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2000
Volume 15, Issue 1
  • ISSN: 2210-3155
  • E-ISSN: 2210-3163

Abstract

Natural products have long garnered the interest of scientific communities as they have proven to be an effective therapeutic resource that paved the path for medicinal research and drug development. Among them, is an entomopathogenic caterpillar fungus with a renowned history of being utilized as a medicinal remedy for centuries in Eastern civilizations. The number of pharmacological functions reported by this specific fungus resulted in continuous efforts to unravel new effective bioactive compounds and their corresponding mechanism of action. As time progresses, computational techniques become the forefront of genomic and proteomic analysis, besides acting as a platform for integrating various up-to-date multidisciplinary data sources. This review briefly introduces alongside the latest known biologically active compounds and their respective therapeutic potential. The need to implement computational applications to cope with the continuous phytochemical evolution of will be illustrated. Moreover, many databases, mathematical algorithms, or sourcing tools that could benefit data visualization, dissemination, and interpretation aligned to fungal-based research are enumerated, in addition to describing some of the broad discoveries relative to in the past. In conclusion, using advanced computational technology may be the foundation to leverage natural product discovery about and contribute to future mass production of this fungus for commercial purposes in the world pharmaceutical industry.

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2025-01-01
2024-11-26
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References

  1. ShresthaB. ZhangW. ZhangY. LiuX. What is the Chinese caterpillar fungus Ophiocordyceps sinensis (Ophiocordycipitaceae)?Mycology20101422823610.1080/21501203.2010.536791
    [Google Scholar]
  2. ZhangY. LiE. WangC. LiY. LiuX. Ophiocordyceps sinensis, the flagship fungus of China: Terminology, life strategy and ecology.Mycology20123121010.1080/21501203.2011.654354
    [Google Scholar]
  3. BhandariK.A. NegiJ.S. BishtV.K. RanaC.S. BhartiM.K. SinghN. Chemical constituent, inorganic elements and properties of cordyceps sinensis-A review.Nat. Sci. Sleep201089253256
    [Google Scholar]
  4. MainsE.B. North American entomogenous species of cordyceps.Mycologia195850216922210.1080/00275514.1958.12024722
    [Google Scholar]
  5. KobayasiY. Keys to the taxa of the genera cordyceps and torrubiella.Trans. Mycol. Soc. Japan 198223329364
    [Google Scholar]
  6. StensrudØ. JonesH.N.L. SchumacherT. Towards a phylogenetic classification of Cordyceps: ITS nrDNA sequence data confirm divergent lineages and paraphyly.Mycol. Res.20051091415610.1017/S095375620400139X15736862
    [Google Scholar]
  7. ShresthaB. ZhangW. ZhangY. LiuX. The medicinal fungus Cordyceps militaris: research and development.Mycol. Prog.201211359961410.1007/s11557‑012‑0825‑y
    [Google Scholar]
  8. PeglerD.N. YaoY.J. LiY. The Chinese ‘Caterpillar Fungus’.Mycologist1994813510.1016/S0269‑915X(09)80670‑8
    [Google Scholar]
  9. MizunoT. Medicinal effects and utilization of cordyceps (Fr.) Link (Ascomycetes) and Isaria Fr. (Mitosporic Fungi) Chinese caterpillar fungi, “Tochukaso”. (Review)Int. J. Med. Mushrooms 19991325126110.1615/IntJMedMushrooms.v1.i3.80
    [Google Scholar]
  10. SungG.H. JonesH.N.L. SungJ.M. ArdL.J.J. ShresthaB. SpataforaJ.W. Phylogenetic classification of Cordyceps and the clavicipitaceous fungi.Stud. Mycol.20075755910.3114/sim.2007.57.0118490993
    [Google Scholar]
  11. JonesH.N.L. Multiples of eight in cordyceps ascospores.Mycol. Res.200210612310.1017/S0953756202235534
    [Google Scholar]
  12. ParkC. HongS. LeeJ.Y. KimG.Y. ChoiB. LeeY. ParkD. ParkY-M. JeongY-K. ChoiY. Growth inhibition of U937 leukemia cells by aqueous extract of Cordyceps militaris through induction of apoptosis.Oncol. Rep.200519245245810.3892/or.13.6.1211
    [Google Scholar]
  13. JinC.Y. KimG.Y. ChoiY.H. Induction of apoptosis by aqueous extract of Cordyceps militaris through activation of caspases and inactivation of Akt in human breast cancer MDA-MB-231 Cells.J. Microbiol. Biotechnol.200818121997200310.4014/jmb.0800.27219131705
    [Google Scholar]
  14. JoW.S. ChoiY.J. KimH.J. LeeJ.Y. NamB.H. LeeJ.D. LeeS.W. SeoS.Y. JeongM.H. The anti-inflammatory effects of water extract from Cordyceps militaris in murine macrophage.Mycobiology2010381465110.4489/MYCO.2010.38.1.04623956624
    [Google Scholar]
  15. ChuH.L. ChienJ.C. DuhP.D. Protective effect of Cordyceps militaris against high glucose-induced oxidative stress in human umbilical vein endothelial cells.Food Chem.2011129387187610.1016/j.foodchem.2011.05.03725212312
    [Google Scholar]
  16. ReisF.S. BarrosL. CalhelhaR.C. ĆirićA. van GriensvenL.J.L.D. SokovićM. FerreiraI.C.F.R. The methanolic extract of Cordyceps militaris (L.) Link fruiting body shows antioxidant, antibacterial, antifungal and antihuman tumor cell lines properties.Food Chem. Toxicol.201362919810.1016/j.fct.2013.08.03323994083
    [Google Scholar]
  17. RumaM.W. PutrantoE.W. KondoE. WatanabeR. SaitoK. InoueY. YamamotoK.I. NakataS. KaihataM. MurataH. SakaguchiM. Extract of Cordyceps militaris inhibits angiogenesis and suppresses tumor growth of human malignant melanoma cells.Int. J. Oncol.201445120921810.3892/ijo.2014.239724789042
    [Google Scholar]
  18. SongJ. WangY. TengM. CaiG. XuH. GuoH. LiuY. WangD. TengL. Studies on the antifatigue activities of Cordyceps militaris fruit body extract in mouse model.Evid. Based Complement. Alternat. Med.2015201511510.1155/2015/17461626351509
    [Google Scholar]
  19. QuyT. XuanT. Xanthine oxidase inhibitory potential, antioxidant and antibacterial activities of Cordyceps militaris (L.) link fruiting body.Medicines 2019612010.3390/medicines601002030699961
    [Google Scholar]
  20. CuiJ.D. ZhangB.Z. Comparison of culture methods on exopolysaccharide production in the submerged culture of Cordyceps militaris and process optimization.Lett. Appl. Microbiol.201152212312810.1111/j.1472‑765X.2010.02987.x21214603
    [Google Scholar]
  21. LimL. LeeC. ChangE. Optimization of solid state culture conditions for the production of adenosine, cordycepin, and D-mannitol in fruiting bodies of medicinal caterpillar fungus Cordyceps militaris (L.:Fr.) Link (Ascomycetes).Int. J. Med. Mushrooms201214218118710.1615/IntJMedMushr.v14.i2.6022506578
    [Google Scholar]
  22. LianT. YangT. LiuG. SunJ. DongC. Reliable reference gene selection for Cordyceps militaris gene expression studies under different developmental stages and media.FEMS Microbiol. Lett.201435619710410.1111/1574‑6968.1249224953133
