The DOI matches its Crossref record.
Topological Approach to Drug Design
Abstract
In this paper we demonstrated that by an adequate combination of different topological indices it is possible to select and design new active compounds in different therapeutical scopes, with a very high efficiency level. Particularly successful in the search of new "lead drugs", the results show the surprising ability of the topological methods to describe molecular structures.
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Citations
Cited by
Walters, W. P., Stahl, M. T., & Murcko, M. A. (1998) · Drug Discovery Today · doi:10.1016/s1359-6446(97)01163-x · Cited by 991
Sharma, V., Goswami, R., & Madan, A. K. (1997) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci960049h · Cited by 441
Zahrt, A. F., Athavale, S. V., & Denmark, S. E. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00425 · Cited by 212
Metadata
- Authors
- Galvez, J., Garcia-Domenech, R., de Julian-Ortiz, J. V., & Soler, R.
- Venue
- Journal of Chemical Information and Computer Sciences
- Publisher
- American Chemical Society (ACS)
- Published
- 1995-03-01
- Volume
- 35
- Issue
- 2
- Pages
- 272-284
- ISSN
- 0095-2338 (ISSN-L)
- 1520-5142
- OpenAlex
- W1977402279
- Cited by
- 177
- References
- 0
- FWCI
- 10.20
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
