A practical approach to docking of zinc metalloproteinase inhibitors

Hu, Xin; Baláž, Štefan; Shelver, William H.

doi:10.1016/j.jmgm.2003.11.002

Cited by 94 publications

(88 citation statements)

References 65 publications

(52 reference statements)

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“…DOCK 4.0 (16) was used for docking. Zinc parameters were optimized using the same training set as that described by Hu et al (23). In all cases, the scoring grids were defined to include the whole active site around the Zn.…”

Section: Methodsmentioning

confidence: 99%

Identification and Biochemical Characterization of Small-Molecule Inhibitors of Clostridium botulinum Neurotoxin Serotype A

Roxas-Duncan

Enyedy

Montgomery

et al. 2009

Antimicrob Agents Chemother

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An integrated strategy that combined in silico screening and tiered biochemical assays (enzymatic, in vitro, and ex vivo) was used to identify and characterize effective small-molecule inhibitors of Clostridium botulinum neurotoxin serotype A (BoNT/A). Virtual screening was initially performed by computationally docking compounds of the National Cancer Institute (NCI) database into the active site of BoNT/A light chain (LC). A total of 100 high-scoring compounds were evaluated in a high-performance liquid chromatography (HPLC)-based protease assay using recombinant full-length BoNT/A LC. Seven compounds that significantly inhibited the BoNT/A protease activity were selected. Database search queries of the best candidate hit [7-((4-nitroanilino)(phenyl)methyl)-8-quinolinol (NSC 1010)] were performed to mine its nontoxic analogs. Fifty-five analogs of NSC 1010 were synthesized and examined by the HPLC-based assay. Of these, five quinolinol derivatives that potently inhibited both full-length BoNT/A LC and truncated BoNT/A LC (residues 1 to 425) were selected for further inhibition studies in neuroblastoma (N2a) cell-based and tissue-based mouse phrenic nerve hemidiaphragm assays. Consistent with enzymatic assays, in vitro and ex vivo studies revealed that these five quinolinol-based analogs effectively neutralized BoNT/A toxicity, with CB 7969312 exhibiting ex vivo protection at 0.5 M. To date, this is the most potent BoNT/A small-molecule inhibitor that showed activity in an ex vivo assay. The reduced toxicity and high potency demonstrated by these five compounds at the biochemical, cellular, and tissue levels are distinctive among the BoNT/A small-molecule inhibitors reported thus far. This study demonstrates the utility of a multidisciplinary approach (in silico screening coupled with biochemical testing) for identifying promising small-molecule BoNT/A inhibitors.

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Section: Methodsmentioning

confidence: 99%

Identification and Biochemical Characterization of Small-Molecule Inhibitors of Clostridium botulinum Neurotoxin Serotype A

Roxas-Duncan

Enyedy

Montgomery

et al. 2009

Antimicrob Agents Chemother

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“…Recent reports of success at reproducing docked geometries include the targets matrix metalloproteinases (11,12) and carbonic anhydrase (13). Molecular docking methods have also been used for lead optimization starting from a structure of the dizinc enzyme leucine aminopeptidase (14) and similarly for hydroxamic acid ligands against histone deacetylase (15).…”

mentioning

confidence: 99%

Virtual Screening against Metalloenzymes for Inhibitors and Substrates

2005

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Molecular docking uses the three-dimensional structure of a receptor to screen databases of small molecules for potential ligands, often based on energetic complementarity. For many docking scoring functions, which calculate nonbonded interactions, metalloenzymes are challenging because of the partial covalent nature of metal-ligand interactions. To investigate how well molecular docking can identify potential ligands of metalloenzymes using a "standard" scoring function, we have docked the MDL Drug Data Report (MDDR), a functionally annotated database of 95 000 small molecules, against the X-ray crystal structures of five metalloenzymes. These enzymes included three zinc proteases, the nickel analogue of an iron enzyme, and a molybdenum metalloenzyme. The ability of the docking program to retrospectively enrich the annotated ligands as high-scoring hits for each enzyme and to calculate proper geometries was evaluated. In all five systems, the annotated ligands within the MDDR were enriched at least 20 times over random. To test the approach prospectively, a sixth target, the zinc -lactamase from Bacteroides fragilis, was screened against the fragment-like subset of the ZINC database. We purchased and tested 15 compounds from among the top 50 top-ranked ligands from docking, and found 5 inhibitors with apparent K i values less than 120 µM, the best of which was 2 µM. A more ambitious test still was predicting actual substrates for a seventh target, a Zn-dependent phosphotriesterase from Pseudomonas diminuta. Screening the Available Chemicals Directory (ACD) identified 25 thiophosphate esters as potential substrates within the top 100 ranked compounds. Eight of these, all previously uncharacterized for this enzyme, were acquired and tested, and all were confirmed experimentally as substrates. These results suggest that a simple, noncovalent scoring function may be used to identify inhibitors of at least some metalloenzymes.Metalloenzymes are important therapeutic targets, having attracted interest for diseases such as cancer (1, 2), arthritis (3), glaucoma (4), and infectious disease (5), among others. There has been considerable interest in the structural bases for their actions, and the structures of many metalloenzyme targets have been determined. These structures have provided templates for atomic resolution modeling of reaction mechanism and for inhibitor discovery.A problem faced in modeling metalloenzymes is the key role played by the metal. Molecular mechanics potential functions, which underlie most modeling approaches, have been parametrized to treat molecules as interacting either covalently or noncovalently. Metal-ligand interactions fit uncomfortably into either of these categories. Whereas vibrational spectroscopy indicates the presence of a metal ligand bond consistent with a force field treatment, the dative covalent "bond" is nearly an order of magnitude weaker than a covalent bond between first and second row elements. Further complicating the calculations is the unusually high charge ...

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“…[7][8][9][10][11] In these reports, the inhibition effect of small molecules was investigated by studying their binding behaviors on protease surfaces. However, the binding properties of ligand molecules to locally regulated fluctuating proteins are incompletely understood.…”

Section: Introductionmentioning

confidence: 99%

Effect of altering local protein fluctuations using artificial intelligence

Nishiyama

2017

AIP Advances

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The fluctuations in Arg111, a significantly fluctuating residue in cathepsin K, were locally regulated by modifying Arg111 to Gly111. The binding properties of 15 dipeptides in the modified protein were analyzed by molecular simulations, and modeled as decision trees using artificial intelligence. The decision tree of the modified protein significantly differed from that of unmodified cathepsin K, and the Arg-to-Gly modification exerted a remarkable effect on the peptide binding properties. By locally regulating the fluctuations of a protein, we may greatly alter the original functions of the protein, enabling novel applications in several fields.

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A practical approach to docking of zinc metalloproteinase inhibitors

Cited by 94 publications

References 65 publications

Identification and Biochemical Characterization of Small-Molecule Inhibitors of Clostridium botulinum Neurotoxin Serotype A

Identification and Biochemical Characterization of Small-Molecule Inhibitors of Clostridium botulinum Neurotoxin Serotype A

Virtual Screening against Metalloenzymes for Inhibitors and Substrates

Effect of altering local protein fluctuations using artificial intelligence

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