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Pharmacophore Alignment Search Tool (PhAST): Significance Assessment of Chemical Similarity
Volker Hähnke1, Matthias Rupp2, Alexander K Hartmann3
1Eidgenössische Technische Hochschule (ETH), Department of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, Wolfgang-Pauli-Str. 10, 8093 Zürich, Switzerland phone: +1 (202)436-5989. volker@cheminformatics.de.
Abstract:
Previously, we proposed a ligand-based virtual screening technique (PhAST) based on global alignment of linearized interaction patterns. Here, we applied techniques developed for similarity assessment in local sequence alignments to our method resulting in p-values for chemical similarity. We compared two sampling strategies, a simple sampling strategy and a Markov Chain Monte Carlo (MCMC) method, and investigated the similarity of sampled distributions to Gaussian, Gumbel, modified Gumbel, and Gamma distributions. The Gumbel distribution with a Gaussian correction term was identified as the most similar to the observed empirical distributions. These techniques were applied in retrospective screenings on a drug-like dataset. Obtained p-values were adjusted to the size of the screening library with four different methods. Evaluation of E-value thresholds corroborated the Bonferroni correction as a preferred means to identify significant chemical similarity with PhAST. An online version of PhAST with significance estimation is available at http://modlab-cadd.ethz.ch/.
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