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18# Research Results in Pharmacology
Research Results in Pharmacology 8(2): 69-75
UDC: 615.224 DOI 10.3897/rrpharmacology. 8.77854
3 Research Article
Searching for novel antagonists of adenosine A1 receptors among azolo[1,5-a]pyrimidine nitro derivatives
Dmitry S. Yakovlev1,2, Pavel M. Vassiliev1, Yana V. Agatsarskaya1, Anastasia A. Brigadirova1, Kira T. Sultanova1, Maria O. Skripka1,2, Alexander A. Spasov1,2, Konstantin V. Savateev3, Vladimir L. Rusinov3, Dmitriy V. Maltsev1,2
1 Volgograd State Medical University, 1 Pavshikh Bortsov Sq., Volgograd 400131, Russia
2 Volgograd Medical Research Center, 1 Pavshikh Bortsov Sq., Volgograd 400131, Russia
3 Ural Federal University named after the first President of Russia B.N.Yeltsin, 19 Mira St., Ekaterinburg 620002, Russia Corresponding author: Maria O. Skripka (rete.mirabile.renis@gmail.com)
Academic editor: Mikhail Korokin ♦ Received 10 November 2021 ♦ Accepted 5 April 2022 ♦ Published 15 June 2022
Citation: Yakovlev DS, Vassiliev PM, Agatsarskaya YV, Brigadirova AA, Sultanova KT, Skripka MO, Spasov AA, Savateev KV, Rusinov VL, Maltsev DV (2022) Searching for novel antagonists of adenosine A1 receptors among azolo[1,5-a]pyrimidine nitro derivatives. Research Results in Pharmacology 8(2): 69-75. https://doi.org/10.3897/rrpharmacology.8.77854
Abstract
Introduction: Ligands of adenosine A1Rs are potential candidates for the development of drugs for the treatment of paroxysmal supraventricular tachycardia, angina pectoris, hypertriglyceridemia, type 2 diabetes mellitus, neuropathic pain, and heart failure. At the same time, there is a deficiency of drugs that can regulate the functions of A1 receptors. A number of A1-antagonists are at the various stages of clinical trials; other drugs are not very selective or are characterized by an insufficient breadth of their therapeutic action. Therefore, the search for new medicinal compounds for the prevention and treatment of A1-depended diseases among nitro derivatives of tetrazolo[1,5-a]pyrimidine and 1,2,4-triazolo[1,5-a]pyrimidine is of scientific interest.
Materials and methods: The search for active compounds was carried out by in silico and in vitro methods. At the first stage, a computer forecast of A1-antagonistic activity was carried out using the Microcosm BioS software. At the second stage, the prediction results were verified in vitro in a model of isolated mouse atria.
Results and discussion: Based on the results of the prediction by the method of maximum similarity to standards, the most active compounds III, VIII, and XVII were selected. After testing the prediction results by the isolated atria method, the compound VIII was characterized by A1-blocking effect in vitro at a concentration of 10 ^mol/L.
Conclusion: The most promising compound with Allocking effect in vitro was identified; it is a derivative of tetrazolo[1,5-a]pyrimidine under the code of VIII. It is of interest for us for further in-depth study of its pharmacological properties.
Keywords
adenosine 1 type receptor, isolated tissue, Microcosm Bios, tetrazolo[1,5- a]pyrimidine, 1,2,4-triazolo[1,5-a]pyrimidine.
Copyright Yakovlev DS etal. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Introduction
Adenosine receptors (ARs) are targets for the development of new methods of pharmacological correction of various diseases (Manjunath et al. 2009; Jamwal et al. 2019). Adenosine is an endogenous purine-based nucleoside expressed nearly in all body tissues (Saini et al. 2022). It exhibits multiple biological effects and regulates a number of physiological functions, including the functioning of the cardiovascular system (Headrick et al. 2011; Albrecht-Küpper et al. 2012; Guieu et al. 2020). It is known that adenosine regulates myocardial function and the intensity of coronary circulation, and also has a pronounced vasodilatory effect (Reiss et al. 2019). At the same time, the clinical potential of AjRs regulation has not been fully realized to date. In modern medicine, only a few drugs with Aj antagonistic properties are used.
