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Exploring the molecular basis for selective binding of homoserine dehydrogenase from Mycobacterium leprae TN toward inhibitors: a virtual screening study.

Zhan D, Wang D, Min W, Han W - Int J Mol Sci (2014)

Bottom Line: Using the template, homoserine dehydrogenase from Thiobacillus denitrificans (PDB Id 3MTJ), a sequence identity of 40% was found and molecular dynamics simulation was used to optimize a reliable structure.These ligands therefore seemed to be new chemotypes for HSD.Our results may be helpful for further experimental investigations.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Jilin University, Changchun 130023, China. zdlgale@126.com.

ABSTRACT
Homoserine dehydrogenase (HSD) from Mycobacterium leprae TN is an antifungal target for antifungal properties including efficacy against the human pathogen. The 3D structure of HSD has been firmly established by homology modeling methods. Using the template, homoserine dehydrogenase from Thiobacillus denitrificans (PDB Id 3MTJ), a sequence identity of 40% was found and molecular dynamics simulation was used to optimize a reliable structure. The substrate and co-factor-binding regions in HSD were identified. In order to determine the important residues of the substrate (L-aspartate semialdehyde (L-ASA)) binding, the ASA was docked to the protein; Thr163, Asp198, and Glu192 may be important because they form a hydrogen bond with HSD through AutoDock 4.2 software. neuraminidaseAfter use of a virtual screening technique of HSD, the four top-scoring docking hits all seemed to cation-π ion pair with the key recognition residue Lys107, and Lys207. These ligands therefore seemed to be new chemotypes for HSD. Our results may be helpful for further experimental investigations.

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Related in: MedlinePlus

Receiving operating characteristic (ROC) curve.
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f7-ijms-15-01826: Receiving operating characteristic (ROC) curve.

Mentions: It was reported that the receiving operating characteristic (ROC) evaluation is described as the ratio of the true positive rate to the false positive rate when a given proportion of known decoys have been observed [31,32]. Moreover, the receiving operating characteristic (ROC) curve, a graphical plot of the sensitivity (true positive rate, sensitivity) VS specificity (false positive rate), was calculated to avoid the sensitivity for small changes in ranking, where T score represents the number of correctly identified actives, and F score (false positives) represents the number of decoys incorrectly predicted as actives. The area under the ROC curve (AUC plot) gives the probability of ranking a randomly selected active higher than a randomly chosen decoy [33]. It ranges from 0 to 1, where 1 indicates a perfect ranking, where in all actives ranked above the decoys. A traditional academic point system for classifying the accuracy of a virtual screening test is known as follows: AUC < 0.5 is fail; 0.5 ≤ AUC < 0.70 is poor; 0.7 ≤ AUC < 0.8 is fair; 0.8 ≤ AUC < 0.9 is good; and 0.9 ≤ AUC ≤ 1 is excellent [34]. Essentially independent of the actual number of positive and negative instances, the AUC of an ROC plot gives an objective measure of query performance. In this study, 32 inhibitors [14,15,35,36] were used to generate the decoys using DUD-E on line [31]. Autodock 4.2 [27,29], Autodock vina [29,30] and Dock 3.6 [37] are used for docking. The ROC curve is shown in Figure 7. From Figure 7, AUC plot with Autodock 4.2 is 0.64, which is larger than that of AutoDock vina and Dock 3.6. And so Autodock 4.2 is used to further virtual screening.


Exploring the molecular basis for selective binding of homoserine dehydrogenase from Mycobacterium leprae TN toward inhibitors: a virtual screening study.

Zhan D, Wang D, Min W, Han W - Int J Mol Sci (2014)

Receiving operating characteristic (ROC) curve.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3958823&req=5

f7-ijms-15-01826: Receiving operating characteristic (ROC) curve.
Mentions: It was reported that the receiving operating characteristic (ROC) evaluation is described as the ratio of the true positive rate to the false positive rate when a given proportion of known decoys have been observed [31,32]. Moreover, the receiving operating characteristic (ROC) curve, a graphical plot of the sensitivity (true positive rate, sensitivity) VS specificity (false positive rate), was calculated to avoid the sensitivity for small changes in ranking, where T score represents the number of correctly identified actives, and F score (false positives) represents the number of decoys incorrectly predicted as actives. The area under the ROC curve (AUC plot) gives the probability of ranking a randomly selected active higher than a randomly chosen decoy [33]. It ranges from 0 to 1, where 1 indicates a perfect ranking, where in all actives ranked above the decoys. A traditional academic point system for classifying the accuracy of a virtual screening test is known as follows: AUC < 0.5 is fail; 0.5 ≤ AUC < 0.70 is poor; 0.7 ≤ AUC < 0.8 is fair; 0.8 ≤ AUC < 0.9 is good; and 0.9 ≤ AUC ≤ 1 is excellent [34]. Essentially independent of the actual number of positive and negative instances, the AUC of an ROC plot gives an objective measure of query performance. In this study, 32 inhibitors [14,15,35,36] were used to generate the decoys using DUD-E on line [31]. Autodock 4.2 [27,29], Autodock vina [29,30] and Dock 3.6 [37] are used for docking. The ROC curve is shown in Figure 7. From Figure 7, AUC plot with Autodock 4.2 is 0.64, which is larger than that of AutoDock vina and Dock 3.6. And so Autodock 4.2 is used to further virtual screening.

Bottom Line: Using the template, homoserine dehydrogenase from Thiobacillus denitrificans (PDB Id 3MTJ), a sequence identity of 40% was found and molecular dynamics simulation was used to optimize a reliable structure.These ligands therefore seemed to be new chemotypes for HSD.Our results may be helpful for further experimental investigations.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Jilin University, Changchun 130023, China. zdlgale@126.com.

ABSTRACT
Homoserine dehydrogenase (HSD) from Mycobacterium leprae TN is an antifungal target for antifungal properties including efficacy against the human pathogen. The 3D structure of HSD has been firmly established by homology modeling methods. Using the template, homoserine dehydrogenase from Thiobacillus denitrificans (PDB Id 3MTJ), a sequence identity of 40% was found and molecular dynamics simulation was used to optimize a reliable structure. The substrate and co-factor-binding regions in HSD were identified. In order to determine the important residues of the substrate (L-aspartate semialdehyde (L-ASA)) binding, the ASA was docked to the protein; Thr163, Asp198, and Glu192 may be important because they form a hydrogen bond with HSD through AutoDock 4.2 software. neuraminidaseAfter use of a virtual screening technique of HSD, the four top-scoring docking hits all seemed to cation-π ion pair with the key recognition residue Lys107, and Lys207. These ligands therefore seemed to be new chemotypes for HSD. Our results may be helpful for further experimental investigations.

Show MeSH
Related in: MedlinePlus