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Computer-aided study of selective flavonoids against chikungunya virus replication using molecular docking and DFT-based approach

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Abstract

Chikungunya fever has a high morbidity rate in humans and is caused by chikungunya virus (CHIKV). Currently, there is no vaccination or treatment available to show an effective efficacy against this disease. This study targets four non-structural proteins of CHIKV using 650 flavonoids from various medicinal plants, inhabited in Pakistan and India. The compounds are initially screened on the basis of their effective pharmacological properties and are docked against the four proteins. A threshold of − 8.5 kcal/mol is applied to screen and reduce the number of flavonoids for further analysis. The reactivity of screened flavonoids is analyzed using the density functional theory (DFT). Cirsimaritin, apigenin, tamarixetin, and 5,7,3′,4′-tetrahydroxyflavone from Andrographis paniculata have shown a high binding affinity against nsP1. Rhamnetin, tamarixetin and medioresinol have shown a strong binding affinity against nsP2. Four flavonoids, i.e. 5,7,3′,4′-tetrahydroxyflavone, 5,7,4′-trihydroxyflavone, tamarixetin and rhamnetin, showed a high binding affinity for nsP3 while apigenin depicted a strong binding affinity for nsP4. Pharmacological properties of these flavonoids illustrate an effective disposition in humans. The results manifest that the screened eight flavonoids can be analyzed against CHIKV for in vitro and in vivo cell replication, due to their effective pharmacological properties, strong inhibition and high reactivity.

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References

  1. Mallhi TH, Khan YH, Tanveer N, Bukhsh A, Khan AH, Aftab RA, Khan OH, Khan TM (2018) Awareness and knowledge of Chikungunya infection following its outbreak in Pakistan among health care students and professionals: a nationwide survey. PeerJ 6:e5481

    Article  PubMed  PubMed Central  Google Scholar 

  2. Keramagi AR, Skariyachan S (2018) Prediction of binding potential of natural leads against the prioritized drug targets of chikungunya and dengue viruses by computational screening. 3 Biotech 8(6):274

    Article  PubMed  PubMed Central  Google Scholar 

  3. Oliveira AF, Teixeira RR, Oliveira AS, Souza AP, Silva ML, Paula SO (2017) Potential antivirals: natural products targeting replication enzymes of dengue and chikungunya viruses. Molecules 22(3):505

    Article  PubMed Central  Google Scholar 

  4. Rashad AA, Mahalingam S, Keller PA (2013) Chikungunya virus: emerging targets and new opportunities for medicinal chemistry. J Med Chem 57(4):1147–1166

    Article  PubMed  Google Scholar 

  5. Powers AM (2018) Vaccine and therapeutic options to control chikungunya virus. Clin Microbiol Rev 31(1):e00104–e00116

    PubMed  Google Scholar 

  6. Al Mahdy A, Jamal M, Kinoshita H, Hossan T (2018) Chikungunya virus outbreak-a threat to global public health including Bangladesh. Bangladesh Journal of Medical Science 17(2):183–184

    Article  Google Scholar 

  7. Lokireddy S, Vemula S, Vadde R (2008) Connective tissue metabolism in chikungunya patients. Virol J 5(1):31

    Article  PubMed  PubMed Central  Google Scholar 

  8. Ji HF, Li XJ, Zhang HY (2009) Natural products and drug discovery. EMBO Rep 10(3):194–200

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Mishra K, Sharma N, Diwaker D, Ganju L, Singh S (2013) Plant derived antivirals: a potential source of drug development. J Virol Antivir Res 2:2–9

    Google Scholar 

  10. Delang L, Li C, Tas A, Quérat G, Albulescu I, De Burghgraeve T, Guerrero NS, Gigante A, Piorkowski G, Decroly E (2016) The viral capping enzyme nsP1: a novel target for the inhibition of chikungunya virus infection. Sci Rep 6:31819

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Brunetti C, Di Ferdinando M, Fini A, Pollastri S, Tattini M (2013) Flavonoids as antioxidants and developmental regulators: relative significance in plants and humans. Int J Mol Sci 14(2):3540–3555

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hendra R, Ahmad S, Sukari A, Shukor MY, Oskoueian E (2011) Flavonoid analyses and antimicrobial activity of various parts of Phaleria macrocarpa (Scheff.) Boerl fruit. Int J Mol Sci 12(6):3422–3431

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Orhan DD, Özçelik B, Özgen S, Ergun F (2010) Antibacterial, antifungal, and antiviral activities of some flavonoids. Microbiol Res 165(6):496–504

    Article  CAS  PubMed  Google Scholar 

  14. Rathee P, Chaudhary H, Rathee S, Rathee D, Kumar V, Kohli K (2009) Mechanism of action of flavonoids as anti-inflammatory agents: a review. Inflamm Allergy Drug Targets 8(3):229–235

