|
1
|
Hong J: Role of natural product diversity
in chemical biology. Curr Opin Chem Biol. 15:350–354.
2011.PubMed/NCBI View Article : Google Scholar
|
|
2
|
Bernardini S, Tiezzi A, Laghezza Masci V
and Ovidi E: Natural products for human health: An historical
overview of the drug discovery approaches. Nat Prod Res.
32:1926–1950. 2018.PubMed/NCBI View Article : Google Scholar
|
|
3
|
Beutler JA: Natural Products as a
Foundation for Drug Discovery. Curr Protoc Pharmacol.
46:9.11.1–9.11.21. 2009.PubMed/NCBI View Article : Google Scholar
|
|
4
|
Newman DJ and Cragg GM: Natural products
as sources of new drugs over the last 25 years. J Nat Prod.
70:461–477. 2007.PubMed/NCBI View Article : Google Scholar
|
|
5
|
Thomford NE, Senthebane DA, Rowe A, Munro
D, Seele P, Maroyi A and Dzobo K: Natural Products for Drug
Discovery in the 21st Century: Innovations for Novel Drug
Discovery. Int J Mol Sci. 19(E1578)2018.PubMed/NCBI View Article : Google Scholar
|
|
6
|
Kayser O, Kiderlen AF and Croft SL:
Natural products as antiparasitic drugs. Parasitol Res. 90 (Suppl
2):S55–S62. 2003.PubMed/NCBI View Article : Google Scholar
|
|
7
|
Salam AM and Quave CL: Opportunities for
plant natural products in infection control. Curr Opin Microbiol.
45:189–194. 2018.PubMed/NCBI View Article : Google Scholar
|
|
8
|
Sut S, Dall'Acqua S, Zengin G, Senkardes
I, Bulut G, Cvetanović A, Stupar A, Mandić A, Picot-Allain C, Dogan
A, et al: Influence of different extraction techniques on the
chemical profile and biological properties of Anthemis
cotula L.: Multifunctional aspects for potential pharmaceutical
applications. J Pharm Biomed Anal. 173:75–85. 2019.PubMed/NCBI View Article : Google Scholar
|
|
9
|
Salis C, Papageorgiou L, Papakonstantinou
E, Hagidimitriou M and Vlachakis D: Olive Oil Polyphenols in
Neurodegenerative Pathologies. Adv Exp Med Biol. 1195:77–91.
2020.PubMed/NCBI View Article : Google Scholar
|
|
10
|
Treml J, Gazdová M, Šmejkal K, Šudomová M,
Kubatka P and Hassan STS: Natural Products-Derived Chemicals:
Breaking Barriers to Novel Anti-HSV Drug Development. Viruses.
12(E154)2020.PubMed/NCBI View Article : Google Scholar
|
|
11
|
Koumandou VL, Papageorgiou L, Tsaniras SC,
Papathanassopoulou A, Hagidimitriou M, Cosmidis N and Vlachakis D:
Microbiome Hijacking Towards an Integrative Pest Management
Pipeline. Adv Exp Med Biol. 1195:21–32. 2020.PubMed/NCBI View Article : Google Scholar
|
|
12
|
Kong DX, Li XJ and Zhang HY: Where is the
hope for drug discovery? Let history tell the future. Drug Discov
Today. 14:115–119. 2009.PubMed/NCBI View Article : Google Scholar
|
|
13
|
Wagner H and Ulrich-Merzenich G: Synergy
research: Approaching a new generation of phytopharmaceuticals.
Phytomedicine. 16:97–110. 2009.PubMed/NCBI View Article : Google Scholar
|
|
14
|
Calixto JB: The role of natural products
in modern drug discovery. An Acad Bras Cienc. 91 (Suppl
3)(e20190105)2019.PubMed/NCBI View Article : Google Scholar
|
|
15
|
Newman DJ and Cragg GM: Natural Products
as Sources of New Drugs from 1981 to 2014. J Nat Prod. 79:629–661.
