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Molecular modeling, dynamics studies and virtual screening of Fructose 1, 6 biphosphate aldolase-II in community acquired- methicillin resistant Staphylococcus aureus (CA-MRSA).

Yadav PK, Singh G, Gautam B, Singh S, Yadav M, Srivastav U, Singh B - Bioinformation (2013)

Bottom Line: The MDS results suggest that the modeled structure is stable.Based on the docking energy scores, it was found that top four ligands i.e. ZINC01690699, ZINC13154304, ZINC29590257 and ZINC29590259 were having lower energy scores which reveal higher binding affinity towards the active site of FBA.However, pharmacological studies are required to confirm the inhibitory activity of these ligands against the FBA in CA-MRSA.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Biology & Bioinformatics, Sam Higginbottom Institute of Agriculture, Technology & Sciences (Deemed University), Allahabad-211007, India.

ABSTRACT
Community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) has recently emerged as a nosocomial pathogen to the community which commonly causes skin and soft-tissue infections (SSTIs). This strain (MW2) has now become resistant to the most of the beta-lactam antibiotics; therefore it is the urgent need to identify the novel drug targets. Recently fructose 1,6 biphosphate aldolase-II (FBA) has been identified as potential drug target in CA-MRSA. The FBA catalyses the retro-ketolic cleavage of fructose-1,6-bisphosphate (FBP) to yield dihydroxyacetone phosphate (DHAP) and glyceraldehyde-3-phosphate (G3P) in glycolytic pathway. In the present research work the 3D structure of FBA was predicted using the homology modeling method followed by validation. The molecular dynamics simulation (MDS) of the predicted model was carried out using the 2000 ps time scale and 1000000 steps. The MDS results suggest that the modeled structure is stable. The predicted model of FBA was used for virtual screening against the NCI diversity subset-II ligand databases which contain 1364 compounds. Based on the docking energy scores, it was found that top four ligands i.e. ZINC01690699, ZINC13154304, ZINC29590257 and ZINC29590259 were having lower energy scores which reveal higher binding affinity towards the active site of FBA. These ligands might act as potent inhibitors for the FBA so that the menace of antimicrobial resistance in CA-MRSA can be conquered. However, pharmacological studies are required to confirm the inhibitory activity of these ligands against the FBA in CA-MRSA.

No MeSH data available.


Related in: MedlinePlus

Schematic representation of FBA-Ligand interactions in CA-MRSA A) ZINC01690699; B) ZINC13154304; C)ZINC29590257; D) ZINC29590259.
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Figure 3: Schematic representation of FBA-Ligand interactions in CA-MRSA A) ZINC01690699; B) ZINC13154304; C)ZINC29590257; D) ZINC29590259.

Mentions: Active site identification in the target protein is the startingpoint for virtual screening. Using the metaPocket 2.0 server,ligand binding site (pocket) was located in the 3D structure ofthe fructose biphosphate aldolase (FBA) of CA-MRSA. Threepockets were located in the target, and based on furtheranalysis of amino acid residues involved in the active site, 2ndpocket was chosen for the docking. This pocket was having 13residues in which Asn26, Gln237, Asp85, His86, His181 andHis209 have been reported to be conserved in the active site ofFBA [25]. The active site in the 3D structure of FBA on X, Y & Zcoordinates were located as -22.686Å, 55.957Å and 36.002Årespectively. Before performing the virtual screening for theFBA as a drug target, the receptor was prepared using a Pythonscript in the MGL tools package. The grid size for the receptorfor docking was given as 30 Å, 30Å and 30Å on X, Y & Zcoordinates respectively, which makes sure that the searchspace is large enough for the ligand to rotate in. Using theAutodock vina package, 1364 molecules from the NCI diversitysubset II were screened by the protein-ligand docking method.The Autodock vina algorithm searches the ligands in differentorientations in the active site of receptor. Two componentssearching and scoring are involved in most of the dockingalgorithms. The vina scoring function amalgamates knowledgebasedpotentials and empirical scoring functions, which extractsempirical information from both the conformational preferencesof the receptor-ligand complexes and the experimental affinitymeasurements [26]. After performing the virtual screeningusing the vina package, the docking results were analyzed fromthe log files using a Python script in the ADT (Auto Dock Tool).Based on the energy score, top 10 ligands from the NCIdiversity subset II molecules were selected for further analysisTable 1 (see supplementary material). Using theLigPlot+ program, schematic diagrams of protein-ligandinteractions for top four receptor-ligand docked complexeswere generated in 2D space. This diagram represents thehydrogen and hydrophobic interactions between ligand andactive site residues of the FBA (Figure 3). The moleculeZINC01690699 was interacting with Lys65 and Glu68 residuethrough hydrogen bond at a distance of 3.01 Å and 2.97 Årespectively while Tyr61, Met66, Asn27, Tyr56, Leu261, Tyr260,Pro257, Glu29, Leu28 & Gly69 residues were involved inhydrophobic interactions.


