1.
2.
3.
4.
5.
6.
7.
Wilder-Smith, A. Can dengue virus be sexually transmitted? J. Travel Med. 2019, 26, 1195–1982. [CrossRef]
[PubMed]
Gibbons, R.V.; Vaughn, D.W. Dengue: An escalating problem. BMJ 2002, 324, 1563–1566. [CrossRef]
World Health Organisation. Dengue and Dengue Haemorrhagic Fever; World Health Organisation: Geneva,
Switzerland, 2002.
Guzman, M.G.; Gubler, D.J.; Izquierdo, A.; Martinez, E.; Halstead, S.B. Dengue infection. Nat. Rev. Dis.
Primers 2016, 2, 16055. [CrossRef] [PubMed]
Disease, T.V.-B. Dengue Situation in Thailand. 2017. Available online: http://www.thaivbd.org/n/dengues/
view/587 (accessed on 5 March 2017).
Rodriguez, R.C.; Carrasquilla, G.; Porras-Ramírez, A.; Galera-Gelvez, K.; Yescas, J.G.L.; Rueda-Gallardo, J.A.
The Burden of Dengue and the Financial Cost to Colombia, 2010-2012. Am. J. Trop. Med. Hyg. 2016, 94,
1065–1072. [CrossRef] [PubMed]
Yacoub, S.; Farrar, J. 15-Dengue, in Manson’s Tropical Infectious Diseases, 23th ed.; Farrar, J., Hotez, P.J.,
Junghanss, T., Kang, G., Lalloo, D., White, N.J., Eds.; W.B. Saunders: London, UK, 2014; pp. 162–170.e2.
Molecules 2020, 25, 1883
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
14 of 18
Halstead, S.; Wilder-Smith, A. Severe dengue in travellers: Pathogenesis, risk and clinical management.
J. Travel Med. 2019, 26, 1195–1982. [CrossRef] [PubMed]
Guzman, M.G.; Alvarez, M.; Halstead, S.B. Secondary infection as a risk factor for dengue hemorrhagic
fever/dengue shock syndrome: An historical perspective and role of antibody-dependent enhancement of
infection. Arch. Virol. 2013, 158, 1445–1459. [CrossRef]
Rey, F.A.; Stiasny, K.; Vaney, M.; Dellarole, M.; Heinz, F.X. The bright and the dark side of human antibody
responses to flaviviruses: Lessons for vaccine design. EMBO Rep. 2017, 19, 206–224. [CrossRef] [PubMed]
Rothman, A.L. Immunology and Immunopathogenesis of Dengue Disease, in Advances in Virus Research; Academic
Press: Cambridge, MA, USA, 2003; pp. 397–419.
Normile, D. Dengue vaccine trial poses public health quandary. Sci. 2014, 345, 367–368. [CrossRef] [PubMed]
The Lancet Infectious, D. The dengue vaccine dilemma. Lancet Infect. Dis. 2018, 18, 123. [CrossRef]
Boonyasuppayakorn, S.; Reichert, E.D.; Manzano, M.; Nagarajan, K.; Padmanabhan, R. Amodiaquine, an
antimalarial drug, inhibits dengue virus type 2 replication and infectivity. Antivir. Res. 2014, 106, 125–134.
[CrossRef] [PubMed]
Byrd, C.M.; Dai, N.; Grosenbach, U.W.; Berhanu, A.; Jones, K.F.; Cardwell, K.B.; Schneider, C.; Wineinger, K.A.;
Page, J.M.; Harver, C.; et al. A Novel Inhibitor of Dengue Virus Replication That Targets the Capsid Protein.
