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Kosmos
Astronomia Astrofizyka
Inne

Kultura
Sztuka dawna i współczesna, muzea i kolekcje

Metoda
Metodologia nauk, Matematyka, Filozofia, Miary i wagi, Pomiary

Materia
Substancje, reakcje, energia
Fizyka, chemia i inżynieria materiałowa

Człowiek
Antropologia kulturowa Socjologia Psychologia Zdrowie i medycyna

Wizje
Przewidywania Kosmologia Religie Ideologia Polityka

Ziemia
Geologia, geofizyka, geochemia, środowisko przyrodnicze

Życie
Biologia, biologia molekularna i genetyka

Cyberprzestrzeń
Technologia cyberprzestrzeni, cyberkultura, media i komunikacja

Działalność
Wiadomości | Gospodarka, biznes, zarządzanie, ekonomia

Technologie
Budownictwo, energetyka, transport, wytwarzanie, technologie informacyjne

Drug Design for Influenza a Pandemic (H1N1) 2009 Virus Isolates from India

The membranes of influenza A virus subtype H1N1 contain two functional surface glycoprotein’s hemagglutinin (HA) and neuraminidase (NA) to initiate and spreading of infection to target cells. By inhibiting HA and NA proteins could prevent virus infection to host cells. In order to inhibit HA and NA proteins, the amino acid sequence of HA (Accession No: ACZ97508) and NA(Accession No: ACZ97471) of influenza A virus subtype H1N1 of A/Pune/NIV6196/2009(H1N1) were retrieved from influenza virus resource database. The 3D model of HA and NA proteins were built using comparative homology modeling program Modeller9v7. The computed models of HA and NA were optimized by using molecular dynamics approach through same program Modeller and eventually validated using PROCHECK program. The model of HA and NA were submitted in protein model database (PMID-ID: PM0076654 for HA and PM0076653 for NA). Homology models of hemagglutinin and neuraminidase were used for virtual screening against 131 drug like compounds using AutoDock3.0.5. These 131 compounds were screened from ZINC (a database of commercially-available compounds) on the basis of structure base similarity search of known drugs Oseltamivir and Zanamivir. The docked complexes were validated and enumerated based on docked energy. Six potent inhibitors were found and suggested as potent dual target candidate drugs with lowest docked energy. These inhibitors were designed with computational tools having greater binding affinity with HA and NA proteins than known drugs Oseltamivir and Zanamivir. The results may help to solve the drug-resistant problem and stimulate designing more effective drugs against 2009-H1N1 influenza pandemic, yet pharmacological studies have to confirm it.

Trends in Bioinformatics 2012/05/21 - 20:31 Czytaj