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AbstractThe environmental impact of hydroxy- and amino-polysubstituted benzenes—constituents of natural and synthetic molecules of interest in food, pharmaceutical, and textile industries—demands new procedures for degradation of such pollutants, electrochemical oxidation being an important tool. Electrochemical studies have been performed to characterize these benzene derivatives by cyclic voltammetry (CV), differential pulse voltammetry (DPV), square wave voltammetry (SWV), and rotating disk electrode voltammetry (RDE). Their oxidation potential (EOX) has been measured by CV, DPV, and SWV. Linear correlations EOX vs. pH were established for the nondissociated forms of these compounds and good fitting was noticed for EOX vs. Hammett constant for the meta and para-substituted compounds. Diffusion coefficients were also estimated. According to the reversibility of their electrochemical oxidation, studied by CV, the compounds were classified into two main groups: reversible-type I (benzene-1,2-diol, benzene-1,4-diol, and benzene-1,2,4-triol) and irreversible-type II (benzene-1,3-diol, benzene-1,2,3-triol, benzene-1,3,5-triol, 4-aminophenol, benzene-1,4-diamine, and 3,4,5-trihydroxybenzoic acid). A quantitative structure–property relationship (QSPR) study has revealed the characteristics that influence their EOX values. A very good agreement resulted between the calculated and experimental EOX values. The proposed descriptors may be used in the prediction of EOX value for other related compounds. Thus, the optimal conditions for the degradation by electrochemical procedures of environmental pollutants containing such structures can be easily estimated.Graphic abstract

The characteristics of the proposed algorithm are (a) the use of a new formula for the quality of the QSPRs (b) the outlier (atypical) character is defined using a classic criterion (c) the condition for elimination of the outliers includes the quality of the equation (d) only ‘the most atypical’ molecule is eliminated and all calculations are automatically repeated (e) the elimination of outliers is stopped if the condition for elimination is not fulfilled or if the number of the eliminated molecules exceeds a predetermined limit. The second situation in (e) was encountered once in the four examples discussed. The number of descriptors in ‘the best’ equation and the number of outliers removed can not be a priori predicted. The text proposes also a criterion for the identification of ‘outliers for lead hopping’. There were no molecules of this type in the four examples discussed. The initial number of molecules in the calibration sets was 50, 60, 133 and 54 respectively, the number of descriptors in ‘the best’ equations was 5, 5, 9, and 9 respectively and the number of eliminated outliers was 0, 0, 8, and 6 respectively. If there were outliers, the best equation obtained in the presence of the outliers and the best equation obtained in the absence of outliers, were very different.

Regarding the molecular shape, shapes’ similarity and shapes’ diversity the paper presents (1) a new molecular descriptor, (2) using of the new descriptor together with the previous Ultrafast Shape Recognition (USR) formula, (3) a quantitative method to verify the observance of the ‘QSAR axiom’, (4) a formula for identification of the activity and shape ‘cliffs’, (5) a method to divide in classes any group of molecules, (6) a criterion to identify the ‘atypical’ molecules and (7) a method, based on Shannon entropy formula, for computation of the molecules’ diversity and the similarity of two groups of molecules. The proposed formulas/procedures are simple and suggestive. The algorithm which uses the proposed descriptor and USR formula describes correctly enough the molecular similarity in three analyzed groups of molecules.

We report a quantitative structure–property relationship (QSPR) study regarding LogP. The text includes some comments regarding the influence of diversity of molecules on results of QSPR computation. The calibration (training) set was selected, according to specific molecular diversity/similarity criteria, from certain group of 621 molecules, without oxygen and nitrogen atoms. The calibration set includes 211 molecules (hydrocarbons, halo-derivatives, thioethers, phosphines etc.) having much higher diversity from the point of view of chemical structure, size, shape and lipophilicity. The validation set includes the non-selected 410 molecules. The observed value of LogP is within (0.20, 9.14) range in calibration set and within (1.08, 9.36) range in prediction/validation set. The best QSPR multilinear formula includes three quantum mechanics descriptors and does not include molecular fragments’ descriptors. For calibration set, the predictive power of QSPR is high (r2 = 0.9489; SEE = 0.4117), close to KOWWIN (r2 = 0.9545; SEE = 0.3961) and miLogP (r2 = 0.9477; SEE = 0.4736) results. The predictor ‘conductor-like screening model area’ has largest influence on the value of LogP. The quality of prediction for validation set is good (r2 = 0.9517; SEE = 0.4334), close to result obtained by KOWWIN (r2 = 0.9676, SEE = 0.3286) and miLogP (r2 = 0.9612; SEE = 0.4776).

We report here: (a) formulas/procedures for calculating the similarity of molecules, considering their chemical structure, size, shape and hydrophilicity (b) a procedure for clusterization of the sets of molecules, according to similarity (c) formulas/procedures for calculating the diversity of molecules in clusterized sets as well as similarity of clusterized sets, based on Shannon Entropy formalism The paper analyses the influence of the diversity of molecules and similarity of calibration/prediction sets on the quality of prediction for prediction set molecules. The calculated influence of certain molecular feature (chemical structure, size, shape and hydrophilicity) on toxicity depends on the structure of the database, specifically the number of molecules and diversity of molecules having analyzed molecular feature. A QSAR analysis of 49 phenol derivatives revealed the effect of the diversity of molecules in sets and of the similarity of sets on the quality of prediction for prediction set molecules: (a) a direct correlation with the similarity of sets, regardless of analyzed molecular feature (b) an inverse correlation with the diversity of molecules in the calibration set, from the point of view of chemical structure, size and shape (c) a direct correlation with the diversity of molecules in calibration set, from the point of view of hydrophilicity (d) a direct correlation with the diversity of molecules in prediction set, regardless of analyzed feature.

