Chemical Science Transactions | Chem Sci Trans | CST | Online Chemistry Journal | Open Access
Home | Table of Contents | Submit an article | Subscribe | Login | Register

Indexing Metadata

QSAR Study of (5-Nitroheteroaryl-1,3,4-thiadiazole-2-yl)piperazinyl Derivatives to Predict New Similar Compounds as Antileishmanial Agents

DUBLINCOREMETADATA ITEM METADATA FOR THIS DOCUMENT
1TitleTitle of DocumentQSAR Study of (5-Nitroheteroaryl-1,3,4-thiadiazole-2-yl)piperazinyl Derivatives to Predict New Similar Compounds as Antileishmanial Agents
2CreatorAuthor's name, affiliation, country ABDELLAH OUSAA1*, BOUHYA ELIDRISSI1, MOUNIR GHAMALI1, SAMIR CHTITA1, ADNANE AOUIDATE1, MOHAMMED BOUACHRINE2 and TAHAR LAKHLIFI1
1Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, Moulay Ismail University, Meknes, Morocco
2MEM, ESTM, Moulay Ismail University, Meknes, Morocco
3SubjectDicipline(s) Chemical Science
3SubjectKeywords
4DescriptionAbstract To search of newer and potent antileishmanial drugs, a series of 36 compounds of 5-(5-nitroheteroaryl-2-yl)-1,3,4-thiadiazole derivatives were subjected to a quantitative structure-activity relationship (QSAR) analysis for studying, interpreting and predicting activities and designing new compounds using several statistical tools, The multiple linear regression (MLR), non-linear regression (RNLM) and artificial neural network (ANN) models were developed using 30 molecules having pIC50 ranging from 3.155 to 5.046. The best generated MLR, RNLM and ANN models show conventional correlation coefficients R of 0.750, 0.782 and 0.967 as well as their leave-one-out cross-validation correlation coefficients RCV of 0.722, 0.744 and 0.720, respectively. The predictive ability of those models was evaluated by the external validation using a test set of 6 molecules with predicted correlation coefficients Rtest of 0.840, 0.850 and 0.802, respectively. The applicability domains of MLR and MNLR transparent models were investigated using William?s plot to detect outliers and outsides compounds. We expect that this study would be of great help in lead optimization for early drug discovery of new similar compounds.
5PublishersOrganizing agency, location WWW Publications, India
6Contributor Sponsor(s) -
7DateDate (YYYY-MM-DD) -
8TypeStatus & genre Peer-reviewed Article
8TypeType
9FormateFile Formate PDF
10IdentifierUniform Resource Identifier Click Here
10IdentifierDigital Object Identifier
11SourceJournal/conference title; vol., no. (Year)Chemical Science Transactions, Volume  8 , Number  (1), (2019)
12LanuguageEnglish=en en
13RelationSupp.files
14Coverage -
15CopyrightCopyright and permissions
Chemical Science Transactions | Chem Sci Trans | CST | Online Chemistry Journal | Open Access
Home | Table of Contents | Submit an article | Subscribe | Login | Register