Antimicrob. Agents Chemother. 2012, 57, 15–25. [CrossRef] [PubMed]
Capeding, M.R.; Tran, N.H.; Hadinegoro, S.R.S.; Ismail, H.I.H.M.; Chotpitayasunondh, T.; Chua, M.N.;
Luong, C.Q.; Rusmil, K.; Wirawan, D.N.; Nallusamy, R.; et al. Clinical efficacy and safety of a novel tetravalent
dengue vaccine in healthy children in Asia: A phase 3, randomised, observer-masked, placebo-controlled
trial. Lancet 2014, 384, 1358–1365. [CrossRef]
Chew, M.-F.; Poh, K.-S.; Poh, C.-L. Peptides as Therapeutic Agents for Dengue Virus. Int. J. Med Sci. 2017, 14,
1342–1359. [CrossRef] [PubMed]
Lim, S.P. Dengue drug discovery: Progress, challenges and outlook. Antivir. Res. 2019, 163, 156–178.
[CrossRef] [PubMed]
Karlas, A.; Berre, S.; Couderc, T.; Varjak, M.; Braun, P.; Meyer, M.; Gangneux, N.; Karo-Astover, L.; Weege, F.;
Raftery, M.; et al. A human genome-wide loss-of-function screen identifies effective chikungunya antiviral
drugs. Nat. Commun. 2016, 7, 11320. [CrossRef] [PubMed]
Wong, K.Z.; Chu, J.J.H. The Interplay of Viral and Host Factors in Chikungunya Virus Infection: Targets for
Antiviral Strategies. Viruses 2018, 10, 294. [CrossRef]
Kanyaboon, P.; Saelee, T.; Suroengrit, A.; Hengphasatporn, K.; Rungrotmongkol, T.; Chavasiri, W.;
Boonyasuppayakorn, S. Cardol triene inhibits dengue infectivity by targeting kl loops and preventing
envelope fusion. Sci. Rep. 2018, 8, 16643. [CrossRef]
Teerasripreecha, D.; Phuwapraisirisan, P.; Puthong, S.; Kimura, K.; Okuyama, M.; Mori, H.; Kimura, A.;
Chanchao, C. In vitro antiproliferative/cytotoxic activity on cancer cell lines of a cardanol and a cardol
enriched from Thai Apis mellifera propolis. BMC Complement. Altern. Med. 2012, 12, 27. [CrossRef]
Hundt, J.; Li, Z.; Liu, Q. The Inhibitory Effects of Anacardic Acid on Hepatitis C Virus Life Cycle. PLoS ONE
2015, 10, e0117514. [CrossRef]
Chao, L.; Jang, J.; Johnson, A.; Nguyen, A.; Gray, N.S.; Yang, P.L.; Harrison, S.C. How small-molecule
inhibitors of dengue-virus infection interfere with viral membrane fusion. eLife 2018, 7, e36461. [CrossRef]
Coloma, J.; Harris, E. Broad and strong: The ultimate antibody to dengue virus. Nat. Immunol. 2015, 16,
135–137. [CrossRef] [PubMed]
Crill, W.D.; Roehrig, J. Monoclonal Antibodies That Bind to Domain III of Dengue Virus E Glycoprotein
Are the Most Efficient Blockers of Virus Adsorption to Vero Cells. J. Virol. 2001, 75, 7769–7773. [CrossRef]
[PubMed]
Cabarcas-Montalvo, M.; Maldonado-Rojas, W.; Montes-Grajales, D.; Bertel-Sevilla, A.; Wagner-Döbler, I.;
Sztajer, H.; Reck, M.; Alarcón, M.C.F.; Ocazionez, R.; Olivero-Verbel, J. Discovery of antiviral molecules for
dengue: In silico search and biological evaluation. Eur. J. Med. Chem. 2016, 110, 87–97. [CrossRef] [PubMed]
Fernando, S.; Fernando, T.; Stefanik, M.; Eyer, L.; Ružek,
D. An Approach for Zika Virus Inhibition Using
Homology Structure of the Envelope Protein. Mol. Biotechnol. 2016, 58, 801–806. [CrossRef] [PubMed]
Hughes, J.; Rees, S.; Kalindjian, S.; Philpott, K. Principles of early drug discovery. Br. J. Pharmacol. 2011, 162,
1239–1249. [CrossRef] [PubMed]
Molecules 2020, 25, 1883
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
15 of 18
Campillos, M.; Kuhn, M.; Gavin, A.-C.; Jensen, L.J.; Bork, P. Drug Target Identification Using Side-Effect
Similarity. Sci. 2008, 321, 263–266. [CrossRef] [PubMed]
Keiser, M.J.; Setola, V.; Irwin, J.J.; Laggner, C.; Abbas, A.I.; Hufeisen, S.J.; Jensen, N.H.; Kuijer, M.B.;
Matos, R.C.; Tran, T.B.; et al. Predicting new molecular targets for known drugs. Nature 2009, 462, 175–181.
