Loading…

Computational analysis of quinoline derivatives as potent topoisomerase-II inhibitors

Quantitative structure–activity relationship (QSAR) is an attempt to correlate structural or property descriptors of compounds quantitatively with biological activities. QSARs currently are being applied in many disciplines, with many pertaining to drug design and environmental risk assessment. The...

Full description

Saved in:
Bibliographic Details
Published in:Medicinal chemistry research 2015, Vol.24 (1), p.383-393
Main Authors: Vaidya, Ankur, Jain, Shweta, Jain, Abkishek K., Prashanthakumar, B. R., Kashaw, Sushil K., Agrawal, Ram K.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c288t-f1b78810495891b9cf8a9217f2c3d00cd4fdda79c8e5fcef3ca1e4abeb26ac2c3
cites cdi_FETCH-LOGICAL-c288t-f1b78810495891b9cf8a9217f2c3d00cd4fdda79c8e5fcef3ca1e4abeb26ac2c3
container_end_page 393
container_issue 1
container_start_page 383
container_title Medicinal chemistry research
container_volume 24
creator Vaidya, Ankur
Jain, Shweta
Jain, Abkishek K.
Prashanthakumar, B. R.
Kashaw, Sushil K.
Agrawal, Ram K.
description Quantitative structure–activity relationship (QSAR) is an attempt to correlate structural or property descriptors of compounds quantitatively with biological activities. QSARs currently are being applied in many disciplines, with many pertaining to drug design and environmental risk assessment. The 3D QSARs between the structures of 29 quinoline compounds and their topoisomerase-II inhibitor activity have been developed using the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and stepwise k nearest neighbor molecular field analysis [(SW) kNN MFA] method, and 3D QSAR models with the considerable prediction ability are obtained. The CoMFA, CoMSIA, and [(SW) kNN MFA] studies resulted in reliable and significant computational models. These models are more significant guide to trace the important chemical features with respect to the design of new potent compounds. The information obtained from the CoMFA, CoMSIA, and [(SW) kNN MFA] contour maps can be utilized for the design and development of new, more potent topoisomerase-II inhibitor.
doi_str_mv 10.1007/s00044-014-1131-9
format article
fullrecord <record><control><sourceid>crossref_sprin</sourceid><recordid>TN_cdi_crossref_primary_10_1007_s00044_014_1131_9</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_1007_s00044_014_1131_9</sourcerecordid><originalsourceid>FETCH-LOGICAL-c288t-f1b78810495891b9cf8a9217f2c3d00cd4fdda79c8e5fcef3ca1e4abeb26ac2c3</originalsourceid><addsrcrecordid>eNp9kMtOwzAQRS0EEqXwAez8A4YZxyHOElU8KlViQ9eW49jgqo2DJ63Uv8dVWbOZuYtzR5rD2D3CAwI0jwQASglAJRArFO0Fm2FdK6FRwmXJULKsZXXNbog2AFUDqp6x9SLtxv1kp5gGu-W2jCNF4inwn30c0jYOnvc-x0NBDp64JT6myQ8Tn9KYIqWdz5a8WC55HL5jF6eU6ZZdBbslf_e352z9-vK5eBerj7fl4nklnNR6EgG7RmsE1da6xa51QdtWYhOkq3oA16vQ97ZpnfZ1cD5UzqJXtvOdfLKuQHOG57suJ6Lsgxlz3Nl8NAjm5MWcvZjixZy8mLZ05LlDhR2-fDabtM_lb_qn9AvV12jJ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Computational analysis of quinoline derivatives as potent topoisomerase-II inhibitors</title><source>Springer Nature</source><creator>Vaidya, Ankur ; Jain, Shweta ; Jain, Abkishek K. ; Prashanthakumar, B. R. ; Kashaw, Sushil K. ; Agrawal, Ram K.</creator><creatorcontrib>Vaidya, Ankur ; Jain, Shweta ; Jain, Abkishek K. ; Prashanthakumar, B. R. ; Kashaw, Sushil K. ; Agrawal, Ram K.