    [Google Scholar]
  23. LinH.Y. TsaiS.Y. TsengY.L. LinC.P. Gamma irradiation for improving functional ingredients and determining the heat treatment conditions of Cordyceps militaris mycelia.J. Therm. Anal. Calorim.2015120143944810.1007/s10973‑015‑4523‑2
    [Google Scholar]
  24. HurH. Chemical ingredients of Cordyceps militaris.Mycobiology200836423323510.4489/MYCO.2008.36.4.23323997632
    [Google Scholar]
  25. CunninghamK.G. MansonW. SpringF.S. HutchinsonS.A. Cordycepin, a metabolic product isolated from cultures of Cordyceps militaris (Linn.) link.Nature1950166423194994910.1038/166949a014796634
    [Google Scholar]
  26. TsaiY.J. LinL.C. TsaiT.H. Pharmacokinetics of adenosine and cordycepin, a bioactive constituent of Cordyceps sinensis in rat.J. Agric. Food Chem.20105884638464310.1021/jf100269g20302371
    [Google Scholar]
  27. LeeJ.B. AdrowerC. QinC. FischerP.M. de MoorC.H. GershkovichP. Development of cordycepin formulations for preclinical and clinical studies.AAPS PharmSciTech20171883219322610.1208/s12249‑017‑0795‑028560504
    [Google Scholar]
  28. HolbeinS. WengiA. DecourtyL. FreimoserF.M. JacquierA. DichtlB. Cordycepin interferes with 3′ end formation in yeast independently of its potential to terminate RNA chain elongation.RNA200915583784910.1261/rna.145890919324962
    [Google Scholar]
  29. RottmanF. GuarinoA.J. The inhibition of phosphoribosyl-pyrophosphate amidotransferase activity by cordycepin monophosphate.Biochim. Biophys. Acta19648946547210.1016/0926‑6569(64)90072‑0
    [Google Scholar]
  30. HeW. ZhangM. YeJ. JiangT. FangX. SongY. Cordycepin induces apoptosis by enhancing JNK and p38 kinase activity and increasing the protein expression of Bcl-2 pro-apoptotic molecules.J. Zhejiang Univ. Sci. B201011965466010.1631/jzus.B100008120803769
    [Google Scholar]
  31. JeongJ.W. JinC.Y. ParkC. HongS.H. KimG.Y. JeongY.K. LeeJ.D. YooY.H. ChoiY.H. Induction of apoptosis by cordycepin via reactive oxygen species generation in human leukemia cells.Toxicol. In Vitro 201125481782410.1016/j.tiv.2011.02.00121310227
    [Google Scholar]
  32. SunY. WangY.H. QuK. ZhuH.B. Beneficial effects of cordycepin on metabolic profiles of liver and plasma from hyperlipidemic hamsters.J. Asian Nat. Prod. Res.201113653454610.1080/10286020.2011.57536421623517
    [Google Scholar]
  33. RameshT. YooS.K. KimS.W. HwangS.Y. SohnS.H. KimI.W. KimS.K. Cordycepin (3′-deoxyadenosine) attenuates age-related oxidative stress and ameliorates antioxidant capacity in rats.Exp. Gerontol.2012471297998710.1016/j.exger.2012.09.00323000874
    [Google Scholar]
  34. ChaJ.Y. AhnH.Y. ChoY.S. JeJ.Y. Protective effect of cordycepin-enriched Cordyceps militaris on alcoholic hepatotoxicity in Sprague–Dawley rats.Food Chem. Toxicol.201360525710.1016/j.fct.2013.07.03323876821
    [Google Scholar]
  35. ChoiY.H. KimG.Y. LeeH.H. Anti-inflammatory effects of cordycepin in lipopolysaccharide-stimulated RAW 264.7 macrophages through Toll-like receptor 4-mediated suppression of mitogen-activated protein kinases and NF-κB signaling pathways.Drug Des. Devel. Ther.201481941195310.2147/DDDT.S7195725342887
    [Google Scholar]
  36. MaL. ZhangS. DuM. Cordycepin from Cordyceps militaris prevents hyperglycemia in alloxan-induced diabetic mice.Nutr. Res.201535543143910.1016/j.nutres.2015.04.01125940982
    [Google Scholar]
  37. PengJ. WangP. GeH. QuX. JinX. Effects of cordycepin on the microglia-overactivation-induced impairments of growth and development of hippocampal cultured neurons.PLoS One2015105e012590210.1371/journal.pone.012590225932642
    [Google Scholar]
  38. ZhangP. HuangC. FuC. TianY. HuY. WangB. StrasnerA. SongY. SongE. Cordycepin (3′-deoxyadenosine) suppressed HMGA2, Twist1 and ZEB1-dependent melanoma invasion and metastasis by targeting miR-33b.Oncotarget20156129834985310.18632/oncotarget.338325868853
    [Google Scholar]
  39. DuY. YuJ. DuL. TangJ. FengW.H. Cordycepin enhances epstein–barr virus lytic infection and epstein–barr virus-positive tumor treatment efficacy by doxorubicin.Cancer Lett.2016376224024810.1016/j.canlet.2016.04.00127063964
    [Google Scholar]
  40. KwonH.W. ShinJ.H. LimD.H. OkW.J. NamG.S. KimM.J. KwonH.K. NohJ.H. LeeJ.Y. KimH.H. KimJ.L. ParkH.J. Antiplatelet and antithrombotic effects of cordycepin-enriched WIB-801CE from Cordyceps militaris ex vivo, in vivo, and in vitro.BMC Complement. Altern. Med.201616150810.1186/s12906‑016‑1463‑827927214
    [Google Scholar]
  41. YaoW.L. KoB.S. LiuT.A. LiangS.M. LiuC.C. LuY.J. TzeanS.S. ShenT.L. LiouJ.Y. Cordycepin suppresses integrin/FAK signaling and epithelial-mesenchymal transition in hepatocellular carcinoma.Anticancer. Agents Med. Chem.2014141293410.2174/1871520611313999030523855336
    [Google Scholar]
  42. CuiZ.Y. ParkS.J. JoE. HwangI.H. LeeK.B. KimS.W. KimD.J. JooJ.C. HongS.H. LeeM.G. JangI.S. Cordycepin induces apoptosis of human ovarian cancer cells by inhibiting CCL5-mediated Akt/NF-κB signaling pathway.Cell Death Discov.2018416210.1038/s41420‑018‑0063‑429844932
    [Google Scholar]
  43. ZhangY. ChengJ. SuY. LiM. WenJ. LiS. Cordycepin induces M1/M2 macrophage polarization to attenuate the liver and lung damage and immunodeficiency in immature mice with sepsis via NF-κB/p65 inhibition.J. Pharm. Pharmacol.202274222723510.1093/jpp/rgab16234850068
    [Google Scholar]
  44. BrunsR.F. Role of adenosine in energy supply/demand balance.Nucleosides Nucleotides199110593194310.1080/07328319108047231
    [Google Scholar]
  45. BurnstockG. VerkhratskyA. Receptors for purines and pyrimidines.Pharmacol. Rev.201250311924410.1007/978‑3‑642‑28863‑0_59755289
    [Google Scholar]
  46. NewbyA.C. Adenosine and the concept of ‘retaliatory metabolites’.Trends Biochem. Sci.198492424410.1016/0968‑0004(84)90176‑2
    [Google Scholar]
  47. OlahM.E. StilesG.L. Adenosine receptor subtypes: Characterization and therapeutic regulation.Annu. Rev. Pharmacol. Toxicol.199535158160610.1146/annurev.pa.35.040195.0030537598508
    [Google Scholar]
  48. PeleliM. FredholmB.B. SobreviaL. CarlströmM. Pharmacological targeting of adenosine receptor signaling.Mol. Aspects Med.2017554810.1016/j.mam.2016.12.00228088486
    [Google Scholar]
  49. ShryockJ.C. BelardinelliL. Adenosine and adenosine receptors in the cardiovascular system: Biochemistry, physiology, and pharmacology.Am. J. Cardiol.19977912A21010.1016/S0002‑9149(97)00256‑7
    [Google Scholar]
  50. RossJ. Energy transfer from adenosine triphosphate.J. Phys. Chem. B2006110136987699010.1021/jp055686216571012
    [Google Scholar]
  51. VallonV. OsswaldH. Adenosine receptors and the kidney.Handb. Exp. Pharmacol.200919319344347010.1007/978‑3‑540‑89615‑9_1519639291
    [Google Scholar]
  52. HuangZ.L. UradeY. HayaishiO. The role of adenosine in the regulation of sleep.Curr. Top. Med. Chem.20111181047105710.2174/15680261179534765421401496
