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Quantitative structure–activity relationship study on prolonged anticonvulsant activity of terpene derivatives in pentylenetetrazole test

  • Mariia Nesterkina EMAIL logo , Viacheslav Muratov , Luidmyla Ognichenko , Iryna Kravchenko and Victor Kuz’min
Published/Copyright: December 10, 2021
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Open Chemistry
From the journal Open Chemistry Volume 19 Issue 1

Abstract

Quantitative structure–activity relationship (QSAR) study has been conducted on 36 terpene derivatives with anticonvulsant activity in timed pentylenetetrazole (PTZ) infusion test. QSAR models for anticonvulsant activity prediction of hydrazones and esters of some monocyclic/bicyclic terpenoids were developed using simplex representation of molecular structure (SiRMS; informational field [IF]) approach based on the SiRMS and the IF of molecule. Four 2D partial least squares QSAR consensus models were developed with the coefficient of determination for test sets R test 2 > 0.62 . Based on the established QSAR models, we found that carvone and verbenone cores possess the most significant contribution to antiseizure action examined on the model of PTZ-induced convulsions at 3 and 24 h after oral administration of terpene derivatives. Moreover, carbonyl and hydroxy group substitution in terpenoid molecules followed by hydrazones and esters formation leads to enhancement and prolongation of antiseizure action due to the contribution of additional molecular fragments. The presented QSAR models might be utilized to predict anticonvulsant effect among terpene derivatives for their oral administration against onset seizures.

Keywords: QSAR models; terpenes; anticonvulsant activity; SiRMS approach

1 Introduction

The field of drug investigation aimed at seizure prevention during epilepsy has become a cornerstone in medicinal chemistry due to the limitations of existing antiepileptic medications such as ineffectiveness or various side effects: diplopia, dizziness, ataxia, sedation, and so on [1]. In this context, particular attention is paid on natural biologically active substances including glycosides, coumarins, flavonoids, alkaloids, and terpenoids that have limited or no toxic side effects [2]. The latter compounds were found to positively modulate human recombinant γ-aminobutyric acid type A receptors (GABAA) receptors or activate glutamic acid decarboxylase enzyme (a key enzyme in the biosynthesis of GABA) confirming terpenoids' potential for the treatment of epilepsy and seizures [3]. To enhance anticonvulsant properties, terpenes/terpenoids were synthetically converted to miscellaneous derivatives comprising hydrazones [4,5,6], epoxides [7], and esters [8,9]. The main concept of modification consists in pharmacophore fragments introduction into the molecule leading to increased bonding to receptors. In contrast, the labile bonds of the aforementioned compounds undergo hydrolytic cleavage both in vitro and in vivo followed by the release of active ingredients [10].

To date, the creation of a new medicine costs more than 1 billion dollars and the costs of this process are growing up steadily [11]. Therefore, different theoretical approaches are used for a facilitation and acceleration of a new drugs development process that is very expensive, multistep, and prolonged [12]. To this end, quantitative structure–activity relationship (QSAR) analysis is widely applied for virtual screening of potential bioactive compounds followed by their structure optimization. QSAR methods allow discovering correlation between numerical physicochemical property or molecular feature of compounds and their biological or pharmacological activity [13]. The present study is a logical continuation of our current research devoted to the QSAR analysis for a number of terpene derivatives [14]. The goal of our study is to develop predictive QSAR models for anticonvulsant activity assessment of terpenoids and their derivatives.

2 Materials and methods

The data set consisting of 36 terpene derivatives was used in the current study: hydrazones of menthone, carvone, and verbenone and esters of menthol, thymol, carvacrol, borneol, eugenol, and guaiacol. Minimum effective doses (MEDs) of convulsant pentylenetetrazole (PTZ) that induce clonic–tonic convulsions (DCTC) and tonic extension (dose inducing tonic extension [DTE]) in experimental animals have been registered and used as properties. Anticonvulsant activity of terpene derivatives was estimated at different time points – 3 and 24 h after oral administration according to the described procedure [15]. Thus, four data sets were formed: two of which contain information on PTZ MED causing clonic–tonic seizures determined after 3 and 24 h, DCTC (3 h) and DCTC (24 h), and the other two with data on PTZ MED causing tonic extension, DTE (3 h) and DTE (24 h), respectively.

For all the investigated compounds, the structural descriptors were calculated using the simplex representation of molecular structure (SiRMS; informational field [IF]) approach [16]. QSAR methods on the basis of SiRMS [17,18] along with the IF of molecule [19] already demonstrated their efficiency when dealing with variety of QSAR tasks. Two different methods are united in the system of structural parameters resulting in system (SiRMS (IF)) that exhibits versatility of simplex approach along with sensitivity to the structural features within the scope of IF. Through the use of SiRMS (IF) approach, simplex vertexes might be better differentiated since informational potential (IP) vary according to the impact of near and far surroundings. In SiRMS (IF), the IF characteristics are applied for atom’s differentiation in simplexes. Notably, the potentials of the aforementioned IFs weighed by different atomic properties (charge, lipophilicity, electronic polarizability, etc.) might be exploited.

