The receptor-dependent LQTA-QSAR: application to a set of trypanothione reductase inhibitors
A new Receptor - Dependent LQTA - QSAR approach, RD - LQTA - QSAR , is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for e...
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Veröffentlicht in: | Journal of computer-aided molecular design 2012-09, Vol.26 (9), p.1055-1065 |
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creator | Barbosa, Euzébio G. Pasqualoto, Kerly Fernanda M. Ferreira, Márcia M. C. |
description | A new Receptor
-
Dependent LQTA
-
QSAR
approach,
RD
-
LQTA
-
QSAR
, is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for each compound. Such an ensemble is used to build molecular interaction field-based QSAR models, as in CoMFA. To show the potential of this methodology, a set of 38 phenothiazine derivatives that are specific competitive
T. cruzi
trypanothione reductase inhibitors, was chosen. Using a combination of molecular docking and molecular dynamics simulations, the binding mode of the phenotiazine derivatives was evaluated in a simulated induced fit approach. The ligands alignments were performed using both ligand and binding site atoms, enabling unbiased alignment. The models obtained were extensively validated by leave-
N
-out cross-validation and
y
-randomization techniques to test for their robustness and absence of chance correlation. The final model presented
Q
2
LOO of 0.87 and
R
² of 0.92 and a suitable external prediction of
= 0.78. The adapted binding site obtained is useful to perform virtual screening and ligand structure-based design and the descriptors in the final model can aid in the design new inhibitors. |
doi_str_mv | 10.1007/s10822-012-9598-2 |
format | Article |
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-
Dependent LQTA
-
QSAR
approach,
RD
-
LQTA
-
QSAR
, is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for each compound. Such an ensemble is used to build molecular interaction field-based QSAR models, as in CoMFA. To show the potential of this methodology, a set of 38 phenothiazine derivatives that are specific competitive
T. cruzi
trypanothione reductase inhibitors, was chosen. Using a combination of molecular docking and molecular dynamics simulations, the binding mode of the phenotiazine derivatives was evaluated in a simulated induced fit approach. The ligands alignments were performed using both ligand and binding site atoms, enabling unbiased alignment. The models obtained were extensively validated by leave-
N
-out cross-validation and
y
-randomization techniques to test for their robustness and absence of chance correlation. The final model presented
Q
2
LOO of 0.87 and
R
² of 0.92 and a suitable external prediction of
= 0.78. The adapted binding site obtained is useful to perform virtual screening and ligand structure-based design and the descriptors in the final model can aid in the design new inhibitors.</description><identifier>ISSN: 0920-654X</identifier><identifier>EISSN: 1573-4951</identifier><identifier>DOI: 10.1007/s10822-012-9598-2</identifier><identifier>PMID: 22972559</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Animal Anatomy ; Binding Sites ; Chemical compounds ; Chemistry ; Chemistry and Materials Science ; Computer Applications in Chemistry ; Computer simulation ; Derivatives ; Enzyme Inhibitors - pharmacology ; Enzymes ; Histology ; Inhibitor drugs ; Inhibitors ; Ligands ; Mathematical models ; Models, Molecular ; Molecular dynamics ; Molecular Dynamics Simulation ; Molecular structure ; Morphology ; NADH, NADPH Oxidoreductases - antagonists & inhibitors ; Physical Chemistry ; Quantitative Structure-Activity Relationship ; Receptors, Cell Surface - drug effects ; Reductases</subject><ispartof>Journal of computer-aided molecular design, 2012-09, Vol.26 (9), p.1055-1065</ispartof><rights>Springer Science+Business Media B.V. 2012</rights><rights>Springer Science+Business Media Dordrecht 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-82c7a9e4877ee92e63e7334fa0746324c1584c6a127601e2da3794c4622b39b3</citedby><cites>FETCH-LOGICAL-c438t-82c7a9e4877ee92e63e7334fa0746324c1584c6a127601e2da3794c4622b39b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10822-012-9598-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10822-012-9598-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22972559$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Barbosa, Euzébio G.</creatorcontrib><creatorcontrib>Pasqualoto, Kerly Fernanda M.</creatorcontrib><creatorcontrib>Ferreira, Márcia M. C.</creatorcontrib><title>The receptor-dependent LQTA-QSAR: application to a set of trypanothione reductase inhibitors</title><title>Journal of computer-aided molecular design</title><addtitle>J Comput Aided Mol Des</addtitle><addtitle>J Comput Aided Mol Des</addtitle><description>A new Receptor
-
Dependent LQTA
-
QSAR
approach,
RD
-
LQTA
-
QSAR
, is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for each compound. Such an ensemble is used to build molecular interaction field-based QSAR models, as in CoMFA. To show the potential of this methodology, a set of 38 phenothiazine derivatives that are specific competitive
T. cruzi
trypanothione reductase inhibitors, was chosen. Using a combination of molecular docking and molecular dynamics simulations, the binding mode of the phenotiazine derivatives was evaluated in a simulated induced fit approach. The ligands alignments were performed using both ligand and binding site atoms, enabling unbiased alignment. The models obtained were extensively validated by leave-
N
-out cross-validation and
y
-randomization techniques to test for their robustness and absence of chance correlation. The final model presented
Q
2
LOO of 0.87 and
R
² of 0.92 and a suitable external prediction of