    [Google Scholar]
  53. JiangY. WongJ.H. FuM. NgT.B. LiuZ.K. WangC.R. LiN. QiaoW.T. WenT.Y. LiuF. Isolation of adenosine, iso-sinensetin and dimethylguanosine with antioxidant and HIV-1 protease inhibiting activities from fruiting bodies of Cordyceps militaris.Phytomedicine2011182-318919310.1016/j.phymed.2010.04.01020576416
    [Google Scholar]
  54. HaskóG. PacherP. Regulation of macrophage function by adenosine.Arterioscler. Thromb. Vasc. Biol.201232486586910.1161/ATVBAHA.111.22685222423038
    [Google Scholar]
  55. WolskaN. RozalskiM. Blood platelet adenosine receptors as potential targets for anti-platelet therapy.Int. J. Mol. Sci.20192021547510.3390/ijms2021547531684173
    [Google Scholar]
  56. FredholmB.B. IJzermanA.P. JacobsonK.A. KlotzK.N. LindenJ. International union of pharmacology. XXV. Nomenclature and classification of adenosine receptors.Pharmacol. Rev.200153452755211734617
    [Google Scholar]
  57. BrugarolasM. NavarroG. PinillaM.E. AngelatsE. CasadóV. LanciegoJ.L. FrancoR. G-protein-coupled receptor heteromers as key players in the molecular architecture of the central nervous system.CNS Neurosci. Ther.201420870370910.1111/cns.1227724809909
    [Google Scholar]
  58. FredholmB.B. IJzermanA.P. JacobsonK.A. LindenJ. MüllerC.E. International union of basic and clinical pharmacology. LXXXI. Nomenclature and classification of adenosine receptors--An update.Pharmacol. Rev.201163113410.1124/pr.110.00328521303899
    [Google Scholar]
  59. DickensonJ.M. BlankJ.L. HillS.J. Human adenosine A 1 receptor and P2Y 2 ‐purinoceptor‐mediated activation of the mitogen‐activated protein kinase cascade in transfected CHO cells.Br. J. Pharmacol.199812471491149910.1038/sj.bjp.07019779723963
    [Google Scholar]
  60. SchulteG. FredholmB.B. Signalling from adenosine receptors to mitogen-activated protein kinases.Cell. Signal.200315981382710.1016/S0898‑6568(03)00058‑512834807
    [Google Scholar]
  61. PretiD. BaraldiP.G. MoormanA.R. BoreaP.A. VaraniK. History and perspectives of A2A adenosine receptor antagonists as potential therapeutic agents.Med. Res. Rev.201535479084810.1002/med.2134425821194
    [Google Scholar]
  62. WuF. YanH. MaX. JiaJ. ZhangG. GuoX. GuiZ. Comparison of the structural characterization and biological activity of acidic polysaccharides from Cordyceps militaris cultured with different media.World J. Microbiol. Biotechnol.20122852029203810.1007/s11274‑012‑1005‑622806024
    [Google Scholar]
  63. ElkhateebW. DabaG. ThomasP. WenT-C. Medicinal mushrooms as a new source of natural therapeutic bioactive compounds.Egypt. Pharm. J.201918288101
    [Google Scholar]
  64. ChenX. WuG. HuangZ. Structural analysis and antioxidant activities of polysaccharides from cultured Cordyceps militaris.Int. J. Biol. Macromol.201358182210.1016/j.ijbiomac.2013.03.04123537797
    [Google Scholar]
  65. JingY. CuiX. ChenZ. HuangL. SongL. LiuT. LvW. YuR. Elucidation and biological activities of a new polysaccharide from cultured Cordyceps militaris.Carbohydr. Polym.201410228829610.1016/j.carbpol.2013.11.06124507284
    [Google Scholar]
  66. WangL. XuN. ZhangJ. ZhaoH. LinL. JiaS. JiaL. Antihyperlipidemic and hepatoprotective activities of residue polysaccharide from Cordyceps militaris SU-12.Carbohydr. Polym.201513135536210.1016/j.carbpol.2015.06.01626256194
    [Google Scholar]
  67. LiuJ. Immunomodulatory and antioxidative activity of Cordyceps militaris polysaccharides in mice.Int. J. Biol. Macromol.20168659459810.1016/j.ijbiomac.2016.02.00926853825
    [Google Scholar]
  68. DongY. HuS. LiuC. MengQ. SongJ. LuJ. ChengY. GaoC. LiuY. WangD. TengL. Purification of polysaccharides from Cordyceps militaris and their anti-hypoxic effect.Mol. Med. Rep.20151121312131710.3892/mmr.2014.278625351532
    [Google Scholar]
  69. MethacanonP. MadlaS. KirtikaraK. PrasitsilM. Structural elucidation of bioactive fungi-derived polymers.Carbohydr. Polym.200560219920310.1016/j.carbpol.2004.12.006
    [Google Scholar]
  70. RaoY.K. FangS.H. WuW.S. TzengY.M. Constituents isolated from Cordyceps militaris suppress enhanced inflammatory mediator’s production and human cancer cell proliferation.J. Ethnopharmacol.2010131236336710.1016/j.jep.2010.07.02020633630
    [Google Scholar]
  71. NallathambyN. Guan-SermL. VidyadaranS. MalekS.N.A. RamanJ. SabaratnamV. Ergosterol of Cordyceps militaris attenuates LPS induced inflammation in BV2 microglia cells. Nat. Prod. Commun.20151061934578X1501000623.10.1177/1934578X1501000623
    [Google Scholar]
  72. ZhangJ. ZhangW. YinZ. LiC. KangW. Procoagulant constituents from Cordyceps militaris.Food Sci. Hum. Wellness20187428228610.1016/j.fshw.2018.11.001
    [Google Scholar]
  73. WongJ.H. NgT.B. WangH. SzeS.C.W. ZhangK.Y. LiQ. LuX. Cordymin, an antifungal peptide from the medicinal fungus Cordyceps militaris.Phytomedicine201118538739210.1016/j.phymed.2010.07.01020739167
    [Google Scholar]
  74. SongJ. WangY. TengM. ZhangS. YinM. LuJ. LiuY. LeeR.J. WangD. TengL. Cordyceps militaris induces tumor cell death via the caspase-dependent mitochondrial pathway in HepG2 and MCF-7 cells.Mol. Med. Rep.20161365132514010.3892/mmr.2016.517527109250
    [Google Scholar]
  75. YuanG. DuP. XuG. AnL. XieL. LiH. ShengY. HanX. Immunomodulatory mechanism of Cordyceps militaris polypeptide through regulating gene Hist1h2bp, Ctsg, and elane in mice.Pharmacogn. Mag.2018145640410.4103/pm.pm_412_17
    [Google Scholar]
  76. HuangL. LiangY.Z. GuoF.Q. ZhouZ.F. ChengB.M. Simultaneous separation and determination of active components in Cordyceps sinensis and Cordyceps militarris by LC/ESI-MS.J. Pharm. Biomed. Anal.20033351155116210.1016/S0731‑7085(03)00415‑114656607
    [Google Scholar]
  77. LeeK.H. MinT.J. Purification and Characterization of a Chitinase in Culture Media of Cordyceps militaris (Linn.).Link. Hanguk Kyun. Hakoe Chi200331316817410.4489/KJM.2003.31.3.168
    [Google Scholar]
  78. RukachaisirikulV. PramjitS. PakawatchaiC. IsakaM. SupothinaS. 10-membered macrolides from the insect pathogenic fungus Cordyceps militaris BCC 2816.J. Nat. Prod.200467111953195510.1021/np040141515568800
    [Google Scholar]
  79. WangZ. HeZ. LiS. YuanQ. Purification and partial characterization of Cu, Zn containing superoxide dismutase from entomogenous fungal species Cordyceps militaris.Enzyme Microb. Technol.200536786286910.1016/j.enzmictec.2004.12.026
    [Google Scholar]
  80. JungE.C. KimK.D. BaeC.H. KimJ.C. KimD.K. KimH.H. A mushroom lectin from ascomycete Cordyceps militaris.Biochim. Biophys. Acta, Gen. Subj.20071770583383810.1016/j.bbagen.2007.01.00517306462
    [Google Scholar]
  81. DongJ.Z. WangS.H. AiX.R. YaoL. SunZ.W. LeiC. WangY. WangQ. Composition and characterization of cordyxanthins from Cordyceps militaris fruit bodies.J. Funct. Foods2013531450145510.1016/j.jff.2013.06.002
