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Identification of novel bacterial histidine biosynthesis inhibitors using docking, ensemble rescoring, and whole-cell assays.

ABSTRACT: The rapid spread on multidrug-resistant strains of Staphylococcus aureus requires not just novel treatment options, but the development of faster methods for the identification of new hits for drug development. The exponentially increasing speed of computational methods makes a more extensive use in the early stages of drug discovery attractive if sufficient accuracy can be achieved. Computational target identification using systems-level methods suggested the histidine biosynthesis pathway as an attractive target against S. aureus. Potential inhibitors for the pathway were identified through docking, followed by ensemble rescoring, that is sufficiently accurate to justify immediate testing of the identified compounds by whole-cell assays, avoiding the need for time-consuming and often difficult intermediary enzyme assays. This novel strategy is demonstrated for three key enzymes of the S. aureus histidine biosynthesis pathway, which is predicted to be essential for bacterial biomass productions. Virtual screening of a library of approximately 10(6) compounds identified 49 potential inhibitors of three enzymes of this pathway. Eighteen representative compounds were directly tested on three S. aureus- and two Escherichia coli strains in standard disk inhibition assays. Thirteen compounds are inhibitors of some or all of the S. aureus strains, while 14 compounds weakly inhibit growth in one or both E. coli strains. The high hit rate obtained from a fast virtual screen demonstrates the applicability of this novel strategy to the histidine biosynthesis pathway.

SUBMITTER: Henriksen ST

PROVIDER: S-EPMC2903657 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

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Identification of novel bacterial histidine biosynthesis inhibitors using docking, ensemble rescoring, and whole-cell assays.

Henriksen S T ST Liu J J Estiu G G Oltvai Z N ZN Wiest O O

Bioorganic & medicinal chemistry 20100601 14

The rapid spread on multidrug-resistant strains of Staphylococcus aureus requires not just novel treatment options, but the development of faster methods for the identification of new hits for drug development. The exponentially increasing speed of computational methods makes a more extensive use in the early stages of drug discovery attractive if sufficient accuracy can be achieved. Computational target identification using systems-level methods suggested the histidine biosynthesis pathway as a ...[more]

PMID: 20573514

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Project description:Molecular docking computationally screens thousands to millions of organic molecules against protein structures, looking for those with complementary fits. Many approximations are made, often resulting in low "hit rates." A strategy to overcome these approximations is to rescore top-ranked docked molecules using a better but slower method. One such is afforded by molecular mechanics-generalized Born surface area (MM-GBSA) techniques. These more physically realistic methods have improved models for solvation and electrostatic interactions and conformational change compared to most docking programs. To investigate MM-GBSA rescoring, we re-ranked docking hit lists in three small buried sites: a hydrophobic cavity that binds apolar ligands, a slightly polar cavity that binds aryl and hydrogen-bonding ligands, and an anionic cavity that binds cationic ligands. These sites are simple; consequently, incorrect predictions can be attributed to particular errors in the method, and many likely ligands may actually be tested. In retrospective calculations, MM-GBSA techniques with binding-site minimization better distinguished the known ligands for each cavity from the known decoys compared to the docking calculation alone. This encouraged us to test rescoring prospectively on molecules that ranked poorly by docking but that ranked well when rescored by MM-GBSA. A total of 33 molecules highly ranked by MM-GBSA for the three cavities were tested experimentally. Of these, 23 were observed to bind--these are docking false negatives rescued by rescoring. The 10 remaining molecules are true negatives by docking and false positives by MM-GBSA. X-ray crystal structures were determined for 21 of these 23 molecules. In many cases, the geometry prediction by MM-GBSA improved the initial docking pose and more closely resembled the crystallographic result; yet in several cases, the rescored geometry failed to capture large conformational changes in the protein. Intriguingly, rescoring not only rescued docking false positives, but also introduced several new false positives into the top-ranking molecules. We consider the origins of the successes and failures in MM-GBSA rescoring in these model cavity sites and the prospects for rescoring in biologically relevant targets.

Dataset Information

Identification of novel bacterial histidine biosynthesis inhibitors using docking, ensemble rescoring, and whole-cell assays.

Publications

Identification of novel bacterial histidine biosynthesis inhibitors using docking, ensemble rescoring, and whole-cell assays.

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