Molecular similarity in medicinal chemistry.

By G. Maggiora, Martin Vogt, Dagmar Stumpfe, Jürgen Bajorath. 2014

576 citations recorded by the source corpus.

Similarity is a subjective and multifaceted concept, regardless of whether compounds or any other objects are considered. Despite its intrinsically subjective nature, attempts to quantify the similarity of compounds have a long history in chemical informatics and drug discovery. Many computational methods employ similarity measures to identify new compounds for pharmaceutical research. However, chemoinformaticians and medicinal chemists typically perceive similarity in different ways. Similarity methods and numerical readouts of similarity calculations are probably among the most misunderstood computational approaches in medicinal chemistry. Herein, we evaluate different similarity concepts, highlight key aspects of molecular similarity analysis, and address some potential misunderstandings. In addition, a number of practical aspects concerning similarity calculations are discussed.

Subfields: Computational Theory and Mathematics, Pharmacology, Spectroscopy

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Pharmacology

Noel M. O'Boyle

In Spectroscopy

Citations in the corpus

Ligand biological activity predicted by cleaning positive and negative chemical correlations (2019, background): “41 to any molecule in the training set—this level of (dis-)similarity is the same as two molecules randomly drawn from ZINC, a large database often used in virtual screening (39).”
Molecular fingerprint similarity search in virtual screening. (2015, background): “Similarity in itself is subjective and can be measured and their results interpreted in several ways [6–8].”
Comparing structural fingerprints using a literature-based similarity benchmark (2016, background): “While there has been some recent work on comparing human and computational measures of structural similarity [21], it is still the case that the “cognitive algorithms by which medicinal chemists perceive similarity are largely unknown” (to quote Maggiora et al. [22]).”
Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations? (2015, background): “Quantifying the similarity of two molecules is a key concept and a routine task in cheminformatics [1-3].”
Predicting protein–ligand affinity with a random matrix framework (2016, background): “A corollary is that ligands with similar chemical functionality are expected to share similar binding affinity toward a particular receptor (3, 4).”