Caffeine causes most of its biological effects via antagonizing all types of ARs. When acting as nonselective AR antagonist (Chen et al. 2017), caffeine, used acutely, is doing the opposite of activation of adenosine receptors, due to removal of the adenosinergic tonus (Ribeiro and Sebastiäo 2010). Synthetic xanthines, analogues of caffeine - Tonapofylline (BG-9928), Rolofylline (KW-3902 or MK-7418) and Derenofylline (SLV-320) were first announced in 2010-2012 and went through the stages of clinical trials (Sureechatchaiyan et al. 2018) for the treatment of congestive heart failure, acute decompensated heart failure and renal dysfunction (Pang et al. 2011). These compounds are more selective AjR antagonists (Ensor and Russell 2010; Teerlink et al. 2012).
Single administration of Rolofylline in patients with heart failure and impaired renal function produced a consistently increased diuresis and natriuresis without compromising renal function (Ponikowski et al. 2010). In phase III clinical trials, the AjR antagonist Rolofylline was not sufficiently effective in worsening renal function in patients with acute heart failure (Voors et al. 2011). Clinical trials of Derenophylline and Tonapofylline were terminated for reasons beyond the effects of the drugs. Taking this into account, the issue of developing and creating new Aj-antagonists remains very relevant.
In this regard, this study is focused on continuing the search for new A1R antagonists among pyrimidine derivatives as possible drug candidates for subsequent use in medical practice. Analysis of the chemical structure of known Aj-antagonists (Tonapofylline and Rolofylline are derivatives of imidazopyrimidines and Derenofylli-ne is pyrrolo[2,3-d]pyrimidine) suggests a high prospect of searching for potential AjR antagonists among pyri-midine derivatives. The current investigation is aimed to study the A1R antagonism potential of earlier synthesized nitro derivatives of tetrazolo[1,5-a]pyrimidine (Savateev et al. 2018) and 1,2,4-triazolo[1,5-a]pyrimi-dine (Rusinov et al. 2017).
Materials and methods
Experimental design
At the first stage, a database was formed in silico on the structure of the reference ligands of adenosine Aj receptors studied by the world scientific community using the search engines IUPHAR, Tocris, SelleckChem. Thus, 20 selective Aj adenosine receptor antagonists were selected. Then, a database was formed on the structure of 25 new chemical compounds, derivatives of azolo[1,5-a]pyri-midine. The data on the structure of 25 new compounds were collected and generated using ChemFinder 9.0, a ChemOffice 9.0 software package (URL: http://www. cambridgesoft.com/12).
The processing of the data set and their translation into QL language descriptors were carried out using the utilities of the IT Microcosm software package; the following modules were used: ActUtil, TranQL2, and MakeData (Vassiliev et al. 2014). First, using the ActUtil utility, a data set consisting of * .actv and * .tba files was created. Second, the VMNC.sdf file was processed in the TranQL2 module to obtain * .qll files. At the last stage, the final data set was obtained using the MakeData utility.
The most active substances according to in silico forecast were tested for their Aj-antagonistic activity with isolated tissue technique in vitro.
Predicted affinity for adenosine Aj receptors of new compounds using the Microcosm BioS software
In this study, the prediction of affinity for adenosine A1 receptors was carried out using the Microcosm BioS v.18.1.9 system, which includes the original QSAR database containing verified, structured and processed information on the chemical structure and activity level of the known compounds studied by the world scientific community at various types of biological activity.
The specified QSAR database was formed outside the scope of this study, using information obtained from three well-known international search engines: ChEM-BL (URL: https://www.ebi.ac.uk/chembl/), BindingDB (URL: https://www.bindingdb.org/) and PubChem (URL: https://pubchem.ncbi.nlm.nih.gov). The primary dataset was checked for correct chemical structural formulas, so incorrect and duplicate entries were removed from it.
