PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE
The objective of this study was to predict the pharmacokinetic parameters of 5,6,7,8-tetrahydroquinoline-3-amine derivatives using the ADMET 2.0 web resource and compare them with 4-aminoquinoline and chloroquine. The tested substances exhibited favorable indicators of intestinal absorption, cleara...
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| Дата: | 2024 |
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V.I.Vernadsky Institute of General and Inorganic Chemistry
2024
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Репозитарії
Ukrainian Chemistry Journal| _version_ | 1871466022494535680 |
|---|---|
| author | Varenichenko, Svetlana Farat, Oleg |
| author_facet | Varenichenko, Svetlana Farat, Oleg |
| author_institution_txt_mv | [
{
"author": "Svetlana Varenichenko",
"institution": "Associate Professor Department of Pharmacies and Technology of Organic Substances, Ukrainian State Chemical Technology University, Dnipro, Ukraine"
},
{
"author": "Oleg Farat",
"institution": "Department of Pharmacies and Technology of Organic Substances, Ukrainian State Chemical Technology University, Dnipro, Ukraine"
}
] |
| author_sort | Varenichenko, Svetlana |
| baseUrl_str | https://ucj.org.ua/index.php/journal/oai |
| collection | OJS |
| datestamp_date | 2026-07-22T08:23:53Z |
| description | The objective of this study was to predict the pharmacokinetic parameters of 5,6,7,8-tetrahydroquinoline-3-amine derivatives using the ADMET 2.0 web resource and compare them with 4-aminoquinoline and chloroquine. The tested substances exhibited favorable indicators of intestinal absorption, clearance, half-life, and liver damage, mutagenicity, and carcinogenicity. The derivatives of 5,6,7,8-tetrahydroquinolin-3-amine studied here have increased indicators of blood-brain barrier penetration. Therefore, they cannot be recommended for the production of drugs that act on the central nervous system. Based on the prediction results, the compounds with tert-butyl and tert-amyl substituents in the 7th position were found to be the most effective. The SuperPred 3.0 web resource was used to predict the molecular targets for binding of derivatives of 5,6,7,8-tetrahydroquinoline-3-amine. The aminoquinolines and chloroquine studied in this research have common binding targets, including tyrosyl-DNA-phosphodiesterase 1, DNA-(apurine or apyrimidine site) lyase, neuronal acetylcholine receptor alpha3/beta4, and cathepsin D. These predicted binding targets play important roles in regulating cell function. The derivatives of 5,6,7,8-tetrahydroquinoline-3-amines presented in this study are promising compounds for further pharmacological research due to their effective synthesis method and pharmacokinetic properties. |
| doi_str_mv | 10.33609/2708-129X.90.1.2024.15-25 |
| first_indexed | 2025-09-24T17:43:55Z |
| format | Article |
| fulltext |
15
UDK 547.854.856 doi: 10.33609/2708-129X.90.1.2024.15-25
PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE
DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE.
S.A. Varenichenko, O.K. Farat
Ukrainian State University of Chemical Technology,
8 Gagarina ave, 49005 Dnipro, Ukraine
*е-mail: svetlanavarenichenko@gmail.com
The objective of this study was to predict the pharmacokinetic parameters of 5,6,7,8-tetra
hydroquinoline-3-amine derivatives using the ADMET 2.0 web resource and compare them
with 4-aminoquinoline and chloroquine. The tested substances exhibited favorable indica-
tors of intestinal absorption, clearance, half-life, and liver damage, mutagenicity, and carcino-
genicity. The derivatives of 5,6,7,8-tetrahydroquinolin-3-amine studied here have increased
indicators of blood-brain barrier penetration. Therefore, they cannot be recommended for
the production of drugs that act on the central nervous system. Based on the prediction
results, the compounds with tert-butyl and tert-amyl substituents in the 7th position were
found to be the most effective. The SuperPred 3.0 web resource was used to predict the mo-
lecular targets for binding of derivatives of 5,6,7,8-tetrahydroquinoline-3-amine. The amino-
quinolines and chloroquine studied in this research have common binding targets, including
tyrosyl-DNA-phosphodiesterase 1, DNA-(apurine or apyrimidine site) lyase, neuronal acetyl-
choline receptor alpha3/beta4, and cathepsin D. These predicted binding targets play impor-
tant roles in regulating cell function. The derivatives of 5,6,7,8-tetrahydroquinoline-3-amines
presented in this study are promising compounds for further pharmacological research due
to their effective synthesis method and pharmacokinetic properties.
