Variable Important In Projection Research Articles

Untargeted Metabolomics Analysis of Gingival Tissue in Patients with Severe Periodontitis.

The purpose of this study was to determine potential metabolic biomarkers and therapeutic drugs in the gingival tissue of individuals with periodontitis. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) were used to analyze the gingival tissue samples from 20 patients with severe periodontitis and 20 healthy controls. Differential metabolites were identified using variable important in projection (VIP) values from the orthogonal partial least squares discrimination analysis (OPLS-DA) model and then verified for significance between groups using a two-tailed Student's t test. In total, 65 metabolites were enriched in 33 metabolic pathways, with 40 showing a significant increase and 25 expressing a significant decrease. In addition, it was found that patients with severe periodontitis have abnormalities in metabolic pathways, such as glucose metabolism, purine metabolism, amino acid metabolism, and so on. Furthermore, based on a multidimensional analysis, 12 different metabolites may be the potential biomarkers of severe periodontitis. The experiment's raw data have been uploaded to the MetaboLights database, and the project number is MTBLS8357. Moreover, osteogenesis differentiation characteristics were detected in the selected metabolites. The findings may provide a basis for the study of diagnostic biomarkers and therapeutic metabolites in severe periodontitis.

Anti-Rheumatoid Arthritis Pharmacodynamic Substances Screening of Periploca forrestii Schltr.: Component Analyses In Vitro and In Vivo Combined with Multi-Technical Metabolomics.

The purpose of this study was to elucidate the metabolic action patterns of P. forrestii against rheumatoid arthritis (RA) using metabolomics, and to obtain its potential effective substances for treating RA. First, the therapeutic effects of P. forrestii against RA were confirmed; second, the chemical composition of P. forrestii was analyzed, and 17 prototypes were absorbed into blood; subsequently, plasma metabolomics studies using UPLC-Triple-TOF-MS/MS and GC-MS were performed to disclose the metabolomics alterations in groups, which revealed 38 altered metabolites after drug intervention. These metabolites were all associated with the arthritis pathophysiology process (-log(p) > 1.6). Among them, sorted by variable important in projection (VIP), the metabolites affected (VIP ≥ 1.72) belonged to lipid metabolites. Finally, Pearson's analysis between endogenous metabolites and exogenous compounds was conducted to obtain potential pharmacological substances for the P. forrestii treatment of RA, which showed a high correlation between five blood-absorbed components and P. forrestii-regulated metabolites. This information provides a basis for the selection of metabolic action modes for P. forrestii clinical application dosage, and potential pharmacological substances that exerted anti-RA effects of P. forrestii were discovered. The study provided an experimental basis for further research on pharmacoequivalence, molecular mechanism validation, and even the development of new dosage forms in the future.

Discrimination of Filter Coffee Extraction Methods of a Medium Roasted Specialty Coffee Based on Volatile Profiles and Sensorial Traits.

An untargeted gas chromatography-mass spectrometry (GC-MS) approach combined with sensory analysis was used to present the effects of different extraction methods (i.e., Pure Brew, V60, AeroPress, and French Press) on specialty graded Coffea arabica from Kenya. Partial Least Square Discriminant analysis and hierarchical clustering were applied as multivariate statistical tools in data analysis. The results showed good discrimination and a clear clustering of the groups of samples based on their volatile profiles. Similarities were found related to the filter material and shape used for the extraction. Samples extracted with paper filters (V60 and AeroPress) resulted in higher percentages of caramel-, and flowery-related compounds, while from metal filter samples (Pure Brew and French Press), more fruity and roasted coffees were obtained. Discriminant analysis allowed the identification of eight compounds with a high VIP (variable important in projection) discriminant value (i.e., >1), with 2-furanmethanol being the main feature in discrimination. Sensorial analyses were carried out through an expert panel test. The main evaluations revealed the French Press system as the lowest-scored sample in all the evaluated parameters, except for acidity, where its score was similar to V60. In conclusion, the data obtained from GC-MS analyses were in line with the sensorial results, confirming that the extraction process plays a fundamental role in the flavor profile of filter coffee beverages.

Comprehensive Evaluation of Quality Characteristics of Four Oil-Tea Camellia Species with Red Flowers and Large Fruit.

