A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis

Afantitis, Antreas; Melagraki, G.; Sarimveis, H.; Koutentis, Panayiotis Andreas; Markopoulos, J.; Igglessi-Markopoulou, O.

doi:10.1007/s11030-005-9012-2

dc.contributor.author	Afantitis, Antreas	en
dc.contributor.author	Melagraki, G.	en
dc.contributor.author	Sarimveis, H.	en
dc.contributor.author	Koutentis, Panayiotis Andreas	en
dc.contributor.author	Markopoulos, J.	en
dc.contributor.author	Igglessi-Markopoulou, O.	en
dc.creator	Afantitis, Antreas	en
dc.creator	Melagraki, G.	en
dc.creator	Sarimveis, H.	en
dc.creator	Koutentis, Panayiotis Andreas	en
dc.creator	Markopoulos, J.	en
dc.creator	Igglessi-Markopoulou, O.	en
dc.date.accessioned	2019-11-21T06:16:15Z
dc.date.available	2019-11-21T06:16:15Z
dc.date.issued	2006
dc.identifier.issn	1381-1991
dc.identifier.uri	http://gnosis.library.ucy.ac.cy/handle/7/55233
dc.description.abstract	A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl] -6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (RCV 2 = 0.8160	en
dc.description.abstract	SPRESS = 0.5680) proved to be very accurate both in training and predictive stages. © Springer 2006.	en
dc.source	Molecular diversity	en
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-33846475687&doi=10.1007%2fs11030-005-9012-2&partnerID=40&md5=a499fe21b07add4702b0374d4f1d12a4
dc.subject	article	en
dc.subject	mathematical model	en
dc.subject	Humans	en
dc.subject	prediction	en
dc.subject	priority journal	en
dc.subject	unclassified drug	en
dc.subject	Human immunodeficiency virus	en
dc.subject	Anti-HIV Agents	en
dc.subject	Linear Models	en
dc.subject	HIV-1	en
dc.subject	Reverse Transcriptase Inhibitors	en
dc.subject	antiviral activity	en
dc.subject	accuracy	en
dc.subject	Neural Networks (Computer)	en
dc.subject	QSAR	en
dc.subject	quantitative structure activity relation	en
dc.subject	Quantitative Structure-Activity Relationship	en
dc.subject	drug structure	en
dc.subject	multiple linear regression analysis	en
dc.subject	1 [(2 hydroxyethoxy)methyl] 6 (phenylthio)thymine	en
dc.subject	1 [(2 hydroxyethoxy)methyl] 6 (phenylthio)thymine derivative	en
dc.subject	Anti-HIV	en
dc.subject	HEPT derivatives	en
dc.subject	HIV-1 Reverse Transcriptase	en
dc.subject	MLR	en
dc.subject	step wise multiple regression	en
dc.subject	Stepwise regression	en
dc.subject	Thymine	en
dc.title	A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis	en
dc.type	info:eu-repo/semantics/article
dc.identifier.doi	10.1007/s11030-005-9012-2
dc.description.volume	10
dc.description.issue	3
dc.description.startingpage	405
dc.description.endingpage	414
dc.author.faculty	002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.department	Τμήμα Χημείας / Department of Chemistry
dc.type.uhtype	Article	en
dc.description.notes	<p>Cited By :48</p>	en
dc.source.abbreviation	Mol.Diversity	en
dc.contributor.orcid	Koutentis, Panayiotis Andreas [0000-0002-4652-7567]
dc.contributor.orcid	Afantitis, Antreas [0000-0002-0977-8180]
dc.contributor.orcid	Igglessi-Markopoulou, O. [0000-0002-7683-8526]
dc.gnosis.orcid	0000-0002-4652-7567
dc.gnosis.orcid	0000-0002-0977-8180\|0000-0002-7683-8526

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