Keywords: 5,6,7,8-tetrahydroquinoline-3-amine derivatives, electrophilic rearrangement,
spiroimidazolidones, in silico, ADMET 2.0, SuperPred 3.0
INTRODUCTION. Quinoline derivatives
have a broad range of pharmacological activity,
and the quinoline core is present in many drugs.
Classical antimalarial drugs, such as 4-ami
noquinoline [1], chloroquine [2], and hydro
xychloroquine [3], are well-known examples.
Although these compounds were tested for
the treatment of COVID-19, they exhibit-
ed high toxicity and several side effects [4].
Dequalinium, the basis of a synthetic antibi-
otic, has antifungal and antiprotozoal effects
and contains a quinoline core. Although hyd
roquinolines are not included in active drugs,
there are examples of their pharmacological
16 ISSN 2708-129X. Укр. хім. журн., 2024
PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE.ORGANIC CHEMISTRY
activity. However, the lack of available methods
for the synthesis of hydroquinoline derivatives
has led scientists to focus on finding and deve
loping effective synthesis methods. A previ
ous method for synthesizing hydroquinolines
with good yields was published, which result-
ed from the electrophilic rearrangement of
spiroimidazolidones [12–13].
The aim of this article is to predict the bio
logical activity of 5,6,7,8-tetrahydroquino-
line-3-amine derivatives 1–8 (Figure 1) using
in silico methods.
Figure 1. Synthesized derivatives of 5,6,7,8-tetrahydroquinoline-3-amine.
EXPERIMENT AND RESULTS DISCU
SSION. The ADMETlab 2.0 software resource
[14] was used to assess the capabilities of com-
pounds 1–8 to bind to biological targets and
predict their metabolic profile, excretion, toxi
city, and ADMET ligand properties. The pre-
dicted values for compounds 1–8 were com-
pared to those of active drugs containing the
quinoline core, 4-aminoquinoline 9, and chlo-
roquine 10 (Figure 2).
During the comparative analysis, visualiza-
tion of the results is presented in the form of
“spider web” graphs in Figure 3.
1 2 3 4
N
NH2
Cl N
NH2
Br N
NH2
Cl N
NH2
Br
5 6
N
NH2
Cl N
NH2
Br
7 8
N
NH2
Cl N
NH2
Br
Figure 1. Synthesized derivatives of 5,6,7,8-tetrahydroquinoline-3-amine.
EXPERIMENT AND RESULTS DISCUSSION. The ADMETlab 2.0 software resource [14]
was used to assess the capabilities of compounds 1–8 to bind to biological targets and predict their
metabolic profile, excretion, toxicity, and ADMET ligand properties. The predicted values for
compounds 1–8 were compared to those of active drugs containing the quinoline core, 4-
aminoquinoline 9, and chloroquine 10 (Figure 2).
9 10
N N
NH2
Cl
HN
N
Figure 2. Comparison drugs, 4-aminoquinoline and chloroquine.
During the comparative analysis, visualization of the results is presented in the form of
“spider web” graphs in Figure 3.
a b
c d
a – compound 1; b – compound 6; c – compound 9; d – compound 10
Figure 3. Graphic images of the analysis of physical and chemical authorities 1, 6, 9 and 10.
1 2 3 4
N
NH2
Cl N
NH2
Br N
NH2
Cl N
NH2
Br
5 6
N
NH2
Cl N
NH2
Br
7 8
N
NH2
Cl N
NH2
Br
Figure 1. Synthesized derivatives of 5,6,7,8-tetrahydroquinoline-3-amine.