[CrossRef]
Leelananda, S.P.; Lindert, S. Computational methods in drug discovery. Beilstein J. Org. Chem. 2016, 12,
2694–2718. [CrossRef]
Rognan, D. Docking Methods for Virtual Screening: Principles and Recent Advances, in Virtual Screening;
Wiley-VCH Verlag GmbH & Co.: Hoboken, NJ, USA, 2011; pp. 153–176.
Bredel, M.; Jacoby, E. Chemogenomics: An emerging strategy for rapid target and drug discovery. Nat. Rev.
Genet. 2004, 5, 262–275. [CrossRef]
Hengphasatporn, K.; Garon, A.; Wolschann, P.; Langer, T.; Shigeta, Y.; Huynh, T.; Chavasiri, W.; Saelee, T.;
Boonyasuppayakorn, S.; Rungrotmongkol, T. Multiple Virtual Screening Strategies for the Discovery of Novel
Compounds Active against Dengue Virus: A Hit Identification Study. Sci. Pharm. 2019, 88, 2. [CrossRef]
Chiu, Y.-Y.; Tseng, J.-H.; Liu, K.-H.; Lin, C.-T.; Hsu, K.-C.; Yang, T.-P. Homopharma: A new concept for
exploring the molecular binding mechanisms and drug repurposing. BMC Genom. 2014, 15, S8. [CrossRef]
[PubMed]
Lomenick, B.; Hao, R.; Jonai, N.; Chin, R.M.; Aghajan, M.; Warburton, S.; Wang, J.; Wu, R.P.; Gomez, F.;
Loo, J.A.; et al. Target identification using drug affinity responsive target stability (DARTS). Proc. Natl. Acad.
Sci. USA 2009, 106, 21984–21989. [CrossRef] [PubMed]
Li, J.; Zhang, Q.; Chen, Z.; Xu, D.; Wang, Y. A network-based pathway-extending approach using DNA
methylation and gene expression data to identify altered pathways. Sci. Rep. 2019, 9, 11853. [CrossRef]
[PubMed]
Yu, D.; Kim, M.S.; Xiao, G.; Hwang, T.H. Review of Biological Network Data and Its Applications. Genom.
Informatics 2013, 11, 200–210. [CrossRef] [PubMed]
Lo, Y.-C.; Senese, S.; Li, C.-M.; Hu, Q.; Huang, Y.; Damoiseaux, R.; Torres, J. Large-Scale Chemical Similarity
Networks for Target Profiling of Compounds Identified in Cell-Based Chemical Screens. PLoS Comput. Boil.
2015, 11, e1004153. [CrossRef]
Dey, L.; Mukhopadhyay, A. DenvInt: A database of protein–protein interactions between dengue virus and
its hosts. PLOS Neglected Trop. Dis. 2017, 11, e0005879. [CrossRef] [PubMed]
Plaimas, K.; Koenig, R. Identifying Antimalarial Drug Targets by Cellular Network Analysis. 2016.
Kim, S. Getting the most out of PubChem for virtual screening. Expert Opin. Drug Discov. 2016, 11, 843–855.
