Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs

Suleiman A Khan; Ali Faisal; John Patrick Mpindi; Juuso A Parkkinen; Tuomo Kalliokoski; Antti Poso; Olli P Kallioniemi; Krister Wennerberg; Samuel Kaski

doi:10.1186/1471-2105-13-112

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs

Suleiman A Khan, Ali Faisal, John Patrick Mpindi, Juuso A Parkkinen, Tuomo Kalliokoski, Antti Poso, Olli P Kallioniemi, Krister Wennerberg, Samuel Kaski

15 Citationer (Scopus)

Abstract

BACKGROUND: Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile.

RESULTS: Integrated analysis of both the chemical and biological space was more informative than either dataset alone in predicting drug similarity as measured by shared protein targets. We identified ten major components that link distinct VolSurf chemical features across multiple compounds to specific cellular responses. For example, component 2 (hydrophobic properties) strongly linked to DNA damage response, while component 3 (hydrogen bonding) was associated with metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides.

CONCLUSIONS: In summary, our approach identified several novel links between specific chemical structure properties and distinct biological responses in cells incubated with these drugs. Importantly, the analysis focused on chemical-biological properties that emerge across multiple drugs. The decoding of such systematic relationships is necessary to build better models of drug effects, including unanticipated types of molecular properties having strong biological effects.

Originalsprog	Engelsk
Tidsskrift	BMC Bioinformatics
Vol/bind	13
Sider (fra-til)	112
ISSN	1471-2105
DOI	https://doi.org/10.1186/1471-2105-13-112
Status	Udgivet - 30 maj 2012
Udgivet eksternt	Ja

FN’s Verdensmål

Dette resultat bidrager til følgende verdensmål

Adgang til dokumentet

10.1186/1471-2105-13-112Licens: CC BY

1471-2105-13-112Forlagets udgivne version, 3,78 MBLicens: CC BY

Citationsformater

@article{fadab74143104fe6bd5533f298873f9c,

title = "Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs",

abstract = "BACKGROUND: Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile.RESULTS: Integrated analysis of both the chemical and biological space was more informative than either dataset alone in predicting drug similarity as measured by shared protein targets. We identified ten major components that link distinct VolSurf chemical features across multiple compounds to specific cellular responses. For example, component 2 (hydrophobic properties) strongly linked to DNA damage response, while component 3 (hydrogen bonding) was associated with metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides.CONCLUSIONS: In summary, our approach identified several novel links between specific chemical structure properties and distinct biological responses in cells incubated with these drugs. Importantly, the analysis focused on chemical-biological properties that emerge across multiple drugs. The decoding of such systematic relationships is necessary to build better models of drug effects, including unanticipated types of molecular properties having strong biological effects.",

keywords = "Antineoplastic Agents/chemistry, Biomarkers, Pharmacological, Gene Expression Profiling/statistics & numerical data, Genome, Human/drug effects, Humans, Neoplasms/genetics, Oligonucleotide Array Sequence Analysis, Structure-Activity Relationship, Systems Biology/methods, Transcriptome",

author = "Khan, {Suleiman A} and Ali Faisal and Mpindi, {John Patrick} and Parkkinen, {Juuso A} and Tuomo Kalliokoski and Antti Poso and Kallioniemi, {Olli P} and Krister Wennerberg and Samuel Kaski",

year = "2012",

month = may,

day = "30",

doi = "10.1186/1471-2105-13-112",

language = "English",

volume = "13",

pages = "112",

journal = "B M C Bioinformatics",

issn = "1471-2105",

publisher = "BioMed Central Ltd.",

}

TY - JOUR

T1 - Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs

AU - Khan, Suleiman A

AU - Faisal, Ali

AU - Mpindi, John Patrick

AU - Parkkinen, Juuso A

AU - Kalliokoski, Tuomo

AU - Poso, Antti

AU - Kallioniemi, Olli P

AU - Wennerberg, Krister

AU - Kaski, Samuel

PY - 2012/5/30

Y1 - 2012/5/30

N2 - BACKGROUND: Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile.RESULTS: Integrated analysis of both the chemical and biological space was more informative than either dataset alone in predicting drug similarity as measured by shared protein targets. We identified ten major components that link distinct VolSurf chemical features across multiple compounds to specific cellular responses. For example, component 2 (hydrophobic properties) strongly linked to DNA damage response, while component 3 (hydrogen bonding) was associated with metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides.CONCLUSIONS: In summary, our approach identified several novel links between specific chemical structure properties and distinct biological responses in cells incubated with these drugs. Importantly, the analysis focused on chemical-biological properties that emerge across multiple drugs. The decoding of such systematic relationships is necessary to build better models of drug effects, including unanticipated types of molecular properties having strong biological effects.

AB - BACKGROUND: Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile.RESULTS: Integrated analysis of both the chemical and biological space was more informative than either dataset alone in predicting drug similarity as measured by shared protein targets. We identified ten major components that link distinct VolSurf chemical features across multiple compounds to specific cellular responses. For example, component 2 (hydrophobic properties) strongly linked to DNA damage response, while component 3 (hydrogen bonding) was associated with metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides.CONCLUSIONS: In summary, our approach identified several novel links between specific chemical structure properties and distinct biological responses in cells incubated with these drugs. Importantly, the analysis focused on chemical-biological properties that emerge across multiple drugs. The decoding of such systematic relationships is necessary to build better models of drug effects, including unanticipated types of molecular properties having strong biological effects.

KW - Antineoplastic Agents/chemistry

KW - Biomarkers, Pharmacological

KW - Gene Expression Profiling/statistics & numerical data

KW - Genome, Human/drug effects

KW - Humans

KW - Neoplasms/genetics

KW - Oligonucleotide Array Sequence Analysis

KW - Structure-Activity Relationship

KW - Systems Biology/methods

KW - Transcriptome

U2 - 10.1186/1471-2105-13-112

DO - 10.1186/1471-2105-13-112

M3 - Journal article

C2 - 22646858

SN - 1471-2105

VL - 13

SP - 112

JO - B M C Bioinformatics

JF - B M C Bioinformatics

ER -

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs

Abstract

FN’s Verdensmål

Adgang til dokumentet

Fingeraftryk

Citationsformater