Combination of furosemide, gold, and dopamine as a potential therapy for breast cancer.
Breast cancer
Drug combination
Drug repositioning
MD Simulation
Nanoparticles
Journal
Functional & integrative genomics
ISSN: 1438-7948
Titre abrégé: Funct Integr Genomics
Pays: Germany
ID NLM: 100939343
Informations de publication
Date de publication:
21 Mar 2023
21 Mar 2023
Historique:
received:
27
07
2022
accepted:
01
03
2023
revised:
28
02
2023
entrez:
21
3
2023
pubmed:
22
3
2023
medline:
24
3
2023
Statut:
epublish
Résumé
Breast cancer is one of the leading causes of death in women worldwide. Initially, it develops in the epithelium of the ducts or lobules of the breast glandular tissues with limited growth and the potential to metastasize. It is a highly heterogeneous malignancy; however, the common molecular mechanisms could help identify new targeted drugs for treating its subtypes. This study uses computational drug repositioning approaches to explore fresh drug candidates for breast cancer treatment. We also implemented reversal gene expression and gene expression-based signatures to explore novel drug candidates computationally. The drug activity profiles and related gene expression changes were acquired from the DrugBank, PubChem, and LINCS databases, and then in silico drug screening, molecular dynamics (MD) simulation, replica exchange MD simulations, and simulated annealing molecular dynamics (SAMD) simulations were conducted to discover and verify the valid drug candidates. We have found that compounds like furosemide, gold, and dopamine showed significant outcomes. Furthermore, the expression of genes related to breast cancer was observed to be reversed by these shortlisted drugs. Therefore, we postulate that combining furosemide, gold, and dopamine would be a potential combination therapy measurement for breast cancer patients.
Identifiants
pubmed: 36943579
doi: 10.1007/s10142-023-01007-1
pii: 10.1007/s10142-023-01007-1
doi:
Substances chimiques
Dopamine
VTD58H1Z2X
Furosemide
7LXU5N7ZO5
Gold
7440-57-5
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
94Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Références
Adey A et al (2013) The haplotype-resolved genome and epigenome of the aneuploid HeLa cancer cell line. Nature 500:207–211
pubmed: 23925245
pmcid: 3740412
Barretina J et al (2012) The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483:603–607
pubmed: 22460905
pmcid: 3320027
Barretina J et al (2019) Addendum: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 565:E5–E6
pubmed: 30559381
Barrett T, Edgar R (2006) Mining microarray data at NCBIʼs Gene Expression Omnibus (GEO)*. Methods Mol Biol 338:175–190
pubmed: 16888359
pmcid: 1619899
Bouhaddou M et al (2016) Drug response consistency in CCLE and CGP. Nature 540:E9–E10
pubmed: 27905419
pmcid: 5554885
Wishart DS et al (2008) DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res 36:D901–D906
pubmed: 18048412
Bowers KJ et al. (2006) Scalable algorithms for molecular dynamics simulations on commodity clusters. In: conference on high performance computing (supercomputing)
Chen W et al (2016) Cancer statistics in China, 2015. CA Cancer J Clin 66:115–132
pubmed: 26808342
Chen I-J, Foloppe N (2013) Tackling the conformational sampling of larger flexible compounds and macrocycles in pharmacology and drug discovery. Bioorg Med Chem 21:7898–7920
pubmed: 24184215
Chong CR, Sullivan DJ Jr (2007) New uses for old drugs. Nature 448:645–646
pubmed: 17687303
Xue H, Li J, Xie H, Wang Y (2018) Review of drug repositioning approaches and resources. Int J Biol Sci 14:1232–1244