    [Google Scholar]
  82. ChanJ.S.L. BarseghyanG.S. AsatianiM.D. WasserS.P. Chemical composition and medicinal value of fruiting bodies and submerged cultured mycelia of caterpillar medicinal fungus Cordyceps militaris CBS-132098 (Ascomycetes).Int. J. Med. Mushrooms201517764965910.1615/IntJMedMushrooms.v17.i7.5026559699
    [Google Scholar]
  83. ChiuC.P. LiuS.C. TangC.H. ChanY. El-ShazlyM. LeeC.L. DuY.C. WuT.Y. ChangF.R. WuY.C. Anti-inflammatory cerebrosides from cultivated Cordyceps militaris.J. Agric. Food Chem.20166471540154810.1021/acs.jafc.5b0593126853111
    [Google Scholar]
  84. SorokinaM. SteinbeckC. Review on natural products databases: Where to find data in 2020.J. Cheminform.20201212010.1186/s13321‑020‑00424‑933431011
    [Google Scholar]
  85. GarciaN.L. TawfikD.S. Enzyme evolution in natural products biosynthesis: Target- or diversity-oriented?Curr. Opin. Chem. Biol.20205914715410.1016/j.cbpa.2020.05.01132771972
    [Google Scholar]
  86. XiaoG. ZhangX. GaoQ. Bioinformatic approaches for fungal omics.BioMed Res. Int.20172017110.1155/2017/727048528396870
    [Google Scholar]
  87. ThomfordN. SenthebaneD. RoweA. MunroD. SeeleP. MaroyiA. DzoboK. Natural products for drug discovery in the 21st century: Innovations for novel drug discovery.Int. J. Mol. Sci.2018196157810.3390/ijms1906157829799486
    [Google Scholar]
  88. SayersE.W. BoltonE.E. BristerJ.R. CaneseK. ChanJ. ComeauD.C. ConnorR. FunkK. KellyC. KimS. MadejT. BauerM.A. LanczyckiC. LathropS. LuZ. NissenT.F. MurphyT. PhanL. SkripchenkoY. TseT. WangJ. WilliamsR. TrawickB.W. PruittK.D. SherryS.T. Database resources of the national center for biotechnology information.Nucleic Acids Res.202250D1D20D2610.1093/nar/gkab111234850941
    [Google Scholar]
  89. CrousP.W. GamsW. StalpersJ.A. RobertV. StegehuisG. MycoBank: An online initiative to launch mycology into the 21st century.Stud. Mycol.20045011922
    [Google Scholar]
  90. RobertV. VuD. AmorA.B.H. van de WieleN. BrouwerC. JabasB. SzokeS. DridiA. TrikiM. DaoudS. ChouchenO. VaasL. de CockA. StalpersJ.A. StalpersD. VerkleyG.J.M. GroenewaldM. dos SantosF.B. StegehuisG. LiW. WuL. ZhangR. MaJ. ZhouM. GorjónS.P. EurwilaichitrL. IngsriswangS. HansenK. SchochC. RobbertseB. IrinyiL. MeyerW. CardinaliG. HawksworthD.L. TaylorJ.W. CrousP.W. MycoBank gearing up for new horizons.IMA Fungus20134237137910.5598/imafungus.2013.04.02.1624563843
    [Google Scholar]
  91. GrigorievI.V. NikitinR. HaridasS. KuoA. OhmR. OtillarR. RileyR. SalamovA. ZhaoX. KorzeniewskiF. SmirnovaT. NordbergH. DubchakI. ShabalovI. MycoCosm portal: Gearing up for 1000 fungal genomes.Nucleic Acids Res.201442D1D699D70410.1093/nar/gkt118324297253
    [Google Scholar]
  92. BasenkoE. PulmanJ. ShanmugasundramA. HarbO. CrouchK. StarnsD. WarrenfeltzS. AurrecoecheaC. StoeckertC.Jr KissingerJ. RoosD. FowlerH.C. FungiD.B. FungiDB. An integrated bioinformatic resource for fungi and oomycetes.J. Fungi 2018413910.3390/jof401003930152809
    [Google Scholar]
  93. VětrovskýT. MoraisD. KohoutP. LepinayC. AlgoraC. HolláA.S. BahnmannB.D. BílohnědáK. BrabcováV. D’AlòF. HumanZ.R. JomuraM. KolaříkM. KvasničkováJ. LladóS. MondéjarL.R. MartinovićT. MašínováT. MeszárošováL. MichalčíkováL. MichalováT. MundraS. NavrátilováD. OdriozolaI. ChoquetteP.S. ŠtursováM. ŠvecK. TláskalV. UrbanováM. VlkL. VoříškováJ. ŽifčákováL. BaldrianP. GlobalFungi, a global database of fungal occurrences from high-throughput-sequencing metabarcoding studies.Sci. Data20207122810.1038/s41597‑020‑0567‑731896794
    [Google Scholar]
  94. HarrisonP.W. AhamedA. AslamR. AlakoB.T.F. BurginJ. BusoN. CourtotM. FanJ. GuptaD. HaseebM. HoltS. IbrahimT. IvanovE. JayathilakaS. KadhirveluB.V. KumarM. LopezR. KayS. LeinonenR. LiuX. O’CathailC. PaksereshtA. ParkY. PesantS. RahmanN. RajanJ. SokolovA. VijayarajaS. WaheedZ. ZyoudA. BurdettT. CochraneG. The European nucleotide archive in 2020.Nucleic Acids Res.202149D1D82D8510.1093/nar/gkaa102833175160
    [Google Scholar]
  95. FukudaA. KodamaY. MashimaJ. FujisawaT. OgasawaraO. DDBJ update: Streamlining submission and access of human data.Nucleic Acids Res.202149D1D71D7510.1093/nar/gkaa98233156332
    [Google Scholar]
  96. RobbertseB. TatusovaT. Fungal genome resources at NCBI.Mycology20112314216010.1080/21501203.2011.58422737589
    [Google Scholar]
  97. OlteanH.N. EtienneK.A. RoeC.C. GadeL. McCotterO.Z. EngelthalerD.M. LitvintsevaA.P. Utility of whole-genome sequencing to ascertain locally acquired cases of coccidioidomycosis, Washington, USA.Emerg. Infect. Dis.201925350150610.3201/eid2503.18115530789132
    [Google Scholar]
  98. HoweK.L. AchuthanP. AllenJ. AllenJ. JarretaA.J. AmodeM.R. ArmeanI.M. AzovA.G. BennettR. BhaiJ. BillisK. BodduS. CharkhchiM. CumminsC. Da FiorettoR.L. DavidsonC. DodiyaK. HoudaiguiE.B. FatimaR. GallA. GironG.C. GregoT. ClarkeG.C. HaggertyL. HemromA. HourlierT. IzuoguO.G. JuettemannT. KaikalaV. KayM. LavidasI. LeT. LemosD. MartinezG.J. MarugánJ.C. MaurelT. McMahonA.C. MohananS. MooreB. MuffatoM. OhehD.N. ParaschasD. ParkerA. PartonA. ProsovetskaiaI. SakthivelM.P. SalamA.I.A. SchmittB.M. SchuilenburgH. SheppardD. SteedE. SzpakM. SzubaM. TaylorK. ThormannA. ThreadgoldG. WaltsB. WinterbottomA. ChakiachviliM. ChaubalA. De SilvaN. FlintB. FrankishA. HuntS.E. IIsley, G.R.; Langridge, N.; Loveland, J.E.; Martin, F.J.; Mudge, J.M.; Morales, J.; Perry, E.; Ruffier, M.; Tate, J.; Thybert, D.; Trevanion, S.J.; Cunningham, F.; Yates, A.D.; Zerbino, D.R.; Flicek, P. Ensembl 2021.Nucleic Acids Res.202149D1D884D89110.1093/nar/gkaa94233137190
    [Google Scholar]
  99. CruickshanksH.A. McBryanT. NelsonD.M. VanderKraatsN.D. ShahP.P. van TuynJ. RaiS.T. BrockC. DonahueG. DunicanD.S. DrotarM.E. MeehanR.R. EdwardsJ.R. BergerS.L. AdamsP.D. Senescent cells harbour features of the cancer epigenome.Nat. Cell Biol.201315121495150610.1038/ncb287924270890
    [Google Scholar]
  100. OonoY. KobayashiF. KawaharaY. YazawaT. HandaH. ItohT. MatsumotoT. Characterisation of the wheat (Triticum aestivum L.) transcriptome by de novo assembly for the discovery of phosphate starvation-responsive genes: Gene expression in Pi-stressed wheat.BMC Genomics20131417710.1186/1471‑2164‑14‑7723379779
    [Google Scholar]
  101. DarmanisS. NongR.Y. VänelidJ. SiegbahnA. EricssonO. FredrikssonS. BäcklinC. GutM. HeathS. GutI.G. WallentinL. GustafssonM.G. MoghaddamK.M. LandegrenU. ProteinSeq: High-performance proteomic analyses by proximity ligation and next generation sequencing.PLoS One201169e2558310.1371/journal.pone.002558321980495
    [Google Scholar]
  102. KellD.B. OliverS.G. The metabolome 18 years on: A concept comes of age.Metabolomics201612914810.1007/s11306‑016‑1108‑427695392
    [Google Scholar]
