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Ultrafast shape recognition to search compound databases for similar molecular shapes
Abstract
Finding a set of molecules, which closely resemble a given lead molecule, from a database containing potentially billions of chemical structures is an important but daunting problem. Similar molecular shapes are particularly important, given that in biology small organic molecules frequently act by binding into a defined and complex site on a macromolecule. Here, we present a new method for molecular shape comparison, named ultrafast shape recognition (USR), capable of screening billions of compounds for similar shapes using a single computer and without the need of aligning the molecules before testing for similarity. Despite its extremely fast comparison rate, USR will be shown to be highly accurate at describing, and hence comparing, molecular shapes. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007
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DrugBank: a comprehensive resource for in silico drug discovery and exploration
Wishart, D. S. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj067 · Cited by 3,892
Cited by
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Kearnes, S., McCloskey, K., Berndl, M., Pande, V., & Riley, P. (2016) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-016-9938-8 · Cited by 1,631
Sastry, M., Lowrie, J. F., Dixon, S. L., & Sherman, W. (2010) · Journal of Chemical Information and Modeling · doi:10.1021/ci100062n · Cited by 332
DeepUMQA: Ultrafast Shape Recognition-based Protein Model Quality Assessment using Deep Learning
Guo, S.-S., Liu, J., Zhou, X.-G., & Zhang, G.-J. (2021) · doi:10.1101/2021.10.02.462491 · Cited by 53
DeepUMQA: ultrafast shape recognition-based protein model quality assessment using deep learning
Guo, S.-S., Liu, J., Zhou, X.-G., & Zhang, G.-J. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac056 · Cited by 53
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Metadata
- Authors
- Ballester, P. J., & Richards, W. G.
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 2007-03-06
- Volume
- 28
- Issue
- 10
- Pages
- 1711-1723
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- OpenAlex
- W2057350662
- Cited by
- 327
- References
- 1
- FWCI
- 19.79
- Type
- journal article
- Language
- en
- Open access
- closed
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