2016.PubMed/NCBI View Article : Google Scholar
|
|
16
|
Agrafiotis DK, Bandyopadhyay D, Wegner JK
and Vlijmen H: Recent advances in chemoinformatics. J Chem Inf
Model. 47:1279–1293. 2007.PubMed/NCBI View Article : Google Scholar
|
|
17
|
Lo YC, Rensi SE, Torng W and Altman RB:
Machine learning in chemoinformatics and drug discovery. Drug
Discov Today. 23:1538–1546. 2018.PubMed/NCBI View Article : Google Scholar
|
|
18
|
Muegge I and Mukherjee P: An overview of
molecular fingerprint similarity search in virtual screening.
Expert Opin Drug Discov. 11:137–148. 2016.PubMed/NCBI View Article : Google Scholar
|
|
19
|
Fernandes JPS: The Importance of Medicinal
Chemistry Knowledge in the Clinical Pharmacist's Education. The
Importance of Medicinal Chemistry Knowledge in the Clinical
Pharmacist's Education. Am J Pharm Educ. 82(6083)2018.PubMed/NCBI View
Article : Google Scholar
|
|
20
|
Mitsis T, Papageorgiou L, Efthimiadou A,
Bacopoulou F, Vlachakis D, Chrousos GP and Eliopoulos E: A
comprehensive structural and functional analysis of the ligand
binding domain of the nuclear receptor superfamily reveals highly
conserved signaling motifs and two distinct canonical forms through
evolution. World Acad Sci J. 1:264–274. 2019.
|
|
21
|
Papageorgiou L, Shalzi L, Pierouli K,
Papakonstantinou E, Manias S, Dragoumani K, Nicolaides N,
Giannakakis A, Bacopoulou F, Chrousos G, et al: An updated
evolutionary study of the nuclear receptor protein family. World
Acad Sci J. 3(51)2021.
|
|
22
|
Chaudhari R, Tan Z, Huang B and Zhang S:
Computational polypharmacology: A new paradigm for drug discovery.
Expert Opin Drug Discov. 12:279–291. 2017.PubMed/NCBI View Article : Google Scholar
|
|
23
|
Pushpakom S, Iorio F, Eyers PA, Escott KJ,
Hopper S, Wells A, Doig A, Guilliams T, Latimer J, McNamee C, et
al: Drug repurposing: Progress, challenges and recommendations. Nat
Rev Drug Discov. 18:41–58. 2019.PubMed/NCBI View Article : Google Scholar
|
|
24
|
Vlachakis D, Papageorgiou L, Papadaki A,
Georga M, Kossida S and Eliopoulos E: An updated evolutionary study
of the Notch family reveals a new ancient origin and novel
invariable motifs as potential pharmacological targets. PeerJ.
8(e10334)2020.PubMed/NCBI View Article : Google Scholar
|
|
25
|
Awale M, Visini R, Probst D, Arús-Pous J
and Reymond JL: Chemical Space: Big Data Challenge for Molecular
Diversity. Chimia (Aarau). 71:661–666. 2017.PubMed/NCBI View Article : Google Scholar
|
|
26
|
Voigt JH, Bienfait B, Wang S and Nicklaus
MC: Comparison of the NCI open database with seven large chemical
structural databases. J Chem Inf Comput Sci. 41:702–712.
2001.PubMed/NCBI View Article : Google Scholar
|
|
27
|
Wishart DS, Knox C, Guo AC, Cheng D,
Shrivastava S, Tzur D, Gautam B and Hassanali M: DrugBank: A
knowledgebase for drugs, drug actions and drug targets. Nucleic
Acids Res. 36 (Suppl 1):D901–D906. 2008.PubMed/NCBI View Article : Google Scholar
|
|
28
|
Wishart DS, Feunang YD, Guo AC, Lo EJ,
Marcu A, Grant JR, Sajed T, Johnson D, Li C, Sayeeda Z, et al:
DrugBank 5.0: A major update to the DrugBank database for 2018.