  103. ShendureJ. JiH. Next-generation DNA sequencing.Nat. Biotechnol.200826101135114510.1038/nbt148618846087
    [Google Scholar]
  104. MakA.C.Y. LaiY.Y.Y. LamE.T. KwokT.P. LeungA.K.Y. PoonA. MostovoyY. HastieA.R. StedmanW. AnantharamanT. AndrewsW. ZhouX. PangA.W.C. DaiH. ChuC. LinC. WuJ.J.K. LiC.M.L. LiJ.W. YimA.K.Y. ChanS. SibertJ. DžakulaŽ. CaoH. YiuS.M. ChanT.F. YipK.Y. XiaoM. KwokP.Y. Genome-wide structural variation detection by genome mapping on nanochannel arrays.Genetics2016202135136210.1534/genetics.115.18348326510793
    [Google Scholar]
  105. EidJ. FehrA. GrayJ. LuongK. LyleJ. OttoG. PelusoP. RankD. BaybayanP. BettmanB. BibilloA. BjornsonK. ChaudhuriB. ChristiansF. CiceroR. ClarkS. DalalR. DeWinterA. DixonJ. FoquetM. GaertnerA. HardenbolP. HeinerC. HesterK. HoldenD. KearnsG. KongX. KuseR. LacroixY. LinS. LundquistP. MaC. MarksP. MaxhamM. MurphyD. ParkI. PhamT. PhillipsM. RoyJ. SebraR. ShenG. SorensonJ. TomaneyA. TraversK. TrulsonM. VieceliJ. WegenerJ. WuD. YangA. ZaccarinD. ZhaoP. ZhongF. KorlachJ. TurnerS. Real-time DNA sequencing from single polymerase molecules.Science2009323591013313810.1126/science.1162986
    [Google Scholar]
  106. RobertsR.J. CarneiroM.O. SchatzM.C. The advantages of SMRT sequencing.Genome Biol.201314640510.1186/gb‑2013‑14‑6‑40523822731
    [Google Scholar]
  107. AigleB. LautruS. SpitellerD. DickschatJ.S. ChallisG.L. LeblondP. PernodetJ.L. Genome mining of Streptomyces ambofaciens.J. Ind. Microbiol. Biotechnol.201441225126310.1007/s10295‑013‑1379‑y24258629
    [Google Scholar]
  108. EscribanoG.J. AltS. BibbM. Next generation sequencing of actinobacteria for the discovery of novel natural products.Mar. Drugs20161447810.3390/md1404007827089350
    [Google Scholar]
  109. UeokaR. BhushanA. ProbstS.I. BrayW.M. LokeyR.S. LiningtonR.G. PielJ. Genome‐based identification of a plant‐associated marine bacterium as a rich natural product source.Angew. Chem. Int. Ed.20185744145191452310.1002/anie.20180567330025185
    [Google Scholar]
  110. NiehsS.P. DoseB. RichterS. PidotS.J. DahseH.M. StinearT.P. HertweckC. Mining symbionts of a spider‐transmitted fungus illuminates uncharted biosynthetic pathways to cytotoxic benzolactones.Angew. Chem. Int. Ed.202059207766777110.1002/anie.20191600732040253
    [Google Scholar]
  111. SchatzM.C. DelcherA.L. SalzbergS.L. Assembly of large genomes using second-generation sequencing.Genome Res.20102091165117310.1101/gr.101360.10920508146
    [Google Scholar]
  112. ZhengP. XiaY. XiaoG. XiongC. HuX. ZhangS. ZhengH. HuangY. ZhouY. WangS. ZhaoG.P. LiuX. St LegerR.J. WangC. Genome sequence of the insect pathogenic fungus Cordyceps militaris, a valued traditional chinese medicine.Genome Biol.20111211R11610.1186/gb‑2011‑12‑11‑r11622112802
    [Google Scholar]
  113. KramerG.J. NodwellJ.R. Chromosome level assembly and secondary metabolite potential of the parasitic fungus Cordyceps militaris.BMC Genomics201718191210.1186/s12864‑017‑4307‑029178836
    [Google Scholar]
  114. ChenY. WuY. LiuL. FengJ. ZhangT. QinS. ZhaoX. WangC. LiD. HanW. ShaoM. ZhaoP. XueJ. LiuX. LiH. ZhaoE. ZhaoW. GuoX. JinY. CaoY. CuiL. ZhouZ. XiaQ. RaoZ. ZhangY. Study of the whole genome, methylome and transcriptome of Cordyceps militaris.Sci. Rep.20199189810.1038/s41598‑018‑38021‑430696919
    [Google Scholar]
  115. BensonG. Tandem repeats finder: A program to analyze DNA sequences.Nucleic Acids Res.199927257358010.1093/nar/27.2.5739862982
    [Google Scholar]
  116. FlynnJ.M. HubleyR. GoubertC. RosenJ. ClarkA.G. FeschotteC. SmitA.F. RepeatModeler2 for automated genomic discovery of transposable element families.Proc. Natl. Acad. Sci. 2020117179451945710.1073/pnas.192104611732300014
    [Google Scholar]
  117. SmithA. HubleyR. GreenP. RepeatMasker Open-4.0. 2013.Available from: https://www.repeatmasker.org/
    [Google Scholar]
  118. BaoW. KojimaK.K. KohanyO. Repbase update, a database of repetitive elements in eukaryotic genomes.Mob. DNA2015611110.1186/s13100‑015‑0041‑926045719
    [Google Scholar]
  119. SlaterG.S.C. BirneyE. Automated generation of heuristics for biological sequence comparison.BMC Bioinformat.2005613110.1186/1471‑2105‑6‑3115713233
    [Google Scholar]
  120. KeilwagenJ. WenkM. EricksonJ.L. SchattatM.H. GrauJ. HartungF. Using intron position conservation for homology-based gene prediction.Nucleic Acids Res.2016449e89e8910.1093/nar/gkw09226893356
    [Google Scholar]
  121. SolovyevV. KosarevP. SeledsovI. VorobyevD. Automatic annotation of eukaryotic genes, pseudogenes and promoters.Genome Biol.20067S1S1010.1186/gb‑2006‑7‑s1‑s1016925832
    [Google Scholar]
  122. ScalzittiN. Jeannin-GirardonA. ColletP. PochO. ThompsonJ.D. A benchmark study of ab initio gene prediction methods in diverse eukaryotic organisms.BMC Genomics202021129310.1186/s12864‑020‑6707‑932272892
    [Google Scholar]
  123. WrightJ.C. SugdenD. McIntyreF.S. GarciaR.I. GaskellS.J. GrigorievI.V. BakerS.E. BeynonR.J. HubbardS.J. Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger.BMC Genomics20091016110.1186/1471‑2164‑10‑6119193216
    [Google Scholar]
  124. TrapnellC. WilliamsB.A. PerteaG. MortazaviA. KwanG. van BarenM.J. SalzbergS.L. WoldB.J. PachterL. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation.Nat. Biotechnol.201028551151510.1038/nbt.162120436464
    [Google Scholar]
  125. AltschulS.F. GishW. MillerW. MyersE.W. LipmanD.J. Basic local alignment search tool.J. Mol. Biol.1990215340341010.1016/S0022‑2836(05)80360‑22231712
    [Google Scholar]
  126. BrinkmanF.S.L. WanI. HancockR.E.W. RoseA.M. JonesS.J. PhyloBLAST: Facilitating phylogenetic analysis of BLAST results.Bioinformatics200117438538710.1093/bioinformatics/17.4.38511301315
    [Google Scholar]
  127. EnrightA.J. Van DongenS. OuzounisC.A. An efficient algorithm for large-scale detection of protein families.Nucleic Acids Res.20023071575158410.1093/nar/30.7.157511917018
    [Google Scholar]
  128. GasteigerJ. The central role of chemoinformatics.Chemom. Intell. Lab. Syst.2006821-220020910.1016/j.chemolab.2005.06.022
    [Google Scholar]
  129. AltschulS. MaddenT.L. SchäfferA.A. ZhangJ. ZhangZ. MillerW. LipmanD.J. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs.Nucleic Acids Res.199725173389340210.1093/nar/25.17.33899254694
    [Google Scholar]
  130. EddyS.R. Profile hidden Markov models.Bioinformatics199814975576310.1093/bioinformatics/14.9.7559918945
    [Google Scholar]
  131. ShaferP. LinD.M. YonaG. EST2Prot: Mapping EST sequences to proteins.BMC Genomics2006714110.1186/1471‑2164‑7‑4116515706
    [Google Scholar]
  132. HanY. BurnetteJ.M.III WesslerS.R. TARGeT: A web-based pipeline for retrieving and characterizing gene and transposable element families from genomic sequences.Nucleic Acids Res.20093711e7810.1093/nar/gkp29519429695
    [Google Scholar]
