Protein domain fusion analysis in sexually transmitted human pathogenic bacteria

Postgraduate Thesis uoadl:1315736 215 Read counter

Unit:
ΠΜΣ Μικροβιακή Βιοτεχνολογία
Library of the School of Science
Deposit date:
2015-04-02
Year:
2015
Author:
Βλαχοπάνου Δήμητρα
Supervisors info:
Αμαλία Δ. Καραγκούνη-Κύρτσου Καθηγήτρια
Original Title:
Ανάλυση γεγονότων συγχώνευσης πρωτεϊνών σε παθογόνα βακτήρια υπεύθυνα για σεξουαλικώς μεταδιδόμενα νοσήματα στον άνθρωπο
Languages:
Greek
Translated title:
Protein domain fusion analysis in sexually transmitted human pathogenic bacteria
Summary:
Proteins accomplish basic functions at almost every biological process and
protein-protein interactions are operative at every level of cell function.
Because of their importance in biological functions, proteins have been the
object of intense research for many years. Functions of uncharacterized
proteins may be predicted through comparison with the interactions of similar
known proteins. Computational methods have traditionally assigned function by
sequence similarity to a characterized protein. However, new methods have been
developed which they group proteins that are part of the same pathway or
assembly and define them as being ‘functionally linked’. One such method is the
protein domain fusion analysis. It is based on the fact that if two separate
proteins from one organism are fused in a protein from another organism, then
they are likely to interact and have relevant functions. The main purpose of
this thesis is the detection of protein domain fusion events between ten
pathogenic bacteria which cause sexually transmitted diseases and a fungus.
Infections with sexually transmitted pathogens constitute an emerging global
threat. For this reason there needs to be a systematic research of the
molecular basis of sexually transmitted diseases in order to develop new
antibiotics. Protein domain fusion analysis is performed by the computational
application Matlab R2009b and an automated algorithm which is based on the
BLASTp algorithm. Finally, the use of appropriate databases (SMART) leads to
the analysis of the protein domain fusion events and the searching of
potential functional correlation of proteins
Keywords:
Protein function prediction, Protein-protein interaction prediction, Protein fusion, Protein domain fusion, Sexually transmitted diseases
Index:
No
Number of index pages:
0
Contains images:
Yes
Number of references:
133
Number of pages:
145

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