Nucleic Acids Res. 46 (D1):D1074–D1082. 2018.PubMed/NCBI View Article : Google Scholar
|
|
29
|
Zeng X, Zhang P, He W, Qin C, Chen S, Tao
L, Wang Y, Tan Y, Gao D, Wang B, et al: NPASS: Natural product
activity and species source database for natural product research,
discovery and tool development. Nucleic Acids Res. 46
(D1):D1217–D1222. 2018.PubMed/NCBI View Article : Google Scholar
|
|
30
|
Choi H, Cho SY, Pak HJ, Kim Y, Choi JY,
Lee YJ, Gong BH, Kang YS, Han T, Choi G, et al: NPCARE: Database of
natural products and fractional extracts for cancer regulation. J
Cheminform. 9(2)2017.PubMed/NCBI View Article : Google Scholar
|
|
31
|
Cheng S, Zhu C, Chu C, Huang T, Kong X and
Zhu LC: Prediction of bioactive compound pathways using chemical
interaction and structural information. Comb Chem High Throughput
Screen. 19:161–169. 2016.PubMed/NCBI View Article : Google Scholar
|
|
32
|
Ihlenfeldt WD, Voigt JH, Bienfait B,
Oellien F and Nicklaus MC: Enhanced CACTVS browser of the Open NCI
Database. J Chem Inf Comput Sci. 42:46–57. 2002.PubMed/NCBI View Article : Google Scholar
|
|
33
|
Knox C, Law V, Jewison T, Liu P, Ly S,
Frolkis A, Pon A, Banco K, Mak C, Neveu V, et al: DrugBank 3.0: A
comprehensive resource for ‘omics’ research on drugs. Nucleic Acids
Res. 39 (Database):D1035–D1041. 2011.PubMed/NCBI View Article : Google Scholar
|
|
34
|
Hähnke VD, Kim S and Bolton EE: PubChem
chemical structure standardization. J Cheminform.
10(36)2018.PubMed/NCBI View Article : Google Scholar
|
|
35
|
Heller SR, McNaught A, Pletnev I, Stein S
and Tchekhovskoi D: InChI, the IUPAC International Chemical
Identifier. J Cheminform. 7(23)2015.PubMed/NCBI View Article : Google Scholar
|
|
36
|
Reyes-Aldasoro CC: The proportion of
cancer-related entries in PubMed has increased considerably; is
cancer truly ‘The Emperor of All Maladies’? PLoS One.
12(e0173671)2017.PubMed/NCBI View Article : Google Scholar
|
|
37
|
Dunn MJ, Jorde LB, Little PFR and
Subramaniam S (eds): Encyclopedia of Genetics, Genomics, Proteomics
and Bioinformatics, 8 Volume Set. John Wiley & Sons Ltd.,
Hoboken NJ, 2005.
|
|
38
|
Vilar S, Cozza G and Moro S: Medicinal
chemistry and the molecular operating environment (MOE):
Application of QSAR and molecular docking to drug discovery. Curr
Top Med Chem. 8:1555–1572. 2008.PubMed/NCBI View Article : Google Scholar
|
|
39
|
Mhlanga P, Wan Hassan WA, Hamerton I and
Howlin BJ: Using combined computational techniques to predict the
glass transition temperatures of aromatic polybenzoxazines. PLoS
One. 8(e53367)2013.PubMed/NCBI View Article : Google Scholar
|
|
40
|
Ihlenfeldt WD, Takahashi Y, Abe H and
Sasaki S: Computation and management of chemical properties in
CACTVS: An extensible networked approach toward modularity and
compatibility. J Chem Inf Comput Sci. 34:109–116. 1994.
|
|
41
|
Huggins DJ, Venkitaraman AR and Spring DR:
Rational methods for the selection of diverse screening compounds.