Red-flowered oil-tea camellia (ROC) is an important woody oil species growing in the south, and its oil has high nutritional value. There are four main species of ROC in China, namely, Camellia chekiangoleosa (CCH), Camellia polyodonta (CPO), Camellia semiserrata (CSE) and Camellia reticulata (CRE). Reports on the comprehensive comparative analysis of ROC are limited. This study investigated the fruit characteristics and nutritional components of four ROC fruits, and the results showed that ROC had high oil content with levels of 39.13%-58.84%, especially the CCH fruit, which reached 53.6-58.84%. The contents of lipid concomitants of ROC oil were also substantial, including β-amyrin (0.87 mg/g-1.41 mg/g), squalene (0.43 mg/g-0.69 mg/g), β-sitosterin (0.47 mg/g-0.63 mg/g) and α-tocopherol (177.52 μg/g-352.27 μg/g). Moreover, the transverse diameter(TD)/longitudinal diameter (LD) of fruits showed a significant positive correlation with the oil content, and ROC fruits with thinner peels seemed to have better oil quality, which is similar to the result of the oil quality evaluation obtained by the gray correlation coefficient evaluation method. Four ROC oils were evaluated using the gray correlation coefficient method based on 11 indicators related to the nutritional value of ROC. CCH oil had the highest score of 0.8365, and YS-2 (a clone of CCH) was further evaluated as the best CCH oil. Finally, the results of heatmap analysis showed that triglycerides could be used as a characteristic substance to distinguish CCH oil from the other three ROC oils. The PLSDA (Partial least squares regression analysis) model and VIP (Variable important in projection) values further showed that P/S/O, P/O/O, P/L/L, P/L/Ln, S/S/O, S/O/O and P/S/S (these all represent abbreviations for fatty acids) could be used as characteristic differential triglycerides among the four ROC oils. This study provides a convenient way for planters to assess the nutritional quality of seed oil depending on fruit morphology and a potential way to distinguish between various ROC oils.

Metabolomics analysis reveals how water extract of Gastrodia elata helps against heroin addiction

To investigate the metabolomics changes and potential metabolic mechanisms of water extract of Gastrodia elata (WGE) in the treatment of heroin addicted mice. Sixty male Kunming mice were randomly divided into four groups as control group (n = 10), heroin addicted group (n = 10), natural withdrawal group (n = 10), and GE treatment group (500, 1000, 2000 mg/kg, n = 30). Heroin addicted group were injected subcutaneously in the 13 days with increased dosage from 3 mg/kg to 30 mg/kg. The control group was injected with the same amount of saline in the same manner. After 13 days of heroin administration, the treatment groups were given GE by gavage for a week. The natural withdrawal group was injected with the same amount of saline in the same manner. The metabolites were determined using ultra performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS). The scatting diagrams were plotted based on orthogonal partial least squares discrimination analysis (OPLS-DA). Potential differential metabolites were obtained using the combination of variable important in projection (VIP) and p value methods. Their metabolic pathways were analyzed using databases such as METLIN, HMDB, KEGG and metaboanalyst 5.0. The GE treatment group (500 mg/kg) could significantly reduce the withdrawal symptoms induced by heroin addiction and significantly improve the weight loss of heroin addicted mice. The metabolomics results showed that GE could regulate the levels of 30 different metabolites in heroin addicted mice, which mainly involved in the metabolism of Glutamic acid, Glutathione and Purine. The water extract of Gastrodia elata in the treatment of heroin addiction was confirmed for the first time in this study. The metabolomics analysis demonstrated that the metabolic disorder of endogenous substances changes from pretreatment to posttreatment. The potential biomarkers of brain damage may be feasible to elucidate its metabolic mechanisms.

Effects and evaluation of different processing and drying methods on components in Paeoniae Radix Alba

The present study evaluates different processing and drying methods and investigates their effects on the chemical components in Paeoniae Radix Alba via content determination. The fresh medicinal materials of Paeoniae Radix Alba collected from Bozhou of Anhui province were processed(boiled and peeled) and dried(hot air-dried, infrared-dried, and microwave-dried) at different temperatures(40, 50, 60 and 70 ℃), and the 11 components(monoterpene glycosides, polyphenols, tannin, and benzoic acid) in Paeoniae Radix Alba were determined by ultra-performance liquid chromatography coupled to triple quadrupole with electrospray tandem mass spectrometry(UPLC-TQ-MS). Then the compounds in processed and dried samples were analyzed by partial least squares discriminant analysis(PLS-DA) and orthogonal partial least squares discriminant analysis(OPLS-DA), and the contribution rates of differential components were evaluated by variable important in projection(VIP). The results indicated that the samples obtained by different processing and drying methods could be distinguished. Albiflorin, gallic acid, 1,2,3,4,6-pentakis-O-galloyl-β-D-glucose, and benzoic acid were the common differential components in boiled Paeoniae Radix Alba. Benzoic acid was the common differential component in peeled Paeoniae Radix Alba. Gallic acid was the common differential component in Paeoniae Radix Alba dried by different methods. The samples could not be distinguished after drying at different temperatures due to the lack of common differential components. This study is expected to provide a reference for the selection of processing and drying methods and the optimization of processing parameters.