  133. BurgeC. KarlinS. Prediction of complete gene structures in human genomic DNA.J. Mol. Biol.19972681789410.1006/jmbi.1997.09519149143
    [Google Scholar]
  134. SalzbergS.L. PerteaM. DelcherA.L. GardnerM.J. TettelinH. Interpolated Markov models for eukaryotic gene finding.Genomics1999591243110.1006/geno.1999.585410395796
    [Google Scholar]
  135. KorfI. Gene finding in novel genomes.BMC Bioinformatics2004515910.1186/1471‑2105‑5‑5915144565
    [Google Scholar]
  136. BorodovskyM. LomsadzeA. Eukaryotic gene prediction using GeneMark. Hmm-E and GeneMark-ES.Curr Protoc Bioinformat20114.6.14.6.1010.1002/0471250953.bi0406s35
    [Google Scholar]
  137. CantarelB.L. KorfI. RobbS.M.C. ParraG. RossE. MooreB. HoltC. AlvaradoS.A. YandellM. MAKER: An easy-to-use annotation pipeline designed for emerging model organism genomes.Genome Res.200818118819610.1101/gr.674390718025269
    [Google Scholar]
  138. StankeM. SteinkampR. WaackS. MorgensternB. AUGUSTUS: A web server for gene finding in eukaryotes.Nucleic Acids Res.200432S2W309W31210.1093/nar/gkh37915215400
    [Google Scholar]
  139. TestaA.C. HaneJ.K. EllwoodS.R. OliverR.P. CodingQuarry: Highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts.BMC Genomics201516117010.1186/s12864‑015‑1344‑425887563
    [Google Scholar]
  140. HoltC. YandellM. MAKER2: An annotation pipeline and genome-database management tool for second-generation genome projects.BMC Bioinformat.201112149110.1186/1471‑2105‑12‑49122192575
    [Google Scholar]
  141. EilbeckK. MooreB. HoltC. YandellM. Quantitative measures for the management and comparison of annotated genomes.BMC Bioinformatics20091016710.1186/1471‑2105‑10‑6719236712
    [Google Scholar]
  142. GasteigerE. GattikerA. HooglandC. IvanyiI. AppelR.D. BairochA. ExPASy: The proteomics server for in-depth protein knowledge and analysis.Nucleic Acids Res.200331133784378810.1093/nar/gkg56312824418
    [Google Scholar]
  143. BoutetE. LieberherrD. TognolliM. SchneiderM. BansalP. BridgeA.J. PouxS. BougueleretL. XenariosI. Uniprotkb/swiss-prot, the manually annotated section of the uniprot knowledgebase: How to use the entry view.Methods Mol. Biol.20161374235410.1007/978‑1‑4939‑3167‑5_2
    [Google Scholar]
  144. FinnR.D. AttwoodT.K. BabbittP.C. BatemanA. BorkP. BridgeA.J. ChangH.Y. DosztányiZ. El-GebaliS. FraserM. GoughJ. HaftD. HollidayG.L. HuangH. HuangX. LetunicI. LopezR. LuS. BauerM.A. MiH. MistryJ. NataleD.A. NecciM. NukaG. OrengoC.A. ParkY. PesseatS. PiovesanD. PotterS.C. RawlingsN.D. RedaschiN. RichardsonL. RivoireC. VegasS.A. SigristC. SillitoeI. SmithersB. SquizzatoS. SuttonG. ThankiN. ThomasP.D. TosattoS.C.E. WuC.H. XenariosI. YehL.S. YoungS.Y. MitchellA.L. InterPro in 2017—beyond protein family and domain annotations.Nucleic Acids Res.201745D1D190D19910.1093/nar/gkw110727899635
    [Google Scholar]
  145. El-GebaliS. MistryJ. BatemanA. EddyS.R. LucianiA. PotterS.C. QureshiM. RichardsonL.J. SalazarG.A. SmartA. SonnhammerE.L.L. HirshL. PaladinL. PiovesanD. TosattoS.C.E. FinnR.D. The Pfam protein families database in 2019.Nucleic Acids Res.201947D1D427D43210.1093/nar/gky99530357350
    [Google Scholar]
  146. SaierM.H.Jr ReddyV.S. TsuB.V. AhmedM.S. LiC. HagelsiebM.G. The transporter classification database (TCDB): recent advances.Nucleic Acids Res.201644D1D372D37910.1093/nar/gkv110326546518
    [Google Scholar]
  147. GalperinM.Y. MakarovaK.S. WolfY.I. KooninE.V. Expanded microbial genome coverage and improved protein family annotation in the COG database.Nucleic Acids Res.201543D1D261D26910.1093/nar/gku122325428365
    [Google Scholar]
  148. RawlingsN.D. BarrettA.J. BatemanA. Merops: The peptidase database.Nucleic Acids Res.201038S1D227D23310.1093/nar/gkp97119892822
    [Google Scholar]
  149. SirimD. WagnerF. LisitsaA. PleissJ. The cytochrome P450 engineering database: Integration of biochemical properties.BMC Biochem.20091012710.1186/1471‑2091‑10‑2719909539
    [Google Scholar]
  150. GriesemerM. KimbrelJ.A. ZhouC.E. NavidA. D’haeseleerP. Combining multiple functional annotation tools increases coverage of metabolic annotation.BMC Genomics201819194810.1186/s12864‑018‑5221‑930567498
    [Google Scholar]
  151. AshburnerM. BallC.A. BlakeJ.A. BotsteinD. ButlerH. CherryJ.M. DavisA.P. DolinskiK. DwightS.S. EppigJ.T. HarrisM.A. HillD.P. Issel-TarverL. KasarskisA. LewisS. MateseJ.C. RichardsonJ.E. RingwaldM. RubinG.M. SherlockG. Gene Ontology: Tool for the unification of biology.Nat. Genet.2000251252910.1038/7555610802651
    [Google Scholar]
  152. KanehisaM. SatoY. KawashimaM. FurumichiM. TanabeM. KEGG as a reference resource for gene and protein annotation.Nucleic Acids Res.201644D1D457D46210.1093/nar/gkv107026476454
    [Google Scholar]
  153. LouH.W. ZhaoY. TangH.B. YeZ.W. WeiT. LinJ.F. GuoL.Q. Transcriptome analysis of Cordyceps militaris reveals genes associated with carotenoid synthesis and identification of the function of the Cmtns gene.Front. Microbiol.201910210510.3389/fmicb.2019.0210531552008
    [Google Scholar]
  154. ChenB.X. WeiT. XueL.N. ZhengQ.W. YeZ.W. ZouY. YangY. YunF. GuoL.Q. LinJ.F. Transcriptome analysis reveals the flexibility of cordycepin network in Cordyceps militaris activated by L-alanine addition.Front. Microbiol.20201157710.3389/fmicb.2020.0057732390960
    [Google Scholar]
  155. WuQ.X. MuellerG.M. LutzoniF.M. HuangY.Q. GuoS.Y. Phylogenetic and biogeographic relationships of eastern Asian and eastern North American disjunct Suillus species (fungi) as inferred from nuclear ribosomal RNA ITS sequences.Mol. Phylogenet. Evol.2000171374710.1006/mpev.2000.081211020303
    [Google Scholar]
  156. PowellJ.R. ParrentJ.L. HartM.M. KlironomosJ.N. RilligM.C. MaheraliH. Phylogenetic trait conservatism and the evolution of functional trade-offs in arbuscular mycorrhizal fungi.Proc. Biol. Sci.200927616764237424510.1098/rspb.2009.101519740877
    [Google Scholar]
  157. FeauN. DecourcelleT. HussonC. LoustauD.M.L. DutechC. Finding single copy genes out of sequenced genomes for multilocus phylogenetics in non-model fungi.PLoS One201164e1880310.1371/journal.pone.001880321533204
    [Google Scholar]
  158. WangL. ZhangW.M. HuB. ChenY.Q. QuL.H. Genetic variation of cordyceps militaris and its allies based on phylogenetic analysis of RDNA ITS sequence data.Fungal Divers.200831147155
    [Google Scholar]
  159. NeedlemanS.B. WunschC.D. A general method applicable to the search for similarities in the amino acid sequence of two proteins.J. Mol. Biol.197048344345310.1016/0022‑2836(70)90057‑45420325
    [Google Scholar]
  160. SmithT.F. WatermanM.S. Identification of common molecular subsequences.J. Mol. Biol.1981147119519710.1016/0022‑2836(81)90087‑57265238
    [Google Scholar]
  161. ThompsonJ.D. HigginsD.G. GibsonT.J. CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.Nucleic Acids Res.199422224673468010.1093/nar/22.22.46737984417
