Docking and 3D QSAR study of thiourea analogs as potent inhibitors of influenza virus neuraminidase

Surflex-Dock was applied to study interactions between 30 thiourea analogs and neuraminidase (NA). The docking results showed that hydrogen bonding and electrostatic interactions were highly correlated with the activities of neuraminidase inhibitors (NIs), followed by hydrophobic and steric factors. Moreover, there was a strong correlation between the predicted binding affinity (total score) and experimental pIC₅₀ (correlation coefficient r = 0.870; P < 0.0001). A three dimensional holographic vector of atomic interaction field (3D-HoVAIF) was employed to construct a QSAR model. The r ², q ² and r ² _test values of the optimal QSAR model were 0.849, 0.724 and 0.689, respectively. From the QSAR model, it could be seen that electrostatic, hydrophobic and steric interactions were closely related to inhibitory activity, which was consistent with the docking results. Based on the docking and QSAR results, five new compounds with high predicted activities were designed.     

In silico QSAR studies of anilinoquinolines as EGFR inhibitors

Members of the epidermal growth factor receptor (EGFR) family of proteins are frequently overactive in solid tumors. A relatively new therapeutic approach to inhibit the kinase activity is the use of ATP-competitive small molecules. In silico techniques were employed to identify the key interactions between inhibitors and their protein receptors. A series of EGFR inhibitory anilinoquinolines was studied within the framework of hologram quantitative structure activity relationship (HQSAR), density functional theory (DFT)-based QSAR, and three-dimensional (3D) QSAR (CoMFA/CoMSIA). The HQSAR analysis implied that substitutions at certain sites on the inhibitors play an important role in EGFR inhibition. DFT-based QSAR results suggested that steric and electronic interactions contributed significantly to the activity. Ligand-based 3D-QSAR and receptor-guided 3D-QSAR analyses such as CoMFA and CoMSIA techniques were carried out, and the results corroborated the previous two approaches. The 3D QSAR models indicated that steric and hydrophobic interactions are dominant, and that substitution patterns are an important factor in determining activity. Molecular docking was helpful in identifying a bioactive conformer as well as a plausible binding mode. The docked geometry-based CoMFA model with steric and electrostatic fields effect gave q ² = 0.66, r ² = = 0.94 with r ² _predictive = 0.72. Similarly, CoMSIA with hydrophobic field gave q ² = 0.59, r ² = 0.85 with r ² _predictive = 0.63. Bulky groups around site 3 of ring “C”, and hydrophilic and bulky groups at position 6 of ring “A” are desirable, with a hydrophobic and electron-donating group at site 7 of ring “A” being helpful. Accordingly, potential EGFR inhibitors may be designed by modification of known inhibitors.     

2D-QSAR study,molecular docking,and molecular dynamics simulation studies of interaction mechanism between inhibitors and transforming growth factor-beta receptor I (ALK5)

Transforming growth factor type 1 receptor (ALK5) is kinase associated with a wide variety of pathological processes, and inhibition of ALK5 is a good strategy to treat many kinds of cancer and fibrotic diseases. Recently, a series of compounds have been synthesized as ALK5 inhibitors. However, the study of their selectivity against other potential targets remains elusive. In this research, a data-set of ALK5 inhibitors were collected and studied based on the combination of 2D-QSAR, molecular docking and molecular dynamics simulation. The quality of QSAR models were assessed statistically by F, R², and R²_ADJ, proved to be credible. The cross-validations for the models (q²_LOO = 0.571 and 0.629, respectively) showed their robustness, while the external validations (r²_test = 0.703 and 0.764, respectively) showed their predictive power. Besides, the predicted binding free energy results calculated by MM/GBSA method were in accordance with the experimental data, and the van der Waals energy term was the factor that had the most significant impact on ligand binding. What is more, several important residues were found to significantly affect the binding affinity. Finally, based on our analyses above, a proposed series of molecules were designed.     