pubmed: 30123072
pmcid: 6097480
DiMasi JA, Hansen RW, Grabowski HG (2003) The price of innovation: new estimates of drug development costs. J Health Econ 22:151–185
pubmed: 12606142
Doucet N, Pelletier JN (2007) Simulated annealing exploration of an active‐site tyrosine in TEM‐1β‐lactamase suggests the existence of alternate conformations. Proteins 69:340–348
Dovrolis N, Kolios G, Spyrou G, Maroulakou I (2017) Laying in silico pipelines for drug repositioning: a paradigm in ensemble analysis for neurodegenerative diseases. Drug Discov Today 22:805–813
pubmed: 28363518
Taqi MM, Waseem D, Ismatullah H, Haider SA, Faisal M (2016) In silico transcriptional regulation and functional analysis of dengue shock syndrome associated SNPs in PLCE1 and MICB genes. Funct Integr Genomics 16:335–345
pubmed: 27038471
pmcid: 4850189
Sirota M et al. (2011) Discovery and preclinical validation of drug indications using compendia of public gene expression data. Sci Transl Med 3:96ra77
Duan Q et al (2014) LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures. Nucleic Acids Res 42:W449-460
pubmed: 24906883
pmcid: 4086130
Gagnon JK, Law SM, Brooks CL III (2016) Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM. J Comput Chem 37:753–762
pubmed: 26691274
Giuliano AE, et al. (2017) Breast cancer-major changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA Cancer J Clin 67:290–303
Global Burden of Disease Cancer C et al. (2017) Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015: a systematic analysis for the global burden of disease study. JAMA Oncol 3:524–548
Golestan S, Soltani BM, Jafarzadeh M, Ghaemi Z, Nafisi N (2023) LINC02381 suppresses cell proliferation and promotes apoptosis via attenuating IGF1R/PI3K/AKT signaling pathway in breast cancer. Funct Integr Genomics 23:40
pubmed: 36648607
Tseng GC, Ghosh D, Feingold E (2012) Comprehensive literature review and statistical considerations for microarray meta-analysis. Nucleic Acids Res 40:3785–3799
pubmed: 22262733
pmcid: 3351145
Guo Z, Mohanty U, Noehre J, Sawyer TK, Sherman W, Krilov G (2010) Probing the alpha-helical structural stability of stapled p53 peptides: molecular dynamics simulations and analysis. Chem Biol Drug Des 75:348–359
pubmed: 20331649
Harvell DM et al (2013) Genomic signatures of pregnancy-associated breast cancer epithelia and stroma and their regulation by estrogens and progesterone. Horm Cancer 4:140–153
pubmed: 23479404
Hess B, Bekker H, Berendsen HJ, Fraaije JG (1997) LINCS: a linear constraint solver for molecular simulations. J Comput Chem 18:1463–1472
Huang CS, Lin CH, Lu YS, Shen CY (2010) Unique features of breast cancer in Asian women–breast cancer in Taiwan as an example. J Steroid Biochem Mol Biol 118:300–303
pubmed: 20045728
Huang G, Li J, Wang P, Li W (2017) A review of computational drug repositioning approaches. Comb Chem High Throughput Screen
Iorio F, Rittman T, Ge H, Menden M, Saez-Rodriguez J (2013) Transcriptional data: a new gateway to drug repositioning? Drug Discov Today 18:350–357
pubmed: 22897878
pmcid: 3625109
Jao CC, Hegde BG, Chen J, Haworth IS, Langen R (2008) Structure of membrane-bound α-synuclein from site-directed spin labeling and computational refinement. Proc Natl Acad Sci 105:19666–19671
pubmed: 19066219
pmcid: 2605001
Jiang Y, Wang M (2010) Personalized medicine in oncology: tailoring the right drug to the right patient. Biomark Med 4:523–533
pubmed: 20701441
Kang DD, Sibille E, Kaminski N, Tseng GC (2012) MetaQC: objective quality control and inclusion/exclusion criteria for genomic meta-analysis. Nucleic Acids Res 40:e15
