Q2 Values Research Articles

UPLC-Q-TOF/MS-based metabolomic analysis reveals the effects of asomate on the citrus fruit

The regulation of the sugar-acid ratio is of great significance to the improvement of citrus fruit quality. The citric acid level in fruit is influenced by many factors. Among them, cultivar selection and production practices are the most important strategies under the grower's control. In recent years, an arsenic-containing preparation called “Tianmisu”, with the main ingredient of asomate, has occasionally been reported to be used in citrus cultivation to improve the sweetness of fruits. In order to reveal the effects of the pesticide on citrus fruits, ‘Harumi’ tangor was treated with “Tianmisu”, and the impact of this pesticide on fruit quality and metabolites was investigated through UPLC-Q-TOF/MS-based metabolomic analysis. Compared with the control, the concentration of titratable acidity, in particular citric acid, in the pulp of ‘Harumi’ tangor treated with the pesticide, was significantly reduced by 60.5%. The differences in metabolites between the pesticide-treated samples and the control were illustrated by Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA). The PLS-DA analysis demonstrated a clear discrimination, with R2Y and Q2 values of 0.982 and 0.933 in the positive mode and 0.984 and 0.900 in the negative mode, respectively. A total of 155 compounds were identified, and 63 characteristic components were screened out from the pesticide-treated samples compared to the control. Aside from the upregulation observed for a few metabolites, the majority of the compounds, including citric acid and various lipids, were down-regulated in the treated citrus fruits compared to the control. This study can serve as a basis for understanding the regulatory mechanism of organic acids in citrus and will be helpful in developing different strategies to improve citrus quality.

Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes

Chronic myelogenous leukemia (CML) which is resulted from the BCR-ABL tyrosine kinase (TK) chimeric oncoprotein, is a malignant clonal disorder of hematopoietic stem cells. Imatinib is used as an inhibitor of BCR-ABL TK in the treatment of CML patients. The main object of the present manuscript is focused on constructing quantitative activity relationships (QSARs) models for the prediction of inhibition potencies of a large series of imatinib derivatives against BCR-ABL TK. Herren, the inbuilt Monte Carlo algorithm of CORAL software is employed to develop QSAR models. The SMILES notations of chemical structures are used to compute the descriptor of correlation weights (CWs). QSAR models are established using the balance of correlation method with the index of ideality of correlation (IIC). The data set of 306 molecules is randomly divided into three splits. In QSAR modeling, the numerical value of R2, Q2, and IIC for the validation set of splits 1 to 3 are in the range of 0.7180–0.7755, 0.6891–0.7561, and 0.4431–0.8611 respectively. The numerical result of {CR}_{p}^{2} > 0.5 for all three constructed models in the Y-randomization test validate the reliability of established models. The promoters of increase/decrease for pIC50 are recognized and used for the mechanistic interpretation of structural attributes.

Discrimination of the geographical origin of dry red pepper using inorganic elements: A multielement fingerprinting analysis

This study was based on inductively coupled plasma optical emission spectroscopy and mass spectrometry. The purpose of this study was to develop an accurate method for clearly discriminating the origin of dry red pepper. Sixty-four domestic and 51 imported samples were acid treated in a microwave system. The geographical origin of each sample was identified using the contents of 60 elements. The OPLS-DA results showed that the R2 and Q2 values were 0.873 and 0.765, respectively, indicating a high ratio and prediction ratio of this model. A total of 26 elements with a VIP (Variable Importance in Projection) value of greater than 1 were selected, and each element had a decisive influence on the domestic and imported groups. An ROC (Receiver Operating Characteristic) analysis confirmed the accuracy of the identification of domestic and imported products using the selected 26 elements. The accuracy based on the ROC was 98.7%. A heatmap was used to select elements that were influential in identifying domestic and imported dry red pepper samples. All of the most influential elements were rare earth elements (REEs). The REE content of dry red pepper was significantly higher in imported than in domestic samples. CDA (Canonical Discriminant Analysis) showed that the accuracy of classification by group was 100% for each group.