    Article  CAS  PubMed  Google Scholar 

  15. Seyedi SS, Shukri M, Hassandarvish P, Oo A, Shankar EM, Abubakar S, Zandi K (2016) Computational approach towards exploring potential anti-chikungunya activity of selected flavonoids. Sci Rep 6:24027

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Qaddir I, Rasool N, Hussain W, Mahmood S (2017) Computer-aided analysis of phytochemicals as potential dengue virus inhibitors based on molecular docking, ADMET and DFT studies. J Vector Borne Dis 54(3):255

    Article  CAS  PubMed  Google Scholar 

  17. Rasool N, Iftikhar S, Amir A, Hussain W (2018) Structural and quantum mechanical computations to elucidate the altered binding mechanism of metal and drug with pyrazinamidase from Mycobacterium tuberculosis due to mutagenicity. J Mol Graph Model 80:126–131

    Article  CAS  PubMed  Google Scholar 

  18. Amjad H, Hussain W, Rasool N (2018) Molecular simulation investigation of prolyl oligopeptidase from Pyrobaculum calidifontis and in silico docking with substrates and inhibitors. Open Access J Biomed Eng Biosci 2(4):185–194

  19. Hussain W, Ali M, Sohail Afzal M, Rasool N (2018) Penta-1,4-diene-3-one oxime derivatives strongly inhibit the replicase domain of tobacco mosaic virus: elucidation through molecular docking and density functional theory mechanistic computations. J Antivir Antiretrovir 10(3). https://doi.org/10.4172/1948-5964.1000177

  20. Hussain W, Qaddir I, Mahmood S, Rasool N (2018) In silico targeting of non-structural 4B protein from dengue virus 4 with spiropyrazolopyridone: study of molecular dynamics simulation, ADMET and virtual screening. Virusdisease 29:1–10

    Article  Google Scholar 

  21. Rasool N, Jalal A, Amjad A, Hussain W (2018) Probing the pharmacological parameters, molecular docking and quantum computations of plant derived compounds exhibiting strong inhibitory potential against NS5 from Zika virus. Braz Arch Biol Technol 61. https://doi.org/10.1590/1678-4324-2018180004

  22. Rasool N, Hussain W (2019) Three major phosphoacceptor sites in HIV-1 capsid protein enhances its structural stability and resistance against inhibitor: explication through molecular dynamics simulation, Molecular Docking and DFT Analysis. Comb Chem High Throughput Screen. https://doi.org/10.2174/1386207323666191213142223

  23. Mumtaz A, Ashfaq UA, ul Qamar MT, Anwar F, Gulzar F, Ali MA, Saari N, Pervez MT (2017) MPD3: a useful medicinal plants database for drug designing. Nat Prod Res 31(11):1228–1236

    Article  CAS  PubMed  Google Scholar 

  24. Akhtar A, Amir A, Hussain W, Ghaffar A, Rasool N (2019) In silico computations of selective phytochemicals as potential inhibitors against major biological targets of diabetes mellitus. Curr Comput Aided Drug Des. https://doi.org/10.2174/1573409915666190130164923

  25. Akhtar A, Hussain W, Rasool N (2019) Probing the pharmacological binding properties, and reactivity of selective phytochemicals as potential HIV-1 protease inhibitors. Univ Sci 24(3):441–464

    Article  Google Scholar 

  26. Arif N, Subhani A, Hussain W, Rasool N (2019) In silico inhibition of BACE-1 by selective phytochemicals as novel potential inhibitors: molecular docking and DFT studies. Curr Drug Discov Technol. https://doi.org/10.2174/1570163816666190214161825

  27. Rasool N, Ashraf A, Waseem M, Hussain W, Mahmood S (2019) Computational exploration of antiviral activity of phytochemicals against NS2B/NS3 proteases from dengue virus. Turk J Biochem 44(3): 1–17

  28. Rasool N, Husssain W, Khan YD (2019) Revelation of enzyme activity of mutant pyrazinamidases from Mycobacterium tuberculosis upon binding with various metals using quantum mechanical approach. Comput Biol Chem 83:107108

    Article  CAS  PubMed  Google Scholar 

  29. Zhang Y (2008) I-TASSER server for protein 3D structure prediction. BMC Bioinformatics 9(1):40

    Article  PubMed  PubMed Central  Google Scholar 

  30. Huang B (2009) MetaPocket: a meta approach to improve protein ligand binding site prediction. OMICS 13(4):325–330

    Article  CAS  PubMed  Google Scholar 

  31. Daina A, Michielin O, Zoete V (2017) SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 7:42717

    Article  PubMed  PubMed Central  Google Scholar 

  32. Lee SK, Lee IH , Kim HJ, Chang GS, Chung JE, No KT (2003) "The PreADME Approach: Web-based program for rapid prediction of physico-chemical, drug absorption and drug-like properties." EuroQSAR designing drugs and crop protectants: processes, problems and solutions 418–20

