Quantum chemical QSAR study of flavones and their radical-scavenging activity

DFT and QSAR studies of PTFE/ZnO/SiO2 nanocomposite

Polytetrafluoroethylene (PTFE) is one of the most significant fluoropolymers, and one of the most recent initiatives is to increase its performance by using metal oxides (MOs). Consequently, the surface modifications of PTFE with two metal oxides (MOs), SiO₂ and ZnO, individually and as a mixture of the two MOs, were modeled using density functional theory (DFT). The B3LYPL/LANL2DZ model was used in the studies conducted to follow up the changes in electronic properties. The total dipole moment (TDM) and HOMO/LUMO band gap energy (∆E) of PTFE, which were 0.000 Debye and 8.517 eV respectively, were enhanced to 13.008 Debye and 0.690 eV in the case of PTFE/4ZnO/4SiO₂. Moreover, with increasing nano filler (PTFE/8ZnO/8SiO₂), TDM changed to 10.605 Debye and ∆E decreased to 0.273 eV leading to further improvement in the electronic properties. The molecular electrostatic potential (MESP) and quantitative structure activity relationship (QSAR) studies revealed that surface modification of PTFE with ZnO and SiO₂ increased its electrical and thermal stability. The improved PTFE/ZnO/SiO₂ composite can, therefore, be used as a self-cleaning layer for astronaut suits based on the findings of relatively high mobility, minimal reactivity to the surrounding environment, and thermal stability.

Designing of the N-ethyl-4-(pyridin-4-yl)benzamide based potent ROCK1 inhibitors using docking, molecular dynamics, and 3D-QSAR

Rho-associated kinase-1 (ROCK1) has been recognized for its pivotal role in heart diseases, different types of malignancy, and many neurological disorders. Hyperactivity of ROCK phosphorylates the protein kinase-C (PKC), which ultimately induces smooth muscle cell contraction in the vascular system. Inhibition of ROCK1 has been shown to be a promising therapy for patients with cardiovascular disease. In this study, we have conducted molecular modeling techniques such as docking, molecular dynamics (MD), and 3-Dimensional structure-activity relationship (3D-QSAR) on a series of N-ethyl-4-(pyridin-4-yl)benzamide-based compounds. Docking and MD showed critical interactions and binding affinities between ROCK1 and its inhibitors. To establish the structure-activity relationship (SAR) of the compounds, 3D-QSAR techniques such as Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were used. The CoMFA (q ² = 0.774, r ² = 0.965, ONC = 6, and r p r e d 2 = 0.703) and CoMSIA (q ² = 0.676, r ² = 0.949, ONC = 6, and r p r e d 2 = 0.548) both models have shown reasonable external predictive activity, and contour maps revealed favorable and unfavorable substitutions for chemical group modifications. Based on the contour maps, we have designed forty new compounds, among which, seven compounds exhibited higher predictive activity (pIC₅₀). Further, we conducted the MD study, ADME/Tox, and SA score prediction using the seven newly designed compounds. The combination of docking, MD, and 3D-QSAR studies helps to understand the coherence modification of existing molecules. Our study may provide valuable insight into the development of more potent ROCK1 inhibitors.