In this study, SiRMS (IF) approach has been applied for the representation of molecular structure at 2D level. According to this model, each molecule can be represented in the form of molecular graph. The vertices of such a graph provide a whole range of information which spreads only on the graph edges. Noteworthy, all potential bindings between every atom pair are recognized:

The topological IP of ith atom can be described as [16]

IP i = w i ⋅ ∑ j = 1 n ∑ m lb r 2 R i j + 1 m ,

where m is the number of all possible paths between every atom pair, n is the number of atoms in the given molecule, R ij is the number of bonds between the ith and jth atoms (path length), w i is the weighed parameters describing any property (p) of the atoms (w i  = 1 in the case of unweighted IP), and r is the tuning parameter of the model, w i = p i / ∑ i = 1 n p i .

The example of simplex differentiation on the basis of atomic topologic IP for alanine at 2D level is shown in Figure 1.

Figure 1 Example of simplex descriptor generation using atomic topological IPs for alanine at 2D level.
Figure 1

Example of simplex descriptor generation using atomic topological IPs for alanine at 2D level.

For the weighed molecular topological IPs in the preliminary stage, the range of all possible values is divided into a certain number of discrete groups. The number of groups is a tuning parameter. The label of an atom is determined from the point of view of its belonging to a particular group. The following schemes were used in the calculation of simplex-informational descriptors:

Unweighted topological IP: A < 3.45 ≤ B < 3.84 ≤ C  < 4.22 ≤ D < 4.60 ≤ E < 4.99 ≤ F < 5.37 ≤ G.

Topological IP weighed by electronegativity: A <  3.51 ≤ B < 3.89 ≤ C < 4.27 ≤ D < 4.65 ≤ E < 5.03 ≤  F < 5.41 ≤ G.

Topological IP weighed by refraction: A < 3.65 ≤ B <  4.02 ≤ C < 4.38 ≤ D < 4.75 ≤ E < 5.12 ≤ F < 5.49 ≤ G.

Topological IP weighed by atomic charge: A <  −0.51 ≤ B < −0.38 ≤ C < −0.26 ≤ D < −0.13 ≤ E <  0 ≤ F < 0.12 ≤ G.

Topological IP weighed by van der Waals radius: A < 3.75 ≤ B < 4.11 ≤ C < 4.47 ≤ D < 4.83 ≤ E < 5.2 ≤  F < 5.56 ≤ G.

Topological IP weighed by lipophilicity: A < 0.58  ≤ B < 1.32 ≤ C < 2.06 ≤ D < 2.81 ≤ E < 3.55 ≤ F < 4.29 ≤ G.

A total of 2,374 simplex-informational descriptors were calculated for the investigated molecules. log P (I.log P), molecular refraction (I.RF), equalized electronegativity (I.EN), and molecular mass (I.AW) were used as trivial integral parameters of the molecules [17,18]. The relationships between calculated descriptors and investigated properties were established with common method of partial least squares (PLS) [20]. The removal of highly correlated and constant descriptors, the trend vector method [21], genetic algorithm [22], and the automatic variable selection strategy [18] have all been used to select the descriptors in PLS. Structures of monocyclic/bicyclic terpenoids and their derivatives used in this study and corresponding values of their anticonvulsant activity are collected in Table 1.

Table 1

Structures and anticonvulsant activities of terpenes and their derivatives

Structure Core R i 3 h 24 h
DCTC (%) DTE (%) DCTC (%) DTE (%)
A R1 157 197 166 176
R2 171 182 191 205
R3 223 261 200 224
R4 177 203 177 189
R5 189 232 166 182
R6 174 179 169 182
B R1 196 200 130 138
R2 193 204 240 220
R3 267 269 204 204
R4 227 246 204 208
R5 221 233 209 227
R6 196 204 204 212
C R1 179 180 130 138
R2 218 212 240 220
R3 278 303 204 204
R4 207 235 204 208
R5 216 230 209 227
R6 160 162 204 212
D R7 167 186 167 189
R8 162 192 162 194
R9 152 186 167 189
E R7 213 181 214 183
R8 207 190 208 189
R9 198 144 198 132
F R7 197 142 197 127
R8 235 155 226 152
R9 154 136 144 133
G R7 186 157 179 147
R8 214 207 203 203
R9 183 114 186 108
H R7 190 207 183 208
R8 242 161 267 171
R9 217 165 217 158
I R7 240 156 241 155
R8 210 156 212 159
R9 168 168 159 176

Note: R1: O; R2–R6: X = H (R2); Br (R3); Cl (R4); C(CH3)3 (R5); O–Ph (R6); R7: –OOC–(CH2)3–NH2; R8: –OOC–CH2–NH2; R9: –OH.

DCTC, dose inducing clonic–tonic convulsions; DTE, dose inducing tonic extension.