Plasma metabolomics in perioperative period of defect repair in patients with pulmonary arterial hypertension associated with congenital heart disease

Abstract Background The pathophysiological alterations in response to shunt correction in patients with pulmonary arterial hypertension associated with congenital heart disease (CHD-PAH) is still not clear. Purpose To explore the dynamic plasma metabolite profiling and its relationship with clinical characteristics in patients with CHD-PAH during the perioperative period of defect repair. Methods Plasma samples from 13 patients with CHD-PAH were harvested at four time points: before cardiopulmonary bypass (CPB) after anesthesia (Pre), immediately after CPB (T0), 24 h (T24), and 48 h (T48) after defect repair. The untargeted metabolomics strategy based on UPLC Q-TOF MS was used to detect the metabolites. Clinical measures were recorded at indicated time points. Results The sample distribution at four time points was well separated (Figure 1A, B). 193 metabolites were distinguished at different time points according to Variable Important in Projection (VIP) score (Figure 1C), enriched in pathways such as carnitine synthesis, phospholipid biosynthesis and oxidation of branched chain fatty acids (Figure 2A). 17 metabolites alterations were significantly correlated with gradients in mean pulmonary arterial pressure (mPAP) at T48 versus Pre, indicative of the response to defect correction (Figure 2B). Intriguingly, 4 out of the 17 (23.5%) metabolites including propionylcarnitine, butenylcarnitine, isobutyryl-L-carnitine and hexanoylcarnitine were enriched in oxidation of branched chain fatty acids. They were increased at both T24 and T48 (all P<0.05 except propionylcarnitine with P<0.05 at T24) (Figure 2C). Conclusions This is the first study to show the altered metabolic profiles of CHD-PAH patients in perioperative period of defect repair. Metabolites that respond to shunt correction could be a suitable non-invasive marker and would be of great value in disease monitoring and evaluating future therapeutic interventions. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): 13th Five-Year Plan–Precise Medicine–Key Research and Development Program–Clinical Cohort of Rare Disease; National Natural Science Foundation of China Figure 1. Overall analysis of metabolitesFigure 2. Shunt correction associated metabolites

Metabolic profiling of serum from dogs with pituitary-dependent hyperadrenocorticism

Hyperadrenocorticism (HAC) is one of the most common endocrine diseases in dogs characterized by excessive cortisol production caused by an adrenocorticotropic hormone (ACTH)-secreting tumor, namely pituitary-dependent HAC (PDH) or cortisol-secreting adrenal tumor. Metabolomics presents the ability to identify small molecule metabolites. Thus, the use of metabolomics techniques in canine PDH can provide information about the pathophysiology and metabolic changes in this disease. This study aimed to identify and compare differences in serum metabolites between dogs with PDH and healthy dogs. The metabolomic profile of 20 dogs diagnosed with PDH was compared with 20 healthy dogs using liquid chromatography/mass spectrometry (LC/MS), and metabolite discrimination was performed using partial least squares-discriminant analysis (PLS-DA), the variable important in projection (VIP) and fold changes (FC) group-wise comparisons. The hypergeometric test identified the significantly altered pathways. A total of 21 metabolites were found to be significantly different between the two groups. The major alterations were found in arachidonic and decanoic acid, and phospholipids related to phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidylinositol (PI). These metabolites are related to insulin resistance and other complications (i.e. hypertension). Our results indicate that PDH produces changes in serum metabolites of dogs, and the knowledge of these changes can aid to better understanding of pathophysiological processes involved and contribute to potentially detect new biomarkers for this disease.