EXPERIMENT AND RESULTS DISCUSSION. The ADMETlab 2.0 software resource [14]
was used to assess the capabilities of compounds 1–8 to bind to biological targets and predict their
metabolic profile, excretion, toxicity, and ADMET ligand properties. The predicted values for
compounds 1–8 were compared to those of active drugs containing the quinoline core, 4-
aminoquinoline 9, and chloroquine 10 (Figure 2).
9 10
N N
NH2
Cl
HN
N
Figure 2. Comparison drugs, 4-aminoquinoline and chloroquine.
During the comparative analysis, visualization of the results is presented in the form of
“spider web” graphs in Figure 3.
a b
c d
a – compound 1; b – compound 6; c – compound 9; d – compound 10
Figure 3. Graphic images of the analysis of physical and chemical authorities 1, 6, 9 and 10.
Figure 2. Comparison drugs, 4-aminoquinoline and chloroquine.
17https://ucj.org.ua
S.A. Varenichenko, O.K. Farat UCJ № 1 / Vol. 90
a – compound 1; b – compound 6; c – compound 9; d – compound 10
Figure 3. Graphic images of the analysis of physical and chemical authorities 1, 6, 9 and 10.
a b
c d
a – compound 1; b – compound 6; c – compound 9; d – compound 10
Figure 3. Graphic images of the analysis of physical and chemical authorities 1, 6, 9 and 10.
Table 1 presents prediction data for 13 physicochemical compounds 1–10. For clinical trial
applicants, it is essential to comply with the Lipinski rule [15]. Additionally, topological polar
surface area (TPSA), number of rotatable bonds (nRot), and lipid solubility parameter (Log P) at
physiological pH = 7.4 Log D are also crucial in predicting the oral bioavailability of a substance.
Таблиця 1. Фізико-хімічні показники сполук 1–10 за допомогою ADMETlab 2.0
Table 1. Physico-chemicalindicatorsofcompounds 1–10 using ADMETlab 2.0.
Compound MW Log P nHA nHD TPSA nRot Log D
Normativeindicators <500 <5 <10 <5 <140 <11 <3
1 182 2.233 2 2 38.91 0 2.366
2 226 2.554 2 2 38.91 0 2.509
a b
c d
a – compound 1; b – compound 6; c – compound 9; d – compound 10
Figure 3. Graphic images of the analysis of physical and chemical authorities 1, 6, 9 and 10.
Table 1 presents prediction data for 13 physicochemical compounds 1–10. For clinical trial
applicants, it is essential to comply with the Lipinski rule [15]. Additionally, topological polar
surface area (TPSA), number of rotatable bonds (nRot), and lipid solubility parameter (Log P) at
physiological pH = 7.4 Log D are also crucial in predicting the oral bioavailability of a substance.
Таблиця 1. Фізико-хімічні показники сполук 1–10 за допомогою ADMETlab 2.0
Table 1. Physico-chemicalindicatorsofcompounds 1–10 using ADMETlab 2.0.
Compound MW Log P nHA nHD TPSA nRot Log D
Normativeindicators <500 <5 <10 <5 <140 <11 <3
1 182 2.233 2 2 38.91 0 2.366
2 226 2.554 2 2 38.91 0 2.509
Table 1 presents prediction data for 13 phy
sicochemical compounds 1–10. For clinical
trial applicants, it is essential to comply with
the Lipinski rule [15]. Additionally, topological
polar surface area (TPSA), number of rotatable
bonds (nRot), and lipid solubility parameter
(Log P) at physiological pH = 7.4 Log D are
also crucial in predicting the oral bioavailabi
lity of a substance.
18 ISSN 2708-129X. Укр. хім. журн., 2024
PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE.ORGANIC CHEMISTRY
Таблиця 1. Фізико-хімічні показники сполук 1–10 за допомогою ADMETlab 2.0
Table 1. Physico-chemicalindicatorsofcompounds 1–10 using ADMETlab 2.0.