    [Google Scholar]
  162. BartonG.J. SternbergM.J.E. A strategy for the rapid multiple alignment of protein sequences.J. Mol. Biol.1987198232733710.1016/0022‑2836(87)90316‑03430611
    [Google Scholar]
  163. AlonN. ChorB. PardiF. RapoportA. Approximate maximum parsimony and ancestral maximum likelihood.IEEE/ACM Trans. Comput. Biol. Bioinformatics20107118318710.1109/TCBB.2008.1320150680
    [Google Scholar]
  164. SaitouN. NeiM. The neighbor-joining method: A new method for reconstructing phylogenetic trees.Mol. Biol. Evol.19874440642510.1093/oxfordjournals.molbev.a0404543447015
    [Google Scholar]
  165. GronauI. MoranS. Optimal implementations of UPGMA and other common clustering algorithms.Inf. Process. Lett.2007104620521010.1016/j.ipl.2007.07.002
    [Google Scholar]
  166. DaugelaiteJ. O’ DriscollA. SleatorR.D. An overview of multiple sequence alignments and cloud computing in bioinformatics.ISRN Biomath.2013201311410.1155/2013/615630
    [Google Scholar]
  167. NotredameC. HigginsD.G. HeringaJ. T-coffee: A novel method for fast and accurate multiple sequence alignment 1 1Edited byJ. Thornton. J. Mol. Biol.2000302120521710.1006/jmbi.2000.404210964570
    [Google Scholar]
  168. KatohK. MisawaK. KumaK. MiyataT. MAFFT: A novel method for rapid multiple sequence alignment based on fast Fourier transform.Nucleic Acids Res.200230143059306610.1093/nar/gkf43612136088
    [Google Scholar]
  169. EdgarR.C. MUSCLE: A multiple sequence alignment method with reduced time and space complexity.BMC Bioinformatics20045111310.1186/1471‑2105‑5‑11315318951
    [Google Scholar]
  170. SieversF. WilmA. DineenD. GibsonT.J. KarplusK. LiW. LopezR. McWilliamH. RemmertM. SödingJ. ThompsonJ.D. HigginsD.G. Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega.Mol. Syst. Biol.20117153910.1038/msb.2011.7521988835
    [Google Scholar]
  171. ParkJ.E. KimG.Y. ParkH.S. NamB.H. AnW.G. ChaJ.H. LeeT.H. LeeJ.D. Phylogenetic analysis of caterpillar fungi by comparing ITS 1-5.8S-ITS 2 ribosomal DNA sequences.Mycobiology200129312113110.1080/12298093.2001.12015773
    [Google Scholar]
  172. KangN. LeeH.H. ParkI. SeoY.S. Development of high cordycepin-producing cordyceps militaris strains.Mycobiology2017451313810.5941/MYCO.2017.45.1.3128435352
    [Google Scholar]
  173. KeplerR.M. Luangsa-ardJ.J. Hywel-JonesN.L. QuandtC.A. SungG.H. RehnerS.A. AimeM.C. HenkelT.W. SanjuanT. ZareR. ChenM. LiZ. RossmanA.Y. SpataforaJ.W. ShresthaB. A phylogenetically-based nomenclature for Cordycipitaceae (Hypocreales).IMA Fungus20178233535310.5598/imafungus.2017.08.02.0829242779
    [Google Scholar]
  174. WeberT. BlinK. DuddelaS. KrugD. KimH.U. BruccoleriR. LeeS.Y. FischbachM.A. MüllerR. WohllebenW. BreitlingR. TakanoE. MedemaM.H. antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters.Nucleic Acids Res.201543W1W237W24310.1093/nar/gkv43725948579
    [Google Scholar]
  175. KhaldiN. SeifuddinF.T. TurnerG. HaftD. NiermanW.C. WolfeK.H. FedorovaN.D. SMURF: Genomic mapping of fungal secondary metabolite clusters.Fungal Genet. Biol.201047973674110.1016/j.fgb.2010.06.00320554054
    [Google Scholar]
  176. VongsangnakW. MujchariyakulW. WizazaC. PatumcharoenpolP. KittichotiratW. Comparative gene clusters analysis of cordyceps militaris and related entomopathogenic fungi. ACM International Conference Proceeding Series, December 20182018,1610.1145/3291757.3291759
    [Google Scholar]
  177. WolfT. ShelestV. NathN. ShelestE. CASSIS and SMIPS: Promoter-based prediction of secondary metabolite gene clusters in eukaryotic genomes.Bioinformatics20163281138114310.1093/bioinformatics/btv71326656005
    [Google Scholar]
  178. ZierepP.F. CeciA.T. DobrusinI. KollmannR.S.C. GüntherS. SeMPI 2.0—A web server for PKS and NRPS predictions combined with metabolite screening in natural product databases.Metabolites20201111310.3390/metabo1101001333383692
    [Google Scholar]
  179. BlinK. KimH.U. MedemaM.H. WeberT. Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters.Brief. Bioinform.20192041103111310.1093/bib/bbx14629112695
    [Google Scholar]
  180. CimermancicP. MedemaM.H. ClaesenJ. KuritaK. BrownW.L.C. MavrommatisK. PatiA. GodfreyP.A. KoehrsenM. ClardyJ. BirrenB.W. TakanoE. SaliA. LiningtonR.G. FischbachM.A. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters.Cell2014158241242110.1016/j.cell.2014.06.03425036635
    [Google Scholar]
  181. UmemuraM. KoikeH. NaganoN. IshiiT. KawanoJ. YamaneN. KozoneI. HorimotoK. Shin-yaK. AsaiK. YuJ. BennettJ.W. MachidaM. MIDDAS-M: Motif-independent de novo detection of secondary metabolite gene clusters through the integration of genome sequencing and transcriptome data.PLoS One2013812e8402810.1371/journal.pone.008402824391870
    [Google Scholar]
  182. MuñozN.J.C. MojicaS.N. MullowneyM.W. KautsarS.A. TryonJ.H. ParkinsonE.I. De Los SantosE.L.C. YeongM. MoralesC.P. AbubuckerS. RoetersA. LokhorstW. GuerraF.A. CappeliniL.T.D. GoeringA.W. ThomsonR.J. MetcalfW.W. KelleherN.L. GomezB.F. MedemaM.H. A computational framework to explore large-scale biosynthetic diversity.Nat. Chem. Biol.2020161606810.1038/s41589‑019‑0400‑931768033
    [Google Scholar]
  183. BrownF.K. Chemoinformatics: What is it and how does it impact drug discovery.Annu. Rep. Med. Chem.19983337538410.1016/S0065‑7743(08)61100‑8
    [Google Scholar]
  184. MacalinoS.J.Y. GosuV. HongS. ChoiS. Role of computer-aided drug design in modern drug discovery.Arch. Pharm. Res.20153891686170110.1007/s12272‑015‑0640‑526208641
    [Google Scholar]
  185. MandalS. MoudgilM. MandalS.K. Rational drug design.Eur. J. Pharmacol.20096251-39010010.1016/j.ejphar.2009.06.06519835861
    [Google Scholar]
  186. AndersonA.C. The process of structure-based drug design.Chem. Biol.200310978779710.1016/j.chembiol.2003.09.00214522049
    [Google Scholar]
  187. KalyaanamoorthyS. ChenY.P.P. Structure-based drug design to augment hit discovery.Drug Discov. Today20111617-1883183910.1016/j.drudis.2011.07.00621810482
    [Google Scholar]
  188. BermanH.M. WestbrookJ. FengZ. GillilandG. BhatT.N. WeissigH. ShindyalovI.N. BourneP.E. The protein data bank.Nucleic Acids Res.200028123524210.1093/nar/28.1.23510592235
    [Google Scholar]
  189. ChengT. LiQ. ZhouZ. WangY. BryantS.H. Structure-based virtual screening for drug discovery: A problem-centric review.AAPS J.201214113314110.1208/s12248‑012‑9322‑022281989
    [Google Scholar]
  190. FangY. Ligand–receptor interaction platforms and their applications for drug discovery.Expert Opin. Drug Discov.201271096998810.1517/17460441.2012.71563122860803
    [Google Scholar]
  191. HartT.N. ReadR.J. A multiple‐start monte carlo docking method.Proteins199213320622210.1002/prot.3401303041603810
    [Google Scholar]