Instant quantification of sugars in milk tablets using near-infrared spectroscopy and chemometric tools

Milk tablets are a popular dairy product in many Asian countries. This research aimed to develop an instant and rapid method for determining sucrose and lactose contents in milk tablets using near-infrared (NIR) spectroscopy. For the quantitative analysis, a training set composed of laboratory-scale milk samples was generated based on a central composite design (CCD) and used to establish partial least squares (PLS) regression for the predictions of sucrose and lactose contents resulting in R2 values of 0.9749 and 0.9987 with the corresponding root mean square error of calibration (RMSEC) values of 1.69 and 0.35. However, the physical difference between the laboratory-scale powder and the final product milk tablet samples resulted in spectral deviations that dramatically affected the predictive performance of the PLS models. Therefore, calibration transfer methods called direct standardization (DS) and piecewise direct standardization (PDS) were used to adjust the NIR spectra from the real milk tablet samples before the quantitative prediction. Using high-performance liquid chromatography (HPLC) as a reference method, the developed NIR-chemometric model could be used to instantly predict the sugar contents in real milk tablets by producing root mean square error of prediction (RMSEP) values for sucrose and lactose of 5.04 and 4.22 with Q2 values of 0.7973 and 0.9411, respectively, after the PDS transformation.

MODEL RLB TURUNAN NAFTAKUINON INHIBITOR SEL LINE HELA

Cervical cancer is a disease that is dangerous for life. Naphtaquinone is an anticancer agent whose derivatives have been successfully synthesized, so it is necessary to study QSAR to evaluate its potency. The purpose of this study was to determine the molecular descriptors of naphtoquinone-derived compounds that have a significant effect on the anticancer activity of HeLa cells and compile them into a valid QSAR model. A total of 15 compounds from naphtoquinone derivatives were used for modeling. The descriptors that were tried included 1,863 topological descriptors and physico-chemical properties descriptors. Results of correlation analysis obtained 17 descriptors that are feasible to be tested in modeling. Results of backward method obtained 3 descriptors that have a significant effect, namely AATSC6Z, AATSC7m, and MAXaaCH. The MLR model based on 3 descriptors fulfills the goodness of fit requirements with R=0.873, R2=0.763, R 2 Adjusted=0.698, F value=0.0009 (Ftable=11.778). The results of the validation test using the CV-LOO method obtained a value of Q2=0.572 and CV-LMO obtained a value of Q2=0.518 so that this HKSA model can be stated as a valid HKSA model.

Palliative care learning model based on transformational learning theory in palliative care of nursing students in Indonesia

IntroductionPalliative care competence is one of the competencies that must be possessed by generalist nurses. For this reason, strategies for developing palliative care learning models need to be carried out to ensure nursing students have palliative care competencies. Therefore, this study was structured to develop a transformation theory-based palliative care learning model that prioritizes the active participation of students to deal with palliative care in future practice. MethodsThis study was a cross-sectional study involving 189 nursing students as participants. The proposed model involves six variables, namely student characteristics, educator characteristics, learning media, palliative care competencies, transformative learning theory (TLT)-based palliative learning, and competency achievement. Data were collected using a questionnaire that was tested using the Structural Equation Modeling (SEM) technique. ResultsSEM analysis showed that the R2 value of TLT-based palliative care learning was 0.707 or 70.7%. These results indicate that the diversity of TLT-based palliative care learning variables can be explained by the variables of students, educators, palliative competencies, and learning media by 70.7%. Each construct has a value of Q2 > 0, which means the model is satisfactory. The path coefficient value of 0.627 indicates that the characteristics of educators have the most significant contribution to the TLT-based palliative care learning model. ConclusionIt can be concluded that the teaching-learning process based on TLT is a promising strategy to support nursing students to achieve palliative care competence.

Effected Factors on Standard Measurement Method Adoption in Construction Projects Using SEM Approach