QSAR investigations must be used to make predictions for compounds with unknown activity. Five-fold cross-validation was performed for each property to assess the prediction ability. The molecules within each data set are ordered according to the values of their anticonvulsant activity and then every fifth molecule in this row is selected into the test set. Significantly, among the five data sets obtained, each molecule enters in the test set only once. The test set (20% of the total number of molecules) is excluded from the model building process. Based on the training set data, a model used to predict the properties of test set compounds is built. Thus, for each of the four data sets (DCTC [3 h], DCTC [24 h], DTE [3 h], DTE [24 h]), five data sets are formed, each containing training and test sets.

According to the OECD principles of QSAR model validation, in this task, the following domain applicability (DA) procedures were used:

  1. This method is based on the estimation of leverage value h i . It has been visualized as the Williams plot [23]. The new molecule is situated outside of the DA if h i  > h cr = 3(A + 1)/N, where N is the number of molecules in a work set.

  2. DA ellipsoid that developed [17], where the distribution of a training set of molecules in a space of latent variables (A) T 1–T A (axes of coordinates), can be obtained from the PLS. DA represents an ellipsoid that is built from the molecules at the center of the training set (T 1 = 0; T 2 = 0) with the semiaxes length 3ST1 and 3ST2, respectively (where ST1 and ST2 are the root mean square deviations). The prognoses for molecules approximated to the center of the DA are the most reliable.

The “randomization” procedure (Y-scrambling) [18] was used to confirm the “nonrandomness” of the developed QSAR models. Y-scrambling procedure is the creation of the models using the method of random selection of coefficients. The essence of this method is that after developing the model on a work set, random mixing of the values of the property is carried out. If the model is retrained, then a fairly good model will be obtained on the Y-randomized set. If the model parameters do not lead to retraining, then after Y-randomization, there will be a significant deterioration in the descriptive ability of the model.

The following formulas were used for calculating of statistical characteristics:

Coefficient of determination R 2 = ∑ i = 1 N ( y i obs − y ¯ ) 2 − ∑ i = 1 N ( y i calc − y i obs ) 2 ∑ i = 1 N ( y i obs − y ¯ ) 2 ,

where y i obs is the observed value of property for i molecule, y i calc is the calculated (predicted) value of property for i molecule, and N is the number of molecules, y ¯ = 1 N ∑ i = 1 N y i obs ;

Root mean square error ( RMSE) = ∑ i = 1 N ( y i calc − y i obs ) 2 N ,

Mean absolute error ( MAE) = 1 N ∑ i = 1 N ∣ ( y i calc − y i obs ) ∣ .

To calculate simplex-informational descriptors and integral parameters of the molecules and also to develop QSAR models, software HiTQSAR developed in the Department of Molecular Structures and Chemoinformatics (A.V. Bogatsky Physical-Chemical Institute NAS of Ukraine) was used.

3 Results and discussion

At the first stage, in the construction of PLS ratios, all molecules were included in the study (a training set of 36 terpene derivatives). For DCTC (3 h), DCTC (24 h), DTE (3 h), and DTE (24 h) data sets 2D PLS QSAR models M1–M4 were developed. Models M1–M4 had the number of latent variables A = 2 and adequate statistical characteristics (Table 2).

Table 2

The statistical characteristics of 2D QSAR models

Model Anticonvulsant activity Work set Leave-one-out Y-Scrambling
R 2 RMSE MAE Q 2 RMSE MAE R 2 Q 2
M1 DCTC (3 h) 0.88 10.6 7.9 0.81 13.5 10.1 0.26 ± 0.03 0.11 ± 0.03
M2 DCTC (24 h) 0.91 9.2 7.4 0.81 13.5 10.6 0.17 ± 0.02 0.08 ± 0.02
M3 DTE (3 h) 0.80 15.6 12.1 0.75 18.0 14.1 0.14 ± 0.02 0.04 ± 0.03
M4 DTE (24 h) 0.90 9.9 8.0 0.86 12.4 9.8 0.19 ± 0.03 0.11 ± 0.03

Note: R 2 – coefficient of determination; Q 2 – coefficient of determination for cross validation (leave-one-out); RMSE – root mean square error; MAE – mean absolute error.

The models obtained using the Y-scrambling procedure had low values of R (Y-scr) 2 < 0.29 and Q ( Y-scr ) 2 < 0.14 , indicating that the nonrandomness of the established relationship between the structure of compounds and their anticonvulsant activities obtained from the previous models M1–M4.

Five-fold cross-validation was performed for each property to assess the prediction ability. Adequate 2D QSAR models were obtained and used further as basis for the consensus models. For consensus models, the coefficient of determination for test sets was found to be ( R test 2 ) > 0.62 (Table 3).

Table 3

The statistical characteristics of consensus models (test set)

Anticonvulsant activity R 2 RMSE MAE
DCTC (3 h) 0.62 18.8 15.3
DCTC (24 h) 0.79 13.9 11.6
DTE (3 h) 0.75 17.6 14.3
DTE (24 h) 0.81 14.7 11.2

Noteworthy, the quality of the models for 24 h is better than those for 3 h that, obviously, may be due to the fact that some compounds fully manifest their activity after time. Relationship between observed and predicted values of anticonvulsant activities for the test set within the consensus models for four sets is presented in Figure 2a–d. As described, significant correlation between observed and predicted values of anticonvulsant activities in DCTC (3 h), DCTC (24 h), DTE (3 h), and DTE (24 h) sets was revealed for the majority of compounds.

