Predviđanje specifičnosti izbora supstrata domena za adenilaciju

master's thesis

• Title (english): Prediction of adenilation domains substrate specificity
• Author: Marija Duvnjak
• Mentor: Antonio Starčević (mentor)
• Granter: University of Zagreb; Faculty of Food Technology and Biotechnology; (Department of Biochemical Engineering); (Section for Bioinformatics); Zagreb
• Defense date and country: 2012-10-09, Croatia
• Scientific / art field, discipline and subdiscipline: BIOTECHNICAL SCIENCES; Biotechnology

Abstract

U posljednje se vrijeme, u znanstvenoj javnosti, pojavilo veliko zanimanje za oblikovanje novih lijekova. Genske nakupine čiji proteinski produkti sudjeluju u sintezi biološki aktivnih supstancija za oblikovanje novih lijekova nalaze se u genomima sekvenciranih mikroorganizama. Razvijen je čitav niz javno dostupnih baza podataka i bioinformatičkih alata za njihovu analizu. To se posebno odnosi na bioinformatičke alate koji analiziraju genske nakupine, čiji produkti sudjeluju u sintezi sekundarnih metabolita u uvjetima in silico. Jedna od skupina zanimljivih prirodnih spojeva jesu neribosomalno sintetizirani peptidi. Adenilacijske domene (A-domene), obavezne podjedinice modula neribosomalno sintetiziranih peptid sintetaza (NRPS), prepoznaju i aktiviraju aminokiseline koje moraju biti ugrađene u konačni produkt, neribosomalno sintetizirani peptid. Poznavanje specifičnosti A-domena za supstrat omogućit će predviđanje konačne kemijske strukture produkata genskih nakupina NRPS i dizajn novih biološki aktivnih prirodnih spojeva. U ovom su radu predviđanja aminokiselinskih supstrata, koje aktiviraju A-domene, provedena pomoću višestrukih poravnanja upotrebom bioinformatičkog programa Clustal W i filogenetskih analiza upotrebom bioinformatičkog programa za molekularne evolucijske genetske analize, MEGA, te bioinformatičkog programa HMMER 3 za konstrukciju HMM profila za prepoznavanje supstrata.

Abstract (english)

During the last several years there is an increased scientific interest for the design of novel drugs. Gene clusters whose protein products are involved in the synthesis of these biologically active substances used for novel drug design are present in sequenced microbial genomes. For that reason a number of publically available databases and bioinformatic tools were developed to analyse gene clusters whose products are involved in the biosynthesis of natural products in silico. One class of interesting natural products is nonribosomally synthesized peptides. Adenylation domains (A-domains), obligatory subunits of modules of non-ribosomally synthesised peptide synthetases (NRPS), are recognising and activating amino acid that are incorporated into the final product, non-ribosomally sythesised peptide. Knowing the A-domain substrate specificity for every sequenced A-domain would enable the prediction of final chemical structure of NRPS gene cluster product and the design of novel biologically active natural products. In this work, the multiple alignments by the bioinformatics program Clustal W, followed by phylogenetic analysis by the bioinformatics program for the molecular evolutionary genetics analysis, MEGA and bioinformatics program HMMER 3 for the construction of HMM profiles were used for the prediction of the amino acid substrates which are activated by A-domains.

• Keywords: A-domene; višestruka poravnanja; filogenetske analize; predviđanje specifičnosti
• Keywords (english): A-domains; multiple alignments; phylogenetic analysis; specificity prediction
• Language: croatian
• URN:NBN: urn:nbn:hr:159:275764
• Study programme: Title: Biotechnology; specializations in: Biochemical Engineering; Course: Biochemical Engineering; Study programme type: university; Study level: graduate; Academic / professional title: diplomirani inženjer biotehnologije; smjer biokemijsko inženjerstvo (diplomirani inženjer biotehnologije; smjer biokemijsko inženjerstvo)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Access restricted to students and staff of home institution
• Created on: 2017-05-17 09:54:42