Various factors affect the standard method of measurement adoption in civil construction projects, especially in developing countries such as Malaysia. Hence, this study investigates the relationship between affected factors towards standard adoption using the SEM approach. As a case study, this study focused on quantity surveyors working at a consulting firm in Selangor, Malaysia. This study identifies the effect of standard measuring technique adoption in Malaysian building projects that have a beneficial impact. The factors research model is the first stage in determining the reasons for using the most recent standard measuring technique in civil engineering construction projects and explaining the link between the barrier factors and standard adoption. The information was gathered using a questionnaire survey sent to participants at construction firms that used the standard measurement method. The PLS-SEM approach was used by SmartPLS 3 software to construct and assess a hierarchical model to assess variables and their effects on measuring method adoption. The findings revealed that 17 barrier factor indicators had a significant impact on adopting the standard assessment technique. The coefficient of determination (R2 value) of 0.307 represents the proportion of variance in the dependent variable that one or more predictor variables can explain. Furthermore, the conceptual model’s predictive significance value Q2 is 0.156 greater than zero, indicating that it can predict endogenous latent components. The measured effect size (f2) between the barrier factors (exogenous latent) and the adoption of the model’s standard (endogenous latent) was 0.443, indicating that the developed model had significant explanatory power to represent the relationship among the variables of the factors and the effect on measurement method adoption. There is a need to improve the methods and increase the driver elements described in this study to promote the adoption of standard measurement in construction projects, which impacts the adoption of the standard method of measuring. In the future, researchers can start from this study to compare the situation in Malaysia with developed countries to discover shortcomings and develop a framework for measurement factors that can be applied.

The hadronic running of the electromagnetic coupling and the electroweak mixing angle from lattice QCD

We compute the hadronic running of the electromagnetic and weak couplings in lattice QCD with Nf = 2 + 1 flavors of mathcal{O} (a) improved Wilson fermions. Using two different discretizations of the vector current, we compute the quark-connected and –disconnected contributions to the hadronic vacuum polarization (HVP) functions overline{varPi} γγ and overline{varPi} γZ for Euclidean squared momenta Q2 ≤ 7 GeV2. Gauge field ensembles at four values of the lattice spacing and several values of the pion mass, including its physical value, are used to extrapolate the results to the physical point. The ability to perform an exact flavor decomposition allows us to present the most precise determination to date of the SU(3)-flavor-suppressed HVP function overline{varPi} 08 that enters the running of sin2θW. Our results for overline{varPi} γγ, overline{varPi} γZ and overline{varPi} 08 are presented in terms of rational functions for continuous values of Q2 below 7 GeV2. We observe a tension of up to 3.5 standard deviation between our lattice results for Delta {alpha}_{mathrm{had}}^{(5)} (−Q2) and estimates based on the R-ratio for space-like momenta in the range 3–7 GeV2. The tension is, however, strongly diminished when translating our result to the Z pole, by employing the Euclidean split technique and perturbative QCD, which yields Delta {alpha}_{mathrm{had}}^{(5)}left({M}_Z^2right) = 0.02773(15) and agrees with results based on the R-ratio within the quoted uncertainties.

3D-QSAR, molecular docking and ADMET studies of thioquinazolinone derivatives against breast cancer

Breast cancer is a deadly disease and the second largest cause of mortality on a worldwide platform. Despite the availability of several cancer treatments, life expectancies stay relatively poor. Consequently, the medicinal chemistry community prioritizes the quick discovery of novel anticancer drugs. In recent years, computational approaches have been widely used to accelerate the drug development process. In light of this, in the current work, we performed three-dimensional quantitative structure-activity relationships (3D-QSAR) and molecular docking analyses on thioquinazolinone derivatives with aromatase enzyme (PDB: 3S7S). External validation was used to validate the prediction capabilities of the generated model. The best CoMSIA (comparative molecular similarity indices analysis) model exhibited the significant values of Q2, R2andRpred2. These findings suggested that the electrostatic, hydrophobic and hydrogen bond donor and acceptor fields have a significant effect on inhibition of breast cancer. Thus, a number of innovative potent aromatase inhibitors were designed and their biological activities were predicted based on the best model. Furthermore, molecular docking studies were carried out for the designed compounds against breast cancer. Additionally, ADMET proprieties were used to evaluate drug-likeness of these novel drug candidates. The most active compounds found by these computational studies could be helpful for synthesis and testing as prospective future anti-cancer treatments.