Figure 2 Observed versus predicted diagram for anticonvulsant activities of terpene derivatives: (a) DCTC (3 h); (b) DCTC (24 h); (c) DTE (3 h); and (d) DTE (24 h).
Figure 2

Observed versus predicted diagram for anticonvulsant activities of terpene derivatives: (a) DCTC (3 h); (b) DCTC (24 h); (c) DTE (3 h); and (d) DTE (24 h).

Physicochemical and structural interpretation of the models was carried out based on consensus 2D-QSAR models developed for the DCTC (3 h), DCTC (24 h), DTE (3 h), and DTE (24 h) samples. To define the relative influence of the different physical and chemical factors on the character of the molecules interaction with the biological target, it is necessary to sum and compare absolute values of PLS regression coefficients of simplexes for all used groups for atom differentiation. Figure 3 shows the relative influence of some physicochemical factors on the anticonvulsant activity of terpene derivatives at 3 and 24 h after oral administration. As seen, the analysis of the obtained 2D QSAR model using SiRMS (IF) approach confirms that in all cases the contribution of electrostatic factor is predominant (48–63%). Equally important factors are the steric factors that are determined, on the one hand, by values of the van der Waals radii (20–35%), and on the other hand, by topology which is associated with the molecular form (13–22%). Lipophilicity effect in all instances was minimal, less than 9% from the sum of all considered factors.

Figure 3 Relative influence of some structural factors on anticonvulsant activity of terpene derivatives estimated on the basis of consensus 2D-QSAR models: (a) DCTC (3 h); (b) DCTC (24 h); (c) DTE (3 h); and (d) DTE (24 h).
Figure 3

Relative influence of some structural factors on anticonvulsant activity of terpene derivatives estimated on the basis of consensus 2D-QSAR models: (a) DCTC (3 h); (b) DCTC (24 h); (c) DTE (3 h); and (d) DTE (24 h).

One of SiRMS approach advantages, also proper to the SiRMS (IF), is the possibility of appropriate structural interpretation. The influence of each atom (as a part of simplex) into investigated property can be calculated on the basis of the obtained QSAR models [17,18]. The contribution (C) of each j-atom in the molecule can be defined as the ratio of the sum of PLS regression coefficient (b I ) of all simplexes this atom contains (M) to the number of atoms (n) in the simplex (or fragment): C j = 1 n ∑ I = 1 M b I (for simplex n = 4). According to this formula, the atomic contribution depends on the number of simplexes that include this atom. This value (count of simplexes) is not constant, and it varies in different molecules and depends on other constituents (surroundings); hence, this contribution is nonadditive [16]. The analysis of such information allowed selecting molecular fragments which have positive and negative influence on considered activity.

The entire set consisting of 36 terpene derivatives was divided into nine subgroups in which the effect of R substituents was analyzed. The contribution of the structural cores A–I was also evaluated (Table 4).

Table 4

Relative contribution of structural cores on anticonvulsant activity of terpenoids and their derivatives

Cores DCTC (3 h) DCTC (24 h) DTE (3 h) DTE (24 h)
A −1.3 4.8 8.5 7.5
B 17.7 18.7 18.8 9.6
C 14.8 13.1 19.8 5.9
D −18.4 1.2 −12.8 23.8
E 6.6 −2.9 4.8 1.2
F 8.6 −15.4 −0.1 −16.8
G 1.2 −12.9 −0.6 −9.5
H 5.5 0.5 17.9 8.7
I 15.3 −4.9 11.1 −5.0

The higher the value of the MEDs of seizure agent that induce DCTC and DTE, the greater the anticonvulsant effect of the compound. As demonstrated in Table 3, carvone (B) and verbenone (C) nuclei were discovered to facilitate the manifestation of anticonvulsant activity in the case of DCTC (3 h) and DCTC (24 h). The influence of eugenol nucleus (I) in its derivatives prevents the manifestation of anticonvulsant activity with increase in time after oral administration of compounds. The effects of menthol (D) and menthone (A) nuclei become positive during the transition from 3 to 24 h after the administration of their derivatives; consequently, the presence of the aforementioned nuclei in the molecule structure will contribute to the expression of antiseizure action. This phenomenon might be explained by higher lipophilicity of menthone (log P 2.63) core compared with verbenone (log P 1.97) and carvone (log P 2.26) leading to prolonged action of menthone derivatives and their more pronounced activity over a long time period (24 h).

In the case of DTE (3 h), the nuclei of verbenone (C), carvone (B), and borneol (H) derivatives were the most conducive to the manifestation of anticonvulsant activity. Similarly to DCTC, the presence of menthol nucleus (D) initially prevents the expression of effect; however, over time its effect becomes reversed leading to enhanced seizure protection due to gradual enzymatic hydrolysis of ester bond in menthol derivatives. Generally, the presence of carvone (B), verbenone (C), and borneol (H) nuclei in the structure of terpenoid derivatives at all time periods (3 and 24 h) promote the demonstration of anticonvulsant activity on the model of PTZ-induced seizures. Comparative analysis of substituent (R) contribution to anticonvulsant effect was also conducted and its results are summarized in Table 5.

