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Efficient detection of nitric oxide a biomarker associated with COVID19 via N, P co-doped C60 fullerene: a computational study

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Abstract

Context

Coronavirus (COVID-19) is a novel respiratory viral infection, causing a relatively large number of deaths especially in people who underly lung diseases such as chronic obstructive pulmonary and asthma, and humans are still suffering from the limited testing capacity. In this article, a solution is proposed for the detection of COVID-19 viral infections through the analysis of exhaled breath gasses, i.e., nitric oxide, a prominent biomarker released by respiratory epithelial, as a non-invasive and time-saving approach. Here, we designed a novel and low-cost N and P co-doped C60 fullerene-based breathalyzer for the detection of NO gas exhaled from the respiratory epithelial cells. This breathalyzer shows a quick response to the detection of NO gas by directly converting NO to NO2 without passing any energy barrier (0 kcal/mol activation energy). The recovery time of breathalyzer is very short (0.98 × 103 s), whereas it is highly selective for NO sensing in the mixture of CO2 and H2O gasses. The study provides an idea for the synthesis of low-cost (compared to previously reported Au atom decorated nanostructure and metal-based breathalyzer), efficient, and highly selective N and P co-doped C60 fullerene-based breathalyzer for COVID-19 detection.

Methods

The geometries of N and P-doped systems and gas molecules are simulated using spin-polarized density functional theory calculations.

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Data availability

All relevant data generated or analyzed during the work are included in this paper and any additional data can be made available upon reasonable request.

References

  1. Zhonghua Liu Xing Bing Xue Za Zhi (2020) The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. 41. https://doi.org/10.3760/cma.j.issn.0254-6450.2020.02.003

  2. Ge C, Li M, Li M, Peyghan AA (2020) Au-decorated BN nanotube as a breathalyzer for potential medical applications. J Mol Liq 312:113454. https://doi.org/10.1016/j.molliq.2020.113454

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Li F (2013) Receptor recognition and cross-species infections of SARS coronavirus. Antiviral Res 100(1):246–254. https://doi.org/10.1016/j.antiviral.2013.08.014

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Li W, Wong SK, Li F, Kuhn JH, Huang IC, Choe H, Farzan M (2006) Animal origins of the severe acute respiratory syndrome coronavirus: insight from ACE2-S-protein interactions. J Virol 80(9):4211–4219. https://doi.org/10.1128/jvi.80.9.4211-4219.2006

  5. Nagy PD, Simon AE (1997) New insights into the mechanisms of RNA recombination. Virology 235(1):1–9. https://doi.org/10.1006/viro.1997.8681

  6. Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C et al (2020) Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med 8(4):420–422. https://doi.org/10.1016/S2213-2600(20)30076-X

  7. https://www.worldometers.info/coronavirus/#google_vignette

  8. Cinatl J, Morgenstern B, Bauer G, Chandra P, Rabenau H, Doerr HW (2003) Treatment of SARS with human interferons. Lancet 362(9380):293–294. https://doi.org/10.1016/S0140-6736(03)13973-6

  9. Chan JF, Chan KH, Kao RY, To KK, Zheng BJ, Li CP et al (2013) Broad-spectrum antivirals for the emerging Middle East respiratory syndrome coronavirus. J Infect 67(6):606–616. https://doi.org/10.1016/j.jinf.2013.09.029

  10. Cheng KW, Cheng SC, Chen WY, Lin MH, Chuang SJ, Cheng IH et al (2015) Thiopurine analogs and mycophenolic acid synergistically inhibit the papain-like protease of Middle East respiratory syndrome coronavirus. Antivir Res 115:9–16. https://doi.org/10.1016/j.antiviral.2014.12.011

  11. Wang Y, Sun Y, Wu A, Xu S, Pan R, Zeng C et al (2015) Coronavirus nsp10/nsp16 methyltransferase can be targeted by nsp10-derived peptide in vitro and in vivo to reduce replication and pathogenesis. J Virol 89(16):8416–8427. https://doi.org/10.1128/jvi.00948-15

  12. Mair-Jenkins J, Saavedra-Campos M, Baillie JK, Cleary P, Khaw FM, Lim WS et al (2015) The effectiveness of convalescent plasma and hyperimmune immunoglobulin for the treatment of severe acute respiratory infections of viral etiology: a systematic review and exploratory meta-analysis. J Infect Dis 211(1):80–90. https://doi.org/10.1093/infdis/jiu396

  13. Gouma PI, Wang L, Simon SR, Stanacevic M (2017) Novel isoprene sensor for a flu virus breath monitor. Sensors 17(1):199. https://doi.org/10.3390/s17010199

  14. Mashir A, Paschke KM, Van Duin D, Shrestha NK, Laskowski D, Storer MK et al (2011) Effect of the influenza a (H1N1) live attenuated intranasal vaccine on nitric oxide (FENO) and other volatiles in exhaled breath. J Breath Res 5(3):037107. https://doi.org/10.1088/1752-7155/5/3/037107