Compound MW Log P nHA nHD TPSA nRot Log D
Normativeindicators <500 <5 <10 <5 <140 <11 <3
1 182 2.233 2 2 38.91 0 2.366
2 226 2.554 2 2 38.91 0 2.509
3 196 2.629 2 2 38.91 0 2.631
4 240 2.951 2 2 38.91 0 2.799
5 238 3.873 2 2 38.91 1 3.962
6 282 4.192 2 2 38.91 1 4.046
7 252 4.244 2 2 38.91 2 4.184
8 296 4.601 2 2 38.91 2 4.287
9 144 1.327 2 2 38.91 0 1.361
10 319 4.217 3 1 28.16 8 3.755
Upon analyzing the results, it is evident
that 4-aminoquinoline and compounds 1–4
meet the required standards, while synthe-
sized compounds 5, 6, 7, 8, and chloroquine 9
demonstrate a Log D parameter slightly out-
side the required range.
Subsequently, we conducted an analysis of
the pharmacokinetic parameters, which are
presented in Table 2.
Таблиця 2. Фармакокінетичні показники сполук 1–10
Table 2. Pharmacokinetic parameters of compounds 1–10.
Compound HIA BBB CL T1/2
Normativeindicators 0–0.3 excellent
0.3–0.7 medium
0.7–1.0 poor
0–0.3 excellent
0.3–0.7 medium
0.7–1.0 poor
>5 0–0.3 excellent
0.3–0.7 medium
0.7–1.0 poor
1 0.003 0.99 8.248 0.337
2 0.004 0.995 4.336 0.289
3 0.004 0.986 9.976 0.286
4 0.007 0.992 5.437 0.251
5 0.007 0.966 0.177
6 0.031 0.977 4.966 0.145
7 0.07 0.967 8.242 0.154
8 0.029 0.981 4.475 0.12
9 0.006 0.402 6.122 0.32
10 0.002 0.679 6.818 0.134
19https://ucj.org.ua
S.A. Varenichenko, O.K. Farat UCJ № 1 / Vol. 90
The human intestinal absorption (HIA) pa-
rameter is considered an alternative indicator
for oral bioavailability because good intestinal
absorption is necessary for the effectiveness
of an oral drug in humans. It is assumed that
all compounds tested have good absorption.
Drugs that act on the central nervous sys-
tem must cross the blood-brain barrier (BBB)
to reach their molecular target. For periphe
rally targeted drugs, little or no BBB penetra-
tion may be required to avoid CNS side effects.
Compounds 1–8 cannot be recommended for
manufacturing drugs that act on the central
nervous system due to their increased BBB
values. Control drugs 9 and 10 show average
values.
When comparing clearance (CL), only com
pounds 2, 6, and 8 will be excreted less in urine.
The half-life of all tested compounds falls
within normal limits.
Table 3 presents predicted toxicities for com-
pounds 1–10, an important safety indicator.
Таблиця 3. Показники токсичності, мутагенності і канцерогенності сполук 1–10
Table 3. Indicators of toxicity, mutagenicity and carcinogenicity of compounds 1–10.
Compound DILI AMES CARC
Normative indicators
0–0.3 excellent
0.3–0.7 medium
0.7–1.0 poor
1 0.334 0.554 0.621
2 0.336 0.158 0.599
3 0.307 0.629 0.702
4 0.33 0.147 0.654
5 0.236 0.018 0.081
6 0.102 0.015 0.07
7 0.291 0.035 0.094
8 0.166 0.018 0.079
9 0.802 0.849 0.564
10 0.733 0.634 0.089
Drug-induced liver injury (DILI) is a major
safety concern in drug withdrawal. The con-
nections with the safest parameters are 5, 6, 7,
and 8, while the control connections 9 and 10
have high readings.