Untargeted metabolomic analysis of serum samples from children with mycoplasma pneumonia in a hospital in Beijing

Objective: This study was aimed to analyze the untargeted metabolomics of serum samples from children with mycoplasma pneumonia in a hospital in Beijing. Methods: A total of 50 children with mycoplasma pneumonia as the case group were recruited from Department of Pediatrics, China-Japan Friendship Hospital in Beijing from January 2019 to February 2020, and meanwhile 50 age-and gender-matched heathy children were selected and formed the control group. 2 ml venous fasting blood samples was collected from all children. Serum metabolites were quantified by using the untargeted ultra-high performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) technique. Unsupervised principle component analysis and (orthogonal) partial least-squares-discriminant analysis were employed to identify differential metabolites between cases and controls. MBRole software was used for pathway enrichment analysis. Results: There were 27 boys and 23 girls in the case group with an average age of (6.0±3.65) years, and the control group consisted of 28 boys and 22 girls with an average age of (6.62±2.64) years. A total of 392 different metabolites were detected. Compared with the control group, 306 metabolites were decreased and 86 increased in case group. Forty-one differential metabolites with variable important in projection (VIP) values larger than 5 and P values less than 0.05 were teased out, and they mainly concentrated on phospholipid. The levels of 38 metabolites were significantly lower in the case group, yet 4 metabolites were significantly higher than that of the control group. Metabolic enrichment analysis showed that different metabolites were related to the biosynthesis of phenylalanine, tyrosine, tryptophan, unsaturated fatty acid, ammonia acyl tRNA and insulin signaling pathway, as well as the metabolism of ABC transporters. Conclusion: The serum untargeted metabolomics differed remarkably between children with mycoplasma pneumonia and healthy children.

Comparative physiology and transcriptome response patterns in cold-tolerant and cold-sensitive varieties of Zanthoxylum bungeanum Maxim

Zanthoxylum bungeanum is an economically important tree species of edible, medicinal, and ornamental value. The trees grow in varied climates from tropical to subtropical regions owing to their high resistance to adverse environment. The unstable environmental temperature is one of the important factors affecting the yield and quality of Z. bungeanum. To investigate complex responses to cold stress in Z. bungeanum, we compared cold-tolerant “Fuguhuajiao” (FG) and cold-sensitive “Fengxiandahongpao” (FX) varieties. Physiological measurements and transcriptome sequencing were performed using plant leaves collected at six different timepoints (0, 1, 3, 6, 12, and 24 h) of 4 °C treatment. Chemometrics analysis showed that the physiological cold response in FX at late stage was similar to that in FG at early stage. Based on orthogonal partial least squares discriminant analysis (OPLS-DA), the variable important in projection (VIP) values of peroxidase (POD) and soluble protein were 1.11 and 1.41, which were identified as important physiological indices in the two varieties. Under low temperature stress, there were 3513 differentially expressed genes in FG and 25,157 in FX. Weighted gene co-expression network analysis (WGCNA) revealed that many cold-response genes and pathways were enriched in the MEfirebrick4 module which had a high correlation with POD. Hub genes identified in this module indicated that Z. bungeanum can respond and adapt to cold stress by altering signal transduction, plant hormones, transcription factors, protein modification, functional proteins, metabolism, cell structure, light response, and the circadian clock. Endocytosis-related gene ERD7, abscisic acid pathway-related gene PP2C, late embryogenesis abundant gene LEA D-29, and two plasma membrane/lipid raft-associated remorin genes ZB01477 and pp34 are located at the core of the network, and all play pivotal roles in cold responses. These results of this study highlight cold response mechanisms at the physiological and molecular levels in Z. bungeanum and will contribute to a better understanding of low temperature resistance in related plants.

Hyperspectral imaging coupled with multivariate methods for seed vitality estimation and forecast for Quercus variabilis.

In this study, the feasibility of estimation and forecast of different vitality Quercus variabilis seeds by a hyperspectral imaging technique were investigated. Artificially accelerated aging was conducive to achieve the division of four vitality levels. Hyperspectral data in the first 10h of germination were continuously collected at one-hour intervals. The optimal band was selected for the original and pre-processed spectra which were treated by multiple scatter correction (MSC) and the Savitzky-Golay first derivative (SG 1st). Five characteristic wavelength methods were compared: successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), genetic algorithm (GA), variable important in projection (VIP), and random frog (RF). Partial least square-discriminant analysis (PLS-DA) and K-nearest neighbor (KNN) built the vitality estimation model based on different data sets, and GA+PLS-DA constructed the optimal model with the highest accuracy. According to the weight coefficient and reflectance of the characteristic band extracted by the GA, the reflectance curves of different levels over time were plotted. The data of 0h was employed to establish the vitality forecast model. The forecast model had a high recognition rate, with PLS-DA exceeding 99% and KNN exceeding 85%. This indicated that hyperspectral imaging of seed germination processes could achieve non-destructive estimation of Q. variabilis seed vitality, and accurate prediction in a shorter time is feasible.