Molecular modeling, dynamics studies and virtual screening of Fructose 1, 6 biphosphate aldolase-II in community acquired- methicillin resistant Staphylococcus aureus (CA-MRSA).

Yadav PK, Singh G, Gautam B, Singh S, Yadav M, Srivastav U, Singh B - Bioinformation (2013)

Schematic representation of FBA-Ligand interactions in CA-MRSA A) ZINC01690699; B) ZINC13154304; C)ZINC29590257; D) ZINC29590259.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3569604&req=5

Figure 3: Schematic representation of FBA-Ligand interactions in CA-MRSA A) ZINC01690699; B) ZINC13154304; C)ZINC29590257; D) ZINC29590259.
Mentions: Active site identification in the target protein is the startingpoint for virtual screening. Using the metaPocket 2.0 server,ligand binding site (pocket) was located in the 3D structure ofthe fructose biphosphate aldolase (FBA) of CA-MRSA. Threepockets were located in the target, and based on furtheranalysis of amino acid residues involved in the active site, 2ndpocket was chosen for the docking. This pocket was having 13residues in which Asn26, Gln237, Asp85, His86, His181 andHis209 have been reported to be conserved in the active site ofFBA [25]. The active site in the 3D structure of FBA on X, Y & Zcoordinates were located as -22.686Å, 55.957Å and 36.002Årespectively. Before performing the virtual screening for theFBA as a drug target, the receptor was prepared using a Pythonscript in the MGL tools package. The grid size for the receptorfor docking was given as 30 Å, 30Å and 30Å on X, Y & Zcoordinates respectively, which makes sure that the searchspace is large enough for the ligand to rotate in. Using theAutodock vina package, 1364 molecules from the NCI diversitysubset II were screened by the protein-ligand docking method.The Autodock vina algorithm searches the ligands in differentorientations in the active site of receptor. Two componentssearching and scoring are involved in most of the dockingalgorithms. The vina scoring function amalgamates knowledgebasedpotentials and empirical scoring functions, which extractsempirical information from both the conformational preferencesof the receptor-ligand complexes and the experimental affinitymeasurements [26]. After performing the virtual screeningusing the vina package, the docking results were analyzed fromthe log files using a Python script in the ADT (Auto Dock Tool).Based on the energy score, top 10 ligands from the NCIdiversity subset II molecules were selected for further analysisTable 1 (see supplementary material). Using theLigPlot+ program, schematic diagrams of protein-ligandinteractions for top four receptor-ligand docked complexeswere generated in 2D space. This diagram represents thehydrogen and hydrophobic interactions between ligand andactive site residues of the FBA (Figure 3). The moleculeZINC01690699 was interacting with Lys65 and Glu68 residuethrough hydrogen bond at a distance of 3.01 Å and 2.97 Årespectively while Tyr61, Met66, Asn27, Tyr56, Leu261, Tyr260,Pro257, Glu29, Leu28 & Gly69 residues were involved inhydrophobic interactions.

Bottom Line: The MDS results suggest that the modeled structure is stable.Based on the docking energy scores, it was found that top four ligands i.e. ZINC01690699, ZINC13154304, ZINC29590257 and ZINC29590259 were having lower energy scores which reveal higher binding affinity towards the active site of FBA.However, pharmacological studies are required to confirm the inhibitory activity of these ligands against the FBA in CA-MRSA.

View Article: PubMed Central - PubMed

Affiliation: Department of Computational Biology & Bioinformatics, Sam Higginbottom Institute of Agriculture, Technology & Sciences (Deemed University), Allahabad-211007, India.

ABSTRACT
Community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) has recently emerged as a nosocomial pathogen to the community which commonly causes skin and soft-tissue infections (SSTIs). This strain (MW2) has now become resistant to the most of the beta-lactam antibiotics; therefore it is the urgent need to identify the novel drug targets. Recently fructose 1,6 biphosphate aldolase-II (FBA) has been identified as potential drug target in CA-MRSA. The FBA catalyses the retro-ketolic cleavage of fructose-1,6-bisphosphate (FBP) to yield dihydroxyacetone phosphate (DHAP) and glyceraldehyde-3-phosphate (G3P) in glycolytic pathway. In the present research work the 3D structure of FBA was predicted using the homology modeling method followed by validation. The molecular dynamics simulation (MDS) of the predicted model was carried out using the 2000 ps time scale and 1000000 steps. The MDS results suggest that the modeled structure is stable. The predicted model of FBA was used for virtual screening against the NCI diversity subset-II ligand databases which contain 1364 compounds. Based on the docking energy scores, it was found that top four ligands i.e. ZINC01690699, ZINC13154304, ZINC29590257 and ZINC29590259 were having lower energy scores which reveal higher binding affinity towards the active site of FBA. These ligands might act as potent inhibitors for the FBA so that the menace of antimicrobial resistance in CA-MRSA can be conquered. However, pharmacological studies are required to confirm the inhibitory activity of these ligands against the FBA in CA-MRSA.

No MeSH data available.


Related in: MedlinePlus