Computational approaches to predict the toxicity of bioactive natural products: a mini review of methodologies

Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This find...

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Published inFood science and biotechnology Vol. 34; no. 2; pp. 299 - 305
Main Authors Choi, Kwanyong, Kim, Ji Yeon
Format Journal Article
LanguageEnglish
Published Korea (South) Springer Nature B.V 01.01.2025
한국식품과학회
Subjects
Biocompatibility
Biological activity
Biotechnology
Composition effects
computer simulation
Food composition
Food safety
Food science
Food selection
Functional foods & nutraceuticals
Machine learning
Natural & organic foods
Natural products
Physiological effects
Predictions
Side effects
Toxicity
Toxicity testing
식품과학
In silico
Top-down
Natural products
Toxicity
Bottom-up
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Abstract Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This finding emphasizes the need for machine learning (ML)-based food safety predictions focused on intrinsic toxicity. This review explores various strategies involved in current methods of model selection and validation techniques used in predictive analysis, highlighting their strengths, limitations, and progress. Future studies should focus on testing compound combinations using top-down or bottom-up approaches with appropriate models to advance in silico toxicity modeling of bioactive natural products.
AbstractList Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This finding emphasizes the need for machine learning (ML)-based food safety predictions focused on intrinsic toxicity. This review explores various strategies involved in current methods of model selection and validation techniques used in predictive analysis, highlighting their strengths, limitations, and progress. Future studies should focus on testing compound combinations using top-down or bottom-up approaches with appropriate models to advance in silico toxicity modeling of bioactive natural products.Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This finding emphasizes the need for machine learning (ML)-based food safety predictions focused on intrinsic toxicity. This review explores various strategies involved in current methods of model selection and validation techniques used in predictive analysis, highlighting their strengths, limitations, and progress. Future studies should focus on testing compound combinations using top-down or bottom-up approaches with appropriate models to advance in silico toxicity modeling of bioactive natural products.
Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This finding emphasizes the need for machine learning (ML)-based food safety predictions focused on intrinsic toxicity. This review explores various strategies involved in current methods of model selection and validation techniques used in predictive analysis, highlighting their strengths, limitations, and progress. Future studies should focus on testing compound combinations using top-down or bottom-up approaches with appropriate models to advance in silico toxicity modeling of bioactive natural products.
Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition remain. Bioactive natural products can potentially interfere with physiological activity regulation and lead to undesired side effects. This finding emphasizes the need for machine learning (ML)-based food safety predictions focused on intrinsic toxicity. This review explores various strategies involved in current methods of model selection and validation techniques used in predictive analysis, highlighting their strengths, limitations, and progress. Future studies should focus on testing compound combinations using top-down or bottom-up approaches with appropriate models to advance in silico toxicity modeling of bioactive natural products. KCI Citation Count: 0
Author Kim, Ji Yeon
Choi, Kwanyong
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Cites_doi 10.1016/j.tox.2014.09.003
10.1186/s40360-018-0282-6
10.1093/toxsci/kfz243
10.1109/ACCESS.2018.2874089
10.1093/bib/bbx151
10.1016/j.tips.2005.02.006
10.1002/0470857897.ch8
10.1093/toxsci/kfl103
10.3390/life12030363
10.1016/j.tox.2004.01.028
10.1007/s10068-022-01047-6
10.1186/1472-6882-8-58
10.1007/s13530-020-00056-4
10.1109/NAFOSTED.2017.8108071
10.1023/A:1025361621494
10.1016/j.fct.2015.01.020
10.1038/nbt0702-649
10.1111/cbdd.13690
10.1177/1177932220921350
10.3389/fnut.2024.1393366
10.1007/s00204-021-03023-1
10.1080/15563650.2017.1333123
10.1007/s40484-019-0172-y
10.14573/altex.1803011
10.1093/bioinformatics/btw228
10.1016/j.drudis.2016.02.015
10.1155/2016/6012761
10.1201/9781003075363-20
10.1016/j.jff.2020.103896
10.1016/j.compbiolchem.2020.107402
10.1038/nphys260
10.1371/journal.pone.0142498
10.1021/acs.molpharmaceut.5b00465
10.1016/j.tifs.2023.104191
10.1080/1062936X.2015.1136680
10.1186/s12859-018-2199-x
10.1186/s12911-018-0592-z
10.1016/j.jbi.2010.01.002
10.1111/j.1365-2621.2005.tb09054.x
10.1055/a-0605-3786
10.3389/fphar.2022.961012
10.1038/s43016-021-00316-7
10.1016/S0278-6915(03)00018-8
10.1111/bcp.12234
10.3390/biom11020216
10.1021/acssynbio.7b00296
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Keywords In silico
Top-down
Natural products
Toxicity
Bottom-up
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References L Pu (1701_CR35) 2019; 20
JC Dearden (1701_CR4) 2003; 17
S Li (1701_CR27) 2021; 95
S-H Huang (1701_CR15) 2015; 78
N Tsamandouras (1701_CR42) 2015; 79
H Luo (1701_CR29) 2016; 32
M Yang (1701_CR44) 2015; 12
S Ekins (1701_CR9) 2005; 26
ME Manful (1701_CR30) 2023; 142
Z Mozafari (1701_CR31) 2020; 96
GC Fonger (1701_CR12) 2014; 325
L Wang (1701_CR43) 2018; 7
T Tralau (1701_CR41) 2021; 2
1701_CR24
Y Li (1701_CR26) 2016
R Kroes (1701_CR22) 2004; 198
I Lee (1701_CR25) 2018; 19
NA Rivero-Segura (1701_CR37) 2021; 11
RS Thomas (1701_CR40) 2018; 35
V Jakkula (1701_CR17) 2006; 37
A Oulas (1701_CR33) 2017; 20
S Yoo (1701_CR46) 2018; 6
A Hudson (1701_CR16) 2018; 84
KT Rim (1701_CR36) 2020; 12
V Sharma (1701_CR39) 2020; 14
B Palsson (1701_CR34) 2002; 20
LD Díaz (1701_CR6) 2020; 68
Y-C Fang (1701_CR11) 2008; 8
P Ruiz (1701_CR38) 2020; 174
S Dimitrov (1701_CR7) 2016; 27
J An (1701_CR1) 2022; 13
DJ Dix (1701_CR8) 2007; 95
B Devleesschauwer (1701_CR5) 2015; 10
SE Kenny (1701_CR20) 2022; 12
P Zhao (1701_CR47) 2017; 55
1701_CR19
1701_CR13
A Bausch (1701_CR2) 2006; 2
EP Gutiérrez-Grijalva (1701_CR14) 2024; 11
C Kruger (1701_CR23) 2003; 41
X Jiao (1701_CR18) 2021; 90
X Zhou (1701_CR48) 2010; 43
J Fan (1701_CR10) 2019; 7
1701_CR32
M Chen (1701_CR3) 2016; 21
MA Lila (1701_CR28) 2005; 70
K Yang (1701_CR45) 2018; 18
S-S Kim (1701_CR21) 2022; 31
References_xml – volume: 325
  start-page: 209
  year: 2014
  ident: 1701_CR12
  publication-title: Toxicology
  doi: 10.1016/j.tox.2014.09.003
– volume: 20
  start-page: 1
  year: 2019
  ident: 1701_CR35
  publication-title: BMC Pharmacology and Toxicology
  doi: 10.1186/s40360-018-0282-6