The mutagenic effect (AMES) is closely re-
lated to carcinogenicity and is the most wide-
ly used method for testing the mutagenicity
of compounds. The compounds with the best
indications for predicting mutagenicity among
those tested were compounds 2 and 4–8. For
drugs 9 and 10, mutagenicity indicators are
within normal limits, but may be overestimated.
Carcinogenicity (CARC) of chemical com-
pounds is due to their ability to damage the ge-
nome and disrupt cellular metabolic processes.
Compounds 5, 6, 7, 8, and 10 are expected to
have the least carcinogenic effect. It is important
20 ISSN 2708-129X. Укр. хім. журн., 2024
PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE.ORGANIC CHEMISTRY
to note that toxicity of the compounds decreas-
es with increasing branching of the alkyl sub-
stituent.
Based on the data analysis, compounds 5,
6, 7, and 8 show the most promise for further
research.
The SuperPred 3.0 web resource (https://
prediction.charite.de/index.php) was used to
predict the binding of the tested compounds to
molecular targets.
This web server compares the structural fin-
gerprint of an incoming molecule with a data-
base of drugs associated with their targets and
pathways. The web server allows for predic-
tions about the medical indication domain of
new compounds to be made and new leads to
be found for known targets, based on the high-
ly predictable biological effect when the struc-
tural similarity is sufficient. This information
can be useful for drug classification and target
prediction [16, 17], as well as assisting in the
drug development process by predicting ATC
codes or small molecule targets and obtain-
ing compound information. The web server's
ATC forecast and target prediction are based
on a machine learning model that uses logistic
regression and Morgan fingerprints of length
2048. The ChEMBL version 29 database was
used to identify the target.
Binding predictions were performed for
compound 6 (Table 4) and chloroquine 10 (Ta
ble 5). The analysis considered results up to 80%.
Таблиця 4. Прогнозовані цілі зв’язування з молекулою сполуки 6
Table 4. Predicted targets of binding to the compound 6.
TargetName ChEMBL-ID PDB
Visualization Probability Indications of predicted
targets
Tyrosyl-DNA phosphodiesterase
1 CHEMBL1075138 6N0D 97.48%
DNA-(apurinic or apyrimidinic
site) lyase CHEMBL5619 6BOW 93.29%
Glioma, Melanoma,
Ocularcancer, Solid tumor/
cancer
Nuclear factor NF-kappa-B
p105 subunit CHEMBL3251 1SVC 92.74%
Phosphodiesterase 3A CHEMBL241 7LRC 92.51%
Bronchial asthma,
Cardiacfailure,
Cardiovascular disease,
Cardiovasculardisease,
Congestive heart failure,
Intermittent claudication,
Thrombocythemia
Neuronal acetylcholine receptor;
alpha3/beta4 CHEMBL1907594 6PV7 90.11%
Alzheimerdisease,
Tobaccodependence
LSD1/CoRESTcomplex CHEMBL3137262 5L3D 89.15%
G-proteincoupledreceptor 55 CHEMBL1075322 – 88.78%
Attentiondeficithyperactivity
disorder
21https://ucj.org.ua
S.A. Varenichenko, O.K. Farat UCJ № 1 / Vol. 90
TargetName ChEMBL-ID PDB
Visualization Probability Indications of predicted
targets
Endoplasmic reticulum-associ-
ated amyloid beta-peptide-bind-
ing protein CHEMBL4159 2O23 85.82%
Cannabinoid CB2 receptor CHEMBL253 6KPF 84.56%
Eglninehomolog 1 CHEMBL5697 4BQY 83.88%
NT-3 growthfactorreceptor CHEMBL5608 6KZD 83.38%
Transcriptionintermediaryfactor
1-alpha CHEMBL3108638 4YBM 83.06%
Cathepsin D CHEMBL2581 4OD9 82.5%
Hypertension,
Multiplesclerosis
Kruppel-likefactor 5 CHEMBL1293249 – 82.02%
Tyrosine-proteinkinase FYN CHEMBL1841 2DQ7 81.88%
Chronic myelogenousleukae-
mia, Multiple myeloma,
Solid tumour/cancer
LysosomalPro-X
carboxypeptidase CHEMBL2335 3N2Z 81.15%
Proteinkinase N1 CHEMBL3384 4OTH 80.8%
Sodium/hydrogenexchanger 1 CHEMBL2781 7DSX 80.44%
Angina pectoris,
Cardiacarrhythmias,
Heart arrhythmia,
Myocardial infarction
Таблиця 5. Прогнозовані цілі зв’язування сполуки 10
Table 5. Predicted targets of binding to the compound 10.