Table 5

Relative contribution of molecular fragments on anticonvulsant activity of terpenoids and their derivatives

Structural cores Fragments (R) DCTC (3 h) DCTC (24 h) DTE (3 h) DTE (24 h)
A R1 0.1 0 0 0.4
R2 3.1 14.1 −2.9 33.8
R3 20.3 10.2 32.7 34.6
R4 7.2 8.8 4.9 33.7
R5 8.4 1.9 30.3 20.0
R6 −6.3 4.3 −10.2 10.2
B R1 0.1 0 0 0.4
R2 9.1 21.6 0.1 40.3
R3 24.6 14.9 30.0 35.7
R4 15.8 17.5 11.8 37.3
R5 25.1 15.5 38.9 48.0
R6 4.2 16.1 −3.2 40.3
C R1 0.1 0 0 0.4
R2 12.9 24.9 3.4 39.8
R3 25.2 18.1 37.2 35.9
R4 15.8 19.6 27.8 36.0
R5 18.8 17.5 33.1 47.4
R6 −8.3 14.5 −7.2 38.8
D R7 −3.9 4.9 −2.3 5.7
R8 −7.6 6.5 −4.2 7.6
R9 −5.1 1.3 −0.5 1.3
E R7 5.9 3.6 4.4 3.2
R8 6.6 4.1 13.6 7.0
R9 −0.3 0.2 0 0.5
F R7 25.7 −2.3 15.2 4.4
R8 4.6 −2.0 6.6 1.2
R9 −4.6 −0.02 −0.1 0.5
G R7 3.9 18.6 2.3 26.9
R8 0.3 2.2 2.4 8.4
R9 −0.6 −0.2 −0.8 0.5
H R7 24.9 −1.7 31.2 4.4
R8 3.9 8.1 −1.4 12.7
R9 2.0 −0.3 3.7 0.5
I R7 14.5 1.9 5.6 6.3
R8 8.1 2.3 12 6.0
R9 0.1 0.9 −1.5 2.2

DCTC, dose inducing clonic–tonic convulsions; DTE, dose inducing tonic extension.

When analyzing the influence of substituents (R1–R9) on the manifestation of anticonvulsant activity, it was found that the replacement of the carbonyl group linked to the cyclic terpene fragment with hydrazone substituents as well as replacement of the hydroxyl group with GABA or glycine residues resulted in strengthening of antiseizure action.

4 Conclusion

In the present study, QSAR models for anticonvulsant activity prediction of hydrazones and esters based on monocyclic/bicyclic terpenoids were developed using SiRMS (IF) approach, which captured the essence of simplex representation for molecular structure and its IF. Physicochemical and structural interpretation of the models was carried out. The contribution of electrostatic factor on the anticonvulsant activity of terpene derivatives at 3 and 24 h after oral administration is predominant (48–63%). Equally important factors are the steric factors: values of the van der Waals radii (20–35%) and topology (13–22%). Molecular fragments responsible for the manifestation of anticonvulsant action defined on the basis of the developed models. In particular, we found that carvone, verbenone cores possess the most significant contribution to antiseizure action examined on the model of PTZ-induced convulsions at 3 and 24 h after oral administration of terpene derivatives. Moreover, carbonyl and hydroxy group substitution in terpenoid molecules followed by hydrazones and esters formation leads to enhancement and prolongation of antiseizure action due to the contribution of additional molecular fragments. The presented QSAR models contribute significantly to design of novel terpene derivatives for oral administration against onset seizures.

Abbreviations

DA

domain applicability

DCTC

dose inducing clonic–tonic convulsions

DTE

dose inducing tonic extension

MAE

mean absolute error

MED

minimum effective dose

PTZ

pentylenetetrazole

QSAR

quantitative structure–activity relationship

RMSE

root mean square error

SiRMS

simplex representation of molecular structure

IF

informational field

IP

informational potential

PLS

partial least squares

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  1. Funding information: No funding to declare.

  2. Author contributions: All authors contributed to the study conception and design. M.N., L.O., and V.M. performed material preparation, data collection, and writing of original draft. I.K. and V.K.: supervision, editing of original draft. All authors read and approved the final manuscript.

  3. Conflict of interest: The authors declare no potential conflict of interest.

  4. Ethical approval: The conducted research is not related to either human or animal use.

  5. Data availability statement: The data sets generated during the present study are available from the corresponding author on reasonable request.

