Ring-modified analogues and molecular dynamics studies to probe the requirements for fungicidal activities of malayamycin A and its N-nucleoside variants

Journal of Organic Chemistry

Volumn 72, Issue 17, 2007, Pages 6353-6363

  Loiseleur, Olivier ^a   Ritson, Dougal ^c   Nina, Mafalda ^a   Crowley, Patrick ^b   Wagner, Trixie ^d   Hanessian, Stephen ^c  

^a JEALOTT S HILL RESEARCH STATION   (United Kingdom)

^b JEALOTT S HILL INTERNATIONAL RESEARCH CENTRE   (United Kingdom)

^c UNIVERSITÉ DE MONTRÉAL   (Canada)

^d NOVARTIS PHARMA AG   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

FUNGICIDAL ACTIVITIES; PERHYDROFURAN CORES; RING MODIFIED ANALOGUES;

FUNGICIDES; PROTEINS; SYNTHESIS (CHEMICAL);

MOLECULAR DYNAMICS;

1 CYTOSINYLMALAYAMYCIN A; 9 ADENYLMALAYAMYCIN A; BICYCLO COMPOUND; DIMETHYL ETHER; EZOMYCIN A2; EZOMYCIN B1; FURAN DERIVATIVE; MALAYAMYCIN A; NORMALAYAMYCIN A; NUCLEOSIDE DERIVATIVE; UNCLASSIFIED DRUG; UREA;

ARTICLE; DRUG CONFORMATION; DRUG STRUCTURE; DRUG SYNTHESIS; FUNGICIDAL ACTIVITY; MOLECULAR DYNAMICS; NONHUMAN; STEREOCHEMISTRY;

BICYCLO COMPOUNDS, HETEROCYCLIC; CATALYSIS; FUNGICIDES, INDUSTRIAL; MAGNETIC RESONANCE SPECTROSCOPY; MODELS, MOLECULAR; MOLECULAR PROBES; NUCLEOSIDES; SPECTROMETRY, MASS, ELECTROSPRAY IONIZATION;

EID: 34547948213     PISSN: 00223263     EISSN: None     Source Type: Journal    
DOI: 10.1021/jo070520d     Document Type: Article

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46. Molecular dynamics simulations in explicit water were performed on 1-cytosinyl-N-malayamycin A (7) and congeners 42 and 43 with the molecular mechanics CHARMm software and CHARMM22 force field (Accelrys). The MD simulation used the continuum reaction field treatment of long-range SSBP module (Beglov; Roux J. Chem. Phys. 1994, 100, 9050) as implemented in the CHARMm module from InsightII (Accelrys). Force field parameters for the ligands consistent with the CHARMM22 force field were produced with the software WitNotP (Novartis Pharma). Three independent MD simulations were performed with the crystal structure of 1-cytosinyl-N-malayamycin A (7), and global minimum optimized geometries HF/3-21G* for 42 and 43 as starting conformations. A spherical region of 14 Å radius was simulated in atomic detail, including the inhibitor and 350 TIP3 water molecules for a total of 1101 atoms. This sphere size ensured that the solute has a solvation shell of explicit water at least 8 Å thick in all directions. The solvent outside this sphere was treated as a dielectric continuum with a dielectric constant of 80. The inner region has a dielectric of 1. Atomic partial charges in the inner region polarize the outer continuum, giving rise to a reaction field on each explicit atom, which is approximated here by a spherical harmonic expansion of order 15. Within the spherical region, electrostatic interactions were treated without any truncation by using a multipole approximation.
47. Each simulation was run for 20 ns and trajectories were analyzed with an in-house clustering method derived from a previous work (Hamprecht, F. A.; Peter, C.; Daura, X.; Thiel, W.; van Gunsteren, W. F. J. Chem. Phys. 2001, 114, 2079). For each simulation, 10 000 structures were extracted from the last 10 ns of the trajectory at 1 ps intervals for analysis. The clustering was performed in Cartesian space. For each structure, a least-square translational and rotational fit was performed with the heavy atoms of residues 4-11 and the atom positional root-mean-square difference (RMSd) for this set of atoms was calculated. Terminal residues were not taken into account, as they tend to have more freedom of motion. The number of structures satisfying the similarity criterion set to RMSd ≤1 Å for the heavy atoms was determined in the pool of 10 000 structures. The structure with the highest number of neighbors (i.e. structures satisfying the similarity criterion) was taken as the central member of the first cluster. All structures belonging to the first cluster were removed from the pool. The number of neighbors was computed again with the remaining structures. The structure with the highest number of neighbors becomes the central member of the second cluster. The process is iterated until all structures were assigned to a cluster.