Lal Bahadur Nagar, India


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Kumar A.,Mangalayatan University | Mohan A.,Bipin Tripathi Institute of Technology | Sharma D.K.,Mangalayatan University | Srivastava S.,BIOBRAINZ | And 2 more authors.
Trends in Bioinformatics | Year: 2012

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(HlNl) 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-avail able 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. © 2012 Asian Network for Scientific Information.

Sharma D.K.,Mangalayatan University | Rawat A.K.,BIOBRAINZ | Srivastava S.,BIOBRAINZ | Srivastava R.,BIOBRAINZ | Kumar A.,Mangalayatan University
Journal of Proteomics and Bioinformatics | Year: 2010

The swine flu is an infectious disease of swine and human, causing a huge amount of death to both. The aim of this study was to analyse the mutation possibility of swine influenza virus sub-type A/Swine/Nebraska/(H1N1) from swine of Nebraska. The H1N1 amino acid sequences of neuraminidase (GenBank Acc. No: ABR28650) and hemagglutinin (GenBank Acc. No: ABR28647) were analyzed for mutations using BLASTP and ClustalW programs. Our in silico analysis predicted that hemagglutinin and neuraminidase of swine influenza virus are sensitive to mutations at positions 225, 283 and 240, 451 respectively. These mutations were significant for its pathogenic nature because they are involved in change in polarity or hydrophobicity. Domain and motif search shows that mutations were detected in NA (T240A, G451S) and HA (I283V) at a predicted site of N-myristoylation. Secondary structure analysis predicted that no structural conformation changes were observed in HA and NA at positions 225, 283 and 240, 451 respectively. The program PROTMUTATION was developed in Perl CGI programming using Needleman-Wunsch algorithm for global sequence alignment. This program was used to monitor the mutations and predicts the trend of mutations. © 2010 Sharma DK, et al.

Shukla P.,BIOBRAINZ | Srvastava S.,BIOBRAINZ | Srvastava R.,BIOBRAINZ | Rawat A.K.,BIOBRAINZ
African Journal of Microbiology Research | Year: 2011

A bacterial strain Bz19 was isolated from a water sample collected from river Gomati at the Indian city of Lucknow. We characterized the strain using 16S rRNA gene sequence. Phylogenetic analysis showed that the strain formed a monophyletic clade with members of the genus Staphylococcus. The closest phylogenetic relative was Staphylococcus arlettae with 99% 16S rRNA gene sequence similarity. It is proposed that the identified strain Bz19 be assigned as the type strain of a species of the genus Staphylococcus (Staphylococcus sp. Bz19) based on phylogenetic tree analysis together with the 16S rRNA gene sequence search in Ribosomal Database Project, small subunit rRNA and large subunit rRNA databases. The sequence was deposited in GenBank with the accession number HM488958. ©2011 Academic Journals.

Type: Journal Article | Journal: Bioinformation | Year: 2011

Farnesyl transferase (FTase) is an enzyme responsible for post-translational modification in proteins having a carboxy-terminal CaaX motif in human. It catalyzes the attachment of a lipid group in proteins of RAS superfamily, which is essential in signal transduction. FTase has been recognized as an important target for anti cancer therapeutics. In this work, we performed virtual screening against FTase with entire 125 compounds from Indian Plant Anticancer Database using AutoDock 3.0.5 software. All compounds were docked within binding pocket containing Lys164, Tyr300, His248 and Tyr361 residues in crystal structure of FTase. These complexes were ranked according to their docking score, using methodology that was shown to achieve maximum accuracy. Finally we got three potent compounds with the best Autodock docking Score (Vinorelbine: -21.28 Kcal/mol, Vincristine: -21.74 Kcal/mol and Vinblastine: -22.14 Kcal/mol) and their energy scores were better than the FTase bound co-crystallized ligand (L- 739: -7.9 kcal/mol). These three compounds belong to Vinca alkaloids were analyzed through Python Molecular Viewer for their interaction studies. It predicted similar orientation and binding modes for these compounds with L-739 in FTase.Thus from the complex scoring and binding ability it is concluded that these Vinca alkaloids could be promising inhibitors for FTase. A 2-D pharmacophore was generated for these alkaloids using LigandScout to confirm it. A shared feature pharmacophore was also constructed that shows four common features (one hydogen bond Donar, Two hydrogen bond Acceptor and one ionizable area) help compounds to interact with this enzyme.

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