Shape-based approaches have many potential areas for development in the future for application to in silico pharmacology. Further exploration of the role of molecular shape may lead to better understanding of the substrate specificity of enzymes and the possibility to reduce toxic effects that may be caused by ligands binding to undesired target proteins. Methods exploiting molecular shape for activity and toxicity prediction might have a great influence on the drug discovery process. There are different approaches that might be used for this purpose, e.g. shape fingerprints and shape multipoles. Both methods describe the shape of molecules, discarding any chemical information, using numerical values. Focusing only on shape can lead to identifying novel core structures of molecules, with improved properties. Molecular fingerprints are binary bit strings that encode the structure or shape of compounds; shape is measured indirectly by alignment to a database of standard molecular shapes – the reference shapes. The Shape Database should represent a wide range of possible molecular shapes to produce accurate results. Therefore, this was the main focus of the investigation. The shape multipoles method is a fast computational method to describe the shape of molecules by using only numbers and therefore it requires low storage needs and comparison is performed by simple mathematical operations. To describe the shape, it uses only 13 values (3 quadrupole components and 10 octupole components). The performances of both methods in grouping compounds based on shared biological activity were evaluated using several test sets with slightly better results in case of shape fingerprints. However, the shape multipole approach showed potential in finding differences in shape between enantiomers. Among the possible applications of the shape fingerprints method are solubility prediction (on comparable level as well-established methods) and virtual screening.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:745917 |
| Date | January 2018 |
| Creators | Zarnecka, J. M. |
| Contributors | Leach, A. ; Enoch, S. J. ; Cronin, M. T. D. |
| Publisher | Liverpool John Moores University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://researchonline.ljmu.ac.uk/8888/ |
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