Experimental animals
The experiments were carried out on 30 white outbred mice m=18-30 g, obtained from the Rappolovo Nursery, Leningrad region (Russia). The animals were kept in a vivarium with a natural light regimen on a standard diet of laboratory animals, with access to food and water ad libitum. The vivarium maintained standard conditions in accordance with Order No. 51 of August 29, 2014 of the Chief State Sanitary Doctor of the Russian Federation
"On Approval of Sanitary Regulations 2.2.1.3218-14 "Sanitary and Epidemiological Requirements for Managing, Equipping and Maintaining Experimental Biological Clinics (Vivariums)" on a special hygienic wood filler (LLC Production Complex GlavRezerv). Twelve hours before the start of the experiment, the animals were deprived of access to food, while access to water remained free. The experimental procedures on animals were carried out in accordance with the Local Ethics Committee of Volgograd State Medical University, Volgograd, Russia (Minutes No. IRB 00005839 IORG 0004900 (OHRP)). All the experiments were carried out in accordance with "The Guidelines for Conducting Preclinical Studies of Drugs" (Mironov 2012).
where AHR _ - the difference between the baseline
control
heart rate and the heart rate calculated after adenosine administration; AHR t , - the difference between the
7 treated
baseline heart rate and the heart rate calculated after adenosine administration in mice under the influence of the test compounds.
Statistical analysis
Statistical analysis of the obtained data was carried out in the GraphPad Prism 6.0 software using the Kruskal-Wal-lis test and post hoc Dunn's test. The data are presented as mean ± standard error of mean (M±SEM). The p<0.05 values were considered statistically significant.
Isolated atria technique
After cervical dislocation of the rodents, the heart was removed and both atria were isolated. The isolated samples of the left and right atria were fixed in a 20 ml bath, filled with Krebs-Henseleit nutrient solution with constant oxygenation of 95% O2 -5% CO2 and a temperature of 37 °C in a 4-channel system for maintaining the vital functions of isolated tissues TISSUEBATH4 (Biopac Systems, Inc., USA). The isolated atria were fixed on an isometric sensor TSD125C with a sensitivity range of 0-50 g at an isometric load of 1 g. The organ was left for adaptation for 45-60 min before the start of the experiment. During the adaptation period and the subsequent experiment, the buffer solution in the bath was replaced every 10-15 min.
A1-antagonistic activity of compounds under study
The A1-antagonistic activity of novel nitro derivatives of azolo[1,5-a]pyrimidines was investigated by addition of the tested compound (200 ^l) 3 min before the introduction of adenosine (200 ^l) with an exposure for 30 s before a registered decrease in chronotropism of atria, working in their own rhythm (without stimulation). Between each administration of adenosine, the isolated atrial sample was left to relax for at least 10-15 min to return the atrial chronotropism to the initial level. The reference drug was caffeine at an equimolar concentration of 10 ^mol/L. The A1-antagonistic effect of the test substances and the control sample was assessed by a degree of suppression of adenosine-induced decrease in chronotropism of the isolated atrial tissue in comparison with the effect of adeno-sine obtained in control measurements (A%).
Contractions of isolated atria were recorded using Ac-qKnowledge 4.0 software (Biopac Systems, Inc., USA). The number of isolated atria contractions was measured over a 30-second interval with subsequent calculation of the heart rate. The amount of atrial chronotropism suppression (A%) was calculated by the formula:
&% = 100-
AHR.
'control
4IHRtreated
x 100
Results and discussion
Results of in silico prediction of the adenosine A1 activity levels of new chemical compounds.
On this basis, the QSAR database was calculated using six specially created programs, containing the QL-descriptor representation of chemical structural information, in the form of working files in the format developed earlier when creating the IT Microcosm package (Vassiliev et al. 2014).
The QSAR database obtained in this way includes information on the structure of 625888 known chemical compounds tested by world scientific studies for 11509 different types of biological activity, with details of a type of biotarget, test organism and the measured activity indicator. In total, this database contains information on 6016 biotargets, on 325 species of test organisms, indicating the quantitative values of activity for 4 different indicators.
The specified QSAR base is part of the Microcosm BioS system, designed to predict the spectrum of targeted biological activity of new chemical compounds.
The QSAR-base of the Microcosm Bios v18.1.9 system contains information on the structure and level of affinity for the adenosine Aj receptor of 7455 compounds studied in experimental tests on five different organisms, including data for 5373 compounds for Homo sapiens. The calculation of the predicted spectrum of targeted biological activity of new chemical compounds was carried out using the original Microcosm BioS system by the method of maximum similarity to standards. The well-known compounds studied by the world scientific community for A1-antagonistic activity were used as standards. Information about these compounds was accumulated in the above-described Microcosm BioS QSAR database.
The forecast results were saved as a tab-delimited text file; part of the primary listing is shown in Fig. 1.