Molecular Modeling Study of c-KIT/PDGFRα Dual Inhibitors for the Treatment of Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are the most common Mesenchymal Neoplasm of the gastrointestinal tract. The tumorigenesis of GISTs has been associated with the gain-of-function mutation and abnormal activation of the stem cell factor receptor (c-KIT) and platelet-derived growth factor receptor alpha (PDGFRα) kinases. Hence, inhibitors that target c-KIT and PDGFRα could be a therapeutic option for the treatment of GISTs. The available approved c-KIT/PDGFRα inhibitors possessed low efficacy with off-target effects, which necessitated the development of potent inhibitors. We performed computational studies of 48 pyrazolopyridine derivatives that showed inhibitory activity against c-KIT and PDGFRα to study the structural properties important for inhibition of both the kinases. The derivative of phenylurea, which has high activities for both c-KIT (pIC₅₀ = 8.6) and PDGFRα (pIC₅₀ = 8.1), was used as the representative compound for the dataset. Molecular docking and molecular dynamics simulation (100 ns) of compound 14 was performed. Compound 14 showed the formation of hydrogen bonding with Cys673, Glu640, and Asp810 in c-KIT, and Cys677, Glu644, and Asp836 in PDGFRα. The results also suggested that Thr670/T674 substitution in c-KIT/PDGFRα induced conformational changes at the binding site of the receptors. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed based on the inhibitors. Contour map analysis showed that electropositive and bulky substituents at the para-position and the meta-position of the benzyl ring of compound 14 was favorable and may increase the inhibitory activity against both c-KIT and PDGFRα. Analysis of the results suggested that having bulky and hydrophobic substituents that extend into the hydrophobic pocket of the binding site increases the activity for both c-KIT and PDGFRα. Based on the contour map analysis, 50 compounds were designed, and the activities were predicted. An evaluation of binding free energy showed that eight of the designed compounds have potential binding affinity with c-KIT/PDGFRα. Absorption, distribution, metabolism, excretion and toxicity (ADMET) and synthetic feasibility tests showed that the designed compounds have reasonable pharmaceutical properties and synthetic feasibility. Further experimental study of the designed compounds is recommended. The structural information from this study could provide useful insight into the future development of c-KIT and PDGFRα inhibitors.

QSPR/QSAR: State-of-Art, Weirdness, the Future

Ability of quantitative structure-property/activity relationships (QSPRs/QSARs) to serve for epistemological processes in natural sciences is discussed. Some weirdness of QSPR/QSAR state-of-art is listed. There are some contradictions in the research results in this area. Sometimes, these should be classified as paradoxes or weirdness. These points are often ignored. Here, these are listed and briefly commented. In addition, hypotheses on the future evolution of the QSPR/QSAR theory and practice are suggested. In particular, the possibility of extending of the QSPR/QSAR problematic by searching for the "statistical similarity" of different endpoints is suggested and illustrated by an example for relatively "distanced each from other" endpoints, namely (i) mutagenicity, (ii) anticancer activity, and (iii) blood-brain barrier.

Adaptive neuro-fuzzy inference system-applied QSAR with bond dissociation energy for antioxidant activities of phenolic compounds

The aim of this study was to develop quantitative structure-activity relationship (QSAR) models for predicting antioxidant activities of phenolic compounds. The bond dissociation energy of O-H bond (BDE) was calculated by semi-empirical quantum chemical methods. As a new parameter for QSAR models, sum of reciprocals of BDE of enol and phenol groups (X _BDE ) was calculated. Significant correlations were observed between X _BDE and antioxidant activities, and X _BDE was introduced as a parameter for developing QSAR models. Linear regression-applied QSAR models and adaptive neuro-fuzzy inference system (ANFIS)-applied QSAR models were developed. QSAR models by both of linear regression and ANFIS achieved high prediction accuracies. Among the developed models, ANFIS-applied models achieved better prediction accuracies than linear regression-applied models. From these results, the proposed parameter of X _BDE was confirmed as an appropriate variable for predicting and analysing antioxidant activities of phenolic compounds. Also, the ANFIS could be applied on QSAR models to improve prediction accuracy.

4-Thiazolidinone derivatives: synthesis, antimicrobial, anticancer evaluation and QSAR studies

A series of novel 4-thiazolidinone derivatives (1–18) was synthesized evaluated for its antimicrobial and anticancer potential.

Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids

One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

QSAR study of the DPPH· radical scavenging activity of coumarin derivatives and xanthine oxidase inhibition by molecular docking

A Quantitative Structure-Activity Relationship (QSAR) of coumarins by genetic algorithms employing physicochemical, topological, lipophilic and electronic descriptors was performed. We have used experimental antioxidant activities of specific coumarin derivatives against the DPPH· radical molecule. Molecular descriptors such as Randic Path/Walk, hydrophilic factor and chemical hardness were selected to propose a mathematical model. We obtained a linear correlation with R2 = 96.65 and Q LOO2 = 93.14 values. The evaluation of the predictive ability of the model was performed by applying the Q ASYM2, $\hat r^2 $ and Δr m2 methods. Fukui functions were calculated here for coumarin derivatives in order to delve into the mechanics by which they work as primary antioxidants. We also investigated xanthine oxidase inhibition with these coumarins by molecular docking. Our results show that hydrophobic, electrostatic and hydrogen bond interactions are crucial in the inhibition of xanthine oxidase by coumarins.

Synthesis and in vitro antioxidant activity evaluation of 3-carboxycoumarin derivatives and QSAR study of their DPPH• radical scavenging activity

The in vitro antioxidant activities of eight 3-carboxycoumarin derivatives were assayed by the quantitative 1,1-diphenyl-2-picrylhydrazil (DPPH•) radical scavenging activity method. 3-Acetyl-6-hydroxy-2H-1-benzopyran-2-one (C1) and ethyl 6-hydroxy-2-oxo-2H-1-benzopyran-3-carboxylate (C2) presented the best radical-scavenging activity. A quantitative structure-activity relationship (QSAR) study was performed and correlated with the experimental DPPH• scavenging data. We used structural, geometrical, topological and quantum-chemical descriptors selected with Genetic Algorithms in order to determine which of these parameters are responsible of the observed DPPH• radical scavenging activity. We constructed a back propagation neural network with the hydrophilic factor (Hy) descriptor to generate an adequate architecture of neurons for the system description. The mathematical model showed a multiple determination coefficient of 0.9196 and a root mean squared error of 0.0851. Our results shows that the presence of hydroxyl groups on the ring structure of 3-carboxy-coumarins are correlated with the observed DPPH• radical scavenging activity effects.

Any colour you like. Excited state and ground state proton transfer in flavonols and applications

The photoinduced and ground state proton transfer processes occurring in flavonols are responsible for their multi-wavelength emission. This peculiar behavior has touched on a wide range of research areas, ranging from biology to chemistry of materials leading, among others, to the development of fluorescent probes for physical and biophysical parameters, laser dyes, and wavelentgh shifting devices. This account aims to be a brief introduction to the multi-faceted applications of flavonols.

The basic antioxidant structure for flavonoid derivatives

An antioxidant structure-activity study is carried out in this work with ten flavonoid compounds using quantum chemistry calculations with the functional of density theory method. According to the geometry obtained by using the B3LYP/6-31G(d) method, the HOMO, ionization potential, stabilization energies, and spin density distribution showed that the flavonol is the more antioxidant nucleus. The spin density contribution is determinant for the stability of the free radical. The number of resonance structures is related to the π-type electron system. 3-hydroxyflavone is the basic antioxidant structure for the simplified flavonoids studied here. The electron abstraction is more favored in the molecules where ether group and 3-hydroxyl are present, nonetheless 2,3-double bond and carbonyl moiety are facultative.

13C NMR spectral data and molecular descriptors to predict the antioxidant activity of flavonoids

Tissue damage due to oxidative stress is directly linked to development of many, if not all, human morbidity factors and chronic diseases. In this context, the search for dietary natural occurring molecules with antioxidant activity, such as flavonoids, has become essential. In this study, we investigated a set of 41 flavonoids (23 flavones and 18 flavonols) analyzing their structures and biological antioxidant activity. The experimental data were submitted to a QSAR (quantitative structure-activity relationships) study. NMR 13C data were used to perform a Kohonen self-organizing map study, analyzing the weight that each carbon has in the activity. Additionally, we performed MLR (multilinear regression) using GA (genetic algorithms) and molecular descriptors to analyze the role that specific carbons and substitutions play in the activity.