Titanium dioxide nanoparticles preferentially bind in subdomains IB,IIA of HSA and minor groove of DNA

Titanium dioxide nanoparticles (TiO₂-NPs) interaction with human serum albumin (HSA) and DNA was studied by UV–visible spectroscopy, spectrofluorescence, circular dichroism (CD), and transmission electron microscopy (TEM) to analyze the binding parameters and protein corona formation. TEM revealed protein corona formation on TiO₂-NPs surface due to adsorption of HSA. Intrinsic fluorescence quenching data suggested significant binding of TiO₂-NPs (avg. size 14.0 nm) with HSA. The Stern–Volmer constant (K_sv) was determined to be 7.6 × 10² M^?1 (r² = 0.98), whereas the binding constant (K_a) and number of binding sites (n) were assessed to be 5.82 × 10² M^?1 and 0.97, respectively. Synchronous fluorescence revealed an apparent decrease in fluorescence intensity with a red shift of 2 nm at Δλ = 15 nm and Δλ = 60 nm. UV–visible analysis also provided the binding constant values for TiO₂-NPs–HSA and TiO₂-NPs-DNA complexes as 2.8 × 10² M^?1 and 5.4 × 10³ M^?1. The CD data demonstrated loss in α-helicity of HSA and transformation into β-sheet, suggesting structural alterations by TiO₂-NPs. The docking analysis of TiO₂-NPs with HSA revealed its preferential binding with aromatic and non-aromatic amino acids in subdomain IIA and IB hydrophobic cavity of HSA. Also, the TiO₂-NPs docking revealed the selective binding with A-T bases in minor groove of DNA.     

Exploring QSAR for CYP11B2 binding affinity and CYP11B2/CYP11B1 selectivity of diverse functional compounds using GFA and G/PLS techniques

A data set of a series of 132 structurally diverse compounds with cytochrome 11B2 and 11B1 (CYP11B2 and CYP11B1) enzyme inhibitory activities was subjected to molecular shape analysis to explore contributions of shape features as well as electronic, structural, and physicochemical parameters toward enzyme inhibitory activities, in search of appropriate molecular scaffolds with optimum substitutions for highly potent CYP11B2 inhibitors. Genetic function approximation (GFA) and genetic partial least squares (G/PLS) were used as chemometric tools for modeling, and the derived equations were of acceptable statistical quality considering both internal and external validation parameters (Q²: 0.514–0.659, R²_pred: 0.510–0.734). The G/PLS models with spline option for CYP11B2 and CYP11B1 inhibition and selectivity modeling appeared to be the best models based on r_m²_(overall) criterion. The study indicates the importance of the pyridinylnaphthalene and pyridylmethylene-indane scaffolds with less polar and electrophilic substituents for optimum CYP11B2 inhibitory activity and CYP11B2/CYP11B1 selectivity.     

3D-QSAR study of c-Src kinase inhibitors based on docking

Cancer is a significant world health problem for which efficient therapies are in urgent demand. c-Src has emerged as an attractive target for drug discovery efforts toward antitumor therapies. Toward this target several series of c-Src inhibitors that showed activity in the assay have been reported. In this article, 3D-QSAR models have been built with 156 anilinoquinazoline and quinolinecarbonitrile derivative inhibitors by using CoMFA and CoMSIA methods. These studies indicated that the QSAR models were statistically significant with high predictabilities (CoMFA model, q ² = 0.590, r ² = 0.855; CoMSIA model, q ² = 0.538, r ² = 0.748). The details of c-Src kinase/inhibitor binding interactions in the crystal structure of complex provided new information for the design of new inhibitors. As a result, docking simulations were also conducted on the series of potent inhibitors. The flexible docking method, which was performed by the DOCK program, positioned all of the inhibitors into the active site to determine the probable binding conformation. The CoMFA and CoMSIA models based on the flexible docking conformations also yielded statistically significant and highly predictive QSAR models (CoMFA model, q ² = 0.507, r ² = 0.695; CoMSIA model, q ² = 0.463, r ² = 0.734). Our models would offer help to better comprehend the structure-activity relationships that exist for this class of compounds and also facilitate the design of novel inhibitors with good chemical diversity.     