</creatorcontrib><description>Quantitative structure–activity relationship (QSAR) is an attempt to correlate structural or property descriptors of compounds quantitatively with biological activities. QSARs currently are being applied in many disciplines, with many pertaining to drug design and environmental risk assessment. The 3D QSARs between the structures of 29 quinoline compounds and their topoisomerase-II inhibitor activity have been developed using the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and stepwise k nearest neighbor molecular field analysis [(SW) kNN MFA] method, and 3D QSAR models with the considerable prediction ability are obtained. The CoMFA, CoMSIA, and [(SW) kNN MFA] studies resulted in reliable and significant computational models. These models are more significant guide to trace the important chemical features with respect to the design of new potent compounds. The information obtained from the CoMFA, CoMSIA, and [(SW) kNN MFA] contour maps can be utilized for the design and development of new, more potent topoisomerase-II inhibitor.</description><identifier>ISSN: 1054-2523</identifier><identifier>EISSN: 1554-8120</identifier><identifier>DOI: 10.1007/s00044-014-1131-9</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Biochemistry ; Biomedical and Life Sciences ; Biomedicine ; Cell Biology ; Original Research ; Pharmacology/Toxicology</subject><ispartof>Medicinal chemistry research, 2015, Vol.24 (1), p.383-393</ispartof><rights>Springer Science+Business Media New York 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c288t-f1b78810495891b9cf8a9217f2c3d00cd4fdda79c8e5fcef3ca1e4abeb26ac2c3</citedby><cites>FETCH-LOGICAL-c288t-f1b78810495891b9cf8a9217f2c3d00cd4fdda79c8e5fcef3ca1e4abeb26ac2c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Vaidya, Ankur</creatorcontrib><creatorcontrib>Jain, Shweta</creatorcontrib><creatorcontrib>Jain, Abkishek K.</creatorcontrib><creatorcontrib>Prashanthakumar, B. R.</creatorcontrib><creatorcontrib>Kashaw, Sushil K.</creatorcontrib><creatorcontrib>Agrawal, Ram K.</creatorcontrib><title>Computational analysis of quinoline derivatives as potent topoisomerase-II inhibitors</title><title>Medicinal chemistry research</title><addtitle>Med Chem Res</addtitle><description>Quantitative structure–activity relationship (QSAR) is an attempt to correlate structural or property descriptors of compounds quantitatively with biological activities. QSARs currently are being applied in many disciplines, with many pertaining to drug design and environmental risk assessment. The 3D QSARs between the structures of 29 quinoline compounds and their topoisomerase-II inhibitor activity have been developed using the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and stepwise k nearest neighbor molecular field analysis [(SW) kNN MFA] method, and 3D QSAR models with the considerable prediction ability are obtained. The CoMFA, CoMSIA, and [(SW) kNN MFA] studies resulted in reliable and significant computational models. These models are more significant guide to trace the important chemical features with respect to the design of new potent compounds. The information obtained from the CoMFA, CoMSIA, and [(SW) kNN MFA] contour maps can be utilized for the design and development of new, more potent topoisomerase-II inhibitor.</description><subject>Biochemistry</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Cell Biology</subject><subject>Original Research</subject><subject>Pharmacology/Toxicology</subject><issn>1054-2523</issn><issn>1554-8120</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNp9kMtOwzAQRS0EEqXwAez8A4YZxyHOElU8KlViQ9eW49jgqo2DJ63Uv8dVWbOZuYtzR5rD2D3CAwI0jwQASglAJRArFO0Fm2FdK6FRwmXJULKsZXXNbog2AFUDqp6x9SLtxv1kp5gGu-W2jCNF4inwn30c0jYOnvc-x0NBDp64JT6myQ8Tn9KYIqWdz5a8WC55HL5jF6eU6ZZdBbslf_e352z9-vK5eBerj7fl4nklnNR6EgG7RmsE1da6xa51QdtWYhOkq3oA16vQ97ZpnfZ1cD5UzqJXtvOdfLKuQHOG57suJ6Lsgxlz3Nl8NAjm5MWcvZjixZy8mLZ05LlDhR2-fDabtM_lb_qn9AvV12jJ</recordid><startdate>2015</startdate><enddate>2015</enddate><creator>Vaidya, Ankur</creator><creator>Jain, Shweta</creator><creator>Jain, Abkishek K.</creator><creator>Prashanthakumar, B. R.</creator><creator>Kashaw, Sushil K.</creator><creator>Agrawal, Ram K.