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http://elea.unisa.it/xmlui/handle/10556/3018
Titolo: | Computational design of new antimicrobial peptides |
Autore: | Sbardella, Gianluca Piotto, Stefano Parisi, Rosaura |
Parole chiave: | Antimicrobial;QSAR |
Data: | 13-apr-2018 |
Abstract: | Antimicrobial peptides (AMP) are evolutionarily conserved components of the innate immune system. They have a broad spectrum of action against bacteria, fungi and viruses. Therefore, AMP are studied as probable substitutes of the traditional antibiotics, for which most pathogens have developed resistance. The main objective of this work was the design of novel linear peptides capable to interact with the cellular membrane of the common pathogens. In this work, sequences of active AMP were carefully obtained from the scientific literature and collected in Yadamp (http://yadamp.unisa.it/), a database of AMP created recently in the laboratory where this project was carried out. In Yadamp, there are information about peptides name, amino acid sequence, length, presence of disulfide bridges, date of discovery, activity and taxonomy. The most relevant chemical-physical properties are also listed. This database is mainly focused on the peptides activities. Experimental MIC values (the lowest concentration of an antimicrobial that inhibits the visible growth of a microorganism) are constantly obtained from careful reading the original papers. In this work, a great contribution was made in the enrichment of the database. In fact, 1009 sequences were added to Yadamp. It currently contains 3142 AMP sequences. For these AMP, 573 molecular descriptors were calculated. In addition, this project also involved the search for new molecular descriptors. Yadamp is a resource for QSAR investigations on AMP. It allows to create subsets of AMP, homogeneous in one, two or more parameters...[abstract by Author] |
Descrizione: | 2016 - 2017 |
URI: | http://hdl.handle.net/10556/3018 http://dx.doi.org/10.14273/unisa-1308 |
È visualizzato nelle collezioni: | Scienze del farmaco |
File in questo documento:
File | Descrizione | Dimensioni | Formato | |
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tesi di dottorato R. Parisi.pdf | tesi di dottorato | 9,38 MB | Adobe PDF | Visualizza/apri |
abstract in inglese R. Parisi.pdf | abstract in inglese a cura dell'autore | 138,62 kB | Adobe PDF | Visualizza/apri |
abstract in italiano R. Parisi.pdf | abstract in italiano a cura dell'autore | 69,15 kB | Adobe PDF | Visualizza/apri |
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