Investigation of binding mechanism of novel 8-substituted coumarin derivatives with human serum albumin and α-1-glycoprotein

Coumarin molecules have biological activities possessing lipid-controlling activity, anti-hepatitis C activity, anti-diabetic, anti-Parkinson activity, and anti-cancer activity. Here, we have presented an inclusive study on the interaction of 8-substituted-7-hydroxy coumarin derivatives (Umb-1/Umb-2) with α-1-glycoprotein (AGP) and human serum albumin (HSA) which are the major carrier proteins in the human blood plasma. Binding constants obtained from fluorescence emission data were found to be K_Umb-1=3.1 ± .01 × 10⁴ M^?1, K_Umb-2 = 7 ± .01 × 10⁴ M^?1, which corresponds to ?6.1 and ?6.5 kcal/mol of free energy for Umb-1 and Umb-2, respectively, suggesting that these derivatives bind strongly to HSA. Also these molecules bind to AGP with binding constants of K_Umb-1-AGP=3.1 ± .01 × 10³ M^?1 and K_Umb-2-AGP = 4.6 ± .01 × 10³ M^?1. Further, the distance, r between the donor (HSA) and acceptor (Umb-1/Umb-2) was calculated based on the Forster’s theory of non-radiation energy transfer and the values were observed to be 1.14 and 1.29 nm in Umb-1–HSA and Umb-2–HSA system, respectively. The protein secondary structure of HSA was partially unfolded upon binding of Umb-1 and Umb-2. Furthermore, site displacement experiments with lidocaine, phenylbutazone (IIA), and ibuprofen (IIIA) proves that Umb derivatives significantly bind to subdomain IIIA of HSA which is further supported by docking studies. Furthermore, Umb-1 binds to LYS402 with one hydrogen bond distance of 2.8 Å and Umb-2 binds to GLU354 with one hydrogen bond at a distance of 2.0 Å. Moreover, these molecules are stabilized by hydrophobic interactions and hydrogen bond between the hydroxyl groups of carbon-3 of coumarin derivatives.     

In silico studies on the interaction between bioactive ligands and ALK5, a biological target related to the cancer treatment

Studies have showed that there are many biological targets related to the cancer treatment, for example, TGF type I receptor (TGF-βRI or ALK5). The ALK5 inhibition is a strategy to treat some types of cancer, such as breast, lung, and pancreas. Here, we performed CoMFA and CoMSIA studies for 70 ligands with ALK5 inhibition. The internal validation for both models (q²_LOO = 0.887 and 0.822, respectively) showed their robustness, while the external validations showed their predictive power (CoMFA: r²_test = 0.998; CoMSIA: r²_test = 0.975). After all validations, CoMFA and CoMSIA maps indicated physicochemical evidences on the main factors involved in the interaction between bioactive ligands and ALK5. Therefore, these results suggest molecular modifications to design new ALK5 inhibitors.     

3D-QSAR (CoMFA,CoMSIA), molecular docking and molecular dynamics simulations study of 6-aryl-5-cyano-pyrimidine derivatives to explore the structure requirements of LSD1 inhibitors

Recently, Histone Lysine Specific Demethylase 1 (LSD1) was regarded as a promising anticancer target for the novel drug discovery. And several small molecules as LSD1 inhibitors in different structures have been reported. In this work, we carried out a molecular modeling study on the 6-aryl-5-cyano-pyrimidine fragment LSD1 inhibitors using three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamics simulations. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to generate 3D-QSAR models. The results show that the best CoMFA model has q² = 0.802, r²_ncv = 0.979, and the best CoMSIA model has q² = 0.799, r²_ncv = 0.982. The electrostatic, hydrophobic and H-bond donor fields play important roles in the models. Molecular docking studies predict the binding mode and the interactions between the ligand and the receptor protein. Molecular dynamics simulations results reveal that the complex of the ligand and the receptor protein are stable at 300 K. All the results can provide us more useful information for our further drug design.     