3D-QSAR and Docking Studies on Pyrimidine Derivatives of Second-Generation ALK Inhibitors

AbstractAnaplastic lymphoma kinase (ALK) is a promising target for the treatment of non-small cell lung cancer. Under crizotinib treatment, drug resistance and progressive disease appeared after the point mutations arising in the kinase domain of ALK. Second-generation ALK inhibitors can solve the deficiencies of the first generation, especially the drug resistance in cancer chemotherapy. Ceritinib (LDK378), a pyrimidine derivative, for example, can inhibit the activity of ALK with an IC50 value of 40.7 nmol/L, and can experience disease progression after initial treatment with crizotinib. Unfortunately, clear structure–activity relationships have not been identified to date, impeding the rational design of future compounds possessing ALK inhibition activity. To explore interesting insights into the structures of pyrimidine derivatives that influence the activities of the second-generation ALK inhibitors, three-dimensional quantitative structure–activity relationship (3D-QSAR) and molecular docking were performed on a total of 45 derivatives of pyrimidine. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques were used to generate 3D-QSAR models. CoMFA and CoMSIA were performed using the Sybyl X 2.0 package. Molecular docking analysis was performed using the Surflex-Dock module in SYBYL-X 2.0 package. We found in the CoMFA model that the non-cross-validated r2 value was 0.998, the cross-validated q 2 value was 0.663, and the F statistic value was 2,401.970, while the r2 value was 0.988; q 2 value was 0.730, and F value was 542.933 in CoMSIA models, suggesting the good predictability of the CoMFA and CoMSIA models. 3D contour maps and docking results suggested that different groups on the core parts of the compounds could enhance the biological activities. Based on these results, the established 3D-QSAR models and the binding structures of ALK inhibitors obtained favor the prediction of the activity of new inhibitors and will be helpful in the reasonable design of ALK inhibitors in the future.

Postmortem metabolic fingerprinting in death investigations

Explore the possibility of using postmortem metabolic fingerprinting for determine cause of death. We have previously demonstrated that the low-weight molecules present in a biological system after death has the potential to reflect the events leading up to death. That molecular overview (i.e. the postmortem metabolome) could potentially be used as a fingerprint useful in determining the cause of death. In Sweden, approximately five thousand forensic autopsies are carried out each year where approximately fifteen hundred cases have died either from drug intoxication ( n ≈800), strangulations by hanging ( n ≈500), pneumonia ( n ≈150) or acidosis ( n ≈50). The aim of this study was to investigate if our toxicological screening could be used to generate a postmortem metabolic fingerprint of autopsy cases that died either from drug intoxication, strangulation by hanging, pneumonia or acidosis. All autopsy cases handled at the Swedish National Board of Forensic Medicine between June 2017 and October 2020, in which the cause of death was opioid and benzodiazepine intoxications, hanging, pneumonia or acidosis, with a toxicological screening in femoral blood, with a BMI between 18,5–30 kg/m 2 , with an age between 30–65 years, were considered for this study. From each of the four causes of death, twenty-nine autopsy cases were randomly selected ( n = 116). The ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) data were processed using XCMS (R) and evaluated with principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). Three quarters of the samples ( n = 88) were used for model building while the remaining quarter ( n = 28) were used for external model validation. A simplified model was built with the most pronounced and significant chromatographic peaks. The chromatographic peaks were identified using the online databases METLIN and HMDB. For the training set, with 1355 chromatographic peaks as x-variables a full group separation was observed and with a 100% correct classification of intoxication, hanging, pneumonia and acidosis cases. The model had a R2 and Q2 value of 0.88 and 0.49 respectively, indicating that the model described the data well and that the model was reproducible. For the validation set, 82% of the samples were correctly classified. In a simplified model, only based on 20 chromatographic peaks (e.g. acylcarnitines, aminoacids, ketonbodies, polyethyleneglycols, steroid hormones), 72% of the cases in the validation set were correctly classified. This study demonstates that postmortem metabolic fingerprinting could potentially be used as a quick screening approach in search of plausible cause of death which could be a vital addition in death investigations. Further, several of the identified chromatographic peaks seemed to be biologically relevant. For example, increased levels of cortisone and decreased levels of LysoPC observed in the pneumonia cases could reflect the severity of illness and the prolonged agonal period expected in pneumonia cases in comparison to the other cases. Furthermore, decreased levels of acylcarnitines were observed in the intoxication cases which could reflect the respiratory function and the mitochondrial activity, being an indicator for respiratory depression. Postmortem metabolic fingerprints is a promising tool in death investigations, but more studies are needed to fully explore its potential.