The final results of the prediction in Microcosm BioS of new compounds adenosine A1 receptor affinity are shown in Table 1.
In total, according to the prediction data by the method of maximum structural similarity to the standards,
Homo sapiens pKi
Homo sapiens pKi
Homo sapiens pKi
Bos taurus pKi
Homo sapiens pKi
Homo sapiens pKi
Homo sapiens pKi
Bos taurus pKi
Homo sapiens pKi
Homo sapiens pKi
The results of forecast of target activity spectrum by the method of maximum similarity to standards
BindingDB_Trunc : VMNC - Konus ards : 10
Number of structures : 625888 Number of structures : 31
Structure Target organism
Threshold2 Index
KC-0547 Adenosine Receptor Al -4
KC-0547 Adenosine Receptor Al -4
KC-0547 Adenosine Receptor Al -4
KC-0547 Adenosine Al receptor +3
KC-0547 Adenosine Receptor Al -3
KC-0547 Adenosine Receptor Al +1
KC-0547 Adenosine Receptor Al -4
KC-0547 Adenosine Al receptor -2
KC-0547 Adenosine Receptor Al -4
KC-0547 Adenosine Receptor Al +1
KC-0646a
5.5384 -4 KC-0646a
5.0000 -5 KC-0646a
7.5086 +2 KC-0646a
7.9586 +3 KC-0646a
5.5384 -4 KC-0646a
6.7052 -1 KC-0646a
5.9674 -3 KC-0646a
Parameter Homo sapiens pKi Homo sapiens Homo sapiens Bos tau rus Homo sapiens Homo sapiens Homo sapiens Bos tau rus Homo sapiens Homo sapiens
pKi pKi pKi pKi pKi pKi pKi pKi pKi
Adenosine Receptor Al Adenosine Al receptor Adenosine Al receptor Adenosine Al receptor Adenosine Receptor Al Adenosine Al receptor Adenosine Al receptor Adenosine Receptor Al
Homo sapiens Bos tau rus Bos tau rus Bos tau rus Homo sapiens Bos tau rus Bos tau rus Homo sapiens
N
3695
3695
3695
719
3695
3695
3695
719
3695
3695
pKi
pKi
pKi
pKi
pKi
pKi
pKi
pKi
Mediane Min 6.3492 5.0000
6.3492 6.3492 6.7052 6.3492 6.3492 6.3492 6.7052 6.3492 6.3492 3695 719 719 719 3695 719 719 3695
5.0000 5.0000 5.0000 5.0000 5.0000 5.0000 5.0000 5.0000 5.0000 6.3492 6.7052 6.7052 6.7052 6.3492 6.7052 6.7052 6.3492
Max 7.9208 7.9208 7.9208 8.3872 7.9208 7.9208 7.9208 8.3872 7.9208 7.9208 5.0000 5.0000 5.0000 5.0000 5.0000 5.0000 5.0000 5.0000
Tmax 0.4647 0.4626 0.4583 0.4578 0.4554 0.4538 0.4526 0.4470 0.4441 0.4441 7.9208 8.3872 8.3872 8.3872 7.9208 8.3872 8.3872 7.9208
Mol ID 537793
447558
447559 344711 272616 537799 453951 344699 453949 453967 0.4970 0.4881 0.4863 0.4780 0.4685 0.4606 0.4584 0.4544
Monomer ID 50360196
50255249
50255250 50120765 50048026 50360202 50266382 50120753 50266380 50266415
447558 50255249 344702 50120756 344704 50120758 344711 50120765
447559 50255250 344700 50120754 344715 50120769 234682 50009698
Value 5.4283 5.3501 5.3050 7.9208 5.6440 6.4634 5.0902 6.0680 5.4731 6.4949
Thresholdl
5.0000 5.0000 5.0000 7.5086 5.5384 6.3492 5.0000 5.9674 5.0000 6.3492 5.3501 5.0000 7.3872 7.9208 S.30S0 6.6364 5.4089 5.9263
. 5384 . 5384 . 5384 .9586 .9062 .6047 . 5384 .3372 . 5384 .6047 .0000 .0000 .0678 . 5086 .0000 .3372 .3716 .9062
>1 (ANSI - KMpM/MHip)
Figure 1. The beginning of listing the results of the spectrum prediction of Ax-antagonistic activity levels in the Microcosm BioS v.18.1.9 system.
