Abstract
The QSAR/QSPR technique is now a widely practiced tool in chemical research both in the industry and academia. Because of the enormous potential applications of predictive modeling analysis, various newer methods have recently been developed to improve the usefulness and applicability of QSAR techniques. Binary QSAR, hologram QSAR (HQSAR), group-based QSAR (G-QSAR), multivariate image analysis (MIA)-based QSAR (MIA-QSAR), etc., are some of the new approaches in the realm of QSAR formalisms. Furthermore, QSAR techniques are also employed in various newer research areas in addition to the conventional drug design and predictive toxicology paradigm. QSAR models have been observed to be fruitful in modeling various property endpoints in the field of material informatics. In addition to that, predictive modeling of properties and/or toxicities of nanoparticles (NPs), cosmetics, peptides, ionic liquids, phytochemicals, etc., also represents the emerging application areas of the QSAR technique. This present chapter gives an overview of both the new methods and new application areas of QSAR studies.
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Roy, K., Kar, S., Das, R.N. (2015). Newer Directions in QSAR/QSPR. In: A Primer on QSAR/QSPR Modeling. SpringerBriefs in Molecular Science. Springer, Cham. https://doi.org/10.1007/978-3-319-17281-1_4
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DOI: https://doi.org/10.1007/978-3-319-17281-1_4
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