</creator><general>Springer US</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>2015</creationdate><title>Computational analysis of quinoline derivatives as potent topoisomerase-II inhibitors</title><author>Vaidya, Ankur ; Jain, Shweta ; Jain, Abkishek K. ; Prashanthakumar, B. R. ; Kashaw, Sushil K. ; Agrawal, Ram K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c288t-f1b78810495891b9cf8a9217f2c3d00cd4fdda79c8e5fcef3ca1e4abeb26ac2c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Biochemistry</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Cell Biology</topic><topic>Original Research</topic><topic>Pharmacology/Toxicology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vaidya, Ankur</creatorcontrib><creatorcontrib>Jain, Shweta</creatorcontrib><creatorcontrib>Jain, Abkishek K.</creatorcontrib><creatorcontrib>Prashanthakumar, B. R.</creatorcontrib><creatorcontrib>Kashaw, Sushil K.</creatorcontrib><creatorcontrib>Agrawal, Ram K.</creatorcontrib><collection>CrossRef</collection><jtitle>Medicinal chemistry research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vaidya, Ankur</au><au>Jain, Shweta</au><au>Jain, Abkishek K.</au><au>Prashanthakumar, B. R.</au><au>Kashaw, Sushil K.</au><au>Agrawal, Ram K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computational analysis of quinoline derivatives as potent topoisomerase-II inhibitors</atitle><jtitle>Medicinal chemistry research</jtitle><stitle>Med Chem Res</stitle><date>2015</date><risdate>2015</risdate><volume>24</volume><issue>1</issue><spage>383</spage><epage>393</epage><pages>383-393</pages><issn>1054-2523</issn><eissn>1554-8120</eissn><abstract>Quantitative structure–activity relationship (QSAR) is an attempt to correlate structural or property descriptors of compounds quantitatively with biological activities. QSARs currently are being applied in many disciplines, with many pertaining to drug design and environmental risk assessment. The 3D QSARs between the structures of 29 quinoline compounds and their topoisomerase-II inhibitor activity have been developed using the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and stepwise k nearest neighbor molecular field analysis [(SW) kNN MFA] method, and 3D QSAR models with the considerable prediction ability are obtained. The CoMFA, CoMSIA, and [(SW) kNN MFA] studies resulted in reliable and significant computational models. These models are more significant guide to trace the important chemical features with respect to the design of new potent compounds. The information obtained from the CoMFA, CoMSIA, and [(SW) kNN MFA] contour maps can be utilized for the design and development of new, more potent topoisomerase-II inhibitor.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s00044-014-1131-9</doi><tpages>11</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1054-2523
ispartof Medicinal chemistry research, 2015, Vol.24 (1), p.383-393
issn 1054-2523
1554-8120
language eng
recordid cdi_crossref_primary_10_1007_s00044_014_1131_9
source Springer Nature
subjects Biochemistry
Biomedical and Life Sciences
Biomedicine
Cell Biology
Original Research
Pharmacology/Toxicology
title Computational analysis of quinoline derivatives as potent topoisomerase-II inhibitors
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T20%3A18%3A58IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Computational%20analysis%20of%20quinoline%20derivatives%20as%20potent%20topoisomerase-II%20inhibitors&rft.jtitle=Medicinal%20chemistry%20research&rft.au=Vaidya,%20Ankur&rft.date=2015&rft.volume=24&rft.issue=1&rft.spage=383&rft.epage=393&rft.pages=383-393&rft.issn=1054-2523&rft.eissn=1554-8120&rft_id=info:doi/10.1007/s00044-014-1131-9&rft_dat=%3Ccrossref_sprin%3E10_1007_s00044_014_1131_9%3C/crossref_sprin%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c288t-f1b78810495891b9cf8a9217f2c3d00cd4fdda79c8e5fcef3ca1e4abeb26ac2c3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true