Metabolic Signatures of Surface-Modified Poly(lactic-co-glycolic acid) Nanoparticles in Differentiated THP-1 Cells Derived with Liquid Chromatography-Mass Spectrometry-based Metabolomics.

Polymeric nanoparticles (NPs) are widely used in preclinical drug delivery investigations, and some formulations are now in the clinic. However, the detailed effects of many NPs at the subcellular level have not been fully investigated. In this study, we used differentiated THP-1 macrophage cells, as a model, to investigate the metabolic changes associated with the use of poly (lactic-co-glycolic acid) (PLGA) NPs with different surface coating or conjugation chemistries. Liquid chromatography-mass spectrometry-based metabolic profiling was performed on the extracts (n = 6) of the differentiated THP-1 cells treated with plain, Pluronic (F-127, F-68, and P-85)-coated and PEG–PLGA NPs and control (no treatment). Principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA) in conjunction with univariate and pathway analyses were performed to identify significantly changed metabolites and pathways related to exposure of the cells to NPs. OPLS-DA of each class in the study compared to the control showed clear separation and clustering with cross-validation values of R2 and Q2 > 0.5. A total of 105 metabolites and lipids were found to be significantly altered in the differentiated THP-1 cell profiles due to the NP exposure, whereas more than 20 metabolic pathways were found to be affected. These pathways included glycerophospholipid, sphingolipid, linoleic acid, arginine and proline, and alpha-linolenic acid metabolisms. PLGA NPs were found to perturb some amino acid metabolic pathways and altered membrane lipids to a different degree. The metabolic effect of the PLGA NPs on the cells were comparable to those caused by silver oxide NPs and other inorganic nanomaterials. However, PEG–PLGA NPs demonstrated a reduced impact on the cellular metabolism compared to Pluronic copolymer-coated PLGA and plain PLGA NPs.

Computational Investigations of Coumarin Derivatives as Cyclindependent Kinase 9 Inhibitors Using 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation.

Cyclin-dependent Kinase 9 as one of the serine/threonine protein kinases has become an important target for the treatment of cancer especially driven by transcriptional dysregulation. This thesis was conducted to elucidate the structure-activity relationship and interaction mode of coumarin compounds acting on CDK9. Three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics simulation were conducted to reveal the structural requirements for bioactivities. The 3D-QSAR model was constructed to find the features required for different substituents on the coumarin scaffold. Molecular docking and molecular dynamics simulation were employed to generate the binding mode and stability of CDK9. The Q2 and R2 values of the CoMFA model were calculated as 0.52 and 0.999, while those for the CoMSIA model were 0.606 and 0.998. It is believed that the significant statistical parameters of CoMFA and CoMSIA models revealed high activity-descriptor relationship efficiency. Therefore, we considered the 3D-QSAR model to be robust and accurate. The contour maps provided a deep structure-activity relationship and valuable clues for rational modification. Based on the contour maps, 4 novel CDK9 inhibitors which were predicted to have satisfactory pharmacokinetic characteristics were designed and exhibited better-predicted activities. Subsequently, molecular docking was employed to generate the binding mode of CDK9. Furthermore, 50 ns MD simulation was of great help in verifying the accuracy of docking results and the stability of the complexes. The study is a valuable insight for further research on novel and effective inhibitors targeting CDK9.

Impact of digitalization on the attractiveness of employee recruitment and retention in Moroccan companies

The relevant evolution of social networks and the expansion of digitalization has led to significant changes in the classical processes used by Moroccan companies in different fields such as marketing, human resources management, etc. This paper investigates the effects of digitalization on the attractiveness of Moroccan companies in terms of recruitment and safeguarding these constructs by using structural equation models according to the PLS approach. The study was carried out to touch 74 companies in different sectors. The study showed positive relationships between management support, digitalization, and recruitment performance (defined as the attractiveness of a company for recruitment and federalization of employees). The results show that the T-statistics are equal to 67.55, 6.862, and 5.941, respectively. The Q² value is 0.884 for scanning and 0.937 for performance, which means that the model is predictive in nature. The GoF is 1.388, which means that model is sufficiently large for the overall validity of the PLS model. While jobseeker behavior and competitive intensity did not affect recruitment performance because the test T-statistics is less than 1.64, the two factors have no moderating effect as the p-values are 0.228 and 0.082, respectively, exceeding the threshold of 0.05.