TargetName ChEMBL-ID PDB
Visualization
Probability Indications of predicted
targets
Sigma opioid receptor CHEMBL287 5НК1 99%
Sigmaintracellularreceptor 2 CHEMBL4105907 – 99%
Tyrosyl-DNAphosphodiesterase
1 CHEMBL1075138 6N0D 99%
HERG CHEMBL240 5VA1 98.19%
Malaria, Angina pectoris,Car-
diac failure, Heartarrhythmia,
Pain, Ovariancancer
Pregnane X receptor CHEMBL3401 6TFI 97.01% Arteriosclerosis,
Таблиця 4.
Table 4.
22 ISSN 2708-129X. Укр. хім. журн., 2024
PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE.ORGANIC CHEMISTRY
TargetName ChEMBL-ID PDB
Visualization
Probability Indications of predicted
targets
Cathepsin D CHEMBL2581 4OD9 96.6%
Hypertension,
Multiplesclerosis
Dual specificity protein kinase
CLK4 CHEMBL4203 6FYV 93.63%
Nuclear factor NF-kappa-B
p105 subunit CHEMBL3251 1SVC 93.32%
DNA-(apurinic or apyrimidinic
site) lyase CHEMBL5619 6BOW 92.82%
Glioma, Melanoma, Ocular
cancer
LysosomalPro-X carboxypep-
tidase CHEMBL2335 3N2Z 91.57%
Telomerasereversetranscriptase CHEMBL2916 7BG9 90.86%
Acute myeloid leukaemia,
Brain cancer, Breast cancer,
Essentialthrombocythemia,
Headand neck cancer
Dihydrofolatereductase CHEMBL202 1KMV 90.57%
Acute bacterial skininfection,
Bacterialinfection, Bladder
cancer
Neuronal acetylcholine receptor;
alpha3/beta4 CHEMBL1907594 6PV7 90.26%
Alzheimerdisease,
Tobaccodependence
Adenosine A1 receptor CHEMBL226 T92072 89.85%
Acute and chronic heart
failure, Atrial fibrillation,
Autoimmune diabetes
Serotonin 7 (5-HT7) receptor CHEMBL3155 T79062 89.21%
Alzheimer disease, Attention
deficit hyperactivity disorder,
Major depressive disorder
Nuclear factor erythroid 2-relat-
ed factor 2 CHEMBL1075094 – 88.99%
Cyclooxygenase-1 CHEMBL221 – 88.27%
Histonedeacetylase 7 CHEMBL2716 – 87.5%
Glutathione S-transferasePi CHEMBL3902 T21669 87.35%
Sodium channel protein type III
alpha subunit CHEMBL5163 T76937 87.17%
G-proteincoupledreceptor 55 CHEMBL1075322 T87670 86.82%
Adenosine A2b receptor CHEMBL255 T86679 85.96%
Acute and chronic heart-
failure, Alzheimer disease,
Asthma
Dipeptidylpeptidase II CHEMBL3976 – 85.95%
Таблиця 5.
Table 5.
23https://ucj.org.ua
S.A. Varenichenko, O.K. Farat UCJ № 1 / Vol. 90
Common binding targets for compound
6 and chloroquine 10 include Tyrosyl-DNA
phosphodiesterase 1, DNA-(apurinic or apy-
rimidinic site) lyase, Neuronal acetylcholine
receptor alpha3/beta4, and Cathepsin D.
