Multi-dimensional computational pipeline for large-scale deep screening of compound effect assessment: an in silico case study on ageing-related compounds.


Journal

NPJ systems biology and applications
ISSN: 2056-7189
Titre abrégé: NPJ Syst Biol Appl
Pays: England
ID NLM: 101677786

Informations de publication

Date de publication:
2019
Historique:
received: 22 05 2018
accepted: 23 09 2019
entrez: 5 12 2019
pubmed: 5 12 2019
medline: 28 4 2020
Statut: epublish

Résumé

Designing alternative approaches to efficiently screen chemicals on the efficacy landscape is a challenging yet indispensable task in the current compound profiling methods. Particularly, increasing regulatory restrictions underscore the need to develop advanced computational pipelines for efficacy assessment of chemical compounds as alternative means to reduce and/or replace in vivo experiments. Here, we present an innovative computational pipeline for large-scale assessment of chemical compounds by analysing and clustering chemical compounds on the basis of multiple dimensions-structural similarity, binding profiles and their network effects across pathways and molecular interaction maps-to generate testable hypotheses on the pharmacological landscapes as well as identify potential mechanisms of efficacy on phenomenological processes. Further, we elucidate the application of the pipeline on a screen of anti-ageing-related compounds to cluster the candidates based on their structure, docking profile and network effects on fundamental metabolic/molecular pathways associated with the cell vitality, highlighting emergent insights on compounds activities based on the multi-dimensional deep screen pipeline.

Identifiants

pubmed: 31798962
doi: 10.1038/s41540-019-0119-y
pii: 119
pmc: PMC6879499
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

42

Informations de copyright

© The Author(s) 2019.

Déclaration de conflit d'intérêts

Competing interestsThe authors declare no competing interests.