– volume: 174
  start-page: 38
  year: 2020
  ident: 1701_CR38
  publication-title: Toxicological Sciences
  doi: 10.1093/toxsci/kfz243
– volume: 6
  start-page: 58106
  year: 2018
  ident: 1701_CR46
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2018.2874089
– volume: 20
  start-page: 806
  year: 2017
  ident: 1701_CR33
  publication-title: Briefings in Bioinformatics
  doi: 10.1093/bib/bbx151
– volume: 26
  start-page: 202
  year: 2005
  ident: 1701_CR9
  publication-title: Trends in Pharmacological Sciences
  doi: 10.1016/j.tips.2005.02.006
– ident: 1701_CR19
  doi: 10.1002/0470857897.ch8
– volume: 95
  start-page: 5
  year: 2007
  ident: 1701_CR8
  publication-title: Toxicological Sciences
  doi: 10.1093/toxsci/kfl103
– volume: 12
  start-page: 363
  year: 2022
  ident: 1701_CR20
  publication-title: Life
  doi: 10.3390/life12030363
– volume: 198
  start-page: 213
  year: 2004
  ident: 1701_CR22
  publication-title: Toxicology
  doi: 10.1016/j.tox.2004.01.028
– volume: 31
  start-page: 399
  year: 2022
  ident: 1701_CR21
  publication-title: Food Science and Biotechnology
  doi: 10.1007/s10068-022-01047-6
– volume: 8
  start-page: 58
  year: 2008
  ident: 1701_CR11
  publication-title: BMC Complementary and Alternative Medicine
  doi: 10.1186/1472-6882-8-58
– volume: 12
  start-page: 191
  year: 2020
  ident: 1701_CR36
  publication-title: Toxicol Environ Health Sci
  doi: 10.1007/s13530-020-00056-4
– ident: 1701_CR24
  doi: 10.1109/NAFOSTED.2017.8108071
– volume: 17
  start-page: 119
  year: 2003
  ident: 1701_CR4
  publication-title: Journal of Computer-Aided Molecular Design
  doi: 10.1023/A:1025361621494
– volume: 78
  start-page: 71
  year: 2015
  ident: 1701_CR15
  publication-title: Food and Chemical Toxicology
  doi: 10.1016/j.fct.2015.01.020
– volume: 20
  start-page: 649
  year: 2002
  ident: 1701_CR34
  publication-title: Nature Biotechnology
  doi: 10.1038/nbt0702-649
– volume: 96
  start-page: 812
  year: 2020
  ident: 1701_CR31
  publication-title: Chemical Biology & Drug Design
  doi: 10.1111/cbdd.13690
– volume: 14
  start-page: 117793222092135
  year: 2020
  ident: 1701_CR39
  publication-title: Bioinformatics and Biology Insights
  doi: 10.1177/1177932220921350
– volume: 11
  start-page: 1393366
  year: 2024
  ident: 1701_CR14
  publication-title: Frontiers in Nutrition
  doi: 10.3389/fnut.2024.1393366
– volume: 95
  start-page: 1683
  year: 2021
  ident: 1701_CR27
  publication-title: Archives of Toxicology
  doi: 10.1007/s00204-021-03023-1
– volume: 55
  start-page: 996
  year: 2017
  ident: 1701_CR47
  publication-title: Clinical Toxicology
  doi: 10.1080/15563650.2017.1333123
– volume: 7
  start-page: 83
  year: 2019
  ident: 1701_CR10
  publication-title: Quantitative Biology
  doi: 10.1007/s40484-019-0172-y
– volume: 35
  start-page: 163
  year: 2018
  ident: 1701_CR40
  publication-title: Altex
  doi: 10.14573/altex.1803011
– volume: 32
  start-page: 2664
  year: 2016
  ident: 1701_CR29
  publication-title: Bioinformatics
  doi: 10.1093/bioinformatics/btw228
– volume: 21
  start-page: 648
  year: 2016
  ident: 1701_CR3
  publication-title: Drug Discovery Today
  doi: 10.1016/j.drudis.2016.02.015
– year: 2016
  ident: 1701_CR26
  publication-title: Evidence-Based Complementary and Alternative Medicine
  doi: 10.1155/2016/6012761
– ident: 1701_CR13
  doi: 10.1201/9781003075363-20
– volume: 68
  start-page: 103896
  year: 2020
  ident: 1701_CR6
  publication-title: Journal of Functional Foods