  33. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30(16):2785–2791

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Ai C, Li Y, Wang Y, Li W, Dong P, Ge G, Yang L (2010) Investigation of binding features: effects on the interaction between CYP2A6 and inhibitors. J Comput Chem 31(9):1822–1831

    CAS  PubMed  Google Scholar 

  35. Spessard GO (1998) ACD Labs/LogP dB 3.5 and ChemSketch 3.5. J Chem Inf Comput Sci 38(6):1250–1253

    Article  CAS  Google Scholar 

  36. Ghersi D, Sanchez R (2009) Improving accuracy and efficiency of blind protein-ligand docking by focusing on predicted binding sites. Proteins 74(2):417–424

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Neese F (2012) The ORCA program system. Wiley Interdiscip Rev Comput Mol Sci 2(1):73–78

  38. Gill PM, Johnson BG, Pople JA, Frisch MJ (1992) The performance of the Becke—Lee—Yang—Parr (B—LYP) density functional theory with various basis sets. Chem Phys Lett 197(4–5):499–505

    Article  CAS  Google Scholar 

  39. Lovell SC, Davis IW, Arendall III WB, De Bakker PI, Word JM, Prisant MG, Richardson JS, Richardson DC (2003) Structure validation by Cα geometry: ϕ, ψ and Cβ deviation. Proteins: Structure, Function, and Bioinformatics 50(3):437–450

    Article  CAS  Google Scholar 

  40. Nguyen PT, Yu H, Keller PA (2015) Identification of chikungunya virus nsP2 protease inhibitors using structure-base approaches. J Mol Graph Model 57:1–8

    Article  CAS  PubMed  Google Scholar 

  41. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 23(1–3):3–25

    Article  CAS  Google Scholar 

  42. Tran N (2011) Blood-brain barrier. Encycl Clin Neuropsychol:426–426

  43. Ritter J (2008) Wiley handbook of current and emerging drug therapies. Br J Clin Pharmacol 65(3):449

    Article  Google Scholar 

  44. Szymański P, Markowicz M, Mikiciuk-Olasik E (2012) Adaptation of high-throughput screening in drug discovery—toxicological screening tests. Int J Mol Sci 13(1):427–452

    Article  PubMed  Google Scholar 

  45. Parashar D, Cherian S (2014) Antiviral perspectives for chikungunya virus. Biomed Res Int 2014:631642

    Article  PubMed  PubMed Central  Google Scholar 

  46. Oo A, Hassandarvish P, Chin SP, Lee VS, Bakar SA, Zandi K (2016) In silico study on anti-Chikungunya virus activity of hesperetin. PeerJ 4:e2602

    Article  PubMed  PubMed Central  Google Scholar 

  47. Ahmadi A, Hassandarvish P, Lani R, Yadollahi P, Jokar A, Bakar SA, Zandi K (2016) Inhibition of chikungunya virus replication by hesperetin and naringenin. RSC Adv 6(73):69421–69430

    Article  CAS  Google Scholar 

  48. Mishra P, Kumar A, Mamidi P, Kumar S, Basantray I, Saswat T, Das I, Nayak TK, Chattopadhyay S, Subudhi BB (2016) Inhibition of chikungunya virus replication by 1-[(2-methylbenzimidazol-1-yl) methyl]-2-oxo-indolin-3-ylidene] amino] thiourea (MBZM-N-IBT). Sci Rep 6:20122

  49. Eroglu E, Türkmen H (2007) A DFT-based quantum theoretic QSAR study of aromatic and heterocyclic sulfonamides as carbonic anhydrase inhibitors against isozyme, CA-II. J Mol Graph Model 26(4):701–708

    Article  CAS  PubMed  Google Scholar 

  50. Gogoi D, Baruah VJ, Chaliha AK, Kakoti BB, Sarma D, Buragohain AK (2017) Identification of novel human renin inhibitors through a combined approach of pharmacophore modelling, molecular DFT analysis and in silico screening. Comput Biol Chem 69:28–40

    Article  CAS  PubMed  Google Scholar 

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Hussain, W., Amir, A. & Rasool, N. Computer-aided study of selective flavonoids against chikungunya virus replication using molecular docking and DFT-based approach. Struct Chem 31, 1363–1374 (2020). https://doi.org/10.1007/s11224-020-01507-x

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