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The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.

A perspective on multi‐target drug discovery and design for complex diseases

Open access
Ramsay, Rona R., Popovic‐Nikolic, Marija R., Nikolic, Katarina, Uliassi, Elisa, Bolognesi, Maria Laura·2018·Clinical and Translational Medicine

Abstract

Diseases of infection, of neurodegeneration (such as Alzheimer's and Parkinson's diseases), and of malignancy (cancers) have complex and varied causative factors. Modern drug discovery has the power to identify potential modulators for multiple targets from millions of compounds. Computational approaches allow the determination of the association of each compound with its target before chemical synthesis and biological testing is done. These approaches depend on the prior identification of clinically and biologically validated targets. This Perspective will focus on the molecular and computational approaches that underpin drug design by medicinal chemists to promote understanding and collaboration with clinical scientists.

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Crossref · 10.1186/s40169-017-0181-2

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Metadata

Authors
Ramsay, R. R., Popovic‐Nikolic, M. R., Nikolic, K., Uliassi, E., & Bolognesi, M. L.
Venue
Clinical and Translational Medicine
Publisher
Wiley
Published
2018-01-17
Volume
7
Issue
1
Pages
3-3
ISSN
2001-1326 (ISSN-L)
OpenAlex
W2783897572
Cited by
718
References
101
FWCI
55.04
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: A perspective on multi‐target drug discovery and design for complex diseases. https://app.cochat.ai/papers/10.1186/s40169-017-0181-2
The paper
Ramsay, R. R., Popovic‐Nikolic, M. R., Nikolic, K., Uliassi, E., & Bolognesi, M. L. (2018). A perspective on multi‐target drug discovery and design for complex diseases. Clinical and Translational Medicine. https://doi.org/10.1186/s40169-017-0181-2

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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.