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Pregled bibliografske jedinice broj: 1175028

Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking


Kandagalla, Shivananda; Novak, Jurica; Shekarappa, Sharath Belenahalli; Grishina, Maria A; Potemkin, Vladimir A; Kumbar, Bhimanagoud
Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking // Journal of biomolecular structure & dynamics, 40 (2022), 24; 13547-13563 doi:10.1080/07391102.2021.1990131 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1175028 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking

Autori
Kandagalla, Shivananda ; Novak, Jurica ; Shekarappa, Sharath Belenahalli ; Grishina, Maria A ; Potemkin, Vladimir A ; Kumbar, Bhimanagoud

Izvornik
Journal of biomolecular structure & dynamics (0739-1102) 40 (2022), 24; 13547-13563

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Kyasanur forest disease ; NS3 ; molecular dynamics ; aspertryptanthrin C ; grazoprevir

Sažetak
Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to Flavivirus (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, in silico drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to de novo developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using in silico molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, in silico molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV.

Izvorni jezik
Hrvatski

Znanstvena područja
Kemija, Biotehnologija u biomedicini (prirodno područje, biomedicina i zdravstvo, biotehničko područje)



POVEZANOST RADA


Profili:

Avatar Url Jurica Novak (autor)

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Kandagalla, Shivananda; Novak, Jurica; Shekarappa, Sharath Belenahalli; Grishina, Maria A; Potemkin, Vladimir A; Kumbar, Bhimanagoud
Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking // Journal of biomolecular structure & dynamics, 40 (2022), 24; 13547-13563 doi:10.1080/07391102.2021.1990131 (međunarodna recenzija, članak, znanstveni)
Kandagalla, S., Novak, J., Shekarappa, S., Grishina, M., Potemkin, V. & Kumbar, B. (2022) Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking. Journal of biomolecular structure & dynamics, 40 (24), 13547-13563 doi:10.1080/07391102.2021.1990131.
@article{article, author = {Kandagalla, Shivananda and Novak, Jurica and Shekarappa, Sharath Belenahalli and Grishina, Maria A and Potemkin, Vladimir A and Kumbar, Bhimanagoud}, year = {2022}, pages = {13547-13563}, DOI = {10.1080/07391102.2021.1990131}, keywords = {Kyasanur forest disease, NS3, molecular dynamics, aspertryptanthrin C, grazoprevir}, journal = {Journal of biomolecular structure and dynamics}, doi = {10.1080/07391102.2021.1990131}, volume = {40}, number = {24}, issn = {0739-1102}, title = {Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking}, keyword = {Kyasanur forest disease, NS3, molecular dynamics, aspertryptanthrin C, grazoprevir} }
@article{article, author = {Kandagalla, Shivananda and Novak, Jurica and Shekarappa, Sharath Belenahalli and Grishina, Maria A and Potemkin, Vladimir A and Kumbar, Bhimanagoud}, year = {2022}, pages = {13547-13563}, DOI = {10.1080/07391102.2021.1990131}, keywords = {Kyasanur forest disease, NS3, molecular dynamics, aspertryptanthrin C, grazoprevir}, journal = {Journal of biomolecular structure and dynamics}, doi = {10.1080/07391102.2021.1990131}, volume = {40}, number = {24}, issn = {0739-1102}, title = {Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking}, keyword = {Kyasanur forest disease, NS3, molecular dynamics, aspertryptanthrin C, grazoprevir} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Citati:





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