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Received: 2021-08-13
Revised: 2021-11-21
Accepted: 2021-11-22
Published Online: 2021-12-10

© 2021 Mariia Nesterkina et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Regular Articles
  2. Qualitative and semi-quantitative assessment of anthocyanins in Tibetan hulless barley from different geographical locations by UPLC-QTOF-MS and their antioxidant capacities
  3. Effect of sodium chloride on the expression of genes involved in the salt tolerance of Bacillus sp. strain “SX4” isolated from salinized greenhouse soil
  4. GC-MS analysis of mango stem bark extracts (Mangifera indica L.), Haden variety. Possible contribution of volatile compounds to its health effects
  5. Influence of nanoscale-modified apatite-type calcium phosphates on the biofilm formation by pathogenic microorganisms
  6. Removal of paracetamol from aqueous solution by containment composites
  7. Investigating a human pesticide intoxication incident: The importance of robust analytical approaches
  8. Induction of apoptosis and cell cycle arrest by chloroform fraction of Juniperus phoenicea and chemical constituents analysis
  9. Recovery of γ-Fe2O3 from copper ore tailings by magnetization roasting and magnetic separation
  10. Effects of different extraction methods on antioxidant properties of blueberry anthocyanins
  11. Modeling the removal of methylene blue dye using a graphene oxide/TiO2/SiO2 nanocomposite under sunlight irradiation by intelligent system
  12. Antimicrobial and antioxidant activities of Cinnamomum cassia essential oil and its application in food preservation
  13. Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form
  14. Evaluation of the performance of immunoblot and immunodot techniques used to identify autoantibodies in patients with autoimmune diseases
  15. Computational studies by molecular docking of some antiviral drugs with COVID-19 receptors are an approach to medication for COVID-19
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  17. Simultaneous removal efficiency of H2S and CO2 by high-gravity rotating packed bed: Experiments and simulation
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  84. Erratum
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https://doi.org/10.1515/chem-2021-0108
Keywords for this article
QSAR models; terpenes; anticonvulsant activity; SiRMS approach
Creative Commons
BY 4.0