Metabolic Profiling of Pleurotus tuoliensis During Mycelium Physiological Maturation and Exploration on a Potential Indicator of Mycelial Maturation

Pleurotus tuoliensis is a valuable and rare edible fungus with extremely high nutritional and medicinal value. However, the relative immaturity of P. tuoliensis cultivation technology leads to fluctuating yields and quality. The main difficulty in P. tuoliensis cultivation is estimate of mycelial maturity. There is currently no measurable indicator that clearly characterizes the physiological maturation of mycelia. The aim of this study was to identify potential indicators of physiological maturation for P. tuoliensis mycelia by using metabolomics approach. A metabolite profiling strategy involving gas chromatography-mass spectrometry (GC/MS) was used to analyze changes to extracellular metabolites in mycelia collected at mycelium physiological maturation period (MPMP) day 0, MPMP day 35 at 17°C and MPMP day 35 at 29°C. 72 differential metabolites (37.8% up-regulated and 62.2% down-regulated) were identified based on the selected criteria [variable important in projection (VIP) greater than 1.0 and p < 0.01]. Metabolic pathways enrichment analysis showed that these metabolites are involved in glycolysis, organic acid metabolism, amino acid metabolism, tricarboxylic acid cycle (TCA), sugar metabolism, nicotinate and nicotinamide metabolism, and oxidative phosphorylation. In addition, the pyrimidine synthesis pathway was significantly activated during mycelium physiological maturation of P. tuoliensis. The abundance of N-carbamoyl-L-aspartate (CA-asp), a component of this pathway, was significantly increased at MPMP day 35, which motivated us to explore its potential as an indicator for physiological maturation of mycelia. The content of CA-asp in mycelia changed in a consistent manner during physiological maturation. The feasibility of using CA-asp as an indicator for mycelial maturation requires further investigation.

Analysis and evaluation of chemically induced artificial agarwood

In this study,the content of ethanol extraction of agarwood were performed following the method of Chinese Pharmacopoeia(ChP 2015 edition). The chromatographic fingerprints were established by GC-MS. Similarity Evaluation System for Chromatographic Fingerprint of traditional Chinese medicine（TCM）(version 2012) was employed to calculate the similarity of each chromatogram of agarwood. The ratios of sum peak area in the range of 170-270 min and 0-100 min of individual chromatogram were calculated using square peaks to normalization. AMDIS and RI were employed to identify the common and different peaks. Correlation coefficient P(corr) combined with Variable important in projection(VIP) value was employed to screen the different representative components based on OPLS-DA analysis. Grey related degree and TOPSIS were used to evaluate the quality of artificial agarwoods. The results showed that more than 10.0% of the ethanol extract content was found in 15 batches of artificial agarwoods among the total 18. The similarity of 18 batches artificial agarwoods was 0.439-0.779. The peak area ratios of two intervals were in the range of 0.307-13.254. The 9 common components and 8 different components were identified. Meanwhile, 2% salicylic acid is the best inducer based on grey related degree and TOPSIS. Grey related degree and TOPSIS can be used to evaluate the quality of artificial agarwoods rapidly. These results provide a reference data to evaluate the qualityof artificial agarwood.

Near-infrared hyperspectral imaging system coupled with multivariate methods to predict viability and vigor in muskmelon seeds

A near-infrared (NIR) hyperspectral imaging (HSI) system was used to predict viability and vigor (in term of germination periods) in muskmelon seeds. Hyperspectral images of muskmelon seeds were acquired using a NIR push-broom HSI system covering the spectral range of 948–2494nm. After NIR spectra collection, all seeds underwent a germination test to confirm their viability and vigor. The spectra from seeds with 3 and 5 germination days and nongerminated seeds were further used for development of a classification model of partial least-squares discriminant analysis (PLSDA). Most effective wavelengths were selected using three model-based variable selection methods, i.e., variable important in projection (VIP), selectivity ratio (SR), and significance multivariate correlation (sMC), which selected 23, 18, and 19 optimal variables, respectively, from full set of 208 variables. The selected variables from different waveband selection methods were found genuine and significant for interpreting the prediction results of seed viability and vigor. Subsequently, the PLS-DA model was constructed using individual VIP-, SR-, or sMC-selected variables. The results demonstrated that the PLSDA model developed with the selected optimal variables from the different methods provided comparable results for the calibration set; however, the PLSDA-SR method afforded the highest classification accuracy (94.6%) for a validation set used to determine the viability and vigor of muskmelon seeds. The wavelengths selected by the different methods represents chemical components of the seed and the attribute of germination ability was chosen most often.