= 0.78. The adapted binding site obtained is useful to perform virtual screening and ligand structure-based design and the descriptors in the final model can aid in the design new inhibitors.</description><subject>Animal Anatomy</subject><subject>Binding Sites</subject><subject>Chemical compounds</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Computer Applications in Chemistry</subject><subject>Computer simulation</subject><subject>Derivatives</subject><subject>Enzyme Inhibitors - pharmacology</subject><subject>Enzymes</subject><subject>Histology</subject><subject>Inhibitor drugs</subject><subject>Inhibitors</subject><subject>Ligands</subject><subject>Mathematical models</subject><subject>Models, Molecular</subject><subject>Molecular dynamics</subject><subject>Molecular Dynamics Simulation</subject><subject>Molecular structure</subject><subject>Morphology</subject><subject>NADH, NADPH Oxidoreductases - antagonists & inhibitors</subject><subject>Physical Chemistry</subject><subject>Quantitative Structure-Activity Relationship</subject><subject>Receptors, Cell Surface - drug effects</subject><subject>Reductases</subject><issn>0920-654X</issn><issn>1573-4951</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkcFqGzEQhkVpaNykD9BLEfTSixpppJVWvZnQNAFDSOJDDwUha8f1Bnu1lbSHvH3kOC2lUHLSYb7_GzQ_Ie8F_yw4N2dZ8BaAcQHMNrZl8IrMRGMkU7YRr8mMW-BMN-r7MXmb8z2vGav5G3IMYA00jZ2RH8sN0oQBxxIT63DEocOh0MXNcs5u7ua3X6gfx20ffOnjQEuknmYsNK5pSQ-jH2LZ1MHe0U2h-Iy0Hzb9qq-6fEqO1n6b8d3ze0KWF1-X55dscf3t6ny-YEHJtrAWgvEWVWsMogXUEo2Uau25UVqCCqJpVdBegNFcIHReGquC0gAraVfyhHw6aMcUf02Yi9v1OeB26weMU3ZCG6GMVFq_jAohbcsbxSv68R_0Pk5pqP_YU1DPCk-UOFAhxZwTrt2Y-p1PD05wty_JHUpytSS3L8lBzXx4Nk-rHXZ_Er9bqQAcgFxHw09Mf63-r_UR7syaSQ</recordid><startdate>20120901</startdate><enddate>20120901</enddate><creator>Barbosa, Euzébio G.</creator><creator>Pasqualoto, Kerly Fernanda M.</creator><creator>Ferreira, Márcia M. 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C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-82c7a9e4877ee92e63e7334fa0746324c1584c6a127601e2da3794c4622b39b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Animal Anatomy</topic><topic>Binding Sites</topic><topic>Chemical compounds</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Computer Applications in Chemistry</topic><topic>Computer simulation</topic><topic>Derivatives</topic><topic>Enzyme Inhibitors - pharmacology</topic><topic>Enzymes</topic><topic>Histology</topic><topic>Inhibitor drugs</topic><topic>Inhibitors</topic><topic>Ligands</topic><topic>Mathematical models</topic><topic>Models, Molecular</topic><topic>Molecular dynamics</topic><topic>Molecular Dynamics Simulation</topic><topic>Molecular structure</topic><topic>Morphology</topic><topic>NADH, NADPH Oxidoreductases - antagonists & inhibitors</topic><topic>Physical Chemistry</topic><topic>Quantitative Structure-Activity Relationship</topic><topic>Receptors, Cell Surface - drug effects</topic><topic>Reductases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Barbosa, Euzébio G.</creatorcontrib><creatorcontrib>Pasqualoto, Kerly Fernanda M.</creatorcontrib><creatorcontrib>Ferreira, Márcia M. 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C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The receptor-dependent LQTA-QSAR: application to a set of trypanothione reductase inhibitors</atitle><jtitle>Journal of computer-aided molecular design</jtitle><stitle>J Comput Aided Mol Des</stitle><addtitle>J Comput Aided Mol Des</addtitle><date>2012-09-01</date><risdate>2012</risdate><volume>26</volume><issue>9</issue><spage>1055</spage><epage>1065</epage><pages>1055-1065</pages><issn>0920-654X</issn><eissn>1573-4951</eissn><abstract>A new Receptor
-
Dependent LQTA
-
QSAR
approach,
RD
-
LQTA
-
QSAR
, is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for each compound. Such an ensemble is used to build molecular interaction field-based QSAR models, as in CoMFA. To show the potential of this methodology, a set of 38 phenothiazine derivatives that are specific competitive
T. cruzi
trypanothione reductase inhibitors, was chosen. Using a combination of molecular docking and molecular dynamics simulations, the binding mode of the phenotiazine derivatives was evaluated in a simulated induced fit approach. The ligands alignments were performed using both ligand and binding site atoms, enabling unbiased alignment. The models obtained were extensively validated by leave-
N
-out cross-validation and
y
-randomization techniques to test for their robustness and absence of chance correlation. The final model presented
Q
2
LOO of 0.87 and
R
² of 0.92 and a suitable external prediction of
= 0.78. The adapted binding site obtained is useful to perform virtual screening and ligand structure-based design and the descriptors in the final model can aid in the design new inhibitors.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>22972559</pmid><doi>10.1007/s10822-012-9598-2</doi><tpages>11</tpages></addata></record> |
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source | MEDLINE; SpringerLink Journals |
subjects | Animal Anatomy Binding Sites Chemical compounds Chemistry Chemistry and Materials Science Computer Applications in Chemistry Computer simulation Derivatives Enzyme Inhibitors - pharmacology Enzymes Histology Inhibitor drugs Inhibitors Ligands Mathematical models Models, Molecular Molecular dynamics Molecular Dynamics Simulation Molecular structure Morphology NADH, NADPH Oxidoreductases - antagonists & inhibitors Physical Chemistry Quantitative Structure-Activity Relationship Receptors, Cell Surface - drug effects Reductases |
title | The receptor-dependent LQTA-QSAR: application to a set of trypanothione reductase inhibitors |
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