The paper proposes a new manner to use application of Shannon Entropy in similarity computation for any objects and any objects groups. In computation of the chemical similarity cases the proposed formulas use the values of one or more molecular descriptors, divided into classes (categories) by using a suitable criterion. The paper proposes original criteria to made difference between ‘saturated’, ‘non-saturated non-aromatic’ and ‘aromatic’ molecular fragments and between ‘hydrogen-acceptor’ and ‘hydrogen-donor-acceptor’ fragments for the purpose of classifying fragments into classes. According to the proposed formula two molecules A and B are similar enough if the value of Shannon Entropy of A + B aggregate is close to the value of Shannon Entropy of A molecule and close to the value of Shannon Entropy of B molecule. The proposed similarity formula can be used as statistical correlation index, useful if the number of values of two analyzed variables is unequal. The proposed formula is useful in the quantitative evaluation of the ‘representative sample’ character of any ‘sample’. The paper presents the chemical similarity computation in Zimelidine/Fluoxtine/Chloramphenicol/Crufomate/Phoxim group. For comparison purposes, the paper also presents a Tanimoto coefficient calculation for the same molecules group. In addition, the paper presents two non-chemical examples regarding ‘Representative Sample Index’ calculation.

Azulene-containing chalcones have been synthesized via Claisen–Schmidt condensation reaction. Their chemical structure has been established by spectroscopic methods where the 1H-NMR spectra suggested that the title chalcones were geometrically pure and configured trans (J = 15 Hz). The influence of functional groups from azulene-containing chalcones on the biological activity of the 2-propen-1-one unit was investigated for the first time. This study presents optical and fluorescent investigations, QSAR studies, and biological activity of 10 novel compounds. These chalcones were evaluated for their antimicrobial activity against Gram-positive and Gram-negative bacteria. The results revealed that most of the synthesized compounds showed inhibition against Gram-negative microorganisms, independent of the substitution of azulene scaffold. Instead, all azulene-containing chalcones exhibited good antifungal activity against Candida parapsilosis, with MIC values ranging between 0.156 and 0.312 mg/mL. The most active compound was chalcone containing azulene moieties on both sides of the 2-propene-1-one bond, exhibiting good activity against both bacteria-type strains and good antifungal activity. This antifungal activity combined with low toxicity makes azulene-containing chalcones a new class of bioorganic compounds.

The paper presents some difficulties that appear in the application of the classical formula in the identification of “outliers” in a given objects set. The paper proposes a new Monte Carlo-like method for the identification of “outliers” in the calibration set used in QSPR/QSAR computations. Sub-sets of molecules are randomly extracted thousands of times from the given calibration set. The method relies on the idea that the presence of “outlier” molecules in a certain sub-set decreases the prediction power of the QSAR equation that used this particular sub-set of molecules. The presence of “outlier” molecules often leads to poor quality QSAR equations and rarely to high quality QSAR equations. The paper proposes a specific formula for “outlier index”. The molecule with the highest value of the outlier index is eliminated out of the calibration set. The identification/elimination process is repeated until the maximum value of the outlier index stops decreasing. The paper presents five examples of outliers’ identification using various kinds of calibration sets. We compare the results with the results obtained by a classical outlier index formula, using the same calibration set, the same set of descriptors and the same outlier identification/elimination procedure.

Quantitative structure aromaticity relationship studies on various aromatic, non-aromatic and anti-aromatic molecules are presented aiming for checking the predictor quality of finite-difference electronegativity and chemical hardness descriptors in aromaticity computations. The results show that the “aromaticity of peripheral topological path” may be well described by superior finite difference schemes of electronegativity and chemical hardness indices in certain calibrating conditions.

National and international research results have highlighted the fact that workplace stress causes mental and somatic problems. The aim of the present paper is to define exposure to workplace-related risk factors, with special focus on psychosocial risk factors, and the way they interconnect with workplace conditions, relationships with superiors and colleagues, and moral, professional and financial appreciation. Cross-sectional research with the help of an anonymous online self-administered questionnaire was carried out among 261 higher education employees (67% women, 33% men, mean age 43.4 years) from 12 faculties of the University of Szeged, Hungary. Statistical analysis was performed using IBM SPSS 22.0. The primary workplace stress factors for university employees were strict deadlines (80.4%), frequent overwork (64.2%) and difficulty in meeting requirements (56.7%). Communication problems with colleagues and superiors were also highlighted (47.5%). Job strain was higher for women than for men. With regard to low financial, professional, and moral appreciation, employees were characterised by the existence of work requirements impossible to meet, as well as by low autonomy. Experience of anxiety and aggression came along with low financial and moral appreciation (p<0.001). Our data suggests that employees at the university were subject to several psychosocial risk factors, and worked under considerable mental stress, leading to a higher prevalence of mental health problems. The results highlight the need for a health-focused policy-making in higher education to reduce health expenditure and increase efficiency at work.