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Peptide deformylase (PDF) is a class of metalloenzyme responsible for catalyzing the removal of the N-formyl group from N-terminal methionine following translation. PDF inhibitors are moving into new phase of drug development. Initially, PDF was considered as an important target in antibacterial drug discovery; however genome database searches have revealed PDF-like sequences in parasites (P. falciparum) and human, widening the utility of this target in antimalarial and anticancer drug discovery along with antibacterial. Using structural and mechanistic information together with high throughput screening, several types of chemical classes of PDF inhibitors with improved efficacy and specificity have been identified. Various drugs like, GSK-1322322 (Phase II), BB-83698 (Phase I), and LBM-415 (Phase I) have entered into clinical developments. Developments in the field have prompted us to review the current aspects of PDFs, especially their structures, different classes of PDF inhibitors, and molecular modeling studies. In nut shell, this review enlightens PDF as a versatile target along with its inhibitors and future perspectives of different PDF inhibitors.

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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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