TY  - JOUR
A1  - Singh, Krishna P.
A1  - Verma, Neeraj
A1  - Akhoon, Bashir A .
A1  - Bhatt, Vishal
A1  - Gupta, Shishir K.
A1  - Gupta, Shailendra K.
A1  - Smita, Suchi
T1  - Sequence-based approach for rapid identification of cross-clade CD8+ T-cell vaccine candidates from all high-risk HPV strains
JF  - 3 Biotech
N2  - Human papilloma virus (HPV) is the primary etiological agent responsible for cervical cancer in women. Although in total 16 high-risk HPV strains have been identified so far. Currently available commercial vaccines are designed by targeting mainly HPV16 and HPV18 viral strains as these are the most common strains associated with cervical cancer. Because of the high level of antigenic specificity of HPV capsid antigens, the currently available vaccines are not suitable to provide cross-protection from all other high-risk HPV strains. Due to increasing reports of cervical cancer cases from other HPV high-risk strains other than HPV16 and 18, it is crucial to design vaccine that generate reasonable CD8+ T-cell responses for possibly all the high-risk strains. With this aim, we have developed a computational workflow to identify conserved cross-clade CD8+ T-cell HPV vaccine candidates by considering E1, E2, E6 and E7 proteins from all the high-risk HPV strains. We have identified a set of 14 immunogenic conserved peptide fragments that are supposed to provide protection against infection from any of the high-risk HPV strains across globe.
KW  - HPV
KW  - Epitope
KW  - Cytotoxic
KW  - T lymphocytes
KW  - Cervical cancer
KW  - Vaccine
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-191056
VL  - 6
ER  - 
TY  - JOUR
A1  - Kaltdorf, Martin
A1  - Srivastava, Mugdha
A1  - Gupta, Shishir K.
A1  - Liang, Chunguang
A1  - Binder, Jasmin
A1  - Dietl, Anna-Maria
A1  - Meir, Zohar
A1  - Haas, Hubertus
A1  - Osherov, Nir
A1  - Krappmann, Sven
A1  - Dandekar, Thomas
T1  - Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach
JF  - Frontiers in Molecular Bioscience
N2  - New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness (“hubs”), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.
KW  - metabolism
KW  - targets
KW  - antimycotics
KW  - modeling
KW  - structure
KW  - interaction
KW  - fungicide
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147396
VL  - 3
ER  -