ACS Chem Biol. 6:208–217. 2011.PubMed/NCBI View Article : Google Scholar
|
|
42
|
Hudson BD, Hyde RM, Rahr E, Wood J and
Osman J: Parameter Based Methods for Compound Selection from
Chemical Databases. Quant Struct-Act Rel. 15:285–289. 1996.
|
|
43
|
Bajusz D, Rácz A and Héberger K: Why is
Tanimoto index an appropriate choice for fingerprint-based
similarity calculations? J Cheminform. 7(20)2015.PubMed/NCBI View Article : Google Scholar
|
|
44
|
Wolber G and Langer T: LigandScout: 3-D
pharmacophores derived from protein-bound ligands and their use as
virtual screening filters. J Chem Inf Model. 45:160–169.
2005.PubMed/NCBI View Article : Google Scholar
|
|
45
|
Shaker B, Yu MS, Lee J, Lee Y, Jung C and
Na D: User guide for the discovery of potential drugs via protein
structure prediction and ligand docking simulation. J Microbiol.
58:235–244. 2020.PubMed/NCBI View Article : Google Scholar
|
|
46
|
Zhou Y, Tang S, Chen T and Niu MM:
Structure-Based Pharmacophore Modeling, Virtual Screening,
Molecular Docking and Biological Evaluation for Identification of
Potential Poly. Structure-Based Pharmacophore Modeling, Virtual
Screening, Molecular Docking and Biological Evaluation for
Identification of Potential Poly (ADP-Ribose) Polymerase-1 (PARP-1)
Inhibitors. Molecules. 24(E4258)2019.PubMed/NCBI View Article : Google Scholar
|
|
47
|
Bolton EE, Chen J, Kim S, Han L, He S, Shi
W, Simonyan V, Sun Y, Thiessen PA, Wang J, et al: PubChem3D: A new
resource for scientists. J Cheminform. 3(32)2011.PubMed/NCBI View Article : Google Scholar
|
|
48
|
Kim S, Bolton EE and Bryant SH: Similar
compounds versus similar conformers: Complementarity between
PubChem 2-D and 3-D neighboring sets. J Cheminform.
8(62)2016.PubMed/NCBI View Article : Google Scholar
|
|
49
|
Wachtel-Galor S, Yuen J, Buswell JA and
Benzie IFF: Ganoderma lucidum (Lingzhi or Reishi): A Medicinal
Mushroom. In: Herbal Medicine: Biomolecular and Clinical Aspects.
Benzie IFF and Wachtel-Galor S (eds). 2nd edition. CRC Press/Taylor
& Francis, Boca Raton, FL, 2011.
|
|
50
|
Xu J, Chen F, Wang G, Liu B, Song H and Ma
T: The Versatile Functions of G. Lucidum Polysaccharides and G.
Lucidum Triterpenes in Cancer Radiotherapy and Chemotherapy. Cancer
Manag Res. 13:6507–6516. 2021.PubMed/NCBI View Article : Google Scholar
|
|
51
|
Papageorgiou L, Zervou MI, Vlachakis D,
Matalliotakis M, Matalliotakis I, Spandidos DA, Goulielmos GN and
Eliopoulos E: Demetra Application: An integrated genotype analysis
web server for clinical genomics in endometriosis. Int J Mol Med.
47(115)2021.PubMed/NCBI View Article : Google Scholar
|
|
52
|
Spreafico R, Soriaga LB, Grosse J, Virgin
HW and Telenti A: Advances in Genomics for Drug Development. Genes
(Basel). 11(E942)2020.PubMed/NCBI View Article : Google Scholar
|
|
53
|
Cardon LR and Harris T: Precision
medicine, genomics and drug discovery. Hum Mol Genet. 25
(R2):R166–R172. 2016.PubMed/NCBI View Article : Google Scholar
|
|
54
|
Sonehara K and Okada Y: Genomics-driven
drug discovery based on disease-susceptibility genes. Inflamm
Regen. 41(8)2021.PubMed/NCBI View Article : Google Scholar
|
