Read e-book online A Primer on QSAR/QSPR Modeling: Fundamental Concepts PDF
By Kunal Roy
This short is going again to fundamentals and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that signify predictive types derived from the appliance of statistical instruments correlating organic task (including healing and poisonous) and homes of chemical compounds (drugs/toxicants/environmental pollution) with descriptors consultant of molecular constitution and/or houses. It explains how the sub-discipline of Cheminformatics is used for lots of purposes reminiscent of threat evaluation, toxicity prediction, estate prediction and regulatory judgements except drug discovery and lead optimization. The authors additionally current, in simple terms, how QSARs and similar chemometric instruments are widely taken with medicinal chemistry, environmental chemistry and agricultural chemistry for score of capability compounds and prioritizing experiments. at the present, there isn't any regular or introductory booklet to be had that introduces this crucial subject to scholars of chemistry and pharmacy. With this in brain, the authors have rigorously compiled this short so that it will offer a radical and painless creation to the elemental options of QSAR/QSPR modelling. The short is aimed toward beginner readers.
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Extra resources for A Primer on QSAR/QSPR Modeling: Fundamental Concepts
12 Schematic illustration to show how chemical structures are employed to compute descriptors and QSAR model development (frequency of occurrence of a substructure), topological, electronic (molecular orbital calculations), geometric (molecular surface area calculation), or simple indicator parameters (dummy variables). In a broader perspective, descriptors (speciﬁcally, physicochemical descriptors) can be classiﬁed into two major groups: (1) substituent constants and (2) whole molecular descriptors [11, 12].
44 2 Statistical methods in QSAR/QSPR Fig. 3 Example of a dendrogram The k-means clustering is a non-hierarchical method of clustering which can be used when the number of clusters present in the objects or cases is known. It is an unsupervised method of centroid-based clustering. In general, the k-means method will produce the exact k different clusters. The method deﬁnes k centroids, one for each cluster, placed as much as possible far away from each other. The next step is to take each point belonging to a given data set and associate it to the nearest centroid.
Todeschini R, Consonni V (2000) Handbook of molecular descriptors. Wiley-VCH, Weinheim 12. Livingstone DJ (2000) The characterization of chemical structures using molecular properties. A survey. J Chem Inf Comput Sci 40:195–209 13. Roy K, Das RN (2014) A review on principles, theory and practices of 2D-QSAR. Current Drug Metabol 15:346–379 14. Taylor PJ (1991) Quantitative drug design. the rational design, mechanistic study and therapeutic applications of chemical compounds. In: Hansch C, Sammes PG, Taylor JB (eds) Comprehensive medicinal chemistry, vol 4.
A Primer on QSAR/QSPR Modeling: Fundamental Concepts by Kunal Roy