Effects of multiple conformers per compound upon 3-D similarity search and bioassay data analysis

By Sunghwan Kim, Evan E. Bolton, Stephen H. Bryant. 2012

21 citations recorded by the source corpus.

BackgroundTo improve the utility of PubChem, a public repository containing biological activities of small molecules, the PubChem3D project adds computationally-derived three-dimensional (3-D) descriptions to the small-molecule records contained in the PubChem Compound database and provides various search and analysis tools that exploit 3-D molecular similarity. Therefore, the efficient use of PubChem3D resources requires an understanding of the statistical and biological meaning of computed 3-D molecular similarity scores between molecules.ResultsThe present study investigated effects of employing multiple conformers per compound upon the 3-D similarity scores between ten thousand randomly selected biologically-tested compounds (10-K set) and between non-inactive compounds in a given biological assay (156-K set). When the “best-conformer-pair” approach, in which a 3-D similarity score between two compounds is represented by the greatest similarity score among all possible conformer pairs arising from a compound pair, was employed with ten diverse conformers per compound, the average 3-D similarity scores for the 10-K set increased by 0.11, 0.09, 0.15, 0.16, 0.07, and 0.18 for STST-opt, CTST-opt, ComboTST-opt, STCT-opt, CTCT-opt, and ComboTCT-opt, respectively, relative to the corresponding averages computed using a single conformer per compound. Interestingly, the best-conformer-pair approach also increased the average 3-D similarity scores for the non-inactive–non-inactive (NN) pairs for a given assay, by comparable amounts to those for the random compound pairs, although some assays showed a pronounced increase in the per-assay NN-pair 3-D similarity scores, compared to the average increase for the random compound pairs.ConclusionThese results suggest that the use of ten diverse conformers per compound in PubChem bioassay data analysis using 3-D molecular similarity is not expected to increase the separation of non-inactive from random and inactive spaces “on average”, although some assays show a noticeable separation between the non-inactive and random spaces when multiple conformers are used for each compound. The present study is a critical next step to understand effects of conformational diversity of the molecules upon the 3-D molecular similarity and its application to biological activity data analysis in PubChem. The results of this study may be helpful to build search and analysis tools that exploit 3-D molecular similarity between compounds archived in PubChem and other molecular libraries in a more efficient way.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Spectroscopy

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Citations in the corpus

PubChem structure–activity relationship (SAR) clusters (2015, methodology): “The PubChem conformer generation and sampling procedures, described in more detail in our previous papers [17, 21, 23, 24], ensure that 90% of the conformer models have at least one “bioactive” conformer whose (non-hydrogen atom pair-wise) RMSD from the experimentally determined conformation was clo”
PubChem3D: conformer ensemble accuracy (2013, methodology): “One may ask “how good or how bad are these worstcase minimum accuracies?” To answer this question, it is necessary to determine an appropriate cut-off value for a “close” reproduction of the experimental structure, and our recent study [11], which studied the statistical significance of the ROCS-bas”