[CrossRef]
Zhang, H.-Y. One-compound-multiple-targets strategy to combat Alzheimer’s disease. FEBS Lett. 2005, 579,
5260–5264. [CrossRef]
Talevi, A. Multi-target pharmacology: Possibilities and limitations of the “skeleton key approach” from a
medicinal chemist perspective. Front. Pharmacol. 2015, 6, 673. [CrossRef]
Ramsay, R.R.; Nikoli´c, M.P.; Nikolic, K.M.; Uliassi, E.; Bolognesi, M.L. A perspective on multi-target drug
discovery and design for complex diseases. Clin. Transl. Med. 2018, 7, 3. [CrossRef]
Cregan, S.; McDonagh, L.; Gao, Y.; Barr, M.P.; O’Byrne, K.J.; Finn, S.; Cuffe, S.; Gray, S.G. KAT5 (Tip60) is a
potential therapeutic target in malignant pleural mesothelioma. Int. J. Oncol. 2016, 48, 1290–1296. [CrossRef]
[PubMed]
He, W.; Zhang, M.-G.; Wang, X.-J.; Zhong, S.; Shao, Y.; Zhu, Y.; Shen, Z.-J. KAT5 and KAT6B are in positive
regulation on cell proliferation of prostate cancer through PI3K-AKT signaling. Int. J. Clin. Exp. Pathol. 2013,
6, 2864–2871. [PubMed]
Feng, F.-L.; Yu, Y.; Liu, C.; Zhang, B.-H.; Cheng, Q.-B.; Li, B.; Tan, W.-F.; Luo, X.-J.; Jiang, X.-Q. KAT5 silencing
induces apoptosis of GBC-SD cells through p38MAPK-mediated upregulation of cleaved Casp9. Int. J. Clin.
Exp. Pathol. 2013, 7, 80–91. [PubMed]
Keiser, M.J.; Roth, B.L.; Armbruster, B.N.; Ernsberger, P.; Irwin, J.J.; Shoichet, B.K. Relating protein
pharmacology by ligand chemistry. Nat. Biotechnol. 2007, 25, 197–206. [CrossRef] [PubMed]
Lindenbach, B.D.; M, C. Rice Molecular Biology of Flaviviruses, in Advances in Virus Research; Academic Press:
Cambridge, MA, USA, 2003; pp. 23–61.
Molecules 2020, 25, 1883
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
16 of 18
Mukhopadhyay, S.; Kuhn, R.J.; Rossmann, M.G. A structural perspective of the flavivirus life cycle. Nat. Rev.
Genet. 2005, 3, 13–22. [CrossRef] [PubMed]
Garcia, L.; Padilla-S, L.; Castaño, J.C. Inhibitors compounds of the flavivirus replication process. Virol. J.
2017, 14, 95. [CrossRef] [PubMed]
Mishra, B.; Raghuraman, R.; Agarwal, A.; Aduri, R. Finding small molecules with pan-serotype activity to
target Dengue non-structural protein 1. VirusDisease 2019, 30, 477–489. [CrossRef]
Qamar, M.; Mumtaz, A.; Naseem, R.; Ali, A.; Fatima, T.; Jabbar, T.; Ahmad, Z.; Ashfaq, U.A. Molecular
Docking Based Screening of Plant Flavonoids as Dengue NS1 Inhibitors. Bioinformation 2014, 10, 460–465.
[CrossRef]
Zhang, C.; Feng, T.; Cheng, J.; Li, Y.; Yin, X.; Zeng, W.; Jin, X.; Li, Y.; Guo, F.; Jin, T. Structure of the NS5
methyltransferase from Zika virus and implications in inhibitor design. Biochem. Biophys. Res. Commun.