These predicted targets play important roles
in regulating cell activity. For example, DNA-
(apurinic or apyrimidinic site) lyase is a mul-
tifunctional protein that plays a central role in
the cellular response to oxidative stress dur-
ing oxidative stress, melanoma, and cancer of
the eye [18].
CONCLUSIONS. A prediction of the phar-
macological activity of previously synthesized
5,6,7,8-tetrahydroquinoline-3-amine deriva-
tives was conducted in silico. The results of the
prediction were compared to those of the active
drugs, 4-aminoquinoline and chloroquine. All
synthesized compounds comply with Lipinski's
rule and exhibit good intestinal absorption,
clearance, and half-life. The synthesized com-
pounds exhibit lower predicted toxicity, muta-
genicity, and carcinogenicity compared to the
comparison drugs. Additionally, the study pre-
dicts future molecular targets for the synthe-
sized substances in living cells. The derivatives
of 5,6,7,8-tetrahydroquinoline-3-amines pre-
sented in this study are promising compounds
for further pharmacological studies due to
their effective synthesis method and pharma-
cokinetic properties.
ACKNOWLEDGMENTS.
Authors are thankful to the Ministry of
education and science of Ukraine (pro-
ject № 0123U101168) and scholarship
of the Cabinet of Ministers of Ukraine
for the financial support.
ПРОГНОЗУВАННЯ БІОЛОГІЧНОЇ АКТИВНОСТІ
ПОХІДНИХ АМІНОХІНОЛІНУ ЗА ДОПОМОГОЮ
ВЕБ-РЕСУРСУ ADMET 2.0
C. A. Варениченко, O. K. Фарат
Український державний хіміко-технологіч
ний університет,
просп. Гагаріна, 8, Дніпро 49005, Україна
*е-mail: svetlanavarenichenko@gmail.com
Метою цього дослідження було прогно-
зування фармакокінетичних параметрів
похідних 5,6,7,8-тетрагідрохінолін-3-аміну
за допомогою веб-ресурсу ADMET 2.0 та
порівняння їх із 4-амінохіноліном і хлоро-
хіном. Досліджувані речовини продемон-
стрували сприятливі показники кишкової
абсорбції, кліренсу, періоду напіввиведен-
ня та пошкодження печінки, мутагенно-
сті та канцерогенності. Досліджені похідні
5,6,7,8-тетрагідрохінолін-3-аміну мають під
вищені показники проникнення через ге-
матоенцефалічний бар'єр. Тому їх не можна
рекомендувати для розроблення препара-
тів, що діють на центральну нервову си-
стему. За результатами прогнозу найефек-
тивнішими виявилися сполуки з трет-бу-
тильним і трет-амільним замісниками в
7-му положенні. Веб-ресурс SuperPred 3.0
використовували для прогнозування мо-
лекулярних мішеней зв’язування похідних
5,6,7,8-тетрагідрохінолін-3-аміну.
Амінохіноліни та хлорохін, досліджені
в цій роботі, мають загальні мішені зв’я-
зування, включаючи тирозил-ДНК-фос-
фодіестеразу 1, ДНК-(апуриновий або апі-
римідиновий сайт) ліазу, нейрональний
ацетилхоліновий рецептор альфа3/бета4
24 ISSN 2708-129X. Укр. хім. журн., 2024
PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE.ORGANIC CHEMISTRY
та катепсин D. Ці передбачені мішені зв’я-
зування відіграють важливу роль у регу-
ляції роботи клітин. Представлені в цьому
дослідженні похідні 5,6,7,8-тетрагідрохіно-
лін-3-амінів є перспективними сполуками
для подальших фармакологічних дослі-
джень завдяки їхньому ефективному мето-
ду синтезу та фармакокінетичним власти-
востям.
Ключові слова: Похідні 5,6,7,8-тетра-
гідрохінолін-3-аміну, електрофільне пере-
групування, спіроімідазолідони, insilico,
ADMET 2.0, SuperPred 3.0.
REFERENCES
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Стаття надійшла 24.09.2023.
