-
Something wrong with this record ?
In silico mutagenesis and docking studies of Pseudomonas aeruginosa PA-IIL lectin predicting binding modes and energies
J Adam, Z Kriz, MP Prokop, M Wimmerova, J Koca
Language English Country United States
PubMed
18937439
DOI
10.1021/ci8002107
Knihovny.cz E-resources
- MeSH
- Adhesins, Bacterial genetics chemistry MeSH
- Financing, Organized MeSH
- Informatics MeSH
- Protein Structure, Quaternary MeSH
- Lectins genetics chemistry MeSH
- Ligands MeSH
- Models, Molecular MeSH
- Molecular Sequence Data MeSH
- Monosaccharides chemistry MeSH
- Mutagenesis, Site-Directed statistics & numerical data MeSH
- Computer Simulation MeSH
- Pseudomonas aeruginosa genetics chemistry MeSH
- Amino Acid Sequence MeSH
- Sequence Homology, Amino Acid MeSH
- Software MeSH
- Thermodynamics MeSH
- Calcium chemistry MeSH
- Binding Sites genetics MeSH
This article is focused on the application of two types of docking software, AutoDock and DOCK. It is aimed at studying the interactions of a calcium-dependent bacterial lectin PA-IIL (from Pseudomonas aeruginosa) and its in silico mutants with saccharide ligands. The effect of different partial charges assigned to the calcium ions was tested and evaluated in terms of the best agreement with the crystal structure. The results of DOCK were further optimized by molecular dynamics and rescored using AMBER. For both software, the agreement of the docked structures and the provided binding energies were evaluated in terms of prediction accuracy. This was carried out by comparing the computed results to the crystal structures and experimentally determined binding energies, respectively. The performance of both docking software applied on a studied problem was evaluated as well. The molecular docking methods proved efficient in identifying the correct binding modes in terms of geometry and partially also in predicting the preference changes caused by mutation. Obtaining a reasonable in silico method for the prediction of lectin-saccharide interactions may be possible in the future.
References provided by Crossref.org
- 000
- 03185naa 2200493 a 4500
- 001
- bmc11006173
- 003
- CZ-PrNML
- 005
- 20121112132632.0
- 008
- 110331s2008 xxu e eng||
- 009
- AR
- 024 __
- $a 10.1021/ci8002107 $2 doi
- 035 __
- $a (PubMed)18937439
- 040 __
- $a ABA008 $b cze $c ABA008 $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Adam, Jan $7 xx0116781
- 245 10
- $a In silico mutagenesis and docking studies of Pseudomonas aeruginosa PA-IIL lectin predicting binding modes and energies / $c J Adam, Z Kriz, MP Prokop, M Wimmerova, J Koca
- 314 __
- $a National Centre for Biomolecular Research, Department of Biochemistry, and Department of Chemistry, Faculty of Science, Kotlarska 2, Masaryk University, 611 37 Brno, Czech Republic.
- 520 9_
- $a This article is focused on the application of two types of docking software, AutoDock and DOCK. It is aimed at studying the interactions of a calcium-dependent bacterial lectin PA-IIL (from Pseudomonas aeruginosa) and its in silico mutants with saccharide ligands. The effect of different partial charges assigned to the calcium ions was tested and evaluated in terms of the best agreement with the crystal structure. The results of DOCK were further optimized by molecular dynamics and rescored using AMBER. For both software, the agreement of the docked structures and the provided binding energies were evaluated in terms of prediction accuracy. This was carried out by comparing the computed results to the crystal structures and experimentally determined binding energies, respectively. The performance of both docking software applied on a studied problem was evaluated as well. The molecular docking methods proved efficient in identifying the correct binding modes in terms of geometry and partially also in predicting the preference changes caused by mutation. Obtaining a reasonable in silico method for the prediction of lectin-saccharide interactions may be possible in the future.
- 650 _2
- $a bakteriální adheziny $x genetika $x chemie $7 D018829
- 650 _2
- $a sekvence aminokyselin $7 D000595
- 650 _2
- $a vazebná místa $x genetika $7 D001665
- 650 _2
- $a vápník $x chemie $7 D002118
- 650 _2
- $a počítačová simulace $7 D003198
- 650 _2
- $a informatika $7 D048088
- 650 _2
- $a lektiny $x genetika $x chemie $7 D037102
- 650 _2
- $a ligandy $7 D008024
- 650 _2
- $a molekulární modely $7 D008958
- 650 _2
- $a molekulární sekvence - údaje $7 D008969
- 650 _2
- $a monosacharidy $x chemie $7 D009005
- 650 _2
- $a mutageneze cílená $x statistika a číselné údaje $7 D016297
- 650 _2
- $a kvarterní struktura proteinů $7 D020836
- 650 _2
- $a Pseudomonas aeruginosa $x genetika $x chemie $7 D011550
- 650 _2
- $a sekvenční homologie aminokyselin $7 D017386
- 650 _2
- $a software $7 D012984
- 650 _2
- $a termodynamika $7 D013816
- 650 _2
- $a financování organizované $7 D005381
- 700 1_
- $a Kříž, Zdeněk $7 xx0068636
- 700 1_
- $a Prokop, Martin. $7 mub2013762476
- 700 1_
- $a Wimmerová, Michaela $7 ola2004235533
- 700 1_
- $a Koča, Jaroslav, $d 1955-2021 $7 jn20000710314
- 773 0_
- $t Journal of Chemical Information and Modeling $w MED00008945 $g Roč. 48, č. 11 (2008), s. 2234-2242 $x 1549-9596
- 910 __
- $a ABA008 $b x $y 2
- 990 __
- $a 20110414100505 $b ABA008
- 991 __
- $a 20121112132646 $b ABA008
- 999 __
- $a ok $b bmc $g 833786 $s 698265
- BAS __
- $a 3
- BMC __
- $a 2008 $b 48 $c 11 $d 2234-2242 $i 1549-9596 $m Journal of chemical information and modeling $n J Chem Inf Model $x MED00008945
- LZP __
- $a 2011-1B09/dkme