pubmed: 22116060
Keenan AB et al (2018) The library of integrated network-based cellular signatures NIH program: system-level cataloging of human cells response to perturbations. Cell Syst 6:13–24
pubmed: 29199020
Kim S et al (2016) PubChem substance and compound databases. Nucleic Acids Res 44:D1202-1213
pubmed: 26400175
Kirkpatrick S, Gelatt CD Jr, Vecchi MP (1983) Optimization by Simulated Annealing Science 220:671–680
pubmed: 17813860
Koleti A et al (2018) Data Portal for the Library of Integrated Network-based Cellular Signatures (LINCS) program: integrated access to diverse large-scale cellular perturbation response data. Nucleic Acids Res 46:D558–D566
pubmed: 29140462
Lang JE et al (2015) Expression profiling of circulating tumor cells in metastatic breast cancer. Breast Cancer Res Treat 149:121–131
pubmed: 25432738
Law V et al (2014) DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res 42:D1091-1097
pubmed: 24203711
Lee SH, van der Werf JH, Hayes BJ, Goddard ME, Visscher PM (2008) Predicting unobserved phenotypes for complex traits from whole-genome SNP data. PLoS Genet 4:e1000231
pubmed: 18949033
pmcid: 2565502
Lee J, Gross SP, Lee J (2012) Modularity optimization by conformational space annealing. Phys Rev E 85:056702
Li WX et al (2017) Comprehensive tissue-specific gene set enrichment analysis and transcription factor analysis of breast cancer by integrating 14 gene expression datasets. Oncotarget 8:6775–6786
pubmed: 28036274
Simon R, Roychowdhury S (2013) Implementing personalized cancer genomics in clinical trials. Nat Rev Drug Discov 12:358–369
pubmed: 23629504
Li J, Zheng S, Chen B, Butte AJ, Swamidass SJ, Lu Z (2016) A survey of current trends in computational drug repositioning. Brief Bioinform 17:2–12
pubmed: 25832646
Li D, Chen P, Shi T, Mehmood A, Qiu J (2021) HD5 and LL-37 inhibit SARS-CoV and SARS-CoV-2 binding to human ACE2 by molecular simulation. Interdisciplinary Sciences: Computational Life Sciences 13:766–777
pubmed: 34363600
Shivakumar D, Williams J, Wu Y, Damm W, Shelley J, Sherman W (2010) Prediction of absolute solvation free energies using molecular dynamics free energy perturbation and the OPLS force field. J Chem Theory Comput 6:1509–1519
pubmed: 26615687
Wang Y, Xiao J, Suzek TO, Zhang J, Wang J, Bryant SH (2009) PubChem: a public information system for analyzing bioactivities of small molecules. Nucleic Acids Res 37:W623–W633
pubmed: 19498078
pmcid: 2703903
Li M, Zhao Y, Li H, Deng X, Sheng M (2023) Application value of circulating LncRNA in diagnosis, treatment, and prognosis of breast cancer. Funct Integr Genomics 23:61
pubmed: 36792760
Wang L, Wang Y, Bi J (2022) In silico development and experimental validation of a novel 7-gene signature based on PI3K pathway-related genes in bladder cancer. Funct Integr Genomics 22:797–811
pubmed: 35896848
pmcid: 9550739
Locke WJ, Clark SJ (2012) Epigenome remodelling in breast cancer: insights from an early in vitro model of carcinogenesis. Breast Cancer Res 14:215
pubmed: 23168266
pmcid: 4053120
Lu S, Li J, Song C, Shen K, Tseng GC (2010) Biomarker detection in the integration of multiple multi-class genomic studies. Bioinformatics 26:333–340
pubmed: 19965884
Mediratta K, El-Sahli S, D'Costa V, Wang L. (2020) Current progresses and challenges of immunotherapy in triple-negative breast cancer. Cancers 12
Mehla K, Ramana J (2017) Surface proteome mining for identification of potential vaccine candidates against Campylobacter jejuni: an in silico approach. Funct Integr Genomics 17:27–37