Investigation of faecal volatile organic metabolites as novel diagnostic biomarkers in inflammatory bowel disease

The aetiology of inflammatory bowel disease (IBD) remains poorly understood. Recent evidence suggests an important role of gut microbial dysbiosis in IBD, and this may be associated with changes in faecal volatile organic metabolites (VOMs). To describe the changes in the faecal VOMs of patients with IBD and establish their diagnostic potential as non-invasive biomarkers. Faecal samples were obtained from 117 people with Crohn's disease (CD), 100 with ulcerative colitis (UC), and 109 healthy controls. Faecal VOMs were extracted using solid-phase micro-extraction and analysed by gas chromatography mass spectrometry. Data analysis was carried out using partial least squares-discriminate analysis (PLS-DA) to determine class membership based on distinct metabolomic profiles. The PLS-DA model showed clear separation of active CD from inactive disease and healthy controls (P < 0.001). Heptanal, 1-octen-3-ol, 2-piperidinone and 6-methyl-2-heptanone were up-regulated in the active CD group [variable important in projection (VIP) score 2.8, 2.7, 2.6 and 2.4, respectively], while methanethiol, 3-methyl-phenol, short-chain fatty acids and ester derivatives were found to be less abundant (VIP score of 3.5, 2.6, 1.5 and 1.2, respectively). The PLS-DA model also separated patients with small bowel CD from healthy controls and those with colonic CD from UC (P < 0.001). In contrast, less distinct separation was observed between active UC, inactive UC and healthy controls. Analysis of faecal volatile organic metabolites can provide an understanding of gut metabolomic changes in IBD. It has the potential to provide a non-invasive means of diagnosing IBD, and can differentiate between UC and CD.

Modeling calcium channel antagonistic activity of dihydropyridine derivatives using QTMS indices analyzed by GA-PLS and PC-GA-PLS

The usefulness of a novel type of electronic descriptors called quantum topological molecular similarity (QTMS) indices for describing the quantitative effects of molecular electronic environments on the antagonistic activity of some dihydropyridine (DHP) derivatives has been evaluated. QTMS theory produces a matrix of descriptors, including bond (or structure) information in one dimension and electronic effects in another dimension, for each molecule. Some different modeling tools such as multiple linear regression (MLR), principal component analysis (PCA), partial least squares (PLS) and genetic algorithms (GA) were employed to find some appropriate models for noted biological activity. GA was used in order to select the proper variables and also PCA was used for data compression. Then modeling was performed by MLR and PLS. The model performances were accessed by both cross-validation and external prediction set. The results showed that the proposed models could explain above 90% of variances in the biological activity. The significant effects of chemical bonds on the antagonistic activity were identified by calculating variable important in projection (VIP). It was obtained that those belonging to the substituted 4-phenyl ring represent high influence on the biological activity which, confirms their importance in mechanism of action of DHP derivatives.

Application of quantum topological molecular similarity descriptors in QSPR study of the O‐methylation of substituted phenols

The usefulness of a novel type of electronic descriptors called quantum topological molecular similarity (QTMS) indices for describing the quantitative effects of molecular electronic environments on the O-methylation kinetic of substituted phenols has been investigated. QTMS theory produces for each molecule a matrix of descriptors, containing bond (or structure) information in one dimension and electronic effects in another dimension, instead of other methods producing a vector of descriptors for each molecule. A collection of chemometrics tools including principal component analysis (PCA), partial least squares (PLS), and genetic algorithms (GA) were used to model the structure-kinetic data. PCA separated the bond and descriptor effects, and PLS modeled the effects of these parameters on the rate constant data, and GA selected the most relevant subset of variables. The model performances were validated by both cross-validation and external validation. The results indicated that the proposed models could explain about 95% of variances in the rate constant data. The significant effects of variables on the reaction kinetic were identified by calculating variable important in projection (VIP). It was found that the rate constant of esterification of phenols is highly influenced by the electronic properties of the C2--C1--O--H fragment of the parent molecule. Indeed, the C2--X and C4--X bonds (corresponding to ortho and para substituents) were found as highly influential parameters. All of the eight calculated QTMS indices were found significant however, lambda1, lambda2, lambda3, epsilon, and K(r) were detected as highly influential parameters.