CPL - Chalmers Publication Library
| Utbildning | Forskning | Styrkeområden | Om Chalmers | In English In English Ej inloggad.

The interplay of descriptor-based computational analysis with pharmacophore modeling builds the basis for a novel classification scheme for feruloyl esterases

D.B.R.K. Gupta Udatha (Institutionen för kemi- och bioteknik, Industriell Bioteknik ) ; Irene Kouskoumvekaki ; Lisbeth Olsson (Institutionen för kemi- och bioteknik, Industriell Bioteknik ) ; Gianni Panagiotou (Institutionen för kemi- och bioteknik, Industriell Bioteknik )
Biotechnology Advances (0734-9750). Vol. 29 (2011), 1, p. 94-110.
[Artikel, refereegranskad vetenskaplig]

One of the most intriguing groups of enzymes, the feruloyl esterases (FAEs), is ubiquitous in both simple and complex organisms. FAEs have gained importance in biofuel, medicine and food industries due to their capability of acting on a large range of substrates for cleaving ester bonds and synthesizing high-added value molecules through esterification and transesterification reactions. During the past two decades extensive studies have been carried out on the production and partial characterization of FAEs from fungi, while much less is known about FAEs of bacterial or plant origin. Initial classification studies on FAEs were restricted on sequence similarity and substrate specificity on just four model substrates and considered only a handful of FAEs belonging to the fungal kingdom. This study centers on the descriptor-based classification and structural analysis of experimentally verified and putative FAEs; nevertheless, the framework presented here is applicable to every poorly characterized enzyme family. 365 FAE-related sequences of fungal, bacterial and plantae origin were collected and they were clustered using Self Organizing Maps followed by k-means clustering into distinct groups based on amino acid composition and physico-chemical composition descriptors derived from the respective amino acid sequence. A Support Vector Machine model was subsequently constructed for the classification of new FAEs into the pre-assigned clusters. The model successfully recognized 98.2% of the training sequences and all the sequences of the blind test. The underlying functionality of the 12 proposed FAE families was validated against a combination of prediction tools and published experimental data. Another important aspect of the present work involves the development of pharmacophore models for the new FAE families, for which sufficient information on known substrates existed. Knowing the pharmacophoric features of a small molecule that are essential for binding to the members of a certain family opens a window of opportunities for tailored applications of FAEs.

Nyckelord: Phylogenetic analysis; Self organizing maps; k-means clustering; Support vector machine; Catalytic triad; Ligand binding site

Supplementary Files associated with this article can be obtained through e-mail from D.B.R.K. Gupta Udatha (gupta.udatha@chalmers.se)

Den här publikationen ingår i följande styrkeområden:

Läs mer om Chalmers styrkeområden  

Denna post skapades 2010-10-12. Senast ändrad 2015-03-30.
CPL Pubid: 127539


Läs direkt!

Lokal fulltext (fritt tillgänglig)

Länk till annan sajt (kan kräva inloggning)

Institutioner (Chalmers)

Institutionen för kemi- och bioteknik, Industriell Bioteknik (2008-2014)


Bioinformatik och systembiologi
Biokatalys och enzymteknik

Chalmers infrastruktur