Do structurally similar molecules have similar biological activity?
By Y. Martin, J. Kofron, L. Traphagen. Journal of Medicinal Chemistry, 2002
794 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Organic Chemistry, Pharmacology
View Paper: https://www.semanticscholar.org/paper/83ae373df002b5255e4e94f524e8ae2f5989cff7
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In Computational Theory and Mathematics
- Sunghwan Kim
- Evan E. Bolton
- Stephen H. Bryant
- Lianyi Han
- Peer Bork
- Lars Juhl Jensen
- Michael Kuhn
- C. von Mering
In Organic Chemistry
In Pharmacology
- Sunghwan Kim
- Evan E. Bolton
- Michael Kuhn
- Peer Bork
- Stephen H. Bryant
- Lars Juhl Jensen
- Ruth Nussinov
- Peter Csermely
Citations in the corpus
- Developing and validating predictive decision tree models from mining chemical structural fingerprints and high–throughput screening data in PubChem (2008, methodology): “By using Tanimoto coefficient[11,12] as a measurement for the compound similarities, there are only six active compounds that were found to be similar with Tanimoto coefficient threshold of 95%.”
- Large-scale integration of small molecule-induced genome-wide transcriptional responses, Kinome-wide binding affinities and cell-growth inhibition profiles reveal global trends characterizing systems-level drug action (2014, background): “Chemical structure similarity is an important concept in chem-informatics where it is generally assumed that more structurally similar compounds are more likely to have similar biological activity (similarity property principle) (Martin et al., 2002).”
- QSAR Applicability Domain Estimation by Projection of the Training Set in Descriptor Space: A Review (2005, background): “In the domain: training set (8) ( ) and test set (4) ( ); out of the domain: training set ( ) and test set ( ).”
- Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, methodology): “However, the relationship between chemical similarity and biological activity is not always straightforward (Martin et al., 2002), which necessitates the use of sophisticated approaches in drug design, such as the multi-component similarity networks listed in Table 5.”
- In silico methods and tools for drug discovery (2021, background): “…features (e.g., aromaticity, hydrogen bond acceptors, hydrogen bond donors, hydrophobicity, anion, and cation residues) between chemical compounds, under the assumption that compounds sharing high structural and physicochemical similarities are more likely to have similar biological activity [93].”
- ZINC20 – A Free Ultra Large-Scale Chemical Database for Ligand Discovery (2020, methodology): “In addition to its original focus on molecular docking 3 , an important application of ZINC is Analog-by-catalog (ABC), a pragmatic approach based on the molecular similarity principle 6, 7 to identify similar compounds with which to explore structure-activity relationships (SAR).”
- Impact of high-throughput screening in biomedical research (2011, methodology): “There are many methods that can be used to define the chemotype and diversity of compounds, with some validated by years of screening dat”