Time-related eating patterns and chronotype are associated with diet quality in pregnant women

Animal studies strongly suggest that timed feeding can have beneficial physiological effects, including protection against the obesogenic and metabolic consequences of a high-fat diet. However, the relationship between variables related to the timing of eating and diet quality in pregnancy women, which is considered as a period of nutritional vulnerability, is still poorly described in the literature. Therefore, the aim of the present study was to investigate the associations between time-related eating patterns and chronotype with diet quality of pregnant women. This cross-sectional study was conducted with 100 pregnant women in the first gestational trimester (≤12 weeks of gestation). The information regarding food intake was obtained by three 24-Hour Dietary Recall (24HR). Time-related eating patterns, i.e., the interval between the first and the last meal (eating duration), nightly fasting, time of the first and last meals, and number of meals eating on a day were determined. Chronotype was derived using the mid-sleep time on free days on weekends, with a further correction for calculated sleep debt. Diet quality was evaluated using the Brazilian Healthy Eating Index-Revised (BHEI-R), validated for the Brazilian population. Linear regression modeling analyses adjusted for confounders were used to investigate the association between time-related eating patterns and chronotype with diet quality. The BHEI-R total score was negatively associated with time of the first meal (β = ?0.355; p = 0.002; r² adjusted = 0.141), and positively associated with eating duration (β = 0.262; p = 0.024; r² adjusted = 0.086) and number of meals (β = 0.273; p = 0.019; r² adjusted = 0.091). In addition, the score of total fruit component was negatively associated with chronotype (β = ?0.236; p = 0.033; r² adjusted = 0.078), time of the first meal (β = ?0.393; p = 0.001; r² adjusted = 0.171), and positively associated with eating duration (β = 0.259; p = 0.022; r² adjusted = 0.087) and number of meals (β = 0.376; p = 0.001; r² adjusted = 0.159). The score for whole fruit component was negatively associated with time of the first meal (β = ?0.388; p = 0.001; r² adjusted = 0.152), and positively associated with number of meals (β = 0.403; p = 0.001; r² adjusted = 0.164). A longer eating duration, earlier time of the first meal, higher number of meals and morningness tendency are associated with a better diet quality in the first gestational trimester – higher scores of the total BHEI-R and/or fruit components. We suggest that nutritional guidelines should consider time-related eating patterns and chronotype to ensure good diet quality of pregnant women since the beginning of gestation, contributing on prevention of metabolic-nutritional complications.     

QSAR-based prediction of anti-HCV activity of thiourea derivatives

Quantitative structure–activity relationship (QSAR) studies were performed on a series of thioureas to explore the physico-chemical parameters responsible for their activity against the hepatitis C virus (HCV)-infected AVa5 cell. The physico-chemical parameters were calculated using WIN CAChe 6.1. Multiple linear regression analysis, after the variables selection by factor analysis, was performed to derive QSAR models which were further evaluated for their statistical significance and predictive power by internal and external validation. The developed QSAR model had the correlation coefficient (R) = 0.928 and cross-validated squared correlation coefficient (Q ²) = 0.751. The selected significant QSAR model indicates that hydrophobicity, dielectric energy, valence connectivity index (order 1), conformational minimum energy and highest occupied molecular orbital of the whole molecule play an important role in the anti-HCV activity of thioureas.     