Table 1. Prediction of adenosine A1 receptor affinity by the method of maximum similarity to standards
Number
Code
Ind
Ind
1
2
3
4
5
6
7
8
9
10 11 12
13
14
15
16
17
18
19
20 21 22
23
24
25
III VIII XVII
XI X IX
XII 1D II
XIV
XIII
VI
IV
VII 1G
I
V 1A 1E
XVI
XV 1B 1C 1H 1F
0.5 1.2 0.4 0.1 0.4 0.4 0.6 -0.9 -1.8 -1.9 -1.1 -1.4 -2.5 -1.6 -1.9 -2.0 -2.9 -2.8 -3.0 -2.5 -3.7 -3.9 -3.2 -4.1 -4.5
20%
Ind
0.6 1.3 0.5 0.3 0.4 0.4 0.6 -1.1 -2.0 -2.1 -1.3 -1.6 -2.5 -1.9 -2.0 -2.4 -3.1 -3.0 -3.3 -2.9 -3.9 -4.4 -3.9 -4.3 -4.9
2 2 1 1 1 1 1 -2 -2 -2 -2 -2 -3 -3 -3 -4 -4 -4 -4 -4 -4 -5 -5 -5 -5
Note: Ind - average value of activity level indices; Ind20% - 20% truncated mean of activity level indices; IndMed - median activity indices.
7 compounds (highlighted in color) are promising for studying their adenosine A1 receptor affinity, having three non-negative averaged estimates in total. The most interesting for experimental testing are 3 compounds
(highlighted in green), in which all three calculated scores are at least 2 points, which corresponds to a sufficiently high activity.
Results of testing new compounds on isolated tissue model
The results of the study of A1-antagonistic activity of 6 nitro derivatives of tetrazolo[1,5-a]pyrimidine and 1 derivative of 1,2,4-triazolo[1,5-a]pyrimidine are shown in Table 2.
Only one of the seven tested compounds was characterized by an A1-blocking effect in vitro at a concentration of 10 |mol/L: VIII. It is confirmed by more than 45% suppression relative to the control measurements, and, compared to the reference drug caffeine, A1-blocking effect of compounds was inferior by 1.3 times. Compounds XII and IX did not show any A1-antagonistic activity. Derivative of 1,2,4-triazolo[1,5-a]pyrimidine III was inferior to caffeine in terms of its antagonistic activity against A1-adenosine receptors by 1.5 times.
Conclusion
In the course of the study, in silico prediction of adenosine A1 receptor affinity of 25 new compounds was made using the method of maximum structural similarity to the reference standards. As a result of the prediction, 7 promising compounds with the expected moderate or high A1-antagonistic activity were identified, which were recommended for experimental studies. Of these, three
Table 2. A1-inhibitory activity of compounds under study (at a concentration of 10 ^mol/L)
Compound
R.
Inhibition of adenosine negative chronotropic effect, A% (M±SEM)
Caffeine
III
VIII
IX
X
XI
XII
Comparison drug
R,—/
derivatives of 1,2,4-triazolo[1,5-a]pyrimidine
derivatives of tetrazolo[1,5-a]pyrimidine
60.5±3.7
40.1±3.0
45.9±10.7
0.0±0.0*
10.5±3.0
38.3±5.6
0.0±0.0*
XVII
OH
28.1±3.0
NO
N
Note: * - differences are significant compared to caffeine (p<0.05, Kruskal-Wallis test, post hoc Dunn's test).
compounds were recommended to be tested for their Aj-antagonistic activity as a priority.
Seven new nitro derivatives of azolo[1,5-a]pyrimidi-nes were tested for A1-antagonistic activity in vitro. The results of in silico prediction of activity of the compounds under study were confirmed for compound VIII. In terms of isolated atria technique, the inhibition of adenosine negative chronotropic effect was about 45%, under the influence of this substance. So, compound VIII is of interest for us for further in-depth study of its pharmacological properties.
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Conflict of interests
The authors declare no conflict of interests.
Acknowledgements
The reported study was partially funded by the Government of Volgograd region, Agreement No. 6 dated 10.12.2020.
