scholarly journals Global chemical reactivity parameters for several chiral beta-blockers from Density Functional Theory Viewpoint

2016 ◽  
Vol 89 (4) ◽  
pp. 513-518 ◽  
Author(s):  
Mona Maria Talmaciu ◽  
Ede Bodoki ◽  
Radu Oprean
Keyword(s):  
Quantum Chemical ◽  
Density Functional ◽  
Chemical Potential ◽  
Chemical Reactivity ◽  
Beta Blockers ◽  
Chemical Hardness ◽  
Quantum Chemical Descriptors ◽  
Chemical Structures ◽  
Coronary Syndrome ◽  
Chemical Descriptors

Background and aim.  Beta-adrenergic antagonists have been established as first line treatment in the medical management of hypertension, acute coronary syndrome and other cardiovascular diseases, as well as for the prevention of initial episodes of gastrointestinal bleeding in patients with cirrhosis and esophageal varices, glaucoma, and have recently become the main form of treatment of infantile hemangiomas.The aim of the present study is to calculate for 14 beta-blockers several quantum chemical descriptors in order to interpret various molecular properties such as electronic structure, conformation, reactivity, in the interest of determining how such descriptors could have an impact on our understanding of the experimental observations and describing various aspects of chemical binding of beta-blockers in terms of these descriptors.Methods. The 2D chemical structures of the beta-blockers (14 molecules with one stereogenic center) were cleaned in 3D, their geometry was preoptimized using the software MOPAC2012, by PM6 method, and then further refined using standard settings in MOE; HOMO and LUMO descriptors were calculated using semi-empirical molecular orbital methods AM1, MNDO and PM3, for the lowest energy conformers and the quantum chemical descriptors (HLG, electronegativity, chemical potential, hardness and softness, electrophilicity) were then calculated.Results. According to HOMO-LUMO gap and the chemical hardness the most stable compounds are alprenolol, bisoprolol and esmolol. The softness values calculated for the study molecules revolve around 0.100. Propranolol, sotalol and timolol have among the highest electrophilicity index of the studied beta-blocker molecules. Results obtained from calculations showed that acebutolol, atenolol, timolol and sotalol have the highest values for the electronegativity index. Conclusions. The future aim is to determine whether it is possible to find a valid correlation between these descriptors and the physicochemical behavior of the molecules from this class. The HLG could be correlated to the experimentally recorded electrochemical properties of the molecules. HOMO could be correlated to the observed oxidation potential, since the required voltage is related to the energy of the HOMO, because only the electron from this orbital is involved in the oxidation process.

Spectroscopic and Quantum Chemical Investigations of Hypothetical m-Diacetylaminoazopyrimidine and Its Photovoltaic Properties

2021 ◽  
Vol 14 (2) ◽  
pp. 139-154
Keyword(s):  
Excited State ◽  
Quantum Chemical ◽  
Density Functional ◽  
Chemical Potential ◽  
Energy Gap ◽  
Dye Sensitized Solar Cells ◽  
Chemical Hardness ◽  
Quantum Chemical Descriptors ◽  
Photovoltaic Properties ◽  
Chemical Descriptors

Abstract: Here, an attempt is made to theoretically study and predict the electronic and spectroscopic (UV-Vis and IR) and structural properties, quantum chemical descriptors and subsequent application of diacetylaminoazopyrimidine in dye-sensitized solar cells (DSSCs). Ground- and excited-state time-dependent density functional theory (TD-DFT) calculations were carried out using material studio and ORCA software, respectively. The computed ground-state energy gap, chemical hardness, chemical softness, chemical potential, electronegativity and electrophilicity index are: 3.60 eV, 1.80 eV, 0.56 eV, 4.49 eV, -4.49 eV and 5.68, respectively. Conversely, the DFT-predicted excited-state quantum chemical descriptors are: 1.67 eV, 0.83 eV, 1.20 eV, 4.71 eV and -4.71 eV, corresponding to the energy gap, chemical hardness, chemical softness, chemical potential and electronegativity, respectively. Furthermore, vibrational frequency calculations confirm the presence of some key functional groups (N=N, C=O, C-H) present in the dye molecules. The computed optoelectronic parameters, such as light-harvesting efficiency, electron injection and open-circuit voltage are 0.06 eV, -8.59 eV and -5.75 eV, respectively. Overall, the dye possesses a relatively good current conversion efficiency as compared to other dyes studied in the literature; hence, it could be used as a novel material for photovoltaic technological applications. Keywords: Diacetylaminoazopyrimidine, DFT, Excited state, Spectroscopy, DSSCs.