pubmed: 27778110
Mehmood A, Khan MT, Kaushik AC, Khan AS, Irfan M, Wei D-Q (2019) Structural dynamics behind clinical mutants of PncA-Asp12Ala, Pro54Leu, and His57Pro of Mycobacterium tuberculosis associated with pyrazinamide resistance. Frontiers in Bioengineering and Biotechnology 7:404
pubmed: 31921809
pmcid: 6914729
Mehmood A, Nawab S, Jin Y, Hassan H, Kaushik AC, Wei D-Q (2023a) Ranking breast cancer drugs and biomarkers identification using machine learning and pharmacogenomics. ACS Pharmacol Translat Sci
Mehmood A, Nawab S, Jin Y, Kaushik AC, Wei D-Q (2023b) Mutational impacts on the N and C terminal domains of the MUC5B protein: a transcriptomics and structural biology study. ACS Omega
Mehmood A, Kaushik AC, Wang Q, Li C-D, Wei D-Q (2021) Bringing structural implications and deep learning-based drug identification for KRAS mutants. J Chem Inf Model 61:571–586
pubmed: 33513018
Mehmood A, Nawab S, Wang Y, Kaushik AC, Wei D-Q (2022) Discovering potent inhibitors against the Mpro of the SARS-CoV-2. A medicinal chemistry approach. Comp Biol Med 143:105235
Mishra A, Verma M (2010) Cancer biomarkers: are we ready for the prime time? Cancers (basel) 2:190–208
pubmed: 24281040
Mobasheri MB et al (2015) Transcriptome analysis of the cancer/testis genes, DAZ1, AURKC, and TEX101, in breast tumors and six breast cancer cell lines. Tumour Biol 36:8201–8206
pubmed: 25994570
Morris GM et al (2009) AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem 30:2785–2791
pubmed: 19399780
pmcid: 2760638
Wang X, Lin Y, Song C, Sibille E, Tseng GC (2012) Detecting disease-associated genes with confounding variable adjustment and the impact on genomic meta-analysis: with application to major depressive disorder. BMC Bioinformatics 13:52
pubmed: 22458711
pmcid: 3342232
Morris GM et al (2009) AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem 30:2785–2791
pubmed: 19399780
pmcid: 2760638
Nederlof I et al (2019) Comprehensive evaluation of methods to assess overall and cell-specific immune infiltrates in breast cancer. Breast Cancer Res 21:151
pubmed: 31878981
pmcid: 6933637
Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A (2015) Global cancer statistics, 2012. CA Cancer J Clin 65:87–108
pubmed: 25651787
Nogales-Cadenas R et al (2016) MicroRNA expression and gene regulation drive breast cancer progression and metastasis in PyMT mice. Breast Cancer Res 18:75
pubmed: 27449149
pmcid: 4957901
Ober U et al (2012) Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster. PLoS Genet 8:e1002685
pubmed: 22570636
pmcid: 3342952
Oliver S (2000) Guilt-by-association goes global. Nature 403:601–603
pubmed: 10688178
O’Shaughnessy J (2005) Extending survival with chemotherapy in metastatic breast cancer. Oncologist 10(Suppl 3):20–29
pubmed: 16368868
Pan Y, Zhang Q, Zhang H, Kong F (2023) Prognostic and immune microenvironment analysis of cuproptosis-related LncRNAs in breast cancer. Funct Integr Genomics 23:38
pubmed: 36640225
Reddy SM et al (2018) Long-term survival outcomes of triple-receptor negative breast cancer survivors who are disease free at 5 years and relationship with low hormone receptor positivity. Br J Cancer 118:17–23
pubmed: 29235566
Sawyers CL (2008) The cancer biomarker problem. Nature 452:548–552
pubmed: 18385728
Schrödinger L, DeLano W (2020) The PyMOL Molecular Graphics System, Version 2.0; Schrödinger LLC: New York, NY, USA, 2020
Seashore-Ludlow B et al (2015) Harnessing connectivity in a large-scale small-molecule sensitivity dataset. Cancer Discov 5:1210–1223
pubmed: 26482930
pmcid: 4631646