoted to the achievements in analysis of information on chemical reactions using machine learning methods. Four large areas that actively use these methods are outlined: computer-assisted planning of synthesis, analysis and visualization of chemical reaction data, prediction of the quantitative characteristics of reactions and computer-aided design of catalysts

PREDICTION OF METABOLIC TRANSFORMATIONS OF ORGANIC COMPOUNDS BY CYP1A2 ISOENZYME USING СONDENSED GRAPH OF REACTIONS

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"Additive" cooperativity of hydrogen bonds in complexes of catechol with proton acceptors in the gas phase: FTIR spectroscopy and quantum chemical calculations

Experimental study of hydrogen bond cooperativity in hetero-complexes in the gas phase was carried out by IR-spectroscopy method. Stretching vibration frequencies of OH groups in phenol and catechol molecules as well as of their complexes with nitriles and ethers were determined in the gas phase using a specially designed cell. OH groups experimental frequency shifts in the complexes of catechol induced by the formation of intermolecular hydrogen bonds are significantly higher than in the complexes of phenol due to the hydrogen bond cooperativity. It was shown that the cooperativity factors of hydrogen bonds in the complexes of catechol with nitriles and ethers in the gas phase are approximately the same. Quantum chemical calculations of the studied systems have been performed using density functional theory (DFT) methods. It was shown, that theoretically obtained cooperativity factors of hydrogen bonds in the complexes of catechol with proton acceptors are in good agreement with experimental values. Cooperative effects lead to a strengthening of intermolecular hydrogen bonds in the complexes of catechol on about 30%, despite the significant difference in the proton acceptor ability of the bases. The analysis within quantum theory of atoms in molecules was carried out for the explanation of this fact. © 2012 Elsevier B.V. All rights reserved