scholarly journals A Comparative Study of Two Quantum Chemical Descriptors in Predicting Toxicity of Aliphatic Compounds towards Tetrahymena pyriformis

2010 ◽  
Vol 2010 ◽  
pp. 1-17 ◽  
Author(s):  
Altaf Hussain Pandith ◽  
S. Giri ◽  
P. K. Chattaraj
Keyword(s):  
Quantum Chemical ◽  
Chemical Potential ◽  
Chemical Reactivity ◽  
Molecular Descriptor ◽  
Tetrahymena Pyriformis ◽  
Quantitative Structure Activity Relationship ◽  
Quantum Chemical Descriptors ◽  
Data Set ◽  
Aliphatic Compounds ◽  
Chemical Descriptors

Quantum chemical parameters such as LUMO energy, HOMO energy, ionization energy (I), electron affinity (A), chemical potential (μ), hardness (η) electronegativity (χ), philicity (ωα), and electrophilicity (ω) of a series of aliphatic compounds are calculated at the B3LYP/6-31G(d) level of theory. Quantitative structure-activity relationship (QSAR) models are developed for predicting the toxicity (pIGC50) of 13 classes of aliphatic compounds, including 171 electron acceptors and 81 electron donors, towards Tetrahymena pyriformis. The multiple linear regression modeling of toxicity of these compounds is performed by using the molecular descriptor log P (1-octanol/water partition coefficient) in conjunction with two other quantum chemical descriptors, electrophilicity (ω) and energy of the lowest unoccupied molecular orbital (ELUMO). A comparison is made towards the toxicity predicting the ability of electrophilicity (ω) versus ELUMO as a global chemical reactivity descriptor in addition to log P. The former works marginally better in most cases. There is a slight improvement in the quality of regression by changing the unit of IGC50 from mg/L to molarity and by removing the racemates and the diastereoisomers from the data set.

scholarly journals Estimation of n-octanol/water partition coefficients of polycyclic aromatic hydrocarbons by quantum chemical descriptors

2008 ◽  
Vol 6 (2) ◽  
pp. 310-318 ◽  
Author(s):  
Gui-Ning Lu ◽  
Xue-Qin Tao ◽  
Zhi Dang ◽  
Xiao-Yun Yi ◽  
Chen Yang
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Quantum Chemical ◽  
Partition Coefficients ◽  
Density Functional ◽  
Optimal Model ◽  
Quantum Chemical Descriptors ◽  
Polycyclic Aromatic ◽  
Pls Analysis ◽  
Chemical Descriptors

AbstractQuantitative structure-property relationship (QSPR) modeling is a powerful approach for predicting environmental behavior of organic pollutants with their structure descriptors. This study reports an optimal QSPR model for estimating logarithmic n-octanol/water partition coefficients (log K OW) of polycyclic aromatic hydrocarbons (PAHs). Quantum chemical descriptors computed with density functional theory at B3LYP/6-31G(d) level and partial least squares (PLS) analysis with optimizing procedure were used for generating QSPR models for log K OW of PAHs. The squared correlation coefficient (R 2) of the optimal model was 0.990, and the results of crossvalidation test (Q 2cum=0.976) showed this optimal model had high fitting precision and good predictability. The log K OW values predicted by the optimal model are very close to those observed. The PLS analysis indicated that PAHs with larger electronic spatial extent and lower total energy values tend to be more hydrophobic and lipophilic.

