Abstract
The quantitative structure activity relationship (QSAR) study is the most cited and reliable computational technique used for decades to obtain information about a substituent’s physicochemical property and biological activity. There is step-by-step development in the concept of QSAR from 0D to 2D. These models suffer various limitations that led to the development of 3D-QSAR. There are large numbers of literatures available on the utility of 3D-QSAR for drug design. Three-dimensional properties of molecules with non-covalent interactions are served as important tool in the selection of bioactive confirmation of compounds. With this view, 3D-QSAR has been explored with different advancements like COMFA, COMSA, COMMA, etc. Some reports are also available highlighting the limitations of 3D-QSAR. In a way, to overcome the limitations of 3D-QSAR, more advanced QSAR approaches like 4D, 5D and 6D-QSAR have been evolved. Here, in this present review we have focused more on the present and future of more predictive models of QSAR studies. The review highlights the basics of 3D to 6D-QSAR and mainly emphasizes the advantages of one dimension over the other. It covers almost all recent reports of all these multidimensional QSAR approaches which are new paradigms in drug discovery.
Keywords: Biological activity, Molecular descriptors, Multidimensional QSAR, Physicochemical property, QSAR.
Mini-Reviews in Medicinal Chemistry
Title:Recent Advances in Multidimensional QSAR (4D-6D): A Critical Review
Volume: 14 Issue: 1
Author(s): Manoj G. Damale, Sanjay N. Harke, Firoz A. Kalam Khan, Devanand B. Shinde and Jaiprakash N. Sangshetti
Affiliation:
Keywords: Biological activity, Molecular descriptors, Multidimensional QSAR, Physicochemical property, QSAR.
Abstract: The quantitative structure activity relationship (QSAR) study is the most cited and reliable computational technique used for decades to obtain information about a substituent’s physicochemical property and biological activity. There is step-by-step development in the concept of QSAR from 0D to 2D. These models suffer various limitations that led to the development of 3D-QSAR. There are large numbers of literatures available on the utility of 3D-QSAR for drug design. Three-dimensional properties of molecules with non-covalent interactions are served as important tool in the selection of bioactive confirmation of compounds. With this view, 3D-QSAR has been explored with different advancements like COMFA, COMSA, COMMA, etc. Some reports are also available highlighting the limitations of 3D-QSAR. In a way, to overcome the limitations of 3D-QSAR, more advanced QSAR approaches like 4D, 5D and 6D-QSAR have been evolved. Here, in this present review we have focused more on the present and future of more predictive models of QSAR studies. The review highlights the basics of 3D to 6D-QSAR and mainly emphasizes the advantages of one dimension over the other. It covers almost all recent reports of all these multidimensional QSAR approaches which are new paradigms in drug discovery.
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Cite this article as:
Damale G. Manoj, Harke N. Sanjay, Kalam Khan A. Firoz, Shinde B. Devanand and Sangshetti N. Jaiprakash, Recent Advances in Multidimensional QSAR (4D-6D): A Critical Review, Mini-Reviews in Medicinal Chemistry 2014; 14 (1) . https://dx.doi.org/10.2174/13895575113136660104
DOI https://dx.doi.org/10.2174/13895575113136660104 |
Print ISSN 1389-5575 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5607 |
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