Pharmacophore Based Virtual Screening and Docking of Different Aryl Sulfonamide Derivatives of 5HT7R Antagonist

The selective blockade of 5HT7R (5-hydroxytryptamine 7 receptor) displays an antidepressant-like activity. It is a Gs-coupled receptor, which inactivates the adenyl cyclase enzyme or activates the potassium ion channel. Structural information of 5HT7 was obtained by homology modeling using MODELLER v.9.13. In the present study, pharmacophore-based virtual screening, molecular docking, and binding free energy calculations were performed on a series of antagonist aryl sulphonamide derivatives. A five-point pharmacophore hypothesis with two hydrogen bond acceptor (A), one hydrogen bond donor (D), one positive group (p), and one ring (R) was developed with acceptable R2 and Q2 values of 0.90 and 0.602, respectively. Eventually, common pharmacophore hypothesis-based screening was conducted against Asinex databases. Finally, binding free energy and dock score analysis was carried out for the top hits obtained from the docking process. All 14 hits from the database in this study had a satisfactory dock score and binding energy values within the best active compound range. H bond interaction with amino acid residues Ser212 and π-π stacking with Tyr249 were investigated for the best active molecule. Both are present in the top hits, including other interactions as well.

Demographic and clinical profile of RT-PCR confirmed severe acute respiratory syndrome coronavirus 2 patients of Chhindwara, Madhya Pradesh

Background - Globally, over 2.3 million people were infected with Severe Acute Respiratory Syndrome Coronavirus 2 worldwide leading to a global pandemic with mortality rates ranging from 1.4% and 5%. Clinical manifestations of Severe Acute Respiratory Syndrome Coronavirus 2 include asymptomatic carriers, mild upper respiratory tract infections, severe viral pneumonia, multiple organ failure, acute respiratory distress syndrome and death. The present study conducted to describe the demographic and clinical characteristics in RT-PCR confirmed Severe Acute Respiratory Syndrome Coronavirus 2 cases. Material and Methods - Between October 2020 to December 2020, 264 RTPCR confirmed Severe Acute Respiratory Syndrome Coronavirus 2 patients were analyzed for demographic and clinical characteristics.Throat and nasal swabs were collected for qualitative detection of nucleic acid. Results - Among 264 patients, mean age was 51.9 ± 15.9 standard deviation years, 72.34% were males, 65.53% patients admitted in isolation ward and 34.46% patients in ICU. The values of Q1, Q2, Q3 and Q4 were 56 (21.21%), 99 (37.5%), 86 (32.57%) and 23 (8.71%), respectively.Common symptoms were Cough 87 (33.0%), Breathlessness 69 (26.1%) and Fever 60 (22.7%). The highest fatality rate 16.5% was seen in age group of 61-75 years.Significant difference was found in deaths and age p value (0.001).

Non-equilibrium photons from the bottom-up thermalization scenario

In this work, I calculate the p⊥ resolved spectra for the three stages of the bottom-up scenario, which are comparable to the thermal contribution, particularly at higher values of the saturation scale Q2. Analytical solutions are obtained by including a parametrization of scaling solutions from far-from-equilibrium classical statistical lattice simulations into a small angle kinetic rate. Furthermore, a theoretically motivated ansatz is used to account for near-collinear enhancement of the low-p⊥ radiation. The system is phenomenologically constrained using the charged hadron multiplicities from LHC and RHIC as in previous parametric estimates and fair agreement with the data available for photons was found. I find that for this realistic set of parameters, the contribution from the pre-equilibrium dominates the excess photons.