scholarly journals Kernel Methods for Predicting Yields of Chemical Reactions

2021 ◽  
Author(s):  
Alexe Haywood ◽  
Joseph Redshaw ◽  
Magnus Hanson-Heine ◽  
Adam Taylor ◽  
Alex Brown ◽  
...  
Keyword(s):  
Quantum Chemical ◽  
Density Functional ◽  
Aryl Halide ◽  
Reaction Yield ◽  
Support Vector ◽  
Quantum Chemical Descriptors ◽  
Functional Theory ◽  
Molecular Fingerprints ◽  
Chemical Descriptors ◽  
Synthetic Assessment

The use of machine learning methods for the prediction of reaction yield is an emerging area. We demonstrate the applicability of support vector regression (SVR) for predicting reaction yields, using combinatorial data. Molecular descriptors used in regression tasks related to chemical reac?tivity have often been based on time-consuming, computationally demanding quantum chemical calculations, usually density functional theory. Structure-based descriptors (molecular fingerprints and molecular graphs) are quicker and easier to calculate, and are applicable to any molecule. In this study, SVR models built on structure-based descriptors were compared to models built on quantum chemical descriptors. The models were evaluated along the dimension of each reaction component in a set of Buchwald-Hartwig amination reactions. The structure-based SVR models out-performed the quantum chemical SVR models, along the dimension of each reaction compo?nent. The applicability of the models was assessed with respect to similarity to training. Prospec?tive predictions of unseen Buchwald-Hartwig reactions are presented for synthetic assessment, to validate the generalisability of the models, with particular interest along the aryl halide dimension.

scholarly journals The Internal Relation between Quantum Chemical Descriptors and Empirical Constants of Polychlorinated Compounds

Molecules ◽  
2018 ◽  
Vol 23 (11) ◽  
pp. 2935 ◽  
Author(s):  
Jiangchi Fei ◽  
Qiming Mao ◽  
Lu Peng ◽  
Tiantian Ye ◽  
Yuan Yang ◽  
...  
Keyword(s):  
Quantum Chemical ◽  
Chemical Reactivity ◽  
Chemical Properties ◽  
Quantum Chemical Descriptors ◽  
Polychlorinated Naphthalenes ◽  
Empirical Constant ◽  
Intrinsic Correlation ◽  
Chemical Descriptors ◽  
The Relationship ◽  
Empirical Constants

Quantum chemical descriptors and empirical parameters are two different types of chemical parameters that play the fundamental roles in chemical reactivity and model development. However, previous studies have lacked detail regarding the relationship between quantum chemical descriptors and empirical constants. We selected polychlorinated biphenyls (PCBs) as an object to investigate the intrinsic correlation between 16 quantum chemical descriptors and Hammett constants. The results exhibited extremely high linearity for ∑ σ o ,   m ,   p + with Qxx/yy/zz, α and EHOMO based on the meta-position grouping. Polychlorinated dibenzodioxins (PCDDs) and polychlorinated naphthalenes (PCNs) congeners, as two independent compounds, validated the reliability of the relationship. The meta-substituent grouping method between ∑ σ o ,   m ,   p + and α was successfully used to predict the rate constant (k) for •OH oxidation of PCBs, as well as the octanol/water partition coefficient (logKOW) and aqueous solubility (−logSW) of PCDDs, and exhibited excellent agreement with experimental measurements. Revealing the intrinsic correlation underlying the empirical constant and quantum chemical descriptors can develop simpler and higher efficient model application in predicting the environmental behavior and chemical properties of compounds.

scholarly journals Therortical Studies and Investagting of Selected Potnet CDK2 Inhibitors as Anticancer Agents

2021 ◽  
Author(s):  
Mohammad J Abunuwar ◽  
Adnan A Dahadha
Keyword(s):  
Anticancer Agents ◽  
Density Functional ◽  
Chemical Potential ◽  
Chemical Reactivity ◽  
Three Dimensional ◽  
Data Bank ◽  
Basis Set ◽  
Chemical Hardness ◽  
Cyclin Dependent Kinase ◽  
Reactivity Descriptors