Pharmacophore models generation by catalyst and phase consensus-based virtual screening protocol against PI3Kα inhibitors

Phosphoinositide 3-kinases (PI3Ks) family has emerged as promising targets for novel therapeutic agents against neoplastic diseases. Pharmacophore and 3D-quantitative structure–activity relationship modelling were applied to study the structure–activity relationship of PI3K inhibitors. The best HypoGen pharmacophore hypothesis Hypo1 with a correlation coefficient of 0.961 consists of one hydrogen-bond acceptor, one hydrogen-bond donor and two hydrophobic features, whereas the best phase hypothesis AADRRR.378 with favourable statistics (q² = 0.7368, r² = 0.9863) has two hydrogen-bond acceptors, one hydrogen-bond donor and three ring aromatic features. Multiple methods, such as Fischer validation, molecular docking and mapping of test set molecules, were carried out to validate these pharmacophore models. Furthermore, a comparative molecular similarity indices analysis candidate hypothesis model was generated as a supplement of pharmacophore hypothesis. Detailed protein–ligand binding information obtained by Glide was utilised in compound optimisation and virtual screening. A molecular database of 133 known inhibitors and 6179 decoys was built for a screening test to quantitatively analyse various hypotheses and scoring parameters. Finally, we designed a workflow integrating HypoGen pharmacophore searching, phase pharmacophore searching and molecular docking for screening the database. With an improved criterion of enrichment factor (EF = 17.43) and ROC curve (AUC = 0.946), this workflow would provide us an original method for novel PI3K inhibitors.     

Design,synthesis, MTT assay,DNA interaction studies of platinum(II) complexes

The square planar Pt(II) complexes of the type [Pt(Lⁿ)(Cl₂)] (where Lⁿ = L^1?3 = thiophene-2-carboxamide derivatives and L^4?6 = thiophene-2-carbothioamide derivatives) have been synthesized and characterized by physicochemical and various spectroscopic studies. MIC method was employed to inference the antibacterial potency of complexes in reference to free ligands and metal salt. Characteristic binding constant (K_b) and binding mode of complexes with calf thymus DNA (CT-DNA) were determined using absorption titration (0.76–1.61 × 10⁵ M^?1), hydrodynamic chain length assay and fluorescence quenching analysis, deducing the partial intercalative mode of binding. Molecular docking calculation displayed free energy of binding in the range of –260.06 to –219.63 kJmol^?1. The nuclease profile of complexes towards pUC19 DNA shows that the complexes cleave DNA more efficiently compared to their respective metal salt. Cytotoxicity profile of the complexes on the brine shrimp shows that all the complex exhibit noteworthy cytotoxic activity with LC₅₀ values ranging from 7.87 to 15.94 μg/mL. The complexes have been evaluated for cell proliferation potential in human colon carcinoma cells (HCT 116) and IC₅₀ value of complexes by MTT assay (IC₅₀ = 125–1000 μg/mL).     

In silico studies on potential MCF-7 inhibitors: a combination of pharmacophore and 3D-QSAR modeling,virtual screening,molecular docking,and pharmacokinetic analysis

Gallic acid and its derivatives exhibit a diverse range of biological applications, including anti-cancer activity. In this work, a data-set of forty-six molecules containing the galloyl moiety, and known to show anticarcinogenic activity against the MCF-7 human cancer cell line, have been chosen for pharmacophore modeling and 3D-Quantitative Structure Activity Relationship (3D-QSAR) studies. A tree-based partitioning algorithm has been used to find common pharmacophore hypotheses. The QSAR model was generated for three, four, and five featured hypotheses with increasing PLS factors and analyzed. Results for five featured hypotheses with three acceptors and two aromatic rings were the best out of all the possible combinations. On analyzing the results, the most robust (R^2?=?.8990) hypothesis with a good predictive power (Q^2?=?.7049) was found to be AAARR.35. A good external validation (R² = .6109) was also obtained. In order to design new MCF-7 inhibitors, the QSAR model was further utilized in pharmacophore-based virtual screening of a large database. The predicted IC₅₀ values of the identified potential MCF-7 inhibitors were found to lie in the micromolar range. Molecular docking into the colchicine domain of tubulin was performed in order to examine one of the probable mechanisms. This revealed various interactions between the ligand and the active site protein residues. The present study is expected to provide an effective guide for methodical development of potent MCF-7 inhibitors.