  15. Phillips M, Cataneo RN, Chaturvedi A, Danaher PJ, Devadiga A, Legendre DA et al (2010) Effect of influenza vaccination on oxidative stress products in breath. J Breath Res 4(2):026001. https://doi.org/10.1088/1752-7155/4/2/026001

  16. Kamel KMM, Morsali A, Raissi H (2020) Theoretical insights into the intermolecular and mechanisms of covalent interaction of flutamide drug with COOH and COCl functionalized carbon nanotubes: a DFT approach. Chem Rev Lett 3:23–37

    CAS  Google Scholar 

  17. Dos Santos RB, Rivelino R, de Brito Mota F, Gueorguiev GK, Kakanakova-Georgieva A (2015) Dopant species with Al–Si and N–Si bonding in the MOCVD of AlN implementing trimethylaluminum, ammonia and silane. J Phys D Appl Phys 48(29):295104. https://doi.org/10.1088/0022-3727/48/29/295104

  18. Rostamoghli KJR, Vakili M, Banaei A, Pourbashir E (2018) Applying the B12N12 nanoparticle as the CO, CO2, H2O and NH3 sensor. Chem Rev Lett 1:31–36

    Google Scholar 

  19. Beheshtian J, Peyghan AA, Tabar MB, Bagheri Z (2013) DFT study on the functionalization of a BN nanotube with sulfamide. Appl Surf Sci 266:182–187. https://doi.org/10.1016/j.apsusc.2012.11.128

  20. GhafurRauf MSH, Majedi S, E. Abdul kareemMahmood, (2019) Adsorption behavior of the Al- and Ga-doped B12N12 nanocages on COn (n = 1, 2) and HnX (n = 2, 3 and X = O, N): a comparative study. Chem Rev Lett 2:140–150

    Google Scholar 

  21. Freitas RRQ, Gueorguiev GK, de Brito Mota F, De Castilho CMC, Stafström S, Kakanakova-Georgieva A (2013) Reactivity of adducts relevant to the deposition of hexagonal BN from first-principles calculations. Chem Phys Lett 583:119–124. https://doi.org/10.1016/j.cplett.2013.07.077

  22. Babanezhad ABE (2018) The possibility of selective sensing of the straight-chain alcohols (including methanol to n-pentanol) by using the C20 fullerene and C18NB nano cage. Chem Rev Lett 1:82–88

    Google Scholar 

  23. Li F, Asadi H (2020) DFT study of the effect of platinum on the H2 gas sensing performance of ZnO nanotube: explaining the experimental observations. J Mol Liq 309:113139. https://doi.org/10.1016/j.molliq.2020.113139

  24. Siadati SRSA (2018) Switching behavior of an actuator containing germanium, silicon-decorated and normal C20 fullerene. Chem Rev Lett 1:77–81

    Google Scholar 

  25. Gouma P, Prasad A, Stanacevic S (2011) A selective nanosensor device for exhaled breath analysis. J Breath Res 5(3):037110. https://doi.org/10.1088/1752-7155/5/3/037110

  26. Gouma PI, Prasad AK, Iyer KK (2006) Selective nanoprobes for ‘signalling gases’. Nanotechnology 17(4):S48. https://doi.org/10.1088/0957-4484/17/4/008

  27. Huang J, Wan Q (2009) Gas sensors based on semiconducting metal oxide one-dimensional nanostructures. Sensors 9(12):9903–9924. https://doi.org/10.3390/s91209903

  28. He YLY, Chen H-Y, Hou J (2010) Indene−C60 bisadduct: a new acceptor for high-performance polymer solar cells. J Am Chem Soc 132:1377–1382

    Article  CAS  PubMed  Google Scholar 

  29. Yuan YY, Han S, Grozea D, Lu AZ (2006) Fullerene-organic nanocomposite: a flexible material platform for organic light-emitting diodes. Appl Phys Lett 88(9). https://doi.org/10.1063/1.2180876

  30. Sutradhar S, Patnaik A (2017) A new fullerene-C60–Nanogold composite for non-enzymatic glucose sensing. Sensors Actuators B Chem 241:681–689. https://doi.org/10.1016/j.snb.2016.10.111

  31. Esrafili MD, Mohammadirad N (2017) A first-principles study on the adsorption behaviour of methanol and ethanol over C59B heterofullerene. Mol Phys 115(14):1633–1641. https://doi.org/10.1080/00268976.2017.1311423

  32. Moradi M, Nouraliei M, Moradi R (2017) Theoretical study on the phenylpropanolamine drug interaction with the pristine, Si and Al doped [60] fullerenes. Physica E: Low-Dimens Syst Nanostructures 87:186–191. https://doi.org/10.1016/j.physe.2016.11.027