Articles in the same Issue

  1. Regular Articles
  2. Qualitative and semi-quantitative assessment of anthocyanins in Tibetan hulless barley from different geographical locations by UPLC-QTOF-MS and their antioxidant capacities
  3. Effect of sodium chloride on the expression of genes involved in the salt tolerance of Bacillus sp. strain “SX4” isolated from salinized greenhouse soil
  4. GC-MS analysis of mango stem bark extracts (Mangifera indica L.), Haden variety. Possible contribution of volatile compounds to its health effects
  5. Influence of nanoscale-modified apatite-type calcium phosphates on the biofilm formation by pathogenic microorganisms
  6. Removal of paracetamol from aqueous solution by containment composites
  7. Investigating a human pesticide intoxication incident: The importance of robust analytical approaches
  8. Induction of apoptosis and cell cycle arrest by chloroform fraction of Juniperus phoenicea and chemical constituents analysis
  9. Recovery of γ-Fe2O3 from copper ore tailings by magnetization roasting and magnetic separation
  10. Effects of different extraction methods on antioxidant properties of blueberry anthocyanins
  11. Modeling the removal of methylene blue dye using a graphene oxide/TiO2/SiO2 nanocomposite under sunlight irradiation by intelligent system
  12. Antimicrobial and antioxidant activities of Cinnamomum cassia essential oil and its application in food preservation
  13. Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form
  14. Evaluation of the performance of immunoblot and immunodot techniques used to identify autoantibodies in patients with autoimmune diseases
  15. Computational studies by molecular docking of some antiviral drugs with COVID-19 receptors are an approach to medication for COVID-19
  16. Synthesis of amides and esters containing furan rings under microwave-assisted conditions
  17. Simultaneous removal efficiency of H2S and CO2 by high-gravity rotating packed bed: Experiments and simulation
  18. Design, synthesis, and biological activities of novel thiophene, pyrimidine, pyrazole, pyridine, coumarin and isoxazole: Dydrogesterone derivatives as antitumor agents
  19. Content and composition analysis of polysaccharides from Blaps rynchopetera and its macrophage phagocytic activity
  20. A new series of 2,4-thiazolidinediones endowed with potent aldose reductase inhibitory activity
  21. Assessing encapsulation of curcumin in cocoliposome: In vitro study
  22. Rare norisodinosterol derivatives from Xenia umbellata: Isolation and anti-proliferative activity
  23. Comparative study of antioxidant and anticancer activities and HPTLC quantification of rutin in white radish (Raphanus sativus L.) leaves and root extracts grown in Saudi Arabia
  24. Comparison of adsorption properties of commercial silica and rice husk ash (RHA) silica: A study by NIR spectroscopy
  25. Sodium borohydride (NaBH4) as a high-capacity material for next-generation sodium-ion capacitors
  26. Aroma components of tobacco powder from different producing areas based on gas chromatography ion mobility spectrometry
  27. The effects of salinity on changes in characteristics of soils collected in a saline region of the Mekong Delta, Vietnam
  28. Synthesis, properties, and activity of MoVTeNbO catalysts modified by zirconia-pillared clays in oxidative dehydrogenation of ethane
  29. Synthesis and crystal structure of N,N′-bis(4-chlorophenyl)thiourea N,N-dimethylformamide
  30. Quantitative analysis of volatile compounds of four Chinese traditional liquors by SPME-GC-MS and determination of total phenolic contents and antioxidant activities
  31. A novel separation method of the valuable components for activated clay production wastewater
  32. On ve-degree- and ev-degree-based topological properties of crystallographic structure of cuprite Cu2O
  33. Antihyperglycemic effect and phytochemical investigation of Rubia cordifolia (Indian Madder) leaves extract
  34. Microsphere molecularly imprinted solid-phase extraction for diazepam analysis using itaconic acid as a monomer in propanol
  35. A nitric oxide-releasing prodrug promotes apoptosis in human renal carcinoma cells: Involvement of reactive oxygen species
  36. Machine vision-based driving and feedback scheme for digital microfluidics system
  37. Study on the application of a steam-foam drive profile modification technology for heavy oil reservoir development
  38. Ni–Ru-containing mixed oxide-based composites as precursors for ethanol steam reforming catalysts: Effect of the synthesis methods on the structural and catalytic properties
  39. Preparation of composite soybean straw-based materials by LDHs modifying as a solid sorbent for removal of Pb(ii) from water samples
  40. Synthesis and spectral characterizations of vanadyl(ii) and chromium(iii) mixed ligand complexes containing metformin drug and glycine amino acid
  41. In vitro evaluation of lactic acid bacteria with probiotic activity isolated from local pickled leaf mustard from Wuwei in Anhui as substitutes for chemical synthetic additives
  42. Utilization and simulation of innovative new binuclear Co(ii), Ni(ii), Cu(ii), and Zn(ii) diimine Schiff base complexes in sterilization and coronavirus resistance (Covid-19)
  43. Phosphorylation of Pit-1 by cyclin-dependent kinase 5 at serine 126 is associated with cell proliferation and poor prognosis in prolactinomas
  44. Molecularly imprinted membrane for transport of urea, creatinine, and vitamin B12 as a hemodialysis candidate membrane
  45. Optimization of Murrayafoline A ethanol extraction process from the roots of Glycosmis stenocarpa, and evaluation of its Tumorigenesis inhibition activity on Hep-G2 cells
  46. Highly sensitive determination of α-lipoic acid in pharmaceuticals on a boron-doped diamond electrode
  47. Synthesis, chemo-informatics, and anticancer evaluation of fluorophenyl-isoxazole derivatives
  48. In vitro and in vivo investigation of polypharmacology of propolis extract as anticancer, antibacterial, anti-inflammatory, and chemical properties
  49. Topological indices of bipolar fuzzy incidence graph
  50. Preparation of Fe3O4@SiO2–ZnO catalyst and its catalytic synthesis of rosin glycol ester
  51. Construction of a new luminescent Cd(ii) compound for the detection of Fe3+ and treatment of Hepatitis B
  52. Investigation of bovine serum albumin aggregation upon exposure to silver(i) and copper(ii) metal ions using Zetasizer
  53. Discoloration of methylene blue at neutral pH by heterogeneous photo-Fenton-like reactions using crystalline and amorphous iron oxides
  54. Optimized extraction of polyphenols from leaves of Rosemary (Rosmarinus officinalis L.) grown in Lam Dong province, Vietnam, and evaluation of their antioxidant capacity
  55. Synthesis of novel thiourea-/urea-benzimidazole derivatives as anticancer agents
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  57. Simple modifications of nicotinic, isonicotinic, and 2,6-dichloroisonicotinic acids toward new weapons against plant diseases
