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<pubDate>Thu, 21 Aug 2008 15:27:46 BST</pubDate>


	<title>CiteULike: msuarezdiez Brooks</title>
	<description>CiteULike: msuarezdiez Brooks</description>


	<link>http://www.citeulike.org/user/msuarezdiez/author/Brooks</link>
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        <rdf:li rdf:resource="http://www.citeulike.org/user/msuarezdiez/article/695363"/>
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<item rdf:about="http://www.citeulike.org/user/msuarezdiez/article/695363">
    <title>Detailed analysis of grid-based molecular docking: A case study of CDOCKER - A CHARMm-based MD docking algorithm</title>
    <link>http://www.citeulike.org/user/msuarezdiez/article/695363</link>
    <description>&lt;i&gt;Journal of Computational Chemistry, Vol. 24, No. 13. (2003), pp. 1549-1562.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The influence of various factors on the accuracy of protein-ligand docking is examined. The factors investigated include the role of a grid representation of protein-ligand interactions, the initial ligand conformation and orientation, the sampling rate of the energy hyper-surface, and the final minimization. A representative docking method is used to study these factors, namely, CDOCKER, a molecular dynamics (MD) simulated-annealing-based algorithm. A major emphasis in these studies is to compare the relative performance and accuracy of various grid-based approximations to explicit all-atom force field calculations. In these docking studies, the protein is kept rigid while the ligands are treated as fully flexible and a final minimization step is used to refine the docked poses. A docking success rate of 74% is observed when an explicit all-atom representation of the protein (full force field) is used, while a lower accuracy of 66-76% is observed for grid-based methods. All docking experiments considered a 41-member protein-ligand validation set. A significant improvement in accuracy (76 vs. 66%) for the grid-based docking is achieved if the explicit all-atom force field is used in a final minimization step to refine the docking poses. Statistical analysis shows that even lower-accuracy grid-based energy representations can be effectively used when followed with full force field minimization. The results of these grid-based protocols are statistically indistinguishable from the detailed atomic dockings and provide up to a sixfold reduction in computation time. For the test case examined here, improving the docking accuracy did not necessarily enhance the ability to estimate binding affinities using the docked structures. © 2003 Wiley Periodicals, Inc. J Comput Chem 13: 1549-1562, 2003</description>
    <dc:title>Detailed analysis of grid-based molecular docking: A case study of CDOCKER - A CHARMm-based MD docking algorithm</dc:title>

    <dc:creator>Guosheng Wu</dc:creator>
    <dc:creator>Daniel Robertson</dc:creator>
    <dc:creator>Charles Brooks</dc:creator>
    <dc:creator>Michal Vieth</dc:creator>
    <dc:identifier>doi:10.1002/jcc.10306</dc:identifier>
    <dc:source>Journal of Computational Chemistry, Vol. 24, No. 13. (2003), pp. 1549-1562.</dc:source>
    <dc:date>2006-06-14T00:11:40-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:publicationName>Journal of Computational Chemistry</prism:publicationName>
    <prism:volume>24</prism:volume>
    <prism:number>13</prism:number>
    <prism:startingPage>1549</prism:startingPage>
    <prism:endingPage>1562</prism:endingPage>
    <prism:category>charmm</prism:category>
    <prism:category>dynamics</prism:category>
    <prism:category>molecular</prism:category>
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<item rdf:about="http://www.citeulike.org/user/msuarezdiez/article/2239096">
    <title>Interfacing Q-Chem and CHARMM to perform QM/MM reaction path calculations</title>
    <link>http://www.citeulike.org/user/msuarezdiez/article/2239096</link>
    <description>&lt;i&gt;Journal of Computational Chemistry, Vol. 28, No. 9. (2007), pp. 1485-1502.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;A hybrid quantum mechanical/molecular mechanical (QM/MM) potential energy function with Hartree-Fock, density functional theory (DFT), and post-HF (RIMP2, MP2, CCSD) capability has been implemented in the CHARMM and Q-Chem software packages. In addition, we have modified CHARMM and Q-Chem to take advantage of the newly introduced replica path and the nudged elastic band methods, which are powerful techniques for studying reaction pathways in a highly parallel (i.e., parallel/parallel) fashion, with each pathway point being distributed to a different node of a large cluster. To test our implementation, a series of systems were studied and comparisons were made to both full QM calculations and previous QM/MM studies and experiments. For instance, the differences between HF, DFT, MP2, and CCSD QM/MM calculations of H2O···H2O, H2O···Na+, and H2O···Cl- complexes have been explored. Furthermore, the recently implemented polarizable Drude water model was used to make comparisons to the popular TIP3P and TIP4P water models for doing QM/MM calculations. We have also computed the energetic profile of the chorismate mutase catalyzed Claisen rearrangement at various QM/MM levels of theory and have compared the results with previous studies. Our best estimate for the activation energy is 8.20 kcal/mol and for the reaction energy is -23.1 kcal/mol, both calculated at the MP2/6-31+G(d)//MP2/6-31+G(d)/C22 level of theory. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007</description>
    <dc:title>Interfacing Q-Chem and CHARMM to perform QM/MM reaction path calculations</dc:title>

    <dc:creator>Lee Woodcock</dc:creator>
    <dc:creator>Milan Hodo?&#38;ccaron;ek</dc:creator>
    <dc:creator>Andrew Gilbert</dc:creator>
    <dc:creator>Peter Gill</dc:creator>
    <dc:creator>Henry Schaefer</dc:creator>
    <dc:creator>Bernard Brooks</dc:creator>
    <dc:identifier>doi:10.1002/jcc.20587</dc:identifier>
    <dc:source>Journal of Computational Chemistry, Vol. 28, No. 9. (2007), pp. 1485-1502.</dc:source>
    <dc:date>2008-01-16T12:42:26-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Journal of Computational Chemistry</prism:publicationName>
    <prism:volume>28</prism:volume>
    <prism:number>9</prism:number>
    <prism:startingPage>1485</prism:startingPage>
    <prism:endingPage>1502</prism:endingPage>
    <prism:category>charmm</prism:category>
    <prism:category>dynamics</prism:category>
    <prism:category>molecular</prism:category>
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