  doi: 10.1016/j.jff.2020.103896
– volume: 90
  start-page: 107402
  year: 2021
  ident: 1701_CR18
  publication-title: Computational Biology and Chemistry
  doi: 10.1016/j.compbiolchem.2020.107402
– ident: 1701_CR32
– volume: 2
  start-page: 231
  year: 2006
  ident: 1701_CR2
  publication-title: Nature Physics
  doi: 10.1038/nphys260
– volume: 10
  start-page: e0142498
  year: 2015
  ident: 1701_CR5
  publication-title: PloS One
  doi: 10.1371/journal.pone.0142498
– volume: 12
  start-page: 3691
  year: 2015
  ident: 1701_CR44
  publication-title: Molecular Pharmaceutics
  doi: 10.1021/acs.molpharmaceut.5b00465
– volume: 142
  start-page: 104191
  year: 2023
  ident: 1701_CR30
  publication-title: Trends in Food Science & Technology
  doi: 10.1016/j.tifs.2023.104191
– volume: 27
  start-page: 203
  year: 2016
  ident: 1701_CR7
  publication-title: SAR and QSAR in Environmental Research
  doi: 10.1080/1062936X.2015.1136680
– volume: 19
  start-page: 9
  year: 2018
  ident: 1701_CR25
  publication-title: BMC Bioinformatics
  doi: 10.1186/s12859-018-2199-x
– volume: 18
  start-page: 17
  year: 2018
  ident: 1701_CR45
  publication-title: BMC Medical Informatics and Decision Making
  doi: 10.1186/s12911-018-0592-z
– volume: 43
  start-page: 650
  year: 2010
  ident: 1701_CR48
  publication-title: Journal of Biomedical Informatics
  doi: 10.1016/j.jbi.2010.01.002
– volume: 70
  start-page: R20
  year: 2005
  ident: 1701_CR28
  publication-title: Journal of Food Science
  doi: 10.1111/j.1365-2621.2005.tb09054.x
– volume: 84
  start-page: 613
  year: 2018
  ident: 1701_CR16
  publication-title: Planta Medica
  doi: 10.1055/a-0605-3786
– volume: 13
  start-page: 961012
  year: 2022
  ident: 1701_CR1
  publication-title: Frontiers in Pharmacology
  doi: 10.3389/fphar.2022.961012
– volume: 2
  start-page: 463
  year: 2021
  ident: 1701_CR41
  publication-title: Nature Food
  doi: 10.1038/s43016-021-00316-7
– volume: 41
  start-page: 793
  year: 2003
  ident: 1701_CR23
  publication-title: Food and Chemical Toxicology
  doi: 10.1016/S0278-6915(03)00018-8
– volume: 37
  start-page: 3
  year: 2006
  ident: 1701_CR17
  publication-title: School of EECS, Washington State University
– volume: 79
  start-page: 48
  year: 2015
  ident: 1701_CR42
  publication-title: British Journal of Clinical Pharmacology
  doi: 10.1111/bcp.12234
– volume: 11
  start-page: 216
  year: 2021
  ident: 1701_CR37
  publication-title: Biomolecules
  doi: 10.3390/biom11020216
– volume: 7
  start-page: 462
  year: 2018
  ident: 1701_CR43
  publication-title: ACS Synthetic Biology
  doi: 10.1021/acssynbio.7b00296
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Snippet Despite the increasing global demand for functional foods, the challenges associated with bioactive natural food products due to their complex composition...
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SubjectTerms Biocompatibility
Biological activity
Biotechnology
Composition effects
computer simulation
Food composition
Food safety
Food science
Food selection
Functional foods & nutraceuticals
Machine learning
Natural & organic foods
Natural products
Physiological effects
Predictions
Side effects
Toxicity
Toxicity testing
식품과학
Title Computational approaches to predict the toxicity of bioactive natural products: a mini review of methodologies
URI https://www.ncbi.nlm.nih.gov/pubmed/39944664
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Volume 34
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