Violeta I. Perez-Nueno
INRIA Nancy – Grand Est, LORIA

Abstract:

Polypharmacology is becoming an increasingly important aspect in drug design. In the last 4 years, more than 30 drugs have been tested against more than 40 novel secondary targets based on promiscuity predictions.

Current computational techniques for predicting drug pharmacological profiles relate targets to each other based on the similarity in the ligand chemical descriptor space [1], protein target sequence space [2], and more recently, in the pharmacophoric pocket descriptor space [3]. Here we present a shape-based approach which uses spherical harmonic (SH) representations [4,5] to compare molecular surfaces very efficiently. This approach compares targets by the SH similarity of their ligands and also of their binding pockets. This allows promiscuous ligands and targets to be predicted very rapidly.

We present details of our approach applied to the MDL Drug Data Report (MDDR) database containing 202,143 compounds distributed over 633 diverse pharmacological targets. To our knowledge, this is the largest allagainst-all polypharmacological study to have been carried out using shapebased techniques. Correlation between binding pocket and ligand shapes is quantified as an expectation value (E-value). Our promiscuity predictions are compared with experimental activity values extracted from BindingDB.

References
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2. Weskamp, N.; Hüllermeier, E; Klebe, G. Merging chemical and biological space: Structural mapping of enzyme binding pocket space. Proteins 2009, 76: 317–330.
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