2017, 492, 624–630. [CrossRef]
El Sahili, A.; Lescar, J. Dengue Virus Non-Structural Protein 5. Viruses 2017, 9, 91. [CrossRef]
Srivarangkul, P.; Yuttithamnon, W.; Suroengrit, A.; Pankaew, S.; Hengphasatporn, K.; Rungrotmongkol, T.;
Phuwapraisirisan, P.; Ruxrungtham, K.; Boonyasuppayakorn, S.; Phuwapriasirisan, P. A novel flavanone
derivative inhibits dengue virus fusion and infectivity. Antivir. Res. 2018, 151, 27–38. [CrossRef] [PubMed]
Tambunan, U.S.F.; Zahroh, H.; Parikesit, A.A.; Idrus, S.; Kerami, D. Screening Analogs of β-OG Pocket
Binder as Fusion Inhibitor of Dengue Virus 2. Drug Target Insights 2015, 9, 33–49. [CrossRef] [PubMed]
Yennamalli, R.M.; Subbarao, N.; Kampmann, T.; McGeary, R.; Young, P.; Kobe, B. Identification of novel
target sites and an inhibitor of the dengue virus E protein. J. Comput. Mol. Des. 2009, 23, 333–341. [CrossRef]
[PubMed]
Jadav, S.S.; Kaptein, S.; Timiri, A.; De Burghgraeve, T.; Badavath, V.N.; Ganesan, R.; Sinha, B.N.; Neyts, J.;
Leyssen, P.; Jayaprakash, V. Design, synthesis, optimization and antiviral activity of a class of hybrid dengue
virus E protein inhibitors. Bioorganic Med. Chem. Lett. 2015, 25, 1747–1752. [CrossRef] [PubMed]
Ismail, N.A.; Jusoh, S.A. Molecular Docking and Molecular Dynamics Simulation Studies to Predict Flavonoid
Binding on the Surface of DENV2 E Protein. Interdiscip. Sci. Comput. Life Sci. 2016, 9, 499–511. [CrossRef]
Sharma, N.; Murali, A.; Singh, S.K.; Giri, R. Epigallocatechin gallate, an active green tea compound inhibits
the Zika virus entry into host cells via binding the envelope protein. Int. J. Boil. Macromol. 2017, 104,
1046–1054. [CrossRef]
Hengphasatporn, K.; Kungwan, N.; Rungrotmongkol, T. Binding pattern and susceptibility of epigallocatechin
gallate against envelope protein homodimer of Zika virus: A molecular dynamics study. J. Mol. Liq. 2019,
274, 140–147. [CrossRef]
Wirawan, M.; Fibriansah, G.; Marzinek, J.K.; Lim, X.X.; Ng, T.-S.; Sim, A.Y.; Zhang, Q.; Kostyuchenko, V.;
Shi, J.; Smith, S.A.; et al. Mechanism of Enhanced Immature Dengue Virus Attachment to Endosomal
Membrane Induced by prM Antibody. Struct. 2019, 27, 253–267.e8. [CrossRef]
Yasunaga, A.; Hanna, S.L.; Li, J.; Cho, H.; Rose, P.P.; Spiridigliozzi, A.; Gold, B.; Diamond, M.S.; Cherry, S.
Genome-Wide RNAi Screen Identifies Broadly-Acting Host Factors That Inhibit Arbovirus Infection. PLOS
Pathog. 2014, 10, 1003914. [CrossRef]
Yang, S.H.; Liu, M.L.; Tien, C.F.; Chou, S.J.; Chang, R.Y. Glyceraldehyde-3-phosphate dehydrogenase
(GAPDH) interaction with 30 ends of Japanese encephalitis virus RNA and colocalization with the viral NS5
protein. J. Biomed. Sci. 2009, 16, 40. [CrossRef]
Silva, E.M.; Conde, J.N.; Allonso, D.; Ventura, G.T.; Coelho, D.R.; Carneiro, P.H.; Silva, M.L.; Paes, M.V.;
Rabelo, K.; Weissmuller, G.; et al. Dengue virus nonstructural 3 protein interacts directly with human
glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and reduces its glycolytic activity. Sci. Rep. 2019, 9,
2651. [CrossRef] [PubMed]
Raj, M.; Langley, M.; McArthur, S.J.; Jean, F. Moonlighting glycolytic enzyme glyceraldehyde-3-phosphate
dehydrogenase (GAPDH) is required for efficient hepatitis C virus and dengue virus infections in human
Huh-7.5.1 cells. J. Gen. Virol. 2017, 98, 977–991. [CrossRef] [PubMed]
Yi, M.; Schultz, D.E.; Lemon, S.M. Functional Significance of the Interaction of Hepatitis A Virus RNA with
Glyceraldehyde 3-Phosphate Dehydrogenase (GAPDH): Opposing Effects of GAPDH and Polypyrimidine
Tract Binding Protein on Internal Ribosome Entry Site Function. J. Virol. 2000, 74, 6459–6468. [CrossRef]
[PubMed]
Molecules 2020, 25, 1883
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
92.