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Author Contribution
■ Dmitriy S. Yakovlev, Doctor Habil. of Medical Sciences, Professor, Department of Pharmacology and Bioinformatics, Volgograd State Medical University; Senior Researcher, Laboratory of Experimental Pharmacology, Volgograd Medical Research Center, Volgograd, Russia; e-mail: dypharm@list.ru, ORCID ID https://orcid. org/0000-0001-8980-6016. The author defined the idea of research and developed a research plan.
■ Pavel M. Vassiliev, Doctor Habil. of Medical Sciences, Professor, Department of Pharmacology and Bioinformatics, Volgograd State Medical University, Volgograd, Russia; e-mail: pvassiliev@mail.ru, ORCID ID https://orcid. org/0000-0002-8188-5052. The author consulted on the research idea.
■ Yana V. Agatsarskaya, PhD in Pharmacology, Assistant Professor, Department ofPharmacology and Bioinformatics, Volgograd State Medical University ; Junior Researcher, Laboratory of Experimental Pharmacology, Volgograd Medical Research Center, Volgograd, Russia; e-mail: agatsarskaya.i@gmail.com, ORCID ID https://orcid. org/0000-0002-7772-7318. The author took part in conducting experimental work.
■ Anastasia A. Brigadirova, PhD in Pharmacology, Lecturer, Department of Pharmacology and Bioinformatics, Volgograd State Medical University; Researcher, Laboratory of Experimental Pharmacology, Volgograd Medical Research Center, Volgograd, Russia; e-mail: a.brigadirova@gmail.com, ORCID ID https://orcid.org/0000-0003-0957-7087. The author took part in conducting experimental work and writing the original draft.
■ Kira T. Sultanova, PhD in Pharmacology, Assistant Professor, Department of Pharmacology and Bioinformatics, Volgograd State Medical University; Junior Researcher, Laboratory of Experimental Pharmacology, Volgograd Medical Research Center, Volgograd, Russia; e-mail: sultanova.pharma@gmail.com, ORCID ID https://orcid. org/0000-0002-9846-8335. The author took part in conducting experimental work.
■ Maria O. Skripka, PhD student, Department of Pharmacology and Bioinformatics, Volgograd State Medical University; Junior Researcher, Laboratory of Experimental Pharmacology, Volgograd Medical Research Center, Volgograd, Russia; e-mail: rete.mirabile.renis@gmail.com, ORCID ID https://orcid.org/0000-0002-4173-7143. The author took part in analysis of the material and editing the text of the article.
■ Alexander A. Spasov, Doctor Habil. of Medical Sciences, Full Professor, Academician of the Russian Academy of Sciences, Head of the Department of Pharmacology and Bioinformatics, Volgograd State Medical University,; Head of Laboratory of Experimental Pharmacology, Volgograd Medical Research Center, Volgograd, Russia; e-mail: aspasov@mail.ru, ORCID ID https://orcid.org/0000-0002-7185-4826. The author consulted on the research idea, concept and design.
■ Konstantin V. Savateev, PhD in Chemistry, research fellow, Department of Organic and Biomolecular Chemistry, Institute of Chemical Technology, Ural Federal University named after the first President of Russia B.N.Yeltsin, Yekaterinburg, Russia; e-mail: i-krafttt@yandex.ru, ORCID ID https://orcid.org/0000-0001-6040-5155. The author took part in the chemical synthesis of the studied azolo[1,5-a]pyrimidines.
■ Vladimir L. Rusinov, Doctor Habil. of Chemical Sciences, Full Professor, Corresponding Member of the Russian Academy of Sciences, Head of the Department of Organic and Biomolecular Chemistry, Institute of Chemical Technology, Ural Federal University named after the first President of Russia B.N.Yeltsin, Yekaterinburg, Russia; e-mail: v.l.rusinov@urfu.ru, ORCID ID https://orcid.org/0000-0002-1705-4078. The author consulted on the research idea, concept and design.
■ Dmitriy V. Maltsev, PhD in Pharmacology, Lecturer, Department of Pharmacology and Bioinformatics, Volgograd State Medical University; Researcher, Laboratory of Experimental Pharmacology, Volgograd Medical Research Center, Volgograd, Russia; e-mail: maltsevdmitriy@rambler.ru, ORCID ID https://orcid.org/0000-0002-2005-6621. The author took part in conducting experimental work and analysis of the material.