Références

Nature. 2010 Mar 25;464(7288):504-12
pubmed: 20336132
Mt Sinai J Med. 2003 Jan;70(1):3-22
pubmed: 12516005
Biochim Biophys Acta Gen Subj. 2017 Sep;1861(9):2250-2260
pubmed: 28602514
PLoS One. 2015 Feb 03;10(2):e0115341
pubmed: 25647160
Biochem Biophys Res Commun. 2013 Apr 19;433(4):420-5
pubmed: 23523798
Cell Cycle. 2013 Nov 15;12(22):3483-9
pubmed: 24189526
Bioinformatics. 2002 Feb;18(2):251-60
pubmed: 11847073
Cell. 2013 Jun 6;153(6):1194-217
pubmed: 23746838
Cell. 2011 Sep 2;146(5):682-95
pubmed: 21884931
Nat Rev Drug Discov. 2013 Dec;12(12):931-47
pubmed: 24287781
Adv Exp Med Biol. 2017;1002:153-188
pubmed: 28600786
J Clin Aesthet Dermatol. 2017 Jul;10(7):14-17
pubmed: 29104718
Free Radic Res. 2008 Sep;42(9):778-88
pubmed: 18785048
J Mol Graph Model. 2007 Jul;26(1):198-212
pubmed: 16860582
Antioxid Redox Signal. 2013 Feb 10;18(5):481-90
pubmed: 22866967
Bioorg Med Chem. 2010 Jul 15;18(14):5352-66
pubmed: 20558073
Clin Interv Aging. 2006;1(4):327-48
pubmed: 18046911
Math Biosci. 2002 Mar;176(1):71-98
pubmed: 11867085
Nucleic Acids Res. 2015 Jan;43(Database issue):D447-52
pubmed: 25352553
Nature. 2009 Jul 16;460(7253):392-5
pubmed: 19587680
J Am Acad Dermatol. 2018 Jan;78(1):29-39.e7
pubmed: 29146147
Nat Med. 2015 Dec;21(12):1406-15
pubmed: 26646497
J Mol Biol. 1997 Apr 4;267(3):727-48
pubmed: 9126849
Aging (Albany NY). 2013 May;5(5):330-1
pubmed: 23660016
Transl Res. 2014 May;163(5):456-65
pubmed: 24316383
Exp Dermatol. 2012 May;21(5):398-400
pubmed: 22509841
PLoS One. 2012;7(10):e47933
pubmed: 23110134
Nat Rev Drug Discov. 2004 Aug;3(8):711-5
pubmed: 15286737
Bioinformatics. 2013 Nov 1;29(21):2792-4
pubmed: 23962615
Biomed Res Int. 2013;2013:742835
pubmed: 24171171
ALTEX. 2018;35(1):124-126
pubmed: 29374440
Wiley Interdiscip Rev Syst Biol Med. 2015 Jul-Aug;7(4):141-61
pubmed: 25891169
Nature. 2000 Jul 27;406(6794):378-82
pubmed: 10935628
Nat Chem Biol. 2008 Nov;4(11):682-90
pubmed: 18936753
Curr Biol. 2006 Feb 7;16(3):296-300
pubmed: 16461283
Mol Biol Cell. 2015 Dec 15;26(25):4524-31
pubmed: 26668170
Nucleic Acids Res. 2000 Jan 1;28(1):235-42
pubmed: 10592235
Oxid Med Cell Longev. 2017;2017:9175806
pubmed: 28808499
Eur J Dermatol. 2008 Jan-Feb;18(1):36-40
pubmed: 18086587
Aging Cell. 2017 Feb;16(1):104-112
pubmed: 27683245
Aging Cell. 2018 Dec;17(6):e12830
pubmed: 30192051
Annu Rev Physiol. 2013;75:621-44
pubmed: 23190075
Eur J Dermatol. 2011 May-Jun;21(3):359-70
pubmed: 21609902
BMC Bioinformatics. 2013 Apr 11;14:124
pubmed: 23578321
Bioinformatics. 2008 Jul 1;24(13):i366-74
pubmed: 18586736
Genome Res. 2003 Nov;13(11):2498-504
pubmed: 14597658
J Comput Chem. 2010 Jan 30;31(2):455-61
pubmed: 19499576
J Clin Invest. 2013 Mar;123(3):980-9
pubmed: 23454761
J Cell Biol. 1991 Nov;115(3):851-9
pubmed: 1655814
Can J Physiol Pharmacol. 2010 Mar;88(3):273-84
pubmed: 20393592
N Engl J Med. 2011 Jun 9;364(23):2235-44
pubmed: 21651395
PLoS One. 2011;6(10):e25480
pubmed: 21998662
Nat Cell Biol. 2011 Sep 02;13(9):1016-23
pubmed: 21892142
PLoS One. 2013 Dec 31;8(12):e83922
pubmed: 24391846
Cell. 2010 Jul 9;142(1):9-14
pubmed: 20603007
ACS Med Chem Lett. 2014 Mar 06;5(5):453-5
pubmed: 24900858
Pathol Biol (Paris). 2015 Dec;63(6):272-6
pubmed: 26416405
J Med Chem. 2016 May 12;59(9):4103-20
pubmed: 26913380
Nucleic Acids Res. 2016 Jul 8;44(W1):W507-13
pubmed: 27131384
J Biol Chem. 1994 Dec 30;269(52):32821-7
pubmed: 7806506
J Chem Inf Model. 2007 Jul-Aug;47(4):1564-71
pubmed: 17552493
Free Radic Biol Med. 2009 Nov 1;47(9):1304-9
pubmed: 19666107
Cell Death Dis. 2014 Dec 04;5:e1552
pubmed: 25476900
Arch Dermatol Res. 2015 May;307(4):351-64
pubmed: 25740152
Proc Natl Acad Sci U S A. 2010 Jul 27;107(30):13193-4
pubmed: 20647386
Nature. 2001 May 3;411(6833):41-2
pubmed: 11333967
Bioinformatics. 2006 Jun 15;22(12):1540-2
pubmed: 16595560
Front Pharmacol. 2011 Jun 30;2:33
pubmed: 21772821
Mayo Clin Proc. 2000 Jan;75 Suppl:S3-8; discussion S8-9
pubmed: 10959208
Cell Metab. 2010 Jun 9;11(6):554-65
pubmed: 20519126
Pharmacol Rev. 2013 Dec 31;66(1):334-95
pubmed: 24381236
Arch Toxicol. 2011 May;85(5):367-485
pubmed: 21533817
Subcell Biochem. 2012;57:101-21
pubmed: 22094419
Dermatoendocrinol. 2012 Jul 1;4(3):308-19
pubmed: 23467476
PLoS One. 2010 Jan 18;5(1):e8758
pubmed: 20090912
Clin Cosmet Investig Dermatol. 2015 Sep 02;8:463-70
pubmed: 26366101
Nat Rev Drug Discov. 2007 Mar;6(3):202-10
pubmed: 17318209
Cell Metab. 2016 Jun 14;23(6):1060-1065
pubmed: 27304507
FEBS J. 2013 Dec;280(23):5957-80
pubmed: 23552054

Auteurs

Vipul Gupta (V)

1The Systems Biology Institute, Tokyo, Japan.

Alina Crudu (A)

L'Oréal Research and Innovation, Aulnay-sous-Bois, France.

Yukiko Matsuoka (Y)

1The Systems Biology Institute, Tokyo, Japan.

Samik Ghosh (S)

1The Systems Biology Institute, Tokyo, Japan.

Roger Rozot (R)

L'Oréal Research and Innovation, Aulnay-sous-Bois, France.

Xavier Marat (X)

L'Oréal Research and Innovation, Aulnay-sous-Bois, France.

Sibylle Jäger (S)

L'Oréal Research and Innovation, Aulnay-sous-Bois, France.

Hiroaki Kitano (H)

1The Systems Biology Institute, Tokyo, Japan.
3Okinawa Institute of Science and Technology, Okinawa, Japan.

Lionel Breton (L)

L'Oréal Research and Innovation, Aulnay-sous-Bois, France.

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Classifications MeSH