A pragmatic pharmacophore informatics strategy to discover new potent inhibitors against pim-3

Pim-3 (proviral integration site moloney murine leukemia virus-3) is an oncogene which encodes proteins belonging to serine/threonine kinase family and PIM subfamily. It is generally over-expressed in epithelial and hematological tumors. It is known to involve in numerous cellular functions such as cell growth, differentiation, survival, tumorigenesis, and apoptosis. It also plays a crucial role in regulation of signal transduction cascades. Therefore, it emerged as a hopeful therapeutic target for cancer treatment. In the current study, indole derivatives having potent inhibitory activity against Pim-3 were taken and pharmacophore-based virtual screening was carried out. A 5-point pharmacophore hypothesis with one hydrogen bond acceptor, one hydrogen bond donor, and three aromatic rings, i.e., ADRRR, was developed with acceptable R2and Q2 values of 0.913 and 0.748, respectively. It was employed as a query and screening was conducted against Asinex and Otava lead library databases to screen out potent drug like candidates. The obtained compounds were subjected to SP, XP docking using 3D model of pim-3 which was constructed through comparative homology modelling, and finally binding free energies were calculated for top hits. The docking and binding free energy studies revealed that six hit molecules showed higher binding energy in comparison to the best active molecule. Finally, MD simulations of the top hit with the highest binding energy was carried out which indicated that the obtained hit N1 formed a stable complex with pim-3. We believe that these combined protocols will be helpful and cooperative to discover and design more potent pim-3 inhibitors in the near future.

Diagnostic test of dynamic computed tomography in early gastrointestinal lymphoma and precancerous lesions.

BackgroundIn recent years, with the development of imaging technology, the accurate diagnosis of precancerous lesions of digestive system and early lymphoma has attracted wide attention in the medical field.MethodsIn this study, 82 patients with gastrointestinal diseases, including 32 patients with early gastrointestinal lymphoma and 50 patients with gastrointestinal precancerous lesions, underwent dynamic contrast-enhanced computed tomography (CT) scanning. The difference (δ1, δ2) and ratio (Q1, Q2) of density between arterial phase, portal phase and plain scan were measured and compared, and the receiver operating characteristic (ROC) curve of the subjects was drawn.ResultsThe results showed no statistically significant differences in the general condition of patients or a difference for the results of the arterial phase δ1 and Q1 between the two groups (P>0.05). However, the portal venous phase δ2 and Q2 in the early lymphoma group and in precancerous lesion group were 29.50±6.05, 41.55±10.10 Hounsfield units (HU), and 1.70±0.05, 2.06±0.31, respectively. The area under the ROC curve (AUC) values for δ2 and Q2 to identify the two diseases were 0.755 and 0.878, respectively. When δ2 and Q2 were 35.63 and 1.86 HU, the specificity was 89.60% and 67.50%, and sensitivity was 89.60% and 64.90%, respectively. When the two indexes, δ2 and Q2, were combined, the specificity and sensitivity of diagnosis were 98.99% and 56.80%, respectively.ConclusionsDynamic contrast-enhanced CT can effectively distinguish early gastrointestinal lymphoma from precancerous lesions and improve the diagnostic accuracy.

Structural aspects of triazole derivatives as HSP90 inhibitors for the treatment of cancer: in silico studies

HSP90, one important class of chaperons has been intensively investigated as a promising and novel class of drug target for cancer therapy from the past few decades. A series of 2-((4-resorcinolyl)-5-aryl-1, 2, 3-triazol-1-yl) acetate derivatives were taken in the present study for the generation of pharmacophore based models, predictive 3 D-QSAR models, docking and ZINC screening studies against HSP90. The investigation included 30 ligands which emerged DHRRR_1 having survival score of 5.59 was found the most effective pharmacophore model. The generated third PLS factor includes a model with significant Q2, R2, and R2 CV values as 0.62, 0.77, and 0.50, respectively. The molecular docking studies against HSP90 showed interactions with important amino acids such as GLY-97, ASN-106, THR-184, ASN-51, PHE-138 and SER-52 required for HSP90 inhibitory activity. According to the docking analysis compound 34 was the top scoring compound, had a docking score of −10.98 from the series and showed interactions with amino acids likeASP-93, GLY-97, AND ASP-102. Using pharmacophore characteristics, the virtual screening investigation was carried out and DHRRR_1 showed the potential ZINC compounds. The ZINC compounds ZINC72417069 and ZINC77522480 showed best XP docking scores (-8.205 and −7.103 consecutively) and the top-scoring compound ZINC72417069 displayed amino acid binding affinity with GLY-97, ASN-106, and THR-184 against HSP90, PDB ID: 2xjx. These ZINC compounds can be used as target for HSP90. The result of the study may further help to the scientist for the design and development of potential HSP90 inhibitors.