  33. Ganji MD, Yazdani H (2010) Interaction between B-doped C60 fullerene and glycine amino acid from first-principles simulation. Chin Phys Lett 27(4):043102. https://doi.org/10.1088/0256-307X/27/4/043102

  34. Khan AA, Ahmad I, Ahmad R (2020) Influence of electric field on CO2 removal by P-doped C60-fullerene: a DFT study. Chem Phys Lett 742:137155. https://doi.org/10.1016/j.cplett.2020.137155

    Article  CAS  Google Scholar 

  35. Vinit, Ramachandran CN (2017) Structure, stability, and properties of boron encapsulated complexes of C60, C59B, and C59N. J Phys Chem A 121(8):1708–1714. https://doi.org/10.1021/acs.jpca.6b10649

  36. Liang Z, Liu C, Chen M, Qi X, Kumar P, Peera SG et al (2019) Oxygen reduction reaction mechanism on P, N co-doped graphene: a density functional theory study. New J Chem 43(48):19308–19317. https://doi.org/10.1039/c9nj04808a

  37. Han C, Chen Z (2020) The mechanism study of oxygen reduction reaction (ORR) on non-equivalent P, N co-doped graphene. Appl Surf Sci 511:145382. https://doi.org/10.1016/j.apsusc.2020.145382

  38. Delley B (1990) An all-electron numerical method for solving the local density functional for polyatomic molecules. J Chem Phys 92:508–517. https://doi.org/10.1063/1.458452

    Article  CAS  Google Scholar 

  39. Delley B (2000) From molecules to solids with the DMol3 approach. J Chem Phys 113:7756–7764. https://doi.org/10.1063/1.1316015

    Article  CAS  Google Scholar 

  40. Perdew JP, Burke K, Ernzerhof M (1996) Generalized gradient approximation made simple. Phys Rev Lett 77:3865–3868. https://doi.org/10.1103/PhysRevLett.77.3865

    Article  CAS  PubMed  Google Scholar 

  41. Grimme S (2004) Accurate description of van der Waals complexes by density functional theory including empirical corrections. J Comput Chem 25:1463–1473. https://doi.org/10.1002/jcc.20078

    Article  CAS  PubMed  Google Scholar 

  42. Grimme S (2006) Semiempirical GGA-type density functional constructed with a long-range dispersion correction. J Comput Chem 27:1787–1799. https://doi.org/10.1002/jcc.20495

    Article  CAS  PubMed  Google Scholar 

  43. Liu P, Rodriguez JA (2005) Catalysts for hydrogen evolution from the [NiFe] hydrogenase to the Ni 2P(001) surface: the importance of ensemble effect. J Am Chem Soc 127:14871–14878. https://doi.org/10.1021/ja0540019

    Article  CAS  PubMed  Google Scholar 

  44. Yong Y, Cui H, Zhou Q, Su X, Kuang Y, Li X (2019) C2N monolayer as NH3 and NO sensors: a DFT study. Appl Surf Sci 487:488–495. https://doi.org/10.1016/j.apsusc.2019.05.040

  45. Khan AA, Ahmad R, Ahmad I (2020) Density functional theory study of emerging pollutants removal from water by covalent triazine based framework. J Mol Liq 309:113008. https://doi.org/10.1016/j.molliq.2020.113008

    Article  CAS  Google Scholar 

  46. Ma S, Su L, Jin L, Su J, Jin Y (2019) A first-principles insight into Pd-doped MoSe2 monolayer: a toxic gas scavenger. Phys Lett A 383(30):125868. https://doi.org/10.1016/j.physleta.2019.125868

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Acknowledgements

The authors would like to thank “Center for Computational Materials Science of University of Malakand” for its technical support of this work.

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Authors and Affiliations

  1. Center for Computational Materials Science, University of Malakand, Chakdara, Pakistan

    Adnan Ali Khan, Rashid Ahmad & Iftikhar Ahmad

  2. Department of Chemistry, University of Malakand, Chakdara, Pakistan

    Adnan Ali Khan & Rashid Ahmad

  3. Institiute for Advanced Study, Shenzhen University, Shenzhen, 558060, China

    Fazal Mehmood

  4. Department of Physics, University of Malakand, Chakdara, Pakistan

    Iftikhar Ahmad

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  1. Adnan Ali Khan
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Contributions

Adnan Ali Khan: conceptualization, methodology, software, writing—original draft, writing—review and editing. Fazal Mehmood: formal analysis, validation, writing—original draft. Rashid Ahmad: supervision, conceptualization, software, writing—review and editing. Iftikhar Ahmad: conceptualization, software, project administration.

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Correspondence to Adnan Ali Khan or Rashid Ahmad.

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Khan, A.A., Ahmad, R., Mehmood, F. et al. Efficient detection of nitric oxide a biomarker associated with COVID19 via N, P co-doped C60 fullerene: a computational study. J Mol Model 30, 166 (2024). https://doi.org/10.1007/s00894-024-05954-9

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