  192. JonesG. WillettP. GlenR.C. LeachA.R. TaylorR. Development and validation of a genetic algorithm for flexible docking 11Edited by F. E. Cohen. J. Mol. Biol.1997267372774810.1006/jmbi.1996.08979126849
    [Google Scholar]
  193. TeagueS.J. Implications of protein flexibility for drug discovery.Nat. Rev. Drug Discov.20032752754110.1038/nrd112912838268
    [Google Scholar]
  194. VerdonkM.L. ColeJ.C. HartshornM.J. MurrayC.W. TaylorR.D. Improved protein–ligand docking using GOLD.Proteins200352460962310.1002/prot.1046512910460
    [Google Scholar]
  195. TrottO. OlsonA.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.J. Comput. Chem.201031245546110.1002/jcc.2133419499576
    [Google Scholar]
  196. LangP.T. BrozellS.R. MukherjeeS. PettersenE.F. MengE.C. ThomasV. RizzoR.C. CaseD.A. JamesT.L. KuntzI.D. DOCK 6: Combining techniques to model RNA–small molecule complexes.RNA20091561219123010.1261/rna.156360919369428
    [Google Scholar]
  197. MorrisG.M. HueyR. LindstromW. SannerM.F. BelewR.K. GoodsellD.S. OlsonA.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility.J. Comput. Chem.200930162785279110.1002/jcc.2125619399780
    [Google Scholar]
  198. SirithepK. XiaoF. RaethongN. ZhangY. LaotengK. HuG. VongsangnakW. Probing carbon utilization of Cordyceps militaris by sugar transportome and protein structural analysis.Cells20209240110.3390/cells902040132050592
    [Google Scholar]
  199. PanyaA. SongprakhonP. PanwongS. JantakeeK. KaewkodT. TragoolpuaY. SawasdeeN. LeeV.S. NimmanpipugP. YenchitsomanusP. Cordycepin inhibits virus replication in dengue virus-infected vero cells.Molecules20212611311810.3390/molecules2611311834071102
    [Google Scholar]
  200. BibiS. HasanM.M. WangY-B. PapadakosS.P. YuH. Cordycepin as a promising inhibitor of SARS-CoV-2 RNA dependent RNA polymerase (RdRp).Curr. Med. Chem.202229115216210.2174/1875533XMTE3xNDEq034420502
    [Google Scholar]
  201. HanschC. A method for the correlation of biological activity and chemical structure.J. Am. Chem. Soc.19648681616162610.1021/ja01062a035
    [Google Scholar]
  202. PrathipatiP. DixitA. SaxenaA. Computer-aided drug design: Integration of structure-based and ligand-based approaches in drug design.Curr. Computeraided Drug Des.20073213314810.2174/157340907780809516
    [Google Scholar]
  203. TropshaA. Best practices for QSAR model development, validation, and exploitation.Mol. Inform.2010296-747648810.1002/minf.20100006127463326
    [Google Scholar]
  204. VaidyaA. JainS. JainS. JainA.K. AgrawalR.K. Quantitative structure-activity relationships: A novel approach of drug design and discovery.J. Pharm. Sci. Pharmacol.20141321923210.1166/jpsp.2014.1024
    [Google Scholar]
  205. VermaJ. KhedkarV. CoutinhoE. 3D-QSAR in drug design--A review.Curr. Top. Med. Chem.20101019511510.2174/15680261079023226019929826
    [Google Scholar]
  206. DamaleM. HarkeS. KhanK.F. ShindeD. SangshettiJ. Recent advances in multidimensional QSAR (4D-6D): A critical review.Mini Rev. Med. Chem.2014141355510.2174/1389557511313666010424195665
    [Google Scholar]
  207. CramerR.D. PattersonD.E. BunceJ.D. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.J. Am. Chem. Soc.1988110185959596710.1021/ja00226a00522148765
    [Google Scholar]
  208. CramerR.D. Topomer CoMFA: A design methodology for rapid lead optimization.J. Med. Chem.200346337438810.1021/jm020194o12540237
    [Google Scholar]
  209. MurciaM. MorrealeA. OrtizA.R. Comparative binding energy analysis considering multiple receptors: A step toward 3D-QSAR models for multiple targets.J. Med. Chem.200649216241625310.1021/jm060350h17034130
    [Google Scholar]
  210. DatarP.A. KhedkarS.A. MaldeA.K. CoutinhoE.C. Comparative residue interaction analysis (CoRIA): A 3D-QSAR approach to explore the binding contributions of active site residues with ligands.J. Comput. Aided Mol. Des.200620634336010.1007/s10822‑006‑9051‑517009094
    [Google Scholar]
  211. PenceH.E. WilliamsA. ChemSpider: An online chemical information resource.J. Chem. Educ.201087111123112410.1021/ed100697w
    [Google Scholar]
  212. KimS. ThiessenP.A. BoltonE.E. ChenJ. FuG. GindulyteA. HanL. HeJ. HeS. ShoemakerB.A. WangJ. YuB. ZhangJ. BryantS.H. PubChem substance and compound databases.Nucleic Acids Res.201644D1D1202D121310.1093/nar/gkv95126400175
    [Google Scholar]
  213. GaultonA. HerseyA. NowotkaM. BentoA.P. ChambersJ. MendezD. MutowoP. AtkinsonF. BellisL.J. UhalteC.E. DaviesM. DedmanN. KarlssonA. MagariñosM.P. OveringtonJ.P. PapadatosG. SmitI. LeachA.R. The ChEMBL database in 2017.Nucleic Acids Res.201745D1D945D95410.1093/nar/gkw107427899562
    [Google Scholar]
  214. WishartD.S. FeunangY.D. GuoA.C. LoE.J. MarcuA. GrantJ.R. SajedT. JohnsonD. LiC. SayeedaZ. AssempourN. IynkkaranI. LiuY. MaciejewskiA. GaleN. WilsonA. ChinL. CummingsR. LeD. PonA. KnoxC. WilsonM. DrugBank 5.0: A major update to the DrugBank database for 2018.Nucleic Acids Res.201846D1D1074D108210.1093/nar/gkx103729126136
    [Google Scholar]
  215. KahsaiA.W. XiaoK. RajagopalS. AhnS. ShuklaA.K. SunJ. OasT.G. LefkowitzR.J. Multiple ligand-specific conformations of the β2-adrenergic receptor.Nat. Chem. Biol.201171069270010.1038/nchembio.63421857662
    [Google Scholar]
  216. HodgsonJ. ADMET—turning chemicals into drugs.Nat. Biotechnol.200119872272610.1038/9076111479558
    [Google Scholar]
  217. PenzottiJ.E. LandrumG.A. PuttaS. Building predictive ADMET models for early decisions in drug discovery.Curr. Opin. Drug Discov. Devel.200471496114982148
    [Google Scholar]
  218. GilletV.J. WillettP. BradshawJ. Similarity searching using reduced graphs.J. Chem. Inf. Comput. Sci.200343233834510.1021/ci025592e12653495
    [Google Scholar]
  219. LipinskiC.A. LombardoF. DominyB.W. FeeneyP.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings.Adv. Drug Deliv. Rev.2012641-341710.1016/j.addr.2012.09.01911259830
    [Google Scholar]
  220. JarrahpourA. FathiJ. MimouniM. HaddaT.B. SheikhJ. ChohanZ. ParvezA. Petra, osiris and molinspiration (POM) together as a successful support in drug design: Antibacterial activity and biopharmaceutical characterization of some azo Schiff bases.Med. Chem. Res.20122181984199010.1007/s00044‑011‑9723‑0
    [Google Scholar]
  221. AthanasiadisE. CourniaZ. SpyrouG. ChemBioServer: A web-based pipeline for filtering, clustering and visualization of chemical compounds used in drug discovery.Bioinformatics201228223002300310.1093/bioinformatics/bts55122962344
    [Google Scholar]
  222. PiresD.E.V. BlundellT.L. AscherD.B. pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures.J. Med. Chem.20155894066407210.1021/acs.jmedchem.5b0010425860834
    [Google Scholar]
  223. DainaA. MichielinO. ZoeteV. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.Sci. Rep.2017714271710.1038/srep4271728256516
    [Google Scholar]
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