Abstract In this study eight selected of the most potent cyclin dependent kinase 2 inhibitors in which targeting adenosine triphosphate -pocket site theoretically investigated to support literature information of frontier molecular orbitals, molecular electrostatic maps, and global chemical reactivity descriptors such as chemical hardness, chemical softness, chemical potential, electronegativity and electrophilicity of cyclin dependent kinase 2 inhibitors. Calculation and three-dimensional plotting were achieved through Gaussian 09W and Gausview 6 software’s utilizing density functional theory quantum modeling applying both hybrids extended and not extended basis set. Crystal structure of CDK2 with inhibitors was obtained from protein data bank and visualized through PyMol Schrödinger software to assign polar and non-polar interactions of inhibitors with enzyme. A promising conclusion trend obtained in this research regarding to molecules that could have an inhibition activity toward the cyclin dependent kinase 2 enzymes. Our theoretical investigation emphasizes that, the anti-cancer activity has directly relationship with value of chemical hardness and chemical softness, where the most potent compounds was the pyrazolopyrimidine and imidazole pyrimidine and they have higher chemical hardness value and at the same time lower value of chemical softness compared with the rest of compounds.

scholarly journals Conceptual DFT as a Novel Chemoinformatics Tool for Studying the Chemical Reactivity Properties of the Amatoxin Family of Fungal Peptides

2019 ◽  
Vol 17 (1) ◽  
pp. 1133-1139 ◽  
Author(s):  
Norma Flores-Holguín ◽  
Juan Frau ◽  
Daniel Glossman-Mitnik
Keyword(s):  
Density Functional ◽  
Chemical Reactivity ◽  
Active Regions ◽  
Chemical Hardness ◽  
Conceptual Density Functional Theory ◽  
Fukui Functions ◽  
Reactivity Descriptors ◽  
Molecular Systems ◽  
Chemical Structures ◽  
Simple Protocol

AbstractThe chemical structures and molecular reactivities of the Amatoxin group of fungi-derived peptides have been determined by means of the consideration of a model chemistry that has been previously validated as well-behaved for our purposes. The reactivity descriptors were calculated on the basis of a methodological framework built around the concepts that are the outcome of the so called Conceptual Density Functional Theory (CDFT). This procedure in connection with the different Fukui functions allowed to identify the chemically active regions within the molecules. By considering a simple protocol designed by our research group for the estimation of the pKa of peptides through the information coming from the chemical hardness, these property has been established for the different molecular systems explored in this research. The information reported through this work could be of interest for medicinal chemistry researchers in using this knowledge for the design of new medicines based on the studied peptides or as a help for the understanding of the toxicity mechanisms exerted by them.

Prediction of the polarity parameter π for the radical derived from monomer

e-Polymers ◽  
2009 ◽  
Vol 9 (1) ◽  
Author(s):  
Xinliang Yu ◽  
Wenhao Yu ◽  
Bing Yi ◽  
Xueye Wang
Keyword(s):  
Neural Network ◽  
Quantum Chemical ◽  
Density Functional ◽  
Ann Model ◽  
Quantum Chemical Descriptors ◽  
Functional Theory ◽  
The Neural Network ◽  
Polarity Parameter ◽  
Chemical Descriptors ◽  
Artificial Neural Network Ann

AbstractAn artificial neural network (ANN) model was successfully developed for the modelling and prediction of the polarity parameter π used in the revised patterns scheme for the prediction of monomers reactivity ratios in radical polymerizations. Four quantum chemical descriptors based on density functional theory (DFT) calculations were used to develop the ANN model. The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. Simulated with the final optimum BP neural network 4-4-1, the results show that the predicted parameter π values are in good agreement with the experimental ones, with the root mean square (rms) errors being 0.053 (R=0.960) for the training set and 0.070 (R=0.942) for the test set. The ANN model has better statistic quality than the MLR model, which indicates there are nonlinear relationships between these quantum chemical descriptors and the parameter π.

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