Comparison of in silico tools for binding site prediction applied for structure-based design of autolysin inhibitors. Issue 7 (2nd July 2016)
- Record Type:
- Journal Article
- Title:
- Comparison of in silico tools for binding site prediction applied for structure-based design of autolysin inhibitors. Issue 7 (2nd July 2016)
- Main Title:
- Comparison of in silico tools for binding site prediction applied for structure-based design of autolysin inhibitors
- Authors:
- Tibaut, T.
Borišek, J.
Novič, M.
Turk, D. - Abstract:
- Abstract: Autolysin E (AtlE) is a bacteriolytic enzyme which plays an important role in division and growth of bacterial cells and therefore represents a promising potential drug target. Its 3D structure has been recently elucidated. We used in silico prediction tools to study substrate or ligand (inhibitor) binding regions of AtlE. We applied several freely available tools and a commercial tool for binding site identification and compared results of the prediction. Calculation time, number of predictions and output data provided by specific software vary according to the different approaches utilized by specific method categories. Despite different approaches, binding sites in similar locations on the protein were predicted. Specific amino acid residues that form these binding sites were predicted as binding residues. The predicted residues, especially those with predicted highest conservation score, could theoretically have catalytic and binding properties. According to our results, we assume that E138, which has the highest conservation score, is the catalytic residue and F161, G162 and Y224, which are also highly conserved, are responsible for substrate binding. Ligands developed with binding specificity towards these residues could inhibit the catalysis and binding of the substrate of AtlE. The molecules with inhibitory potency could therefore represent potential new antibacterial agents.
- Is Part Of:
- SAR and QSAR in environmental research. Volume 27:Issue 7(2016)
- Journal:
- SAR and QSAR in environmental research
- Issue:
- Volume 27:Issue 7(2016)
- Issue Display:
- Volume 27, Issue 7 (2016)
- Year:
- 2016
- Volume:
- 27
- Issue:
- 7
- Issue Sort Value:
- 2016-0027-0007-0000
- Page Start:
- 573
- Page End:
- 587
- Publication Date:
- 2016-07-02
- Subjects:
- Binding site identification -- autolysin E -- binding residues -- potential drug target -- in silico tools comparison
Structure-activity relationships (Biochemistry) -- Periodicals
QSAR (Biochemistry) -- Periodicals
572.4 - Journal URLs:
- http://www.tandfonline.com/toc/gsar20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/1062936X.2016.1217271 ↗
- Languages:
- English
- ISSNs:
- 1062-936X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8075.965500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14470.xml