17 of 18
Zhang, X.; Xie, X.; Xia, H.; Zou, J.; Huang, L.; Popov, V.L.; Chen, X.; Shi, P.-Y. Zika Virus NS2A-Mediated
Virion Assembly. mBio 2019, 10, e02375-19. [CrossRef] [PubMed]
Zhang, Y.; Gao, W.; Li, J.; Wu, W.; Jiu, Y. The Role of Host Cytoskeleton in Flavivirus Infection. Virol. Sin.
2019, 34, 30–41. [CrossRef] [PubMed]
Kumar, V.E.; Cherupanakkal, C.; Catherine, M.; Kadhiravan, T.; Parameswaran, N.; Rajendiran, S.; Pillai, A.B.
Endogenous gene selection for relative quantification PCR and IL6 transcript levels in the PBMC’s of severe
and non-severe dengue cases. BMC Res. Notes 2018, 11, 550. [CrossRef]
Srisutthisamphan, K.; Jirakanwisal, K.; Ramphan, S.; Tongluan, N.; Kuadkitkan, A.; Smith, D.R. Hsp90
interacts with multiple dengue virus 2 proteins. Sci. Rep. 2018, 8, 4308. [CrossRef]
Kim, S.; Thiessen, P.A.; Bolton, E.; Chen, J.; Fu, G.; Gindulyte, A.; Han, L.; He, J.; He, S.; Shoemaker, B.A.;
et al. PubChem Substance and Compound databases. Nucleic Acids Res. 2015, 44, D1202–D1213. [CrossRef]
Bajusz, D.; Rácz, A.; Héberger, K. Why is Tanimoto index an appropriate choice for fingerprint-based
similarity calculations? J. Chemin. 2015, 7, 20. [CrossRef]
Cereto-Massagué, A.; Ojeda, M.J.; Valls, C.; Mulero, M.; Garcia-Vallvé, S.; Pujadas, G. Molecular fingerprint
similarity search in virtual screening. Methods 2015, 71, 58–63. [CrossRef]
Anastasiu, D.; Karypis, G. Efficient identification of Tanimoto nearest neighbors. Int. J. Data Sci. Anal. 2017,
4, 153–172. [CrossRef]
Backman, T.; Cao, Y.; Girke, T. ChemMine tools: An online service for analyzing and clustering small
molecules. Nucleic Acids Res. 2011, 39, W486–W491. [CrossRef] [PubMed]
Liang, L.; Ma, C.; Du, T.; Zhao, Y.; Zhao, X.; Liu, M.; Wang, Z.; Lin, J. Bioactivity-explorer: A web application
for interactive visualization and exploration of bioactivity data. J. Cheminform. 2019, 11, 47. [CrossRef]
[PubMed]
Bento, A.P.S.F.F.; Gaulton, A.; Hersey, A.; Bellis, L.; Chambers, J.; Davies, M.; A Kruger, F.; Light, Y.; Mak, L.;
McGlinchey, S.; et al. The ChEMBL bioactivity database: An update. Nucleic Acids Res. 2013, 42, D1083–D1090.