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| id | oai:ojs2.1444248.nisspano.web.hosting-test.net:article-629 |
| institution | Ukrainian Chemistry Journal |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2026-07-23T01:11:19Z |
| publishDate | 2024 |
| publisher | V.I.Vernadsky Institute of General and Inorganic Chemistry |
| record_format | ojs |
| resource_txt_mv | ucjorgua/f5/7ef9f8f508c82210b713f745585ad1f5.pdf |
| spelling | oai:ojs2.1444248.nisspano.web.hosting-test.net:article-6292026-07-22T08:23:53Z PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE Varenichenko, Svetlana Farat, Oleg 5,6,7,8-tetrahydroquinoline-3-amine derivatives, electrophilic rearrangement, spiroimidazolidones, in silico, ADMET 2.0, SuperPred 3.0 The objective of this study was to predict the pharmacokinetic parameters of 5,6,7,8-tetrahydroquinoline-3-amine derivatives using the ADMET 2.0 web resource and compare them with 4-aminoquinoline and chloroquine. The tested substances exhibited favorable indicators of intestinal absorption, clearance, half-life, and liver damage, mutagenicity, and carcinogenicity. The derivatives of 5,6,7,8-tetrahydroquinolin-3-amine studied here have increased indicators of blood-brain barrier penetration. Therefore, they cannot be recommended for the production of drugs that act on the central nervous system. Based on the prediction results, the compounds with tert-butyl and tert-amyl substituents in the 7th position were found to be the most effective. The SuperPred 3.0 web resource was used to predict the molecular targets for binding of derivatives of 5,6,7,8-tetrahydroquinoline-3-amine. The aminoquinolines and chloroquine studied in this research have common binding targets, including tyrosyl-DNA-phosphodiesterase 1, DNA-(apurine or apyrimidine site) lyase, neuronal acetylcholine receptor alpha3/beta4, and cathepsin D. These predicted binding targets play important roles in regulating cell function. The derivatives of 5,6,7,8-tetrahydroquinoline-3-amines presented in this study are promising compounds for further pharmacological research due to their effective synthesis method and pharmacokinetic properties. V.I.Vernadsky Institute of General and Inorganic Chemistry 2024-02-26 Article Article Organic chemistry Органическая xимия Органічна xімія application/pdf https://ucj.org.ua/index.php/journal/article/view/629 10.33609/2708-129X.90.1.2024.15-25 Ukrainian Chemistry Journal; Vol. 90 No. 1 (2024): Ukrainian Chemistry Journal; 15-25 Украинский химический журнал; ##issue.vol## 90 ##issue.no## 1 (2024): Ukrainian Chemistry Journal; 15-25 Український хімічний журнал; Том 90 № 1 (2024): Ukrainian Chemistry Journal; 15-25 2708-129X 2708-1281 en https://ucj.org.ua/index.php/journal/article/view/629/315 Copyright (c) 2024 Svetlana Varenichenko, Oleg Farat https://creativecommons.org/licenses/by-nc/4.0 |
| spellingShingle | Varenichenko, Svetlana Farat, Oleg PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE |
| title | PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE |
| title_full | PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE |
| title_fullStr | PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE |
| title_full_unstemmed | PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE |
| title_short | PREDICTION OF BIOLOGICAL ACTIVITY OF AMINOQUINOLINE DERIVATIVES USING THE ADMET 2.0 WEB RESOURCE |
| title_sort | prediction of biological activity of aminoquinoline derivatives using the admet 2.0 web resource |
| topic_facet | 5,6,7,8-tetrahydroquinoline-3-amine derivatives electrophilic rearrangement spiroimidazolidones in silico ADMET 2.0 SuperPred 3.0 |
| url | https://ucj.org.ua/index.php/journal/article/view/629 |
| work_keys_str_mv | AT varenichenkosvetlana predictionofbiologicalactivityofaminoquinolinederivativesusingtheadmet20webresource AT faratoleg predictionofbiologicalactivityofaminoquinolinederivativesusingtheadmet20webresource |