  58. Synthesis, optical and structural characterisation of ZnS nanoparticles derived from Zn(ii) dithiocarbamate complexes
  59. Presence of short and cyclic peptides in Acacia and Ziziphus honeys may potentiate their medicinal values
  60. The role of vitamin D deficiency and elevated inflammatory biomarkers as risk factors for the progression of diabetic nephropathy in patients with type 2 diabetes mellitus
  61. Quantitative structure–activity relationship study on prolonged anticonvulsant activity of terpene derivatives in pentylenetetrazole test
  62. GADD45B induced the enhancing of cell viability and proliferation in radiotherapy and increased the radioresistance of HONE1 cells
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  64. Dynamics of λ-cyhalothrin disappearance and expression of selected P450 genes in bees depending on the ambient temperature
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  66. Study on the speciation of arsenic in the genuine medicinal material honeysuckle
  67. Two Cu(ii)-based coordination polymers: Crystal structures and treatment activity on periodontitis
  68. Conversion of furfuryl alcohol to ethyl levulinate in the presence of mesoporous aluminosilicate catalyst
  69. Review Articles
  70. Hsien Wu and his major contributions to the chemical era of immunology
  71. Overview of the major classes of new psychoactive substances, psychoactive effects, analytical determination and conformational analysis of selected illegal drugs
  72. An overview of persistent organic pollutants along the coastal environment of Kuwait
  73. Mechanism underlying sevoflurane-induced protection in cerebral ischemia–reperfusion injury
  74. COVID-19 and SARS-CoV-2: Everything we know so far – A comprehensive review
  75. Challenge of diabetes mellitus and researchers’ contributions to its control
  76. Advances in the design and application of transition metal oxide-based supercapacitors
  77. Color and composition of beauty products formulated with lemongrass essential oil: Cosmetics formulation with lemongrass essential oil
  78. The structural chemistry of zinc(ii) and nickel(ii) dithiocarbamate complexes
  79. Bioprospecting for antituberculosis natural products – A review
  80. Recent progress in direct urea fuel cell
  81. Rapid Communications
  82. A comparative morphological study of titanium dioxide surface layer dental implants
  83. Changes in the antioxidative properties of honeys during their fermentation
  84. Erratum
  85. Erratum to “Corrosion study of copper in aqueous sulfuric acid solution in the presence of (2E,5E)-2,5-dibenzylidenecyclopentanone and (2E,5E)-bis[(4-dimethylamino)benzylidene]cyclopentanone: Experimental and theoretical study”
  86. Erratum to “Modified TDAE petroleum plasticiser”
  87. Corrigendum
  88. Corrigendum to “A nitric oxide-releasing prodrug promotes apoptosis in human renal carcinoma cells: Involvement of reactive oxygen species”
  89. Special Issue on 3rd IC3PE 2020
  90. Visible light-responsive photocatalyst of SnO2/rGO prepared using Pometia pinnata leaf extract
  91. Antihyperglycemic activity of Centella asiatica (L.) Urb. leaf ethanol extract SNEDDS in zebrafish (Danio rerio)
  92. Selection of oil extraction process from Chlorella species of microalgae by using multi-criteria decision analysis technique for biodiesel production
  93. Special Issue on the 14th Joint Conference of Chemistry (14JCC)
  94. Synthesis and in vitro cytotoxicity evaluation of isatin-pyrrole derivatives against HepG2 cell line
  95. CO2 gas separation using mixed matrix membranes based on polyethersulfone/MIL-100(Al)
  96. Effect of synthesis and activation methods on the character of CoMo/ultrastable Y-zeolite catalysts
  97. Special Issue on Electrochemical Amplified Sensors
  98. Enhancement of graphene oxide through β-cyclodextrin composite to sensitive analysis of an antidepressant: Sulpiride
  99. Investigation of the spectroelectrochemical behavior of quercetin isolated from Zanthoxylum bungeanum
  100. An electrochemical sensor for high sensitive determination of lysozyme based on the aptamer competition approach
  101. An improved non-enzymatic electrochemical sensor amplified with CuO nanostructures for sensitive determination of uric acid
  102. Special Issue on Applied Biochemistry and Biotechnology 2020
  103. Fast discrimination of avocado oil for different extracted methods using headspace-gas chromatography-ion mobility spectroscopy with PCA based on volatile organic compounds
  104. Effect of alkali bases on the synthesis of ZnO quantum dots
  105. Quality evaluation of Cabernet Sauvignon wines in different vintages by 1H nuclear magnetic resonance-based metabolomics
  106. Special Issue on the Joint Science Congress of Materials and Polymers (ISCMP 2019)
  107. Diatomaceous Earth: Characterization, thermal modification, and application
  108. Electrochemical determination of atenolol and propranolol using a carbon paste sensor modified with natural ilmenite
  109. Special Issue on the Conference of Energy, Fuels, Environment 2020
  110. Assessment of the mercury contamination of landfilled and recovered foundry waste – a case study
  111. Primary energy consumption in selected EU Countries compared to global trends
  112. Modified TDAE petroleum plasticiser
  113. Use of glycerol waste in lactic acid bacteria metabolism for the production of lactic acid: State of the art in Poland
  114. Topical Issue on Applications of Mathematics in Chemistry
  115. Theoretical study of energy, inertia and nullity of phenylene and anthracene
  116. Banhatti, revan and hyper-indices of silicon carbide Si2C3-III[n,m]
  117. Topical Issue on Agriculture
  118. Occurrence of mycotoxins in selected agricultural and commercial products available in eastern Poland
  119. Special Issue on Ethnobotanical, Phytochemical and Biological Investigation of Medicinal Plants
  120. Acute and repeated dose 60-day oral toxicity assessment of chemically characterized Berberis hispanica Boiss. and Reut in Wistar rats
  121. Phytochemical profile, in vitro antioxidant, and anti-protein denaturation activities of Curcuma longa L. rhizome and leaves
  122. Antiplasmodial potential of Eucalyptus obliqua leaf methanolic extract against Plasmodium vivax: An in vitro study
  123. Prunus padus L. bark as a functional promoting component in functional herbal infusions – cyclooxygenase-2 inhibitory, antioxidant, and antimicrobial effects
  124. Molecular and docking studies of tetramethoxy hydroxyflavone compound from Artemisia absinthium against carcinogens found in cigarette smoke
  125. Special Issue on the Joint Science Congress of Materials and Polymers (ISCMP 2020)
  126. Preparation of cypress (Cupressus sempervirens L.) essential oil loaded poly(lactic acid) nanofibers
  127. Influence of mica mineral on flame retardancy and mechanical properties of intumescent flame retardant polypropylene composites
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