[CrossRef]
Huang, R.; Xia, M. Editorial: Tox21 Challenge to Build Predictive Models of Nuclear Receptor and Stress
Response Pathways As Mediated by Exposure to Environmental Toxicants and Drugs. Front. Environ. Sci.
2017, 5, 906. [CrossRef]
Gilson, M.K.; Liu, T.; Baitaluk, M.; Nicola, G.; Hwang, L.; Chong, J. BindingDB in 2015: A public database
for medicinal chemistry, computational chemistry and systems pharmacology. Nucleic Acids Res. 2015, 44,
D1045–D1053. [CrossRef] [PubMed]
Wadman, M. National prescription for drug development. Nat. Biotechnol. 2012, 30, 309–312. [CrossRef]
Wang, Y.; Xiao, J.; Suzek, T.; Zhang, J.; Wang, J.; Zhou, Z.; Han, L.; Karapetyan, K.; Dracheva, S.;
Shoemaker, B.A.; et al. PubChem’s BioAssay Database. Nucleic Acids Res. 2011, 40, D400–D412. [CrossRef]
Jensen, L.J.; Kuhn, M.; Stark, M.; Chaffron, S.; Creevey, C.J.; Muller, J.; Doerks, T.; Julien, P.; Roth, A.;
Simonovic, M.; et al. STRING 8–a global view on proteins and their functional interactions in 630 organisms.
Nucleic Acids Res. 2008, 37, D412–D416. [CrossRef]
Bastian, M.; Heymann, S.; Jacomy, M. Gephi: An Open Source Software for Exploring and Manipulating
Networks. In Proceedings of the Third International AAAI Conference on Weblogs and Social Media,
San Jose, CA, USA, 17–20 May 2009.
Rodrigues, F.A. Network Centrality: An. Introduction, in A Mathematical Modeling Approach from Nonlinear
Dynamics to Complex Systems; Macau, E.E.N., Ed.; Springer: Berlin/Heidelberg, Germany, 2019; pp. 177–196.
Plaimas, K.; Eils, R.; König, R. Identifying essential genes in bacterial metabolic networks with machine
learning methods. BMC Syst. Boil. 2010, 4, 56. [CrossRef]
Yu, H.; Kim, P.M.; Sprecher, E.; Trifonov, V.; Gerstein, M. The Importance of Bottlenecks in Protein Networks:
Correlation with Gene Essentiality and Expression Dynamics. PLoS Comput. Boil. 2007, 3, e59. [CrossRef]
[PubMed]
Feng, Y.; Wang, Q.; Wang, T. Drug Target Protein-Protein Interaction Networks: A Systematic Perspective.
BioMed Res. Int. 2017, 2017, 1–13. [CrossRef] [PubMed]
Barabasi, A.-L.; Oltvai, Z.N. Network biology: Understanding the cell’s functional organization. Nat. Rev.
Genet. 2004, 5, 101–113. [CrossRef] [PubMed]
Molecules 2020, 25, 1883
93.
94.
95.
18 of 18
Kolountzakis, M.N.; Miller, G.; Peng, R.; Tsourakakis, C.E. Efficient Triangle Counting in Large Graphs via
Degree-Based Vertex Partitioning. In Algorithms and Models for the Web-Graph; Springer: Berlin/Heidelberg,
Germany, 2010.
UniProt Consortium; The UniProt Consortium UniProt: A hub for protein information. Nucleic Acids Res.
2014, 43, D204–D212.
Rappaport, N.; Nativ, N.; Stelzer, G.; Twik, M.; Guan-Golan, Y.; Stein, T.I.; Bahir, I.; Belinky, F.; Morrey, C.P.;
Safran, M.; et al. MalaCards: An integrated compendium for diseases and their annotation. Database 2013,
2013, bat018. [CrossRef] [PubMed]
Sample Availability: Samples are not available from the authors.
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
...
論文の公開元へ
